ESMAP TECHNICAL PAPER 003 Assessing Markets for Renewable Energy in Rural Areas of Northwestern China 21359 ~~~~~~~~~~~ Energy Sector Management %A y FILE COPY Assistance FILIE- 1 Programme k:ugust 2000O Papers in the ESMAP e¢chnical Sriesi are discuwon documents, not final project reports. They are sjblect teo he same copyrights as other ESM4AP publications. JOINT UNDP / WORLD BANK ENERGY SECTOR MANAGEMENT ASSISTANCE PROGRAMME (ESMAP) PURPOSE The Joint UNDP/World Bank Energy Sector Management Assistance Programme (ESMAP) is a special global technical assistance program run as part of the World Bank's Energy, Mining and Telecommunications Department. ESMAP provides advice to governments on sustainable energy development. Established with the support of UNDP and bilateral official donors in 1983, it focuses on the role of energy in the development process with the objective of contributing to poverty alleviation, improving living conditions and preserving the environment in developing countries and transition economies. ESMAP centers its interventions on three priority areas: sector reform and restructuring; access to modern energy for the poorest; and promotion of sustainable energy practices. GOVERNANCE AND OPERATIONS ESMAP is governed by a Consultative Group (ESMAP CG) composed of representatives of the UNDP and World Bank, other donors, and development experts from regions benefiting from ESMAP's assistance. The ESMAP CG is chaired by a World Bank Vice President, and advised by a Technical Advisory Group (TAG) of four independent energy experts that reviews the Programme's strategic agenda, its work plan, and its achievements. ESMAP relies on a cadre of engineers, energy planners, and economists from the World Bank to conduct its activities under the guidance of the Manager of ESMAP, responsible for administering the Programme. FUNDING ESMAP is a cooperative effort supported over the years by the World Bank, the UNDP and other United Nations agencies, the European Union, the Organization of American States (OAS), the Latin American Energy Organization (OLADE), and public and private donors from countries including Australia, Belgium, Canada, Denmark, Germany, Finland, France, Iceland, Ireland, Italy, Japan, the Netherlands, New Zealand, Norway, Portugal, Sweden, Switzerland, the United Kingdom, and the United States of America. FURTHER INFORMATION An up-to-date listing of completed ESMAP projects is appended to this report. For further information, a copy of the ESMAP Annual Report, or copies of project reports, contact: ESMAP c/o Energy, Mining and Telecommunications Department The World Bank 1818 H Street, NW Washington, DC 20433 U.S.A. ASSESSING MARKETS FOR RENEWABLE ENERGY IN RURAL AREAS OF NORTHWESTERN CHINA Prepared by. Tuntivate Voravate Douglas F. Barnes V. Susan Bogach Joint UNDP/World Bank Energy Sector Management Assistance Programmne (ESMAP) Copyright @ 1999 The International Bank for Reconstruction and Development/THE WORLD BANK 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. All rights reserved Manufactured in the United States of America First printing August 2000 ESMAP Reports are published to communicate the results of the ESMAP's work to the development comnunity with the least possible delay. The typescript of the paper therefore has not been prepared in accordance with the procedures appropriate to formal documents. Some sources cited in this paper may be informal documents that are not readily available. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) and should not be attributed in any manner to the World Bank, or its affiliated organizations, or to members of its Board of Executive Directors or the countries they represenL Tle World Bank does not guarantee the accuracy of the data included in this publication and accepts no responsibility whatsoever for any consequence of their use. The Boundaries, colors, denominations, other information shown on any map in this volume do not imply on the part of the World Bank Group any judgement on the legal status of any territory or the endorsement or acceptance of such boundaries. The material in this publication is copyrighted. Requests for permission to reproduce portions of it should be sent to the ESMAP Manager at the address shown in the copyright notice above. ESMAP encourages dissemination of its work and will normally give permission promptly and, when the reproduction is for noncommercial purposes, without asking a fee. CONTENTS Contents ........................................................... ii Abstract ........................................................... vii Acknowledgments ........................................................... ix Abbreviations and Acronyms ........................................................... xi Currency Equivalents ........................................................... xi Units of Measure ........................................................... xi Executive Summary ...........................................................1I Background ...........................................................I The Survey Region ............................................................2 Results and Recommendations ............................................................2 Target Population Characteristics ............................................................2 Familiarity with Credit ............................................................3 Awareness of Benefits of Electricity ............................................................3 Existing Use of Renewable Energy Technologies ...................................................3 Characteristics of Existing Owners of photovoltaic systems ...................................4 Experience with Photovoltaic Systems ............................................................ 4 Potential Markets for Photovoltaic Systems ............................................................5 Conclusions ............................................................5 1 Background ............................................................7 Electricity in China ............................................................7 Purpose of the Study ............................................................8 2 Background on Areas Tageted by the Survey ........................................................... ll Background on Provinces in Study ........................................................... 11 Current Photovoltaic System Business ........................................................... 12 Description of Typical Photovoltaic Systems Used in Rural Areas in China ........ 13 Bfief Description of the Study Design ........................................................... 14 Conclusion ........................................................... 15 3 Survey of Results: Socioeconomic Characteristics of Households Without Electricity ........................................... 17 Income, Occupation, and Education ........................................... 17 Value of Rural Household Assets ........................................... 19 Experience with Banking and Credit ........................................... 21 Current Energy Use and Expenditure for Household Lighting .............................. 24 Attitudes and Preference toward Energy Services ........................................... 29 Knowledge of and Access to Photovoltaic Systems ........................................... 33 Conclusion ........................................... 33 4 Profile of Households With Pbotovoltaic Systems . ............. .35 Profile of Photovoltaic System Owners ...................................... 35 ii The Type of Photovoltaic System Purchased by Households ................................ 39 System Performance and Quality of Service ......................................................... 41 Conclusion ......................................................... 43 5 Potential Market for Photovoltaic Systems in Four Provinces ................................ 45 Ability to Pay Cash for Photovoltaic Systems ....................................................... 45 Potential Demand for Larger Systems ......................................................... 47 Attitudes and Preferences for Types of System and Payment Methods ................. 48 Conclusion ......................................................... 49 6 Conclusions and Recommendations ......................................................... 51 The Market for Photovoltaic Systems Exists and Is Growing ............................... 51 Households Appear to Have Little Interest in Using Credit to Purchase Photovoltaic Systems ......................................................... 53 Sales and After-Sales Networks Need to Be Expanded ......................................... 53 Standards and Specifications May Be Important for Market Development .......... 53 Conclusion ......................................................... 54 Bibliography ......................................................... 125 APPENDICES Appendix A: Descriptive Statistics from the Northwest China Rural Energy Survey ......................................................... 55 Appendix B: Data and Sampling Methods ......................................................... 73 Target Population ......................................................... 73 Sample Size and Design ..............75 Sample Size and Design ~~~.............................................................. Purposive Selection of Photovoltaic Households .................................................. 77 Questionnaire and Conduct of the Survey ......................................................... 78 Data Processing ......................................................... 79 Data Weighting Procedures ......................................................... 79 Appendix C: Questionnaire .............................................................. ..83 TABLES Table 2.1: Socioeconomic Characteristics Of Four Provinces In Survey, 1997 ................ 12 Table 2.2: Households without Electricity in Counties and Provinces .............................. 15 Table 3.1: Household Monthly Income by Type of Occupation of Household Head ........ 18 Table 3.2: Average Value of Livestock Classified by Occupation of Head of Household and Type of Asset .............................................................. 20 Table 3.3: Household Borrowing Patterns in Villages without Electricity in Four Provinces .............................................................. 22 iii Table 3.4: Household Use of Loans in Villages without Electricity in Four Provinces (percent) ............................................................. 23 Table 3.5: Comparison of Income and Value of Livestock between Households that Have not and Have Taken a Loan Before ..................................................... 23 Table 3.6: Household Energy Use for Lighting by Income Class ....................................... 25 Table 3.7: Household Monthly Spending for Lighting Energy .......................................... 28 Table 3.8: Monthly Spending on Lighting for Households Using Renewable Energy Systems ............................................ 29 Table 3.9: Household Energy Attitudes and Lighting Preferences .................................... 30 Table 3.10: Satisfaction with Lighting Source According to Electricity Source ............... 32 Table 3.11: Household Knowledge of Renewable Energy Systems .................................. 33 Table 4.1: Owners of Photovoltaic Systems Whose Household Monthly Income Falls within Each Income Category for All Households (percent) .................. 37 Table 4.2: The Nature of Photovoltaic System Purchases in Four Provinces .................... 40 Table 4.3: Experiences with Repairs and Services ............................................................ 42 Table 5. 1: Households That Could Afford Small Photovoltaic Systems ........................... 46 Table 5.2: Households That Could Afford to Purchase Large Photovoltaic Systems ....... 47 Table 5.3: Households Interested in Buying a Different Size Photovoltaic System Using Cash or Credit (percent) ............................................................. 48 Table A-I: Socioeconomic Indicators ............................................................. 55 Table A-2: Households' Experience with Credit ............................................................. 56 Table A-3: Household Energy Use for Lighting ............................................................. 57 Table A-4: Households' Energy Expenditure ............................................................. 57 Table A-5: Household Energy Attitude and Lighting Preferences .................................... 58 Table A-6: Households that Have Heard about or Have Seen 20-Watt Photovoltaic Systems (percent) ............................................................. 62 Table A-7: Households That Are Interested in Buying 20-Watt Photovoltaic Systems (percent) ............................................................. 62 Table A-8: Reason for Not Being Interested in Purchasing 20-Watt Photovoltaic Systems .............................................................. 63 Table A-9: Households That Have Heard about or Have Seen 50-Watt Photovoltaic Systems (percent) ............................................................. 64 Table A-10: Households That Are Interested in Buying 50-Watt Photovoltaic Systems (percent) ............................................................. 64 Table A- 1: Reason for Not Being Interested in Purchasing 50-Watt Photovoltaic Systems ............................................................. 65 Table A-12: Households That Have Heard about or Have Seen Small Hybrid Photovoltaic-Wind Systems (percent) ............................................................. 66 Table A- 13: Reason for Not Being Interested in Purchasing Hybrid Photovoltaic-Wind Systems ............................................................. 67 Table A-14: Photovoltaic Systems Owned by Households ............................................... 68 Table A-15: Attitude toward Photovoltaic Systems amnong System Owners ..................... 68 Table A-1 6: Reasons for Photovoltaic System Owners to Obtain Systems ....................... 69 Table A-17: Perceived Benefits of Photovoltaic Systems among System Owners ........... 70 Table A-18: Attitude of Photovoltaic System Owners toward System Perfornance ........ 71 iv Table A-19: Changes in Lifestyles of Photovoltaic System Owners ................................. 71 Table B-1: Rural Households and Unelectrified Households ............................................ 74 Table B-2: Targeted Households in Villages without Grid Electricity in Four Selected Provinces ............................................................. 74 Table B-3: Households in Villages without Grid Electricity in Sampled Counties and All Other Counties .................................................... 75 Table B-4: Sample Selection for Photovoltaic Market Survey in Four Selected Provinces in China ............................................................. 77 Table B-5: Sample Size Broken Down by Random and Purposive Selection of Households ............................................................. 78 Table B-6: Weight Adjustment for County ............................................................. 79 Table B-7: Weight Adjustment for Province ............................................................. 80 Table B-8: Final Weight Adjustment Procedure ............................................................. 80 Estimation of Standard Errors and Confidence Interval .................................................... 80 Table B-9: Estimated Variance and Standard Errors of Household Monthly Income in Gansu ............................................................. 80 Table B-l0: Summary of Standard Error and Confidence Interval .................................... 81 FIG URES Figure 3.1: Total Monthly Spending on Lighting Fuel in Energy and Electricity ............. 26 Figure 3.2: Total Monthly Spending on Lighting Energy and Electricity .......................... 27 Figure 4.1: Distribution of Owners of Photovoltaic Systems Based on Income Deciles ... 36 Figure 4.2: Distribution of Photovoltaic Owners Based on Income and Assets Owned ... 38 Figure 4.3: Average Size of Photovoltaic System Owned by Income ............................... 41 v ABSTRACT The main objective of this study was to determine the market potential for photovoltaic systems in the remote areas of China, especially in villages without access to grid electricity. A number of photovoltaic systems have been sold in the remote provinces, but the size and nature of this market was not well understood. The study produced data that addresses several needs. It yielded an estimate of the size of the potential market for photovoltaic systems in four Chinese provinces; provided important information on the characteristics, ability to pay, and preferences of potential customers; detailed positive and negative experiences with existing photovoltaic systems; and developed recommendations to increase the penetration of photovoltaic systems in rural China as part of the upcoming China Renewable Energy Development Project. The main conclusion of the report is that there is significant desire by households in remote areas for electricity, and that there is significant potential market demand for photovoltaic systems. vii ACKNOWLEDGMENTS We gratefully acknowledge the support of the Japanese Grants for Preparation of the Renewable Energy Development Project and assistance from the Netherlands Altemative Energy Policy and Project Development Trust Fund in Support of the Asia Altemative Energy Program, which provided funding to carry out the survey in China and supported analysis of the data by local and intemational experts. Thc efforts of the staff of the Center for Renewable Energy Development (CRED) deserve special mention for organizing and supervising the field survey work under very difficult conditions, for entering and verifying the data, and for drafting a report on the findings of the survey. CRED's team was led by Ms. Li Jingjing in the early stages of the survey work and by Mr. Li Junfeng throughout most of the work. Many other CRED staff members made substantial contributions to this project. The authors would like to acknowledge the guidance provided throughout the course of the project by Mr. Noureddine Berrah, the Task Team Leader, who supervised, reviewed, and provided extensive support for the completion of the work. Mr. Liu Hongpeng, of the State Economic and Trade Commission, also provided extensive guidance, support, and comments during the survey. The report owes much to their guidance and support. We would like to thank Jeremy Levin, who wrote the executive summary and abstract and assisted in the report's preparation, as well as Rebecca Kary of Alpha-Omega Services, Inc., who edited the report. We would also like to thank several reviewers of the report, who made useful contributions. The reviewers included Messrs. Richard Spencer, Anil Cabraal, and Enno Heijndernans (World Bank); and Mr. Jim Finucane and Ms. Miao Hong (consultants). lx ABBREVIATIONS AND ACRONYMS CRED Center for Renewable Energy Development ESMAP Energy Sector Management Assistance Programme GEF Global Enviromnent Facility PV Photovoltaic TVE Township and village enterprise CURRENCY EQUIVALENTS (1998) U.S. dollars ($) = currency equivalent $1.00 = 8.3 yuan UNITS OF MEASURE GW Gigawatt kW Kilowatt kWh Kilowatt-hour Mu Chinese unit of land measurement MW Megawatt W Watt xi EXECUTIVE SUMMARY There is a growing consensus that renewable energy will play a significant role in future development programs. This consensus has grown out of such reports as the United Nations Development Programme's "Energy after Rio," Shell Petroleum's "Energy for Development," and the World Bank's recent papers on "Fuel for Thought" and "Rural Energy and Development." In spite of this acceptance, surprisingly few studies have been made on the emerging markets for renewable energy in most countries. The main purpose of this study was to determine the market potential for photovoltaic systems in the remote areas of China, especially in villages without access to grid electricity. A number of photovoltaic systems have been sold in the remote provinces, but the size and nature of this market is not well understood. The study produced information that addresses several needs. It estimated the size of the potential market for photovoltaic systems in four Chinese provinces. It provided important information on the characteristics, ability to pay, and preferences of potential customers. It detailed positive and negative experiences with existing photovoltaic systems, and it developed recommendations to increase the penetration of photovoltaic systems in rural China as part of the upcoming China Renewable Energy Development Project. The main conclusion of the report is that households in remote areas have a significant desire for electricity, and that a significant potential market exists for photovoltaic systems in many regions. BACKGROUND During the last 40 years, the Chinese program to provide electricity to rural populations achieved remarkable success. Today the percentage of households with access to electricity from large and small grid systems is approximately 93 percent, representing more than 96 percent of the villages in China. Despite this success, a great many people still have no access to electricity in the remote areas of China Approximately 75 million people do not have access to electricity from a local or regional grid system. In these remote provinces, the people are relatively poor, and the population density is low. Compared with other areas of China, little business or commercial activity exists. The low demand and sparse populations make it very expensive to reach these areas through grid extension. Hence, they are unlikely to be connected to the national grid for many years. Retailers have been very active in selling renewable energy systems in the northwestem provinces of China, both wind and photovoltaic. Based on reports from photovoltaic companies, an estimated 45,000 photovoltaic systems were sold in 1997 alone, primarily on a cash basis. Little is known, however, about the potential size of the market for photovoltaic systems in these remote areas. None of the photovoltaic system retailers and distributors servicing these areas has conducted any type of formal survey to deterine the size of the market for renewable energy systems. I The World Bank has recently approved a loan and Global Environment Facility (GEF) grant to China for the Renewable Energy Development Project (LN 4488-CHA, 1999), which includes a large photovoltaic component. This component will provide assistance to photovoltaic system companies to market, sell, and maintain an estimated 300,000-400,000 systems in the remote areas of China's northwestem provinces. The results of this study are intended to help guide the implementation of the photovoltaic component. THE SURVEY REGION The survey was conducted in four remote provinces in China-Gansu, Inner Mongolia, Qinghai, and Xinjiang. All these provinces will be served by the recently approved Bank project. The target population (also known as the "population frame") within these provinces for the photovoltaic market survey consisted of all rural households living in villages without access to grid electricity in counties where more than 15 percent of households did not have electricity.' The main reason that the market survey concentrated on such counties was that the villages without electricity in these counties have less chance of gaining access to electricity in the near future. The photovoltaic market survey in the rural areas in Gansu, Inner Mongolia, Qinghai, and Xinjiang Provinces was conducted using a multistage random sampling design. Responses to detailed questionnaires were gathered from 2,286 households between August 1998 and April 1999. RESULTS AND RECOMMENDATIONS The survey yielded important information on the characteristics of the target population, their familiarity with the use of credit, their energy preferences, their use of remote renewable energy technologies, the characteristics of existing owners of photovoltaic systems, and observed experiences with solar home systems. Recommendations for increasing the acceptance of photovoltaic systems were developed based upon these observed results, and they are highlighted below. TARGET POPULATION CHARACTERISTICS The provinces differ significantly in income, occupation, and education. The average monthly household incomes of the target population in the provinces range from a low of about Y 200 in Gansu to more than 1,300 in Inner Mongolia. Significant variations also exist in the occupations of the respondents: more than 90 percent of the households in unelectrified areas of Gansu are farmers, while more than 60 percent of the households in comparable areas of Inner Mongolia are herders. Quinghai has an even higher percentage of herders than Inner Mongolia, although they do not earn as much 'Tbe 15 percent cutoff point was arbitrrily chosen based on the avenge 17 percent unclectnfied rate in the conbmed 4 provinces. 2 income as the Inner Mongolian herders do. Xinjiang is predominantly a farming area. Its high average income level (Y 713) is probably attributable to its greater share of high- value cash crop production. The education levels in the provinces are very high for such remote areas. Only one out of the four provinces has very low levels of education: Qinghai-where the rural households in the areas without electricity have the lowest educational levels. These variations in income, occupation, and education will lead to differing markets for photovoltaic systems in each of the provinces. In addition to collecting data on yearly household income, the study estimated the assets of the rural households. Comparing the assets of farmers to those of herders revealed a pattern similar to that of yearly household income. In general, herders have higher incomes and greater total assets than farmers, making them more likely to be able to afford renewable energy systems. The conclusion is that a significant number of households in the target population can afford to purchase photovoltaic systems, even on a cash basis. FAMILIARITY WITH CREDIT Many people in these provinces are familiar with credit. Between 30 and 40 percent of the households in three of the provinces already have experience with obtaining credit from rural banks, credit unions, or other sources. Although households are very likely to borrow money for productive uses (such as agricultural inputs), there is no indication that they would borrow money for photovoltaic systems that improve the quality of life. The household predisposition to borrow for photovoltaic systems should be investigatedfurther to ensure that all potential approaches to increasing the affordability of photovoltaic systems are fully pursued. AWARENESS OF BENEFITS OF ELECTRICITY The findings of the study verify that most households are aware of the benefits of electricity, and would like to have access to the better lighting, entertainment, and information made possible by electricity. Higher-income households are more dependent on electric lighting than others, and are willing to pay a very high price for electricity. The results of the study clearly demonstrate that the benefits of electricity are widely recognized by rural households. This represents a key factor in the demand for photovoltaic systens in areas with no immediate prospects for grid access and high costs of alternative sources of electricity. EXISTING USE OF RENEWABLE ENERGY TECHNOLOGIES Interestingly, a significant number of households in remote areas without electricity are already using renewable energy sources, such as wind and, to a limited degree, photovoltaic systems. Even the households with photovoltaic and wind energy 3 systems, however, are not totally satisfied with the service they are receiving. The survey noted that customers were dissatisfied with the seasonal variation from wind system power output. Furthermore, there is some evidence of discontent with the quality and quantity of lighting received from renewable energy, which includes solar and wind. Close to 40 percent of surveyed owners of photovoltaic systems reported that the photovoltaic systems they owned were too small and do not provide enough electricity for their families' needs. Despite the presence of a developing photovoltaic market, not all households in the sample areas of this study were aware of photovoltaic systems. About one-third of the households in the provinces had never heard about photovoltaic systems. An emerging market for photovoltaic systems is developing in the northwestern provinces of China, even on a cash-only basis. At present, this market is at an early stage of development, as commercial retailers have only begun to service these provinces during the last three years. There is a need to increase both the awareness and availability of photovoltaic systems. Finally, given the intermittent nature of electricity from wind systems, the possibility of developing small and inexpensive hybrid systems should be explored. CHARACTERISTICS OF EXISTING OWNERS OF PHOTOVOLTAIC SYSTEMS Existing photovoltaic system owners tend to have higher incomes, greater assets, and more education than those who do not own systems. Income and the total value of assets owned, particularly livestock, are complementary indicators of whether households can afford to purchase a photovoltaic system. The measured ability to pay is a fairly good indicator of potential photovollaic purchasers, as is education level. The relatively large numbers of better-educated households and higher income and asset levels indicate that there is a large potential market for photovoltaic systems. EXPERIENCE WITH PHOTOVOLTAIC SYSTEMS Most households that have purchased photovoltaic systems have chosen systems that were affordable, but which did not give the level of electricity service they desired, for example, enough lighting. Most systems in the region surveyed are less than two years of age and are relatively small in size, 20 watts or less. Although the majority of systems seem to be performing well, several problems have been observed with lamp and battery performance. Additionally, when systems do need repairs, few convenient facilities are available. The average wait time for repairs is about one month. In spite of the problems, almost all photovoltaic system owners across all four provinces are satisfied with the performance of their systems and would recommend them to relatives or friends. Therefore, a significant market may exist to upgrade the existing typical 20-watt systems. A modular approach may be wan-anted, in which a household has a choice of 4 different types of systems that offer an easy upgrade path to larger systems. Rather than concentrating on one-time sales, the market should be viewed as a continuing source of sales of equipment and upgrades. Most households in the remote areas have no access to the retailers that sell networks. Even in areas where photovoltaic systems have been sold, there is very little in the way of after-sales support. Assistance needs to be provided to accelerate the growth in sales of photovoltaic systems and after-sales support networks to increase access to photovoltaic systems and reduce waiting time for repairs. The adoption of mandatory standards, certification of photovoltaic products, and perhaps a modular approach to sales will help address the quality and performance problems identified in the study. POTENTIAL MARKETS FOR PHOTOVOLTAIC SYSTEMS The results of the survey allow for an estimation of the potential market size for sales of photovoltaic systems by using the observed income and asset levels of the respondents. This analysis is based on a comparison of characteristics of rural households living in villages without grid electricity services and a profile of current photovoltaic system owners. Forty-one percent of rural households in the four provinces have levels of income and assets similar to those who have already purchased small photovoltaic systems with cash, representing 562,573 households that can afford to purchase small photovoltaic systems in the four provinces. Furthermore, it is estimated that approximately 264,515 of these households can afford to buy larger photovoltaic systems (greater than 50 watts) with cash. Based on the observed dissatisfaction with the limited capacity of smaller systems, it is conceivable that the demand for larger photovoltaic systems will increase in the near future. CONCLUSIONS A market for photovoltaic systems is emerging in the northwestern provinces of China, even on a cash basis. At present this market is in an early stage of development, because commercial retailers have only begun to service these provinces during the last three years. Several obstacles must be overcome to expand this market: the lack of interest in credit for photovoltaic system purchases by households, which limits their ability to pay for photovoltaic systems, and the weak existing sales and after-sales networks in the region. Other obstacles include competition from alternative sources of electricity, such as diesel or gas generators and wind systems, and potential quality concerns with existing photovoltaic systems. Despite these obstacles, this study revealed that significant opportunities exist for introducing photovoltaic systemns in the rural areas of China. Many households can already afford to purchase small systems on a cash basis. This number could be significantly expanded if the use of credit to purchase systems was widely available and accepted. Furthermore, there appears to be a market for photovoltaic system expansion, 5 beyond the initial purchase of smaller, more affordable systems. This market includes both upgrades to existing small photovoltaic systems and possible hybridization with existing wind systems. Overall, the market for photovoltaic products is likely to expand quickly. Households in the areas seem to appreciate the benefits of electricity service from the systems, and many have the necessary income to pay for systems. 6 1 BACKGROUND The potential for renewable energy in developing countries has been a topic of great interest among international development specialists in recent years. Several recent reports have highlighted renewable energy as a long-term contribution to global energy supplies, such as the United Nations Development Programme's "Energy after Rio," Shell Petroleum's "Energy for Development," and the World Bank's recent papers on "Fuel for Thought" and "Rural Energy and Development." All these reports endorse the development of renewable energy, as well as the relevance for future energy strategies in developing countries. Despite the growing acceptance that renewable energy will play a greater role in future development programs, surprisingly few good studies have been made on the markets for renewable energy in most countries. Without an understanding of the unique niche or market for renewable energy systems, programs can be misguided and waste valuable resources in attempting to develop markets where little potential exists for systems sales. In fact, many programs involving household photovoltaic systems have experienced implementation problems. This survey on the potential market for household photovoltaic systems in the northwest part of China, carried out as part of a World Bank project, demonstrates the value of proper market assessments. The results of the study are being utilized to guide the strategies to promote the sales of household photovoltaic systems under the project. In addition, the study should provide a useful benchmark or good practice model for future studies on how to identify and assess market segments in the development of rural and renewable energy programs. To this end, appendixes to this report include a descriptive list of tables from the survey (Appendix A); a description of the methodology and the sample design (Appendix B); and the questionnaire (Appendix C) used in the market study. ELECTRiCITY IN CHINA China is one of the handful of developing countries in which a high percentage of people have access to electricity. During the last 40 years, programs to provide electricity to rural populations have achieved remarkable success. Today the percentage of 7 households in China with electricity from large and small grid systems is about 93 percent, including more than 96 percent of the country's villages. The rural electrification program has also been very different from those in other countries. In China, the responsibility of providing electricity service to rural areas was delegated to local power companies. At first, most of the companies were very small, and coverage was limited to the main cities and towns. The companies had the responsibility of both local generation and distribution of electricity. This was often accomplished through local networks connected to small coal-generating stations and mini- and micro-hydropower systems. Today the national grid also reaches many of these small regional power companies, complementing and sometimes replacing the original power plants. More recently, a small amount of China's electricity supply has been provided by renewable energy resources, such as wind, solar, and geothermal energy. The wide availability of electricity in both urban and rural areas in China is a major accomplishment. Despite this success in reaching hundreds of millions of people in the countryside, though, many people are still without electricity in the remote areas of China. About 75 million people do not have access to electricity from a local or regional gnrd system. In these remote provinces, the populations are relatively poor and can be very sparsely distributed. Many of the people make their living by farming and herding. The grid is unlikely to reach them for many years to come. Compared with other areas of China, there is little business or commercial activity. As a consequence, most of the demand for electricity comes from rural households. The low demand and sparse populations make it very expensive to reach these areas by extending the electricity grid. Despite the remoteness of these areas, retailers have recently dramatically stepped up sales of renewable energy systems-particularly wind (starting in the early 1980s) and photovoltaic home systems (during the last three years). Based on the sales information, about 45,000 photovoltaic systems alone are reported to have been sold in 1997. Almost all the systems were sold on a cash basis. Because the market is still in the early stage of development, little is known about the potential and size of the market for renewable energy systems in general and photovoltaic systems in particular in such remote areas. Although some photovoltaic system distributors are already servicing these areas, none of them has conducted a formal survey to determine the size of the market for renewable energy systems. PURPOSE OF THE STUDY The overall purpose of this study was to determine the size of the potential market for renewable energy systems in the remote areas of Northwest China by focusing mainly on household photovoltaic systems. Very few reliable government statistics exist for these remote areas. The number of systems being sold suggests that there is a market, but the size and nature of the market is not well understood. One could question whether the market is big enough to justify the increased sales that would result from a World Bank lending operation. To answer this question, several different types of information on the market for photovoltaic systems were required. 8 One important question that was answered by the market survey is what size systems should be developed for rural markets. The traditional view has been that households would not want systems below 50 watts, because they would not supply sufficient power. However, recent studies have indicated that because of the cost, many people are purchasing the smaller rather than the larger systems. Thus, it is important to characterize the market for different sizes of photovoltaic systems and to profile the groups of people who already own such systems. A second issue involved the willingness or ability of rural households to pay for photovoltaic systems. This study was fortunate to have access to many households in the remote provinces that already own photovoltaic systems. As a consequence, the income and attitudes of these households could be compared with those that do not yet have them. This provided a firn basis for estimating or understanding the willingness to pay for household systems. Another goal of the study was to examine the role that credit might play in expanding the sales of household photovoltaic systems in the rural areas without access to electricity. Credit is an obvious way to make the purchase of photovoltaic systems more affordable to people with low incomes. We know that today most of the purchases of renewable energy systems are on a cash basis, and previous work in these areas has not dealt with credit issues. Therefore, the study documented the household experience with credit, and whether households are predisposed to borrow money for the purchase of a household photovoltaic system. Finally, the market survey also addressed the issue of whether adequate after-sales support is available for photovoltaic systems in the areas where systems are being sold. Much has been written concerning the role of after-sales service in the promotion of and market development for household photovoltaic systems. This study examined the reliability of existing systems and people's perception of after-sales service. The results of the study confirm that a significant market exists in the remote provinces of China for electricity. The details are provided in the following chapters. In chapter 2, the provinces and the methods used to conduct the market study are described. Following that, chapter 3 describes the survey population, along with their awareness and use of renewable energy. Chapter 4 presents an analysis of a special sample of households that currently use renewable energy, mainly to determine the characteristics of those that have adopted the technology. Chapter 5 discusses the implications of this study for the development of the renewable energy in the four provinces. 9 2 BACKGROUND ON AREAS TARGETED BY THE SURVEY This chapter provides a description of the local conditions in rural areas where many people have no access to grid electricity services in the provinces of Gansu, Inner Mongolia, Qinghai, and Xinjiang. A World Bank/GEF project for photovoltaic systems will be undertaken in these remote provinces of China.2 BACKGROUND ON PROVINCES IN STUDY The provinces covered in this report are located in some of the most remote areas of China, mainly in the north and northwestem part of the country. The provinces include Gansu, Inner Mongolia, Qinghai, and Xinjiang (see map IBRD 30439 at the back of this report). These 4 provinces cover an area of 4 mnillion square kilometers, with a total of 18 million households (70.4 million people) living in the rural areas. The vast majority (approximately 83 percent) of these people already has access to some form of grid electricity.3 The remaining 17 percent of the rural population in these four provinces live in the more remote, isolated rural areas where extending grid electricity is both difficult and expensive. The four provinces or autonomous regions are characterized by large land areas relative to population (see Table 2.1). Density of rural households and rural income levels are much lower than the national average. Three of the four areas also have large minority populations, especially target areas of the survey. Two of the provinces are autonomous regions, which means that a significant share of the population is of non-Han nationality. In Inner Mongolia, the largest single ethnic minority is Mongolian, while in Xinjiang it is Uigur. In Qinghai, the majority ethnic population is Tibetan, since much of the territory was once part of Tibet. 2 Tbe project area was later expanded to include Tibet and Western Sechuan 3 Tbese houeholds have access to either national-regional or mini and isolated grid electricity. II Table 2.1: Socioeconomic Characteristics Of Four Provinces In Survey, 1997 National Gansu Inner Qinghai Xinjiang Land area (thousands of 9,600 450 1,100 720 1,600 square kilometers) Population (millions) 1,236 24.9 22.6 5.0 17.2 Density (persons per 129 55 21 7 II square kilomete) Rural per capita nct 2,090 1,185 1,602 1,320.63 1,500 income (yuan) Han nationalny (%) 94 43.5 79.6 41.6 38.4 Minonty (t.) 6 56.5 20.4 58.4 61.6 Main agncultural Grain, cotton, Grain, oil- Grain, oil- Grain, oil- products oil-beanng bearing plants, bearing plants, bearing plan. plants, pigs, sugar beets, sugar beets, sugar beets, sheep wool, pigs, cattic, pigs, cattle, pigs, cattic, poultry, and sheep, goats, yaks, sheep, sheep, goas cggs wool, and goats, wool, horses, camels, cashmere and cashmere wool, cashmnere, and milk products Source: China Statusuical Yearbook, 1998. The areas covered by the survey are also characterized by different geographic conditions-mainly mountains, basins, and plateaus. At the westem edge of Xinjiang, the targeted area contains huge differences in elevation, from 4,000-5,000 meters at the western edge, to the Tarim Basin area, much of which is desert. The Qinghai-Tibet Plateau, known as the roof of the world, towers in the southwest at more than 4,000 meters. The Gansu comdor, a narrow 1,000 kilometer corridor where the Qinghai-Tibet, Loess, and Inner Mongolian Plateaus join, was part of the ancient Silk Road leading to Xinjiang and areas to the west. In the east, the terrain of Inner Mongolia ranges from mountains with dense forests in the northeast to the vast Hulunbuer Plateau for grazing in the center, with the rest of the area containing numerous deserts, sands, salt and alkali lakes, and scattered highlands. CURRENT PHOTOVOLTAIC SYSTEM BUSINESS Despite the remoteness of these areas, photovoltaic businesses have been growing in the provinces. During the last five years, several different types of companies have been selling photovoltaic systems mainly centered in Qinghai. These companies are those that have grown from research institutes, larger ones that assemble photovoltaic systems for many applications (including telecommunications) and that may also produce 12 photovoltaic modules, and other commercial companies like television manufacturers and small wind turbine manufacturers. The companies selling photovoltaic systems typically involve three different types of operations. The businesses include urban-based distributors that procure major components from manufacturers and purchase locally minor components themselves, small assembly shops that sell systems and components of systems to system installers, and retailers that sell systems directly to end users. Some companies have their own retail networks, selling mainly through these established channels. There are also a few vertically integrated suppliers that have their own manufacturing facilities for key components, including modules and controllers. Although sales of photovoltaic home systems have increased steadily in recent years, none of these companies has a well- developed retail network. During the past five years, photovoltaic system sales in these provinces have increased dramatically. The businesses in some provinces started out as partially owned by the state, and sold systems with significant subsidies. Recently, however, many of the subsidies have been reduced or eliminated, and many new smaller companies have emerged that are dedicated to selling renewable energy systems on a commercial basis. These smaller, privately owned companies have entered the market focusing on the smaller systems that are more affordable to their customers. Although such companies have a comparative cost disadvantage because of small-scale operations and low-volume production, they have been cutting costs to compete. The emphasis on smaller systems and cutting costs is a common strategy employed by photovoltaic companies to make systems more affordable and marketable to a larger segment of the population. The photovoltaic market is increasingly competitive. Sales data collected from photovoltaic companies indicate that in 1997, the largest 4 companies held 51 percent of the market in unit sales, 31 percent of market in watt power sales, and 36 percent of the market in sales revenue. In 1997, the top four ranked companies in terms of photovoltaic system sales revenue all were registered during the past three years. The company with the largest market share increased the number of photovoltaic units sold from 3,500 in 1995 to about 7,500 units in 1997. Most of the units were the 20-watt systems, and were sold to customers in Gansu, Qinghai, Sichuan, and Tibet. The photovoltaic market is likely to remain competitive in the near future because the start-up capital requirements are small, with little investment required in equipment, buildings, and vehicles. Also, the technology required to put systems together is also relatively simple and widely available. Presently, there are no dominant brands, and the companies compete based on their product presentation and promises of quality, performance, and customer convenience. DESCRIMOION OF TYPICAL PHOTOVOLTAIC SYSTEMS USED IN RURAL AREAS IN CHINA Photovoltaic systems are typically used by individual households, and commercial and small industrial establishments to provide electricity in areas where there is no grid 13 electricity. A typical photovoltaic system is made up of a photovoltaic panel, battery, and a battery or load controller. For individual home usage, a photovoltaic system is typically used to power two to four indoor lights, an outdoor security light, and a television set or a radio-cassette. The most common systems used in the four targeted provinces and elsewhere in the country are 10 and 20-watt photovoltaic systems. The systems can power two lights and a radio-cassette for four hours. A small number of larger photovoltaic systems are also being sold. They include a 50- and 75-watt photovoltaic array. A photovoltaic system can be upgraded by adding additional panels. With an upgrade to 75 watts, the photovoltaic system will enable users to operate a color television. In China, the panel and the other components are usually packaged in two self- contained wooden boxes. Two lights are usually included in the box, and the system wiring is complete. The user simply needs to set the panel in place and connect the battery to the panel in order to be ready to start operation. BRIEF DESCRIPTION OF THE STUDY DESIGN The findings presented in this report are based on a field survey and interviews of 2,886 rural households who live in villages without access to grid electricity in the provinces of Gansu, Inner Mongolia, Qinghai, and Xinjiang (see Appendix B for the details of the methods and sample design). The surveys were conducted during August and September 1998.4 Out of 2,886 cases selected through the random sampling process, 111 homeowners had photovoltaic systems, and 439 had small wind systems. A supplemental sample also was collected for households that use photovoltaic systems. The rationale for purposely selecting households that use photovoltaic systems was to help the study develop a profile of households using these systems in the region of the study. For this purpose, an additional 27 households that own photovoltaic household systems were interviewed during the course of the project. The goal of the study, as discussed earlier, was to profile the potential market for photovoltaic systems that can provide electricity to rural households. Because so many households had electricity or were near electricity distribution systems, it made little sense to draw the sample from the provincial population. More than 80 percent of households in the selected provinces already have electricity service from grid systems. Households in counties with extensive rates of household electrification are less likely to adopt photovoltaic systems. The grid systems in China provide higher levels of electricity service, and the price for electricity is very low. The few consumers without electricity in these counties may opt to wait for grid electricity, instead of buying a photovoltaic system. As a consequence, the target population or population frame for the market survey consists of those households living in villages without grid electricity, and in the counties JThe only exception is the suvey in Abagaqi Cotmty in Inner Mongotia (a total of 90 cases), which was conducted in April 1999. 14 in which at least 15 percent of villages are without electricity.5 The population frame and the sample population are illustrated in Map IBRD 30439 at the end of this report. For the four provinces, about 1.4 million households are in such counties with an electrification rate of less than 85 percent (see Tables 2.2 and B-2 for details). Only 270,000 households without electricity are in the counties that are not in the sample frame of this study. Thus, the population universe in the study-the households in villages without electricity-are well represented by the counties that have the lowest penetration rate for grid electricity systems. Table 2.2: Households without Electricity in Counties and Provinces Gansu Mongolia Xinjiang Qinghai Total Total number of rural households in 4,169,218 2,753,990 2,248,512 493,414 9,665,134 counties with: Electricity rate greater than 85% 2,301,491 1,963,192 504,265 318,916 5,087,864 Electricity rate less than 85% 1,867,727 790,798 1,744,247 174,498 4,577,270 Total number of rural households 693,S42 383,367 4S9,956 104,052 1,640,917 without electricity in counties with: Electricity rate greater than 85% 121,637 87,011 43,735 19,348 271,731 Electricity rate less than 85% 571,905 296,356 416,221 84,704 1,369,186 Source: CRED 1998. CONCLUSION The sample of households in the region without electricity should be representative of the possible market for household photovoltaic systems. For the four provinces, the population universe of the sample covers more than 90 percent of the households without electricity in the provinces. The sample covers some of the most isolated and poorest areas of China. In the chapters that follow, details of the socioeconomic characteristics of the households without electricity access are described in detail. SThe 15 percent cutoff point was chosen based on the averagc 17 percent of households without electncity m the combined 4 provinces. 15 3 SURVEY RESULTS: SOCIOECONOMIC CHARACTERISTICS OF HOUSEHOLDS WITHOUT ELECTRICITY The purpose of this chapter is to understand the characteristics of the households in the areas without electricity in the four provinces. This provides a background for identifying the characteristics of households that would be most likely to purchase or lease household photovoltaic systems. For instance, one goal of the study was to ascertain whether incomes in such areas are high enough to make such systems affordable. Another issue is whether households are familiar with or have access to credit to purchase photovoltaic systems. These and other issues are the topic of this chapter. INCOME, OCCUPATION, AND EDUCATION The income and occupations in the four provinces are quite diverse. For instance, Gansu is an extremely poor province composed of poor farmers. This province has long been considered one of the poorest in China More than 90 percent of the households without electricity in Gansu earn their living as farmers (see Table 3. 1), but they produce very little income. The incomes in areas of Gansu that were in the survey are about Y 200 or about $25 per family per month, which is close to 6 times lower than in Inner Mongolia. In the year before the survey, a severe drought in Gansu may have affected incomes. Because of the drought, it may be possible that farmers consumed most, if not all, of the food they grew during this period, with very few cash sales of crops. Even without the drought, however, Gansu is a very poor area. The rural households in Inner Mongolia have the highest income of the four provinces (see Table 3.1). Just over 60 percent of the households living in areas without electricity in Inner Mongolia are herders. The income of the herders is close to 10 times higher compared to farmers in this same province, illustrating that herding is a good occupation for people in the area. The average income of the herders is more than Y 17 2,000 per household or $250 per month. Within China, the demand for the meat products produced by herders has been increasing, especially in urban areas. Qinghai has an even higher percentage of herders than Inner Mongolia. More than three-quarters of the populations living in areas without access to electricity in Qinghai are herders, and only 10 percent of the populations are farmers. The herders in Qinghai, however, do not earn as much income as those in Inner Mongolia. They earn about Y 675 per household per month. Table 3.1: Household Monthly Income by Type of Occupation of Household Head Gansu Mongolia Xinjiang Qinghai Toial Farmer (yuan) 200 167 759 300 365 Population represented 515,829 96,651 266,604 9,255 890,338 Percent within province 90 33 64 11 65 Herdsman (yuan) - 2,121 610 673 1410 Population represented - 180,319 98,732 66,724 345,778 Percent within province - 61 24 79 25 Mixed herding farming 288 230 645 326 428 (yuan) Population represented 26,592 10,995 31,300 8,520 77,407 Percent within province 5 4 7 10 6 Local TVE worker (yuan) 298 - 836 - 493 Population represented 5,418 - 3,078 - 8,496 Percent within province 0.9 - 0.7 - 0.6 Outside TVE worker 183 198 - - 183 (yuan) Population represented 10,753 192 - - 10,945 Percent within province 2 0.1 - - 0.8 Local mnanager (yuan) 345 390 594 - 423 Population represented 2,591 1,844 1,539 - 5,974 Percent within province 0.5 0.6 0.4 - 0.4 Retired (yuan) S00 1,711 1,064 - 1,157 Population represented 184 603 2,300 - 3,086 Percent within province - 0.2 0.6 - 0.2 Other(yuan) 378 575 642 866 529 Population represented 10,539 3,018 12,180 205 25,943 Percent within province 2 1 3 0.2 2 All households (yuan) 208 1,370 713 598 637 Population represented 571,905 295,622 415,733 84,704 1,367,964 Percent within province 100 100 100 100 100 Note: This table presents the weighted results of the sample survey. The average income of all households classified by type of occupation of household is slightly different from the average income of all households because there are a few cases with missing values for type of occupation. The U- indicates zero income. TVE stands for township and village enterprise. Source: China Market Survey 1998. Xinjiang is predominately composed of farming areas. As opposed to Gansu, the average farmer in Xinjiang has a higher income than the average herding family in the 18 same province. Their income is about two and a half to almost five times higher than farmers in three other provinces. The distribution of household income among different occupations within the province is more homogeneous than in three other provinces. The reason for this is probably that the farming in Xinjiang is very different than in Gansu. Xinjiang produces high-value cash crops, such as grapes and melons, as opposed to the grain, cotton, and oil-bearing plants grown in Gansu. The education levels in the provinces are very high for such remote areas. Only one out of the four provinces has very low levels of education. Among the four provinces, the rural households in the areas without electricity in Qinghai have the lowest educational levels. More than half of the heads of households surveyed cannot read or have never attended school, and most of the people who had attended school have only a primary school level of education. Furthermore, in about a third of rural households without electricity in Qinghai, they are illiterate or they have never attended school, or both. In the other three provinces, only 7-12 percent of the heads of households are illiteratc or have never attended school. Only 1-4 percent of the households in the thrce provinces is illitcrate. The conclusion is that the provinces differ significantly in termns of both income and occupation. The average incomes in the provinces range from a low of about Y 200 in Gansu to more than Y 1,300 in Inner Mongolia. The percentage of herders range from almost none in Gansu to more than three-quarters of the population in Qinghai. This clearly illustrates that there are likely to be very differing markets in each of the provinces, based on relative incomes and quite different occupations. VALUE OF RURAL HOUSEHIOLD ASSETS In provinces with large herding populations, income could be a misleading indicator of ability to pay for renewable energy systems. Herders may or may not havc income, depending on when they sell their livestock. As opposed to agricultural crops that are harvested on an annual basis, livestock can be sold over a period of years. Herds are a very liquid asset, and can be considered a form of savings. As a consequence, this study has also estimated the assets of the rural households, in order to supplement the infornation on family income (see Table 3.2). The value of all livestock owned determines the total assets for the rural households in this study.6 The idea for computing this value was to see whether the income of farmers and herders was an adequate measure of the ability to purchase renewable energy systems. Although this is not a true measure of total assets, realistically herders or farmers can sell livestock to raise money to 6The value of livestock is calculated from the anhxwt of hvestock oed at the um of survey NW the price at which the household sold lhvestock the year before the survey. 19 purchase consumer goods.7 Hence, it is an appropriate measure for the purposes of this study. Table 3.2: Average Value of Livestock Classified by Occupation of Head of Household and Type of Asset Gansu Inner Xinjiang Qinghai Total Mongolia Occupation Farner (yuan) 3,002 4,361 5,421 1,727 3,865 Population represented 513,373 98,651 266,109 9,255 887,378 Herdsman (yuan) .. 80,792 28,416 63,664 62,583 Population represented .. 180,319 98,211 66,681 345,212 Herdsman and farnner (yuan) 7,092 5,065 14,063 22,792 11,329 Population represented 26,592 10,995 30,681 8,520 76,788 Local TVE worker (yuan) 565 .. 5,712 .. 2,429 Population represented 5,418 .. 3078 .. 8,496 Outside TVE worker (yuan) 643 1529 .. .. 659 Population represented 10,753 192 .. .. 10,945 Local manager (yuan) 859 21,032 10,510 .. 9,572 Population represented 2,591 1,844 1,539 .. 5,974 Retired (yuan) 553 59,549 10,707 .. 19,648 Population represented 184 603 2,300 .. 3,086 Other(yuan) 3,536 11,921 2,137 72,996 4,404 Population represented 10,539 3,018 12,180 205 25,943 Total Average value of all livestock 3,124 51,382 11,458 52,802 19,213 All households (population 569,449 296,356 414,586 84,662 1,365,053 reprcsented) .. Negligible. Note: Because of the missing values of variables representing type of occupation, there are slight differences in total number of population represented and the summation of population represented by types of occupation. TVE stands for township and village enterprise. Source: China Market Survey 1998. 7 In China, land is still considered property of the state, although pcople have the right to use it, and these rights can be bought or sold. Because of the remoteness of these counties, however, land is not bought or sold as often or, when land is bought or sold, it is typically for agricultural uses and not for commercial or other uses. As a result, the price of the land is generally determined by an amount of money that can be derived or generated from agricultural activities. 20 In general, farm households are much poorer than herders in the region of the study. It should be remembered that these are farms in very remote areas, where agricultural land is poor. The only exception is in Xinjiang, where farmland is more productive than in the other three provinces.8 Most farmers in these areas are very poor. Both the evidence based on income and the proxy evidence based on assets confirm that the herders in the region are wealthier than farmers. Thus, the herders have an advantage of both income and assets over the poor farmers in these areas, which this is relevant in terrns of their ability to pay for renewable energy systems. EXPERIENCE WITH BANKING AND CREDIT The availability of credit in remote areas is often very poor. The purchase of photovoltaic systems without credit requires households to have Y 1,000-2,000 in hand, and most agree that this can be a major stumbling block to the promotion of systems. The availability of credit for the purchase of photovoltaic systems can expand the market by lowering the initial cash outlays for the systems. Because availability of credit is often considered a major barrier to the adoption of photovoltaic systems, one goal of the survey was to determine the experience of rural households with making purchases on credit. Today most purchases of renewable energy systems are on a cash basis. This chapter explores the extent of households' credit experience, along with their attitude toward and preference for using credit to purchase photovoltaic systems. Many people in these areas are familiar with credit. Between 30 and 40 percent of the households in three of the provinces already have experience with taking credit from rural banks, credit unions, or other sources (Table 3.3). The province with the lowest participation in credit markets is Qinghai, where slightly less than 10 percent of rural households reported taking a loan. As will be seen later in this chapter, most of the loans are taken for business purposes. Thus, to a certain degree, the length and the type of the loan conform to what might be expected of a small business loan for purchasing seasonal inputs for farming or herding. The average length of a loan is about one year for the three provinces with the highest percentage of borrowers. As the survey reveals, about 80 to 90 percent of borrowing households took their loans in 1997 and 1998. The amount of the loan is relatively small, ranging from Y 1,000-4,000 ($125-500). Most of the money was borrowed either from a bank or a credit union. In fact, credit unions are the most common source of loans in the area of the study. The main exception to this trend was in Inner Mongolia and Qinghai, where more people are dependent on informal credit. For Inner Mongolia and Qinghai, neighbors and relatives account for about a quarter of all loans taken by rural households in these two provinces. 'FanIland in Xinjiang is used to grow higher-pnced fuint, such as mclons and graps. 21 Table 3.3: Household Borrowing Patterns in Villages without Electricity in Four Provinces Gansu Inner Xinjiang Qinghai Mongolia Credit experience (% of 30 29 43 10 households) Average loan amount (yuan) 1,253 4,210 2,388 1,858 Average length of loan 15 12 13 22 (months) Year of last loan taken (% of households with loan) 1998 46 15 57 25 1997 34 76 26 53 1996 8 4 8 19 Before 1996 11 5 9 3 Source of loan (% of households with loan Bank 28 13 38 7 Credit union 70 58 47 51 Relatives 2 18 8 26 Neighbor 5 2 1 Others .. 6 5 15 Negligible. Source: China Market Survey, 1998. Most of the borrowing in rural areas is for business activities, which include farming and herding. Many of these loans are for purchasing inputs necessary for these activities. Farmers have seasonal needs for credit, and herders sometimes need to purchase fodder for their livestock. The loans taken out for such purposes range from one-half to two-thirds of all loans (Table 3.4). The remainder of the loans is spread evenly among a wide variety of purposes, including purchasing food, health care, house repairs, and others. Very few households have borrowed money to buy appliances. This may be because banks or credit unions in rural areas do not typically finance this type of loan. Consumers may also be somewhat conservative in taking out loans that do not generate income for them. The reason for this is that productive activities produce income that will enable the household to repay the loan. 22 Table 3.4: Household Use of Loans in Villages without Electricity in Four Provinces (percent) Use of loan Gansu Inner Xinjiang Qinghai Total Mongolia Buy food 4.9 2.0 10.9 23.7 7.1 Build, expand, or repair 7.4 4.1 3.5 4.7 5.1 house Health care 14.9 12.1 9.6 5.6 12.0 Business 63.6 64.6 64.4 52.4 64.0 Buy equipment or 2.0 3.6 4.3 5.2 3.3 appliances Important family 5.5 4.1 3.4 3.6 4.3 activities, for example, marriages and funerals Others 1.8 9.4 3.8 4.8 4.2 Total 100 100 100 100 100 Includes buying fodder and grass. Source: China Market Survey 1998. Another issue relevant to market development for renewable energy is the income of households that typically borrow money in rural areas. Households that have borrowed money have lower incomes than households who have not borrowed money (see Table 3.5). The only exception to this pattern is in Xinjiang, where people who borrow money have higher incomes compared with those who do not borrow money. Table 3.5: Comparison of Income and Value of Livestock between Households that Have not and Have Taken a Loan Before Whether households have taken Inner any loan before Gansu Mongolia Xinjiang Qinghai Total No Income 199 1,610 574 644 667 Livestock value 3,411 62,807 13,201 55,310 23,966 Percent of household) 70 71 57 90 67 Yes Income 157 514 950 337 556 Livestock value 2,829 20,758 10,063 21,594 9,619 Percent of household) 30 29 43 10 32 Total income 186 1296 735 614 631 Total livestock value 3,233 50,760 11,857 52,025 19,251 Households represented (valid 490,425 270,408 381,514 64,249 1,206,596 N) Source: China Market Survey 1998. Rural lending institutions lend money for productive uses, such as inputs to farming or for raising livestock. Although households are very likely to borrow money for 23 such purposes, there is no certainty that they will borrow money for photovoltaic systems that result mainly in improving the quality of life for rural households. CURRENT ENERGY USE AND EXPENDITURE FOR HOUSEHOLD LIGHTING An understanding of existing energy use and expenditure patterns for lighting is very important for determining the potential willingness or ability to pay for better lighting services. Generally, surveys of rural households reveal that all households use some form of lighting during the evening hours. Although the lighting may be used for short periods, and it may be of poor quality, all households use it. Given the poor light given off by most non-electric forms of lighting, the expenditures on lighting can often be considered a minimum willingness or ability to pay. Similar to elsewhere in the developing world, the major sources of energy for lighting for rural households living in villages with no access to grid electricity are kerosene lamps for general use, flashlights for task-specific and mobile purposes, and to some extent candles (see Table 3.6). Although present in all households, kerosene, diesel, and gasoline lamps are the most common in lower-income rural households. In the lowest income groups, more than 90 percent of households rely on petroleum lamps. For the higher-income groups, this figure declines modestly until the highest income group, in which only about one-fifth of the population use these lamps. A high percentage of households in Inner Mongolia area are getting light from electricity produced by renewable energy sources. Approximately 57 percent of rural households in villages with no access to grid electricity in Inner Mongolia are using small wind systems. Such systems are an especially important option for herders. Wind systems were introduced with strong government support during the last two decades. The herders actually fold up these systems and take them when they move from one grazing area to another. Outside Inner Mongolia, there is not much use of wind systems. As might be expected, the higher-income groups in the province are the primary purchasers of wind generators. During the past few years photovoltaic home systems have been introduced to rural households in these four provinces. Considerable success has been achieved in reaching remote rural populations in Qinghai, where about 9 percent of rural households in survey areas own small photovoltaic home systems. Also, rapidly increasing sales of photovoltaic systems are also reported in Tibet and Sichuan, which border Qinghai and share its cultural characteristics in these border areas. Qinghai is a province in which retailers have been most active in promoting photovoltaic home systems. Only a limited number of households in the other three provinces still use photovoltaic systems. 24 Table 3.6: Household Energy Use for Lighting by Income Class (Percent of households within group) Candles Kero- Dry cell Small Small Small PV House- or sene, batterie genera- wind hybrid home holds butter diesel, s tor sets systems systems systems repre- or sented by gasoline sample Income deciles (yuan per month) < 51.67 34.3 96.0 62.2 0.4 3.4 .. 0.0 139,141 51.67-103.33 24.8 90.5 74.4 0.5 7.3 .. 0.2 133,970 103.34-155.83 19.4 93.4 80.1 0.2 4.7 .. 0.0 136,474 155.84-208.33 33.4 93.9 85.0 0.4 3.6 0.2 0.5 135,461 208.34-275.00 27.3 93.6 78.5 2.0 4.2 0.0 0.8 141,926 275.01-378.33 26.7 82.5 80.4 1.3 7.5 0.1 1.5 133,824 378.34-500.00 40.3 84.8 79.0 2.2 4.8 0.1 0.8 137,781 500.01-716.66 52.6 71.1 87.9 5.3 10.6 .. 1.8 137,922 716.67- 62.1 56.2 89.8 10.2 23.7 .. 2.7 135,790 1,275.00 >1,275.01 81.4 18.9 95.5 20.5 62.4 0.5 2.2 136,898 Province Gansu 18.5 98.5 84.6 0.4 0.3 .0 .0 571,905 Inner 75.7 35.8 87.2 11.3 57.3 0.2 2.0 296,356 Mongolia Xinjiang 39.8 87.2 72.8 5.4 2.2 .. 0.1 416,221 Qinghai 64.8 44.0 80.3 0.5 0.1 0.3 9.1 84,704 Occupation Farner 27.3 93.6 77.4 2.4 1.9 .. 0.1 890,338 Herdsman 75.7 35.1 95.3 9.9 45.5 0.2 3.5 345,775 Herdsman and 34.7 93.5 75.3 2.4 3.2 0.3 1.0 77,407 farmner Local TVE 23.7 86.7 51.7 3.0 .. .. .. 8,496 worker Outside TVE 2.7 100.0 9.5 .. .. .. .. 10,945 worker Local manager 45.5 34.3 100.0 .. 18.6 .. .. 5,974 Retired 86.9 89.2 100.0 .. 10.8 .. .. 3,086 Other 42.0 71.6 74.0 3.1 9.0 .. 0.4 25,943 All households 40.2 78.1 81.3 4.3 13.2 0.1 1.1 1,367,964 .. Negligible. Note: TVE stands for township and village enterprise. Source: China Market Stuvey 1998. The source of lighting for rural households also varies according to income class. Electricity tends to be used among higher-income households. Only a small percentage of 25 lower-income households use electricity from small electric generators, but about 1O-20 percent of households in the ninth and tenth income deciles use these sources of energy for electricity. Similarly, the percentage of households using small wind systems rises from only a few percent among the lowest income groups to more than half the population in the highest income group, which involves mainly households in Inner Mongolia. For small photovoltaic home systems, only 2 percent of the highest income group use photovoltaic systems for lighting. Although dry cell batteries are widely used by most households, the number of households that use them also increases among higher-income classes. This suggests that higher-income households are more dependent on electric lighting than others, and they are willing to pay a very high price for electricity from dry cell batteries. The comparison of total monthly spending for lighting energy and electricity also reveals that households in Gansu, which is the poorest of all four provinces, spend the least on lighting. The total monthly spending for lighting of households in three other provinces, which also have higher income levels, is about three times more than households in Gansu Province (Figure 3.1). It should be noted that the relatively high monthly spending among households in Qinghai reflects the high market value of butter. In Qinghai, in spite of its high commercial value, butter produced from yak milk is used within the family for lighting and religious purposes, and only the butter that is left over is sold. Figure 3.1: Total Monthly Spending on Lighting Fuel in Energy and Electricity 35 31.8 0 30- E 25 - o6 20- * ~~~~ ~~14.7 14.6 15 0 eg 5 0 V-1 Gansu Inner Mongolia Xlnjbang QhngHal Note: High monthly expenses for households in Qinghai reflect the high opportunity cost of using butter for lighting. These figures do not contain the anortized costs of hghting equipment or generators. Source: China Market Survey 1998. Higher-income households spend much more than lower-income households on lighting services, and yet the amount they spend accounts for a smaller proportion of their income than lower-income counterparts. This is a pattern that is found in most developing 26 countries (Figure 3.2). For these areas, the total amount of money spent for lighting energy and electricity is relatively low, ranging from only about Y 5-6 per month among the poorest households and reaching about Y 25 per month among the highest income groups. The poorest households in the region spend between 5 and 13 percent of their cash income on purchased energy for lighting. As indicated, this is mainly because of low incomes rather than because of significant cash outlays for energy. The higher-income group spends more on energy, but spend only about 1-3 percent of their income on it (see Table 3.7). It is interesting that these higher-income groups continue to spend similar levels of money on candles and kerosene, but in addition they spend more on batteries, and in the highest group on small generator sets. Renewable energy systems are purchased for cash, and do not account for any monthly expenses for fuel. Figure 3.2: Total Monthly Spending on Lighting Energy and Electricity (energy expenses in yuan and expenses as percentage of income) 16- E 14- 0 c 12 C o 10- 0 6 -5 _ |204 4; * ** 2- 1 2 3 4 5 6 7 8 9 10 30- 25 - o 20- ~15 c 10 0 1 2 3 4 5 6 7 8 9 10 Income class Note: tmocj groups are the same as in Table 3.6. Source: Chin Market Survey 1998. 27 Table 3.7: Household Monthly Spending for Lighting Energy Candle Kerosene Dry cell Small Total As % of or butter , diesel, batteries generato spending income or r set gasoline Income (yuan per month) < 51.67 0.67 3.12 1.20 0.06 5.06 13.7 51.67-103.33 0.65 3.28 1.40 0.03 5.38 6.8 103.34-155.83 0.68 3.53 1.47 0.02 5.69 4.4 155.84-208.33 1.00 4.06 2.35 0.05 7.48 4.1 208.34-275.00 1.50 3.88 2.29 0.76 8.46 3.3 275.01-378.33 2.69 4.43 2.74 0.21 10.07 2.9 378.34-500.00 4.15 5.05 2.79 0.53 12.64 2.8 500.01-716.66 7.58 4.88 4.82 1.51 18.78 3.0 716.67-1,275.00 5.94 5.26 5.69 4.21 21.13 2.2 > 1,275.01 5.97 2.39 9.00 7.31 24.69 1.0 Province Gansu 0.34 3.56 1.67 0.08 5.66 5.5 Inner Mongolia 3.57 1.69 4.6 4.62 14.71 3.0 Xinjiang 2.09 6.5 4.65 1.39 14.65 3.7 Qinghai 24.8 2.39 4.38 0.17 31.79 5.5 Occupation Farmer 1.00 3.84 2.14 0.53 7.53 4.9 Herdsman 8.77 4.23 6.90 4.09 24.02 3.6 Herdsman and 2.58 5.44 2.68 1.02 11.72 4.1 farmer Local TVEworker 1.33 5.87 2.56 2.10 11.85 2.8 Outside IVE 0.01 2.17 0.25 .. 2.43 2.2 worker Local manager 3.33 1.64 2.61 .. 7.58 4.6 Retired 2.57 4.01 4.01 .. 10.60 1.0 Other 2.22 2.01 2.44 1.18 7.91 1.4 Spending per month 3.09 3.99 3.37 1.47 11.96 4.4 All households 1,367,177 1,359,783 1,367,753 1,369,186 1,357,172 1,357,172 .. Negligible. Note: TVE stands for township and viRlage enterprise. Source: China Market Survey 1998. The expenditure patterns for lighting services also vary significantly among herders and farmer households. About 45 percent of all herders use small wind systems compared with only 2 percent of farming households (see Table 3.6). Also, about one- tenth of all herdsman households get electricity for lighting from a small electric generator or from a community grid. Almost 4 percent of all herdsman households own photovoltaic home systems, while almost no farmer households own them. Herders also spend more for lighting energy and electricity than farmer households. 28 Households that have renewable energy devices, such as small wind, hybrid, or photovoltaic systems, are still spending more than households without any renewable energy devices. In general, households with renewable energy systems have higher incomes and spend more on all different types of lighting services (Table 3.8). The use of renewable energy for lighting, however, appears to be a significant substitute for petroleum-based fuels. It is interesting that the use of butter for lighting does not decline when households use renewable energy, further reinforcing the notion that it is used for religious and ceremonial purposes. The use of dry cell batteries also does not decline, but rather actually increases in households using renewable energy systems. This challenges the notion that renewable energy is a substitute for all batteries used by rural households; dry cell battery usage is determined largely by income, and the batteries are generally used for mobile formns of lighting. Table 3.8: Monthly Spending on Lighting for Households Using Renewable Energy Systems Candles Kerosene, D cell Small All energy As % of Income or butter diesel or battenes generator income per month gasoline set PV home systems Nonusers 3.05 4.02 3.36 1.48 11.96 4.5 632.59 Users 6.35 0.97 4.42 0.49 12.34 1.7 1,122.53 Small wind systems Nonusers 2.91 4.38 2.93 1.00 11.26 4.7 456.11 Users 4.27 1.42 6.31 4.56 16.61 2.3 1,832.51 All users of PV/wind/hybrid/systems Nonusers 2.87 4.42 2.92 1.00 11.25 4.8 451.05 Users 4.41 1.40 6.13 4.29 16.29 2.3 1,770.52 Total 3.09 3.99 3.37 1.47 11.96 4.4 637.76 Note: The percentage of households using renewable energy systemns is presented in Table 3.6. Source: China Market Survey 1998. Finally, another interesting finding from this study is that the households using small wind systems also spend more on small generators. The amount of monthly spending on small generating systems-which includes private or neighbor-owned small generator sets or community-village grids-indicates that a significant number of wind system users also use small generator systems. One reason for this might be that during the summer months, there is not enough wind for electricity everyday, and households without a source of electricity may have to do without lighting and television during these periods. In addition, about 37 percent of small wind system users reported that their systems broke down at least once during the previous 12 month. Perhaps because of such reliability problems, about 14 percent of all households that use small wind systems also get electricity from a generator or small grid electricity system. Another significant finding is that the households that have wind systems have monthly incomes of greater than Y 1,800, while households with photovoltaic systems have incomes of Y 1,100 per month. 29 ATTITUDES AND PREFERENCE TOWARD ENERGY SERVICES The attitude toward lighting services is important for understanding whether households would be inclined to purchase photovoltaic systems. In general, the survey indicated that people in rural areas who do not have access to grid electricity have a very favorable attitude toward electric lighting. The results in this chapter are based on attitude questions in which households were asked to agree or disagree with a list of statements. The households perceive that having electricity is important for both reading and studying. Virtually all households agree that it is easier to read with electric light compared with kerosene lamps, and children are more likely to study in the evening (Table 3.9). Almost all members of households in areas without electricity understand that electricity can provide a higher quality of lighting that makes it possible to read and complete close work in the evenings. The only province in which the favorable rating was less than 90 percent was Qinghai. Most of the households in these areas without electricity are unhappy with the light they get from their current fuels or energy sources. More than three-quarters of the households in the survey disagree with the statement that they are extremely happy with their current lighting fuel, and this includes a large number of households with renewable energy systems. Table 3.9: Household Energy Attitudes and Lighting Preferences (percent of households agreeing with statement) Provinces All provinces Inner No With Gansu gli Xinjiang Qinghai Iet°cit electricity Total Lighting Readmg easier 99 99 94 82 96 98 96 with electric light conpared to kerosene. Because of good 99 99 95 78 95 99 96 light, children study mrre at mghL PV systcns are a 70 31 38 42 56 27 51 good source of etectncity for lighting. Myfamrilyis 12 19 17 11 14 25 15 cxtrcnely happy with the light we get from our curent fuel. Icopletework 81 77 64 72 72 77 74 in my house after it is dark 30 outside. Television, News, and Entertainment Television takes 63 64 26 35 48 79 55 study time away from children. Watching 98 98 79 63 88 96 90 television would provide my family with great entertainment It is difficult for 85 80 67 50 76 71 75 my family to get news and infonnation. Security (i) My farnily 88 88 84 65 83 90 86 feels secure in the evening. (ii) Light at night 69 71 59 60 64 71 65 is useful to keep the herd together. Health Lighting with 68 71 68 39 64 72 66 kerosene or diesel can cause health problerms. Source: China Market Survey 1998. Households with access to some form of electricity for lighting, including photovoltaic systems, small wind systems, photovoltaic-wind hybrid systems, small generators, and community-village grids, are happier with their lighting source compared to those without electricity. However, a significant number of these households are still unhappy with their lighting situation. The households with some form of electricity are happier with their lighting source, but the number is still somewhat low, involving only one-quarter of the households with systems. In the provinces of Inner Mongolia and Qinghai, where a great enough number of households have photovoltaic systems, it was found that between 33 and 46 percent of the households with some forn of electricity were satisfied with their lighting services (Table 3.10). 31 Table 3.10: Satisfaction with Lighting Source According to Electricity Source (percent of households agreeing with statement) Percentage agreeing with statement "my family is happy with the light we get from our current fuel" Inner Gansu Mongoli Xinjiang Qinghai Total a No electricity 14 15 21 6 14 Generate their own electricity (all 17 34 13 47 34 systems) PV system n.a. 33 n.a. 46 44 Wind system n.a. 35 13 n.a. 33 Note: N. means that there are not enough households that own systems to be relevant to question. Source: China Market Survey 1998. The low satisfaction level for the households with some formn of electricity may be because of several factors. First, close to 40 percent of owners of photovoltaic systems reported that the photovoltaic systems they own are too small and do not provide enough electricity for their family needs. Second, a large number of owners of photovoltaic systems in Qinghai are experiencing problems with their electric lamps (a detailed discussion is provided in Chapter 4). Finally, the wind systems do not provide electricity for the entire year, because of insufficient winds. The relatively large number of unsatisfied customers suggests a need for further research into the opportunities of photovoltaic systems for this market segment. Households, especially those who have access to electricity, are aware of the utilities and benefits of electricity services for education and entertainrment. An overwhelming majority of surveyed households-and an even larger proportion of those with some form of electricity-believe that electricity is very useful for their productive activities, such as keeping herds together. Also, most households, and especially those who have access to electricity, reported that they complete their work in the evening after it was dark outside. Conceming entertainment, 9 out of 10 households agree that watching television would provide their family with great entertainment, but there is a concern among many households, especially those with electricity, that television takes study time away from children. On the issue of access to news and information, many households in Gansu and Inner Mongolia (85 and 75 percent, respectively) feel that it is difficult for them to get news and inforrnation, but fewer households in Qinghai and Xinjiang feel the same. About 50 and 67 percent of households in Qinghai and Xinjiang, respectively, agree that it is difficult for them to get news and information (see Table 3.9). Interestingly, households with access to electricity feel that it is easier for them to get news compared to those without electricity. This finding suggests that having electricity may reduce the feeling of isolation arnong those who live in very remote areas of the country. 32 The rural households also recognize that using electricity is a cleaner form of lighting compared to kerosene. Two-thirds of the surveyed households in three provinces feel that lighting with kerosene or diesel can cause health problems. One possible reason for the lower number of households in Qinghai that believe that kerosene causes indoor air pollution is that most households in Qinghai are used to intense smoke in their homes. Typically, herders in Qinghai use dried dung, which emits an intense level of smoke when used for cooking. In sum, the findings verify that most households would like to have access to the better lighting, entertainment, and information available with access to electricity. They are very knowledgeable about the benefits of electricity. In addition, once households have directly experienced the benefits of electricity, they become dissatisfied with the service limitations of smaller systems. KNOWLEDGE OF AND ACCESS TO PHOTOVOLTAIC SYSTEMS Because electricity is so extensive in China, most households are aware of the benefits of electricity. Not all households in the remote sample areas of this study, however, have heard about photovoltaic systems. About one-third of the households in the provinces have never heard about photovoltaic systems, and about two-thirds of them have not heard about wind-photovoltaic hybrid systems (see Table 3.11). The households that have heard about systems have either seen a system at their neighbor's or have heard about them from a neighbor. Table 3.11: Household Knowledge of Renewable Energy Systems (percent of households who have never heard of systems) System Gansu Inner Xinjiang Qinghai Total Mongolia PV systems of 20 watts 37 32 31 32 34 Small wind-PV hybrid 71 56 70 74 67 systems Source: China Market Survey 1998. Thus, word of mouth has played a very important role in disseminating information about photovoltaic systems. Opinion leaders appear to be a significant source of information with regards to the spread of such systems. Many people, however, still have not heard about the renewable energy systems. More than one-third of households have never heard about these systems, which illustrates that the retailers still are not reaching a significant proportion of the potential market. There is still scope for programs that raise awareness of these systems, an issue that will be addressed in the concluding chapter of this report. CONCLUSION A fairly large population in the remote areas of China has no access to electricity. Interestingly, many of these households are already using renewable energy sources, such 33 as wind and to limited degree photovoltaic systems. Even the households with photovoltaic and wind energy systems, however, are not totally satisfied with the service they are receiving from them. There is discontent over the quality and quantity of lighting received from such systems. Also, there are still large proportions of these populations that do not have knowledge of the availability of these systems or the wider technical options that are available to them. Finally, there is some degree of dissatisfaction with the existing systems. Many of these issues are addressed in the next chapter, which involves a more detailed analysis of households with photovoltaic energy systems. 34 4 PROFILE OF HOUSEHOLDS WITH PHOTOVOLTAIC SYSTEMS In this chapter, a profile is developed for the households that have purchased photovoltaic systems. An understanding of the existing customer base for photovoltaic systems is essential for any program that has the goal of expanding the market for these systems. The characteristics of photovoltaic system owners that are examined include level of income, assets, credit experience, education, type of photovoltaic system owned, methods of purchase, system performance, and quality of services. The study was designed to survey households with photovoltaic systems, even if they were not selected as part of the random sample (see Appendix B for details). It was fortunate that enough households were selected as part of the random sample in Inner Mongolia and Qinghai so that a special sample did not have to be drawn. In other words, the owners of photovoltaic systems in these two provinces are representative of the region. There were not enough sampled owners of systems in Gansu and Xinjiang Provinces, however, so in the course of conducting the survey, a purposive sample of photovoltaic system owners was selected. Although these households cannot be considered representative for the provinces, they provide valuable insight into the markets for renewable energy in the region of the survey. PROFILE OF PHOTOVOLTAIC SYSTEM OWNERS Most owners of photovoltaic systems in the four provinces are herders. More than 90 percent of photovoltaic system owners in Inner Mongolia are herder households. About 84 and 63 percent of photovoltaic system owners in Qinghai and Xinjiang, respectively, are herders, and many of the remaining households have mixed occupations of farming and herding. Only in Gansu do farmer households own photovoltaic systems, mainly because almost all the households in this province are farmers. Also, in this province the households with photovoltaic systems were not part of the random sample, and systems were probably distributed or subsidized as part of a government program. Photovoltaic system owners also tend to have higher incomes, greater assets, and more education than those who do not own systems. The income categories used in Table 35 4.1 are based on the income deciles for the entire population of the study. This gives a view of where households owning photovoltaic systems fall within the income distribution of the provinces. It should be remembered that because of differing income distributions for the provinces, there are more households in the lower half of income distribution for Gansu (75 percent) and a greater number of households in the higher half for the other provinces (65-85 percent). The households with photovoltaic systems all have incomes in the highest half of the income distribution for the four provinces (see Figure 4.1). Households with monthly incomes below Y 300 or close to $40 cannot readily afford to purchase households systems. Below this level only 10 percent of the households own systems. As mentioned, owners of photovoltaic systems in Gansu are poorer than in the other provinces. The main reason that some of the low-income households in Gansu own photovoltaic systems is that they have received them as part of a poverty reduction program. Figure 4.1: Distribution of Owners of Photovoltaic Systems Based on Income Deciles 100% 0~~~~~~~~~~~~~~~~~~~~~~~~~~~0~ 60%/ -. ~ 40%- jjj jjA 4 0~~~~~~~~~~~~~~~~1 620% - ° 6 a * 40% - a1 0% Lowest income decile Source: China Market Survey 1998. Given these results, as expected, the average income of households that own a photovoltaic system is higher than the average incomes for the provinces. The average income for all the 143 photovoltaic system owners is about Y 966 (just over $100), which 36 is about Y 300 higher than the average income for the general population in this study.9 Thus, the typical owner of a household photovoltaic system has greater income than the general population but the threshold for purchasing such systems is below the average income for the areas in the study. As indicated in Table 4.1, the threshold for households that have purchased the systems with cash is Y 275 per month or close to $35, and they are likely to have a significant number of livestock as well. Table 4.1: Owners of Photovoltaic Systems Whose Household Monthly Income Falls within Each Income Category for All Households (percent) Household monthly income deciles Gansu Inner Xinjiang Qinghai Toial for all provinces Mongolia < 51.67 13 .. .. 1 2 51.67-103.33 .. .. .. 3 2 103.34-155.83 .. .. 155.84-208.33 19 .. 6 3 5 208.34-275.00 12 7 6 3 5 275.01-378.33 19 .. 12 22 18 378.34-500.00 .. .. 19 12 11 500.01-716.66 .. 13 25 15 14 716.67-1275.00 .. 27 19 27 23 >1275.01 37 53 13 14 20 Income per household per month 1,241 2,131 644 791 966 (PV households Income per household per month 208 1,370 713 597 636 (general population) Asset value (PV households) 49,994 69,351 33,396 74,891 66,825 Asset value (general population) 5,311 51,910 18,505 52,802 22,406 Number of sample households with 16 15 16 96 143 systems .. Neglgible. Note: Households in Gansu and Qinghai Provinces were not selected at random for interview, but households in Inner Mongolia and Qinghai were randomly selected for interview. Source: China Market Survey 1998. Similar to income, the average value of livestock owned by owners of photovoltaic systems is significantly higher than the provincial average. Based on the combined income and asset profile of owners of photovoltaic systems, owners can be classified into four groups. Households in the first group have income and assets that are within the highest half of the general population. This group accounts for about 82 percent of owners of photovoltaic systems selected for interview (Figure 4.2). The second group is interesting because it involves households with low income, but with high assets. 9The smaller average income could result from that fact that data used to descrnbe solar photovoltaic system owners for the province were not randomly selected, and very few cases showed up in the data 37 This group accounts for 9 percent of owners of photovoltaic systems, in spite of their low incomes. Figure 4.2: Distribution of Photovoltaic Owners Based on Income and Assets Owned Low income, Lowest low assets income and 6% | ssets Low income, high assets 9% X | ~~High g w | ~high assetsZ Source: China Market Survey 1998. The remaining two groups account for only about 9 percent of total system owners. This confirms that income and the total value of assets owned, particularly livestock, are complementary indicators of whether households can afford to purchase a photovoltaic system. Almost all owners of photovoltaic systems in the third and fourth groups-high-income and low-asset, and low-income and low-asset-are from Gansu Province. As indicated, these households may have acquired their photovoltaic systems through the government-sponsored poverty alleviation program with significant subsidies from the government or other sources. The households that own photovoltaic systems generally have higher educational levels compared with households without photovoltaic systems. In households that own photovoltaic systems, more than 94 percent of the heads of households in Xinjiang and Gansu Provinces and all the heads of households in Inner Mongolia could read. In Qinghai about two-thirds of households with photovoltaic systems could read. Furthermore, the heads of households with photovoltaic system owners in Gansu and Xinjiang Province generally have higher levels of education compared with the provincial averages. Educational levels of owners of photovoltaic systems in Qinghai are higher than the provincial average. Clearly, there is a strong link between education and ownership of households photovoltaic systems. 38 The reasons for households to purchase a photovoltaic system included better lighting and the ability to watch television, among others. As expected, virtually all the owners of photovoltaic systems cited that they bought their systems to obtain better lighting. Television viewing was also a primary reason for more than 80 percent of households' owning systems in Gansu. Some households also indicated that the systems were cheaper to use for lighting compared to kerosene or other fuels. Finally, many families with systems felt that they were important for their children's education. THE TYrPE OF PHOTOVOLTAIC SYSTEM PURCHASED BY HOUSEHOLDS All households that owned photovoltaic systems had only one system, and these systems were purchased with cash. The households with photovoltaic systems rank in the highest half of the income distribution for the provinces, and most are in the top 30 percent. Generally, households do not perceive that the systems are overly expensive. Although about two-thirds of owners of photovoltaic systems in Xinjiang and Qinghai thought that the systems were expensive, in Inner Mongolia and Gansu most households thought that that the systems were priced fairly. Although credit is available for other purposes in the provinces, it has not been used for the purchase of household photovoltaic systems. As a consequence, it is not surprising that the households with photovoltaic systems have limited experience with credit, and that few distinctions exist regarding the use of credit between households with and without photovoltaic systems. Among the four provinces, the proportion of owners of photovoltaic systems in Gansu and Qinghai who have taken loans before is almost the same as the general population, but this does not hold for Inner Mongolia and Xinjiang (Table 4.1). Only about a third of owners of photovoltaic systems in Gansu and a tenth in Qinghai have taken a loan before, but the figures are higher for Inner Mongolia and Xinjiang. About half the owners of photovoltaic systems in Inner Mongolia and a third in Xinjiang have taken loans before. Furthermore, there is no difference in the amount, term, and purpose of the loans between owners of photovoltaic systems and other households in the provinces. The typical size of photovoltaic systems owned by rural households tends to be small, at about 20 watts (see Table 4.2). This finding is consistent with other recent intemational studies of photovoltaic system sales and ownership patterns. About 76 percent of owners of photovoltaic systems reported that they own 20-watt systems; 14 percent own system of 30-50 watts; and the rest are divided between very small (less than 20 watts) and very large systems (larger than 50 watts). As expected, the larger systems are more expensive, and are purchased by households whose incomes fall in the upper 20 percent of the income distribution (see Figure 4.3). 39 Table 4.2: The Nature of Photovoltaic System Purchases in Four Provinces Household monthly income Gansu Inner Xinjiang Qinghai Total deciles for all provinces Mongolia Size of systems (watts for 19 43 24 22 24 modules) Average price of systems 1,644 1,244 1,493 1,740 1,661 Number of years with system (% of households) One ycar 33 13 27 29 28 Two years 47 34 40 35 Thre ycars 13 .. 33 20 18 Four years .. .. .. 1.0 1 Five years 6 7 .. 8 7 More than five ycars .. 80 6 2 11 Total 100 100 100 100 100 Expenencc with credit (% of houscholds) PV system owners 36 50 31 8 18 General population 30 29 43 10 33 Niumber of systems surveyed 16 15 16 96 143 .. Negligible Source: Chma Market Survey 1998. Although photovoltaic home systems have been in use in these four provinces for some time, about 80 percent of the owners of photovoltaic systems have purchased their systems during the past three years. This indicates that the market for photovoltaic systems is relatively new. The only exception is in Inner Mongolia where the average photovoltaic system owned by households is larger and less expensive than in the othcr provinces. The reason for this is that households in Inner Mongolia have been using photovoltaic systems for about a decade. At the time of purchase, the prices were lowcr than they are today.'" Also, the systems that were available at that time were subsidized through a government program. Fewer recent purchases of systems have been reported in Inner Mongolia, however, where wind systems are prevalent. Recently, the subsidies for wind systems werc reduced; it is now a commercial program. By contrast, the prograrn for photovoltaic systems has becn mainly on a demonstration basis. Recently, the subsidies for photovoltaic systems have been largely phased out. In spite of this, the sales of photovoltaic systems have been increasing, but it is from a very small base. '°A signmficant nunber of pbotovoltaic system ownews iD Inne Mongolia have had their system for a long ame, and the reported prices pud by the hotseholds wrv relatuvely low, reflecting the subsidizcd prices at the tim. 40 Figure 4.3: Average Size of Photovoltaic System Owned by Income 35 30- 25 2 5 * 20 - * 7 m m m m m _ E10- 1 2 3 4 5 6 7 8 9 10 Income class Note: There were no systems owned in income class 3. Source: China Market Survey 1998. Typically, households purchase photovoltaic systems for better lighting and for watching television. The people benefit from these uses by being able to read and write, work, watch news and entertainment programs on television, and enjoy social visits in the evening. On average, households use electricity from photovoltaic systems for lighting for about two hours per evening in Inner Mongolia and for up to five hours in Xinjiang. With respect to the adequacy of photovoltaic systems, about 40 percent of system owners in Gansu and Inner Mongolia reported that the electricity from their systems is just enough for household use, compared to about 50 percent and 67 percent of households in Qinghai and Xinjiang, respectively. In general, close to 40 percent of the owners of photovoltaic systems reported that electricity generated from their photovoltaic system is not enough for household use. This finding appears to confirm that households in these four provinces settled on smaller systems because of the cost, so there may be a market for upgrading systems through the addition of system components in the future. SYSTEM PERFORMANCE AND QUALITY OF SERVICE Most of the photovoltaic systems in the provinces have performed relatively well so far. As indicated in the previous chapter, however, more than 60 percent of owners of photovoltaic systems have had their systems for less than two years. Most of the systems and system components are designed to last three years or longer. For instance, photovoltaic panels are designed to last 20 years, the system controllers can last 10 years, and the batteries generally can continue working about 3 years. Because of this, more than 60 percent of system owners in Gansu, Inner Mongolia, and Xinjiang reported that their systems have never broken down. Among those in Gansu, Inner Mongolia, and Xinjiang who reported to have system problems, the majority indicated that their systems have had problems only once or twice since they bought them. The main problem with the systems has been with the 41 compact fluorescent lamps and the batteries (see Table 4.3). In Qinghai, the lamp failures have been much higher than in the other provinces. The high rate of problems with compact fluorescent lamps, fluorescent tubes, and even the batteries in Qinghai may suggest that the quality of these parts may be below standard, or they may have been installed in poorly designed systems. For instance, many systems are sold without battery controllers. Also, compact fluorescent lamps and fluorescent tubes should last more than two years, given that these light bulbs or tubes are used only a few hours a day. Furthermore, the average ownership of the systems is only 22 months, and during this time the compact fluorescent lamps or fluorescent tube should not have to be replaced." The reason for the short period of ownership is that most systems have been purchased during the last five years. Table 4.3: Experiences with Repairs and Services Gansu Inner Xinjiang Qinghai Total Mongolia Number of times PV system has broken down since it was purchased ('Io of households) None 63 77 67 49 55 One time 13 15 27 5 9 Two times 6 .. .. 9 8 Three times or more 18 7 6 36 28 Average number of days PV system was out of service (days) 38 64 28 21 27 Average distance to repair shop 50 41 118 455 353 (kilomneters) Part of PVsystem that was out of order (%lo of households) Battcry 33 67 43 33 35 Light bulb or tube 42 33 67 96 81 Charge or discharge controller 36 .. .. 12 15 ACIDC adapter .. 33 20 .. 3 Average total cost of repair (yuan 26 n.a. 173 26 41 per repair) Mode of transportation to repair shop (%/ of households) Car, bus, truck, or motorcycle 100 100 S0 53 59 Horse, yak, or cart 33 3 7 Combination of above .. .. 17 44 34 Number of systems surveyed 16 15 16 96 143 .. Negligible. ni. Not available. Sowce: China Market Survey 1998. "For cxale. a 7-wan or I I-watt-12-volt DC comwact fluorescent lamps, Solsum brand name mnde in Chin and available in the US. mariet, has a tife expectancy of approximately 6,000 hours, which mfysm the banps should last 3 to 6 years depending on usagc. 42 For photovoltaic systems in need of repair, the average number of days that the systems were out of service during the last year ranged from 21 to 64 days (see Table 4.3). The reasons for the delays in repairs were mainly because of the difficulty getting parts and the relatively long distances to repair facilities. With the exception of Gansu, the majority of owners of photovoltaic systems take their systems to a repair shop when they have problems with them. Because there are no repair shops in the township or county, photovoltaic system owners have difficulty getting their systems repaired. For instance, owners of photovoltaic systems in Qinghai and Xinjiang often take combined modes of transportation, including bus, truck, horse, or yak. The average distance owners of photovoltaic systems have to travel to reach a repair shop ranges from 118 kilometers in Xinjiang to 455 kilometers in Qinghai. By contrast, owners of photovoltaic systems in Gansu and Inner Mongolia can have their systems repaired closer to their villages. Thus, the after-sales service is very poor, and repair shops tend to be located in larger cities. This raises the question as to whether the shortage of these parts and the long waits for system repairs is adversely effecting the expansion of the markets in these provinces. CONCLUSION At present, the main market for photovoltaic systems in the four provinces are the households in the highest half of the income distribution. Such households also have fairly high levels of education. Most households buy systems that are affordable to them, but perhaps which do not give the level of electricity service that they desire. Most systems in the region are less than two years of age and are relatively small-about 20- watt systems. Currently, the market is for cash sales only, and credit is not used for the purchase of systems. Although the majority of systems seem to be performing well, the main problems are with the lamps and batteries. When systems do need repairs, few convenient facilities are available, and the average wait time for repairs is about one month. In spite of the problems, almost all photovoltaic system owners across all four provinces are satisfied with the performance of their systems and would recommend them to relatives or friends. The general characteristics of the households in remote areas without access to grid electricity were described in a previous chapter. This chapter has provided a profile of typical owners of photovoltaic systems, with systems and without systems have been detailed. In the next chapter, insights from both of these groups-the adapters of photovoltaic systems and the general population-are used to develop a profile of the potential market for systems in the four provinces. 43 5 POTENTIAL MARKET FOR PHOTOVOLTAIC SYSTEMS IN FouR PROVINCES This chapter provides an analysis of the affordability of photovoltaic systems, and includes an estimate of the size of market based on different ways for people to pay for the systems. The analysis is based on a comparison of the characteristics of rural households in villages without grid electricity services and a profile of current photovoltaic system owners. In two provinces, the random sample contained a significant number of households with renewable energy systems. Because these households are representatives of the households without access to grid electricity in these two provinces, the estimate the size of the potential market in these areas is more precise. The main criteria that have been used to determine the potential market for renewable energy systems are income, assets, education, and the attitude toward credit of the owners of photovoltaic systems and the surveyed rural households. In the case of China, the existing expenditures on energy are very low, so this is not a useful indicator for estimating the market for renewable energy systems. In addition, the households with renewable energy systems seem to continue to spend close to the same amount of money on lighting services provided by kerosene, diesel, candles and other sources of energy. As a consequence, the purchase of a renewable system does not appear to be a replacement for current fuels, but rather it involves additional or new uses of the services made possible by the availability of electricity. ABILITY TO PAY CASH FOR PHOTOVOLTAIC SYSTEMS In the previous chapter, it was found that households with high incomes and with fairly great assets could afford to purchase photovoltaic systems. In terms of income, about 90 percent of all owners of photovoltaic systems in Inner Mongolia, Qinghai, and Xinjiang are concentrated in the upper 50 percent of the income distribution for the provinces. The main exception is Gansu, a very poor province where photovoltaic systems have been distributed through a government subsidy program. Assets may also be an important factor in making photovoltaic systems affordable. Virtually all households in Inner Mongolia and Xinjiang, and more than 98 percent of households in Qinghai possess the asset value classified in the upper 50 percent of asset distribution for the 45 provinces. The main exception to this pattern is Gansu, which is a very poor province with both low income and low assets. Combining the results of the survey of photovoltaic system owners with the general survey, about 41 percent of rural households in the four provinces appear to have similar levels of income and assets as those who have already purchased photovoltaic system with cash. The typical system purchased was small-20 watts or less-so these findings apply mainly to small systems. Assuming that a functioning retail market exists in these remote provinces, such households definitely could afford to purchase photovoltaic systems. These households have higher incomes, as well as greater assets, with monthly incomes that are greater than Y 275, and the total value of assets starts at about Y 7,163 per household. In this group are about 562,573 households in the 4 provinces. This includes 171,154 households in Inner Mongolia, 237,329 households in Xinjiang, and 62,425 in Qinghai (see Table 5.1). For Inner Mongolia, it should be cautioned that about half the households have small wind systems, which provides a service similar to that of a photovoltaic system. Thus, the marketing of photovoltaic systems may have to compete with, or in the case of a market for hybrid systems, complement wind systems. Because there is not as much wind during the summer months when solar radiation is the greatest, photovoltaic systems may be the perfect complement to wind systems. Table 5.1: Households That Could Afford Small Photovoltaic Systems Gansu Inner Xinjiang Qinghai Total Mongolia Small systems are affordable High-income and high-asset 43,838 180,186 196,991 62,026 483,040 households Percentage of households 8 61 47 73 35 Small systems may be affordable Low-income and high-asset 93,775 56,064 35,596 13,471 198,906 households Percentage of households 16 19 9 16 15 High-income and low-asset 98,988 3,962 91,708 4,473 199,131 households Percentage of households 17 1 22 5 15 Small systems are probably not affordable Low-income and low-asset 332,849 56,144 90,291 4,691 383,975 households Percentage of households 59 19 22 6 35 All households 569,449 296,356 414,586 84,662 1,365,053 Note: High refers to upper 50 percent brackets and low refcrs to lower 50 percent brackets. Source: China Market Survey 1998. The households in the poorest group are located mostly in Gansu Province. In Gansu about two-thirds of the households have both low income and few assets. As might 46 be expected, the number of households that can afford to purchase systems on a cash basis in Gansu is 8 percent of the total population, which is very small compared with the other provinces. The people in the areas without electricity in this province are very poor, and they have little ability to pay for the systems. These estimates are for all households in the region, whether or not they presently own an altemative energy source, such as a generator set or a wind system. The reason for not excluding the households that already have some other way to generate electricity is that the survey indicated that it is quite common to have multiple means of electricity generation, especially in the higher-income groups. It could even be speculated that the adoption of some form of electrical lighting, along with the new awareness of the benefits of electricity that is associated with the lighting, actually increases the demand for altemative sources of electricity. Therefore, it is assumed in Table 5.1 that demand for photovoltaic systems exist even in households with some other form of electrical lighting. The reason for this is that the households with renewable energy systems have expressed dissatisfaction with the level of service. POTENTIAL DEMAND FOR LARGER SYSTEMS More than 50 percent of households reported that they were not satisfied with their level of lighting service. Many households also supplement the service from their renewable energy systems by purchasing energy devices, such as kerosene, candles, and even generator sets. Many households in the upper three income deciles own the larger photovoltaic systems, at a cost of between Y 3,800 and Y 6,000 each. From this, one can infer that the target group for the larger systems is in the top two income deciles. As a result, it is estimated that approximately 264,515 households in all four provinces could afford to buy larger photovoltaic systems with cash. This accounts for 47 percent of the estimated total number of households that could afford to buy a small 20-watt photovoltaic system with cash (see Table 4.2). As a result, it is quite possible that a demand for larger systems or system upgrades will emerge. It is also conceivable that the larger photovoltaic systems will be in greater demand in the foreseeable future (see Table 5.2). Table 5.2: Households That Could Afford to Purchase Large Photovoltaic Systems Estimated number of Gansu Inner Xinjiang Qinghai Total households that: Mongolia Could afford a larger system with cash 3,613 133,348 84,421 23,226 244,607 May be able to afford a larger system with cash and credit 8,125 17,377 50,882 3,259 79,643 Probably could not afford to buy a larger system 32,100 29,461 61,688 35,541 158,790 Total number of households in the upper 5 icome and 43,838 180,186 196,991 62,026 483,040 asset brackets Source: China Market Survey 1998. 47 The availability of credit may make it possible for the households below the highest income groups to be able to afford larger systems. Many of these households have access to credit and have used different types of credit. Assuming that the credit could be made available to this middle group of households, close to 80,000 additional households might be able to purchase systems. It should be cautioned, however, that the use of credit for major household purchases is not common in these provinces. ATTITUDES AND PREFERENCES FOR TYPES OF SYSTEM AND PAYMENT METHODS The analysis of affordability showed that about half the households in all four surveyed provinces can afford to buy at least a small 20-watt photovoltaic system with cash. Only 20 percent of all surveyed households across four provinces, however, indicatc that they are interested in buying a 20-watt photovoltaic system with cash (Table 5.3). For Inner Mongolia, which has the high penetration of small wind systems, the figure is even lower-at about II percent. The situation does not improve much with the possibility of purchasing a system on credit for one or two years. Table 5.3: Households Interested in Buying a Different Size Photovoltaic System Using Cash or Credit (percent) Gansu Inner Xinjiang Qinghai Toial Mongolia Households interested in buying 20-watt PV systems with: Cash 26 11 13 18 19 One year credit 4 2 5 4 4 Two years' crcdit 1 0.5 4 11 2 Households interested in buying 50-watt pv systems with: Cash 25 19 31 19 24 Orc year credit 3 4 8 6 4 Twoyears' credit 3 0.6 19 17 6 l1ouscholds interested in buying 70-watt PV systenms with: Cash 18 33 33 32 24 One year credit 15 7 16 .. 13 Twoycse' credit 2 1 22 2 5 Negligible. Note: Thesrwvey results preented jD this table are based on a series of bypothetical questions designed to gauge the interest and knowledge of respondents about 20-, 50-, and 70-watt PV systeza. See Appendix Tables A-6 drough A-1 I for details. Source: China Market Survey 1998. Although many households expressed interest in purchasing systems, some families lacked interest. It should be cautioned that the indication of interest among respondents is measured by several hypothetical questions concerning interest in buying photovoltaic systems of three sizes (20, 50, and 70 watts). There are several reasons that households might not be interested in purchasing systems. First, many households know 48 nothing about photovoltaic systems. Second, some households are not comfortable with the idea of buying major appliances with credit. Of those who have been exposed to credit, the majority borrowed money for business purposes. Furthermore, their exposure to credit is still very limited. Third, some households are simply not interested in photovoltaic home systems. Fourth, the majority-about 55 percent-indicated that their main reason for not buying the systems was that they believe that photovoltaic home systems are very expensive. Other reasons were given by households for not being interested in purchasing. They feel that there is "no convenient location to buy them," "they can't get credit," "they worry about the quality," "the system capacity is not enough," or "they will get connected to the grid soon or will purchase a small diesel generator set soon." Given the hypothetical nature of the questions that were asked of respondents, the results cannot be considered a definitive indication of the market for photovoltaic systems. For instance, significant numbers of respondents who are interested in buying systems, particularly the larger sizes, do not have enough income to afford them. On the other hand, a significant number of respondents who are interested in buying systems with a capacity of less than 20 watts have enough income and assets to purchase such systems either with cash or credit. In any event, the results clearly indicate some of the major hurdles to expanding the market for these products. CONCLUSION This chapter outlined the potential market for photovoltaic systems in remote provinces of China. Many households in these remote areas can afford photovoltaic systems, and in fact, many have already purchased them. The main reason households in these provinces can afford them is that many of them are herders who own many animals. With a significant and growing demand for meat in China, they are able to sell their animals at very attractive prices and earn a high income. In addition to high income, households with higher education levels are more likely to purchase systems than those with lower levels of education. Affordability does not always translate into the purchase of systems, however. As indicated in this study, in spite of the continuing development of retail markets in these provinces, many problems remain. When systems have problems, households have great difficulties in getting spare parts or repairs. The credit system in the provinces is geared toward seasonal credit for agriculture and not toward the purchase of items for household use. At present, people in the region seem resistant to using credit for large purchases of household appliances. Given the remote locations of these areas and the lack of access to grid electricity, development of any type of market will be challenging. There are reasons for optimism as well, though. Incomes turned out to be higher than expected at the beginning of the study. In one province, about half the households without electricity already have purchased inexpensive wind systems, and close to one-tenth of households in Qinghai have purchased photovoltaic systems for lighting. In the next chapter, policy recommendations based on this study are discussed. 49 6 CONCLUSIONS AND RECOMMENDATIONS In many countries, households without access to electricity spend a significant amount of their income on petroleum fuels and batteries for household lighting. In the survey areas covered in this study, people without electricity spend very little of their monthly income on energy, although many households have purchased wind energy systems or electricity generator sets with cash to get improved lighting and communication services. About half the households in the areas surveyed in Inner Mongolia have wind generation systems, and 11 percent of the households have generator sets that run on petroleum fuels. From the survey, it is clear that people value electricity for lighting, communications, entertainment, and other services. The provinces covered by the study include Gansu, Inner Mongolia, Qinghai, and Xinjian. The areas within these provinces covered by the survey are limited to the counties with more than 15 percent of households that do not have electricity service from a grid system. Further, only communities without access to grid electricity were included in the survey. Within this study area, there are wide variations in occupations, incomes, and levels education. In general, herders are much wealthier than farmers in the provinces. With herders concentrated in Inner Mongolia and Qinghai, as expected, Inner Mongolia has the highest income for the study areas involving only villages without electricity. Many people in the provinces have extensive experience with credit, but the credit is used mostly for productive activities and not for household consumer goods. THE MARKET FOR PHOTOVOLTAIC SYSTEMS EXISTS AND Is GROWING The market for photovoltaic systems in the provinces is small, but growing. In two out of the four states, a significant number of households that own photovoltaic systems even show up in our random sample. The existing sales figures for the photovoltaic industry are considerably higher than the numbers indicated by the survey, which is consistent with the companies' reports that they are selling to other areas, especially westem Sichuan and Tibet. The systems that people have purchased are mostly small and inexpensive, and have been purchased on a cash basis. People in the households with systems definitely would recommend them to their friends. They value highly the benefits of having electricity, including lighting, entertainment, and information, but the inexpensive systems also can result in maintenance difficulties, such as problems with 51 lights and batteries. People also are not totally satisfied with the level of service they get from such small systems. They want more service from their systems. In these remote provinces in China, many households are now able to afford to pay for small photovoltaic systems with cash. The study found that about 500,000 households can afford to pay cash for systems that are less than 20-watt photovoltaic. Most of these households are in Inner Mongolia, Qinghai, and Xinjiang. This estimate includes many households that already own some form of electricity generation, such as a wind generator or a generator set. For instance, in Inner Mongolia about half the households in the study area already have wind systems. We have not excluded these households from the estimated market, because a significant number of households own multiple systems to generate electricity.'2 In Gansu, the household incomes are generally below the threshold level for the purchase of a system. In this province, a viable commercial market for systems sold on a cash basis appears unlikely. In Gansu, some form of subsidy or credit, or combination of the two, would be necessary to encourage broad adoption of photovoltaic systems. As might be expected, the households that are purchasing photovoltaic systems generally are literate, and it appears that both education and income are key factors in predicting whether a household will purchase a system. Most of the existing systems are in households that are in the upper half of the income distribution for the areas without electricity, and most of them have higher education levels than average for the population. Most people in the provinces are not happy with their source of lighting. This includes households with and without renewable energy systems. Households with photovoltaic systems are happy with their performance and would recommend their purchase to a neighbor, but many feel that the systems do not provide enough lighting or other electricity services. Therefore, a significant market may exist to upgrade the existing typical 20-watt systems that people are using today. One note of caution concerning these results is warranted. The dissatisfaction with the service of renewable systems may be the result of comparisons with grid service levels. Given the extensive reach of the grid service in rural areas of China, unrealistic anticipation or expectations of grid service coming soon to an area would likely be very detrimental to the expansion of the market for renewable systems. 12 Akhough we have not atwmneed to estimate marke outside the four provinces covered by the survey, an additional 500,000 households without electricity in Tibet and Sichuan are part of the potential n3arket for photovohtaic system. 52 HOUSEHOLDS APPEAR TO HAVE LITTLE INTEREST IN USING CREDIT TO PURCHASE PHOTOVOLTAIC SYSTEMS Many households in the survey are utilizing credit for their commercial activities, including farming. They borrow money from rural banks and cooperatives to purchase agricultural inputs and other items. Loans are often of very short duration, with the most common loan being repaid in one year. Presently, credit appears not to be used to purchase consumer durable goods in these areas. In addition, households in the region appeared uninterested in purchasing a photovoltaic system on credit, preferring instead to pay with cash. For wealthy herders, paying with cash would not be much of a problem, because they would only have to sell off a few animals. To deepen the market by reaching the middle- and lower-income groups, and perhaps to allow higher-income households to purchase larger systems, some form of credit or installment payment is necessary. The lack of interest shown by households toward purchasing consumer durable goods with credit, along with the importance of credit toward deepening the potential market for systems, indicates a need for further work in this area. Therefore, it is recommended that this topic be investigated through focus group interviews that seek the reasons for the lack of interest and explore all potential approaches to increasing the affordability of the systems. SALES AND AFTER-SALES NETWORKS NEED TO BE EXPANDED Most households in the areas without access to electricity in the remote provinces have no access to retailers that sell photovoltaic systems. Even where systems are sold, there is very little after-sales support for systems. Customers often wait about one month for systems repairs. The average distance to a repair shop varies from 50 kilometers to more than 400 kilometers. Simple parts for common problems with systems, such as lamp failures, are not available locally. STANDARDS AND SPECIFICATIONS MAY BE IMPORTANT FOR MARKET DEVELOPMENT The systems that are being sold in the study area are mainly small systems of less than 20 watts. The practice of selling inexpensive systems makes systems affordable to a wider segment of the population. Less expensive systems are affordable, but there is a higher incidence of repairs and system component failures in areas with many small systems. This can be very costly in terms of product acceptance. If the systems have operational problems in some households-especially those of the early adopters-others may postpone or not purchase systems. The adoption of mandatory standards and certification of products is one important way to reduce the quality and after-sales service problems found through the survey. Such standards and certification procedures have already been introduced in preparation for the China Renewable Energy Development Project. 53 CONCLUSION With the exception of Gansu, all the other provinces in the study area have significant potential markets for photovoltaic systems, even on a cash basis. At present, the development of these markets in its infancy. Commercial retailers have begun to service the three provinces only during the last three years, and they are often in competition with more established firns that have been involved in previous government programs. There will be many problems that are faced in expanding the market beyond the richest households in the provinces. They include the lack of interest in credit for photovoltaic system purchases by households, the weak existing sales and after-salcs networks in the region, and the need to replace system components as the systems begin to age. Also, the high number of wind systems in Inner Mongolia may affect sales in that province. In spite of the problems, there are significant opportunities. In three of the provinces, a significant number of households can afford to purchase small systems on a cash basis. This number could be expanded greatly if issues are resolved concerning the availability of credit and resistance to using credit. There appears to be a market for system expansion, after the initial purchase of small, affordable systems. The only exception is Gansu where households do not have the requisite income to purchase systems without some type of assistance from the government. Clearly, a different strategy would be necessary for the promotion of household photovoltaic systems in this province. Markets for photovoltaic products in the other provinces are likely to expand quickly, however, as households in the areas seem to appreciate the benefits of electricity from the systems, and many have the necessary income to pay for systems. 54 APPENDIX A: DESCRIPTIVE STATISTICS FROM THE NORTHWEST CHINA RuRAL ENERGY SURVEY Table A-1: Socioeconomic Indicators Gansu Inner Xinjiang Qinghai A ll four Mongolia provinces Age of head of household Mean 40 42 43 45 43 Valid N 715 723 721 719 2,878 Number of persons in the household Mean 5 4 6 5 5 Valid N 704 724 717 720 2865 Total monthly income Mean 195 1580 737 624 785 Valid N 720 724 722 720 2,886 Total value of livestock owned Mean 3,558 57,576 20,699 55,445 34,371 Valid N 718 724 719 719 2,880 Education of head of household (percent) Illiterate 17 6 10 51 21 Primary school 36 44 47 40 42 Junior high school 35 41 33 9 29 Senior high scbool 11 8 8 0 7 High vocational school 1 1 I 0 1 College and university education I 0 1 .. I Postgraduate education .. Valid N 719 722 722 720 2,883 Highest education of household memb (percent) Illitcrate 6 1 1 26 9 PTimuy school 17 14 17 38 22 Junior high school 42 46 40 24 38 Senior high school 28 27 24 9 22 High vocational school 4 6 10 1 5 College and university education 3 5 7 2 4 Post graduate education .. .. Vatid N 706 700 715 712 2,833 Occupation of head of household (prcent) Farmcr 90 34 57 8 47 Herdsnan .. 62 30 77 42 Mixed herding anddfrning 5 3 9 15 8 Local TVE worker I .. I .. 0.3 Outside TVE worker 2 .. .. .. 0.4 55 Local manager 0.4 0.3 0.4 .. 0.3 Retired 0.1 0.3 0.4 .. 0.2 Other 2 1 2 0.4 1 Valid N 720 722 721 720 2,883 Negligible. Note: TVE stands for township and village enterprise. Source: China Market Survey 1998. Table A-2: Households' Experience with Credit Gansu Inner Xinjiang Qinghai All four Mongolia provinces Credit expenence (lo of households) No (%) 68 76 59 89 73 Ycs (%) 32 24 41 11 28 Total (valid N) 637 641 682 596 2,556 Avcrage loan arnount (yuan) 1,173 3,242 4,802 2,449 3,201 Valid N 200 147 279 63 689 Average length of loan (rnnths) 16 12 I l 26 14 Valid N 202 146 270 64 682 Year of last loan taken (°/0 of households with loan) 1998 (%) 37 25 60 22 43 1997 (%) 42 63 26 50 41 1996 (%) 10 5 7 23 9 Before 1996(%) 11 7 7 5 8 Total (valid N) 201 147 280 64 692 Source of loan ('Io of households with loan) Bank (%) 23 17 35 7 25 Credit union (%) 73 58 52 47 59 Relatives(%) 3 18 8 21 10 Neighbor (%) .. 4 2 1 2 Others (%) .. 3 3 24 4 Total (valid N) 203 152 273 72 700 Purpose of loan (% of households with loan) To buy food (%) 8 3 10 19 9 To build, expand, or repair house 8 7 3 4 5 (%) Medical treatment or redicine (%) 18 13 10 10 13 Business(%) 55 54 67 57 60 To buy equipnent or appliance (%) 4 3 4 4 4 Family social function, rnarriage, 5 7 3 3 5 funeal, etc. (%) Others(%) 2 14 4 3 5 Total (valid N) 204 152 273 72 701 Negligible. Source: China Market Survey 1998. 56 Table A-3: Household Energy Use for Lighting Gansu Inner Xinjiang Qinghai All four Mongolia provinces Candle or butter No (%) 80 27 60 36 51 Yes (%) 20 73 40 64 49 Total (Valid N) 720 724 722 720 2,886 Kerosene, diesel, or gasoline No (%) 1 65 14 52 33 Yes (%) 99 35 86 49 67 Total (Valid N) 720 724 722 720 2886 Dry cel batteries No (%) 14 12 20 19 16 Yes (%) 87 88 81 81 84 Total (Valid N) 705 718 719 720 2,862 Car batteries, generator set, or conmunity grid No (%) 100 91 92 98 95 Yes (%) 0 9 8 2 5 Total (Valid N) 720 724 722 720 2,886 PV-Wind hybrid system No (%) 100 100 100 100 100 Yes(%) 0 0 0 0 Total (Valid N) 720 724 722 720 2,886 PV system No (%) 100 98 99 87 96 Yes (%/O) 0 2 1 13 4 Total (Valid N) 720 724 722 720 2,886 Wind system No (%) 100 43 97 100 85 Yes (%) 0 57 3 0 15 Total (Valid N) 720 724 722 720 2,886 Negligible. Source: China Market Survey 1998. Table A4: Households' Energy Expenditure Gansu Inner Xinjiang Qinghai Allfour .______________ _ Mongolia provinces Candle or butter 0.39 3.21 2.39 17.40 5.85 Total (valid N) 719 719 722 720 2,880 Kerosene, dieseL or gasoline 3.63 1.38 7.10 2.98 3.78 Total (validN) 717 713 721 719 2,870 Dry cell batteries 1.68 5.02 4.66 4.69 4.02 Total (valid N) 717 721 720 720 2,878 Car battcries, geneTtor set, or 0.07 3.41 1.82 0.51 1.46 comnunity grid Total (valid N) 720 724 722 720 2,886 Total spending 5.79 13.22 15.98 25.61 15.17 Total (validN) 714 707 719 719 2,859 As percent of income 5.96 2.62 3.91 4.65 4.29 Total (valid N) 714 707 719 719 2,859 Source: China Market Survey 1998. 57 Table A-5: Household Energy Attitude and Lighting Preferences Gansu Inner Xinjiang Qinghai Alifour Mongolia provinces Electricity is beneficial to production _ activities Strongly agree (%) 91 93 86 73 86 Agree (%) 5 6 12 23 11 No opinion(%) 4 1 3 4 3 Disagree (%) 0 0 0 0 0 Strongly disagree (%) 0 0 0 0 0 Total valid N 719 713 719 720 2,871 Because of good light, children study more at night Strongly agree (%) 92 87 85 42 76 Agree (%) 6 11 12 36 16 No opinion (%) 2 3 3 21 7 Disagree (%) 0 0 0 0 0 Strongly disagree (%) 0 0 0 0 0 Total (valid N) 719 714 719 720 2,872 Reading is easier with electric light compared to kerosene lamnps Strongly agree (%) 92 78 81 53 76 Agree (%) 6 19 16 32 18 No opinion(%) 1 3 3 15 5 Disagree (%) 0 0 0 0 0 Strongly disagree (%) 0 0 0 0 0 Total (valid N) 719 712 719 719 2,869 Source: China Market Survey 1998. 58 Table A-5: Household Energy Attitude and Lighting Preferences (continued) Gansu Inner Xinjiang Qinghai Allfour Mongolia _ provinces Myfamilyfeel very secure at night Strongly agree (%) 64 47 61 23 49 Agree (%) 19 37 28 39 31 No opinion (%) 11 14 7 30 16 Disagree (%) 6 2 4 7 5 Strongly disagrce(%) I I 0 Total (valid N) 718 713 718 719 2,868 Myfamil iLs extremely happy with the light we getfrom our currentfuel Strongly agrce (°o) 7 12 15 3 9 Agrm (%) 7 16 5 9 9 No opuunon (%/) 3 8 10 10 8 Dtsagree 29 36 22 41 32 Strongly disagrce (%) 55 29 47 37 42 Total (valid N) 718 715 718 718 2,869 Electncint Ls imporsanifor our local water supply Strongly agree (°%) 73 65 65 33 59 Agree (%,6) 19 23 19 36 25 No opmuon (%) 5 10 14 27 14 Disagre (%) 3 2 2 4 3 Strongly disagree(%) 0 0 0 0 Total (valid N) 719 713 718 718 2,868 Car baneries are good source of electricityfor lighting Strongly agree (%) 12 9 10 5 9 Agree (%) 21 14 14 13 15 No option (%) 19 19 35 47 30 Dtsagree (%) 44 49 29 29 38 Strongly disagree(%) 4 10 12 5 8 Total (valid N) 716 713 694 719 2,842 PVsystem Is good source of electnrcity for lighting Sarongly agree (%) 32 7 21 15 19 Agree (%) 32 19 16 27 23 No opuuon(%) 26 45 43 45 40 Disagree (%) 10 24 16 14 16 Strongly disagrce(%) 1 5 4 0 3 Total (valid N) 718 706 691 719 2,834 Lighting with kerosene or diesel can cause health problems Strongly agree(%) 42 27 48 14 33 Agr (%) 22 38 21 25 26 No opnion(%) 13 23 21 52 27 Disagree (%) 6 3 3 7 5 Surongly disagrec(%) 17 11 7 2 9 Total (valid N) 719 708 719 719 2,865 Negligible. Sore.: China Market Survey 1998. 59 Table A-5: Household Energy Attitude and Lighting Preferences (continued) Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces It is difficult for my family to get news and information Strongly agree (%) 70 35 48 13 41 Agree (%) 17 34 24 38 28 No opinion(%) 6 19 22 35 20 Disagree (%) 1 7 4 14 7 Strongly disagree (%) 5 6 3 1 4 Total (valid N) 715 713 719 718 2,865 Watching television would provide my family with great entertainment Strongly agree (%) 76 70 67 32 61 Agree (%) 20 26 16 34 24 No opinion (%) 3 4 10 33 12 Disagree (%) 1 0 7 2 3 Strongly disagree (%) 0 0 0 0 0 Total (valid N) 718 711 719 719 2,867 Television takes study time away from children Strongly agree (%) 26 29 7 7 17 Agree (%) 40 42 22 27 33 No opinion (%) 19 8 29 55 28 Disagree (%) 14 12 32 10 17 Strongly disagree(%) 1 9 10 1 5 Total (valid N) 719 709 718 719 2,865 I complete work in my house during the evening after it is dark outside Strongly agree (%) 37 32 34 29 33 Agree (%) 44 45 30 43 41 No opinion (%) 4 7 8 5 6 Disagree (%) 12 11 13 12 12 Strongly disagree (%) 3 5 15 11 9 Total (valid N) 712 717 660 719 2,808 We often receive friends, relatives, or neighbors visiting us in the evening after it is dark outside Strongly agree (%) 27 34 35 23 30 Agree (%) 59 44 45 52 50 No opinion(%) 3 3 6 5 4 Disagree (%) 7 14 10 16 12 Strongly disagree(%) 4 6 4 6 5 Total (valid N) 713 717 718 719 2,867 Today life is better than it was five years ago Strongly agree (%) 68 74 55 56 63 Agree (%) 30 21 33 38 30 No opnion (%) 1 4 6 4 4 Disagree (%) 1 1 4 2 2 Strongly disagree (%) 1 0 1 0 Total (valid N) 717 717 718 719 2,871 Source: China Market Survey 1998. 60 Table A-5: Household Energy Attitude and Lighting Preferences (continued) Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces I am optimistic that life will get better in thejfiture Strongly agree (%) 74 69 62 51 64 Agree (%) 17 24 17 31 22 No opinion (%) 10 6 21 17 13 Disagree (%) I 0 1 1 Strongly disagree (%) 0 0 Total (valid N) 718 717 718 719 2,872 I prefer to pay cash for my major purchase Strongly agree (%) 60 39 41 36 44 Agree (%) 13 40 26 43 31 No opinion (%) 18 13 16 13 15 Disagree (%) 8 7 13 7 9 Strongly disagree (%) 2 1 3 0 2 Total (valid N) 717 714 718 719 2,868 Light at night is useful to keep the herd together Strongly agree (%) 49 39 46 26 40 Agree (%) 17 28 20 29 24 No opinion (%) 28 18 22 34 25 Disagree (%) 6 11 10 8 9 Strongly disagree (%) 1 5 3 3 3 Total (valid N) 630 711 713 717 2,771 Negligible. Source: China Market Survey 1998. 61 Table A-6: Households that Have Heard about or Have Seen 20-Watt Photovoltaic Systems (percent) Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces Have heard about or have seen 20-watt PV system Never beard of it(%) 45 39 34 31 37 Have heard about it from newspaper 21 5 15 1 1 1 or uagazine (%) Have heard about it from radio, 3 5 5 6 5 television (%) Have hcard about it from neighbors 24 32 36 41 33 or fnends (%) Have sen it in store (%) 6 2 2 Have secn a system istalled at 7 12 10 18 12 friend's, govcrnmcnt's or neighbor's (%) Have beard or secn it from other I 0 0 0 sources (%) Total valid N 704 689 596 616 2.605 .. Negligible Source: China Market Survey 1998. Table A-7: Households That Are Interested in Buying 20-Watt Photovoltaic Systems (percent) Gansu Inner Xinjiang Qinghai Allfour l___l___|_ Mongolia provinces Household interested in buying a 20- watt PVsystem with cash, about Y 1.700 No (%) 34 71 47 40 48 Yes, but no money(°) 42 16 38 41 34 Yes (%) 24 14 16 19 18 Total (valid N) 699 699 588 554 2,540 Household interested in buying a 20- wan PV system with cash down payment and one year credit No (%) 48 80 55 53 60 Yes, but omoneyo () 46 18 38 42 35 Yes (%) 6 2 7 4 5 Total (valid N) 492 554 471 415 1,932 Source: Chua Market Survey 1998. 62 Table A-8: Reason for Not Being Interested in Purchasing 20-Watt Photovoltaic Systems Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces Don 't know about the system No reason (%) 66 71 62 53 63 Main reason (%) 19 14 30 27 22 Secondary reason(%) 15 15 8 21 15 Total (valid N) 378 430 369 372 1,549 System cost too much No reason (%) 27 54 17 36 34 Main reason (%) 58 32 69 56 53 Secondary reason(%) 15 14 14 9 13 Total (valid N) 429 449 371 374 1,623 No convenient location to buy No reason (%) 67 71 69 60 67 Main reason (%) 12 5 8 19 11 Secondary reason (%) 21 24 23 20 22 Total (valid N) 347 424 329 358 1,458 Can 't get credit to buy system No reason (%) 57 72 38 53 56 Main reason (%) 18 8 41 29 23 Secondary reason (%) 25 20 21 18 21 Total (valid N) 352 429 337 353 1,471 Worry about quality, services, not easy to operate, etc. No reason (%) 72 59 34 48 54 Main reason (%) 10 23 21 30 21 Secondary reason(%) 18 18 45 22 25 Total (valid N) 377 430 351 336 1,494 Have had electric supply, or small wind, or small electric generator set No reason (%) 91 59 79 93 78 Main reason (%) 6 26 12 2 13 Secondary rcason (%) 4 16 9 6 9 Total (valid N) 340 504 343 335 1,522 Will get grid connection or will buy small electric generator set No reason (%) 82 76 71 86 78 Man reason (%) 14 17 23 8 16 Secondary reason(%) 4 7 6 6 6 Total (valid N) 352 430 329 333 1,444 Capacity of the system is not enoughfor thefamily to use No reason (%) 46 53 85 72 62 Main reason (%) 52 42 8 17 32 Secondary rason (%) 2 5 7 12 6 Total (valid N) 407 479 333 339 1,558 Source China Market Survey 1998. 63 Table A-9: Households That Have Heard about or Have Seen 50-Watt Photovoltaic Systems (percent) Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces Have heard about or have seen 50-watt PV system Never heard of it(%) 44 46 38 39 42 Have heard about it from newspaper or magazine (%) 27 7 14 7 15 Have heard about it from radio, 1 4 4 6 3 television (%) Have heard about it from neighbors or friends (%) 24 36 27 40 31 Havc seen it in store (%) 0 2 0 1 1 Have seen a system installed at friend's, govemment's or neighbor's 4 4 18 8 7 (%) Have heard or seen it from other 0 0 sources (%) Total valid N 502 343 245 348 1,438 Negligible. Source: China Market Survey 1998. Table A-10: Households That Are Interested in Buying 50-Watt Photovoltaic Systems (percent) Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces Household interested in buying a 5S- Watt PVsystem with cash, about Y 3,800 No (%) 33 64 31 38 42 Yes, but no money(%) 43 10 35 37 32 Yes (%) 24 26 34 25 26 Total (valid N) 495 347 233 329 1,404 Household interested in buying a 50- Wan PV system with cash down payment and one year credit No (%) 38 92 44 48 54 Yes, but no money (%) 58 4 48 47 41 Yes (%) 4 5 8 5 5 Total (valid N) 340 224 147 229 940 Source: China Market Survey 1998. 64 Table A-11: Reason for Not Being Interested in Purchasing 50-Watt Photovoltaic Systems Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces Don't know about the system No reason (%) 67 82 49 66 68 Main reason (%) 25 4 44 21 21 Secondary reason (%) 7 14 7 14 11 Total (valid N) 232 144 69 148 593 System cosr too much No reason (°/O) 31 58 11 24 34 Main reason (%) 59 27 74 67 55 Secondary reason(%) 10 16 15 9 12 Total (valid N) 295 181 86 152 714 No convenient location to buy No reason (%) 70 80 47 66 69 Main reason (%) 19 1 27 11 13 Secondary reason(%) 10 18 27 23 17 Total (valid N) 201 141 49 142 533 Can 't get credit to buy system No reason (%) 57 93 26 61 64 Main reason (%) 15 3 54 24 18 Secondary reason (%) 28 4 19 15 17 Total (valid N) 206 141 57 141 545 Worry about quality, services, not easy to operate, etc. No reason (%) 68 59 26 48 56 Main reason (%) 14 8 40 33 20 Secondary reason (%) 18 33 34 19 24 Total (valid N) 228 141 62 144 575 Has had electric supply, or small wind, or small electric generator set. No reason (%) 91 45 51 94 74 Main reason (%) 9 20 4 2 10 Secondary reason(%) 1 35 45 4 16 Total (valid N) 192 168 49 151 560 Will get grid connection or will buy small electric generator set No reason (%) 85 89 44 97 86 Main reason (%) 15 8 32 I I Secondary reason (%) 1 3 24 3 4 Total (valid N) 199 145 50 149 543 Capacity of the system is not enoughfor thefamily to use No reason (%) 32 6 46 79 37 Main rcason (%) 68 93 40 17 61 Secondary reason (%) 0 1 14 3 2 Total (valid N) 255 172 50 149 626 Negligible. Source: China Market Survey 1998- 65 Table A-12: Households That Have Heard about or Have Seen Small Hybrid Photovoltaic-Wind Systems (percent) Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces Have heard about or have seen small hybrid PV-wind system Never heard of it (%) 71 61 65 73 68 Have heard about it from newspaper 16 5 9 2 8 or magazine (%) Have heard about it from radio, 2 3 3 5 3 television (%) Have heard about it from neighbors 10 23 21 18 18 or friends (%) Have seen it in store (%) 0 2 0 l I Have seen a system installed at 2 6 3 1 3 friend's, government's or neighbor's (%) Have heard or seen it from other sources (%) Total valid N 673 667 529 657 2,526 Household interested in buying hybrid PV-wind system with cash No (%) 46 36 65 57 50 Yes, but no money (%) 35 31 27 25 30 Yes (%) 19 33 8 18 20 Total (valid N) 667 655 518 607 2,447 Household interested in buying a hybrid PV-wind system with cash down payment and credit No (%) 55 51 67 64 59 Yes, but no money (%) 42 44 29 28 36 Yes (%) 3 5 5 8 5 Total (valid N) 531 421 468 493 1,913 Negligible. Source. China Market Survey 1998. 66 Table A-13: Reason for Not Being Interested in Purchasing Hybrid Photovoltaic- Wind Systems Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces Don't know about the system No reason (%) 63 64 42 36 51 Main reason (%) 22 24 46 48 35 Secondary reason (%) 15 12 13 16 14 Total (valid N) 450 367 385 418 1,620 System cost too much No reason (%) 34 49 19 38 35 Main reason (%) 58 39 63 53 54 Secondary rcason (%) 8 12 18 9 11 Total (valid N) 489 363 364 400 1,616 No convenient location to buy No reason (%) 75 70 71 66 71 Main reason (%) 10 4 7 18 10 Secondary reason (%) 15 27 23 17 20 Total (valid N) 418 354 320 392 1,484 Can't get credit to buy system No reason (%) 65 70 49 61 62 Main reason (%) 16 6 30 28 20 Secondary reason (%) 19 24 21 12 19 Total (valid N) 414 360 326 391 1,491 Worry about quality, services, not easy to operate, etc. No reason (%) 73 52 47 51 57 Main reason (%) 9 32 22 28 22 Secondary reason (%) 18 16 31 21 21 Total (valid N) 445 360 333 389 1,527 Have had electric supply, or small wind, or small electric generator set No reason (%) 90 66 84 93 83 Main reason (%) 4 20 11 1 9 Secondary reason (%) 5 14 6 7 8 Total (Valid N) 408 389 335 387 1,519 Will get grid connection or will buy small electric generator set No reason (%) 85 76 77 87 82 Main reason (%) 10 17 18 7 12 Secondary reason(%) 5 7 5 6 6 Total (valid N) 409 354 323 390 1,476 Capacity of the system is not enough for thefamily to use No reason (%) 78 94 87 79 84 Main eason (%) 16 1 4 7 7 Secondary rason(%) 6 5 9 14 9 Total (valid N) 408 350 325 396 1,479 Source: China Market Survey 1998. 67 Table A-14: Photovoltaic Systems Owned by Households Gansu Inner Xinjiang Qinghai Allfour _Mongolia provinces Number of PVsystems owned None(%) 100 98 99 87 96 One (%) 0.1 2 0.6 13 4 Total (valid N) 720 724 722 720 2,886 Source: China Market Survey 1998. Table A-15: Attitude toward Photovoltaic Systems among System Owners Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces What do you think about the price of PV system? Very expensive(%) 7 .. .. 8 6 Expensive (%) 40 14 75 64 58 Right price(%) 53 71 19 24 31 Cheap (%) .. 14 6 3 4 Total (valid N) 15 14 16 95 140 Electricity generatedfrom the PV system is: Not enough for household need (%) 38 67 13 39 38 Just enough for household need (%) 25 25 67 48 46 More than enough for household 38 8 20 13 16 need (%) Total (valid N) 16 12 15 95 138 Note: Because of a small number of owners of photovoltaic systems in Gansu and Xinjiang selected through the random sampling procedure, additional households that owned photovoltaic systems were purposively selected to develop a profile of photovoltaic system owners. Therefore, statistical inferences cannot be drawn for Gansu and Xinjiang. .. Neghgible. Source: China Market Survey 1998. 68 Table A-16: Reasons for Photovoltaic System Owners to Obtain Systems Gansu Inner Xinjiang Qinghai All four Mongolia provinces For children education No reason (%) 15 41 31 Main reason (%/6) 46 18 33 17 22 Secondary reason (%) 39 82 67 41 47 Total (valid N) 13 11 12 87 123 For better lighting No reason (%) 3 2 Main reason (%) 100 100 93 89 92 Secondary reason (%) 7 8 6 Total (valid N) 15 12 15 93 135 To watch television No reason (%) 20 18 79 62 Main reason (%) 80 27 6 14 Secondary reason (%) 100 55 15 25 Total (vald N) 10 10 11 86 117 PV system is cheaper than kerosene & otherfuels No reason(%) 46 67 40 24 31 Main reason(%) 9 .. 40 34 29 Secondary reason (%) 46 33 20 42 40 Total (valid N) 11 9 10 86 116 Note: Because of a small number of owners of photovoltaic systems in Gansu and Xinjiang selected through the random sampling procedure, additional households that owned photovoltaic systems were purposively selected to develop a profile of photovoltaic system owners. Therefore, statistical inferences cannot be drawn for Gansu and Xinjiang. .. Negligible. Source: China Market Survey 1998. 69 Table A-17: Perceived Benefits of Photovoltaic Systems among System Owners Greatest benefits ofPVsystem to my Gansu Inner Xinjiang Qinghai All,four family is: Mongolia provinces Access to news and informnationfrom television and radio No reason (%) 10 8 43 32 Main reason (%) 60 17 25 26 28 Secondary reason (%) 30 83 67 31 40 Total (valid N) 10 12 12 87 121 Provide lightingfor my family No reason (%) 3 2 Main reason (%) 100 92 100 81 86 Secondary reason (%) 8 16 12 Total (vald N) 16 12 16 95 139 Gerting entertainmentfrom television, radio, and tape No reason (%) .. 30 21 Main reason (%) 77 50 24 30 Secondary reason (%) 23 100 50 46 49 Total (valid N) 13 12 14 89 128 Enablingfamily members to read, write, and study in the evening longer than before No reason (%) .. 9 25 18 Main reason (%) 50 50 46 30 35 Secondary reason (%) 50 50 46 46 46 Total (valid N) 14 12 11 88 125 Enabling us to do more work No reason (%) 43 27 31 17 22 Main reason (%) 36 18 15 55 45 Secondary reason (%) 21 55 54 28 33 Total (valid N) 14 11 13 88 126 Note: Because of a small number of owners of photovoltaic systems in Gansu and Xinjiang selected through the random sampling procedure, additional households that owned photovoltaic systems were purposively selected to develop a profile of photovoltaic system owners. Therefore, statistical inferences cannot be drawn for Gansu and Xinjiang. .. Negligible. Source: China Market Survey 1998. 70 Table A-18: Attitude of Photovoltaic System Owners toward System Performance Gansu Inner Xinjiang Qinghai All four Mongolia provinces Satisfied with the performance of the system High (%) 69 8 44 10 20 Rather High(%) .. 25 25 21 19 Fair (%) 19 67 31 63 55 Rather low (%) 6 6 5 Low (%) 6 .. .I 1 Total valid N 16 12 16 95 139 Would recommend PV system to relatives andfriends Yes(%) 6 38 13 17 16 No (%) 94 63 88 83 84 Total (valid N) 16 8 16 96 136 Note: Because of a small number of owners of photovoltaic systems in Gansu and Xinjiang selected through the random sarnpling procedure, additional households that owned photovoltaic systems were purposively selected to develop a profile of photovoltaic system owners. Therefore, statistical inferences cannot be drawn for Gansu and Xinjiang. .. Negligible. Source: China Market Survey 1998. Table A-19: Changes in Lifestyles of Photovoltaic System Owners Gansu Inner Xinjiang Qinghai Allfour Mongolia provinces After installing PV systems, family stays up later than before Go to bed at the same time as before 6 27 31 19 20 Stay up later(%) 94 73 69 81 80 Total valid n 16 11 16 95 138 Note: Because of a smnall number of owners of photovoltaic systems in Gansu and Xinjiang selected through the random sampling procedure, additional households that owned photovoltaic systems were purposively selected to develop a profile of photovoltaic system owners. Therefore, statistical inferences cannot be drawn for Ganisu and Xinjiang. Source: China Market Survey 1998. 71 APPENDIX B: DATA AND SAMPLING METHODS The questionnaire and survey methodologies were designed to assess the potential market and to determine the market size of photovoltaic home systems in the Gansu, Inner Mongolia, Qinghai, and Xinjiang Provinces. To achieve these objectives, the survey collected the following information for rural households: * socioeconomic profile including means of income and wealth; * current energy usage and expenditure for lighting and batteries, including dry cell, motorcycle, and car batteries; * household experience with banking, credit unions, or obtaining credit; * attitudes and preferences toward energy services; * attitudes and preferences with respect to photovoltaic home systems; and * knowledge of and access to the photovoltaic market. As described in the main report, photovoltaic home systems have already been marketed in these four provinces, and many households have already purchased systems. Therefore, through the random sampling process, it was expected that some photovoltaic system homeowners would be selected as part of the random sample. Questions on the type and cost of photovoltaic systems that were owned, methods of purchase, performance of the systems, quality of service, and uses and perceived benefits were included in the questionnaire. These questions were intended to determine the characteristics and profiles of households that have purchased and used photovoltaic systems. Since the number of households with photovoltaic systems selected as part of the random sample was small, it was decided to purposely select households with photovoltaic systems as a supplemental sample. These owners of photovoltaic systems were purposively selected for interview. TARGET POPULATION The survey was conducted in four remote provinces in China-Gansu, Inner Mongolia, Qinghai, and Xinjiang. The target population (population frwne) within these provinces for the photovoltaic market survey consisted of all rural households living in villages with no access to grid electricity in the counties with an unelectrified rate of more than 15 percent.'3 The main reason that the market survey concentrated on counties with an unelectrified rate of more than 15 percent was that the villages without electricity in such counties have less chance of gaining access to electricity any time soon. Therefore, 3 The 15 percent cutoff point was arbitrarily chosen based on the average 17 percent unelectified rate in the combined four provinces. 73 counties that are closer to complete electrification appear not to have good market potential for photovoltaic systems. Consumers in these counties may opt to wait for grid electricity rather than buy a photovoltaic system. Furthermore, the market size of photovoltaic systems in counties with an unelectrified rate of more than 15 percent is small because it consists of fewer unelectrified households. Of all the four selected provinces, the total number of rural households living in unelectrified villages in the counties with an unelectrified rate of more than 15 percent is estimated to be 1.37 mnillion households. Tables B-I and B-2 provide a breakdown of the total number of rural households and unelectrified rural households in counties with unelectrified rates of less than and more than 15 percent. Table B-1: Rural Households and Unelectrifled Households Gansu Inner Xinjiang Qinghai Total Mongolia Total number of rural households 4,169,218 2,753,990 2.248,512 493,414 9,665,134 Number of rural households In County with < 15% 2.301,491 1,963,192 504,265 318,916 5,087,864 unclectnfied rate County with> 15% 1,867,727 790,798 1,744,247 174,498 4,577,270 unelectrfied rate Total number of unelectnfied 693.542 383,367 459,956 104,052 1,640.917 households Number of unelectnfied households in: Countywith< 15% 121,637 87,011 43,735 19,348 271,731 unelectrified rate County with > 15% 571,905 296,356 416,221 84,704 1,369,186 unelectnfied rate Source: CRED 1998. Table B2: Targeted Households in Villages without Grid Electricity in Four Selected Provinces Gansu Inner Xinjiang Qinghai Ailfour Mongolia provinces Total nwnber of rural households 1,867,727 790,798 1,744,247 1,74,498 4,577,270 Number of unelectnfied rural households M.: 8 stuveyed counties 179,988 77,850 42,096 35,121 334,477 (Unelectnfcd rate) (30.92%) (34.47%) (23.04%) (46.51%) (31.43%) Othercountes 391,917 218,506 374,125 49.583 1,034,709 (Unelectrified Tate) (30.48%) (38.67%) (23.96%) (50.09%) (29.45%) Total nunber of unelectrified rural 571,905 296,356 416,221 84,704 1,369,186 households (Unetetrified rate) (30.62%) (37.48%) (23.86%) (48.54%) (29.91%) Note: This tables nclude all counte vith an uneectrined rate of mnre than 15 percenL Source CRED 1998. 74 SAMPLE SIZE AND DESIGN The photovoltaic market survey in the rural areas in Gansu, Inner Mongolia, Qinghai, and Xinjiang Provinces was conducted using a multistage random sampling design. In the survey, questionnaires were used to gauge the market potential for photovoltaic home systems among rural households that have no access to grid electricity. The survey was conducted between August and September 1998. Because of some logistical problems, however, the field survey (of 90 households) in Abagaqi County, Inner Mongolia, was conducted in April 1999. A total of 2,886 households were interviewed. Table B-3: Households in Villages without Grid Electricity in Sampled Counties and All Other Counties Gansu Inner Mongolia County sampled Number of County sampled Number of households households Mznxian 44,263 Shangdu 19,600 Ningxian 32,300 Liangcheng 16,000 Huanxian 25,400 Sizhiwang 12,900 Zhenyuan 23,200 Xiwuzhumuqing 9,850 Xiihe 19,890 Etuokeqian 7,400 Gulang 13955 Dongwuzhumuqing 5,500 Heshui 12,600 Xingbaerhuzhuo 4,000 Zhouqu 8,380 Abaga 2,600 Total (in sampled counties) 179,988 Total (in sampled counties) 77,850 Other counties 391,917 Other counties 218,506 Total tmelectrified 571,905 Total tmelectrified households 296,356 households (all counties (all counties >15% >15% unelectrified rate) unelectrified rate) Source: China Market Survey 1998. 75 Qinghai Xinjiang County sampled Number of County sampled Number of households households Nangqian 8,319 Jiashi 11,303 Gonghe 6,488 Akesu City 8,358 Chengduo 4,667 Habahe 5,932 Menyuan 3,493 Cabucaer 4,740 Zhiduo 3,151 Changji City 3,881 Dulan 2,906 Bole City 3,318 Maqin 2,598 Keping 2,544 Dari 3,499 Yuring 2,020 Total (in samnpled county) 35,121 Total (in sampled counties) 42,096 Other counties 49,583 Other counties 374,125 Total unelectrified 84,704 Total unelectrified households 416,221 households (all counties (all counties >15% >15% unelectrified rate) unelectrified rate) Note: This table includes counties with an unelectrified rate of more than 15 percent. Source: CRED 1998. A three-stage sample selection process was employed for the market survey. The first stage of the sample involved taking a stratified random sampling selection of 8 counties with an unelectrified rate of more than 15 percent from each of the four provinces. The eight counties of each province were systematically selected from each stratum of counties that was compiled in order from the highest to the lowest population in unelectrified rural areas. Only counties with an unelectrified rate of more than 15 percent were included in the population frame. The cutoff point at the unelectrified rate of 15 percent was arbitrarily chosen to establish a pool of counties with many households without electricity. As a result, the total 48 counties that were sampled in the first stage have more than 15 percent unelectrified rate. Tables B-3 and B4 list the counties that were sampled, including the total number of unelectrified households in the county and the province, as well as the number of counties, villages, and unelectrified households that were sampled. The second stage of the sampling process involved selecting villages at random from the sampled county in the first stage. A list of all unelectrified villages in each selected county was compiled and used as the sampling frame for selecting the villages. Six villages were randomly selected from each selected county. In this stage, 192 unelectrified villages from all four provinces (or 48 unelectrified villages for each province) were selected. Because of the remoteness and harshness of terrain in some counties, the survey team was given some flexibility in selecting villages. For example, in some cases a village in the sample could not be located, had moved to the new location, or was not accessible by truck, boat, horse, yak, or on foot in a reasonable amount of 76 time. In such a case, the survey team was allowed to substitute that village with another similar village in the same township.'4 In the final stage of the sampling procedure, 15 households were randomly selected using the random walk technique."5 The main reason for using this technique was that not all villages maintain lists of households, and in many instances lists of households are incomplete or obsolete. Table B-4: Sample Selection for Photovoltaic Market Survey in Four Selected Provinces in China Provinces Sampleframe: Sample selection Counties with Counties Villages (without Households Less than 85 grid electricity) percent of households without grid electricity Gansu 27 8 48 720 inner Mongolia 31 8 48 724 Qmghai 22 8 48 722 Xinjiang 69 8 48 720 Total 149 32 192 2.886 Source: CRED 1998. PURPOSIVE SELECTION OF PHOTOVOLTAIC HOUSEHOLDS Because photovoltaic systems have already been marketed in these four selected provinces and a few rural households have already been using photovoltaic system, the number of photovoltaic households selected at random depended on the actual number of photovoltaic households in the selected counties and villages. Therefore, when the number of households with photovoltaic systems selected at random was high enough (at least 15 households for each province), the purposive selection of photovoltaic home was not necessary. Through the random sampling process, 116 household photovoltaic system owners were selected at random for interview (see Table B4). When the number of households with photovoltaic systems selected at random was not high enough (less than 15 households for each province), however, the purposive selection of homes with photovoltaic systems in the province was necessary. Twenty-seven photovoltaic household owners were purposively selected for interview. The main objective of 14 In an extreme circ s, wherm ther was still no villagc available in the township to substitute, similar villages in a nearby or adjacent township was substituted. Is The mnom wallt tccique for selecing sanple houscholds does not require a list of households. Rather, it s based on the geographical distnbtion of households in a conuminty or village. The size of the vilage is generally known. The ratio of the numnber of households is calculated by dividing the predetermined sanple sme by the total nunber of households. For exanple, m a village of 75 with a smple size of 15, the ratio would be 6. The swvey enumerator would first select one household at random within the conmwity, and then walk through the entire village taang eveiy sixth household encountered. The result is a random selecfion of households from the connunity. 77 purposive selection was to ensure that there were at least 15 households with photovoltaic systems for each province in order to obtain the descriptive characteristics of such households in the provinces, even though they did not show up in the random sample. Although the purposive selection does not permit us to make any statistical interpretation, it shed some light on some salient characteristics and profiles of owners and users of photovoltaic systems. Table B-5 provides details on the number of sample and purposive photovoltaic home by province. Table B-5: Sample Size Broken Down by Random and Purposive Selection of Households Random selection ofhouseholds Purposive selection of Provinces with PV With other All sampled Households with svstems energy PVsvstems Gansu 1 719 720 15 Inner Mongolia 15 707 724 Qinghai 96 626 722 Xinjiang 4 716 720 12 Total 116 2,768 2,886 27 * Field interview was conducted in Januay 1999. Negligible. Source: CRED 1998. QUESTIONNAIRE AND CONDUCT OF THE SURVEY The questionnaire was developed jointly by the World Bank and Center for Renewable Energy Development (CRED) in China. After initial drafts, adjustments and additions were made to the sections on income and expenditure, energy consumption, expenditure for lighting, and awareness and willingness to purchase renewable energy devices. The questionnaire was pre-tested during the summer of 1998. A section concerning the use of hybrid systems was also added to the questionnaire. The final questionnaire was revised based on lessons learned from the pretests conducted in Qinghai Province in July 1998 and a focus group study conducted by CRED staff in Inner Mongolia in May 1998. Revision of the questionnaire also benefited directly from the input of the nrual survey teams in Qinghai Province and the head of the rural survey team from the seven sampled counties in Qinghai Province, who participated in the questionnaire training. The pretest was conducted in two selected villages in Zeku County and Menyeun County, Qinghai Province. Based on the field implementation arranged by CRED and the Rural Electric Power Bureau, the field surveys in each county were conducted by the county nrual survey team. A total of 32 survey teams at the county level were organized to implement the field survey, and each team conducted approximately 90 interviews in the sampled unelectrified villages. Four coordinating offices at the provincial level were selected to help organize survey teams at the county level, as well as to provide technical and logistical support to the survey teams. In Qinghai, the Statistical Office of the province 78 was responsible for helping survey teams of each county in the province to organize the field survey teams, provide backup support (including technical logistical aspects of the survey), and deliver the results of the survey. DATA PROCESSING Completed survey forms were sent to CRED in Beijing, and a subcontractor in Beijing performed the data entry. Once the data entry was completed, CRED staff took two additional steps for checking the accuracy of data entry. These additional steps included randomly reviewing the complete survey form and checking all records and variables in the data set against the original survey form.'6 The final data editing and preparation for data analysis were performed and completed in Washington, D.C. DATA WEIGHTING PROCEDURES As indicated, the sampling method was not based on a self-weighting procedure. In reality, however, the number of counties in each province, the number of villages in each county, and the number of households in the selected village were not the same. As a result of an unequal number of elements in the strata and clusters in each samnpling stage, the data were weighted in accordance with the actual population in each sampling stage. The weighting procedures consisted of three steps. The first step involved the calculation of a weighting adjustment for counties to correct for their assumption of selecting 15 households per village and 6 villages per county. The second step was to calculate the weighting adjustment for provinces to correct for the assumption of collecting 90 households per county and 8 counties per province. Tables B-1 and B-2 show the calculation procedures for the county and provincial weight adjustmnents. The final step involves a calculation to combine the two weights and adjust for the total population covered in the sampling plan (see Table B-3). Table B-6: Weight Adjustment for County Ratio in reality Assumed ratio First weight Total number of households in the sampled villages divided 15/90 Assumed ratio/ by total number of households in all 6 sampled villages of ratio in reality the county Source: China Market Survey 1998. " Approximately 50 percent of survey forms were randomly selected for review. 79 Table B-7: Weight Adjustment for Province Ratio in reality Assumed ratio Second weight Total number of households in all 6 sampled 90/720 Assumed ratio/ratio in villages of the county divided by the total number reality of households in all 8 counties of the provinces (48 villages in the province) * The denominator for Inner Mongolia is 724, and the denominator for Xinjiang is 722 (that is, the exact number of households sampled). Source: China Market Survey 1998. Table B-8: Final Weight Adjustment Procedure Province Calculation procedures Gansu (First Weight x Second weight) x (571,905/720) Inner Mongolia (First Weight x Second weight) x 296,356/724) Xinjiang (First Weight x Second weight) x 416,221/722) Qinghai (First Weight x Second weight) x 84,704/720) Source: China Market Survey 1998. ESTIMATION OF STANDARD ERRORs AND CONFIDENCE INTERVAL As indicated, the data used in this report were based on a complex sample design. Therefore, variance and standard errors must be computed in accordance with the complexity of the sample designs. In this report, the calculation of standard errors of the selected mean are primarily based on separating sources of variation, and then calculating the associated variance of the data collected at different stages of sampling. This has been completed for such variables as the average household monthly income, total value of assets owned, and the average monthly expenditure for lighting fuels and other energy. Relying on "analysis of variance" of the mean techniques, the total components of variance are comprised of (a) variation between counties, (b) variation between villages within counties, and (c) variation within villages. For example, the estimated variance and standard errors of the estimated household monthly income for Gansu Province is demonstrated in Tables B-9 and B1-1O. 7 Table B-9: Estimated Variance and Standard Errors of Household Monthly Income in Gansu Sources of variations Sum of squares Degrees of Mean square Standard freedom error of mean Between cotnties 8,766,750 (8 - 1) = 7 125,239 422 Betweenviflageswitin 15,248,244 8(6- 1)-40 381,206 97 counties Within villages 10,058,479 48(15 - 1) -672 14,967 4.7 Total 25,306723 (720- 1)-719 35,197 69 Source. China Market Survey 1998. 17 Leslie, Kish S5gy Sampling (John Wicy & Sons, Inc., New York, 1965), p. 173. 80 As a consequence, the confidence interval for household monthly income in Gansu can be calculated as follows: Average monthly income +/- (t.a2=.05, 719*SE) 208.46 +/- (1.96 * 6.9966) = 208.46 +/- 13.71 Based on the analysis of the components of variance described above, Table B-10 provides a summary of standard errors and confidence intervals for average household monthly income, the total value of assets owned, and the total monthly expenditure for lighting fuels and other non-cooking energy by province. Table B-O10: Summary of Standard Error and Confidence Interval Monthly income Standard error (SE) Confidence (Yuan) interval (I,/' - 0,719 'SE) Gansu 208.46 6.9966 +/- 13.71 Inner Mongolia 1,372.39 70.1568 +/-137.51 Xinjiang 712.73 119.8234 +/- 234.85 Qinghai 597.66 17.1169 +/- 33.5491 Total value of assets Standard error (SE) Confidence owned interval (t &05. 719 *3E) Gansu 5,311.80 172.2439 +/- 337.60 InnerMongolia 51,910.12 2611.5877 +/-5,118.71 Xinjiang 18,505.64 2290.1155 +/-4,488.63 Qinghai 53,210.77 1680.1724 +/- 3,293.1379 Expendintre of Standard error (SE) Confidence lightingfuels interval (5, 2-7 1.,9'5E) Gansu 5.66 0.1278 +/- 0.25 Inner Mongolia 14.71 0.8631 +/- 1.69 Xinjiang 14.65 0.5517 +/- 1.08 Qinghai 31.79 1.5767 +/- 3.09 Source: China Market Survey 1998. 81 APPENDIX C: QUESTIONNAIRE Household ID no.: LJ | | Household Survey Form CHINA Energy Utilization Questionnaire Form Non-grid Household Survey Date of interview: Tine start: Timne end: Interviewer's name: Supervtisor's narme: Section 1: Household Location Identiflcation Coding number 1.1 Province 1Q.1 1.2 County: | | Ql.2 1.3 Town: [ Ql.3 1.4 Township: F Ql. 1.5 Village: | Q1.5 1.6 Type ofvillage [Z|]Q1.6 Code: [I1 = Faming; [2] = Herding; [3] = Mixed herding and farming; [4] Other; specify: Note. Coding number rust be assigned to county, town, township, and village. Coding: [-71 = Do not apply (-81 = No answer [-9] - Missing value 83 Section 2. Socioeconomic Information Varia- ble name Name of respondent: 2.1a Sex of the respondent Code: [II= Male [2] = Fernale Q2.1a 2.1 b Age of respondent Q2.1b 2. Ic Educational level of respondent: Q2.1c Code: [0] - Illiterate [II - Primary school [21 - Junior high school [3) = Senior high school [41 = lhigb vocational school [51 = Colage and university education 16] - Postgraduate education 2.Id Respondent's relationship to head of household Q2.1d Code: [11 = Head of the household [2] = Head of household's wife or husband [3] = Daughter [4] = Son [5] = Daughter-in-law [61 = Son-in-law [71 = Other, specify: 2.2 Sex of the head of household Code: [Il=Male Q2.2 [21 = Female 2.3 Age of the head of household: years old Q2.3 2.4 Age of spouse of head of household years old Q2.4 2.5 Occupation of the head of household Q2.5 Code; [P - Farmer [21 = Herdsman [3] - Mixed herding and farmiing [4] = Local TVE workers [51 = Outside TVE workcrs [61 - Local manager [7] = Retired [81 - Other 84 Varia- ble name 2.6 Educational level of head of household Q2.6 Code: [0] = Illiterate [1] = Primary school [2] = Junior high school [3] = Senior high school [4] = High vocational school [5] = Collage and university education [6] = Postgraduate education 2.7 How nany persons live in your household for most of the year (that is, more than 6 months in a year)? (Fill in according to age.) 2.7a Less than 6 years Q2.7a 2.7b 7-18 years Q2.7b 2.7c 19-60 years Q2.7c 2.7d 61 years and over _ Q2.7d 2.7e Total _____ Q2.7e 2.8 What is the highest educational level of immediate adult family member of the household? Q2.8 (regardless of where he or she lives) Code: [0] = Illiterate [I] = Primary school [2] = Junior high school [3] = Senior high school [4] = High vocational school [51 = Collage and university education [6] = Postgraduate education 2.9 How many persons in your household earn income? (Include all types of income earned.) Q2.9 Inrormation on Responding Household's Dwelling Unit 2.10 How many dwelling units does your household have? units Q2.10 2.11 What is the size of your permanent home (in square meters)? square meters Q2.11 2.12 How many Tibetan tents does your household have? tents Q2.12 (Enter "O "for do not have any.) 2.13 How many Mongolian tents does your household have? tents Q2.13 (Enter "O "for do not have any.) 85 Section 3. Income from Agricultural Activities, Variable Livestock Holdings, and Livestock name 3.1 Total under cultivation (Mu) (Include all land used to cultivate.) Q3.1 3.2 Total land owned (Mu) Q3.2 Total land Type of Crops Planted Last Year used for Income cultivation from (Mu) sales of crops 3.3 Grain__ Q3.3a Q3.3b 3.4 Oil bearing Q3.4a Q3.4b 3.5 Economic or commercial crops L Q3.5a Q3.5b 3.6 _ _ _ _ _ (Enter name of the crop.) Q3.6a Q3.6b 3.7 naeofte_rp.__Q.a_37 (Enter name of the crop.) Q3.7a Q3.7b 3.8__ _ _ _ _ _ _ _ _ (Ente name of the crop.) Q3.8a Q3.8b Total Expenditure for Agricultural Activities (Include all expenditures, such asforferleizers, herbicides, pesticides, land rental, water pumping fees, or labor.) 3.9 Land rcntal fees Q3.9 3.10 Fertilizers, herbicides, pesticides Q3.10 3.11 Seeding Q3.11 3.12 Irrigation or water user fees Q3.12 3.13 Labor Q3.13 3.14 Other expcnditurcs; specify_ Q3.14 86 Total Number of Livestock and Domestic Fowls Currently Owned by the Family, Number Sold Last Year, Sale Price per Animal, and Net Revenue from Each Type of Animal Sold Total no. Total no. Sale price per Revenue from owned sold animal sold animals sold currently last year last year (yuan) last year 3.15 Sheep Q3.15a Q3.15b Q3.15c Q3.15d 3.16 Goats Q3.16a Q3.16b Q3.16c Q3.16d 3.17 Yaks Q3.17a 3.17 Q3.17c 3.17d 3.18 Cattlc 03.18a Q3.18b Q3.18c Q3.18d 3.19 Horscs Q3.19a Q3.19b QQ3.19c Q3.19d 3.20 Pigs Q3.20 Q3.20b Q3.20c 3.0d 3.21 Domestic fowls Q3.21a Q3.21b Q3.21c Q3.21d 3.22 Other animals; specify: Q3.22a Q3.22b Q3.22c _ Q3.22d Total Expenditure for LUvestock (Include all expenditures related to livestock activities, such as expenditures for vaccinations, the purchase of baby animals, land rental, andfodder.) 3.23 Baby animals, husbandry Q3.23 3.24 Fecdstocks and fodder Q3.24 3.25 Labor Q3.25 3.26 Vaccinations and medicine _ Q3.26 3.27 Other expenditures; specify_ Q3.27 87 Section 4. Household Cash Income and Expenditures Variable Total income last year (whole year) name 4. 1a Cash income from agriculture Q4.la 4.1 b Cash income from sales of livestock and domestic fowls, animal husbandry activities, and related by- Q4.1 b products 4.1c Income from fruit trees, tree planting etc. Q4.1c 4. 1d Wages and bonuses Q4.Id 4. le Government subsidies or remittances from relatives Q4.le 4.1 f Income from cultivation of medicinal and wild plants Q4.lf 4.ig Income from hunting Q4.lg 4.1h Other income; specify_ Q4.1h 4.1 Total household income last year Q4.1 Total Household Expenditures Variable Total expenditures last year name 4.2a Expenditures for agriculture Q4.2a 4.2b Expenditures for animal husbandry and other expenditures related to livestock and domestic fowls Q4.2b 4.2c Expenditures related to fruit trees and tree planting Q4.2c 4.2d Daily living Q4.2d 4.2e Expenditures for coal Q4.2e 4.2f Medical Q4.2f 4.2g Taxes Q4.2g 4.2h Odter expenditures Q4.2b 4.2 Total household expenditures Q4.2 88 Section 5. Purchasing History and Plans History How many durable goods does your household own, and how did you buy any of the following in the past? Code: [I] = Have, but purchased with cash in full payment [2] = Have, but purchased by installment [3] = Have, but purchased by barter [41 = Have, but purchased jointly with neighbor or relative Variable Number Variable Type of name owned name pur- [~~~J ____ ~~~~~ chase Agricultural machinery: 5.1 Seeders Q15.la Q5.lb 5.2 Harvesters Q15.2a = Q5.2b Herding machinery: [ 5.3 Sheep clippers Q15.3a Q5.3b 5.4 Milkers Q15Aa Q5.4b Household appliances: 5.5 Radio-tape cassettes Q15.5a Q5.5b 5.6 Black-and-white televisions Q15.6a. Q5.6b 5.7 Color televisions Q15.7a Q5.7b Vehicles: m 5.8 Cars Q15.8a Q5.8b 5.9 Tractors Q15.9a Q5.9b 5.10 Motorcycles Q15.1Oa QS.lOb 5.11 Others: Q15.lla 1111 QS.11b | 89 Section 5. Purchasing History and Plans Variable Plan name How do you plan to buy any of the following durable goods? Code: [1] = Plan to purchase by cash [2] = Plan to purchase by installment [3] = Plan to purchase barter [4] = Plan to purchase jointly with neighbor or relative [5J = Do not have plan to purchase by any means Agricultural machinery: 5.12 Seeders Q5.12 5.13 Harvesters Q5.13 Herding machinery: 5.14 Sheep clippers Q5.14 5.15 Milkers Q5.15 Household appliances: 5.16 Radio-tape cassettes Q5.16 5.17 Black-and-white televisions Q5.17 5.18 Color televisions _ Q5.18 Vehicles: 5.19 Cars Q5.19 5.20 Tractors Q5.20 5.21 Motorcycles Q5.21 Others: 5.22 ____ ____ ____ ____ ____ ____ ___ QS.22 _9 90 Section 6. Household Credit Standing and History Variable name 6.1 How much savings (in cash) does your household have? yuan Q6.1 (Include all cash saved either at home or deposited at the bank or credit union.) 6.2 Have your household ever taken any loan? Code: [0] = No Q6.2 [1 = Yes (If "No", go to Q7.1.) 6.3 If yes, bow much was the loan? yuan Q6.3 6.4a If yes, in which year did you take current loan? (Enter year, such as 1995, 1997, etc.) 6.4b If yes, how long was the loan? __ ronths Q6.4 6.5 If yes, what was the interest rate? ___ % per year Q6.5 6.6 If yes, how much in loans (yuan) does your household currently have? _ _ yuan Q6.6 (Enter "O" if the loan was paid off or ifyou do not have any outstanding loan.) 6.7 What was the source of your loan? _ Q6.7 Code: [11 = Bank [21 = Credit union [3] = Relatives [4] - Neighbors [5] = Other, specify, 6.8 What was the purpose of the loan? Q6.8 Code: [(I =To buy food [2] - Build, expand, or repair house [3] = Medical treatment or medicine [41 = Business [5] - Buy equipnent or appliance [6] - Fodder [71 - Family social function, nurriage, funeral 18] - Othcr, specify, 91 Section 7. Sources of Electricity and Other Energy What are your usual sources of energy in the Varia- household? ble nanme Code: [0] = No Yes No [11 = Yes 7.1 Dry cell battery Q7.1 7.2 Butter Q7.2 7.3 CandIes Q7.3 7.4 Kerosene = = Q7.4 7.5 Diesel for lighting e Q7.5 7.6 Gasoline for lighting Q7.6 7.7 Car battery = Q7.7 7.8 Small-scale power generator Q7.8 Electric generator set 7.9 Small wind home system Q7.9 7.10 PV-wind hybrid system Q7.10 7.11 PV system (electricity from the household's own PV system) Q7.11 7.12 Firewood Q7.12 7.13 Charcoal Q7.13 7.14 Dried annml dung Q7.14 7.15 Coal and coal briquette Q7.15 7.16 Biogas Q7.16 7.17 Otcr, specify 0 Q7.17 92 Section 8. Dry Cell Batteries Varia- ble name 8.1 During the past 12 months, did your household use dry cell batteries for an application, such as flashlight, Q8.1 lantern, combined flashlight and lantern, radio, or tape cassette? Code: [0] = No [1] = Yes; (If "No ", go to Q9. 1.) 8.2 On the average, how many times does your household buy dry cell batteries per year? hn times per year Q8.2 8.3 On the average how much does your household spend on dry cell battcries for each purchase? _ _ yuan per Q8.3 purchase 8.4 On the average, how nuch does your household spend on dry cell batteries per month? yuan Q8.4 8.5 On the average, how many hours per month does your household use electricity from a dry cell battery for Q8.5 productive purposes? _ _ hours per month (Enter "O "for no use.) 93 Section 9. Butter for Lighting Variable name 9.1 During the past 12 months how often did your household use butter for lighting? Q9.1 Code: [0] = Do not use butter for lighting (If "Not use butter, " go to Q1O. 1.) [I] = Used sometimes [2] = Used butter most of the time [3] = Always How many kilograms of butter does your household 9.2 usually use per month? kilograms Q9.2 9.3 What is the price or market value of butter per kilogram? yuan per kilogram Q9.3 9.4 How many hours per month does your household use butter for lighting for productive purposes? Q9.4 _ hours per month 94 Section 10. Candles Variable name 10.1 During the past 12 months, how often did your household use candles for lighting? Q10.1 Code: [0] = Do not use candle for lighting (7f "Not use candles, " go to Ql 1.1.) [I] = Used sometimes [2] = Used candle most of the time [3] = Always 10.2 How many fines does your household buy candles per year? times per year Q10.2 10.3 On the avcragc, how nmch does your household spend on candles for each purchase? yuan QIO.3 10.4 On the average, how much does your household spend on candles each month? yuan per month Q10.4 10.5 In gencral, how many hours per week does your household use candlelight? ___hours per week Q10.5 10.6 On the average, how many hours per month does your household use candles for productive purposes? Q10.6 hours per month (Enter "O "for no use.) 95 Section 11. Kerosene Varia- ble name 11.1 During the past 12 months, how often did your household use kerosene for lighting? Q11.1 Code: [0] = No, did not use (If "No", go to Q12. 1) [1I = Used sometimes [21 = Used most of the time [3] = Always 11.2 In general, wbich type of unit and how much of the typical unit of kerosene at what price per unit does your bousehold usually purcbase? 11 .2a Which type of unit does your household usually use to buy kerosene? Q1 2a Code: [II = Liter [2] = Kilogram 11 .2b How many of the typical units of kerosene does your household usually buy each tire? Ql 1.2b 11 .2c What is the price of kerosene per typical unit that your household usually buys? _ _ yuan Q11.2c 11.3 Generally, how many times does your household buy kerosene in a year? _ _ times per year QI 1.3 11.4 On the average, how much does your household spend on kerosene per month? _ _ yuan Q1 1A 11.5 When your household uses kerosene, how mnany of the typical units are usually used in a month? units Ql 1.5 per month 11.6 How many of the typical units are used for lighting each month? units per month Ql1.6 (Kerosene may be usedfor many purposes. Askfor the amount used for lighting only.) 11.7 In general, how many hours per day does your household use kerosene for light? _ _ hours per Ql 1.7 day 11.8 On the avcrage how many hours per month does your household use kerosene for productive purposes? Ql 1.8 hours per month (Enter "O "for no use.) 96 Section 12. Diesel for Lighting Varia- ble name 12.1 During the past 12 months, did your household use any diesel for lighting? Q12.1 Code: [0] = No, did not use (If "No': go to Q13.1J [1] = Used sometimes [2] = Used most of the tiDm [3] = Always 12.2 In general, which type of unit and how much of the typical unit of diesel and at what price per unit does your household usually purchase? 1 2.2a Which type of unit does your household usually use to buy diesel? Q12.2a Code: [II = Liter; [2] = Kilogram 12.2b How many of the typical units of diesel does your household usually buy each timne? Q12.2b 12.2c What is the price of diesel per typical unit that your household usually buys? _ _ yuan Q12.2c 12.3 Generally, how many times does your household buy diesel in a year? _ _ times per year _ Q12.3 12.4 On the average, how much does your household spend on diesel per month? _ _ yuan _ Q12.4 12.5 When your household uses dieseL how many of the typical units are usually used in a month? units Q12.5 per month 12.6 How many of the typical units are used for lighting each month? units per month Q12.6 (Diesel may be usedfor many purposes. Askfor the amount usedfor lighting only.) 12.7 In generaL how many hours per day does your household use diesel for light? _ _ hours per day Q12.7 12.8 On the average, how many hours per month does your household use diesel light for productive purposes? _ Q12.8 hours per month (Enter "O "for no use.) 97 Section 13. Gasoline for Specialized Lamps for Lighting Varia- ble name 13.1 During the past 12 months, did your household use any gasoline for lighting? Q13.1 Code: [0] = No, did not use (If "No", go to Q14.1.) [1] = Used sometimes [2] - Used most of the time [3] - Always 13.2 In general, wbich type of unit and how much of the typical unit of gasoline and at what price per unit does your household usually purchase? 13.2a Which type of unit does your household usually use to buy gasoline? Q13.2a Code: [I] = Liter [2] = Kilogramr 13.2b How many of the typical unit of gasoline does your household usually buy each time? Q13.2b 13.2c What is the price of gasoline per typical unit? ,yuan Q13.2c 13.3 Generally, how many times does your household buy gasoline in a year? times per year Q13.3 13.4 On the average, how much does your household spend on gasoline per month? _ _ yuan Q13.4 13.5 When your household uses gasoline, how many of the typical units are usually used in a month? units Q13.5 per month 13.6 How many of the typical units are used for lighting each month? _ _units per month Q13.6 (Gasoline may be usedfor many purposes. Ask for the amount usedfor pressurized lamp lighting only.) 13.7 In general, how many hours per day does your household use gasoline for light? hours per day Q13.7 13.8 On the average, how many hours per month does your household use gasoline light for productive purposes? Q13.8 hours per month (Enter "O "for no use.) 98 Section 14. Electricity from Car Batteries Varia- ble name 14.1 During the past 12 months, did your housebold use a car battery to supply electricity? Q14.1 [0] = No (If "No", go to Q15.1.) [1] = Yes 14.2 During the past 30 days did your household use a car battery to supply electricity? Q142 Code: [0] = No, did not use [I] = Used as supplementary source of electricity [2] = Used as the main source of electricity (1ff I] "Used as the supplementary... " OR f2] "Used as the main source .... " go to Q14.4.) 14.3 Please give me reasons your household has not used your car battery during the past 30 days. Q14.3 Code: [1] = Out of order 12] = Already been electrified [3] = Recharge is too costly [4] = No transportation [5] = Otber, specify: _ _ 14.4 How many batteries do your household have? batteries Q14A 14.5a What is the voltage of yourfirst car battery?__ volts Q145a 14.5b What are the ampere-hours of yourfirst car battery? ampere-hours Q14.5b 14.Sc How much did the first car battery cost? __yuan Q14.5c 14.6a What is the voltage of your second car battery? volts - Q14.6a 14.6b What is the ampere-hours of your second car battery? ampere-hours Q14.6b 14.6c How nmch did the second car baery cost? Q14.6c Yuan 14.7 On the avenge, how much do you spend on recharging for all of your battenes each month? yuan Q14.7 14.8 How much does each recharge cost? yuan Q14._ 99 Section 14. Electricity from Car Batteries Varia- (continued) ble name 14.9 In general how mnany recharges per month do you require for all of your batteries? recharges per Q14.9 month 14.10 How many months did your previous battery last? months Q14.10 (Enter "O" ifyou did not own any battery before.) 14.11 How long does the battery give you service before the next recharge? _ _ days Q14.11 14.12 What is the distance from your home to the recharge station? _ kilometers Q14.12 14.13 Which mode of transport does your household use to go to the recharge station? Q14.13 Code: [1] = Bicycle [21 = Motorcycle [3] = Bus, truck, or car 14] = Horse [5] = Cart [6] = Combination of the above transportation modes [7] = Other; specify: 14.14 What is the average cost of transport to and from the recharge station? yuan (cost per round trip) Q14.14 14.15 In general, how many hours per week does your household use electricity from car batteries? Q14.15 hours per week 14.16 On the average, how rmany hours per month does your household use electricity from a car battery for Q14.16 productive purposes? _ _ hours per month (Enter "O "for no use.) 100 Varia- Section 15. Electricity ble name 15.1 Does your household use electricity that is generated from electric generator and supplies Q15.1 through village or cornmunity grid or neighbor or private entrepreneur or your own electric generator set? Code: [0] = Do not use (If "Do not use, "go to Q16. 1.) l I ] = Use electricity from village- or community- owned generator set 12] - Use electricity from neighbor- or relative- owned generator set 131 - Use electricity from family-owned generator set (Go to Q15.I I) 141 - Othcr, specify. Household uses electricity from village or community, or from neighbor- or relative-own generator set (Ansuwer "I " or "2 " in Q15. 1.) 15.2 How many months has your household had electricity? __-__ months Q15.2 15.3 How many households including your household are sharing electricity from the same source through the Q15.3 same grid with yours? households 15.4 How much does your household pay for electricity per biling period? _ _ yuan Q15.4 15.5 How any days does each bill cover? ___ days = Q15.5 Varia- ble name If you share electricity with other househokls, do you 15.6a pay by kWh? Code: 101 - No Q15.6a [1 Y ' Yes 15.6b If yes, how much electricity did your family use per billing penod? kWh Q15.6b 15.6c If yes, how many yuan per kWh? yuan per Q15.6c kWh 15.7 Do you pay by the umber of hght bulbs or tubes and appliances? Q15.7 Code: (0 - No 101 [1] = Yes 1 5.7a If yes, what is the average wattage of all light bulbs and tubes? watts Q15.7a 15.8 Do you pay in fixed monthly charges? Code: [0] =No Q15.8 [1] = Yes 15.9 How many hours of electricity services you receive per day? hours per day Q15.9 15.10 In general, how many days in a month does your household receive electricity services? _ days per Q15.10 mnonth Family owns electric generator set (Answer "3" in QIS. L.) 15.11 How rnany months has your household had its own electric generator set? rmonths Q15.1I 15.12 How much did your household spend on fuels for your own generator set to generate electricity last year? Q15.12 _______ yuan per year How many households do your household supply 15.13 electricity to? households (Enter "O"for your own household use only) (Ask QIS.114 to household that ans-wered "I ': "2 "' or "3" in QIS.I)J 15.14 On the average, bow many hours in a month does your household use electricity for productive purposes? Q15.14 hours per month (Enter "O"for no use.) 102 Section 16. Owners of Small Wind Systems Variable name 16.1 How many small wind systems does your household have? (If household does not have any, fill in "0 ", and go to Q16.1 Q17.1.) 16.2 What do you think about the price of your small wind Q16.2 system? Code: [I] = Very expensive [2] = Expensive [3] = Right price [4] = Cheap I will ask you some questions about your small wind system. Please answer the foUowing questions concerning the size and cost of your system. (Fill in 20 if the system is 20 watts. If the system is 30 watts, fill in 30. You must then ask to see the system to verify the correct size.) 16.3 What is the size of your small wind system? watts Q16.3 16.4 How long has your household had its small wind system installed? months Q16.4 Please tell me about the total costs of each of your wind power system. 16.5a For the small wind system, how much did you pay up front? yuan Q16.5a (If you paid infull, fill in the totalfull payment, and go to Q)7.1) Descnbe the terms of payment. 16.5b Have to pay _ yuan per payment, Q16.5b 16.5c ... for a total number of payments. Q16.5c 16.5d How many months does each payment cover? Q16.5d months 103 Section 17. Hybrid Systems Variable name Ownership and Cost of Hybrid Systems 17.1 How many hybrid systems do your household have? (If household does not have any, fill in "0", and go to Q18. 1) Q17.1 17.2 What do you think about the price of your hybrid Q17.2 system? Code: [ J = Very expensive 121 = Expensive [3] = Right price [4] = Cheap I will ask you somne questions about your hybrid system. Please answer the following questions concerning the size and cost of your system (Fill in 20 if the system is 20 watts. If the system is 30 watts, fill in 30. You must then ask to see the system to verify the correct size.) 17.3 What is the size of your hybrid system? watts _______ Q17.3 17.4 How long has your household had its hybrid system installed? nmonths Q17.4 Please tell me about the total cost of each of your wind power systems. 1 7.5a For the hybrid system, how much did you pay up front? yuan Q17.5a (7fyou paid in full, fill in the totalfull payment, and go to Q18.1) Please describe the terms of payment. 17.5b Have to pay _ _ yuan per payment, Q17.5b 17.5c ... for a total number of _ payments. Q17.5c 17.5d How nany months does each payment cover? Q17.5d Dmnths 104 Section 18. Appliances Varia- ble name How many of the following appliances does your Number household have? Have (Enter "O "for "do not have. ') 18.1 Fan Q18.1 18.2 Color television Q18.2 18.3 Black-and-white television Q18.3 18.4 Radio/ or tape cassette Q18.4i= 18.5 VCR Q18.5 18.6 SateUite receiver Q18.6 18.7 Refrigerator Q18.7 18.8 Freezer Q18.8 18.9 Washing machine Q18.9 18.10 Ironing Q18.10 18.11 Electric shears Q18.11 18.12 Other, specify: Q18.12 105 Section 19. Lighting Can you please tell me about the type of light bulbs or tubes, their capacity in wattage, how many your household has, and the combined total number of hours all are used for light each day in your household? Type of light bulb or tube: Code: [ I ] = Incandescent light bulb [2] = Fluorescent hght tube [3] = Compact fluorescent light Type of Capacity Number Combined total Type of Capacity Number Total bulb or (watts) of bulbs hours of all light bulb or (watts) of bulbs hours tube tubes bulbs and tubes tube used during a 24- ________ ________ hour period __v_1 r- _S. r or any andnr,.e. or * * L 11 a=copac af such 6amdanu °f KAZAKHSTAN M O N G O I A - PHOTOVOLTAIC MARKET STUDY, 1999 -_ SHAANXI > i{ At< AO' 80°SilH|EN°°YANoX) _ t .4 GUIYANG