Publication: Biofuels : Markets, Targets and Impacts
Loading...
Date
2010-07-01
ISSN
Published
2010-07-01
Author(s)
Abstract
This paper reviews recent developments in biofuel markets and their economic, social and environmental impacts. Several countries have introduced mandates and targets for biofuel expansion. Production, international trade and investment have increased sharply in the past few years. However, several existing studies have blamed biofuels as one of the key factors behind the 2007-2008 global food crisis, although the magnitudes of impacts in these studies vary widely depending on the underlying assumptions and structure of the models. Existing studies also have huge disparities in the magnitude of long-term impacts of biofuels on food prices and supply; studies that model only the agricultural sector show higher impacts, whereas studies that model the entire economy show relatively lower impacts. In terms of climate change mitigation impacts, there exists a consensus that current biofuels lead to greenhouse gas mitigation only when greenhouse gas emissions related to land-use change are not counted. If conversion of carbon rich forest land to crop land is not avoided, the resulting greenhouse gas release would mean that biofuels would not reduce cumulative greenhouse gas emissions until several years had passed. Overall, results from most of the existing literature do not favor diversion of food for large-scale production of biofuels, although regulated production of biofuels in countries with surplus land and a strong biofuel industry are not ruled out. Developments in second generation biofuels offer some hope, yet they still compete with food supply through land use and are currently constrained by a number of technical and economic barriers.
Link to Data Set
Citation
“Timilsina, Govinda R.; Shrestha, Ashish. 2010. Biofuels : Markets, Targets and Impacts. Policy Research working paper ; no. WPS 5364. © http://hdl.handle.net/10986/3848 License: CC BY 3.0 IGO.”
Other publications in this report series
Publication The Worldwide Governance Indicators(Washington, DC: World Bank, 2024-11-07)This paper provides an overview of the data sources and aggregation methodology for the Worldwide Governance Indicators (WGI). The WGI report six aggregate governance indicators measuring Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption in a sample of 214 economies over the period 1996–2023. The aggregate indicators combine information from 35 different existing data sources, capturing subjective perceptions of the quality of various dimensions of governance reported by experts and survey respondents worldwide. The paper briefly discusses how to use reported margins of error when interpreting cross-country and over-time differences in the aggregate indicators. The paper also updates and extends earlier analysis on three key issues relating to the WGI methodology: (a) the effect of correlated perception errors, (b) the robustness of the aggregate indicators to alternative weighting schemes, and (c) the existence on trends in global averages of governance.Publication How Regulations Impact the Labor Market(Washington, DC: World Bank, 2024-11-06)This paper provides an extensive review of the literatures on product and labor market regulations and their effects on labor market outcomes. It uncovers the interdependence of these two types of regulations, an area that has received limited attention in research. The paper highlights why understanding the intricate relationship between product and labor market regulations is crucial for effective policy making and advancement of labor market conditions. The findings strongly discourage adopting uniform policies and advocate for tailored approaches to labor market promotion.Publication Optimal Public Sector Premium, Talent Misallocation, and Aggregate Productivity(Washington, DC: World Bank, 2024-11-06)This paper develops a tractable general equilibrium model to quantify the aggregate productivity gains from adjusting the public sector premium and the size of the public sector to their optimal levels. In the framework, the optimal size of the public sector is contingent on the efficiency level of public goods in increasing the productivity of the private sector. The model also incorporates an endogenous decision between market and non-market activities for women. The model is calibrated using data from the Arab Republic of Egypt, a country that exhibits a disproportionate share of workers, and women especially, in the public sector. The findings show that, under a conservative value for the efficiency of the public sector, aligning the public sector premium with its optimal level, thus lowering the share of employment in the public sector, results in aggregate efficiency gains of 12 percent for output per worker and 8 percent for total factor productivity. For lower values of the elasticity of private output to public goods, the productivity gains are almost twice as large. The optimal premium is positive for women and approaches zero for men, preventing a shift of mid-high-level skilled women from the public sector to non-market activities and also a contraction of the male entrepreneurial sector. Notably, a reduced female public sector premium fosters greater female labor force participation in market activities through an expansion of the female entrepreneurial sector, which increases the demand for production labor and drives wages up.Publication A Toxic Threat to Indonesia’s Human Capital(Washington, DC: World Bank, 2024-11-06)About 27,000 Indonesians died of lead poisoning in 2019. Where mandatory lead-free standards are absent, as is the case in Indonesia, lead paint is among the most common sources of poisoning. Tests for lead in interior paint conducted in a nationally representative sample of households in December 2023 found that at least 44.8 percent of Indonesians live in homes with lead paint, rising to at least 57.9 percent among those living in homes with any visible interior paint. Indonesian children are more often at risk than adults, with about 46 percent aged five or younger—about 10.2 million children—living in homes with lead paint. Deteriorating lead paint puts 14.1 percent of children aged five or younger at risk of more severe exposure, with the poorest 40 percent of Indonesians more than twice as likely to report deteriorating lead paint. Calibrating the Integrated Exposure Uptake Biokinetic Model for Lead in Children model to these estimates suggests that lead paint exposure alone may push 21 percent of children aged five or younger over the 5 micrograms per deciliter blood lead threshold, equivalent to 55 percent of Indonesia’s total estimated cases among children in the Global Burden of Disease database. New lead paint continues to accumulate in the environment: tests conducted on the most popular paint varieties on the market found that 77 percent contained unsafe levels of lead. The results show that poisoning risks from lead paint are high and widespread in Indonesia, and that lead contaminated paint supply chains remain dominant.Publication Yielding Insights(Washington, DC: World Bank, 2024-11-06)This paper addresses the challenge of missing crop yield data in large-scale agricultural surveys, where crop-cutting, the most accurate method for yield measurement, is often limited due to cost constraints. Multiple imputation techniques, supported by machine learning models are used to predict missing yield data. This method is validated using survey data from Mali, which includes both crop-cut and self-reported yield information. The analysis covers several crops, providing insights into the importance of different predictors, including farmer-reported yields and geo-spatial variables, and the conditions under which the approach is valid. The findings show that machine learning-based imputations can provide accurate yield estimates, especially for crops with low intercropping rates and higher commercialization. However, survey-to-survey imputations are less accurate than within-survey imputations, suggesting limitations in extrapolating data across different survey rounds. The study contributes valuable insights into improving cost-efficiency in agricultural surveys and the potential of imputation methods.