Publication:
Recall Length and Measurement Error in Agricultural Surveys

Loading...
Thumbnail Image
Files in English
English PDF (1.7 MB)
332 downloads
English Text (118.42 KB)
30 downloads
Published
2020-01
ISSN
Date
2020-01-30
Editor(s)
Abstract
This paper assesses the relationship between the length of recall and nonrandom error in agricultural survey data. Using data from the World Bank's Living Standards Measurement Study–Integrated Surveys on Agriculture in Malawi and Tanzania, the paper shows that key input and output variables are systematically related to the length of the recall period, indicating the presence of nonrandom measurement error. With longer recall periods, farmers report greater quantities of harvest, labor, and fertilizer inputs. Farmers list fewer plots as the recall period increases. The paper argues that it is plausible that farmers overestimate plot-level outcomes, or they forget some of their more marginal plots due to longer recall periods. The analysis also finds evidence of measurement error related to the length of recall in common measures of agricultural productivity. The size of the recall effect typically varies between 2 and 5 percent per additional month of recall length, which is economically significant. With data reliability affecting policy effectiveness, improving agricultural survey data quality remains an important concern. Mainstreaming objective measures where possible and reducing the risk of recall error through shorter recall periods appear to be promising avenues to improve the quality of key variables in agricultural surveys.
Link to Data Set
Citation
Wollburg, Philip; Tiberti, Marco; Zezza, Alberto. 2020. Recall Length and Measurement Error in Agricultural Surveys. Policy Research Working Paper;No. 9128. © World Bank. http://hdl.handle.net/10986/33264 License: CC BY 3.0 IGO.
Associated URLs
Associated content
Report Series
Report Series
Other publications in this report series
  • Publication
    The Economic Value of Weather Forecasts: A Quantitative Systematic Literature Review
    (Washington, DC: World Bank, 2025-09-10) Farkas, Hannah; Linsenmeier, Manuel; Talevi, Marta; Avner, Paolo; Jafino, Bramka Arga; Sidibe, Moussa
    This study systematically reviews the literature that quantifies the economic benefits of weather observations and forecasts in four weather-dependent economic sectors: agriculture, energy, transport, and disaster-risk management. The review covers 175 peer-reviewed journal articles and 15 policy reports. Findings show that the literature is concentrated in high-income countries and most studies use theoretical models, followed by observational and then experimental research designs. Forecast horizons studied, meteorological variables and services, and monetization techniques vary markedly by sector. Estimated benefits even within specific subsectors span several orders of magnitude and broad uncertainty ranges. An econometric meta-analysis suggests that theoretical studies and studies in richer countries tend to report significantly larger values. Barriers that hinder value realization are identified on both the provider and user sides, with inadequate relevance, weak dissemination, and limited ability to act recurring across sectors. Policy reports rely heavily on back-of-the-envelope or recursive benefit-transfer estimates, rather than on the methods and results of the peer-reviewed literature, revealing a science-to-policy gap. These findings suggest substantial socioeconomic potential of hydrometeorological services around the world, but also knowledge gaps that require more valuation studies focusing on low- and middle-income countries, addressing provider- and user-side barriers and employing rigorous empirical valuation methods to complement and validate theoretical models.
  • Publication
    The Macroeconomic Implications of Climate Change Impacts and Adaptation Options
    (Washington, DC: World Bank, 2025-05-29) Abalo, Kodzovi; Boehlert, Brent; Bui, Thanh; Burns, Andrew; Castillo, Diego; Chewpreecha, Unnada; Haider, Alexander; Hallegatte, Stephane; Jooste, Charl; McIsaac, Florent; Ruberl, Heather; Smet, Kim; Strzepek, Ken
    Estimating the macroeconomic implications of climate change impacts and adaptation options is a topic of intense research. This paper presents a framework in the World Bank's macrostructural model to assess climate-related damages. This approach has been used in many Country Climate and Development Reports, a World Bank diagnostic that identifies priorities to ensure continued development in spite of climate change and climate policy objectives. The methodology captures a set of impact channels through which climate change affects the economy by (1) connecting a set of biophysical models to the macroeconomic model and (2) exploring a set of development and climate scenarios. The paper summarizes the results for five countries, highlighting the sources and magnitudes of their vulnerability --- with estimated gross domestic product losses in 2050 exceeding 10 percent of gross domestic product in some countries and scenarios, although only a small set of impact channels is included. The paper also presents estimates of the macroeconomic gains from sector-level adaptation interventions, considering their upfront costs and avoided climate impacts and finding significant net gross domestic product gains from adaptation opportunities identified in the Country Climate and Development Reports. Finally, the paper discusses the limits of current modeling approaches, and their complementarity with empirical approaches based on historical data series. The integrated modeling approach proposed in this paper can inform policymakers as they make proactive decisions on climate change adaptation and resilience.
  • Publication
    Labor Demand in the Age of Generative AI: Early Evidence from the U.S. Job Posting Data
    (Washington, DC: World Bank, 2025-11-18) Liu, Yan; Wang, He; Yu, Shu
    This paper examines the causal impact of generative artificial intelligence on U.S. labor demand using online job posting data. Exploiting ChatGPT’s release in November 2022 as an exogenous shock, the paper applies difference-in-differences and event study designs to estimate the job displacement effects of generative artificial intelligence. The identification strategy compares labor demand for occupations with high versus low artificial intelligence substitution vulnerability following ChatGPT’s launch, conditioning on similar generative artificial intelligence exposure levels to isolate substitution effects from complementary uses. The analysis uses 285 million job postings collected by Lightcast from the first quarter of 2018 to the second quarter of 2025Q2. The findings show that the number of postings for occupations with above-median artificial intelligence substitution scores fell by an average of 12 percent relative to those with below-median scores. The effect increased from 6 percent in the first year after the launch to 18 percent by the third year. Losses were particularly acute for entry-level positions that require neither advanced degrees (18 percent) nor extensive experience (20 percent), as well as those in administrative support (40 percent) and professional services (30 percent). Although generative artificial intelligence generates new occupations and enhances productivity, which may increase labor demand, early evidence suggests that some occupations may be less likely to be complemented by generative artificial intelligence than others.
  • Publication
    The Lasting Effects of Working while in School
    (Washington, DC: World Bank, 2025-08-18) Ferrando, Mery; Katzkowicz, Noemi; Le Barbanchon, Thomas; Ubfal, Diego
    This paper provides the first experimental evidence on the long-term effects of work-study programs, leveraging a randomized lottery design from a national program in Uruguay. Participation leads to a persistent 11 percent increase in formal labor earnings, observable seven years after the program. Effects are stronger for youth who participate during pivotal educational transitions and are larger for vulnerable youth and men, while remaining positive for women and non-vulnerable youth. The program is highly cost-effective, with average impacts exceeding those of job training programs and comparable to early childhood investments.
  • Publication
    It’s Not (Just) the Tariffs: Rethinking Non-Tariff Measures in a Fragmented Global Economy
    (Washington, DC: World Bank, 2025-10-22) Taglioni, Daria; KEE, Hiau Looi
    As tariffs have declined, non-tariff measures (NTMs) have become central to trade policy, especially in high-income countries and regulated sectors like food and green technologies. Although NTMs may serve legitimate goals, they could also sort countries and firms into or out of markets based on compliance capacity and differences in product mix. Documenting recent advances in the estimation of ad valorem equivalents (AVEs), this paper uncovers new patterns of use and exposure of NTMs. High-income countries rely more heavily on NTMs relative to tariffs, while low- and middle-income countries face steeper AVEs on their exports. Firm-level evidence shows that NTMs disproportionately affect smaller firms, leading to market exit and concentration. Poorly designed NTMs can harm productivity and welfare, while coordinated, capacity-aware use can deliver inclusive outcomes. Policy design, transparency, and diagnostics must evolve to reflect the growing role—and risks—of NTMs in a fragmented global trade landscape.
Journal
Journal Volume
Journal Issue

Related items

Showing items related by metadata.

  • Publication
    What Does Variation in Survey Design Reveal about the Nature of Measurement Errors in Household Consumption?
    (World Bank, Washington, DC, 2013-02) Gibson, John; Beegle, Kathleen; De Weerdt, Joachim; Friedman, Jed
    This paper uses data from eight different consumption questionnaires randomly assigned to 4,000 households in Tanzania to obtain evidence on the nature of measurement errors in estimates of household consumption. While there are no validation data, the design of one questionnaire and the resources put into its implementation make it likely to be substantially more accurate than the others. Comparing regressions using data from this benchmark design with results from the other questionnaires shows that errors have a negative correlation with the true value of consumption, creating a non-classical measurement error problem for which conventional statistical corrections may be ineffective.
  • Publication
    From Necessity to Opportunity
    (World Bank, Washington, DC, 2022-09) Zezza, Alberto; Mcgee, Kevin; Wollburg, Philip; Assefa, Thomas; Gourlay, Sydney
    The COVID-19 pandemic has disrupted survey and data systems globally and especially in low- and middle-income countries. Lockdowns necessitated remote data collection as demand for data on the impacts of the pandemic surged. Phone surveys started being implemented at a national scale in many places that previously had limited experience with them. As in-person data collection resumes, the experience gained provides the grounds to reflect on how phone surveys may be incorporated into survey and data systems in low- and middle-income countries. This includes agricultural and rural surveys supported by international survey programs such as the World Bank’s Living Standards Measurement Study—Integrated Surveys on Agriculture, the Food and Agriculture Organization’s AGRISurvey, or the 50x2030 Initiative. Reviewing evidence and experiences from before and during the pandemic, the paper analyzes and provides guidance on the scope of and considerations for using phone surveys for agricultural data collection. It addresses the domains of sampling and representativeness, post-survey adjustments, questionnaire design, respondent selection and behavior, interviewer effects, as well as cost considerations, all with an emphasis on the particularities of agricultural and rural surveys. Ultimately, the integration of phone interviews with in-person data collection offers a promising opportunity to leverage the benefits of phone surveys while addressing their limitations, including the depth of content constraints and potential coverage biases, which are especially challenging for agricultural and rural populations in low- and middle-income countries.
  • Publication
    Missing(ness) in Action : Selectivity Bias in GPS-Based Land Area Measurements
    (World Bank, Washington, DC, 2013-06) Kilic, Talip; Zezza, Alberto; Carletto, Calogero; Savastano, Sara
    Land area is a fundamental component of agricultural statistics, and of analyses undertaken by agricultural economists. While household surveys in developing countries have traditionally relied on farmers' own, potentially error-prone, land area assessments, the availability of affordable and reliable Global Positioning System (GPS) units has made GPS-based area measurement a practical alternative. Nonetheless, in an attempt to reduce costs, keep interview durations within reasonable limits, and avoid the difficulty of asking respondents to accompany interviewers to distant plots, survey implementing agencies typically require interviewers to record GPS-based area measurements only for plots within a given radius of dwelling locations. It is, therefore, common for as much as a third of the sample plots not to be measured, and research has not shed light on the possible selection bias in analyses relying on partial data due to gaps in GPS-based area measures. This paper explores the patterns of missingness in GPS-based plot areas, and investigates their implications for land productivity estimates and the inverse scale-land productivity relationship. Using Multiple Imputation (MI) to predict missing GPS-based plot areas in nationally-representative survey data from Uganda and Tanzania, the paper highlights the potential of MI in reliably simulating the missing data, and confirms the existence of an inverse scale-land productivity relationship, which is strengthened by using the complete, multiply-imputed dataset. The study demonstrates the usefulness of judiciously reconstructed GPS-based areas in alleviating concerns over potential measurement error in farmer-reported areas, and with regards to systematic bias in plot selection for GPS-based area measurement.
  • Publication
    Agricultural Data Collection to Minimize Measurement Error and Maximize Coverage
    (World Bank, Washington, DC, 2021-07) Carletto, Calogero; Dillon, Andrew; Zezza, Alberto
    Advances in agricultural data production provide ever-increasing opportunities for pushing the research frontier in agricultural economics and designing better agricultural policy. As new technologies present opportunities to create new and integrated data sources, researchers face trade-offs in survey design that may reduce measurement error or increase coverage. This paper first reviews the econometric and survey methodology literatures that focus on the sources of measurement error and coverage bias in agricultural data collection. Second, it provides examples of how agricultural data structure affects testable empirical models. Finally, it reviews the challenges and opportunities offered by technological innovation to meet old and new data demands and address key empirical questions, focusing on the scalable data innovations of greatest potential impact for empirical methods and research.
  • Publication
    Measure for Measure
    (Published by Oxford University Press on behalf of the World Bank, 2021-06-14) Carletto, Gero; Tiberti, Marco; Zezza, Alberto
    This paper uses a large database of surveys of household incomes to characterize income underreporting in household surveys in low- and middle-income countries. The objective is to document (a) the extent of this underreporting, and (b) whether and how it varies systematically with respondent, household, income, and survey design features. Drawing on rural household data from 20 developing and transition countries, and using consumption expenditure as a benchmark, results indicate that the observed income/consumption ratios are very small, being on average around 0.76. Results suggest that income underreporting is systematically associated with household and survey characteristics. In particular, the degree of underreporting is strongly associated with the income source, with agricultural income being the component suffering more than any other components from underreporting. The analysis also provides evidence supporting the well-established proposition that underreporting tends to increase with household welfare: richer households appear to underreport income more. Implications for survey design and for future research are drawn.

Users also downloaded

Showing related downloaded files

  • Publication
    Global Economic Prospects, January 2025
    (Washington, DC: World Bank, 2025-01-16) World Bank
    Global growth is expected to hold steady at 2.7 percent in 2025-26. However, the global economy appears to be settling at a low growth rate that will be insufficient to foster sustained economic development—with the possibility of further headwinds from heightened policy uncertainty and adverse trade policy shifts, geopolitical tensions, persistent inflation, and climate-related natural disasters. Against this backdrop, emerging market and developing economies are set to enter the second quarter of the twenty-first century with per capita incomes on a trajectory that implies substantially slower catch-up toward advanced-economy living standards than they previously experienced. Without course corrections, most low-income countries are unlikely to graduate to middle-income status by the middle of the century. Policy action at both global and national levels is needed to foster a more favorable external environment, enhance macroeconomic stability, reduce structural constraints, address the effects of climate change, and thus accelerate long-term growth and development.
  • Publication
    Global Economic Prospects, June 2025
    (Washington, DC: World Bank, 2025-06-10) World Bank
    The global economy is facing another substantial headwind, emanating largely from an increase in trade tensions and heightened global policy uncertainty. For emerging market and developing economies (EMDEs), the ability to boost job creation and reduce extreme poverty has declined. Key downside risks include a further escalation of trade barriers and continued policy uncertainty. These challenges are exacerbated by subdued foreign direct investment into EMDEs. Global cooperation is needed to restore a more stable international trade environment and scale up support for vulnerable countries grappling with conflict, debt burdens, and climate change. Domestic policy action is also critical to contain inflation risks and strengthen fiscal resilience. To accelerate job creation and long-term growth, structural reforms must focus on raising institutional quality, attracting private investment, and strengthening human capital and labor markets. Countries in fragile and conflict situations face daunting development challenges that will require tailored domestic policy reforms and well-coordinated multilateral support.
  • Publication
    The Container Port Performance Index 2020 to 2024: Trends and Lessons Learned
    (Washington, DC: World Bank, 2025-09-22) World Bank
    The Container Port Performance Index (CPPI) provides a global benchmark of how container ports perform in handling vessel calls. Developed jointly by the World Bank and S&P Global Market Intelligence, it measures the time ships spend in port and relates this to the number of containers moved during that time. This approach makes the CPPI a unique diagnostic tool that can highlight patterns in port operations and shed light on global and regional supply chain dynamics. Now in its fifth edition, the CPPI report covers the period from 2020 to 2024. It builds on a well-established methodology to generate scores for more than 400 container ports worldwide. Over time, the CPPI has become a trusted reference point for policymakers, industry stakeholders, and researchers who seek to understand how ports adapt to shocks, recover from disruptions, and identify opportunities for investments, reform and modernization. A major innovation in this edition is the introduction of multi-year trend analysis. Rather than presenting annual snapshots, the report now tracks how CPPI scores have changed across five years. This longitudinal perspective reveals shifts in port performance, showing where scores have risen, fallen, or remained stable. By linking these movements to external factors, the CPPI offers insights into how global and regional supply chains evolve under pressure. The results clearly mirror the crises that have shaken global trade. During the COVID-19 pandemic, CPPI scores in different regions declined sharply as congestion, equipment shortages, and delays overwhelmed many ports. By 2023, global averages rebounded in parallel with easing freight markets and reduced congestion. Yet 2024 brought new challenges: the Red Sea crisis disrupted major trade lanes, while climate-related constraints at the Panama Canal added further stress. These shocks were reflected in lower global and several regional average scores, underscoring the vulnerability of maritime transport to geopolitical and environmental events. The CPPI is not about comparing one port against another, but about understanding changes in performance over time. Ports that improved their scores often did so by reducing time at anchor, optimizing berth operations, investing in digital tools, and strengthening coordination across logistics partners. The evidence confirms that improvements are possible across ports of all sizes, and that rising scores are linked to deliberate actions to minimize time in port relative to containers moved. By consolidating five years of results, this edition transforms the CPPI into a long-term reference point. It shows how global crises have affected shipping, how different regions have adapted, and what lessons can be drawn for future resilience. The World Bank and S&P Global Market Intelligence remain committed to maintaining the CPPI as a global public good, providing transparency, comparability, and practical insights to support more reliable and sustainable maritime supply chains.
  • Publication
    The Container Port Performance Index 2023
    (Washington, DC: World Bank, 2024-07-18) World Bank
    The Container Port Performance Index (CPPI) measures the time container ships spend in port, making it an important point of reference for stakeholders in the global economy. These stakeholders include port authorities and operators, national governments, supranational organizations, development agencies, and other public and private players in trade and logistics. The index highlights where vessel time in container ports could be improved. Streamlining these processes would benefit all parties involved, including shipping lines, national governments, and consumers. This fourth edition of the CPPI relies on data from 405 container ports with at least 24 container ship port calls in the calendar year 2023. As in earlier editions of the CPPI, the ranking employs two different methodological approaches: an administrative (technical) approach and a statistical approach (using matrix factorization). Combining these two approaches ensures that the overall ranking of container ports reflects actual port performance as closely as possible while also being statistically robust. The CPPI methodology assesses the sequential steps of a container ship port call. ‘Total port hours’ refers to the total time elapsed from the moment a ship arrives at the port until the vessel leaves the berth after completing its cargo operations. The CPPI uses time as an indicator because time is very important to shipping lines, ports, and the entire logistics chain. However, time, as captured by the CPPI, is not the only way to measure port efficiency, so it does not tell the entire story of a port’s performance. Factors that can influence the time vessels spend in ports can be location-specific and under the port’s control (endogenous) or external and beyond the control of the port (exogenous). The CPPI measures time spent in container ports, strictly based on quantitative data only, which do not reveal the underlying factors or root causes of extended port times. A detailed port-specific diagnostic would be required to assess the contribution of underlying factors to the time a vessel spends in port. A very low ranking or a significant change in ranking may warrant special attention, for which the World Bank generally recommends a detailed diagnostic.
  • Publication
    Digital Progress and Trends Report 2023
    (Washington, DC: World Bank, 2024-03-05) World Bank
    Digitalization is the transformational opportunity of our time. The digital sector has become a powerhouse of innovation, economic growth, and job creation. Value added in the IT services sector grew at 8 percent annually during 2000–22, nearly twice as fast as the global economy. Employment growth in IT services reached 7 percent annually, six times higher than total employment growth. The diffusion and adoption of digital technologies are just as critical as their invention. Digital uptake has accelerated since the COVID-19 pandemic, with 1.5 billion new internet users added from 2018 to 2022. The share of firms investing in digital solutions around the world has more than doubled from 2020 to 2022. Low-income countries, vulnerable populations, and small firms, however, have been falling behind, while transformative digital innovations such as artificial intelligence (AI) have been accelerating in higher-income countries. Although more than 90 percent of the population in high-income countries was online in 2022, only one in four people in low-income countries used the internet, and the speed of their connection was typically only a small fraction of that in wealthier countries. As businesses in technologically advanced countries integrate generative AI into their products and services, less than half of the businesses in many low- and middle-income countries have an internet connection. The growing digital divide is exacerbating the poverty and productivity gaps between richer and poorer economies. The Digital Progress and Trends Report series will track global digitalization progress and highlight policy trends, debates, and implications for low- and middle-income countries. The series adds to the global efforts to study the progress and trends of digitalization in two main ways: · By compiling, curating, and analyzing data from diverse sources to present a comprehensive picture of digitalization in low- and middle-income countries, including in-depth analyses on understudied topics. · By developing insights on policy opportunities, challenges, and debates and reflecting the perspectives of various stakeholders and the World Bank’s operational experiences. This report, the first in the series, aims to inform evidence-based policy making and motivate action among internal and external audiences and stakeholders. The report will bring global attention to high-performing countries that have valuable experience to share as well as to areas where efforts will need to be redoubled.