Person:
Jolliffe, Dean

Development Economics Data Group, The World Bank
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Fields of Specialization
Food security, Education economics, Health economics, Data collection methods, Measuring Poverty
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Development Economics Data Group, The World Bank
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Last updated: August 29, 2023
Biography
Dean Jolliffe is a lead economist in the Development Data Group at the World Bank. He is a member of the Living Standards Measurement Study team and co-lead of the team that works on global poverty measurement (PovcalNet). Previously, he worked in the Research Group and the South Asia region of the World Bank. Prior to joining the World Bank, he was a research economist with the Economic Research Service of the U.S. Department of Agriculture, an assistant professor at Charles University Center for Economic Research and Graduate Education in Prague, an adjunct professor at Johns Hopkins University School of Advanced International Studies, an adjunct professor at Georgetown University Public Policy Institute, and a postdoctoral fellow at the International Food Policy Research Institute. Dean holds appointments as a research fellow with the Institute for the Study of Labor, as a co-opted council member of the International Association for Research in Income and Wealth, and as a fellow of the Global Labor Organization. He received his PhD in economics from Princeton University.
Citations 344 Scopus

Publication Search Results

Now showing 1 - 5 of 5
  • Publication
    Land Fragmentation and Food Insecurity in Ethiopia
    (World Bank, Washington, DC, 2018-08) Knippenberg, Erwin; Jolliffe, Dean; Hoddinott, John
    This paper revisits the economic consequences of land fragmentation, taking seriously concerns regarding the exogeneity of fragmentation, its measurement and the importance of considering impacts in terms of welfare metrics. Using data that are well-suited to addressing these issues, the analysis finds that land fragmentation reduces food insecurity. This result is robust to how fragmentation is measured and to how exogeneity concerns are addressed. Further, the paper finds that land fragmentation mitigates the adverse effects of low rainfall on food security. This is because households with diverse parcel characteristics can grow a greater variety of crop types.
  • Publication
    Do Different Types of Assets have Differential Effects on Child Education?: Evidence from Tanzania
    (World Bank, Washington, DC, 2017-05) Kafle, Kashi; Jolliffe, Dean; Winter-Nelson, Alex
    To assess the conventional view that assets uniformly improve childhood development through wealth effects, this paper tests whether different types of assets have different effects on child education. The analysis indicates that household durables and housing quality have the expected positive effects, but agricultural assets have adverse effects on highest grade completed and no effects on exam performance. Extending the standard agricultural-household model by explicitly including child labor, the study uses three waves of panel data from Tanzania to estimate the effects of household assets on child education. The analysis corrects for the endogeneity of assets and uses a Hausman-Taylor instrumental variable panel data estimator to identify the effects of time-invariant observables and more efficiently control for time-invariant unobservables. The negative effect of agricultural assets is more pronounced among rural children and children from farming households, presumably due to the higher opportunity cost of their schooling.
  • Publication
    Food Insecurity and Rising Food Prices: What Do We Learn from Experiential Measures?
    (World Bank, Washington, DC, 2018-05) Seff, Ilana; Jolliffe, Dean; de la Fuente, Alejandro
    Throughout many countries in the world, the measurement of food security currently includes accounting for the importance of perception and anxiety about meeting basic food needs. Using panel data from Malawi, this paper shows that worrying about food security is linked to self-reports of having experienced food insecurity, and the analysis provides evidence that rapidly rising food prices are a source of the anxiety and experiences of food insecurity. This finding controls for individual-level fixed effects and changes in the economic well-being of the individual. A particularly revealing finding of the importance of accounting for anxiety in assessing food insecurity is that individuals report a significant increase in experiences of food insecurity in the presence of rapidly rising food prices even when dietary diversity and caloric intake is stable.
  • Publication
    Land Productivity and Plot Size: Is Measurement Error Driving the Inverse Relationship?
    (Elsevier, 2018-01) Desiere, Sam; Jolliffe, Dean
    This paper revisits the decades-old puzzle of the inverse plot-size productivity relationship (IR), which states that land productivity decreases as plot size increases. While existing studies define land productivity or yields as self-reported production divided by plot size, we consider an alternative approach to estimating yields based on crop cuts. The crop-cut method entails measuring and harvesting randomly selected subplots by trained technicians, and is recommended by the Food and Agricultural Organization for the accurate measurement of crop production. Using data of rural Ethiopia, our analysis indicates that the IR is strong when based on self-reported production, but disappears when based on crop-cut estimates. Our inference from these findings is that the IR is an artifact of systematic over-reporting of production by farmers on small plots, and under-reporting on larger plots. We also discuss how rejecting the inverse plot-size productivity relationship has significant implications for the inverse farm-size productivity relationship.
  • Publication
    Land Productivity and Plot Size: Is Measurement Error Driving the Inverse Relationship?
    (World Bank, Washington, DC, 2017-07) Desiere, Sam; Jolliffe, Dean
    This paper revisits the decades-old puzzle of the inverse plot-size productivity relationship, which states that land productivity decreases as plot size increases. Existing empirical studies on the inverse plot-size productivity relationship define land productivity or yields as self-reported production divided by plot size. This paper considers an alternative approach to estimating yields based on crop cuts. The crop-cut method entails measuring and harvesting randomly selected subplots by trained technicians, and is recommended by the Food and Agriculture Organization for the accurate measurement of crop production. Using data representative of rural Ethiopia, the analysis indicates that the inverse relationship is strong when based on self-reported production, but disappears when based on crop-cut estimates. The inference from these findings is that the inverse relationship is an artifact of systematic overreporting of production by farmers on small plots, and underreporting on larger plots. The paper also discusses how rejecting the inverse plot-size productivity relationship has significant implications for the inverse farm-size productivity relationship.