Jolliffe, Dean

Development Economics Data Group, The World Bank
Profile Picture
Author Name Variants
Fields of Specialization
Food security, Education economics, Health economics, Data collection methods, Measuring Poverty
Development Economics Data Group, The World Bank
Externally Hosted Work
Contact Information
Last updated August 29, 2023
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 324 Scopus

Publication Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    From Tragedy to Renaissance : Improving Agricultural Data for Better Policies
    (Taylor and Francis, 2015-02-13) Carletto, Calogero ; Jolliffe, Dean ; Banerjee, Raka
    Agricultural development is an essential engine of growth and poverty reduction, yet agricultural data suffer from poor quality and narrow sectoral focus. There are several reasons for this: (1) difficult-to-measure smallholder agriculture is prevalent in poor countries; (2) agricultural data are collected with little coordination across sectors; and (3) poor analysis undermines the demand for high-quality data. This article argues that initiatives like the Global Strategy to Improve Agricultural and Rural Statistics bode well for the future. Moving from Devarajan’s statistical tragedy’ to Kiregyera’s statistical ‘renaissance’ will take a continued long-term effort by individual countries and development partners.
  • Thumbnail Image
    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.
  • Thumbnail Image
    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.