Person:
Jolliffe, Dean
Author Name Variants
Fields of Specialization
Food security,
Education economics,
Health economics,
Data collection methods,
Measuring Poverty
Degrees
ORCID
External Links
Departments
Development Economics Data Group, The World Bank
Externally Hosted Work
Contact Information
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.
Publication Search Results
1 - 9 of 9
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Publication
Rising Food Prices and Coping Strategies : Household-level Evidence from Afghanistan
(Taylor and Francis, 2012-02-28)This article investigates the impact of rising wheat prices on household food security in Afghanistan. Exploiting a unique nationally-representative household survey, we find evidence of large declines in the real value of per capita food consumption. Smaller price elasticities with respect to calories than with respect to food consumption suggest that households trade off quality for quantity as they move away from nutrient-rich foods such as meat and vegetables toward staple foods. Our work improves upon country-level simulation studies by providing estimates of actual household food security during a price shock in one of the world's poorest, most food-insecure countries. -
Publication
Conflict, Food Price Shocks, and Food Insecurity : The Experience of Afghan Households
(Elsevier, 2013-10)Using nationally-representative household survey data and confidential geo-coded data on violence, we examine the relationship between conflict and food security in Afghanistan. Spatial mappings of the raw data reveal large variations in levels of food insecurity and conflict across the country; surprisingly, high conflict provinces are not the most food insecure. Using a simple bivariate regression model of conflict (violent incidents and persons killed or injured) on food security (calorie intake and the real value of food consumed), we find mixed associations. But once we move to a multivariate framework, accounting for household characteristics and key commodity prices, we find robust evidence that in Afghanistan levels of conflict and food security are negatively correlated. We also find that households in provinces with higher levels of conflict experience muted declines in food security due to staple food price increases relative to households in provinces with lower levels of conflict, perhaps because the former are more disconnected from markets. Gaining a better understanding of linkages between conflict and food security and knowing their spatial distributions can serve to inform policymakers interested in targeting scarce resources to vulnerable populations, for example, through the placement of strategic grain reserves or targeted food assistance programs. -
Publication
From Tragedy to Renaissance : Improving Agricultural Data for Better Policies
(World Bank Group, Washington, DC, 2015-01)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: (i) difficult-to-measure smallholder agriculture is prevalent in poor countries, (ii) agricultural data are collected with little coordination across ministries of agriculture and national statistics offices, and (iii) poor analysis undermines the demand for high-quality data. This paper 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. -
Publication
From Tragedy to Renaissance : Improving Agricultural Data for Better Policies
(Taylor and Francis, 2015-02-13)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. -
Publication
Food Counts - Measuring Food Consumption and Expenditures in Household Consumption and Expenditure Surveys: Introduction to the Special Issue
(Elsevier, 2017-10)This introductory paper presents the results of an international multi-disciplinary research project on the measurement of food consumption in national household surveys. Food consumption data from household surveys are possibly the single most important source of information on poverty, food security, and nutrition outcomes at national, sub-national and household level, and contribute building blocks to global efforts to monitor progress towards the major international development goals. The paper synthesizes case studies from a diverse set of developing and OECD countries, looking at some of the main outstanding research issues as identified by a recent international assessment of 100 existing national household surveys (Smith et al., 2014). The project mobilized expertise from different disciplines (statistics, economics, food security, nutrition) to work towards enhancing our understanding of how to improve the quality and availability of food consumption and expenditure data, while making them more valuable for a diverse set of users. The individual studies summarized in this paper analyze, both theoretically and empirically, how different surveys design options affect the quality of the data being collected and, in turn, the implications for statistical inference and policy analysis. The conclusions and recommendations derived from this collection of studies will be instrumental in advancing the methodological agenda for the collection of household level food data, and will provide national statistical offices and survey practitioners worldwide with practical insights for survey design, while providing poverty, food and nutrition policymakers with greater understanding of these issues, as well as improved tools for and better guidance in policy formulation. -
Publication
Food Insecurity and Rising Food Prices: What Do We Learn from Experiential Measures?
(World Bank, Washington, DC, 2018-05)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)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)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. -
Publication
Land Fragmentation and Food Insecurity in Ethiopia
(World Bank, Washington, DC, 2018-08)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.