Lanjouw, Peter Frederik

Person:
Lanjouw, Peter Frederik

Poverty and Inequality Team, Development Economics Research Group, World Bank

Fields of Specialization

Poverty and Inequality Analysis; Rural Development; Small Area Estimation; Village Studies

Departments

Poverty and Inequality Team, Development Economics Research Group, World Bank

Last updated January 31, 2023

Biography

Peter Lanjouw, a Dutch national, is Research Manager of the Poverty and Inequality Team in the Development Economics Research Group of the World Bank. He is also an Honorary Fellow of the Amsterdam Institute of International Development, Netherlands. He completed his Ph.D. in economics from the London School of Economics in 1992. From August 2003 until August 2005, he was a visiting scholar at the Agriculture and Resource Economics department at UC Berkeley, and he held the appointment of Professor of Economics at the VU University of Amsterdam between September 1998 and May 2000. He has taught in the Masters in Development Economics program at the University of Namur, Belgium and has also taught at the Foundation for the Advanced Study of International Development in Tokyo, Japan. His research focuses on various aspects of poverty and inequality measurement as well as on rural development issues.

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Publication Search Results

Now showing 1 - 10 of 14

Vietnam's Evolving Poverty Map : Patterns and Implications for Policy

(World Bank, Washington, DC, 2013-02) Lanjouw, Peter ; Marra, Marleen ; Nguyen, Cuong

This paper uses small area estimation techniques to update Vietnam's province and district-level poverty map to 2009. It finds that poverty rates continue to be highest in the northern and central mountainous regions, where ethnic minorities make up a large fraction of the population. Poverty has fallen in most provinces and districts over this decade, but the pace of poverty reduction has been least pronounced in those localities with high initial poverty or inequality levels. As a result, poverty rates have become more spatially concentrated over time, which is consistent with widely observed growth processes linked to agglomeration. The authors hypothesize that this makes geographic targeting of the poor more relevant as a means to re-balance growing welfare disparities between geographic areas. Simulations indicate that in both 1999 and 2009, geographic targeting for poverty alleviation improves upon a uniform lump-sum transfer and this becomes more evident the more spatially disaggregated the target populations. The analysis further indicates that the gains from geographic targeting have become more pronounced over time in Vietnam. Although poverty reduction in Vietnam has been impressive, further progress may thus warrant increased attention to geographic targeting.
Measuring Poverty Dynamics with Synthetic Panels Based on Cross-Sections

(World Bank, Washington, DC, 2013-06) Dang, Hai-Anh ; Lanjouw, Peter

Panel data conventionally underpin the analysis of poverty mobility over time. However, such data are not readily available for most developing countries. Far more common are the “snap-shots” of welfare captured by cross-section surveys. This paper proposes a method to construct synthetic panel data from cross sections which can provide point estimates of poverty mobility. In contrast to traditional pseudo-panel methods that require multiple rounds of cross-sectional data to study poverty at the cohort level, the proposed method can be applied to settings with as few as two survey rounds and also permits investigation at the more disaggregated household level. The procedure is implemented using cross-section survey data from several countries, spanning different income levels and geographical regions. Estimates fall within the 95 percent confidence interval— or even one standard error in many cases—of those based on actual panel data. The method is not only restricted to studying poverty mobility but can also accommodate investigation of other welfare outcome dynamics.
Imputed Welfare Estimates in Regression Analysis

(World Bank, Washington, D.C., 2004-04) Elbers, Chris ; Lanjouw, Jean O. ; Lanjouw, Peter

The authors discuss the use of imputed data in regression analysis, in particular the use of highly disaggregated welfare indicators (from so-called "poverty maps"). They show that such indicators can be used both as explanatory variables on the right-hand side and as the phenomenon to explain on the left-hand side. The authors try out practical ways of adjusting standard errors of the regression coefficients to reflect the error introduced by using imputed, rather than actual, welfare indicators. These are illustrated by regression experiments based on data from Ecuador. For regressions with imputed variables on the left-hand side, the authors argue that essentially the same aggregate relationships would be found with either actual or imputed variables. They address the methodological question of how to interpret aggregate relationships found in such regressions.
Poverty in India during the 1990s : A Regional Perspective

(World Bank, Washington, DC, 2003-10) Kijima, Yoko ; Lanjouw, Peter

The authors provide estimates of poverty at the regional level in India, spanning the 1990s. Such estimates have not been previously available due to concerns regarding non-comparability of the 1993-94 and 1999-2000 National Sample Survey Organization (NSSO) household survey data. They implement an adjustment procedure to restore comparability based on a methodology developed by Elbers and others (2003). The results indicate a less rapid decline of poverty, at the all-India level than has been suggested by Deaton and Dre (2002), based on a related adjustment methodology. The authors attempt to uncover the source of disagreement across these procedures, by probing a number of their underlying assumptions.
Poverty, Education, and Health in Indonesia : Who Benefits from Public Spending?

(World Bank, Washington, DC, 2001-12) Lanjouw, Peter ; Pradhan, Menno ; Saadah, Fadia ; Sayed, Haneen ; Sparrow, Robert

The authors investigate the extent to which Indonesia's poor benefit from public and private provisioning of education and health services. Drawing on multiple rounds of SUSENAS household surveys, they document a reversal in the rate of decline in poverty and a slowdown in social sector improvements resulting from the economic crisis in the second half of the 1990s. Carrying out traditional static benefit-incidence analysis of public spending in education and health, the authors find patterns consistent with experience in other countries: spending on primary education and primary health care tends to be pro-poor, while spending on higher education and hospitals is less obviously beneficial to the poor. These conclusions are tempered once one allows for economies of scale in consumption which weaken the link between poverty status and household size. The authors also examine the incidence of changes in government spending. They find that the marginal incidence of spending in both junior and senior secondary schooling is more progressive than what static analysis would suggest, consistent with "early capture" by the non-poor of education spending. In the health sector marginal and average incidence analysis point to the same conclusion: the greatest benefit to the poor would come from an increase in primary health care spending.
Simulating the Impact of Geographic Targeting on Poverty Alleviation in Morocco : What Are the Gains from Disaggregation?

(World Bank, Washington, DC, 2008-09) Douidich, Mohammed ; Ezzrari, Abdeljouad ; Lanjouw, Peter

The authors employ the recently completed "poverty map" for Morocco, referring to the year 2004, as a tool for an ex-ante evaluation of the distributional incidence of geographic targeting of public resources. They simulate the impact on poverty of transferring an exogenously given budget to geographically defined sub-groups of the population according to their relative poverty status. In both rural and urban areas, the findings reveal large gains from targeting smaller administrative units, such as communes or districts. However, these gains are still far from the poverty reduction that would be possible had the planners had access to information on household level income or consumption. The results indicate that a useful way forward might be to combine fine geographic targeting using a poverty map with within-community targeting mechanisms.
How Good a Map? Putting Small Area Estimation to the Test

(World Bank, Washington, DC, 2007-03) Demombynes, Gabriel ; Elbers, Chris ; Lanjouw, Jean O. ; Lanjouw, Peter

The authors examine the performance of small area welfare estimation. The method combines census and survey data to produce spatially disaggregated poverty and inequality estimates. To test the method, they compare predicted welfare indicators for a set of target populations with their true values. They construct target populations using actual data from a census of households in a set of rural Mexican communities. They examine estimates along three criteria: accuracy of confidence intervals, bias, and correlation with true values. The authors find that while point estimates are very stable, the precision of the estimates varies with alternative simulation methods. While the original approach of numerical gradient estimation yields standard errors that seem appropriate, some computationally less-intensive simulation procedures yield confidence intervals that are slightly too narrow. The precision of estimates is shown to diminish markedly if unobserved location effects at the village level are not well captured in underlying consumption models. With well specified models there is only slight evidence of bias, but the authors show that bias increases if underlying models fail to capture latent location effects. Correlations between estimated and true welfare at the local level are highest for mean expenditure and poverty measures and lower for inequality measures.
Local Inequality and Project Choice: Theory and Evidence from Ecuador

(World Bank, Washington, DC, 2006-08) Araujo, M. Caridad ; Ferreira, Francisco H.G. ; Lanjouw, Peter ; Özler, Berk

This paper provides evidence consistent with elite capture of Social Fund investment projects in Ecuador. Exploiting a unique combination of data-sets on village-level income distributions, Social Fund project administration, and province level electoral results, the authors test a simple model of project choice when local political power is unequally distributed. In accordance with the predictions of the model, poorer villages are more likely to receive projects that provide excludable (private) goods to the poor, such as latrines. Controlling for poverty, more unequal communities are less likely to receive such projects. Consistent with the hypothesis of elite capture, these results are sensitive to the specific measure of inequality used in the empirical analysis, and are strongest for expenditure shares at the top of the distribution.
Micro-Level Estimation of Welfare

(World Bank, Washington, DC, 2002-10) Elbers, Chris ; Lanjouw, Jean O. ; Lanjouw, Peter

The authors construct and derive the properties of estimators of welfare that take advantage of the detailed information about living standards available in small household surveys and the comprehensive coverage of a census or large sample. By combining the strengths of each, the estimators can be used at a remarkably disaggregated level. They have a clear interpretation, are mutually comparable, and can be assessed for reliability using standard statistical theory. Using data from Ecuador, the authors obtain estimates of welfare measures, some of which are quite reliable for populations as small as 15,000 households--a "town." They provide simple illustrations of their use. Such estimates open up the possibility of testing, at a more convincing intra-country level, the many recent models relating welfare distributions to growth and a variety of socioeconomic and political outcomes.
Small Area Estimation-Based Prediction Methods to Track Poverty : Validation and Applications

( 2011-06-01) Christiaensen, Luc ; Lanjouw, Peter ; Luoto, Jill ; Stifel, David

Tracking poverty is predicated on the availability of comparable consumption data and reliable price deflators. However, regular series of strictly comparable data are only rarely available. Price deflators are also often missing or disputed. In response, poverty prediction methods that track consumption correlates as opposed to consumption itself have been developed. These methods typically assume that the estimated relation between consumption and its predictors is stable over time -- an assumption that cannot usually be tested directly. This study analyzes the performance of poverty prediction models based on small area estimation techniques. Predicted poverty estimates are compared with directly observed levels in two country settings where data comparability over time is not a problem. Prediction models that employ either non-staple food or non-food expenditures or a full set of assets as predictors are found to yield poverty estimates that match observed poverty well. This offers some support to the use of such methods to approximate the evolution of poverty. Two further country examples illustrate how an application of the method employing models based on household assets can help to adjudicate between alternative price deflators.