Person:
Lanjouw, Peter Frederik
Author Name Variants
Fields of Specialization
Poverty and Inequality Analysis; Rural Development; Small Area Estimation; Village Studies
Degrees
Departments
Poverty and Inequality Team, Development Economics Research Group, World Bank
Externally Hosted Work
Contact Information
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.
Publication Search Results
1 - 7 of 7
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Publication
Poverty Alleviation through Geographic Targeting: How Much Does Disaggregation Help?
(World Bank, Washington, D.C., 2004-10)Using recently completed "poverty maps" for Cambodia, Ecuador, and Madagascar, the authors simulate the impact on poverty of transferring an exogenously given budget to geographically defined subgroups of the population according to their relative poverty status. They find large gains from targeting smaller administrative units, such as districts or villages. But 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 suggest that a useful way forward might be to combine fine geographic targeting using a poverty map with within-community targeting mechanisms. -
Publication
Imputed Welfare Estimates in Regression Analysis
(World Bank, Washington, D.C., 2004-04)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. -
Publication
How Good a Map? Putting Small Area Estimation to the Test
(World Bank, Washington, DC, 2007-03)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. -
Publication
Local Inequality and Project Choice: Theory and Evidence from Ecuador
(World Bank, Washington, DC, 2006-08)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. -
Publication
Brazil's Bolsa Escola Program : The Role of Local Governance in Decentralized Implementation
(World Bank, Washington, DC, 2005-12)This study analyzes the role of local governance in the implementation of Bolsa Escola, a decentralized conditional cash transfer program for child education in Brazil. It is based on a survey of 260 municipalities in four states of the Northeast. The analysis focuses on program implementation. Results show that there was considerable confusion over the municipality s role in beneficiary selection and consequently much heterogeneity in implementation across municipalities. Social control councils as direct accountability mechanisms were often not in place and poorly informed, weakening their role. However, electoral support for incumbent mayors rewarded larger program coverage, presence of councils, and low leakages of benefits to the non-poor. -
Publication
Intra-generational Mobility and Repeated Cross-Sections : A Three-country Validation Exercise
( 2011-12-01)This paper validates a recently proposed method to estimate intra-generational mobility through repeated cross-sectional surveys. The technique allows the creation of a "synthetic panel" -- done by predicting future or past household income using a set of simple modeling and error structure assumptions -- and thus permits the estimation of lower and upper bounds on directional mobility measures. The authors validate the approach in three different settings where good panel data also exist (Chile, Nicaragua, and Peru). In doing so, they also carry out a number of refinements to the validation procedure. The results are broadly encouraging: the methodology performs well in all three settings, especially in cases where richer model specifications can be estimated. The technique does equally well in predicting short and long-term mobility patterns and is robust to a broad set of additional "stress" and sensitivity tests. Overall, the paper lends support to the application of this approach to settings where panel data are absent. -
Publication
Brazil within Brazil : Testing the Poverty Map Methodology in Minas Gerais
(World Bank, Washington, DC, 2008-02)The small-area estimation technique developed for producing poverty maps has been applied in a large number of developing countries. Opportunities to formally test the validity of this approach remain rare due to lack of appropriately detailed data. This paper compares a set of predicted welfare estimates based on this methodology against their true values, in a setting where these true values are known. A recent study draws on Monte Carlo evidence to warn that the small-area estimation methodology could significantly over-state the precision of local-level estimates of poverty, if underlying assumptions of spatial homogeneity do not hold. Despite these concerns, the findings in this paper for the state of Minas Gerais, Brazil, indicate that the small-area estimation approach is able to produce estimates of welfare that line up quite closely to their true values. Although the setting considered here would seem, a priori, unlikely to meet the homogeneity conditions that have been argued to be essential for the method, confidence intervals for the poverty estimates also appear to be appropriate. However, this latter conclusion holds only after carefully controlling for community-level factors that are correlated with household level welfare.