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Calculating Comparable Statistics from Incomparable Surveys, with an Application to Poverty in India

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Author Info
Alessandro Tarozzi

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Abstract

We develop an intuitive and easily implemented procedure to recover comparability over time of statistics computed using databases made incomparable by changes in survey design. Our methodology can be adopted whenever the statistic of interest satisfies a certain simple moment condition. The moment condition is satisfied by many interesting economic indicators, including a broad range of poverty and inequality measures. The procedure we propose requires the existence of a set of auxiliary variables whose reports are not affected by the different survey design, and whose relation with the main variable of interest is stable across the surveys. The adjusted estimates can be recovered by using a two-step method of moments framework. Root-n consistency follows easily under regularity conditions. Because most household surveys adopt a multi-stage design, we provide expressions for the asymptotic variance which are robust to the presence of clustering and stratification. We use our adjustment procedure to estimate poverty counts from the 55th Round of the Indian National Sample Survey, a large household survey carried out in 1999-2000. Due to important changes in the adopted questionnaire the unadjusted figures are likely to understate poverty relative to the previous rounds. We provide evidence supporting the plausibility of the identifying assumptions and we conclude that most of the very large reduction in poverty implied by the unadjusted figures is real

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Paper provided by Econometric Society in its series Econometric Society 2004 North American Winter Meetings with number 280.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nawm04:280

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Related research
Keywords: Poverty; India; Method of Moments; Household Surveys;

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Find related papers by JEL classification:
O53 - Economic Development, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East
I32 - Health, Education, and Welfare - - Welfare and Poverty - - - Measurement and Analysis of Poverty
C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Lanjouw, Jean Olson & Lanjouw, Peter, 2001. "How to Compare Apples and Oranges: Poverty Measurement Based on Different Definitions of Consumption," Review of Income and Wealth, Blackwell Publishing, vol. 47(1), pages 25-42, March. [Downloadable!] (restricted)
  2. Martin Browning & Thomas F. Crossley & Guglielmo Weber, 2003. "Asking consumption questions in general purpose surveys," Economic Journal, Royal Economic Society, vol. 113(491), pages F540-F567, November. [Downloadable!] (restricted)
    Other versions:
  3. John Gibson & Jikun Huang & Scott Rozelle, 2003. "Improving Estimates of Inequality and Poverty from Urban China's Household Income and Expenditure Survey," Review of Income and Wealth, Blackwell Publishing, vol. 49(1), pages 53-68, 03. [Downloadable!] (restricted)
    Other versions:
  4. Erich Battistin & Raffaele Miniaci & Guglielmo Weber, 2003. "What do we learn from recall consumption data?," Temi di discussione (Economic working papers) 466, Bank of Italy, Economic Research Department. [Downloadable!]
    Other versions:
  5. Angus Deaton & Alessandro Tarozzi, 2000. "Prices and poverty in India," Working Papers 213, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies.. [Downloadable!]
  6. Bhattacharya, Debopam, 2005. "Asymptotic inference from multi-stage samples," Journal of Econometrics, Elsevier, vol. 126(1), pages 145-171, May. [Downloadable!] (restricted)
  7. Gibson, John, 2002. " Why Does the Engel Method Work? Food Demand, Economies of Size and Household Survey Methods," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 341-59, September. [Downloadable!] (restricted)
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  8. Angus Deaton & Jean Dreze, 2002. "Poverty and Inequality in India: A Re-Examination," Working Papers 184, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies.. [Downloadable!]
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  9. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, 07. [Downloadable!] (restricted)
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  10. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January. [Downloadable!] (restricted)
  11. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," Review of Economic Studies, Blackwell Publishing, vol. 72(1), pages 1-19, 01. [Downloadable!] (restricted)
  12. Jeffrey M. Wooldridge, 1999. "Asymptotic Properties of Weighted M-Estimators for Variable Probability Samples," Econometrica, Econometric Society, vol. 67(6), pages 1385-1406, November.
  13. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March. [Downloadable!] (restricted)
  14. Gibson, John & Huang, Jikun & Rozelle, Scott, 2001. "Why is income inequality so low in China compared to other countries?: The effect of household survey methods," Economics Letters, Elsevier, vol. 71(3), pages 329-333, June. [Downloadable!] (restricted)
  15. Erich Battistin, 2002. "Errors in Survey Reports of Consumption Expenditures," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C4-2, International Conferences on Panel Data. [Downloadable!]
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  16. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition and stratification," CeMMAP working papers CWP11/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
  17. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
  18. Orazio Attanasio & Erich Battistin & Hidehiko Ichimura, 2004. "What Really Happened to Consumption Inequality in the US?," NBER Working Papers 10338, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Eric V. Edmonds & Nina Pavcnik & Petia Topalova, 2007. "Trade Adjustment and Human Capital Investments: Evidence from Indian Tariff Reform," NBER Working Papers 12884, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  2. Daniel Egel & Bryan S. Graham & Cristine Campos de Xavier Pinto, 2008. "Inverse Probability Tilting and Missing Data Problems," NBER Working Papers 13981, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  3. Eric Edmonds, 2007. "Trade Adjustment and Human Capital Investments: Evidence from Indian Tariff Reform," Working Papers id:999, esocialsciences.com. [Downloadable!]
  4. Michael Grimm & Isabel Günther, 2005. "Growth and Poverty in Burkina Faso: A Reassessment of the Paradox," Discussion Papers of DIW Berlin 482, DIW Berlin, German Institute for Economic Research. [Downloadable!]
    Other versions:
  5. Melanie Morten, 2006. "Indian Poverty during the 1990s: Resolving Methodological Issues from the 55th NSS Round," ASARC Working Papers 2006-07, Australian National University, Australia South Asia Research Centre. [Downloadable!]
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