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An Economist's Primer on Survey Samples

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Author Info

  • William J Carrington
  • John L Eltinge
  • Kristin McCue

Abstract

Survey data underlie most empirical work in economics, yet economists typically have little familiarity with survey sample design and its effects on inference. This paper describes how sample designs depart from the simple random sampling model implicit in most econometrics textbooks, points out where the effects of this departure are likely to be greatest, and describes the relationship between design-based estimators developed by survey statisticians and related econometric methods for regression. Its intent is to provide empirical economists with enough background in survey methods to make informed use of design-based estimators. It emphasizes surveys of households (the source of most public-use files), but also considers how surveys of businesses differ. Examples from the National Longitudinal Survey of Youth of 1979 and the Current Population Survey illustrate practical aspects of design-based estimation.

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File URL: ftp://ftp2.census.gov/ces/wp/2000/CES-WP-00-15.pdf
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Bibliographic Info

Paper provided by Center for Economic Studies, U.S. Census Bureau in its series Working Papers with number 00-15.

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Date of creation: Sep 2000
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Handle: RePEc:cen:wpaper:00-15

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Keywords: CES; economic; research; micro; data; microdata; chief; economist;

References

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  1. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-38, May.
  2. Thomas MaCurdy & Thomas Mroz & R. Mark Gritz, 1998. "An Evaluation of the National Longitudinal Survey on Youth," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 345-436.
  3. J. A. Hausman, 1976. "Specification Tests in Econometrics," Working papers 185, Massachusetts Institute of Technology (MIT), Department of Economics.
  4. Imbens, Guido W. & Lancaster, Tony, 1996. "Efficient estimation and stratified sampling," Journal of Econometrics, Elsevier, vol. 74(2), pages 289-318, October.
  5. Guido W. Imbens & Judith K. Hellerstein, 1996. "Imposing Moment Restrictions from Auxiliary Data by Weighting," NBER Technical Working Papers 0202, National Bureau of Economic Research, Inc.
  6. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  7. Lillard, Lee & Smith, James P & Welch, Finis, 1986. "What Do We Really Know about Wages? The Importance of Nonreporting and Census Imputation," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 489-506, June.
  8. Jeffrey M. Wooldridge, 1999. "Asymptotic Properties of Weighted M-Estimators for Variable Probability Samples," Econometrica, Econometric Society, vol. 67(6), pages 1385-1406, November.
  9. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
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Citations

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Cited by:
  1. Chandran, Ram, 2004. "A Tobit Analysis of WIC Children's Consumption of Pyramid Group Foods," 2004 Annual meeting, August 1-4, Denver, CO 19998, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  2. Evans Jadotte, 2006. "Income Distribution and Poverty in the Republic of Haiti," Working Papers PMMA 2006-13, PEP-PMMA.
  3. Humberto Barreto & Manu Raghav, 2011. "Understanding and Teaching Unequal Probability of Selection," Working Papers 2011-01, DePauw University, Department of Economics and Management.

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