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A short introduction to the computation of standard errors for AF Measures

Gaston Yalonetzky

  • Computing the standard errors of averages in simple surveys.
  • Computing the asymptotic standard errors for ratios (like the average deprivation score (A)).
  • Asymptotic standard errors fro percentage changes over time (cross-sections and panel datasets).
  • Discussion of the importance of complex survey design for standard errors.

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Guide to video

00:00 Introduction to standard error and the two different types; statistical and analytical standard errors, here the analytical (sub population) approach is applied

10:45 Outline of the lecture

Part 1: The Formulas of Standard Error Computations in the AF method

12:57 Define and describe standard errors in general (sub-population approach)

17:04 Computing the standard errors of the censored headcount

24:15 Computing the asymptotic standard errors of the average deprivation score (Yalonetzky (2011))

33:17 Computing the standard errors for percentage change over time

35:16  Computations in cross section data

36:21 Computations in panel data

Part 2: The Importance of Survey Design for Standard Error Computations

39:17 Computing standard errors in complex surveys (Deaton (1997))

40:52 Define strata

43:08 Define cluster

45:48 Define sample weight

48:18 Explain the STATA command: SVY for computing standard errors

54:16 An example that shows that sample design is not a trivial matter (Lynn (2007))

59:40 Concluding remarks, comparing the sub and final population approach to standard errors.

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Key readings covered in these lectures

Deaton, A. (1997). The analysis of household surveys. A microeconometric approach to development policy. The World Bank

Yalonetzky, G (2011). A note on the standard errors of the members of the Alkire Foster family and its components. OPHI Working Paper 25a (work in progress)

Lynn, P. (2007). Hypothesis testing using complex survey data. Course presented at the University of Essex