External Validity in a Stochastic World: Evidence from Low-Income Countries.

We examine empirically the generalizability of internally valid micro-estimates of causal effects in a fixed population over time when that population is subject to aggregate shocks. Using panel data, we show that the returns to investments in agriculture in India and Ghana, small and medium non-far...

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Publicado en:Review of Economic Studies Vol. 87; no. 1; pp. 343 - 382
Autores principales: Rosenzweig, Mark R, Udry, Christopher
Formato: Artículo
Publicado: Oxford University Press / USA Jan2020
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1093/restud/rdz021
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        atl: External Validity in a Stochastic World: Evidence from Low-Income Countries.
      aug:
        au:
          Rosenzweig, Mark R
          Udry, Christopher
        affil:
          Yale University
          Northwestern University
      su:
        Sri Lanka
        Ghana
        Indonesia
        Low-income countries
        Rainfall anomalies
        Sampling errors
        Rate of return
        Price fluctuations
      sug:
        subj:
          Sri Lanka
          Ghana
          Indonesia
          Low-income countries
          Rainfall anomalies
          Sampling errors
          Rate of return
          Price fluctuations
      keyword:
        Causal estimates
        External validity
        Causal estimates
        External validity
      ab: We examine empirically the generalizability of internally valid micro-estimates of causal effects in a fixed population over time when that population is subject to aggregate shocks. Using panel data, we show that the returns to investments in agriculture in India and Ghana, small and medium non-farm enterprises in Sri Lanka, and schooling in Indonesia fluctuate significantly across time periods. We show how the returns to these investments interact with specific, measurable, and economically relevant aggregate shocks, focusing on rainfall and price fluctuations. We also obtain lower-bound estimates of confidence intervals of the returns based on estimates of the parameters of the distributions of rainfall shocks in our two agricultural samples. We find that even these lower-bound confidence intervals are substantially wider than those based solely on sampling error that are commonly provided in studies, most of which are based on single-year samples. We also find that cross-sectional variation in rainfall cannot be confidently used to replicate within-population rainfall variability. Based on our findings, we discuss methods for incorporating information on external shocks into evaluations of the returns to policy.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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