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On the Validity and Refinement of the Use of Rainfall as Instrument for Transitory Income

  • Surach Tanboon

    (Bank of Thailand)

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    Given that rainfall is externally provided by nature and that it is also correlated with rural income, rainfall shocks seem to be the perfect instrument, as adopted in a popular interpretation of Paxson (1992). However, there are two problems with this reinterpretation: weak instruments and first-stage misspecification. After finding that rainfall is weakly correlated with income, I use Moreira's (2003) pivotal statistics to retest the hypothesis that the propensity to save out of transitory income is one, but still cannot reject the null. Later I find that there are previously untested assumptions on the income equation, and in fact the data indicate that they are invalid. In a new specification the propensity is found to be less than unity.

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    Paper provided by Economic Research Department, Bank of Thailand in its series Working Papers with number 2005-10.

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    Length: 33 pages
    Date of creation: Jan 2005
    Date of revision:
    Handle: RePEc:bth:wpaper:2005-10
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    1. Angrist, Joshua D & Krueger, Alan B, 1995. "Split-Sample Instrumental Variables Estimates of the Return to Schooling," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 225-35, April.
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    3. Marc Gurgand, 2000. "Farmer Education and the Weather : Evidence from Taiwan (1976- 1992)," Working Papers 2000-21, Centre de Recherche en Economie et Statistique.
    4. Anjini Kochar, 1999. "Smoothing Consumption by Smoothing Income: Hours-of-Work Responses to Idiosyncratic Agricultural Shocks in Rural India," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 50-61, February.
    5. Alastair R. Hall & Fernanda P. M. Peixe, 2003. "A Consistent Method for the Selection of Relevant Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 22(3), pages 269-287, January.
    6. Hanan G. Jacoby & Emmanuel Skoufias, 1998. "Testing Theories of Consumption Behavior Using Information on Aggregate Shocks: Income Seasonality and Rainfall in Rural India," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 1-14.
    7. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
    8. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
    9. Kaivan Munshi, 2003. "Networks In The Modern Economy: Mexican Migrants In The U.S. Labor Market," The Quarterly Journal of Economics, MIT Press, vol. 118(2), pages 549-599, May.
    10. Motohiro Yogo, 2004. "Estimating the Elasticity of Intertemporal Substitution When Instruments Are Weak," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 797-810, August.
    11. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-47, February.
    12. Jinyong Hahn & Jerry Hausman, 2003. "Weak Instruments: Diagnosis and Cures in Empirical Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 118-125, May.
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