IDEAS home Printed from https://ideas.repec.org/p/bth/wpaper/2005-10.html
   My bibliography  Save this paper

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

Author

Listed:
  • Surach Tanboon

    (Bank of Thailand)

Abstract

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.

Suggested Citation

  • Surach Tanboon, 2005. "On the Validity and Refinement of the Use of Rainfall as Instrument for Transitory Income," Working Papers 2005-10, Monetary Policy Group, Bank of Thailand.
    • Handle: RePEc:bth:wpaper:2005-10
    as

    Download full text from publisher

    File URL: http://www.bot.or.th/Thai/EconomicConditions/Publication/DiscusPaper/DocLip_discussion/dp012005rurath_thai.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Hall, Alastair R & Rudebusch, Glenn D & Wilcox, David W, 1996. "Judging Instrument Relevance in Instrumental Variables Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 37(2), pages 283-298, May.
    3. 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 225-235, April.
    4. 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.
    5. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    6. Esther Duflo & Christopher Udry, 2003. "Intrahousehold Resource Allocation in Côte D'ivoire: Social Norms, Separate Accounts and Consumption Choices," Working Papers 857, Economic Growth Center, Yale University.
    7. Gurgand, Marc, 2003. "Farmer education and the weather: evidence from Taiwan (1976-1992)," Journal of Development Economics, Elsevier, vol. 71(1), pages 51-70, June.
    8. 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.
    9. Joshua D. Angrist & Alan B. Krueger, 1993. "Split Sample Instrumental Variables," Working Papers 699, Princeton University, Department of Economics, Industrial Relations Section..
    10. Pedro Albarran & Orazio P. Attanasio, 2003. "Limited Commitment and Crowding out of Private Transfers: Evidence from a Randomised Experiment," Economic Journal, Royal Economic Society, vol. 113(486), pages 77-85, March.
    11. 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.
    12. Kaivan Munshi, 2003. "Networks in the Modern Economy: Mexican Migrants in the U. S. Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(2), pages 549-599.
    13. Paxson, Christina H, 1992. "Using Weather Variability to Estimate the Response of Savings to Transitory Income in Thailand," American Economic Review, American Economic Association, vol. 82(1), pages 15-33, March.
    14. 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.
    15. 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.
    16. Ersado, Lire, 2006. "Income diversification in Zimbabwe : welfare implications from urban and rural areas," Policy Research Working Paper Series 3964, The World Bank.
    17. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September.
    18. 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 221-247, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jean-Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 767-808, November.
    2. Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 133-153, July.
    3. John C. Chao & Norman R. Swanson, 2005. "Consistent Estimation with a Large Number of Weak Instruments," Econometrica, Econometric Society, vol. 73(5), pages 1673-1692, September.
    4. Chao, John & Swanson, Norman R., 2007. "Alternative approximations of the bias and MSE of the IV estimator under weak identification with an application to bias correction," Journal of Econometrics, Elsevier, vol. 137(2), pages 515-555, April.
    5. Jean-Marie Dufour & Mohamed Taamouti, 2005. "Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments," Econometrica, Econometric Society, vol. 73(4), pages 1351-1365, July.
    6. DUFOUR, Jean-Marie & JASIAK, Joanna, 1998. "Finite-Sample Inference Methods for Simultaneous Equations and Models with Unobserved and Generated Regressors," Cahiers de recherche 9812, Universite de Montreal, Departement de sciences economiques.
    7. Norman R. Swanson & John C. Chao, 2004. "Estimation and Testing Using Jackknife IV in Heteroskedastic Regressions with Many Weak Instruments," Econometric Society 2004 Far Eastern Meetings 668, Econometric Society.
    8. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2006. "Inflation dynamics and the New Keynesian Phillips Curve: An identification robust econometric analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1707-1727.
    9. Chao, John C. & Swanson, Norman R. & Hausman, Jerry A. & Newey, Whitney K. & Woutersen, Tiemen, 2012. "Asymptotic Distribution Of Jive In A Heteroskedastic Iv Regression With Many Instruments," Econometric Theory, Cambridge University Press, vol. 28(1), pages 42-86, February.
    10. John C. Chao & Norman R. Swanson, 2003. "Asymptotic Normality of Single-Equation Estimators for the Case with a Large Number of Weak Instruments," Departmental Working Papers 200312, Rutgers University, Department of Economics.
    11. Doko Tchatoka, Firmin Sabro, 2012. "Specification Tests with Weak and Invalid Instruments," MPRA Paper 40185, University Library of Munich, Germany.
    12. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    13. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    14. Doko Tchatoka, Firmin & Dufour, Jean-Marie, 2020. "Exogeneity tests, incomplete models, weak identification and non-Gaussian distributions: Invariance and finite-sample distributional theory," Journal of Econometrics, Elsevier, vol. 218(2), pages 390-418.
    15. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    16. Michael P. Murray, 2006. "Avoiding Invalid Instruments and Coping with Weak Instruments," Journal of Economic Perspectives, American Economic Association, vol. 20(4), pages 111-132, Fall.
    17. Nikolaj Malchow-Møller & Jakob R. Munch & Jan Rose Skaksen, 2012. "Do Immigrants Affect Firm-Specific Wages?," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(4), pages 1267-1295, December.
    18. Isaiah Andrews & Timothy B. Armstrong, 2017. "Unbiased instrumental variables estimation under known first‐stage sign," Quantitative Economics, Econometric Society, vol. 8(2), pages 479-503, July.
    19. Gomes, Fábio Augusto Reis & Paz, Lourenço S., 2013. "Estimating the elasticity of intertemporal substitution: Is the aggregate financial return free from the weak instrument problem?," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 63-75.
    20. Doko Tchatoka, Firmin Sabro & Dufour, Jean-Marie, 2008. "Instrument endogeneity and identification-robust tests: some analytical results," MPRA Paper 29613, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bth:wpaper:2005-10. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pornpinun Chantapacdepong (email available below). General contact details of provider: https://edirc.repec.org/data/botgvth.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.