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Aid econometrics: Lessons from a stochastic growth model

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  • Carter, Patrick

Abstract

This paper evaluates the standard empirical methods employed in the study of foreign aid, when the data generating process is a calibrated stochastic growth model in which aid recipients make optimal investment and consumption decisions. When recipients receive a stochastic flow of aid and wish to smooth consumption, standard methods fail to distinguish between the response to transient and permanent aid shocks, and hence yield misleading results concerning the object of interest to policy makers: the long-run impact of aid.

Suggested Citation

  • Carter, Patrick, 2017. "Aid econometrics: Lessons from a stochastic growth model," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 216-232.
  • Handle: RePEc:eee:jimfin:v:77:y:2017:i:c:p:216-232
    DOI: 10.1016/j.jimonfin.2017.06.004
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    Cited by:

    1. Temple, Jonathan & Van de Sijpe, Nicolas, 2017. "Foreign aid and domestic absorption," Journal of International Economics, Elsevier, vol. 108(C), pages 431-443.
    2. Patrick Carter & Jonathan R. W. Temple, 2017. "Virtuous Circles and the Case for Aid," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 65(2), pages 397-425, June.
    3. Kurt Annen & Stephen Kosempel, 2018. "Why Aid-to-GDP Ratios?," Working Papers 1801, University of Guelph, Department of Economics and Finance.
    4. Pierre-Richard Agénor & Nihal Bayraktar, 2020. "Aid Volatility, Human Capital, and Growth," Journal of Human Capital, University of Chicago Press, vol. 14(3), pages 401-448.
    5. repec:oup:jafrec:v:32:y:2022:i:1:p:26-51. is not listed on IDEAS

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    More about this item

    Keywords

    Foreign aid; Stochastic growth model; Convergence; Local projections; Consumption smoothing;
    All these keywords.

    JEL classification:

    • F35 - International Economics - - International Finance - - - Foreign Aid
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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