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Measuring The Impact Of Financial Intermediation: Linking Contract Theory To Econometric Policy Evaluation

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  • Townsend, Robert M.
  • Urzua, Sergio S.

Abstract

We study the impact that financial intermediation can have on productivity through the alleviation of credit constraints in occupation choice and/or an improved allocation of risk, using both static and dynamic structural models as well as reduced-form OLS and IV regressions. Our goal in this paper is to bring these two strands of the literature together. Even though, under certain assumptions, IV regressions can accurately recover the true model-generated local average treatment effect, this is quantitatively different, in order of magnitude and even sign, from other policy impact parameters (e.g., ATE and TT). We also show that laying out clearly alternative models can guide the search for instruments. On the other hand, adding more margins of decision, that is, occupation choice and intermediation jointly, or adding more periods with promised utilities as key state variables, as in optimal multiperiod contracts, can cause the misinterpretation of IV as the causal effect of interest.

Suggested Citation

  • Townsend, Robert M. & Urzua, Sergio S., 2009. "Measuring The Impact Of Financial Intermediation: Linking Contract Theory To Econometric Policy Evaluation," Macroeconomic Dynamics, Cambridge University Press, vol. 13(S2), pages 268-316, September.
    • Handle: RePEc:cup:macdyn:v:13:y:2009:i:s2:p:268-316_09
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    Cited by:

    1. Barnett, William A. & Erwin Diewert, W. & Zellner, Arnold, 2011. "Introduction to measurement with theory," Journal of Econometrics, Elsevier, vol. 161(1), pages 1-5, March.
    2. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2019. "Best linear approximations to set identified functions: with an application to the gender wage gap," CeMMAP working papers CWP09/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Arun Chandrasekhar & Victor Chernozhukov & Francesca Molinari & Paul Schrimpf, 2012. "Inference for best linear approximations to set identified functions," CeMMAP working papers 43/12, Institute for Fiscal Studies.
    4. Alem, Mauro & Townsend, Robert M., 2014. "An evaluation of financial institutions: Impact on consumption and investment using panel data and the theory of risk-bearing," Journal of Econometrics, Elsevier, vol. 183(1), pages 91-103.

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