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Estimating a dose-response function with heterogeneous response to confounders when treatment is continuous and endogenous

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  • Christopher Baum
  • Giovanni Cerulli, CNR-IRCrES

Abstract

To improve policy analysis by formulating a new approach to the estimation of treatment effects which vary in magnitude among treated units. The paper's approach to estimating an average treatment effect (ATE) and counterpart measures for the treated (ATET) and untreated (ATENT) allows for the estimation of a functional relationship between the magnitude of treatment and the treated units' response. In a study of public subsidies to private Italian firms' R&D efforts, we find significant variation in the degree to which public funding 'crowds out' private spending on innovative activities.

Suggested Citation

  • Christopher Baum & Giovanni Cerulli, CNR-IRCrES, 2016. "Estimating a dose-response function with heterogeneous response to confounders when treatment is continuous and endogenous," EcoMod2016 9388, EcoMod.
  • Handle: RePEc:ekd:009007:9388
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    References listed on IDEAS

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    1. David, Paul A. & Hall, Bronwyn H. & Toole, Andrew A., 2000. "Is public R&D a complement or substitute for private R&D? A review of the econometric evidence," Research Policy, Elsevier, vol. 29(4-5), pages 497-529, April.
    2. Giovanni Cerulli, 2010. "Modelling and Measuring the Effect of Public Subsidies on Business R&D: A Critical Review of the Econometric Literature," The Economic Record, The Economic Society of Australia, vol. 86(274), pages 421-449, September.
    3. Wooldridge, Jeffrey M., 2003. "Further results on instrumental variables estimation of average treatment effects in the correlated random coefficient model," Economics Letters, Elsevier, vol. 79(2), pages 185-191, May.
    4. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    5. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, September.
    6. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    7. Giovanni Cerulli, 2015. "ctreatreg: Command for fitting dose–response models under exogenous and endogenous treatment," Stata Journal, StataCorp LP, vol. 15(4), pages 1019-1045, December.
    8. Wooldridge, Jeffrey M., 1997. "On two stage least squares estimation of the average treatment effect in a random coefficient model," Economics Letters, Elsevier, vol. 56(2), pages 129-133, October.
    9. Michela Bia & Carlos A. Flores & Alfonso Flores-Lagunes & Alessandra Mattei, 2014. "A Stata package for the application of semiparametric estimators of dose–response functions," Stata Journal, StataCorp LP, vol. 14(3), pages 580-604, September.
    10. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    11. Giovanni Cerulli, 2014. "ivtreatreg: A command for fitting binary treatment models with heterogeneous response to treatment and unobservable selection," Stata Journal, StataCorp LP, vol. 14(3), pages 453-480, September.
    12. Barbara Guardabascio & Marco Ventura, 2014. "Estimating the dose–response function through a generalized linear model approach," Stata Journal, StataCorp LP, vol. 14(1), pages 141-158, March.
    13. Michela Bia & Alessandra Mattei, 2008. "A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score," Stata Journal, StataCorp LP, vol. 8(3), pages 354-373, September.
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    Cited by:

    1. Avenyo, Elvis Korku & Konte, Maty & Mohnen, Pierre, 2019. "The employment impact of product innovations in sub-Saharan Africa: Firm-level evidence," Research Policy, Elsevier, vol. 48(9), pages 1-1.

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