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CTREATREG: Stata module for estimating dose-response models under exogenous and endogenous treatment

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Abstract

This paper presents ctreatreg, a Stata module for estimating a dose-response function when: (i) treatment is continuous, (ii) individuals may react heterogeneously to observable confounders, and (iii) selection-into-treatment may be endogenous. Two estimation procedures are implemented: OLS under Conditional Mean Independence, and InstrumentalVariables (IV) under selection endogeneity. A Monte Carlo experiment to test the reliability of the proposed command is finally set out. Length: 25 pages

Suggested Citation

  • Giovanni Cerulli, 2014. "CTREATREG: Stata module for estimating dose-response models under exogenous and endogenous treatment," CERIS Working Paper 201405, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
    • Handle: RePEc:csc:cerisp:201405
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    1. Giovanni Cerulli, 2012. "contreatreg: A Stata module for estimating dose response treatment models under (continuous) treatment endogeneity and heterogeneous response to observable confounders," Italian Stata Users' Group Meetings 2012 03, Stata Users Group.
    2. 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.
    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    4. 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 LLC, vol. 8(3), pages 354-373, September.
    5. BIA Michela & FLORES Carlos A. & MATTEI Alessandra, 2011. "Nonparametric Estimators of Dose-Response Functions," LISER Working Paper Series 2011-40, Luxembourg Institute of Socio-Economic Research (LISER).
    6. 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.
    7. Giovanni Cerulli, 2012. "Ivtreatreg: a new STATA routine for estimating binary treatment models with heterogeneous response to treatment under observable and unobservable selection," CERIS Working Paper 201203, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
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    Cited by:

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    2. Michel Dumont, 2015. "Working Paper 05-15 - Evaluation of federal tax incentives for private R&D in Belgium: An update," Working Papers 1505, Federal Planning Bureau, Belgium.
    3. Giovanni Cerulli & Bianca Potì, 2014. "The Impact of Public Support Intensity on Business R&D: Evidence from a Dose-Response Approach," ERSA conference papers ersa14p625, European Regional Science Association.
    4. Portal, Márcio Telles & Laureano, Luis, 2017. "Does Brazilian allowance for corporate equity reduce the debt bias? Evidences of rebound effect and ownership-induced ACE clientele," Research in International Business and Finance, Elsevier, vol. 42(C), pages 480-495.
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    More about this item

    Keywords

    Stata commands; treatment effects; dose-response function; continuous treatment; Monte Carlo; R&D support JEL Codes: C21; C87; D04;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation

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