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Synthetic data: an endogeneity simulation

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  • Carbajal De Nova, Carolina

Abstract

This paper uses synthetic data and different scenarios to test treatments for endogeneity problems under different parameter settings. The model uses initial conditions and provides the solution for a hypothetical equation system with an embedded endogeneity problem. The behavioral and statistical assumptions are underlined as they are used through this research. A methodology is proposed for constructing and computing simulation scenarios. The econometric modeling of the scenarios is developed accordingly with the feedback obtained from previous scenarios. The inputs for these scenarios are synthetic data, which are constructed using random number machines and/or Monte Carlo simulations. The outputs of the scenarios are the model estimators. The research results demonstrated that a treatment for endogeneity can be developed as the sample size increases.

Suggested Citation

  • Carbajal De Nova, Carolina, 2014. "Synthetic data: an endogeneity simulation," MPRA Paper 79158, University Library of Munich, Germany, revised 11 May 2017.
    • Handle: RePEc:pra:mprapa:79158
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    References listed on IDEAS

    as
    1. Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, July.
    2. P.A.V.B. Swamy & Jatinder S. Mehta & I-Lok Chang, 2017. "Endogeneity, Time-Varying Coefficients, and Incorrect vs. Correct Ways of Specifying the Error Terms of Econometric Models," Econometrics, MDPI, vol. 5(1), pages 1-17, February.
    3. Aris Spanos, 2011. "Foundational Issues in Statistical Modeling: Statistical Model Specification and Validation," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 2(47), October.
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    Cited by:

    1. Carbajal-De-Nova, Carolina & Venegas-Martínez, Francisco, 2019. "Synthetic Estimation of Dynamic Panel Models When Either N or T or Both Are Not Large: Bias Decomposition in Systematic and Random Components," MPRA Paper 94405, University Library of Munich, Germany.

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    More about this item

    Keywords

    synthetic data; endogeneity problems; scenarios; Monte Carlo simulations;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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