Synthetic data: an endogeneity simulation

Carbajal De Nova, Carolina (2014): Synthetic data: an endogeneity simulation.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: synthetic data, endogeneity problems, scenarios, Monte Carlo simulations
• Subjects: C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C46 - Specific Distributions ; Specific Statistics; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis

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