Monte Carlo Evidence on the Estimation Method for Industry Dynamics
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Kazufumi Yamana
Abstract
This study presents a structural estimation method for nonlinear stochastic dynamic models of heterogeneous firms. I perform a Monte Carlo experiment to evaluate the performance of the estimators for the AR(1) dynamic panel data subject to sample selection without exogenous regressors. The results suggest a strong need to correct the sample selection and that the proposed structural estimation method works well. These results are important for practical situations where the assumptions of the standard sample selection correction methods are not satisfied.
Matching Summary Statistics
In this Appendix, I calculate and compare the RMSE of ABC estimates using the quartile-based robust measure and the set of octiles as summary statistics following Dominicy and Veredas (2013). Four robust statistics are given by
and the set of octiles are
To quantify which statistic is most appropriate for minimizing the density difference, I consider the case for known fixed cost. Table 5 shows that matching density exhibits lower RMSE than matching summary statistics. This is because matching summary statistics is more inclined to get stuck in a local optimum. Therefore, matching density is more stable and reliable to minimize the density difference.
RMSEs of alternative estimators calculated over fifty replications.
| quartile | octile | KLD | L2 | |
|---|---|---|---|---|
| RMSE(ρ) | 0.0749 | 0.0761 | 0.0690 | 0.0360 |
| RMSE(σϵ) | 0.0334 | 0.0300 | 0.0172 | 0.0195 |
| RMSE(σα) | 0.0514 | 0.0477 | 0.0444 | 0.0335 |
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Artikel in diesem Heft
- Research Articles
- Monte Carlo Evidence on the Estimation Method for Industry Dynamics
- An Empirical Undergraduate Introduction to Estimating Consumer Preferences Using Ride Choices at Disneyland
- Regression-Based Causal Analysis from the Potential Outcomes Perspective
- Level-Based Estimation of Dynamic Panel Models
- How Accurately Do Structural Asymmetric First-Price Auction Estimates Represent True Valuations?
- Adjustments of Rao’s Score Test for Distributional and Local Parametric Misspecifications
- Measuring Benchmark Damages in Antitrust Litigation: Extensions and Practical Implications
- Instrumental Variables Estimation in Large Heterogeneous Panels with Multifactor Structure
