因变量取值于[0,1]且0处有质量点时，能否用xtabond2实现系统GMM估计？

Short answer: Yes, you can use xtabond2 to implement System GMM in this scenario, but there are critical caveats you need to address because of your dependent variable's corner-solution nature (bounded [0,1] with a mass point at 0). Let’s break this down:

Key Considerations #

• Linear vs. Nonlinear GMM: xtabond2 is built primarily for linear dynamic panel models. When your dependent variable is bounded and has a mass at 0, it falls into the corner-solution variable category. Linear GMM assumes a continuous dependent variable, so standard linear moment conditions might not hold perfectly—this could lead to inconsistent estimates if the error term doesn’t meet required distributional assumptions.
• Using xtabond2 as a Baseline: If you want to use xtabond2 for initial estimates, you can run a linear System GMM as a benchmark, but you must:
  • Add the robust option to use robust standard errors, which accounts for heteroskedasticity common with corner-solution variables.
  • Explicitly note the limitation in your results: linear GMM treats the dependent variable as continuous, even though it’s bounded and has a mass point.
• Rigorous Alternative: Nonlinear System GMM: For a more appropriate approach, implement nonlinear System GMM tailored to corner-solution models. While xtabond2 doesn’t have a built-in command for this, you can use it to manually specify moment conditions that account for the censored nature of your dependent variable (e.g., adapting probit/tobit-like logic for dynamic panels). This requires deriving moment conditions that align with your variable’s structure.
• Diagnostic Tests Are Non-Negotiable: No matter which path you take, don’t skip standard System GMM checks:
  • Run Hansen/Sargan tests to validate your instrument set.
  • Test for serial correlation (AR(1) and AR(2) tests)—corner-solution variables can distort these results, so interpret them carefully.
  • Use the collapse option to reduce instrument count and avoid overfitting.

Final Takeaway #

xtabond2 can be used to run System GMM estimates for your data, but linear System GMM is a second-best choice here. If possible, invest time in setting up a nonlinear System GMM framework with xtabond2 by customizing moment conditions to match your dependent variable’s corner-solution structure.

内容的提问来源于stack exchange，提问作者Sagnik Bagchi