论文检索

模型不确定性与弱外生性下的面板增长实证分析AI 解读

This paper considers panel growth regressions in the presence of model uncertainty and reverse causality concerns. For this purpose, my econometric framework combines Bayesian model averaging with a suitable likelihood function for dynamic panel models with weakly exogenous regressors and fixed effects. An application of this econometric methodology to a panel of countries over the 1960–2000 period highlights the difficulties in identifying the sources of economic growth by…

含前定解释变量的动态面板似然估计AI 解读

This article discusses the likelihood-based estimation of panel data models with individual-specific effects and both lagged dependent variable regressors and additional predetermined explanatory variables. The resulting new estimator, labeled as subsystem limited information maximum likelihood (ssLIML), is asymptotically equivalent to standard panel generalized method of moment as N → ∞ for fixed T but tends to present smaller biases in finite samples as illustrated in…

经济增长的决定因素：贝叶斯面板数据方法AI 解读

Model uncertainty hampers consensus on the key determinants of economic growth. Some recent cross-country cross-sectional analyses have employed Bayesian model averaging to tackle the issue of model uncertainty. This paper extends that approach to panel data models with country-specific fixed effects in order to simultaneously address model uncertainty and endogeneity issues. The empirical findings suggest that in a panel setting, the most robust growth determinants are the…