On Testing Conditional Sigma – Convergence*
提出一种新的Wald检验方法，用于检验条件西格玛收敛性，蒙特卡洛模拟显示其表现良好，并应用于欧洲制造业企业规模数据，发现多数国家组和年轻企业存在收敛。
Abstract In a cross‐section where the initial distribution of observations differs from the steady‐state distribution and initial values matter, convergence is best measured in terms of σ ‐convergence over a fixed time period. For this setting, we propose a new simple Wald test for conditional σ ‐convergence. According to our Monte Carlo simulations, this test performs well and its power is comparable with the available tests of unconditional convergence. We apply two versions of the test to conditional convergence in the size of European manufacturing firms. The null hypothesis of no convergence is rejected for all country groups, most single economies, and for younger firms of our sample of 49,646 firms.