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• W166151877 abstract "This paper presents the results of a Monte Carlo study that compares the small sample performance of various unit root tests in short panels using simulated data that mimic the time series and cross sectional properties of commonly used firm level variables. Our conclusion is that in the presence of firm-level heteroskedasticity two methods are preferred, depending on the nature of the preferred alternative: the simplest method based on the ordinary least squares regression of the variable under consideration on its own lag and a version with a more complex alternative hypothesis suggested by Im, Pesaran, and Shin. The paper also reports the results of using these tests for sales, employment, investment, R&D, and cash-flow in three panels of large French, Japanese and US manufacturing firms. In most cases our data reject the presence of a unit root in favor of a first order autoregressive model with a very high autoregressive coefficient, so high that fixed effects are of negligible additional importance in the model." @default.
• W166151877 created "2016-06-24" @default.
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• W166151877 date "2005-06-17" @default.
• W166151877 modified "2023-10-16" @default.
• W166151877 title "Testing for Unit Roots in Panel Data: An Exploration Using Real and Simulated Data" @default.
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• W166151877 doi "https://doi.org/10.1017/cbo9780511614491.020" @default.
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