Reconsideration of the Markov Chain Evidence on Unemployment Rate Asymmetry

Using 15 years worth of additional data, a study is carried out to explore the extent to which the results in Rothman (1991) still hold. The analysis shows that such a comparison is very much dependent on whether: (i) 1-quarter differences or 4-quarter differences are used to construct the underlying state-indicator sequence; and (ii) the asymptotic distribution of the underlying test statistics is used for inference. The considerably higher staying probabilities obtained with the smoother 4-quarter differences argue in favor of their use in addressing the possible asymmetry of the business cycle, as opposed to higher-frequency fluctuations. Also, Monte Carlo simulations suggest the asymptotic p-values for the Markov chain tests are biased.