Non-normalities of the business cycle

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The question of whether business cycles are asymmetric has long been a key area of macroeconomic research. Significant efforts have focused on developing models that highlight differences between recessions and expansions, emphasizing distinct economic mechanisms. The first part of this work provides empirical evidence regarding macroeconomic time series and their non-normalities, which include deepness, steepness, non-zero excess kurtosis, distributional non-normality, distributional asymmetry, conditional asymmetry of expected duration, and asymmetric duration dependence. Utilizing both non-parametric and parametric tests based on Markov-switching processes, we derive necessary formulas for analyzing deepness and steepness. Extensive Monte Carlo studies reveal that non-parametric tests often exhibit low power with short samples and strong serial correlation. Analyzing U.S. postwar data for various economic indicators, we find non-normalities in all variables except consumption and capital, with investment showing the most pronounced non-normalities. The second part examines the capacity of dynamic stochastic general equilibrium (DSGE) models to replicate empirical findings related to deepness, steepness, and excess kurtosis. Standard DSGE models fall short in this regard. We propose two modifications: incorporating non-normal shocks and introducing an upper bound to capacity utilization. While non-normal shocks align qualita