Can modern theories of structural change fit business cycles data?

We investigate the ability of workhorse structural change models in accounting for the business cycle properties of an economy. We consider three different preferences specifications: Herrendorf, Rogerson and Valentinyi (2014, HRV), Boppart (2014), and Comin, Lashkari and Mestieri (2021, CLM), paired with standard sectoral production functions with random total factor productivity (TFP) shocks. In each case, we estimate preference parameters using long-run structural change data, and common TFP processes calibrated on observed relative prices. Our main results can be summarized by: i) all models display a volatility of aggregate variables substantially lower than the data, but they account for a large fraction of the volatility of consumption relative to GDP; ii) at the sectoral level, only CLM accounts for a substantial fraction of absolute and relative volatility; iii) all models do reasonably well in accounting for the cyclicality of aggregate GDP components; and iv) only HRV can account for the cyclicality of sectoral variables.