We estimate a number of macroeconomic variables as logistic smooth transition autoregressive (LSTAR) processes with uncertainty as the transition variable. The notion is that the effects of increases in uncertainty should not be symmetrical with the effects of decreases in uncertainty. Nonlinear estimation allows us to answer several interesting questions left unanswered by a linear model. For a number of important macroeconomic variables, we show that (i) a positive shock to uncertainty has a greater effect than a negative shock and (ii) the effect of the uncertainty shock is highly dependent on the state of the economy. Hence, the usual linear estimates for the consequences of uncertainty are underestimated in circumstances such as the recent financial crisis.
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