A Streamlined Procedure to Construct a Macroeconomic Uncertainty Index with an Application to the Ecuadorian Economy

This paper develops a macroeconomic uncertainty index based on the methodology proposed by Jurado, Ludvigson, and Ng (2015).Our approach streamlines the computation of the macroeconomic uncertainty index by using a state-space model that allows us to obtain the unforecastable component of the macroeconomic variables used to construct the index and the latent factors. Moreover, we estimate this state-space model by maximum likelihood, obtaining the parameters of the model and the latent factors in one step, which is more efficient, by construction, than a multi-stage estimation. Finally, with the forecast errors of the state-space model, we propose to estimate stochastic volatility models also by maximum likelihood, using a density filter that could be faster than a Bayesian estimation. After showing that our methodology produces reasonable results for the United States, we apply it to compute a macroeconomic uncertainty index for Ecuador. Our estimate is the first of this kind for a developing or middle-income country. The results show that the Ecuadorian economy is more volatile and less predictable during recessions. We also provide evidence that macroeconomic uncertainty is detrimental to economic activity, finding that the responses of non-oil GDP, the unemployment rate, and consumer prices to macro uncertainty shocks are sizable and persistent.