Abstract
This paper develops a macroeconomic uncertainty index based on the multistage procedure that combines maximum likelihood and Bayesian estimation methods proposed by Jurado et al. (Am Econ Rev 105(3):1177–1216, 2015). Our approach streamlines the computation of the macroeconomic uncertainty index by specifying a state-space model estimated by maximum likelihood that allows us to obtain in one step the parameters of the model, the dynamic factors, and the forecast errors of the macroeconomic variables used to construct the index. Moreover, we estimate stochastic volatility models on the forecast errors also by maximum likelihood using a density filter that proves to be faster than a Bayesian estimation. After showing that our methodology produces reasonable results for the USA, we apply it to compute a macroeconomic uncertainty index for Ecuador, becoming the first index of this kind for a small 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 output, employment in the formal sector, and consumer prices to macroeconomic uncertainty shocks are sizable and persistent.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00181-021-02069-5.
Highlights
IntroductionUncertainty is a broad concept that frames several circumstances, whether they are economic related or not
The empirical literature has relied on proxies of uncertainty, using subjective concepts based on the volatility of stock market returns, dispersion of firms’ profits, newspaper coverage, survey-based forecasts, and forecaster disagreement
We propose an alternative method to compute the macroeconomic uncertainty index originally put forward by JLN
Summary
Uncertainty is a broad concept that frames several circumstances, whether they are economic related or not. Jurado et al (2015) (JLN hereafter) pioneered the development of an index of macroeconomic uncertainty for the USA. In JLN’s framework, what matters for uncertainty is whether the economy has become more or less predictable through the lens of a forecasting model. Despite its relevance and usefulness, JLN’s macroeconomic uncertainty index has barely been replicated in other economies (especially in developing countries), perhaps because of the lack of data or complications in implementing the procedure. We streamline the procedure put forward by JLN to measure macroeconomic uncertainty and apply it to the Ecuadorian economy. Our intention is to offer a framework that can allow policymakers and researchers in general to construct and update a macroeconomic uncertainty index akin to that of JLN in a relatively timely and straightforward fashion
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