We suggest the use of an Internet job-search indicator (the Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample forecasting comparison analyzing many models that adopt both our preferred leading indicator (GI), the more standard...

In this paper we discuss some strands of the recent literature on the evolution of gender gaps and their driving forces. We will revisit key stylized facts about gender gaps in employment and wages in a few high-income countries. We then discuss and build on one gender-neutral force behind the...

Decreases in labor supply among cash-transfer recipients are often cited as potential drawbacks of social-assistance programs. However, cash transfers can also increase employment. Using variation across cohorts and over time in the eligibility criteria of a nationwide conditional cash-transfer...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...

The empirical literature is very far from any consensus about the appropriate model for oil price forecasting that should be implemented. Relative to the previous literature, this paper is novel in several respects. First of all, we test and systematically evaluate the ability of several...

High-frequency financial and economic activity indicators are usually time aggregated before forecasts of low-frequency macroeconomic events, such as recessions, are computed. We propose a mixed-frequency modelling alternative that delivers high-frequency probability forecasts (including their...

Call centers' managers are interested in obtaining accurate forecasts of call arrivals because these are a key input in staffing and scheduling decisions. Therefore their ability to achieve an optimal balance between service quality and operating costs ultimately hinges on forecast accuracy. We...

We investigate a test of equal predictive ability delineated in Giacomini and White (2006; Econometrica). In contrast to a claim made in the paper, we show that their test statistic need not be asymptotically Normal when a fixed window of observations is used to estimate model parameters. An example...

Sign-restricted Structural Vector Autoregressions (SVARs) are increasingly common. However, they usually result in a set of structural parameters that have very different implications in terms of impulse responses, elasticities, historical decomposition and forecast error variance decomposition...

Forecasting the inflation path is an important task for central banks in an inflation targeting regime. Therefore, central banks must continuously evaluate the forecasting accuracy of the models used to generate inflation forecasts. This paper evaluates the performance of most of the models that...