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

The paper attempts to determine regional unemployment rates for NUTS 2 regions based on data available on a regular basis from Eurostat and ILO. In the first part it is shown how the evolution of regional unemployment rates is determined by national unemployment rates by industry and the...

In this paper, we compare two popular statistical learning techniques, logistic regression and random forest, with respect to their ability to classify jobseekers by their likelihood to become long-term unemployed. We study the performance of the two methods before the COVID-19 pandemic as well...

We propose a unique method of nowcasting and forecasting GDP growth based on a forward-looking measure of unemployment (FLUR) and Okun's law that offers a number of advantages over current leading indicators of the Swiss business cycle. The following investigation, covering the period from...

Big data trends, have gained popularity among practitioners for its potential applications on accurate econometric prediction. This paper presents an application where unemployment job search indicators for the G7 countries are based on Google trends data. For each country, a set of google...

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...

This paper improves short-term forecasting models of monthly tourism arrivals by estimating and evaluating a time-series model with exogenous regressors (ARIMA-X) using a case of Aruba, a small open tourism-dependent economy. Given importance of the US market for Aruba, it investigates...

Predictions of whether newly unemployed individuals will become long-term unemployed are important for the planning and policy mix of unemployment insurance agencies. We analyze unique data on three sources of information on the probability of re-employment within 6 months (RE6), for the same...

We analyze unique data on three sources of information on the probability of re‑employment within 6 months (RE6), for the same individuals sampled from the inflow into unemployment. First, they were asked for their perceived probability of RE6. Second, their caseworkers revealed whether they...

We analyze unique data on three sources of information on the probability of re-employment within 6 months (RE6), for the same individuals sampled from the inflow into unemployment. First, they were asked for their perceived probability of RE6. Second, their caseworkers revealed whether they...