We examine the impact of Articial Intelligence (AI) on productivity in the context of taxi drivers. The AI we study assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI improves drivers' productivity by shortening the...

Population ageing constitutes a central challenge to Finland. Understanding the Finnish economy's likely future trajectory and the key sources of growth is important for the design of policies to counteract these adverse long-term trends. For this purpose, we develop a novel long-run forecast...

Enrollment rates to higher education reveal quite large variation over time which cannot be explained by productivity shocks alone. We develop a human capital investment model in an overlapping generations framework that features endogenous fluctuations in the demand for education. Agents are...

We developed a factor regression model, nicknamed “GUPTY”, to study the business cycles, and their relation to the monetary policy. It covers several major macro-economic quantities, including unemployment rate, GDP, and weekly payrolls in the U.S. after WWII. The model postulates that these...

The aim of the paper is to analyze the ability of internet activity, what has been called Google econometrics, to predict unemployment in Spain. We include a new predictor for Spanish unemployment based on internet information provided by Google Trends. Using monthly data from January 2004 to...

We provide a general framework to consider the effects of algorithmic demand and supply prediction in matching platforms, such as Task Rabbit for labor markets or Amazon for goods markets, where a significant proportion of matches are repeat transactions. We show that algorithmic repeat match...