Using a new data set, we examine the characteristics and dynamics of cross-border mergers and acquisitions during emerging-market financial crises, that is, so-called “fire-sale FDI.” Our findings shed fresh light on whether the transactions undertaken during crisis periods differ in fundamental ways from those undertaken during more tranquil periods.
This monthly newsletter features the latest research publications by Bank of Canada economists including external publications and working papers published on the Bank of Canada’s website.
We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances.
Forecasts of the quarterly real price of oil are routinely used by international organizations and central banks worldwide in assessing the global and domestic economic outlook, yet little is known about how best to generate such forecasts. Our analysis breaks new ground in several dimensions.
We conduct experiments with human subjects in a model with a positive production externality in which productivity is a non-decreasing function of the average level of employment of other firms.
The authors use the Financial Stress Index created by the International Monetary Fund to predict the likelihood of financial stress events for five developed countries: Canada, France, Germany, the United Kingdom and the United States.
This monthly newsletter features the latest research publications by Bank of Canada economists including external publications and working papers published on the Bank of Canada’s website.
This paper calibrates a class of jump-diffusion long-run risks (LRR) models to quantify how well they can jointly explain the equity risk premium and the variance risk premium in the U.S. financial markets, and whether they can generate realistic dynamics of risk-neutral and realized volatilities.
A longstanding finding in the forecasting literature is that averaging forecasts from different models often improves upon forecasts based on a single model, with equal weight averaging working particularly well. This paper analyzes the effects of trimming the set of models prior to averaging.