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Given that China accounts for about half of global copper consumption, it is reasonable to expect that any significant change in Chinese copper consumption will have an impact on the global market.

This paper documents a systematic pattern of how wages, hours and their relationship vary across firms of different sizes. Using a model with heterogeneous firms and workers, we show how the interplay between wages, hours and firm size affect worker sorting and inequality.

We analyze the relationship between the intensity of banks’ use of soft-information and household bankruptcy patterns. Using a unique data set on the universe of Canadian household bankruptcies, we document that bankruptcy rates are higher in markets where the collection of soft, or qualitative locally gathered information, is the weakest.

This article examines what market conditions lead to extreme losses in global financial systems. Using a reverse stress testing approach, it introduces two measures of systemic risk by starting from the tail losses and working backward to identify the events most closely associated with them.

Given the influence that agents’ expectations have on key macroeconomic variables, it is surprising that very few papers have tried to extrapolate agents’ “true” expectations directly from the data. This paper presents one such approach, starting with the hypothesis that there is sluggishness in inflation and real GDP growth forecasts.

We build upon new developments in the international trade literature to isolate and quantify the long-run economic impacts of tariff changes on the United States and the global economy.

The author estimates the relationship between the provincial credit ratings, as assessed by Standard & Poor's, and a number of economic variables, using the ordered probit methodology. All the variables in her estimation prove to be significant. In particular, she finds that downgrades take place at almost the same speed at different levels of the debt-to-GDP ratio, based on a pooled sample of nine provinces.

The Bank of Canada uses several short-term forecasting models for the monitoring of key foreign economies - the United States, the euro area, Japan and China. The design of the forecasting models used for each region is influenced by the level of detail required, as well as the timeliness and volatility of data. Forecasts from different models are typically combined to mitigate model uncertainty, and judgment is applied to the model forecasts to incorporate information that is not directly reflected in the most recent indicators.

Recently, there has been increased interest in real-time forecasts of the real price of crude oil. Standard oil price forecasts based on reduced-form regressions or based on oil futures prices do not allow consumers of forecasts to explore how much the forecast would change relative to the baseline forecast under alternative scenarios about future oil demand and oil supply conditions.

We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models.