Real-Time Forecasts of the Real Price of Oil
We construct a monthly real-time data set consisting of vintages for 1991.1-2010.12 that is suitable for generating forecasts of the real price of oil from a variety of models.
Econometric and statistical methods
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Forecasting the Price of Oil
We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need to know about the choice of sample period and about the tradeoffs between alternative oil price series and model specifications? -
The Canadian Debt-Strategy Model: An Overview of the Principal Elements
The Canadian Debt Strategy Model helps debt managers determine their optimal financing strategy. The model’s code and documentation are available to the public. -
Mixed Frequency Forecasts for Chinese GDP
We evaluate different approaches for using monthly indicators to predict Chinese GDP for the current and the next quarter (‘nowcasts’ and ‘forecasts’, respectively). We use three types of mixed-frequency models, one based on an economic activity indicator (Liu et al., 2007), one based on averaging over indicator models (Stock and Watson, 2004), and a static factor model (Stock and Watson, 2002). -
The Impact of the Global Business Cycle on Small Open Economies: A FAVAR Approach for Canada
Building on the growing evidence on the importance of large data sets for empirical macroeconomic modeling, we use a factor-augmented VAR (FAVAR) model with more than 260 series for 20 OECD countries to analyze how global developments affect the Canadian economy. -
Building New Plants or Entering by Acquisition? Estimation of an Entry Model for the U.S. Cement Industry
In many industries, firms usually have two choices when expanding into new markets: They can either build a new plant (greenfield entry) or they can acquire an existing incumbent. In the U.S. cement industry, the comparative advantage (e.g., TFP or size) of entrants versus incumbents and regulatory entry barriers are important factors that determine the means of expansion. -
'Lean' versus 'Rich' Data Sets: Forecasting during the Great Moderation and the Great Recession
We evaluate forecasts for the euro area in data-rich and ‘data-lean' environments by comparing three different approaches: a simple PMI model based on Purchasing Managers' Indices (PMIs), a dynamic factor model with euro area data, and a dynamic factor model with data from the euro plus data from national economies (pseudo-real time data). -
Testing Linear Factor Pricing Models with Large Cross-Sections: A Distribution-Free Approach
We develop a finite-sample procedure to test the beta-pricing representation of linear factor pricing models that is applicable even if the number of test assets is greater than the length of the time series. Our distribution-free framework leaves open the possibility of unknown forms of non-normalities, heteroskedasticity, time-varying correlations, and even outliers in the asset returns. -
Bank Competition and International Financial Integration: Evidence Using a New Index
This paper finds a strong empirical link between domestic banking sector competitiveness and de facto international integration. De-facto international integration is measured through a new index of financial integration, which measures, for deviations from covered interest parity, the size of no-arbitrage bands and the speed of arbitrage outside the no-arbitrage band. -
Semi-Structural Models for Inflation Forecasting
We propose alternative single-equation semi-structural models for forecasting inflation in Canada, whereby structural New Keynesian models are combined with time-series features in the data. Several marginal cost measures are used, including one that in addition to unit labour cost also integrates relative price shocks known to play an important role in open-economies.