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.
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 purpose of this paper is twofold. First, we provide a detailed social accounting matrix (SAM), which incorporates the income and financial flows into the standard input-output matrix, for the Canadian economy for 2004.
The Canadian Debt Strategy Model helps debt managers determine their optimal financing strategy. The model’s code and documentation are available to the public.
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).
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.
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).
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.
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.
This paper contributes to the debate on fiscal multipliers, in the context of a structural model. I estimate a micro-founded dynamic stochastic general equilibrium model, that features a rich fiscal policy block and a transmission mechanism for government spending shocks, using Bayesian techniques for US data.