We propose a new test for a multivariate parametric conditional distribution of a vector of variables yt given a conditional vector xt.
Staff Working Papers
Historical narratives typically associate financial crises with credit expansions and asset price misalignments. The question is whether some combination of measures of credit and asset prices can be used to predict these events.
Since the advent of standard national accounts data over 60 years ago, economists have traditionally relied on monthly or quarterly data supplied by central statistical agencies for macroeconomic modelling and forecasting.
Using data for 14 countries over the 1994 to 2005 period, we assess the leading indicator properties of gold at horizons ranging from 6 to 24 months.
How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic VariablesFor stationary transformations of variables, there exists a maximum horizon beyond which forecasts can provide no more information about the variable than is present in the unconditional mean. Meteorological forecasts, typically excepting only experimental or exploratory situations, are not reported beyond this horizon; by contrast, little generally accepted information about such maximum horizons is available for economic variables.
The authors examine whether simple measures of Canadian equity and housing price misalignments contain leading information about output growth and inflation.
The authors document the research output of 34 central banks from 1990 to 2003, and use proxies of research inputs to measure the research productivity of central banks over this period.
Estimating Policy-Neutral Interest Rates for Canada Using a Dynamic Stochastic General-Equilibrium FrameworkIn an era when the primary policy instrument is the level of the short-term interest rate, a comparison of that rate with some equilibrium rate can be a useful guide for policy and a convenient method to measure the stance of monetary policy.
Using interest rate yield spreads to explain changes in inflation, we investigate whether such relationships can be modelled using two-regime threshold models.
This paper describes a new test for evaluating conditional density functions that remains valid when the data are time-dependent and that is therefore applicable to forecasting problems. We show that the test statistic is asymptotically distributed standard normal under the null hypothesis, and diverges to infinity when the null hypothesis is false.