Ali Dib

Forecasting Canadian Time Series with the New-Keynesian Model

This paper documents the out-of-sample forecasting accuracy of the New Keynesian Model for Canada. We repeatedly estimate our variant of the model on a series of rolling subsamples, forecasting out-of-sample one to eight quarters ahead at each step. We then compare these forecasts to those arising from simple VARs, using econometric tests of forecasting accuracy. Our results show that the forecasting accuracy of the New Keynesian model compares favourably to that of the benchmarks, particularly as the forecasting horizon increases. These results suggest that the model can become a useful forecasting tool for Canadian time series. The principle of parsimony is invoked to explain our findings.

Countercyclical Bank Capital Requirement and Optimized Monetary Policy Rules

ABSTRACT Using BoC-GEM-Fin, a large-scale dynamic stochastic general equilibrium (DSGE) model with real, nominal, and financial frictions featuring a banking sector, we explore the macroeconomic implications of various types of countercyclical bank capital regulations. Results suggest that countercyclical capital requirements have a significant stabilizing effect on key macroeconomic variables, but mostly after financial shocks. Moreover, the bank capital regulatory policy and monetary policy interact, and this interaction is contingent on the type of shocks that drive the economic cycle. Finally, we analyze loss functions based on macroeconomic and financial variables to arrive at an optimal countercyclical regulatory policy in a class of simple implementable Taylor-type rules. Compared to bank capital regulatory policy, monetary policy is able to stabilize the economy more efficiently after real shocks. On the other hand, financial shocks require the regulator to be more aggressive in loosening/tightening capital requirements for banks, even as monetary policy works to counter the deviations of inflation from the target.