The authors develop a small open-economy dynamic stochastic general-equilibrium (DSGE) model in an attempt to understand the dynamic relationships in Canadian macroeconomic data.
The authors examine evidence of long- and short-run co-movement in Canadian sectoral output data. Their framework builds on a vector-error-correction representation that allows them to test for and compute full-information maximum-likelihood estimates of models with codependent cycle restrictions.
Recent empirical evidence suggests that private consumption is crowded-in by government spending. This outcome violates existing macroeconomic theory, according to which the negative wealth effect brought about by a rise in public expenditure should decrease consumption.
Phillips curves are generally estimated under the assumption of linearity and parameter constancy. Linear models of inflation, however, have recently been criticized for their poor forecasting performance.
The author develops and estimates a quantitative dynamic-optimizing model of a small open economy (SOE) with domestic and import price stickiness and capital-adjustment costs. A monetary policy rule allows the central bank to systematically manage the short-term nominal interest rate in response to deviations of inflation, output, and money growth from their steadystate levels.
The authors estimate and solve a small structural model for the euro area over the 1983–2000 period. Given the assumption of rational expectations, the model implies a set of orthogonality conditions that provide the basis for estimating the model's parameter by generalized method of moments.
The authors apply existing inflation models that have worked well in industrialized countries to Mexico, an emerging market that has recently moved to adopt an inflation-targeting framework for monetary policy. They compare the performance of these models with a mark-up model that has been used extensively to analyze inflation in Mexico.
Traditional structural models cannot distinguish whether changes in activity are a function of altered expectations today or lagged responses to past plans. Polynomial-adjustment-cost (PAC) models remove this ambiguity by explicitly separating observed dynamic behaviour into movements that have been induced by changes in expectations, and responses to expectations, that have been delayed because of adjustment costs.
The authors study the macroeconomic consequences of large military buildups using a New Neoclassical Synthesis (NNS) approach that combines nominal rigidities within imperfectly competitive goods and labour markets. They show that the predictions of the NNS framework generally are consistent with the sign, timing, and magnitude of how hours worked, after-tax real wages, and output actually respond to an upsurge in military purchases.