Explicit integration of differential equations

Explicit integration of differential equation

The Role of Models and Probabilities in the Monetary Policy Process

macroeconomics, Role of Models, Probabilities, Monetary Policy Process

Comparison of Interwar and Postwar Business Cycles: Monetarism Reconsidered

When monthly data on production, prices, and the money stock are interpreted, via a vector autoregression, as generated by dynamic responses to "surprises" in each of the variables, a remarkable similarity in dynamics between interwar and postwar business cycles emerges, though the size of the "surprises" is much larger in the interwar period. Furthermore, the money stock emerges as firmly causally prior, in Granger's sense, in both periods and accounts for a substantial fraction of variance in production in both periods. When a short interest rate is added to the vector autoregression, the remarkable similarity in dynamics between periods persists, but the central role of the money stock surprises evaporates for the postwar period. While there are potential monetarist explanations for such an observation, none of them seem to fit comfortably the estimated dynamics. A non-monetarist explanation of the dynamics, based on the role of expectations in investment behavior, seems to fit the estimated dynamics better. That this explanation, which is consistent with a passive role for money, could account for so much of the observed postwar relation between money stock and income may raise doubts about the monetarist interpretation even of the interwar data.

Does monetary policy generate recessions?

The issue of uncovering the effects of monetary policy is far short of resolution. In the identified VAR literature, restrictions have been imposed to identify the effects of unpredictable monetary policy disturbances. We offer critical views on the unreasonable assumptions in the existing work and argue for careful economic argument about identifying assumptions. We display a structural stochastic equilibrium model in which our VAR identification would produce correct results while drawing attention to the serious lack of time series fit in most of the DSGE literature.Monetary policy

Error Bands for Impulse Responses

We examine the theory and behavior in practice of Bayesian and bootstrap methods for generating error bands on impulse responses in dynamic linear models. The Bayesian intervals have a firmer theoretical foundation in small samples, are easier to compute, and are about as good in small samples by classical criteria as are the best bootstrap intervals. Bootstrap intervals based directly on the simulated small-sample distribution of an estimator, without bias correction, perform very badly. We show that a method that has been used to extend to the overidentified case standard algorithms for Bayesian intervals in reduced form models is incorrect, and we show how to obtain correct Bayesian intervals for this case.

Duality Theory And the Consistent Estimation Of Technological Parameters: Why Cost Function Estimation Can Be Wrong

In this article we show that technological parameter estimates obtained by estimating a cost function that is derivable as the dual of a production function can be biased and inconsistent if the stochastic structure of the model arises from certain types of behavioural assumptions made about rational agents. We consider a specific example in which firms are uncertain about prices. We show that when actual prices differ from expected prices and firms have to make decisions on the basis of their expectations, the inherited stochastic specification of the dual system is highly non-linear in the disturbance terms making consistent parameter estimation impossible by conventional methods. This is demonstrated by a Monte Carlo simulation study of two text-book examples using synthetic data. It is also shown that this type of result can arise when the researcher derives the error structure from the assumption that agents make optimization errors.cost functions; duality; estimation