Monetary Policy Trade-Offs in an Estimated Open-Economy DSGE Model

This paper studies the transmission of shocks and the trade-offs between stabilizing CPI inflation and alternative measures of the output gap in Ramses, the Riksbank's empirical dynamic stochastic general equilibrium (DSGE) model of a small open economy. The main results are, first, that the transmission of shocks depends substantially on the conduct of monetary policy, and second, that the trade-off between stabilizing CPI inflation and the output gap strongly depends on which concept of potential output in the output gap between output and potential output is used in the loss function. If potential output is defined as a smooth trend this trade-off is much more pronounced compared to the case when potential output is defined as the output level that would prevail if prices and wages were flexible.

Interview with Charles Goodhart

Poster for a series of programs dedicated for 2Ls and 3Ls by the Office of Career Planning.https://repository.law.umich.edu/posters/1323/thumbnail.jp

Optimal Monetary Policy in an Operational Medium-Sized DSGE Model

We show how to construct optimal policy projections in Ramses, the Riksbank’s open-economy medium-sized DSGE model for forecasting and policy analysis. Bayesian estimation of the parameters of the model indicates that they are relatively invariant to alternative policy assumptions and supports our view that the model parameters may be regarded as unaffected by the monetary policy specification. We discuss how monetary policy, and in particular the choice of output gap measure, affects the transmission of shocks. Finally, we use the model to assess the recent Great Recession in the world economy and how its impact on the economic development in Sweden depends on the conduct of monetary policy. This provides an illustration on how Rames incorporates large international spillover effects.

Aggregate Investment Expenditures on Traded and

It is a well-established empirical regularity in the macroeconomic literature that the relative price of nontraded goods (expressed in terms of traded goods) correlates positively with income and exhibits large differences across space and time. This paper shows that, despite the large differences in the relative price, aggregate investment expenditure shares on traded and nontraded goods are remarkably similar in rich and poor countries. Furthermore, the two expenditure shares have remained close to constant over time, with the average nontraded expenditure share varying between 0.54-0.60 over the 1960-2002 period. Empirical results of this paper offer a new restriction for the two-sector growth model. We show that, with the restriction imposed on the model, only around 25 percent of the differences in PPP adjusted investment rates between rich and poor countries can be attributed to differences in relative productivity between traded and nontraded sectors, i.e., the Balassa-Samuelson effect

Estimating New-Keynesian Phillips Curves: A Full Information Maximum Likelihood Approach

The New-Keynesian Phillips curve has recently become an important ingredient in monetary policy models. However, using limited information methods, the empirical support for the New-Keynesian Phillips curve appear to be mixed. This paper argues, by means of Monte Carlo simulations with a simple New-Keynesian sticky price model, that single equations methods, e.g. GMM, are likely to produce imprecise and biased estimates. Then, it is argued that estimating the model with full information maximum likelihood (FIML) is a useful way of obtaining better estimates. Finally, a version of the model used in the Monte Carlo simulations is estimated on U.S. data with FIML and although the pure forward-looking New-Keynesian Phillips curve is rejected, a version with both forward- and backward-looking components provides a reasonable approximation of U.S. inflation dynamics.Monetary policy rule; New-Keynesian Phillips curve; Rational expectations IS-curve; Backward-looking Phillips curve; Measurement errors; Full Information Maximum Likelihood estimation