Search Results
Journal Article
A fine time for monetary policy?
Recent research in evaluating the effects of monetary policy is potentially tainted by the problem of time aggregation: that is, effects may be incorrectly estimated using quarterly data if the effects of policy occur rapidly. This study evaluates whether time aggregation is a serious problem in a simple vector autoregression. It shows time aggregation has little impact on evaluating the effect of monetary policy in a simple vector autoregression including total reserves, nonborrowed reserves, and the federal funds rate. This finding suggests that time aggregation is unlikely to be important ...
Journal Article
Are economic forecasts rational?
This paper discusses at an undergraduate level how forecast rationality can be tested. It explains that forecasters should correctly use any relevant information they knew in making their predictions. It shows that forecast rationality can be tested by determining whether the forecasters' prediction errors are predictable. After addressing what data and methods can be used for testing rationality, the paper presents tests of the price-forecast rationality of individual professional forecasters. Unlike results of previous studies, the test results show that those forecasters' price predictions ...
Journal Article
Revisionist history: how data revisions distort economic policy research
This article describes how and why official U.S. estimates of the growth in real economic output and inflation are revised over time, demonstrates how big those revisions tend to be, and evaluates whether the revisions matter for researchers trying to understand the economy?s performance and the contemporaneous reactions of policymakers. The conclusion may seem obvious, but it is a point ignored by most researchers: To have a good chance of understanding how policymakers make their decisions, researchers must use not the final data available, but the data available initially, when the policy ...
Journal Article
The U.S. economy in 1989 and 1990: walking a fine line
Journal Article
No relief in sight for the U.S. economy
For at least the next two years, the U.S. economy will grow more slowly than it has on average since World War II. This is the forecast of a Bayesian vector autoregression model developed and used by researchers at the Minneapolis Federal Reserve Bank. The model's previous forecast?of a very weak start to the 1991?92 recovery?was remarkably accurate. Both forecasts are supported by evidence on long-term problems among consumers, in the commercial real estate industry, and at all levels of government. These problems will most likely constrain economic growth for years, although short spurts of ...
Report
Alternative computational approaches to inference in the multinomial probit model
This research compares several approaches to inference in the multinomial probit model, based on Monte-Carlo results for a seven choice model. The experiment compares the simulated maximum likelihood estimator using the GHK recursive probability simulator, the method of simulated moments estimator using the GHK recursive simulator and kernel-smoothed frequency simulators, and posterior means using a Gibbs sampling-data augmentation algorithm. Each estimator is applied in nine different models, which have from 1 to 40 free parameters. The performance of all estimators is found to be ...
Report
On the relation between the expected value and the volatility of the nominal excess return on stocks
We find support for a negative relation between conditional expected monthly return and conditional variance of monthly return, using a GARCH-M model modified by allowing (i) seasonal patterns in volatility, (ii) positive and negative innovations to returns having different impacts on conditional volatility, and (iii) nominal interest rates to predict conditional variance. Using the modified GARCH-M model, we also show that monthly conditional volatility may not be as persistent as was thought. Positive unanticipated returns appear to result in a downward revision of the conditional ...
Report
Statistical inference in the multinomial multiperiod probit model
Statistical inference in multinomial multiperiod probit models has been hindered in the past by the high dimensional numerical integrations necessary to form the likelihood functions, posterior distributions, or moment conditions in these models. We describe three alternative approaches to inference that circumvent the integration problem: Bayesian inference using Gibbs sampling and data augmentation to compute posterior moments, simulated maximum likelihood (SML) estimation using the GHK recursive probability simulator, and method of simulated moment (MSM) estimation using the GHK simulator. ...