Robert B Litterman
Biographic Data
| ID | 8920128 |
|---|---|
| NAME | Robert B Litterman |
| GIVEN NAMES | Robert B |
| FAMILY NAME | Litterman |
| SIGNATURE | LITTERMAN R B |
| AFFILIATIONS | Federal Reserve Bank of Minneapolis |
| VERIFIED | No |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1983 |
| LATEST PUBLICATION YEAR | 1986 |
| H-INDEX | 0 |
[Forecasting Accuracy of Alternative Techniques
Robert B. Litterman, [Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts]: Comment, Journal of Business & Economic Statistics, Vol. 4, No. 1 (Jan., 1986), pp. 17-19
A Statistical Approach to Economic Forecasting
A recently developed statistical model, called Bayesian vector autoregression, has proven to be a useful tool for economic forecasting. Such a model today forecasts a strong resurgence of growth in the second half of 1985 and in 1986
Forecasting with Bayesian Vector Autoregressions
The results obtained in five years of forecasting with Bayesian vector autoregressions (BVAR's) demonstrate that this inexpensive, reproducible statistical technique is as accurate, on average, as those used by the best known commercial forecasting services. This article considers the problem of economic forecasting, the justification for the Bayesian approach, its implementation, and the performance of one small BVAR model over the past five yea…
Forecasting With Bayesian Vector Autoregressions—Five Years of Experience
The results obtained in five years of forecasting with Bayesian vector autoregressions (BVAR's) demonstrate that this inexpensive, reproducible statistical technique is as accurate, on average, as those used by the best known commercial forecasting services. This article considers the problem of economic forecasting, the justification for the Bayesian approach, its implementation, and the performance of one small BVAR model over the past five yea…
Modelling Procedures for Univariate Economic Time Series
Forecasting and conditional projection using realistic prior distributions
This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. The procedure is applied t o 10 macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate equations. Although cross-variable responses are damped by the prior, considerable interaction among the variables is shown to be captured by the estimates We provide unconditional forecasts as of 1982:12 and 1983…
A Random Walk, Markov Model for the Distribution of Time Series
This article describes a technique for distributing quarterly time series across monthly values. The method generalizes an approach described by Fernández (1981). The article also presents results of a test of the accuracy of these two approaches and of the accuracy of two standard procedures suggested by Chow and Lin (1971)
No prominent works on this page.
A Random Walk, Markov Model for the Distribution of Time Series
This article describes a technique for distributing quarterly time series across monthly values. The method generalizes an approach described by Fernández (1981). The article also presents results of a test of the accuracy of these two approaches and of the accuracy of two standard procedures suggested by Chow and Lin (1971)
Forecasting and conditional projection using realistic prior distributions
This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. The procedure is applied t o 10 macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate equations. Although cross-variable responses are damped by the prior, considerable interaction among the variables is shown to be captured by the estimates We provide unconditional forecasts as of 1982:12 and 1983…
Modelling Procedures for Univariate Economic Time Series
[Forecasting Accuracy of Alternative Techniques
Robert B. Litterman, [Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts]: Comment, Journal of Business & Economic Statistics, Vol. 4, No. 1 (Jan., 1986), pp. 17-19
A Statistical Approach to Economic Forecasting
A recently developed statistical model, called Bayesian vector autoregression, has proven to be a useful tool for economic forecasting. Such a model today forecasts a strong resurgence of growth in the second half of 1985 and in 1986
Forecasting with Bayesian Vector Autoregressions
The results obtained in five years of forecasting with Bayesian vector autoregressions (BVAR's) demonstrate that this inexpensive, reproducible statistical technique is as accurate, on average, as those used by the best known commercial forecasting services. This article considers the problem of economic forecasting, the justification for the Bayesian approach, its implementation, and the performance of one small BVAR model over the past five yea…
Forecasting With Bayesian Vector Autoregressions—Five Years of Experience
The results obtained in five years of forecasting with Bayesian vector autoregressions (BVAR's) demonstrate that this inexpensive, reproducible statistical technique is as accurate, on average, as those used by the best known commercial forecasting services. This article considers the problem of economic forecasting, the justification for the Bayesian approach, its implementation, and the performance of one small BVAR model over the past five yea…
Econometrics (7 works) · Computer Science (6 works) · Forecasting Techniques and Applications (6 works) · Economics (5 works) · Bayesian probability (4 works) · Bayesian vector autoregression (4 works) · Monetary Policy and Economic Impact (4 works) · Artificial Intelligence (3 works) · Mathematics (3 works) · Statistics (3 works)