Jan R Magnus
Biographic Data
| ID | 5738825 |
|---|---|
| NAME | Jan R Magnus |
| GIVEN NAMES | Jan R |
| FAMILY NAME | Magnus |
| SIGNATURE | MAGNUS J R |
| AFFILIATIONS | Vrije Universiteit Amsterdam and Tinbergen Institute Amsterdam the Netherlands |
| ORCID | 0000-0002-3390-639X |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1988 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Bayesian Estimation of the Normal Location Model: A Non‐Standard Approach
We consider the estimation of the location parameter in the normal location model and study the sampling properties of shrinkage estimators derived from a non‐standard Bayesian approach that places the prior on a scaled version of , interpreted as the “population ‐ratio.” We show that the finite‐sample distribution of these estimators is not centred at and is generally non‐normal. In the asymptotic theory, we prove uniform ‐consistency of our est…
Separability and Aggregation
This paper examines the conditions for homothetic separability of a technology that is an aggregate of technologies of individual firms or industries. Given that the primitive (industry or firm) technologies exhibit homothetic separability, the authors establish necessary and sufficient conditions for the aggregate (sectoral) technology to also exhibit homothetic separability. These conditions are expressed in terms of the cost functions of the p…
Econometric Applications of Maximum Likelihood Methods
The advent of electronic computing permits the empirical analysis of economic models of far greater subtlety and rigour than before, when many interesting ideas were not followed up because the calculations involved made this impracticable. The estimation and testing of these more intricate models is usually based on the method of Maximum Likelihood, which is a well-established branch of mathematical statistics. Its use in econometrics has led to…
Specification Analysis in the Linear Model
No prominent works on this page.
Econometric Applications of Maximum Likelihood Methods
The advent of electronic computing permits the empirical analysis of economic models of far greater subtlety and rigour than before, when many interesting ideas were not followed up because the calculations involved made this impracticable. The estimation and testing of these more intricate models is usually based on the method of Maximum Likelihood, which is a well-established branch of mathematical statistics. Its use in econometrics has led to…
Specification Analysis in the Linear Model
Separability and Aggregation
This paper examines the conditions for homothetic separability of a technology that is an aggregate of technologies of individual firms or industries. Given that the primitive (industry or firm) technologies exhibit homothetic separability, the authors establish necessary and sufficient conditions for the aggregate (sectoral) technology to also exhibit homothetic separability. These conditions are expressed in terms of the cost functions of the p…
Bayesian Estimation of the Normal Location Model: A Non‐Standard Approach
We consider the estimation of the location parameter in the normal location model and study the sampling properties of shrinkage estimators derived from a non‐standard Bayesian approach that places the prior on a scaled version of , interpreted as the “population ‐ratio.” We show that the finite‐sample distribution of these estimators is not centred at and is generally non‐normal. In the asymptotic theory, we prove uniform ‐consistency of our est…
Econometrics (4 works) · Economics (3 works) · Mathematics (3 works) · Computer Science (2 works) · Estimation (2 works) · Statistics (2 works) · Advanced Data Processing Techniques (1 works) · Bayes estimator (1 works) · Bayesian probability (1 works) · Complex Systems and Time Series Analysis (1 works)