### Abstract

The marginal propensity to consume in a simple Keynesian model is treated as a random coefficient. This gives rise to the problem of quotient of random variables, i.e., the Fieller-Creasy problem. The Bayesian and maximum likelihood estimators are compared in sampling experiments. The Bayesian estimators have smaller mean squared errors than the maximum likelihood estimators. Marginal posterior probability density functions for a given sample are also presented.

Original language | English |
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Pages (from-to) | 239-249 |

Number of pages | 11 |

Journal | Journal of Econometrics |

Volume | 18 |

Issue number | 2 |

DOIs | |

Publication status | Published - 1982 |

Externally published | Yes |

### Fingerprint

### ASJC Scopus subject areas

- Economics and Econometrics
- Finance
- Statistics and Probability

### Cite this

*Journal of Econometrics*,

*18*(2), 239-249. https://doi.org/10.1016/0304-4076(82)90038-0

**A bayesian analysis of a random coefficient model in a simple keynesian system.** / Tsurumi, Hiroki; Shiba, Tsunemasa.

Research output: Contribution to journal › Article

*Journal of Econometrics*, vol. 18, no. 2, pp. 239-249. https://doi.org/10.1016/0304-4076(82)90038-0

}

TY - JOUR

T1 - A bayesian analysis of a random coefficient model in a simple keynesian system

AU - Tsurumi, Hiroki

AU - Shiba, Tsunemasa

PY - 1982

Y1 - 1982

N2 - The marginal propensity to consume in a simple Keynesian model is treated as a random coefficient. This gives rise to the problem of quotient of random variables, i.e., the Fieller-Creasy problem. The Bayesian and maximum likelihood estimators are compared in sampling experiments. The Bayesian estimators have smaller mean squared errors than the maximum likelihood estimators. Marginal posterior probability density functions for a given sample are also presented.

AB - The marginal propensity to consume in a simple Keynesian model is treated as a random coefficient. This gives rise to the problem of quotient of random variables, i.e., the Fieller-Creasy problem. The Bayesian and maximum likelihood estimators are compared in sampling experiments. The Bayesian estimators have smaller mean squared errors than the maximum likelihood estimators. Marginal posterior probability density functions for a given sample are also presented.

UR - http://www.scopus.com/inward/record.url?scp=49049144006&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=49049144006&partnerID=8YFLogxK

U2 - 10.1016/0304-4076(82)90038-0

DO - 10.1016/0304-4076(82)90038-0

M3 - Article

VL - 18

SP - 239

EP - 249

JO - Journal of Econometrics

JF - Journal of Econometrics

SN - 0304-4076

IS - 2

ER -