Bayesian analysis of structural change in a distributed Lag Model (Koyck Scheme)

• Autorzy: Arvin Paul B. Sumobay , Arnulfo P. Supe
• Języki publikacji: EN

Abstrakty

EN

Structural change for the Koyck Distributed Lag Model is analyzed through the Bayesian approach. The posterior distribution of the break point is derived with the use of the normal-gamma prior density and the break point, ν, is estimated by the value that attains the Highest Posterior Probability (HPP). Simulation study is done using R.
Given the parameter values ϕ = 0.2 and λ = 0.3, the full detection of the structural change when σ² = 1 is generally attained at ν + 1. The after one lag detection is due to the nature of the model which includes lagged variable. The interval estimate HPP near ν consistently and efficiently captures the break point ν in the interval HPPₜ ± 5% of the sample size. On the other hand, the detection of the structural change when σ² = 2 does not show any improvement of the point estimate of the break point ν.

Słowa kluczowe

EN

distributed lag model; posterior distribution; break point

Kategorie tematyczne

• 62F15: Bayesian inference
• 62P20: Applications to economics
• 62C10: Bayesian problems; characterization of Bayes procedures
• 47N30: Applications in probability theory and statistics

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2014
• Tom: 34
• Numer: 1-2
• Strony: 113-126

Daty

wydano

2014

otrzymano

2014-08-29

Twórcy

autor

Arvin Paul B. Sumobay

• Mathematics Department, Mindanao State University, Marawi City, 9700, Philippines

autor

Arnulfo P. Supe

• Department of Mathematics and Statistics, Mindanao State University-Iligan Institute of Technology, Iligan City, 9200, Philippines

Bibliografia

• [1] G. Casella and R. Berger, Statistical Inference, First Edition (Brookes/Cole Publishing Company, 1990).
• [2] A. Chaturvedia and A. Shrivastavab, Bayesian Analysis of a Linear Model Involving Structural Changes in Either Regression Parameters or Disturbances Precision (Department of Statistics, University of Allahabad, Allahabad U.P 211002 India, 2012).
• [3] L.M. Koyck, Distributed lags models and investment analysis (Amsterdam, North-Holland, 1954).
• [4] J.H. Park, Bayesian Analysis of Structural Changes: Historical Changes in US Presidential Uses of Force (Annual Meeting of the Society for Political Methodology, 2007).
• [5] A.P. Supe, Parameter changes in autoregressive processes: A Bayesian approach, Philippine Stat. J. 44-45 (1-8) (1996) 27-32.
• [6] B. Western and M. Kleykamp, A Bayesian Change Point Model for Historical Time Series Analysis (Princeton University, 2004).

Identyfikatory

DOI

10.7151/dmps1171