FACTORS AFFECTING THE NUMBER OF REGISTERED AUTOMOBILE INSURANCE IN MYANMAR BASED ON BAYESIAN MODELING USING THE MCMC PROCEDURE

Aint Phone San
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Aint Phone San: Chiang Mai, University, Thailand

International Journal of Humanities, Arts and Social Sciences, 2016, vol. 2, issue 2, 74-86

Abstract: Insurance plays a vital role in financial sector. Myanmar economy is dramatically developed under new nominally civilian government’s policies. This paper presents how government policy changing in other factors affects automobile insurance premium by using MCMC methods which is developed from Bayesian inference. The annual secondary data of registered vehicles, Gross Domestic Product (GDP), Population, premium of Third Party Liability Motor Insurance and Comprehensive Motor Insurance over the period of 1994 to 2014 were used in this study. The Metropolis-Hastings algorithm and Gibbs sampling are applied in this study. Raftery and Lewis convergence diagnostic are computed for MCMC sampler output to determine accuracy and probability of the parameter within a specified quantile to estimate if the parameters are convergent or not. The results show that there is a positive relationship between automobile insurance and other factors such as GDP, registered vehicles and population. However, the number of registered vehicles has no impact on automobile insurance although there is a mandatory motor insurance law in Myanmar.

Keywords: Myanmar; Automobile Insurance; Registered Vehicles; Bayesian Methodology; MCMC (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:apa:ijhass:2016:p:74-86

DOI: 10.20469/ijhss.2.20004-2

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