Abstract
This paper aimed to measure the welfare of the Thai rice market and provided a new estimation in welfare measurement. We applied the Markov Switching approach to the Seemingly Unrelated Regression model and adopted the Bayesian approach as an estimator for our model. Thus, we have the MS-BSUR model as an innovative tool to measure the welfare. The results showed that the model performed very well in estimating the demand and supply equations of two different regimes; namely, high growth and low growth. The equations were extended to compute the total welfare. Then, the expected welfare during the studied period was determined. We found that a mortgage scheme may lead the market to gain a high level of welfare. Eventually, the forecasts of demand and supply were estimated for 10 months, and we found demand and supply would tend to increase in the next few months before dropping around March, 2015.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Artis, M., Krolzig, H.M., Toro, J.: The European business cycle. Oxford Economic Papers 56(1), 1–44 (2004)
Ayusuk, A., Sriboonchitta, S.: Risk Analysis in Asian Emerging Markets using Canonical Vine Copula and Extreme Value Theory. Thai Journal of Mathematics 59–72 (2014)
Baltagi, B.H., Pirotte, A.: Seemingly unrelated regressions with spatial error components. Empirical Economics 40(1), 5–49 (2011)
Boonyanuphong, P., Sriboonchitta, S.: The Impact of Trading Activity on Volatility Transmission and Interdependence among Agricultural Commodity Markets. Thai Journal of Mathematics 211–227 (2014)
Brandt, P.T.: Empirical Regime Specific Models of International, Inter-group Conflict, and Politics (2009)
Chinnakum, W., Sriboonchitta, S., Pastpipatkul, P.: Factors affecting economic output in developed countries: A copula approach to sample selection with panel data. International Journal of Approximate Reasoning 54(6), 809–824 (2013)
Engel, C., Hamilton, J.D.: Long swings in the exchange rate: Are they in the data and do markets knowing it? (No. w3165). National Bureau of Economic Research (1989)
Frühwirth-Schnatter, S.: Finite Mixture and Markov Switching Models: Modeling and Applications to Random Processes. Springer (2006)
Hamilton, J.D.: A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica: Journal of the Econometric Society 357–384 (1989)
Kim, C.J., Nelson, C.R.: State-space models with regime switching (1999)
Krolzig, H.M.: Markov switching vector autoregressions: modelling, statistical inference and application to business cycle analysis. Springer, Berlin (1997)
Kuson, S., Sriboonchitta, S., Calkins, P.: The determinants of household expenditures in Savannakhet, Lao PDR: A Seemingly Unrelated Regression analysis. The Empirical Econometrics and Quantitative Economics Letters 1(4), 39–60 (2012)
Lar, N., Calkins, P., Sriboonchitta, S., Leeahtam, P.: Policy-based analysis of the intensity, causes and effects of poverty: the case of Mawlamyine, Myanmar. Canadian Journal of Development Studies/Revue canadienne d’études du développement 33(1), 58–76 (2012)
Phitthayaphinant, P., Somboonsuke, B., Eksomtramage, T.: Supply response function of oil palm in Thailand. Journal of Agricultural Technology 9(4), 727–747 (2013)
Sims, C.A., Waggoner, D.F., Zha, T.: Methods for inference in large multiple-equation Markov-switching models. Journal of Econometrics 146(2), 255–274 (2008)
Sriboonchitta, S., Liu, J., Kreinovich, V., Nguyen, H.T.: A vine copula approach for analyzing financial risk and co-movement of the Indonesian, Philippine and Thailand stock markets. In: Huynh, V.-N., Kreinovich, V., Sriboonchitta, S. (eds.) Modeling Dependence in Econometrics. AISC, vol. 251, pp. 281–294. Springer, Heidelberg (2014)
Zellner, A.: An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American statistical Association 57(298), 348–368 (1962)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Pastpipatkul, P., Maneejuk, P., Sriboonchitta, S. (2015). Welfare Measurement on Thai Rice Market: A Markov Switching Bayesian Seemingly Unrelated Regression. In: Huynh, VN., Inuiguchi, M., Demoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2015. Lecture Notes in Computer Science(), vol 9376. Springer, Cham. https://doi.org/10.1007/978-3-319-25135-6_42
Download citation
DOI: https://doi.org/10.1007/978-3-319-25135-6_42
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25134-9
Online ISBN: 978-3-319-25135-6
eBook Packages: Computer ScienceComputer Science (R0)