Next Article in Journal
Economic Reforms, Labour Markets and Formal Sector Employment: Evidence from India
Next Article in Special Issue
Mining Booms and Sustainable Economic Growth in Mongolia—Empirical Result from Recursive Dynamic CGE Model
Previous Article in Journal
Correction of Accounting Errors through Post Balance Sheet Event Analysis for Romanian Companies
Previous Article in Special Issue
Determinants of Sino-ASEAN Banking Efficiency: How Do Countries Differ?
Open AccessArticle

Assessing Regional Economic Performance in the Southern Thailand Special Economic Zone Using a Vine-COPAR Model

1
Faculty of Economics, Prince of Songkla University, Songkhla 90110, Thailand
2
Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand
3
Faculty of Economics, Shandong University of Finance and Economics, Jinan 250000, China
4
Puey Ungphakorn Center of Excellence in Econometrics, Faculty of Economics, Chiang Mai 50200, Thailand
*
Author to whom correspondence should be addressed.
Economies 2019, 7(2), 30; https://doi.org/10.3390/economies7020030
Received: 17 January 2019 / Revised: 25 March 2019 / Accepted: 26 March 2019 / Published: 2 April 2019
(This article belongs to the Special Issue Computational Macroeconomics)
Special economic zones (SEZ) can play an integral role in enhancing both regional and national economic growth. To explore the relationship between regional growth and the presence of an SEZ in Songkhla province, Thailand, the CD Vine–Copula AutoRegressive (CD-Vine COPAR) models were constructed using annual datasets of Songkhla’s economic performance from 1995 to 2016. The findings indicate that the D Vine-COPAR model produced better fitting predictions for the manufacturing sector, while the C Vine-COPAR models better fit for the agriculture and service sectors. A five-year forecast (2017–2021) was also created. For Vine-COPAR-based Granger causality, the Gross Provincial Production, Foreign Direct Investment and Border Trade are evidently important contributors to regional economic development. Consequently, the government should adopt comprehensive strategies to ensure comparative advantages for operating in the region based on favorable local factors. View Full-Text
Keywords: Vine copulas; multivariate time series; forecasting techniques; evaluation of prediction model; Granger causality Vine copulas; multivariate time series; forecasting techniques; evaluation of prediction model; Granger causality
Show Figures

Figure 1

MDPI and ACS Style

Romyen, A.; Liu, J.; Sriboonchitta, S.; Cherdchom, P.; Prommee, P. Assessing Regional Economic Performance in the Southern Thailand Special Economic Zone Using a Vine-COPAR Model. Economies 2019, 7, 30.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop