Skip to main content

Impact Analysis of the Economic Eastern Corridor on the Thai Economy: An Application of Multi-Regional Input–Output Model and Dynamic Computable General Equilibrium Model

  • Chapter
  • First Online:
The Indonesian Economy and the Surrounding Regions in the 21st Century

Part of the book series: New Frontiers in Regional Science: Asian Perspectives ((NFRSASIPER,volume 76))

  • 44 Accesses

Abstract

To facilitate the multi-sectoral investment, the Thai government has initiated a new development project titled Eastern Economic Corridor (EEC), located in the eastern provinces, namely Chachoengsao, Rayong, and Chonburi. This project accommodates the construction of a new high-speed train and the extensions of existing seaports, highways, and airports. Also, investment promotion has been implemented, offering the tax incentive and other benefits to the targeted industries. This study aimed to quantitatively examine the economic impacts of the EEC project by utilizing two methods. First, the multi-regional input–output table (MRIO) and multiplier analysis were applied to investigate the cross-province and cross-region impacts. Second, based on the national Social Accounting Matrix (SAM), the dynamic Computable General Equilibrium (CGE) model was utilized for examining the inter-temporal effects. The result obtained from MRIO showed that investment expansion in the EEC area could induce cross-regional spillover, accounting for approximately 30% of GDP. The dynamic CGE model demonstrated that if the planned investments were continuously implemented, the GDP would consistently increase, resulting in an average household income rise of around 31% in 2034 compared to the base case. This study highlights the complementary use of two models to evaluate the multidimensional impacts of the EEC development project, including short-term spatial spillovers and long-term national effects.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This project was jointly initiated by the discovery of natural gas in the Gulf of Thailand and the expansion of FDI inflows. This special development zone includes Chonburi, Chachoengsao, and Rayong provinces. Based on NESDC’s statistics in 2014, these three provinces contributed an economic output of US$ 65,264 million, approximately 18% of Thailand’s GDP. In particular, there were 39 industrial parks in this development zone, generating 34% of the national industrial production.

  2. 2.

    All cells in Table 11.1 are intentionally left blank. Also, some calls in Table 11.2 are blank because they contain no economic transaction based on the conventional structure of SAM.

References

  • Aggarwal A, Hoppe M, Walkenhorst P (2008) Special economic zones in South Asia: industrial islands or vehicles for diversification? In: Newfarmer R, Shaw W, Walkenhorst P (eds) Breaking into new markets: emerging lessons for export diversification. World Bank, Washington, DC, pp 223–236

    Google Scholar 

  • Akiyama Y (1996) An analysis of the decentralization policy in Thailand with the interregional input-output table. Input-Output Anal 7(3):17–23. (in Japanese)

    Article  Google Scholar 

  • Alder S, Shao L, Zilibotti F (2013) The effect of economic reform and industrial policy in a panel of Chinese cities. Meeting papers 2013 no 1309. Society for Economic Dynamics. https://economicdynamics.org/meetpapers/2013/paper_1309.pdf

  • Asian Development Bank (ADB) (2015) Asian economic integration Report 2015: how can special economic zones catalyze economic development? Asian Development Bank, Mandaluyong City, Philippines

    Google Scholar 

  • Azis I (1998) The relevance of price endogenous models. Reg Sci Rev 17:1–20

    Google Scholar 

  • Bernard AB, Jones CI (1996) Comparing apples to oranges: productivity convergence and measurement across industries and countries. Am Econ Rev 86(5):1216–1238

    Google Scholar 

  • Buera FJ, Kaboski JP, Rogerson R (2015) Skill biased structural change. NBER Working Paper, 21165

    Google Scholar 

  • Caron J, Markusen JR (2014) International trade puzzles: a solution linking production and preferences. Q J Econ 129:1501–1552

    Article  Google Scholar 

  • Comin DA, Lashkari D, Mestieri M (2015) Structural change with long-run income and price effects. National Bureau of Economic Research Working Paper Series, No. 21595

    Google Scholar 

  • Deculawe B, Lemenin A, Robichaud V, Maisonnave H (2013) PEP-1-t. The PEP standard single-country, recursive dynamic CGE model (version 2.1), Partnership for Economic Policy (PEP) Research Network, Université Laval, Québec

    Google Scholar 

  • Duarte M, Restuccia D (2010) The role of the structural transformation in aggregate productivity. Q J Econ 125:129–173

    Article  Google Scholar 

  • Fagerberg J (2000) Technological progress, structural change and productivity growth: a comparative study. Struct Chang Econ Dyn 11(4):393–411

    Article  Google Scholar 

  • Fieler AC (2011) Nonhomotheticity and bilateral trade: evidence and a quantitative explanation. Econometrica 79(4):1069–1101

    Article  Google Scholar 

  • Garcia F, Jin B, Salomon R (2013) Does inward foreign direct investment improve the innovative performance of local firms? Res Policy 42:231–244

    Article  Google Scholar 

  • Griffith R, Redding S, Reenen JV (2004) Mapping the two faces of R&D: productivity growth in a panel of OECD industries. Rev Econ Stat 86(4):883–895

    Article  Google Scholar 

  • Hansen BE (2001) The new econometrics of structural change: dating breaks in U.S. labor productivity. J Econ Perspect 15(4):117–128

    Article  Google Scholar 

  • Hirsch WZ (1959) Interindustry relations of a metropolitan area. Rev Econ Stat 41:360–369

    Article  Google Scholar 

  • Isard W (1951) Interregional and regional input-output analysis: a model of a space-economy. Rev Econ Stat 33(4):318–328

    Article  Google Scholar 

  • Isard W, Azis IJ (1998) Applied general interregional equilibrium. In: Methods of interregional and regional analysis. Routledge, pp 333–400

    Google Scholar 

  • Isard W, Kuenne RE (1953) The impact of steel upon the greater New York-Philadelphia industrial region. Rev Econ Stat 35:289–301

    Google Scholar 

  • Isard W, Langford T (1971) Regional input-output study: recollections, reflections and diverse notes on the Philadelphia experience. The MIT Press, Cambridge, MA

    Google Scholar 

  • Johannsson H, Nilsson L (1997) Export zones as catalysts. World Dev 25(12):2155–2172

    Article  Google Scholar 

  • Leontief W, Strout A (1963) Multiregional input-output analysis. In: Barna T (ed) Structural interdependence and economic development. Macmillan (St. Martin’s Press), London, pp 119–149

    Chapter  Google Scholar 

  • Matsuyama K (2002) The rise of mass consumption societies. J Polit Econ 110(5):1035–1070

    Article  Google Scholar 

  • McMillan M, Rodrik D (2011) Globalization, structural change and productivity growth. NBER Working Paper, w17143

    Google Scholar 

  • Miernyk WH (1982) Regional analysis and regional policy. Oelgeschlager, Gunn & Hain, Inc, Cambridge, MA

    Google Scholar 

  • Miller RE (1957) The impact of the aluminum industry on the Pacific northwest: a regional input-output analysis. Rev Econ Stat 39:200–209

    Article  Google Scholar 

  • Miller R, Blair PD (2009) Input-output analysis foundations and extensions, 2nd edn. Cambridge University Press

    Book  Google Scholar 

  • Nadvi, K., & Schmitz, H. (1994). Industrial clusters in less developed countries: a review of experiences and research agenda. Discussion paper 339. Institute of Development Studies (IDS), University of Sussex, Brighton

    Google Scholar 

  • Osabutey ELC, Williams K, Debrah YA (2014) The potential for technology and knowledge transfers between foreign and local firms: a study of the construction industry in Ghana. J World Bus 49(4):560–571. Elsevier

    Article  Google Scholar 

  • Padilla-Pérez R, Villarreal FG (2017) Structural change and productivity growth in Mexico, 1990-2014. Struct Chang Econ Dyn 41:53–63

    Article  Google Scholar 

  • Phomsoda K, Puttanapong N, Piantanakulchai M (2021) Assessing economic impacts of Thailand’s fiscal reallocation between biofuel subsidy and transportation investment: application of recursive dynamic general equilibrium model. Energies 14(14):4248

    Article  Google Scholar 

  • Polenske KR (1980) The U.S. multiregional input-output accounts and model. Lexington Books (D. C. Heath and Co.), Lexington, MA

    Google Scholar 

  • Roson R, van der Mensbrugghe D (2018) Demand-driven structural change in general equilibrium models. In: Perali F, Scandizzo PL (eds) The new generation of computable general equilibrium models. Springer

    Google Scholar 

  • Shibusawa H, Anantsuksomsri S, Tontisirin N, Puttanapong N (2018) Evaluating the spatial linkages of Thailand’s inter-provincial economies and industries: an input-output approach. In: Komaki Y (ed) The future of southeast Asian countries—population change, climate change, Management of Japanese Companies and Competitiveness. Tokyo, Yachiyo Shuppan

    Google Scholar 

  • Sjöholm F (1999) Productivity growth in Indonesia: the role of regional characteristics and foreign direct investment. Econ Dev Cult Chang 47(3):559–584

    Article  Google Scholar 

  • Sorensen BA (2001) Comparing apples to oranges: productivity convergence and measurement across industries and countries: comment. Am Econ Rev 91(4):1160–1167

    Article  Google Scholar 

  • Thompson E (2002) Clustering of foreign direct investment and enhanced technology transfer: evidence from Hong Kong garment firms in China. World Dev 30(5):873–889

    Article  Google Scholar 

  • Vahter P (2011) Does FDI spur productivity, knowledge sourcing and innovation by incumbent firms? Evidence from manufacturing industry in Estonia. World Econ 34:1308–1326

    Article  Google Scholar 

  • Vu K (2017) Structural change and economic growth: empirical evidence and policy insights from Asian economies. Struct Chang Econ Dyn 41:64–77

    Article  Google Scholar 

  • Wang J (2013) The economic impact of special economic zones: evidence from Chinese municipalities. J Dev Econ 101:133–147

    Article  Google Scholar 

  • Yamada M, Owaki Y (2012) Estimation of the multiregional input-output table for four regions in Aichi. Chukyo University Institute of Economics, Discussion Paper Series, No 1, 205: 1–53. (in Japanese)

    Google Scholar 

  • Young A (2014) Structural transformation, the mismeasurement of productivity growth, and the cost disease of services. Am Econ Rev 104(11):3635–3667

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nattapong Puttanapong .

Editor information

Editors and Affiliations

Appendix

Appendix

1.1 Appendix 1 Details of Investment (for MRIO Multiplier Analysis)

Table 11.11 Estimate of investment in Chachoengsao province in 2021
Table 11.12 Estimate of investment in Chonburi province in 2021
Table 11.13 Estimate of investment in Rayong province in 2021

1.2 Appendix 2 Lists of Sets, Parameters, Variables, and Equations of CGE Model

1.2.1 List of Sets

j

:

All sectors

pub

:

Public sectors

pri

:

Private industries

j0

:

All sectors except sugar cane and petroleum refinery sector

j1

:

Sugar cane and petroleum refinery sector

i

:

All commodities

ij

:

All commodities (alias commodities)

i1

:

All commodities except mixed gasohol and mixed biodiesel

i2

:

Mixed gasohol

i3

:

Mixed biodiesel

i4

:

Mass transportation

i5

:

Freight transportation

l

:

Labor

k

:

Capital

ag

:

All agents (firms, households, government, and the rest of the world)

agng

:

Non-government agents (firms, households, and the rest of the world)

agd

:

Domestic agents (firms, households, and government)

gvt

:

Government

row

:

The rest of the world

f

:

Firms

h

:

Households

t

:

Time for simulation

1.2.2 Lists of Parameters

Input–output coefficient

aij

:

Input–output coefficient of intermediate commodity i for industry j

admj

:

Input–output coefficient of mixed biodiesel for industry j

agmj

:

Input–output coefficient of mixed gasohol for industry j

aftj

:

Input–output coefficient of freight transportation for industry j

amtj

:

Input–output coefficient of mass transportation for industry j

ioj

:

Input–output coefficient (total intermediate consumption) for industry j

vj

:

Input–output coefficient (total value-added) for industry j

Scale share and elasticity of production function

\( {B}_{j,t}^{VAT} \)

:

Scale parameter (CES—Value-added) for industry j

\( {\beta}_j^{VA} \)

:

Share parameter (CES—Value-added) for industry j

\( {\rho}_j^{VA} \)

:

Elasticity parameter (CES—Value-added) for industry j; \( -1<{\rho}_j^{VA}<\infty \)

\( {\sigma}_j^{VA} \)

:

Elasticity of substitution (CES—Value-added) for industry j; \( 0<{\sigma}_j^{VA}<\infty \),

Where \( {\rho}_j^{VA}=\frac{1-{\sigma}_j^{VA}}{\sigma_j^{VA}} \)

\( {B}_j^{KD} \)

:

Scale parameter (CES—Composite capital) for industry j

\( {\beta}_{k,j}^{KD} \)

:

Share parameter (CES—Composite capital) for industry j

\( {\rho}_j^{KD} \)

:

Elasticity parameter (CES—Composite capital) for industry j; \( -1<{\rho}_j^{KD}<\infty \)

\( {\sigma}_j^{KD} \)

:

Elasticity of substitution (CES—Composite capital) for industry j; \( 0<{\sigma}_j^{KD}<\infty \),

Where \( {\rho}_j^{KD}=\frac{1-{\sigma}_j^{KD}}{\sigma_j^{KD}} \)

\( {B}_j^{LD} \)

:

Scale parameter (CES—Composite labor) for industry j

\( {\beta}_{l,j}^{LD} \)

:

Share parameter (CES—Composite labor) for industry j

\( {\rho}_j^{LD} \)

:

Elasticity parameter (CES—Composite labor) for industry j; \( -1<{\rho}_j^{LD}<\infty \)

\( {\sigma}_j^{LD} \)

:

Elasticity of substitution (CES—Composite labor) for industry j; \( 0<{\sigma}_j^{LD}<\infty \),

Where \( {\rho}_j^{LD}=\frac{1-{\sigma}_j^{LD}}{\sigma_j^{LD}} \)

\( {B}_j^{GM} \)

:

Scale parameter (CES—Composite mixed gasohol) for industry j

\( {\beta}_j^{GM} \)

:

Share parameter (CES—Composite mixed gasohol) for industry j

\( {\rho}_j^{GM} \)

:

Elasticity parameter (CES—Mixed gasohol) for industry j; \( -1<{\rho}_j^{GM}<\infty \)

\( {\sigma}_j^{GM} \)

:

Elasticity of substitution (CES—Mixed gasohol) for industry j; \( 0<{\sigma}_j^{GM}<\infty \),

Where \( {\rho}_j^{GM}=\frac{1-{\sigma}_j^{GM}}{\sigma_j^{GM}} \)

\( {B}_j^{DM} \)

:

Scale parameter (CES—Composite mixed biodiesel) for industry j

\( {\beta}_j^{DM} \)

:

Share parameter (CES—Composite mixed biodiesel) for industry j

\( {\rho}_j^{DM} \)

:

Elasticity parameter (CES—Mixed biodiesel) for industry j; \( -1<{\rho}_j^{DM}<\infty \)

\( {\sigma}_j^{DM} \)

:

Elasticity of substitution (CES—Mixed biodiesel) for industry j; \( 0<{\sigma}_j^{DM}<\infty \),

Where \( {\rho}_j^{DM}=\frac{1-{\sigma}_j^{DM}}{\sigma_j^{DM}} \)

\( {B}_j^{MT} \)

:

Scale parameter (CES—Mass transportation) for industry j

\( {\beta}_j^{MT} \)

:

Share parameter (CES—Mass transportation) for industry j

\( {\rho}_j^{MT} \)

:

Elasticity parameter (CES—Mass transportation) for industry j; \( -1<{\rho}_j^{MT}<\infty \)

\( {\sigma}_j^{MT} \)

:

Elasticity of substitution (CES—Mass transportation) for industry j; \( 0<{\sigma}_j^{MT}<\infty \),

Where \( {\rho}_j^{MT}=\frac{1-{\sigma}_j^{MT}}{\sigma_j^{MT}} \)

\( {B}_j^{FT} \)

:

Scale parameter (CES—Freight transportation) for industry j

\( {\beta}_j^{FT} \)

:

Share parameter (CES—Freight transportation) for industry j

\( {\rho}_j^{FT} \)

:

Elasticity parameter (CES—Freight transportation) for industry j; \( -1<{\rho}_j^{FT}<\infty \)

\( {\sigma}_j^{FT} \)

:

Elasticity of substitution (CES—Freight transportation) for industry j; \( 0<{\sigma}_j^{FT}<\infty \),

Where \( {\rho}_j^{FT}=\frac{1-{\sigma}_j^{FT}}{\sigma_j^{FT}} \)

\( {B}_i^M \)

:

Scale parameter (CES—Composite commodity)

\( {\beta}_i^M \)

:

Share parameter (CES—Composite commodity)

\( {\rho}_i^M \)

:

Elasticity parameter (CES—Composite commodity); \( -1<{\rho}_i^M<\infty \)

\( {\sigma}_i^M \)

 

Elasticity of substitution (CES—Composite commodity); \( 0<{\sigma}_i^M<\infty \),

Where \( {\rho}_i^M=\frac{1-{\sigma}_i^M}{\sigma_i^M} \)

\( {B}_{j,i}^X \)

:

Scale parameter (CET—Exports and local sales)

\( {\beta}_{j,i}^X \)

:

Share parameter (CET—Exports and local sales)

\( {\rho}_{j,i}^X \)

:

Elasticity parameter (CET—Exports and local sales); \( 1<{\rho}_{j,i}^X<\infty \)

\( {\sigma}_{j,i}^X \)

:

Elasticity of transformation (CET—Total output); \( 0<{\sigma}_j^{XT}<\infty \),

Where \( {\rho}_{j,i}^X=\frac{1+{\sigma}_{j,i}^X}{\sigma_{j,i}^X} \)

\( {B}_j^{XT} \)

:

Scale parameter (CET—Total output) for industry j

\( {\beta}_{j,i}^{XT} \)

:

Share parameter (CET—Total output) for industry j

\( {\rho}_j^{XT} \)

:

Elasticity parameter (CET—Total output) for industry j; \( 1<{\rho}_j^{XT}<\infty \)

\( {\sigma}_j^{XT} \)

:

Elasticity of transformation (CET—Total output) for industry j; \( 0<{\sigma}_j^{XT}<\infty \),

Where \( {\rho}_j^{XT}=\frac{1+{\sigma}_j^{XT}}{\sigma_j^{XT}} \)

\( {\sigma}_i^{XD} \)

:

Price-elasticity of the world demand for exports of product i

extri, t

:

Export growth rate of product i

Parameters for income saving and investment of institutes

\( {\lambda}_{ag,k}^{RK} \)

:

Share of type k capital income received by agent ag

\( {\lambda}_{h,l}^{WL} \)

:

Share of type l labor income received by type h households

sh0h, t

:

Intercept (type h household savings)

sh1h, t

:

Slope (type h household savings)

\( {\gamma}_{i,h}^{LES} \)

:

Marginal share of commodity i in type h household consumption budget

\( {\gamma}_i^{INVPRI} \)

:

Share of commodity i in total private investment expenditures

\( {\gamma}_i^{INVPUB} \)

:

Share of commodity i in total public investment expenditures

\( {\gamma}_i^{GVT} \)

:

Share of commodity i in total current public expenditures on goods and services

AK _ PRI

:

Scale parameter (price for new private capital)

AK _ PUB

:

Scale parameter (price for new public capital)

ϕk, pri

:

Scale parameter (allocation of investment to industry)

δk, pub

:

Deprecation rate of capital k used in public

Tax and transfer

\( {\lambda}_{ag, ag}^{TR} \)

:

Share parameter (transfer functions) between ag

η

:

Price elasticity of indexed transfers and parameters

tmrgi, i

:

Rate of transport margin applied to domestic commodity i

\( tmr{g}_{i,i}^X \)

:

Rate of transport margin applied to export commodity i

tr0gvt, h, t

:

Intercept (transfers by type h households to government)

tr1gvt, h, t

:

Marginal rate of transfers by type h households to government

ttici, t

:

Tax rate on commodity i

ttdf0f, t

:

Intercept (income taxes of type f businesses)

ttdf1f, t

:

Marginal income tax rate of type f businesses

ttdh0h, t

:

Intercept (income taxes of type h households)

ttdh1h, t

:

Marginal income tax rate of type h households

ttikk, j, t

:

Tax rate on type k capital used by industry j

ttimi, t

:

Rate of taxes and duties on imports of commodity i

ttipj, t

:

Tax rate on the production of industry j

ttiwl, j, t

:

Tax rate on type l worker compensation in industry j

ttixi, t

:

Export tax rate on exported commodity i

1.2.3 List of Variables

Prices and wages

Pj, i, t

:

Basic price of industry j’s production of commodity i

PCi, t

:

Purchaser price of composite commodity i (including all taxes and margins)

\( P{C}_i^0 \)

:

Purchaser price of composite commodity i (base year)

PCIj, t

:

Intermediate consumption price index of industry j

PDi, t

:

Price of local product i sold on the domestic market

PDMj, t

:

Aggregate price of mixed biodiesel by industry j

PEi, t

:

Price received for exported commodity i (excluding export taxes)

\( P{E}_{i,t}^{FOB} \)

:

FOB price of exported commodity i (in local currency)

PFTj, t

:

Aggregate price of freight transportation by industry j

PGMj, t

:

Aggregate price of mixed gasohol by industry j

\( PIXCO{N}_t^{\eta } \)

:

Consumer price index

PIXGDPt

:

GDP deflator

PIXGVTt

:

Public expenditures price index

\( PIXIN{V}_t^{PRI} \)

:

Private investment price index

\( PIXIN{V}_t^{PUB} \)

:

Public investment price index

\( P{K}_t^{PRI} \)

:

Price of new private capital

\( P{K}_t^{PUB} \)

:

Price of new public capital

PLi, t

:

Price of local product i (excluding all taxes on products)

PMi, t

:

Price of imported product i (including all taxes and margins)

PMTj, t

:

Aggregate price of mass transportation by industry j

PPj, t

:

Industry j unit cost

PTj, t

:

Basic price of industry j output

PVAj, t

:

Price of industry j value-added

PWMi, t

:

World price of imported product i (expressed in foreign currency)

PWXi, t

:

World price of exported product i (expressed in foreign currency)

Rk, j, t

:

Rental rate of type k capital in industry j

RCj, t

:

Rental rate of industry j composite capital

RTIk, j, t

:

Rental rate paid by industry j for type k capital, including capital taxes

Wl, t

:

Wage rate of type l labor

WCj, t

:

Wage rate of industry j composite labor

WTIl, j, t

:

Wage rate paid by industry j for type l labor, including payroll taxes

Uk, pri, t

:

User cost of type k capital in private industry

Uk, pub, t

:

User cost of type k capital in public industry

Taxes

TDFf, t

:

Income taxes of type f businesses

TDFTt

:

Total government revenue from business income taxes

TDHh, t

:

Income taxes of type h households

TDHTt

:

Total government revenue from household income taxes

TICi, t

:

Government revenue from indirect taxes on product i

TICTt

:

Total government receipts of indirect taxes on commodities

TIKk, j, t

:

Government revenue from taxes on type k capital used by industry j

TIKTt

:

Total government revenue from taxes on capital

TIMi, t

:

Government revenue from import duties on product i

TIMTt

:

Total government revenue from import duties

TIPj, t

:

Government revenue from taxes on industry j production (excluding taxes directly related to the use of capital and labor)

TIPTt

:

Total government revenue from production taxes (excluding taxes directly related to the use of capital and labor)

TIWl, j, t

:

Government revenue from payroll taxes on type l labor in industry j

TIWTt

:

Total government revenue from payroll taxes

TIXi, t

:

Government revenue from export taxes on product i

TIXTt

:

Total government revenue from export taxes

Quantity

Ci, h, t

:

Consumption of commodity i by type h households

\( {C}_{i,h,t}^{MIN} \)

:

Minimum consumption of commodity i by type h households

CGi, t

:

Public consumption of commodity i (volume)

CIj, t

:

Total intermediate consumption of industry j

CTHh, t

:

Consumption budget of type h households

\( CT{H}_{h,t}^{REAL} \)

:

Real consumption expenditure of households h

DDi, t

:

Domestic demand for commodity i produced locally

DIi, j, t

:

Intermediate consumption of commodity i by industry j

DIDMj, t

:

Aggregate intermediate consumption of mixed biodiesel by industry j

DIFTj, t

:

Aggregate intermediate consumption of freight transportation by industry j

DIGMj, t

:

Aggregate intermediate consumption of mixed gasohol by industry j

DIMTj, t

:

Aggregate intermediate consumption of mass transportation by industry j

DITi, t

:

Total intermediate demand for commodity i

DSj, i, t

:

Supply of commodity i by sector j to the domestic market

EXj, i, t

:

Quantity of product i exported by sector j

EXDi, t

:

World demand for exports of product i

EXDi

:

World demand for exports of product i (base year)

IMi, t

:

Quantity of product i imported

INDk, j, t

:

Volume of new type k capital investment to sector j

INVi, t

:

Final demand of commodity i for investment purposes

\( IN{V}_{i,t}^{PRI} \)

:

Final demand of commodity i for private investment purposes

\( IN{V}_{i,t}^{PUB} \)

:

Final demand of commodity i for public investment purposes

KDk, j, t

:

Demand for type k capital by industry j

KDCj, t

:

Industry j demand for composite capital

KSk, t

:

Supply of type k capital

LDl, j, t

:

Demand for type l labor by industry j

LDCj, t

:

Industry j demand for composite labor

LSl, t

:

Supply of type l labor

MRGNi, t

:

Demand for commodity i as a trade or transport margin

Qi, t

:

Quantity demanded of composite commodity i

VAj, t

:

Value-added of industry j

VSTKi, t

:

Inventory change of commodity i

XSj, i, t

:

Industry j production of commodity i

XSTj, t

:

Total aggregate output of industry j

Value

CABt

:

Current account balance

Gt

:

Current government expenditures on goods and services

\( {G}_t^{REAL} \)

:

Real government expenditures

\( GD{P}_t^{BP\_ REAL} \)

:

Real GDP at basic price

\( GD{P}_t^{MP\_ REAL} \)

:

Real GDP at market price

\( GFC{F}_t^{PRI\_ REAL} \)

:

Real private gross fixed capital formation

\( GFC{F}_t^{PUB\_ REAL} \)

:

Real public gross fixed capital formation

GFCFt

:

Gross fixed capital formation

GDPBP

:

GDP at basic prices

GDPFD

:

GDP at purchasers’ prices from the perspective of final demand

GDPIB

:

GDP at market prices (income-based)

GDPMP

:

GDP at market prices

ITt

:

Total investment expenditures

\( I{T}_t^{PRI} \)

:

Total private investment expenditures

\( I{T}_t^{PUB} \)

:

Total public investment expenditures

RINVk, j, t

:

Reallocation budget k for industry j

SFf, t

:

Savings of type f businesses

SGt

:

Government savings

SROWt

:

Rest-of-the-world savings

SHh, t

:

Savings of type h households

TRh, ag, t

:

Transfers from agent ag to type h households

TPRCTSt

:

Total government revenue from taxes on products and imports

TPRODNt

:

Total government revenue from other taxes on production

YDFf, t

:

Disposable income of type f businesses

YDHh, t

:

Disposable income of type h households

YFf, t

:

Total income of type f businesses

YFKf, t

:

Capital income of type f businesses

YFTRf, t

:

Transfer income of type f businesses

YGt

:

Total government income

YGKt

:

Government capital income

YGTRt

:

Government transfer income

YHh, t

:

Total income of type h households

YHKh, t

:

Capital income of type h households

YHLh, t

:

Labor income of type h households

YHTRh, t

:

Transfer income of type h households

YROWt

:

Rest-of-the-world income

Monetary

et

:

Exchange rate; price of foreign currency in terms of local currency

IRt

:

Interest rate

1.2.4 List of Equations

VAj, t = vjXSTj, t

(11.1)

CIj, t = iojXSTj, t

(11.2)

\( V{A}_{j,t}={B}_j^{VA}{\left[{\beta}_j^{VA} LD{C}_{j,t}^{-{\rho}_j^{VA}}+\left(1-{\beta}_j^{VA}\right) KD{C}_{j,t}^{-{\rho}_j^{VA}}\right]}^{-\frac{1}{\rho_j^{VA}}} \)

(11.3)

\( LD{C}_{j,t}={\left[\frac{\beta_j^{VA}}{1-{\beta}_j^{VA}}\frac{R{C}_{j,t}}{W{C}_{j,t}}\right]}^{\sigma_j^{VA}} KD{C}_{j,t} \)

(11.4)

\( LD{C}_{j,t}={B}_j^{LD}{\left[{\sum}_l{\beta}_{l.j}^{LD}L{D}_{l.j,t}^{-{\rho}_j^{LD}}\right]}^{-\frac{1}{\rho_j^{LD}}} \)

(11.5)

\( KD{C}_{j,t}={B}_j^{KD}{\left[{\sum}_k{\beta}_{k.j}^{KD}K{D}_{k.j,t}^{-{\rho}_j^{KD}}\right]}^{-\frac{1}{\rho_j^{KD}}} \)

(11.6)

\( L{D}_{l,j,t}={\left[\frac{\beta_{l.j}^{LD}W{C}_{j,t}}{WT{I}_{l,j,t}}\right]}^{\sigma_j^{LD}}{\left({B}_j^{LD}\right)}^{\sigma_j^{LD}-1} LD{C}_{j,t} \)

(11.7)

\( K{D}_{k,j,t}={\left[\frac{\beta_{k.j}^{KD}R{C}_{j,t}}{RT{I}_{k,j,t}}\right]}^{\sigma_j^{KD}}{\left({B}_j^{KD}\right)}^{\sigma_j^{KD}-1} KD{C}_{j,t} \)

(11.8)

DIi1, j, t = aiji1, jCIj, t

(11.9)

DIGMj, t = agmjCIj, t

(11.10)

DIDMj, t = admjCIj, t

(11.11)

DIMTj, t = amtjCIj, t

(11.12)

DIFTj, t = aftjCIj, t

(11.13)

\( DIG{M}_{j,t}={B}_j^{GM}{\left[{\sum}_{i2}{\beta}_{i2,j}^{GM}D{I}_{i2.j,t}^{-{\rho}_j^{GM}}\right]}^{-\frac{1}{\rho_j^{GM}}} \)

(11.14)

\( D{I}_{i2,j,t}={\left[\frac{\beta_{i2.j}^{GM} PG{M}_{j,t}}{P{C}_{i2,t}}\right]}^{\sigma_{j1}^{GM}}{\left({B}_j^{GM}\right)}^{\sigma_j^{GM}-1} DIG{M}_{j,t} \)

(11.15)

\( DID{M}_{j,t}={B}_j^{DM}{\left[{\sum}_{i3}{\beta}_{i3,j}^{DM}D{I}_{i3,j,t}^{-{\rho}_j^{DM}}\right]}^{-\frac{1}{\rho_j^{DM}}} \)

(11.16)

\( D{I}_{i3,j,t}={\left[\frac{\beta_{i3.j}^{DM} PD{M}_{j,t}}{P{C}_{i3,t}}\right]}^{\sigma_j^{GM}}{\left({B}_j^{DM}\right)}^{\sigma_j^{DM}-1} DID{M}_{j,t} \)

(11.17)

\( DIM{T}_{j,t}={B}_j^{MT}{\left[{\sum}_{i4}{\beta}_{i4,j}^{MT}D{I}_{i4,j,t}^{-{\rho}_j^{MT}}\right]}^{-\frac{1}{\rho_j^{MT}}} \)

(11.18)

\( D{I}_{i4,j,t}={\left[\frac{\beta_{i4.j}^{MT} PM{T}_{j,t}}{P{C}_{i4,t}}\right]}^{\sigma_j^{MT}}{\left({B}_j^{MT}\right)}^{\sigma_j^{MT}-1} DIM{T}_{j,t} \)

(11.19)

\( DIF{T}_{j,t}={B}_j^{FT}{\left[{\sum}_{i5}{\beta}_{i5,j}^{FT}D{I}_{i5,j,t}^{-{\rho}_j^{FT}}\right]}^{-\frac{1}{\rho_j^{FT}}} \)

(11.20)

\( D{I}_{i5,j,t}={\left[\frac{\beta_{i5.j}^{FT} PF{T}_{j,t}}{P{C}_{i5,t}}\right]}^{\sigma_j^{FT}}{\left({B}_j^{FT}\right)}^{\sigma_j^{FT}-1} DIF{T}_{j,t} \)

(11.21)

YHh, t = YHLh, t + YHKh, t + YHTRh, t

(11.22)

\( YH{L}_{h,t}={\sum}_l{\lambda}_{h,l}^{WL}\left({W}_{l,t}{\sum}_jL{D}_{l,j,t}\right) \)

(11.23)

\( YH{K}_{h,t}={\sum}_k{\lambda}_{h,k}^{RK}\left({\sum}_j{R}_{k,j,t}K{D}_{k,j,t}\right) \)

(11.24)

YHTRh, t = ∑agTRh, ag, t

(11.25)

YDHh, t = YHh, t − TDHh, t − TRgvt, h, t

(11.26)

CTHh, t = YDHh, t − SHh, t − ∑agngTRagng, h, t

(11.27)

SHh, t = PIXCONtηsh0h, t + sh1h, tYDHh, t

(11.28)

YFf, t = YFKf, t + YFTRf, t

(11.29)

\( YF{K}_{f,t}={\sum}_k{\lambda}_{f,k}^{RK}\left({\sum}_j{R}_{k,j,t}K{D}_{k,j,t}\right) \)

(11.30)

YFTRf, t = ∑agTRf, ag, t

(11.31)

SFf, t = YDFf, t − ∑agTRag, f, t

(11.32)

YDFf, t = YFf, t − TDFf, t

(11.33)

YGt = YGKt + TDHTt + TDFTt + TPRODNt + TPRCTSt + YGTRt

(11.34)

\( YG{K}_t={\sum}_k{\lambda}_{gvt,k}^{RK}\left({\sum}_j{R}_{k,j,t}K{D}_{k,j,t}\right) \)

(11.35)

TDHTt = ∑hTDHh, t

(11.36)

TDFTt = ∑fTDFf, t

(11.37)

TPRODNt = TIWTt + TIKTt + TIPTt

(11.38)

TIWTt = ∑l, jTIWl, j, t

(11.39)

TIKTt = ∑k, jTIKk, j, t

(11.40)

TIPTt = ∑jTIPj, t

(11.41)

TPRCTSt = TICTt + TIMTt + TIXTt

(11.42)

TICTt = ∑iTICi, t

(11.43)

TIMTt = ∑iTIMi, t

(11.44)

TIXTt = ∑iTIXi, t

(11.45)

YGTRt = ∑agngTRgvt, agng, t

(11.46)

TDHh, t = PIXCONtηttdh0h, t + ttdh1h, tYHh, t

(11.47)

TDFf, t = PIXCONtηttdf0f, t + ttdf1f, tYFKf, t

(11.48)

TIWl, j, t = ttiwl, j, tWl, tLDl, j, t

(11.49)

TIKk, j, t = ttikk, j, tRk, j, tKDk, j, t

(11.50)

TIPj, t = ttipj, tPPj, tXSTj, t

(11.51)

TICi, t = ttici, t[(PLi, t + ∑ijPCij, ttmrgij, i)DDi, t + ((1 + ttimi, t)PWMi, tet + ∑ijPCij, ttmrgij, j)IMi, t]

(11.52)

TIMi, t = ttimi, tPWMi, tetIMi, t

(11.53)

\( TI{X}_{i,t}= tti{x}_{i,t}\left(P{E}_{i,t}+{\sum}_{ij}P{C}_{ij,t} tmr{g}_{ij,i,t}^X\right) EX{D}_{i,t} \)

(11.54)

SGt = YGt − ∑agngTRagng, gvt, t − Gt

(11.55)

\( YRO{W}_t={e}_t{\sum}_i PW{M}_{i,t}I{M}_{i,t}+{\sum}_k{\lambda}_{row,k}^{RK}\left({\sum}_j{R}_{k,j,t}K{D}_{k,j,t}\right)+{\sum}_{agd}T{R}_{row, agd,t} \)

(11.56)

\( SRO{W}_t= YRO{W}_t-{\sum}_iP{E}_{i,t}^{FOB} EX{D}_{i,t}-{\sum}_{agd}T{R}_{agd, row,t} \)

(11.57)

SROWt =  − CABt

(11.58)

\( T{R}_{agng,h,t}={\lambda}_{agng,h}^{TR} YD{H}_{h,t} \)

(11.59)

\( T{R}_{ag,f,t}={\lambda}_{ag,f}^{TR} YD{F}_{f,t} \)

(11.60)

TRgvt, h, t = PIXCONtηtr0h, t + tr1h, tYHh, t

(11.61)

\( T{R}_{agng, gvt,t}= PIXCO{N_t}^{\eta }T{R}_{agng, gvt}^0 po{p}_t \)

(11.62)

\( T{R}_{agd, row,t}= PIXCO{N_t}^{\eta }T{R}_{agd, row}^0 po{p}_t \)

(11.63)

\( P{C}_{i,t}{C}_{i,h,t}=P{C}_{i,t}{C}_{i,h,t}^{MIN}+{\gamma}_{i,h}^{LES}\left( CT{H}_{h,t}-{\sum}_{ij}P{C}_{ij,t}{C}_{ij,h,t}^{MIN}\right) \)

(11.64)

`GFCFt = ITt − ∑iPCi, tVSTKi, t

(11.65)

\( P{C}_{i,t} IN{V}_{i,t}^{PRI}={\gamma}_i^{INVPRI}I{T}_t^{PRI} \)

(11.66)

\( P{C}_{i,t} IN{V}_{i,t}^{PUB}={\gamma}_i^{INVPUB}I{T}_t^{PUB} \)

(11.67)

\( IN{V}_{i,t}= IN{V}_{i,t}^{PRI}+ IN{V}_{i,t}^{PUB} \)

(11.68)

\( P{C}_{i,t}C{G}_{i,t}={\gamma}_i^{GVT}{G}_t \)

(11.69)

DITi, t = ∑jDIi, j, t

(11.70)

\( MRG{N}_{i,t}={\sum}_{ij} tmr{g}_{i, ij}D{D}_{ij,t}+{\sum}_{ij} tmr{g}_{i, ij}I{M}_{ij,t}+{\sum}_{ij} tmr{g}_{i, ij}^X EX{D}_{ij,t} \)

(11.71)

\( XS{T}_{j1,t}={B}_{j1}^{XT}{\left[{\sum}_i{\beta}_{j1,i}^{XT}X{S}_{j1,i,t}^{\rho_j^{XT}}\right]}^{\frac{1}{\rho_{j1}^{XT}}} \)

(11.72)

\( X{S}_{j1,i,t}=\frac{XS{T}_{j1,t}}{{\left({B}_{j1}^{XT}\right)}^{1+{\sigma}_{j1}^{XT}}}{\left[\frac{P_{j1,i,t}}{\beta_{j1,i}^{XT}P{T}_{j1,t}}\right]}^{\sigma_{j1}^{XT}} \)

(11.73)

XSj0, i, t = XSTj0, t

(11.74)

\( X{S}_{j,i,t}={B}_{j,i}^X{\left[{\beta}_{j,i}^XE{X}_{j,i,t}^{\rho_{j,i}^X}+\left(1-{\beta}_{j,i}^X\right)D{S}_{j,i,t}^{\rho_{j,i}^X}\right]}^{\frac{1}{\rho_{j,i}^X}} \)

(11.75)

\( E{X}_{j,i,t}={\left[\frac{1-{\beta}_{j,i}^XP{E}_{i,t}}{\beta_{j,i}^XP{L}_{i,t}}\right]}^{\sigma_{j,i}^X}D{S}_{j,i,t} \)

(11.76)

\( EX{D}_{i,t}=\mathit{\operatorname{ext}}{r}_{i,t} EX{D}_i^O po{p}_t{\left(\frac{e_t PW{X}_{i,t}}{P{E}_{i,t}^{FOB}}\right)}^{\sigma_i^{XD}} \)

(11.77)

\( {Q}_{i,t}={B}_i^M{\left[{\beta}_i^MI{M}_{i,t}^{-{\rho}_i^M}+\left(1-{\beta}_i^M\right)D{D}_{i,t}^{-{\rho}_i^M}\right]}^{\frac{-1}{\rho_i^M}} \)

(11.78)

\( I{M}_{i,t}={\left[\frac{\beta_i^MP{D}_{i,t}}{1-{\beta}_i^MP{M}_{i,t}}\right]}^{\sigma_i^M}D{D}_{i,t} \)

(11.79)

\( P{P}_{j,t}=\frac{PV{A}_{j,t}V{A}_{j,t}+ PC{I}_{j,t}C{I}_{j,t}}{XS{T}_{j,t}} \)

(11.80)

PTj, t = (1 + ttipj, t)PPj, t

(11.81)

\( PC{I}_{j,t}=\frac{\sum_iP{C}_{i,t}D{I}_{i,j,t}}{C{I}_{j,t}} \)

(11.82)

\( PV{A}_{j,t}=\frac{W{C}_{j,t} LD{C}_{j,t}+R{C}_{j,t} KD{C}_{j,t}}{V{A}_{j,t}} \)

(11.83)

WTIl, j, t = Wl, t(1 + ttiwl, j, t)

(11.84)

RTIk, j, t = Rk, j, t(1 + ttikk, j, t)

(11.85)

Pj0, i, t = PTj0, t

(11.86)

\( {P}_{j,i,t}=\frac{P{E}_{i,t}E{X}_{j,i,t}+P{L}_{i,t}D{S}_{j,i,t}}{X{S}_{j,i,t}} \)

(11.87)

\( P{E}_{i,t}^{FOB}=\left(P{E}_{i,t}+{\sum}_{ij}P{C}_{ij,t} tmr{g}_{ij,i}^X\right)\left(1+ tti{x}_{i,t}\right) \)

(11.88)

PDi, t = (1 + ttici, t)(PLi, t + ∑ijPCij, ttmrgij, it)

(11.89)

PMi, t = (1 + ttici, t)((1 + ttimi, t)etPWMi, t + ∑ijPCij, ttmrgij, i)

(11.90)

\( P{C}_{i,t}=\frac{P{M}_{i,t}I{M}_{i,t}+P{D}_{i,t}D{D}_{i,t}}{Q_{i,t}} \)

(11.91)

\( PIXGD{P}_t=\sqrt{\frac{\sum_j\left( PV{A}_{j,t}+\frac{TI{P}_{j,t}}{V{A}_{j,t}}\right)V{A}_j^O{\sum}_j\left( PV{A}_{j,t}V{A}_{j,t}+ TI{P}_{j,t}\right)}{\sum_j\left( PV{A}_j^OV{A}_j^O+ TI{P}_j^O\right){\sum}_j\left( PV{A}_j^O+\frac{TI{P}_j^O}{V{A}_j^O}\right)V{A}_{j,t}}} \)

(11.92)

\( PIXCO{N}_t=\frac{\sum_iP{C}_{i,t}{\sum}_h{C}_{i,h}^0}{\sum_{ij}P{C}_{ij}^0{\sum}_h{C}_{ij,h}^0} \)

(11.93)

\( PIXIN{V}_t^{PRI}={\prod}_i{\left(\frac{P{C}_{i,t}}{P{C}_i^0}\right)}^{\gamma_i^{INVPRI}} \)

(11.94)

\( PIXIN{V}_t^{PUB}={\prod}_i{\left(\frac{P{C}_{i,t}}{P{C}_i^0}\right)}^{\gamma_i^{INVPUB}} \)

(11.95)

\( PIXGV{T}_t={\prod}_i{\left(\frac{P{C}_{i,t}}{P{C}_i^0}\right)}^{\gamma_i^{GVT}} \)

(11.96)

Qi0, t = ∑hCi0, h, t + CGi0, t + INVi0, t + VSTKi0, t + DITi0, t + MRGNi0, t

(11.97)

jLDl, j, t = LSl, t

(11.98)

jKDk, j, t = KSk, t

(11.99)

ITt = ∑hSHh, t + ∑fSFf, t + SGt + SROWt

(11.100)

\( I{T}_t^{PRI}=I{T}_t-I{T}_t^{PUB}-{\sum}_iP{C}_{i,t} VST{K}_{i,t} \)

(11.101)

jDSj, i, t = DDi, t

(11.102)

jEXj, i, t = EXDi, t

(11.103)

\( GD{P}_t^{BP}={\sum}_j PV{A}_jV{A}_{j,t}+ TIP{T}_t \)

(11.104)

\( GD{P}_t^{MP}= GD{P}_t^{BP}+ TPRCT{S}_t \)

(11.105)

\( GD{P}_t^{IB}={\sum}_{l,j}{W}_{l,t}L{D}_{l,j,t}+{\sum}_{k,j}{R}_{k,j,t}K{D}_{k,j,t}+ TPROD{N}_t+ TPRCT{S}_t \)

(11.106)

\( GD{P}_t^{FD}={\sum}_iP{C}_{i,t}\left[{\sum}_h{C}_{i,h,t}+C{G}_{i,t}+ IN{V}_{i,t}+ VST{K}_{i,t}\right]+{\sum}_iP{E}_{i,t}^{FOB} EX{D}_{i,t}-{\sum}_i{e}_t PW{M}_{i,t}I{M}_{i,t} \)

(11.107)

\( CT{H}_{h,t}^{REAL}=\frac{CT{H}_{h,t}}{PIXCO{N}_t} \)

(11.108)

\( {G}_t^{REAL}=\frac{G_t}{PIXV{T}_t} \)

(11.109)

\( GD{P}_t^{BP\_ REAL}=\frac{GD{P}_t^{BP}}{PIXGD{P}_t} \)

(11.110)

\( GD{P}_t^{MP\_ REAL}=\frac{GD{P}_t^{MP}}{PIXCO{N}_t} \)

(11.111)

\( GFC{F}_t^{PRI\_ REAL}=\frac{I{T}_t^{PRI}}{PIXIN{V}_t^{PRI}} \)

(11.112)

\( GFC{F}_t^{PUB\_ REAL}=\frac{I{T}_t^{PUB}}{PIXIN{V}_t^{PUB}} \)

(11.113)

KDk, j, t + 1 = KDk, j, t(1 − δk, j) + INDk, j, t + RINVk, j, t

(11.114)

\( I{T}_t^{PUB}=P{K}_t^{PUB}{\sum}_{k, pub} IN{D}_{k, pub,t} \)

(11.115)

\( I{T}_t^{PRI}=P{K}_t^{PRI}{\sum}_{k, pri} IN{D}_{k, pri,t} \)

(11.116)

\( P{K}_t^{PRI}=\frac{1}{A^{K\_ PRI}}{\prod}_i{\left[\frac{P{C}_{i,t}}{\gamma_i^{INVPRI}}\right]}^{\gamma_i^{INVPRI}} \)

(11.117)

\( P{K}_t^{PUB}=\frac{1}{A^{K\_ PUB}}{\prod}_i{\left[\frac{P{C}_{i,t}}{\gamma_i^{INVPUB}}\right]}^{\gamma_i^{INVPUB}} \)

(11.118)

\( IN{D}_{k, pri,t}={\phi}_{k, pri}{\left[\frac{R_{k, pri,t}}{U_{k, pri,t}}\right]}^{\sigma_{k, pri}^{INV}}K{D}_{k, pri,t} \)

(11.119)

\( {U}_{k, pri,t}=P{K}_t^{PRI}\left({\delta}_{k, pri}+I{R}_t\right){U}_{k, pub,t}=P{K}_t^{PUB}\left({\delta}_{k, pub}+I{R}_t\right) \)

(11.120)

LEONt = Qi, t − ∑hCi, h, t − CGi, t − INVi, t − VSTKi, t − DITi, t − MRGNi, t

(11.121)

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Puttanapong, N., Sangsubhan, K. (2024). Impact Analysis of the Economic Eastern Corridor on the Thai Economy: An Application of Multi-Regional Input–Output Model and Dynamic Computable General Equilibrium Model. In: Resosudarmo, B.P., Mansury, Y. (eds) The Indonesian Economy and the Surrounding Regions in the 21st Century. New Frontiers in Regional Science: Asian Perspectives, vol 76. Springer, Singapore. https://doi.org/10.1007/978-981-97-0122-3_11

Download citation

Publish with us

Policies and ethics