Stock Market Development and Economic Growth: ARDL Causality in Thailand

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14.02 กรกฎาคม-ธันวาคม 2553

Stock Market Development and Economic Growth: ARDL Causality in Thailand R​ ossarin​​Osathanunkul1​ ​Nisa​​Fusrinual​​2​ ​Chaiwat​​Nimanussornkul​​3​

Abstract​

​ ​This​ ​paper​ ​endeavors​ ​to​ ​investigate​ ​the​ ​relationship​ ​between​ ​the​ ​stock​ ​market​​ development​​and​​economic​​growth​​in​​Thailand​.​​The​​61​​quarterly​​data​​during​​the​​time​​period​​ form​​March​,​​1995​​to​​June​,​​2010​​utilized​​in​​this​​study​​are​​the​​growth​​rate​​of​​Gross​​Domestic​​ Product​​(G​ DP​)​​of​​Thailand​,​​the​​growth​​rate​​of​​Market​​capitalization​​of​​Government​​Bonds​ ​(​BO​)​​and​​the​​growth​​rate​​of​​Market​​capitalization​​of​​the​​Stock​​exchange​​of​​Thailand​​(​MC​)​.​ Two​​stationarity​​tests​​namely​,​​DF​-G​ LS​​test​​and​​Ng​-​Perron​​test​​are​​employed​​to​​find​​the​​ integrating​​order​​of​​the​​variables​​which​​the​​results​​reveal​​that​​all​​variables​​are​​stationary​​at​​ their​​level​​form​​or​​they​​have​​the​​integrated​​of​​order​​zero​,​​I​(​0)​​.​​To​​test​​long​-​run​​robustness​,​ ​ARDL​​bounds​​testing​​technique​​is​​applied​.​​The​​finding​​reveals​​that​​there​​exist​​a​​positive​​ relationship​ ​stock​ ​market​ ​development​ ​and​ ​economic​ ​growth​ ​in​ ​Thailand​ ​implying​ ​that​​ stock​​market​​development​​is​​an​​important​​ingredient​​for​​economic​​growth​​in​​Thailand​.​​The​​ finding​​of​​the​​study​​suggests​​that​​there​​is​​a​​need​​of​​policies​​toward​​rapid​​development​​of​​ the​​stock​​market​​in​​Thailand​.​​​ ​ ​Keywords​:​​ARDL​,​​Stock​​Market​​Development​,​​Economic​​Growth​.​ ​

1 2 3

Professor of Faculty of Economics, Chiang Mai University. Research Assistant of Economic Research Park of Faculty of Economics, Chiang Mai University. Lecturer of Faculty of Economics, Chiang Mai University.

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CMU. Journal of Economics

​1​.​​Introduction​ ​ The​​stock​​market​​has​​been​​crucial​​and​​become​​an​​important​​wheel​​for​​economic​​growth​​ since​​it​​does​​not​​provide​​only​​sources​​of​​external​​financing​​for​​firms​​and​​allocate​​capital​​to​​ corporate​​sectors​​which​​improves​​resource​​allocation​​but​​also​​provide​​the​​change​​of​​stock​​ price​​as​​a​​consequence​​of​​changing​​in​​wealth​​which​​can​​affect​​the​​demand​​for​​consumption​​ and​​investment​​goods​,​​thereby​​stimulating​​real​​economic​​activity​​and​​boost​​up​​economic​​ growth​.​​It​​appears​​that​​stock​​markets​​can​​stimulate​​economic​​growth​​in​​several​​ways​.​​First​,​ stock​​markets​​play​​an​​important​​role​​in​​allocation​​of​​capital​​to​​corporate​​sector​​which​​result​​ in​​an​​increase​​in​​real​​economic​​activities​​(​Shahbaz​,​​et​.​al​,​​2008​)​.​​Second​,​​stock​​markets​​may​​ encourage​​economic​​growth​​through​​increasing​​the​​liquidity​​of​​financial​​assets​​which​​seems​​ to​​be​​crucial​​in​​developing​​countries​.​​Third​,​​stock​​markets​​provide​​investment​​opportunities​​ by​​mobilising​​domestic​​savings​​which​​in​​turn​​promote​​wiser​​investment​​decisions​​(​Caporale​​ et​.​al​,​​2004​).​​​This​​can​​be​​seen​​through​​financial​​liberalization​​in​​a​​number​​of​​developing​​ countries​​especially​​a​​country​​like​​Thailand​​during​​the​​past​​decade​​financial​​liberalization​​ has​​been​​recognized​​as​​a​​significant​​part​​of​​an​​economic​​policy​​in​​developing​​countries​.​ ​It​​is​​believed​​that​​the​​result​​of​​financial​​liberalization​​can​​attract​​both​​international​​and​​ domestic​​capital​​which​​is​​expected​​to​​increase​​resources​​available​​for​​domestic​​investment​.​​ ​There​ ​is​ ​plenty​ ​of​ ​research​ ​concerning​ ​the​ ​relationship​ ​between​ ​the​ ​stock​ ​market​​ development​ ​and​ ​economic​ ​growth​,​ ​including​ ​Bencivenga​ ​and​ ​Smith​ ​(​1992​)​,​ ​Atje​ ​and​​ Jovanic​​(​1993​)​,​​Greenwood​​and​​Smith​​(​1997​)​​and​​Bell​​and​​Rousseau​​(​2001​)​.​​Bencivenga​​ and​​Smith​​(1​ 992​)​​found​​that​​a​​new​​stock​​market​​can​​lead​​to​​economic​​growth​​by​​reducing​ ​holdings​​of​​liquid​​assets​​and​​increasing​​the​​growth​​rate​​of​​physical​​capital​.​​Similarly​,​​Atje​​ and​​Jovanic​​(​1993​)​​concluded​​that​​stock​​markets​​have​​been​​long​-r​un​​affected​​on​​economic​ ​growth​ ​and​ ​manipulate​ ​economic​ ​growth​ ​through​ ​a​ ​number​ ​of​ ​channels​ ​including​​ liquidity​,​​risk​​diversifications​,​​acquisition​​of​​information​​about​​firms​,​​corporate​​governance​​ and​ ​savings​ ​mobilization​.​ ​Greenwood​ ​and​ ​Smith​ ​(​1997​)​ ​also​ ​indicated​ ​that​ ​large​ ​stock​​ markets​​can​​decrease​​the​​cost​​of​​mobilizing​​savings​,​​thus​​facilitating​​investment​​in​​most​​ productive​​technologies​.​​Bell​​and​​Rousseau​​(​2001​)​​investigated​​the​​linkage​​among​​individual​​ macroeconomic​​indicators​​and​​measure​​of​​financial​​development​​in​​India​​which​​reveals​​that​​ the​​financial​​sector​​has​​been​​instrumental​​in​​promoting​​economic​​performance​.​ ​ Therefore​,​​the​​paper​​proceeds​​as​​follows​,​​section​​two​​briefly​​provides​​the​​data​​and​​ methodology​,​​which​​consist​​of​​the​​unit​​root​​test​​by​​using​​the​​Dickey​-F​uller​​Generalizes​​Least​​ Square​​(D​ F​-​GLS​)​​test​​and​​Ng​-​Perron​​(​NP​)​​test​.​​Autoregressive​​models​​with​​distributed​​lags​​

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(​ARDL​)​​then​​was​​used​​to​​estimate​​the​​relationship​​between​​the​​stock​​market​​development​ and​ ​economic​ ​growth​ ​in​ ​Thailand​.​ ​Section​ ​three​ ​discusses​ ​the​ ​principle​ ​results​ ​of​ ​the​ ​econometrical​​test​.​​The​​paper​​ends​​with​​conclusion​.​ ​ The​​main​​objective​​of​​the​​study​​is​​:​ ​ To​​investigate​​the​​relationship​​between​​the​​stock​​market​​development​​and​​economic​​ growth​​in​​Thailand​.​ ​ ​ 2​.​M ​ ethodological​​Framework​

2​ .1​​The​​Model​ ​ This​​study​​aims​​to​​investigate​​the​​relationship​​between​​stock​​market​​development​​and​​ economic​​growth​​in​​Thailand​​by​​using​​the​​following​​model​;​

GDPt = f (GDPt–i , MCt , MCt–j , BOt , BOt–k)



Gt = log(

​​ ​where​ GDPt–i =​ The​​growth​​rate​​of​​the​​previous​​i​​quarter​​of​​Gross​​Domestic​​Product​​of​​ Thailand​​(​i​=​1​,​…​p​)​.​ MCt = ​The​g​ rowth​r​ate​o​ f​M ​ arket​c​ apitalization​o​ f​t​he​S​ tock​e​ xchange of​T​ hailand​​ for​​current​​quarter​.​ MCt–j =​ ​The​​growth​​rate​​of​​previous​j​​​quarter​​of​​Market​​capitalization of​​the​​Stock​​ exchange​​of​​Thailand​(​ ​j​=​1​,​…​q​)​.​ BOt =​ ​The​​growth​​rate​​of​​Market​​capitalization​​of​​Thai​​Government​​Bonds​​for​​ current​​quarter​.​ BOt–k ​= ​The​​growth​​rate​​of​​previous​ ​k​​quarter​​of​​Market​​capitalization of​​Thai​​ Government​​Bonds​​(​k​=​1​,… ​ ​r​)​.​ ​ The​​growth​​rate​​of​​each​​variable​​at​​time​​t​​is​​calculated​​as​​follows​:​ )

​​ ​where​Gt is​​the​​growth​​rate​​of​​the​​variables​, Yt ​and​Yt–1 ​are​​variables​​using​​in​​this​​study​​ which​​are​G ​ DP​,​​MC​​and​​BO ​for​​t​​and​t​​-​1,​ ​respectively​.​​

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2.2​​Data​

​ ​Data​​was​​obtained​​from​​the​​bank​​of​​Thailand​​and​​Ecowin​​database​.​​GDP​​(​expressed​​as​​ million​​of​​Thai​​BHT​)​​was​​obtained​​from​​Ecowin​​and​​the​​data​​of​​stock​​development​​including​​ Market​​capitalization​​of​​the​​Stock​​exchange​​of​​Thailand​​and​​Market​​capitalization​​of​​Thai​​ Government​​Bonds​​were​​obtained​​form​​the​​bank​​of​​Thailand​.​ ​ ​2.3​​Analysis​

I​n​​this​​study​,​​the​​key​​steps​​of​​an​​analysis​​are​​defined​​as​​follows​​:​ • ​The​​unit​​root​​test​ ​Two​​type​​of​​unit​​root​​tests​​namely​​Dickey​-​Fuller​​Generalizes​​Least​​Square​​(​DF​-​GLS​)​ test​​and​​Ng​-​Perron​​(​NP​)​​test​​were​​used​​to​​check​​the​​stationarity​​of​​variables​.​ ​• ARDL​​bounds​​testing​​technique​​​ ​Autoregressive​​models​​with​​distributed​​lags​​(​ARDL​)​​is​​employed​​to​​estimate​​the​​causality​​ relationship​​between​​stock​​market​​development​​and​​economic​​growth​​of​​Thailand​.​ ​ ​2.3.1​​The​​Unit​​Root​​Test​ ​ A​​unit​​root​​test​​is​​required​​to​​test​​whether​​the​​variables​​in​​this​​study​​stationary​​or​ ​non​-​stationary​​and​​what​​are​​the​​order​​of​​integrated​​of​​these​​variables​.​​Thus​,​​we​​employ​​two​​ types​​of​​the​​stationarity​​tests​​namely​,​​the​​Dickey​-​Fuller​​Generalizes​​Least​​Square​​(​DF​-​GLS​)​ test​​and​​Ng​-​Perron​​(​NP​)​​test​.​ ​ ​2.3.1.1​​Dickey​-​Fuller​​Generalizes​​Least​​Square​​(​DF​-​GLS​)​​test​ ​ ​DF​-​GLS​​test​​was​​developed​​by​​Elliot​​et​​al​.​​(​1996​)​​which​​is​​called​​de​-​trending​​test​.​​It​​is​​ similar​​to​​Augmented​​Dickey​-​Fuller​​(​ADF​)​​test​.​​However​,​​it​​has​​an​​advantage​​over​​the​​ADF​​ test​​when​​there​​are​​a​​small​​number​​of​​observations​.​​This​​de​-​trending​​is​​done​​by​​taking​​the​​ explanatory​​variables​​out​​of​​the​​data​​(​see​,​​Elliott​,​​Rothenberg​​and​​Stock​,​​1996​)​.​​The​​following​​ equation​​is​​then​​estimated​​to​​test​​for​​a​​unit​​root​​in​​the​​variable​​:​ ​

Δydt = αydt–1 +

βp​Δydt–p + vt

(​2.3.1​)

​ where​Δ is​​the​​difference​​operator​,​ydt ​is​​the​​Generalised​​Least​​Squares​​de​-​trended​​value​​ of​​the​​variable​,​α and​βp are​​coefficients​​to​​be​​estimated​​and​vt ​is​​the​​independently​​and​​ identically​​distributed​​error​​term​.​​As​​in​​the​​case​​of​​the​​ADF​​test​,​​a​​test​​for​​a​​unit​​root​​of​​the​​ variable​ y​ ​​involves​​examination​​of​​whether​​the​​coefficient​​of​​the​​AR​(​1​)​​term​,​​in​​this​​case​​

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α​​,​​in​​equation​​(2​ .1​)​​is α =​​0​​or​​the​​series​​is​​non​-s​tationary​​against​​the​​alternative​​of​ α​ ≠​​0 or​​the​​series​​is​​stationary​.​​In​​making​​inferences​,​​the​​critical​​values​​tabulated​​in​​Elliott​,​

Rothenberg​​and​​Stock​​(​1996​)​​are​​used​.​ Following​​DF​-​GLS​​test​​established​​by​​Elliot​​et​​al​.​​(​1996​)​,​​then​​equation​​(​2.1​)​​can​​be​​ specified​​as​:​ ​

ΔGDPdt = αGDP GDPdt–1 +



ΔMCdt = αMC MCdt–1 +



ΔBOdt = αBO BOdt–1 +



k=



MZda = [T–1(Ddt)2 – f0] /(2k)



MZdt = MZa × MSB



MSBd = (k/f0)1/2



MPdt = {[

βGDP, p​ΔGDPdt–p + vGDPt βMC, p​ΔMCdt–p + vMCt

(​2.3.2​) (​2.3.3​)

βBO, p​ΔBOdt–p + vBOt

(​2.3.4​)

​ 2.3.1.2​​Ng​-​Perron​​(​NP​)​​test​ ​Ng​-​Perron​ ​(​2001​)​ ​developed​ ​four​ ​statistical​ ​tests​ ​by​ ​utilizing​ ​GLS​ ​de​-​trended​ ​data ​sets​ ​Ddt .​​The​​calculated​​values​​of​​these​​tests​​based​​on​​the​​forms​​of​​Philip​-P​ erron​​(​1988​)​ Zα ​and Zt statistics​,​​Bhargava​​(​1986​)​R1 statistics​,​​Elliot​,​​Rotherberg​​and​​Stock​​(​1996​) ​that​​ created​​best​​optimal​​statistics​.​​The​​terms​​are​​defined​​as​​follows​:​ (Ddt–1)2 / T2

​​ ​While​​de​-t​rended​​GLS​​tailored​​statistics​​are​​as​​given​​below​:​



(Ddt)2]/f0 , ​and​, (

+ (1–

)T–1(Ddt)2/f }0

​​ If​x​ t ​=​{​1​}​​in​​first​​case​,​​and xt ​=​{​1​,​t}​ ​​in​​second​.​ ​ NP​ ​test​ ​is​ ​a​ ​non​-​parametric​ ​approach​ ​to​ ​correct​ ​the​ ​residual​ ​autocorrelation​.​ ​The​​ regression​​of​​this​​test​​was​​estimated​.​

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Δydt = (δ–1) ydt–1 +

​Δydt–p + ut

(​2.3.5​)

p

​ The​​null​​hypothesis​​of​​equation​​(​2.3.5​)​​is H0 : δ =1 ​or​​the​​series​​is​​non​-​stationary​.​​ ​Following​​NP​​test​​(​2001​)​,​​then​​equation​​(​2.3.5​)​​can​​be​​specified​​as​:​ ​​ ​

ΔGDPdt = (δGDP –1) GDPdt–1 +



ΔMCdt = (δMC –1) MCdt–1 +



ΔBOdt = (δBO –1) BOdt–1 +

​GDPydt–p + uGDPt

GDP, p

​ΔMCdt–p + uMCt

MC, p

​ΔBOdt–p + uBOt

BO, p

(​2.3.6​)​ (​2.3.7​)​ (​2.3.8​)

2​ .3.2​​Autoregressive​​Models​​with​​Distributed​​Lags​​(​ARDL​)​ ​ ​The​r​elationship​b​ etween​t​he​s​tock​m​ arket​d​ evelopment​a​ nd​e​ conomic​g​ rowth​i​n​T​hailand​​ was​​conducted​​by​​Autoregressive​​models​​with​​distributed​​lags​​(​ARDL​)​.​​One​​of​​the​​reasons​​ for​​preferring​​the​​ARDL​​is​​that​​ARDL​​can​​also​​be​​used​​to​​examine​​the​​relationship​​the​​stock​​ market​​development​​and​​economic​​growth​​in​​Thailand​​in​​previously​.​​In​​addition​,​​ARDL​​is​​ more​​robust​​and​​perform​​better​​for​​small​​sample​​size​​than​​other​​cointegration​​technique​.​ ARDL​​can​​be​​written​​as​​follows​;​​ ​ ​

GDPt = ω0 +



αi GDPt–i + β0 MCt +

βj MCt–j + γ0BOt +

γkBOt–k + εt

(​2.3.9​)​

​ where​ GDP =​ ​The​​growth​​rate​​of​​Gross​​Domestic​​Product​​of​​Thailand​.​​ ​MC ​=​ The​​growth​​rate​​of​​Market​​capitalization​​of​​the​​Stock​​exchange​​of​​Thailand​.​ BO = The​​growth​​rate​​of​​Market​​capitalization​​of​​Government​​Bonds​.​ t = Time​​(​t​=​1​,​…​,​n​)​.​ εt =​ Independently​​distributed​​random​​error​​term​,​​with​​zero​​mean​​and constant​​ variance​​at​​time​t​​.​ ​ ω0 , αi , β0 , βj , γ0 , γk =​​The​​parameters​​to​​be​​estimated​.​

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3​.​E​ mpirical​​Results​

​In​​this​​section​,​​DF​-​GLS​​test​​and​​NP​​test​​were​​employed​​to​​test​​the​​stationarity​​of​​the​​ variables​​then​​ARDL​​was​​used​​to​​estimate​​the​​relationship​​of​​the​​stock​​market​​development and​ ​economic​ ​growth​ ​of​ ​Thailand​.​ ​The​ ​61​ ​quarterly​ ​data​ ​during​ ​the​ ​time​ ​period​ ​from​​ March​,​​1995​​to​​June​,​​2010​​was​​used​​to​​determine​​the​​relationship​​between​​stock​​market​​ development​​and​​economic​​growth​​in​​Thailand​.​​Table​​2.1​​shows​​the​​descriptive​​statistic​​test​​ of​​the​​variables​. Table​​2.1​​Descriptive​​Statistics​​of​t​he​​variables

Variables Mean

GDP MC BO

Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability

0.007 0.012 0.060

0.006 0.023 0.022

0.094 0.408 1.557

-0.082 -0.429 -0.272

0.044 0.164 0.270

0.366 -0.155 4.045

2.503 3.670 21.178

1.988 1.385 1006.232

0.370 0.500 0.000

3.1​​Unit​​root​​test​

​ ​For​​the​​stationarity​​testing​,​​we​​employed​​DF​-G​ LS​​test​​and​​Ng​-P​ erron​​test​​rather​​than​​ ADF​​test​.​​The​​reason​​for​​using​​these​​two​​techniques​​is​​that​​DF​-G​ LS​​and​​Ng​-​Perron​​are​​more​​ powerful​​and​​more​​suggestive​​tests​​than​​ADF​​test​​when​​there​​are​​small​​sample​​size​​since​​ADF​​ test​​is​​not​​reliable​​for​​small​​sample​​(​Dejong​​et​​al​,​​1992​​and​​Harris​,​​2003​)​.​​The​​stationarity​​ test​​results​​are​​shown​​in​​table​​3.1 Table​​3.1​​Result​o​ f​​The​A​ ugmented​​Dickey​F​ uller​​(​ADF​)​​test​,D​ ickey​-F​ uller Generalizes​​Least​​Square​​ (​DF​-​GLS​)​​test​​and​​Ng​-​Perron​​(​NP​)​​test

Variables

DF-GLS test

GDP MC BO

-3.378** [4] -6.250***[0] -3.812***[0]

MZa

-0.773 -28.626*** -18.983**

MZt

-0.421 -3.782*** -3.080**

Note: The number in bracket is the optimal lag length and bandwidth. Optimal lag length for ADF test is determined by AIC. Modified AIC is used determined the lag length in DF-GLS and NP tests. **,*** denotes the 5% and 1% level of significance, respectively.

NP test

MSB

0.545*** 0.132*** 0.162**

MPT

61.844 3.191*** 4.804**

Lag

[3] [0] [0]

Stock Market Development and Economic Growth: ARDL Causality in Thailand 95

CMU. Journal of Economics

The​​stationarity​​test​​results​​base​​on​​DF​-​GLS​​test​​and​​NP​​test​​in​​table​​3.1​​show​​that​​both​​ DF​-​GLS​​test​​and​​NP​​test​​display​​the​​null​​hypothesis​​can​​be​​rejected​​for​​the​​growth​​rate​​of​​ Market​​capitalization​​of​​the​​Stock​​exchange​​of​​Thailand​​(​MC​)​​and​​the​​growth​​rate​​of​​Market​​ capitalization​​of​​Government​​Bonds​​(​BO​)​​implying​​that​​MC​​and​​BO​​are​​stationary​​at​​their​​ level​​form​​at​​1​%​​and​​5​%​​significant​​level​.​ ​ Although​​only​​MSB​​statistical​​test​​of​​NP​​test​​reveals​​that​​the​​null​​hypothesis​​can​​be​​ rejected​​for​​GDP​,​​DF​-​GLS​​test​​reveals​​that​​the​​null​​hypothesis​​can​​be​​rejected​​at​​1​%​​and​​5​%​ level​​of​​significant​.​​Therefore​,​​we​​can​​conclude​​that​​GDP​​is​​stationary​​at​​its​​level​​form​.​ ​ Overall​​the​​stationarity​​evidences​​show​​that​​all​​variables​​are​​stationary​​at​​their​​level​​ form​​or​​they​​have​​the​​integrated​​of​​order​​zero​,​​I​(​0​)​.​​​ ​ ​3.2​ ​The​​autoregressive​​models​​with​​distributed​​lags​​(A​ RDL​)​​estimates​ ​ The​ ​relationship​ ​and​ ​direction​ ​of​ ​causal​ ​relationship​ ​between​ ​the​ ​stock​ ​market​ ​development​​and​​economic​​growth​​in​​Thailand​​is​​estimated​​by​​Autoregressive​​models​​with​​ distributed​​lags​​(​ARDL​)​,​​shown​​in​​table​​3.2​ Table​​3.2​​The​​autoregressive​m ​ odels​w ​ ith​d​ istributed​​lags​​(​ARDL​)​​estimates​.

Variable C GDPt–1 GDPt–2 GDPt–3 GDPt–4 MC MCt–1 MCt–2 MCt–3 MCt–4 BO BOt–1 BOt–2

Coefficient

0.011 -0.168 -0.529*** -0.194 0.432*** 0.026** 0.081*** 0.022 0.057*** -0.005 -0.065*** 0.043*** 0.000

t-Statistic

2.614 -1.210 -4.633 -1.457 3.650 1.693 5.485 1.266 3.505 -0.281 -5.604 2.777 0.031

Note: **,*** Significant at critical value at 5% and 1% significance level, respectively.

Standard error

0.004 0.139 0.114 0.133 0.118 0.015 0.015 0.018 0.016 0.018 0.012 0.015 0.012

96 วารสารเศรษฐศาสตร์ มหาวิทยาลัยเชียงใหม่

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The​​results​​of​​the​​relationship​​between​​stock​​market​​development​​and​​economic​​growth​​ can​​be​​written​​as​;​ GDPt = –0.529*** GDPt–2 + 0.432*** GDPt–4 + 0.026* MCt + 0.081*** MCt–1 + 0.057*** MCt–3 –0.07*** BOt + 0.04*** BOt–1​ (​3.1​)​

​​​​​​ ​​​​​ ​Equation​ ​(​3.1​)​ ​presents​ ​the​ ​relationship​ ​between​ ​stock​ ​market​ ​development​ ​and​​ economic​​growth​,​​according​​to​​the​​results​​that​GDPt–4 ​,​MCt ​,​MCt–1 ​, MCt–3 ​and BOt–1​ have​​significant​​positive​​impact​​on​ GDPt ​,​​whereas​ GDPt–2 and​ BOt have​​significant​​ negative​​impact​​on​ GDPt ​.​The​​analysis​​of​​the​​results​​show​​that​​in​​long​-​run​​economic​​ growth​​in​​Thailand​​is​​strongly​​influence​​from​​previous​​GDP​​and​​financial​​liberalization​​on​​ stock​​market​​development​​in​​Thailand​. ​4​.​C​ onclusion​

This​ ​paper​ ​attempts​ ​to​ ​explore​ ​the​ ​causal​ ​relationship​ ​between​ ​the​ ​stock​ ​market​​ development​ ​and​ ​economic​ ​growth​ ​by​ ​utilizing​ ​ARDL​.​ ​The​ ​data​ ​set​ ​depended​ ​on​ ​the​​ availability​​of​​the​​data​​series​​which​​is​​taken​​from​​Ecowin​​database​,​​during​​March​​1995​​to​​ June​​2010​​period​.​ ​For​​the​​stationarity​​test​,​​we​​have​​DF​-G​ LS​​test​​and​​Ng​-​Perron​​test​​to​​find​​the​​integrating​​ order​​of​​the​​variables​​utilized​​in​​the​​study​.​​The​​stationarity​​evidences​​reveal​​that​​all​​variables​​ are​​stationary​​at​​their​​level​​form​​or​​they​​have​​the​​order​​of​​integration​​zero​,​​I​(​0​)​.​​​ ​The​ ​causality​ ​and​ ​relationship​ ​between​ ​stock​ ​market​ ​development​ ​and​ ​economic​​ growth​​is​​estimated​​by​​ARDL​.​​The​​findings​​reveal​​that​​the​​market​​capitalization​​has​​the​​ positive​​impact​​on​​economic​​growth​​implying​​that​​greater​​stock​​market​​liquidity​​or​​the​​ability​​ to​​trade​​the​​equity​​easily​​reduce​​the​​downside​​risk​​and​​cost​​of​​investing​​in​​projects​.​​Thus​,​ more​​liquidity​​in​​stock​​market​​may​​accelerate​​the​​growth​​of​​market​​capitalization​,​​thereby​​ stimulating​​the​​economic​​activities​​and​​improving​​resource​​allocation​.​​Consequently​,​​this​​ can​​boost​​economic​​growth​​in​​Thailand​.​​ ​ The​​finding​​confirms​​the​​causality​​between​​stock​​market​​development​​and​​economic​​ growth​​in​​case​​of​​Thailand​​and​​indicates​​that​​stock​​market​​development​​leads​​to​​economic​​ growth​​at​​least​​for​​the​​period​​under​​study​​of​​the​​consideration​,​​which​​suggests​​that​​the​​stock​​

Stock Market Development and Economic Growth: ARDL Causality in Thailand 97

CMU. Journal of Economics

market​​development​​through​​financial​​liberalization​​policy​​has​​become​​an​​important​​wheel​​ for​​economic​​growth​​of​​Thailand​.​​Therefore​,​​it​​is​​suggested​​that​​Thailand​​needs​​to​​continue​​ the​​development​​of​​its​​stock​​market​​through​​government​​policy​.​​The​​policy​​should​​facilitate​​ investment​​as​​well​​as​​increase​​stock​​market​​liquidity​​which​​in​​turn​​increases​​incentive​​of​​ investors​.​

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