interaction of financial development and economic οι...

ΕΠΙθΕΩΡΗΣΗ ΟΙΚΟΝΟΜΙΚΩΝ ΕΠΙΣΤΗΜΩΝ - Τεύχος 12 (2007), 7-20

ΤΗΕ INTERACTION OF FINANCIAL DEVELOPMENT AND ECONOMIC GROWTH. ΤΗΕ CASE OF TURKEY

Abstract

From the economic policy point of view, it is important to know the caυsal relationship between financial development and economic growth. Using the Johansen test approach, ουr stυdy finds that stock market development is cointegrated with economic growth in the case of Tυrkey. Granger-caυsality test based οη vector aυtoregression

(VAR) model reveals that economic growth Granger-caυses stock market development. Hence, this stυdy provides ηο empirical evidence in favor offinance-led growth hypothesis, bυt rather growth-led finance hypothesis for the case of Tυrkey. The resυlts of short-rυn caυsality based οη vector error correction model (VECM) however are qυite the opposite. These findings have important implications οη the side of policy makers.

JEL Classification: C, Ο. Key words: Tυrkish Economy, Financial Development, Economic Growth, Cointegration, Caυsality, Stock Market.

Murat Karagoz

Department οι Econometrics, lnonu University

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1. Introduction

The relationship between economic growth and financial development is a matter of concern for policy makers. The crucial point is that whether there is a dynamic relationship and the further aspect of the discussion is to know the direction of causality both in the short -and long- run. Ιη recent years there is a surge of research regarding these topics. As yet, there is ηο result that can be generalized, that is, that policy-makers could rely upon. The related researches mostly focused οη the role of financial development in spurring economic growth, but recent studies take into account of the stock market development. Levine and Zervos (1998) points out that in the emerging economies, the evolution of stock market has great impact οη the economy through the operation of banking institutions. Ιη fact, this proposition is the starting point of the present study. Accordingly, we aim to investigate whether the developments ίη the Istanbul stock market have any significant impact οη the economic growth of Turkey.

Following Choong et al (2002), the related hypotheses can be categorized as follows. The "finance-led growth" (FLG) hypothesis is an expression of "supplyleading" relationship between financial and economic developments. The existence of financial sector, as a well-functioning intermediation in channeling the limited resources from surplus to deficit units, will provide efficient allocation of resources thereby contribute to the growth process of the economy as a whole. Ιη last decade, a number of studies have argued that the development of financial sector has significantly promoted economic growth (Levine, 1997). The "growth-led finance" (GLF) hypothesis, οη the other side, states that economic growth may create a demand for financial instruments and financial markets will response to these demands. As such, this hypothesis suggests a "demand following" relationship between financial and economic developments (Romer, 1990).

The "feedback" hypothesis, as a reconciliation represents an interactive causal relationship between financial development and economic growth. Αη economy with a well-developed financial system could promote its performance through the innovations. Ιη this way, as reported by Levin (1997), a high demand οη the financial arrangements and services will be created. If the financial markets effectively response to these demands, then these changes will lead a higher economic performance. Hence, both financial development and economic growth are positively interdependent and there is a two-way causality in between.

The principle objective of this study is to re-examine the financial development-economic growth relationship from the perspective of stock market development for the case of Turkey. More specifically, using Grangercausality test based οη vector autoregressive and vector error correction model, we investigate the cointegration and causality relationships both in the short -and long- run between stock market development and economic growth in the context of Turkey.

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The paper is organized as follows. The present section gives the aim of study and a short account of hypotheses οη the financial and economic developments. Ιη the next section we present a brief discussion of recent studies. Studies related to Turkey are reported ίη third section. Ιη the fourth section we describe the methodology employed ίη the study. Empirical results and interpretations are presented ίη the fifth section. Finally in the sixth section we conclude this paper.

2. Α brief review of literature

The empirical works are mostly focused οη the role of financial development ίη stimulating economic growth, without taking into account of the stock market development. Arestis and Demetriades (1997) presented empirical evidence οη the relationship between financial development and economic growth with a view to identifying outstanding issues and offering some suggestions about how these may be addressed ίη the future. Evolution of stock market has impact οη the operation of banking institutions and hence, οη economic promotion. This means that stock market is becoming more crucial, especially in a number of emerging markets.

Using pooled data from fifteen industrial and developing countries, Garcia and Liu (1999) examined the macroeconomic determinants of stock market development, particularly market capitalization. The paper finds that: (1) real income, saving rate, financial intermediary development, and stock market liquidity are important determinants of stock market capitalization; (2) macroeconomic volatility does not prove significant; and (3) stock market development and financial intermediary development are complements instead of substitutes.

Darrat (1999) empirically investigates the role of financial deepening in economic growth ίη three middle-eastern countries (Saudi Arabia, Turkey, and the United Arab Emirates). Using multivariate Granger-causality tests within an error-correction framework, he focuses οη the causal link between the degree of financial deepening and economic growth in order to discriminate between several alternative theoretical hypotheses. The results generally support the view that financial deepening is a necessary causal factor of economic growth, although the strength of the evidence varies across countries and across the proxies used to measure financial deepening. The causal relationships are also predominately long-term ίη nature.

Ιη a series of papers, an analysis of real economic growth prospects ίη emerging markets after financial liberalizations provided by Bekaert and Harvey (2001) and Bekaert et al (2001, 2002, 2003). They identified the financial liberalization dates and examine the influence of liberalizations while controlling for a number of other macroeconomic and financial variables. Their work also introduces an econometric methodology that allows using extensive time-series as well as cross-sectional information for tests. They found across a

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number of different specifications that financial liberalizations are associated with significant increases ίη real economic growth. The effect is found to be larger for countries with high education levels.

Το examine the direction of causality between financial development and economic growth, Calderon and Liu (2002) employs the Geweke decomposition test οη pooled data of 109 developing and industrial countries from 1960 to 1994. The paper finds that (1) financial development generally leads to economic growth; (2) the Granger causality from financial development to economic growth and the Granger causality from economic growth to financial development coexist; (3) financial deepening contributes more to the causal relationships ίη the developing countries than in the industrial countries; ( 4) the longer the sampling interval, the larger the effect of financial development οη economic growth; (5) financial deepening propels economic growth through both a more rapid capital accumulation and productivity growth, with the latter channel being the strongest.

The empirical evidences οη the finance-growth nexus do not yield any clearcut picture. Andersen and Tarp (2003) has shown that the alleged first-order effect whereby financial development causes growth is not adequately supported by econometric work. By way of conclusion, they question whether financial development, ίη the sense of increased formal financial sector intermediation ίη . a deregulated environment can be expected to act as 'engine of growth' ίη the deνelopment process. They argue ίη favor of a more cautious approach to financial sector reform.

Fisman and Love (2004) analyze the relationship between financial development and inter-industry resource allocation ίη the short- and long-run. They suggest that ίη the long-run, economies with high rates of financial development will devote relatively more resources to industries with a 'natural' reliance οη outside finance due to a comparative advantage in these industries. By contrast, in the short-run they argue that financial development facilitates the reallocation of resources to industries with good growth opportunities, regardless of their reliance οη outside finance. They find differential effects of these measures οη industry growth and composition in countries with different levels of financial development. They obtain results that are consistent with financially developed economies specializing in "financially dependent" industries ίη the long-run, and allocating resources to industries with high growth opportunities ίη the short-run.

Claessens et al (2004) studied how local stock market development and listing, trading, and capital raising ίη international exchanges are affected by economic fundamentals. Using panel data, they confirmed that higher income economies with sounder macro policies, more efficient legal systems, better shareholder protection, and greater openness have more developed local markets. They suggest that, with liquidity agglomeration, better fundamentals might further accelerate internationalization, possibly negatively impacting domestic stock markets, with important policy implications.

Loayza and Ranciere (2004) studied the apparent contradiction between


two strands of the literature οη the effects of financial intermediation οη economic activity. The paper accounts for these contrasting effects based οη the distinction between the short -and long- run impacts of financial intermediation. Working with a panel of cross-country and time-series observations, the paper estimates an encompassing model of short - and long- run effects. They conclude that a positive long-run relationship between financial intermediation and output growth co-exists with a mostly negative short-run relationship. The paper further develops an explanation for these contrasting effects by relating them to recent theoretical models, by linking the estimated short-run effects to measures of financial fragility (namely, banking crises and financial volatility), and by jointly analyzing the effects of financial depth and fragility ίη classic panel growth regressions.

Dritsakis and Adamoρoulos (2004) empirically examine the causal relationship between financial development and economic growth by using a multivariate autoregressive V AR model in Greece for the period 1960-2000. Granger causality tests based οη error correction models show that there is a causal relationship between financial development and economic growth.

Caporale et al (2005) re-examines the relationship between stock market development and econoniic growth. lt provides a theoretical basis for establishing the channel through which stock markets affect economic growth ίη the long run. The paper examines the hypothesis of endogenous growth meidels that financial development causes higher growth through its influence οη the level of investment and its productivity. The empirical part of the study exploits techniques recently developed to test for causality in V ARs. The evidence obtained from a sample of four countries suggests that investment productivity is the channel through which stock market development enhances the growth rate in the long run.

3. Finance-growth studies ίη Turkey

The process of liberalization ίη Turkey began around two decades ago simultaneously with a stabilization program that had been designed according to neoclassical model. The effects of liberalization policies οη financial markets in Turkey were analyzed first by Denizer (1997).

Later οη Esen (2000) analyzed the effects of financial liberalization οη the financial and real sectors of the Turkish economy. The implementation addressed first foreign trade, then the domestic financial market and finally foreign capital movements. Contrary to theoretical expectations, the opening of the capital account induced adverse effects οη financial intermediation, savings, investment, growth and foreign debt.

Kar and Pentecost (2000), examined the causal relationship between financial development and economic growth ίη Turkey. Five alternative proxies for financial development were developed and Granger causality tests applied usίng the cointegration and vector error correction methodology (VECM). They showed that the direction of causality between financial development and

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economic growth in Turkey is sensitive to the choice of proxy used for financial development. The proxies they have chosen are different from the present study. The financial development was measured by the ratio of money to income. Alternatively, the bank deposits, private credit and domestic credit ratios were also used as a proxy for financial development. They found that growth leads financial sector development.

Boratav and Yeldan (2001 ), aimed at in their paper to identify and study the main stylized facts and processes characterizing the dynamic macroeconomic adjustments of Turkey since inception of its reforms towards global integration -viz. post- 1980's. They comment that Turkish adjustment experience throughout the post-1980 period reveals a process in which a developing market economy trapped within the needs of integration with the world markets and the distributional requiremeήts warranted by such reorientation, the state apparatus became the bastion of privilege, regulating the mode of income redistribution within the society. They further argued that the elements of this re-distribution involved both direct mechanisms toward attaining favorable production and export subsidies, currency depreciation, wage suppression; as well as indirect mechanisms such as tax evasion οη capital incomes, and conduct of a financial market development strategy which enabled massive income transfers to the rentier class.

4. The employed methodology

As a first step of the time series analysis, a unit root tests for the variables involved should be applied. The original Dickey-Fuller tests considers a first order AR process:

(1)

where α 1 is a parameter and ε1 is assumed to be a white noise sequence. Υ1 is a stationary series if 1 α 1 1< 1. If α 1 = 1, Υ1 is a unit root process. Using simulation studies, Dickey and Fuller (1979) showed that the distribution under the null hypothesis is nonstandard. The variance of Υ1 is not constant over time. If 1 α 1 1> 1, the series is explosive. Το make this test more operational in the common sense of significance tests Υι. 1 is subtracted from both sides of the above equation:

(2)

where ΔΥ1 = Υ1 - Υ1_ 1 , γ = α 1 = - 1 and the null and alternative hypotheses become Η0 : γ = Ο and Η1 : γ = < Ο respectively.

The t-statistic for the estimates of g under the null hypothesis of a unit root does not have the conventional t-distribution. MacΚinnon (1991) has implemented larger sets of simulations and reached more realistic theoretical values. If the series are auto-correlated the assumption of white noise

MURAT KARAGOZ - REVIEW OF ECONOMIC SCIENCES - Νο 12 (2007), 7-20

disturbances will be violated. The ADF approach controls for higher-order correlation by adding lagged values of the dependent variable to the right-hand side:

(3)

This augmented specification is then used to test the same hypothesis as above. Το answer the question of whether to include a constant, a constant and a linear trend, or neither in the test regression, run the test with both a constant and a linear trend since the other two cases are just special cases of this more general specification:

lncluding irrelevant regressors in the regression may reduce the power of the test, in that, one may conclude that there is a unit root when, in fact, there is none. If the series seems to contain a deterministic or stochastic trend, both a constant and trend should be included in the test regression. If the series does not exhibit any trend and has a nonzero mean, only a constant should be included in the regression, while if the series seems to be fluctuating around a zero mean, neither a constant nor a trend should be included in the test regression. If a series Yt gets the stationarity (no unit roots) after d-times of

. differences, it is said that Yt is integrated of order d, and shown as Yt - 1( d) in short. For the existence of a long-run relationship between k-series Υ; = [ Υ1 ι, .. .Yk 1 ], they must be co-integrated.

Johansen's (1991) method of cointegration test starts with a Vector Autoregressive model (VAR) of order p:

(5)

where Π - 1( d) is a k-dimensional vector of non-stationary variables, Χι is a vector of deterministic variables, and Ει is a vector of innovations. Subtracting the lagged vector of Yt-l from both sides, we can rewrite the V AR as:

p-1

ΔΥι = ΠΥι- l + Σ Γ; ΔJΊ_ 1 + ΒΧι +Ει ί-1

Ρ Ρ

where Π = Σ Α; - 1, and Γ; = - Σ Α; . ί -1 j=i+1

(6)

If the coefficient matrix Π has reduced rank r<k, then there exist r · k dimensional matrices of α and β each with rank r such that Π = αβ' and β' Υι is r stationary. r is the number of cointegrating relations and each column of β is the cointegrating vector. The elements of α are known as the adjustment parameters in the vector error correction model (ECM). Johansen's method for cointegration is to estimate the Π matrix in an unrestricted form, and then test the restrictions implied by the reduced rank of Π.

The series at hand may have nonzero means and deterministic trends as well as stochastic trends. Similarly, the cointegrating equations may have intercepts

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and deterministic trends. The asymptotic distribution of the LR test statistic for the reduced rank test does not have the usual χz distribution and depends οη the assumptions made with respect to deterministic trends. If there exists a long run relationship between these variables, a causality relationship must exist by definition in at least one direction (Engle and Granger, 1987).

Granger (1969) approach to causality test for a pair of (Χε , Υι) series depends οη bivariate regressions of the form

Υι = ασ+α1Υε-1 + αzΥι-z + ··· + αιΥι-ι + βιΧε-1 + ··· + βιΧε-t +uε (7)

Χε = Υο+Υ1Χι-1 + YzXε_z + ··· + ΥιΧι-ι + δl Υε-1 + ·· · + δι Υι-t +νι (8)

Α restricted F-statistics (Wald test) is performed for the joint hypotheses Η0 : β 1 = .. . = β1 = Ο and Η0 : δ 1 = ... = δ1 = Ο for equations (7) and (8) respectively. The null hypotheses literally mean that, Χ does not Granger-cause Υ in the first regression and that Υ does not Granger-cause Χ in the second regression.

The short-run dynamics of causality can be explained by Vector Error Correction (VEC) model. Α VEC model is a restricted V AR that involves the cointegration equations as variables. The errors or deviations from long-run equilibrium are corrected gradually through a series of partial short-run adjustments. For a two variable system with a cointegrating regression of

. Υι =α + βΧι +ει and ηο lagged difference terms, the VEC model is

ΔΥι =γ ( Υε-1 - α - β Χ ι-Ι) + Uε ΔΧι =δ ( Υι_ 1 -α -βΧι-Ι) + νι

(9)

(10)

Ιη this model, the right-hand side variable is the error correction term. Ιη long run equilibrium, this term is zero. The coefficients γ and δ are the measures of the speed of adjustment. Here, the two endogenous variables Υι and Χι have ηο trend and the cointegrating equations have an intercept. Ιη general, a VEC specification may assume linear trends in the series and/or a constant ίη the cointegrating equations. Moreover, lagged differences may be required οη the right-hand side to avoid autocorrelations in the error terms. For more information οη VEC models, see Enders (2004, pp. 328-335).

5. Data and emprical results

We have selected two proxies as follows. Economic Growth (EG) represented by quarterly growth rate of GDP series at current New Turkish Lira (YTL) prices. Financial Development (FD) represented by the growth rate of Istanbul Stock Exchange (ISE) daily trading volume series (in YTL Thousand). That is, for an original Υι series, we have used the following transformation to obtain the growth rates proxies: [( Υε - Yt-1) / Υε-Ι] 100. The original data were obtained from the Central Bank of Turkey database.

As a first step of the analysis we perform the unit root tests for the variables involved. Unit root test are carried out for levels and first differences of the


series. The results are presented ίη Table 1 below. According to the results of unit root tests, both of the variables involved in the theory of finance-growth relationship are non-stationary, however their first order differences are stationary. Ιη other words, all the variables are integrated of first order. Hence we can move οη the cointegration tests. Cointegration test results are presented ίη Table 2 below.

LR test reported in Table 3 indicates one cointegrating equation at 5 % significance level. According to the normalized cointegrating coefficients, EG and FD are positively related. Accordingly, The causality relationships between financial and economic development are summarized in Table 3. From this table we see that, there is ηο significant Granger causality from FD towards EG. Nevertheless, there is a Granger-causality running from EG to FD. The Granger causality results abcive are obviously not encouraging for the financialled growth hypothesis. However, it is important to note that the statement "Χ Granger causes Υ" does not imply that Υ is the effect or the result of Χ. Granger causality measures precedence and information content but does not by itself indicate causality in the more common use of the term. Therefore we do not see these results as a hindrance for further analysis.

The results of VEC model are reported in Table 4 below. The cointegration equation is included in the model as a variable. The VEC specification for EG is found to be meaningful according to the t-values of individual parameters and F-test of overall significance. That means that, in the short-run behavior of the EG is dependent οη the FD. As such, this VEC model explains short-run dynamics of EG variable. The estimated speed of adjustment parameter for this model is -2.385804 and significantly different from zero. Here, the two endogenous variables EG and FD have ηο trend and the cointegrating equations have an intercept. For both of the variables however, the intercept term is not significant.

6. Conclusion

The study provides ηο evidence οη the finance-led growth hypothesis in the case of Turkey. Using the Granger vector autoregressive approach; this study finds that stock market development is cointegrated with economic growth. Moreover, this test also suggests that economic growth has a significant positive long-run impact οη stock market development. Granger causality test within VECM framework in testing the short-run relationship reveals the dynamic short run causality between the variables whereby the stock market is viewed as a leading sector in stimulating domestic growth.

Our findings supports the results of studies made for other emerging economies (see Choong et al 2002). These results suggest that the development of financial sector represented by the evolution of stock market cannot stimulate and promote economic growth unless fiscal and monetary authorities adopt liberalized investment and openness policies, improve the size and the regulations of the stock market and macroeconomic stability. Therefore,

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government policies aimed at promoting financial deepening in these countries must be persistent and sustainable ίη order to foster economic development.

References

Andersen, Τ. Β., Tarp, F. 2003. Financial Liberalization, Financial Development and Economic Growth ίη LDCs. Journal of International Development 15, 189-209.

Arestis, Ρ., Demetriades, Ρ. 1997. Financial Development and Economic Growth: Assessing the Evidence. The Economic Journal, 107 May, 783-799.

Bekaert, G.,Harvey, C.R. 2001. Economic Growth and Financial Liberalization. Draft March 8, National Bureau of Economic Research, Cambridge, ΜΑ 02138 USA.

Bekaert, G., C. R. Harvey, C. Lundblad, 2001. Emerging Equity Markets And Economic Development. Journal of Development Economics, Vol. 66, 465-504.

Bekaert, G., C. R. Harvey, C. Lundblad. 2002. Growth Volatility and Equity Market Liberalization. National Bureau of Economic Research, Cambridge, ΜΑ 02138 USA.

Bekaert, G., C. R. Harvey, C. Lundblad. 2003. Does Financial Liberalization Spur Growth?" National Bureau ofEconomic Research, Cambridge, ΜΑ 02138 USA.

Boratav, Κ. , Ε. Ye\dan. 2001. Turkey, 1980-2000: Financial Liberalization, · Macroeconomic (In)-Stability, and Patterns of Distribution. Faculty of Political Science Department of Economics Ankara University Ankara, Cebeci Turkey.

Calderόn, C. , L. Liu. 2002. The Direction Of Causality Between Financial Development And Economic Growth. Central Bank of Chile Working Papers Ν ' 184.

Caporale, G. Μ., Ρ. Howel\s, Α. Μ. Soliman. 2005. Endogenous Growth Models and Stock Market Development: Evidence from Four Countries. Review of Development Economίcs, 9(2), 166-176, 2005.

CBRT (Central Bank of The Republic of Turkey). 2005. EDDS (Electr9nic Data Dissemination System), http ://tcmbf40.tcmb.goν.tr/fame/webfactory/evdpw/

Choong, C.Κ. , Ζ. Yusop, Α.Η. Law, V.L.Κ. Sen. 2002. Financial Development and Economic Growth in Malaysia: The Stock Market Perspective. Economics Working Paper Archive at WUSTL, Macroeconomics series number: 0307010.

Claessens, S., D. Κlingebie\, and S.L. Schmukler. 2004. Stock Market Development and lnternationalization: Do Economic Fundamentals Spur Both Similarly? University of Amsterdam and CEPR, World Bank.

Darrat, Α. F. 1999. Are Financial Deepening And Economic Growth Causally Related? Another Look At The Evidence. Internatίonal Economic Journal, Volume 13, Number 3, Autumn.

Denizer, C. 1997. The Effects of Financial Libera\ization and New Bank Entry οη Market Structure and Competition in Turkey. Macroeconomics and Growth


Development Research Group, World Bank, Washington DC.

Dickey, D.A., W.A. Fuller. 1979. Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the Amerίcan Statίstίcal Assocίatίon, 74, 427-431.

Dritsakis, Ν., Α. Adamopoulos. 2004. Financial Development and Economic Growth in Greece: Αη Empirical Investigation with Granger Causality Analysis. Internatίonal Economίc Joumal, Vol. 18, Νο. 4, 547-55.

Enders, W. 2004. Applied Econometric Time Series. John Wiley Series in Probability and Statistics, New York.

Engle, R.F., Granger, C.W.J. 1987. Cointegration and Error Correction: Representation, Estimation and Testing. Econometrίca, 55, 251-276.

Esen, Ο. 2000. Financial Openness in Turkey. Intematίonal Revίew of Applίed Economίcs, Vol. 14, Νο. 1.

Fisman, R., 1. Love. 2004. Financial Development and Growth in the Short-and Long-run. World Bank Polίcy Research Workίng Paper 3319, May.

Garcia, V. F., L. Liu. 1999. Macroeconomic Determinants of Stock Market Development. Joumal of Applίed Economίcs, Vol. 11, Νο. 1 (May), pp. 29-59.

Granger, C. W. J. 1969. Investigating Causal Relations by Econometric Models and Cross-Spectral Methods. Econometrίca, 37, 424-438.

Johansen, Soren. 1991. Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrίca , 59, 1551-1580.

Kar, Μ., Ε. J. Pentecost. 2000. Financial Development and Economic Growth in Turkey: Further Evidence οη the Causality Issue. Department of Economics Economίc Research Paper Νο. 00/27.

Levine, R. 1997. Financial Development and Economic Growth: Views and Agenda. Joumal of Economίc Lίterature 35, pp.688-726.

Levine, R., S. Zervos. 1998. Stock Markets, Banks and Economic Growth. Amerίcan Economίc Revίew 88, pp. 537-558.

Loayza, Ν., R. Ranciere. 2004. Financial Development, Financial Fragility, and Growth. World Bank WPS3431.

MacΚinnon, J. G. 1991. Critical Values for Cointegration Tests. Chapter 13 in Long-run Economic Relationships: Readίngs ίn Coίntegratίon, edited by R. F. Engle and C.W.J. Granger, Oxford University Press.

Romer, Ρ.Μ. 1990. Endogenous Technological Change. Joumal of Polίtίcal Economy, 98, pp. 71-102.

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Figure 1. Quarterly Seriew of Economic Growth and Financial Development.

400

300 ~

200 !\ : \ .. f '\ .. . \

100

ο

-100

1 -- EG - ---- · FD

Table 1. The Results of Unit Root Tests

Statistics EG FD

Constant 17.104141 31.72079

Gamma -1.011669 -0.737959

DF-Statistic -8.479097 -6.360605

5 % Critical Value -2.901700 -2.901700

DW-statistic 2.009672 1.889148

Note: (1) All the variables were well approximated with a unit root regression having the intercept as the only deterministic regressors. (2) The critical values for 1, 5 and 10 % significance levels are -3.5850, -2.9286 and -2.6021. (3) Starred values show the significant values at 1 % level.

MURAT KARAGOZ - REVIEW OF ECONOMIC SCIENCES - Νο 12 (2007), 7-20

Table 2. Cointegration Test Results.

Eigenvalue Likelihood 5 Percent 1 Percent Hypothesized Ratio Critical Value Critical Value No.ofCE(s)

0.622306 91.07244 15.41 20.04 None ** 0.279178 22.91545 3.76 6.65 At most 1 **

Unnorrnalized Cointegrating Normalized Cointegrating Coefficients: Coefficients:

EG FD- EG FD c 0.015863 -0.000930 1.000000 -0.058617 -13.87193

0.002762 0.002280 (0.01433)

Notes: (1) Sample: 1987:1 2005:2, (2) Included observations: 70, (3) Test assumption: Linear deterministic trend in the data, (4) Series: EG FD, (5) Lags interval: 1 to 2. (6) *(**) denotes rejection of the hypothesis at 5% (1 % ) significance level, (7) L.R. test indicates 2 cointegrating equation(s) at 5% significance level.

Table 3. Pairwise Granger Causality Tests.

Null Hypothesis: F-Statistic Probability

FD does not Granger Cause EG 0.98108 0.38031

EG does not Granger Cause FD 4.95948 0.00985

Notes: (1) Sample: 1987:1 2005:2, (2) Number of observations are 71, (3) Lag

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Table 4. Error Correction Model.

Error Correction: D(EG) St. Errors t-statistics D(FD) St. Errors t-statistics

CointEql -2.385804 0.24786 -9.62552 2.090141 1.19084 1.75518 D(EG(-1)) 1.154164 0.14575 7.91899 -0.950793 0.70023 -1.35783 D(EG(-2)) 0.293675 0.12360 2.37593 -0.344757 0.59385 -0.58055 D(FD(-1)) -0.075173 0.02549 -2.94874 -0.435287 0.12248 -3.55391 D(FD(-2)) -0.024771 0.02384 . -1.03909 -0.098919 0.11454 -0.86365 c 1.591394 1.88442 0.84450 -6.287669 9.05354 -0.69450

Adj, R-squared 0.867238 F-statistic 91.14518 0.270869 F-statistic 6.126649 S.E. equation 15.62486 AkaikeAIC 8.417420 75.06856 AkaikeAIC 11.55650

Notes: (1) Sample(adjusted): 1988:1 2005:2, (2) Included observations: 70 after adjusting endpoints

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interaction of financial development and economic οι...

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