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Balance-of-payments constrained growth model for the Turkish economy
Economic Modelling 35 (2013) 140–144
Contents lists available at ScienceDirect
Economic Modelling journal homepage: www.elsevier.com/locate/ecmod
Balance-of-payments constrained growth model for the Turkish economy Atilla Gökçe a,⁎, Erhan Çankal b,1 a b
Gazi University, Department of Econometrics, 06500 Ankara, Turkey Yildirim Beyazit University, School of Management, Cinnah Cd. 16, 06690 Ankara, Turkey
a r t i c l e
i n f o
Article history: Accepted 18 June 2013 JEL classification: C32 F43 O40 Keywords: Thirlwall model Balance-of-payments constrained growth model Johansen cointegration methodology
a b s t r a c t Economists have investigated the relationship between output and export in order to explain economic growth for long years. Numerous studies have found very close correspondence between the growth of output and export. It is commonly known that Thirlwall's papers indicate very tight relationship between the growth of output and the ratio of the growth of exports to the income elasticity of demand for imports. This paper aims to apply Thirlwall's balance-of-payments-constrained (BPC) model for the Turkish economy for 1968–2011 period. This research also evaluates the procedures of testing Thirlwall's principle by estimation of the income elasticity of demand for imports using the test of stationarity and cointegration methods. The findings are in accordance with the Harrod–Thirlwall growth model. The test results of Johansen cointegration procedure and the comments on these results are presented as well. © 2013 Elsevier B.V. All rights reserved.
1. Introduction The main purpose of this study is to test the validity of Thirlwall's balance-of-payments constrained (BPC) economic growth model for the Turkish economy. For this purpose, dynamic long-term relationships between gross domestic product and export will be determined by using Johansen (1991, 1995) cointegration method that is more preferable in the literature than the Dickey–Fuller test. The study consists of four parts such as literature review, theoretical foundation of the Thirlwall principle, econometric methodology, and empirical findings. Thirlwall (1979) showed that output and export are closely related to the elasticity of demand for import. Although he was unaware at the time, his finding was an estimate of the dynamic Harrod trade multiplier. Thirlwall's research showed that the level of income is equal to the rate of level of export to the marginal propensity to import. Thirlwall also reminded that the slow and rapid growth rates caused by the balance of payments would lead to low and high productivity rates respectively. The countries may sustain their budget deficits financed by the capital flows in the short run. However, in the long run, they can hardly finance the capital inflow that is over a certain percentage
⁎ Corresponding author. Tel.: +90 5326528460; fax: +90 3122132036. E-mail addresses: [email protected] (A. Gökçe), [email protected] (E. Çankal). 1 Tel.:+90 5056163680. 0264-9993/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.econmod.2013.06.019
of Gross Domestic Product (GDP) and ever increasing. International financial authorities push these countries to impose necessary policies to adjust in such situations. This model has been implemented in many countries today. Some of the important studies will be discussed in Section 2. 2. Literature review Atesoglu (1993a, 1993b, 1994) performed a research and used Johansen technique in order to test the BPC model for the U.S., Canada, and Germany. His study showed that export and real income are cointegrated in the long run. Bairam (1988, 1990, 1993) also contributed to the literature by testing the model for many countries using cointegration analysis and supported the hypothesis of BPC growth. The model was also applied for India by Razmi (2005), for Latin America by López and Cruz (2000) and Holland et al. (2004), for Southeast Asia countries by Ansari and Xi (2000), and for Africa and East Asia countries by Hussain (1999). The findings of these studies were mostly in favor of the model except for some sub-periods. Thirlwall and Hussain (1982) studied on an extended model that allows unbalanced foreign trade along with capital flow in the long run. Their research on developing countries also led to the results that supported this extended new model. McCombie and Thirlwall (1997) tried to move the theory forward. Here, they wanted to make sure that the long run economic growth can be sustained by foreign borrowing. The theoretical result indicates that capital flows will not allow a country's growth to be higher than the rate
A. Gökçe, E. Çankal / Economic Modelling 35 (2013) 140–144
ð4Þ
14 12 10 8
lnGDP
6
lnexport
4 2
2010
2007
2004
2001
0 1998
Y t ¼ ½ð1 þ φ−α Þ=π P dt −P ft þ ðρ=πÞZ t
16
1995
Here, ρ, π, α N 0 and φ b 0. X is the growth rate of export and M is the growth rate of import. Z is the rate of increase in the world income and Y is the rate of increase in the gross domestic product of the relevant country. ρ and π are the elasticities of export and import with respect to income respectively. φ and α denote the export and import elasticities to demand respectively. Since pd and pf represent domestic and world prices then (pd − pf) represents relative prices. Eqs. (1) and (2) are the export and import equations and Eq. (3) is the current account balance. Here, the sizeable impact of differences between the elasticities of export and import to income on the economic growth is taken into consideration (McCombie and Thirlwall, 1997). If Eq. (3) is solved for GDP, the following equation can be written as
1992
ð3Þ
Real exports and real income have been moving together, which reveals that these series may be cointegrated. An empirical confirmation of the Harrod–Thirlwall model requires the account of balance to be consistent with data. In the long-run output should be cointegrated with export, where (1/π) is the cointegration coefficient. In this study, the objective is to test the presence of long term relationship between the variables in Eq. (6) using Johansen (1991, 1995) cointegration method. Here, (1/π) is a cointegration parameter as mentioned previously. Johansen's methodology ascribes to the fundamentals of VAR methodology and uses maximum likelihood ratio test. In the first step, the order of cointegration of the series is determined with the augmented Dickey–Fuller (ADF) test. When the long-term equilibrium relationship is revealed by the Johansen cointegration method, the hypothesis of the Thirlwall model will not be rejected and the validity of the model for Turkish Economy will be proved. The Thirlwall model is estimated for the Turkish economy using the annual data for 1968–2011 period. The Johansen cointegration analysis is performed between GDP and export for this period. The Johansen cointegration methodology is employed in order to show the long-run relationship between GDP and export. GDP and export series are used at their current values in million dollars. The series are in their natural logarithmic forms. The data taken from the World Bank shows the movements of lnGDP and lnexport in time on Graph 1.
1989
X t þ P dt ¼ Mt þ pft :
4. Data, model, and methodology
1986
ð2Þ
Eq. (6) shows Harrod foreign-trade multiplier relation, where (1/π) is a foreign-trade multiplier. The economic growth model with the balance of payments constrained is called Thirlwall model. The model is a different version of Harrod's foreign trade multiplier. The Thirlwall model shown in Eq. (6) indicates that the growth rate with the constrained balanced of payments in the long-run is obtained by dividing the export (or the export growth rate) by the income elasticity of demand for imports.
1983
Mt ¼ α P dt −P ft þ πY t
ð6Þ
1980
ð1Þ
Y t ¼ ð1=πÞX t :
1977
X t ¼ φ P dt −P ft þ ρZ t
ð5Þ
When relative prices are measured in the same monetary units, they will be constant and their difference will be equal to zero according to the Marshall–Lerner condition. Hence, the Eq. (5) can be rewritten as:
1974
Thirlwall model (1979) expresses the long-term economic growth via the dynamic Harrod foreign trade multiplier. According to the model, demand side factors are primary actors on economic growth and the dominant constraint on demand is the balance of payments. The primary aim of the Thirlwall model (1979) is to bring a light on how the balance of payments may affect the countries' performances on economic growth. Thirlwall model is expressed by the following three equations:
Y t ¼ ½ð1=πÞð1−α Þ P dt −P ft þ ð1=πÞX t :
1971
3. Theoretical framework
arranging Eq. (1) for Z and replace it in Eq. (4) gives
1968
determined by Thirlwall's model. The capital flows will not be longer than the duration determined by Thirlwall either. Later, Elliot and Rhodd (1999) and Thirlwall and Hussain (1982) showed that more advanced estimations can be obtained including the effect of borrowing using the same countries and time period. Moreno-Brid (1998–99) contributed to the extended BPC growth model developed by Thirlwall and Hussain in 1982 by including the restriction that the current account deficit is constant in the long run. If the capital flows are permitted but the current deficit relative to domestic income remains constant, then Thirlwall's basic principles will still be valid. Similarly, McCombie and Roberts (2002), argued that under reasonable assumptions related to sustainable net foreign capital inflows as the rate of national income, the capital inflows in the BPC growth model do not make a great contribution in loosening the balance of payments restriction. However, according to Barbosa-Filho (2001), the contribution of Moreno-Brid (1998–99) has two limitations; namely, the model with the BPC is not necessary to be stable and it does not distinguish the interest payments from nonfactor services and good imports. So, Barbosa-Filho (2001) extended the model to allow a sustainable foreign borrowing by taking into account the effects of interest rates. Moreno-Brid (2003) argued that Thirlwall's principle does not take the interest payments to borrowed countries into account without referring to the studies done by Elliot and Rhodd (1999) and Barbosa-Filho (2001). They developed a BPC model that contained interest payments. The model was implemented for the Mexican economy and the results were found to be supportive of the model. The Thirlwall model has still been investigated for various countries. There is an increasing number of empirical studies on this topic.
141
Graph 1. lnGDP and lnexport for the Turkish Economy (1968–2011).
142
A. Gökçe, E. Çankal / Economic Modelling 35 (2013) 140–144
As it can be seen on Graph 1, there is a steadily increase in export. The effect of European sovereign-debt crisis can also be clearly seen on the Turkish export after 2009. The path of export seems to grow more steadily compared to that of GDP. Two break tests of Lee and Strazicich (2003) are applied to lnGDP and lnexport series. However, the breaks that are statistically significant could not be found. Eviews 7.0 and Gauss 6.0 programs are used in order to determine the breaks and to obtain the Johansen cointegration estimations, and to perform the other time series analyses. 4.1. Johansen methodology Johansen's methodology takes its starting point in the vector autoregression (VAR) of order p given by yt ¼ μ þ A1 yt−1 þ ⋯ þ Ap yt−p þ εt where yt is an n × 1 vector of variables that is integrated of order one, which is denoted as I(1) and εt is an n × 1 vector of innovations. This VAR can be rewritten as Δyt ¼ μ þ Πyt−1 þ
p−1 X
Γt Δyt−1 þ εt
i¼1
where Π = ∑ pi = 1Ai − I and Γi = − ∑ pj = i + 1Ai. If the coefficient matrix Π has reduced rank r b n, then there exist n × r matrices α and β each with rank r such that Π = αβ′ and β′yt is stationary. r is the number of cointegrating relationships, the elements of α are known as the adjustment parameters in the vector error correction model and each column of β is a cointegrating vector. It can be shown that for a given r, the maximum likelihood estimator of β defines the combination of yt − 1 that yields the largest canonical correlations of Δyt with yt − 1 after correcting for lagged differences and deterministic variables when they present. Johansen proposes two different likelihood ratio tests of the significance of these canonical correlations and thereby the reduced rank of the Π matrix: the trace test and maximum eigenvalue tests are shown in Eqs. (7) and (8) respectively. λtrace ¼ −T
n X
^ ln 1−λ i
ð7Þ
i¼rþ1
^ λmax ¼ −T ln 1−λ rþ1
ð8Þ
^ i is the ith largest canonical correlaHere, T is the sample size and λ tion. The trace test tests the null hypothesis of r cointegrating vectors against the alternative hypothesis of n cointegrating vectors. The maximum eigenvalue test, on the other hand, tests the null hypothesis of r cointegrating vectors against the alternative hypothesis of r + 1 cointegrating vectors. Neither of these test statistics follows a chi square distribution in general; asymptotic critical values can be found in Johansen and Juselius (1990).
Table 2 The determination of time lag length of the VAR model. Lags logL 0 1 2 3 4 5 6 7 8
−65.45654 39.68680 40.78217 41.66481 42.43430 47.75517 54.92190 55.61844 60.09057
LR
FPE
AIC
SCI
HQ
NA 192.7628a 1.886472 1.422030 1.154232 7.390099 9.157492 0.812632 4.720581
0.145418 0.000528a 0.000622 0.000745 0.000901 0.000853 0.000736 0.000920 0.000947
3.747585 −1.871489a −1.710121 −1.536934 −1.357461 −1.430843 −1.606772 −1.423247 −1.449476
3.835559 −1.607569a −1.270254 −0.921121 −0.565702 −0.463137 −0.463120 −0.103648 0.046069
3.778290 −1.779374a −1.556595 −1.321999 −1.081116 −1.093087 −1.207607 −0.962672 −0.927491
logL: logarithmic likelihood, FPE: final prediction error, AIC: Akaike information criteria, SIC: Schwarz information criteria, and HQ: Hannan–Quinn criteria. a Optimum lag lengths are shown in bold.
It is known that most of the time series are not stationary at their own levels and that the cointegration can occur at different orders. Empirical studies have shown that economic series are usually integrated at order one. Before starting the Johansen cointegration method, the order of cointegration of the series has to be known. However, two series are integrated of different orders, they cannot be cointegrated. Therefore, the first step in testing a time series model is to determine the order of integration by means of testing for unit roots. Hence, ADF unit root test is employed and its results are presented in Table 1. 5. Findings According to ADF test, while H0 is accepted at the log levels of GDP and export series, H0 is rejected at first differences at 1% significance level. Based on this result, the first differences of the series are stationary and integrated of order one. In this situation, the long-run relationship of the series can be investigated. The structure of I(1) of the series represents the growth rates of the variables and consistent with the Thirlwall rule. A crucial determination in using the Johansen procedure is the lag length. The first step of the Johansen cointegration analysis is to estimate unconstrained VAR (p) model and determine the lag length. Hence, the VAR model is estimated and the lag lengths are summarized in Table 2. All the criteria have shown that the appropriate lag-length is 1, namely, the model has VAR (1) structure. The goodness of fit tests for residuals are performed following VAR (1) estimation. Breusch– Godfrey Lagrange Multiplier (LM) is used to test for autocorrelation in residuals and Jarque–Bera tests for normality. Based on the test results, autocorrelation does not exist for 12 lags in residuals (Appendix 1). The normality test shows that the variables have normal distributions both individually and jointly (Appendix 2). Whether the model is stable or not have also been investigated in addition to the tests. For the VAR model to have a stable structure, inverse roots of characteristic polynom of AR should be within unit circle. That all AR roots are in the unit circle shows that the estimated model is stable (Appendix 3 and Appendix 4).
Table 3 Johansen cointegration test. λtrace statistics
Table 1 Augmented Dickey–Fuller test results.
Hypothesis
Variables
k
ADF test statistics (τ) (intercept)
k
ADF test statistics (τ) (intercept with trend)
ln Yt ln Xt Δ ln Yt Δ ln Xt
0 0 0 0
−0.352691 −1.507157 −6.464508 −6.050955
0 0 0 0
−2.387948 −1.848831 −6.385545 −6.266660
[−3.592462] [−3.592462] [−3.596616]a [−3.596616]a
[−4.186481] [−4.186481] [−4.192337]a [−4.192337]a
Notes: Y and X represent GDP and export respectively. H0: the relevant series has unit root. The numbers in brackets are t statistics that are significant at 1% level. k denotes the appropriate lag order according to Schwartz information criteria. a Stationary at 1% level.
H0 : r = 0, H1 : r ≥ 1 H0 : r ≤ 1, H1 : r ≥ 2
Eigenvalues 0.542104 0.085246
λtrace
0.05
p
37.41915 3.831316
20.26184 9.164546
0.0001 0.4378
λmax
0.05
p
15.89210 9.164546
0.0000 0.4378
a
λmax statistics Hypothesis H0 : r = 0, H1 : r = 1 H0 : r ≤ 1, H1 : r = 2
Eigenvalues 0.542104 0.085246
a
33.58784 3.831316
a Denotes rejection of the hypothesis at 5% level based on MacKinnon et al. (1999) p-values. Trace and max-eigenvalue tests indicate one cointegrating equation both 5% level.
A. Gökçe, E. Çankal / Economic Modelling 35 (2013) 140–144 Table 4 The results of Johansen cointegration analysis with normalized cointegrating coefficients. Sample period
Intercept
lnexport
1968−2011
10.0973 [5.6650]a
0.3839 [2.0808]b
Notes: lnGDP is the dependent variable. No deterministic trend in the data in the model 2. a The numbers in brackets are the t values, significant at 1% level. b The numbers in brackets are the t values, significant at 5% level.
Table 5 Thirlwall law: country implications. Countries
(1/π)
π
Turkey (1968−2011) Brazil (1955−1998) Mexico (1976−1996) Argentina (1965−1996) Netherlands (1953 −1976) Sweden (1953−1976) USA (1950 −1994) Bolivia (1953−2002) Colombia (1960 −2005) India (1950−1999) S. Korea (1973−1995)
0.3839 0.4200 0.3780 0.4100 0.5494 0.5681 0.4880 0.4641 1.7000 0.3140 1.4285
2.6048 2.3800 2.6455 2.4390 1.8200 1.7600 2.0491 2.1547 0.5882 3.1847 0.7000
143
deviate its long-run equilibrium growth rate. According to Thirlwall, the most important factors in obtaining the balance in the globalized world are export and import. The growth rate in the long-run is determined by the growth rate in export and the income elasticity of import. One of the most crucial factors that affect the growth in an economy is the changes in growth rate of export. There is an inverse relationship between the income elasticity of import and the volume of export. In other words, as the income elasticity of import increases, the positive impact of export on GDP growth declines. The Thirlwall model has been estimated using the data for 1968– 2011 period for the Turkish economy. In order to do this, Johansen cointegration analysis between the GDP and export is performed. Based on the estimation results, statistically significant positive relationship has been found between lnGDP and lnexport. The findings have proven that the Thirlwall's balance-of-payments-constrained growth model is valid for the Turkish economy. The income elasticity of import for the Turkish economy is estimated at 2.6048. The reductions in this value of the elasticity will accelerate the growth in GDP. This will clearly occur not because of the rises in import but the rises in domestic supply. So, this may arise if the domestic demand increases can be fulfilled not by rises in import but rises in domestic production (supply) in an increasing rate. This study verifies the validity of Harrod–Thirlwall growth model for the Turkish economy.
Appendix 1. VAR Residual Serial Correlation LM Tests* To determine the number of cointegrating vectors and Π matrix, λtrace and λmax statistics, which are given Eqs. (7) and (8), are used based on Johansen (1991, 1995).2 Table 3 exhibits the Johansen cointegration test results. By looking at Table 3, we conclude that the null hypothesis of no cointegration between two variables that enter in Eq. (6) can be rejected at the 5% level of significance by both λtrace and λmax tests in 1968–2011 period. So, the rank of Π matrix is one and lnGDP and lnexport have one cointegrating vector. Table 4 presents the results of Johansen cointegration analysis for lnGDP and lnexport. Statistically significant and positive relationship is found between lnGDP and lnexport based on the estimation results. These findings have proved the validity of Thirlwall's BPC growth model for the Turkish economy. The coefficient of lnexport gives the long-term elasticity of GDP with respect to export as shown in Eq. (6) [(1/π) = 0.3839]. This coefficient is called as the Harrod foreign-trade multiplier. The estimated long-run elasticity is finally used to calculate the income elasticity of demand for import ðπ^ ¼ 2:6048Þ. According to the result, a percentage rise in GDP will increase imports by nearly 2.6%. This result concludes that demand for imports is highly sensitive to output growth. The results of the earlier studies of Thirlwall's BPC growth model for some selected countries are exhibited in Table 5. The findings of this research show similarities for the countries that have similar economic structures. It is clear from the results that increase in income elasticity of demand for imports will reduce the positive effect of export on GDP growth. 6. Conclusion Thirlwall's balance-of-payments-constrained growth model and the resulting Thirlwall rule has adopted the post Keynesian theory and created a policy model that has suggested controls for export and import. Based on Thirlwall model, different growth rates amongst nations can be attributed to the differences in demands. The principal factor that limits growth in an open economy is the balance of payments. It emphasizes that a country's sustainable growth should not
Lags
LM-stat
p
1 2 3 4 5 6 7 8 9 10 11 12
2.179815 1.850948 0.571607 7.848113 6.198471 1.766792 0.208449 6.279008 3.199476 1.201392 3.316029 3.113744
0.7027 0.7631 0.9662 0.0973 0.1848 0.7786 0.9949 0.1793 0.5250 0.8779 0.5064 0.5390
*H0: no serial correlation at lag order k.
Appendix 2. VAR residual normality tests*
Component
Jarque–Bera
df
p
1 2 Joint
2.314792 0.029346 2.344138
2 2 4
0.3143 0.9854 0.6727
*H0: residuals are multivariate normal. Orthogonalization: Cholesky (Lutkepohl).
Appendix 3. Roots of characteristic polynomial
Root
Modulus
0.980343 0.831783
0.980343 0.831783
2
The five separate models have been tried based on Pantula principle in conducting the Johansen cointegration test and decided the model 2 to be the most appropriate (no deterministic trend but intercept).
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A. Gökçe, E. Çankal / Economic Modelling 35 (2013) 140–144
Appendix 4. Inverse roots of characteristic polynomial
Inverse Roots of AR Characteristic Polynomial 1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5 -1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
References Ansari, H., Xi, Y., 2000. The chronicle of economic growth in Southeast Asian countries: does Thirlwall's law provide an adequate explanation. Journal of Post Keynesian Economics 22 (4), 573–588 (summer). Atesoglu, H.S., 1993a. Balance of payments constrained growth: evidence from the United States. Journal of Post Keynesian Economics 15, 507–514 (Summer). Atesoglu, H.S., 1993–4b. Exports, capital flows, relative prices and economic growth in Canada. Journal of Post Keynesian Economics 16 (2), 289–297 (Winter). Atesoglu, H.S., 1994. An application of a Kaldorian export-led model of growth to the United States. Applied Economics 26, 479–483 (January). Bairam, E.I., 1988. Balance of payments, the Harrod foreign trade multiplier and economic growth: the European and North American experience, 1970–85. Applied Economics 20, 1635–1642.
Bairam, E.I., 1990. The Harrod trade multiplier revisited. Applied Economics 22, 711–718 (June). Bairam, E.I., 1993. Static versus dynamic specification and the Harrod foreign trade multiplier. Applied Economics 25, 739–742. Barbosa-Filho, N., 2001. The balance-of-payments constraint: from balanced trade to sustainable debt. Banca Nazionale del Lavoro Quarterly Review 219, 381–400 (December). Elliot, D., Rhodd, R., 1999. Explaining growth rate differences in highly indebted countries: an extension to Thirlwall and Hussain. Applied Economics 31. Holland, M., Vieira, F., Canuto, O., 2004. Economic growth and the balance-of-payments constraint in Latin America. Investigacion Economica LXIII, 45–74. Hussain, M.N., 1999. The balance-of-payment constraint and growth rate differences among African and East Asian economies. African Development Review vol. 11, 103–137 (African Development Bank). Johansen, S., 1991. Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica 55, 1551–1580. Johansen, S., 1995. Likelihood-based Inference in Cointegrated Vector Autoregressive Models. Oxford University Press, Oxford. Johansen, S., Juselius, K., 1990. Maximum likelihood estimation and inferences on cointegration—with applications to the demand for money. Oxford Bulletin of Economics and Statistics 52, 169–210. Lee, J., Strazicich, M., 2003. Minimum Lagrange multiplier unit root test with two structural breaks. The Review of Economics and Statistics 85 (4), 1082–1089. López, J., Cruz, A., 2000. Thirlwall's law and beyond: the Latin American experience. Journal of Post Keynesian Economics 22 (3), 477–495. MacKinnon, J.G., Haug, A., Michelis, L., 1999. Numerical distribution functions of likelihood ratio tests for cointegration. Journal of Applied Econometrics 14 (5), 563–577. McCombie, J., Roberts, M., 2002. The role of balance of payments in economic growth. The Economics of Demand-Led Growth.Edward Elgar, MA. McCombie, J., Thirlwall, A., 1997. The dynamic Harrod foreign trade multiplier and the demand oriented approach to economic growth—an evaluation. International Review of Applied Economics 11, 1. Moreno-Brid, J.C., 1998–99. On capital flows and the balance-of-payments constrained growth model. Journal of Post Keynesian Economics 21. Moreno-Brid, J.C., 2003. Capital flows, interest payments and the balance-of-payments constrained growth model: a theoretical and empirical analysis. Metroeconomica 54 (2–3), 346–365. Razmi, A., 2005. Balance of payments constrained growth model: the case of India. Department of Economics, University of Massachesetts Amherst, Working Paper 2005-05. Thirlwall, A.P., 1979. The balance of payments constraint as an explanation of international growth rate differences. Banca Nazionale del Lavoro Quarterly Review 45–53. Thirlwall, A.P., Hussain, M.N., 1982. The balance of payments constraint, capital flows, and growth rate differences between developing countries. Oxford Economic Papers 34 (10), 498–509.
Contents lists available at ScienceDirect
Economic Modelling journal homepage: www.elsevier.com/locate/ecmod
Balance-of-payments constrained growth model for the Turkish economy Atilla Gökçe a,⁎, Erhan Çankal b,1 a b
Gazi University, Department of Econometrics, 06500 Ankara, Turkey Yildirim Beyazit University, School of Management, Cinnah Cd. 16, 06690 Ankara, Turkey
a r t i c l e
i n f o
Article history: Accepted 18 June 2013 JEL classification: C32 F43 O40 Keywords: Thirlwall model Balance-of-payments constrained growth model Johansen cointegration methodology
a b s t r a c t Economists have investigated the relationship between output and export in order to explain economic growth for long years. Numerous studies have found very close correspondence between the growth of output and export. It is commonly known that Thirlwall's papers indicate very tight relationship between the growth of output and the ratio of the growth of exports to the income elasticity of demand for imports. This paper aims to apply Thirlwall's balance-of-payments-constrained (BPC) model for the Turkish economy for 1968–2011 period. This research also evaluates the procedures of testing Thirlwall's principle by estimation of the income elasticity of demand for imports using the test of stationarity and cointegration methods. The findings are in accordance with the Harrod–Thirlwall growth model. The test results of Johansen cointegration procedure and the comments on these results are presented as well. © 2013 Elsevier B.V. All rights reserved.
1. Introduction The main purpose of this study is to test the validity of Thirlwall's balance-of-payments constrained (BPC) economic growth model for the Turkish economy. For this purpose, dynamic long-term relationships between gross domestic product and export will be determined by using Johansen (1991, 1995) cointegration method that is more preferable in the literature than the Dickey–Fuller test. The study consists of four parts such as literature review, theoretical foundation of the Thirlwall principle, econometric methodology, and empirical findings. Thirlwall (1979) showed that output and export are closely related to the elasticity of demand for import. Although he was unaware at the time, his finding was an estimate of the dynamic Harrod trade multiplier. Thirlwall's research showed that the level of income is equal to the rate of level of export to the marginal propensity to import. Thirlwall also reminded that the slow and rapid growth rates caused by the balance of payments would lead to low and high productivity rates respectively. The countries may sustain their budget deficits financed by the capital flows in the short run. However, in the long run, they can hardly finance the capital inflow that is over a certain percentage
⁎ Corresponding author. Tel.: +90 5326528460; fax: +90 3122132036. E-mail addresses: [email protected] (A. Gökçe), [email protected] (E. Çankal). 1 Tel.:+90 5056163680. 0264-9993/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.econmod.2013.06.019
of Gross Domestic Product (GDP) and ever increasing. International financial authorities push these countries to impose necessary policies to adjust in such situations. This model has been implemented in many countries today. Some of the important studies will be discussed in Section 2. 2. Literature review Atesoglu (1993a, 1993b, 1994) performed a research and used Johansen technique in order to test the BPC model for the U.S., Canada, and Germany. His study showed that export and real income are cointegrated in the long run. Bairam (1988, 1990, 1993) also contributed to the literature by testing the model for many countries using cointegration analysis and supported the hypothesis of BPC growth. The model was also applied for India by Razmi (2005), for Latin America by López and Cruz (2000) and Holland et al. (2004), for Southeast Asia countries by Ansari and Xi (2000), and for Africa and East Asia countries by Hussain (1999). The findings of these studies were mostly in favor of the model except for some sub-periods. Thirlwall and Hussain (1982) studied on an extended model that allows unbalanced foreign trade along with capital flow in the long run. Their research on developing countries also led to the results that supported this extended new model. McCombie and Thirlwall (1997) tried to move the theory forward. Here, they wanted to make sure that the long run economic growth can be sustained by foreign borrowing. The theoretical result indicates that capital flows will not allow a country's growth to be higher than the rate
A. Gökçe, E. Çankal / Economic Modelling 35 (2013) 140–144
ð4Þ
14 12 10 8
lnGDP
6
lnexport
4 2
2010
2007
2004
2001
0 1998
Y t ¼ ½ð1 þ φ−α Þ=π P dt −P ft þ ðρ=πÞZ t
16
1995
Here, ρ, π, α N 0 and φ b 0. X is the growth rate of export and M is the growth rate of import. Z is the rate of increase in the world income and Y is the rate of increase in the gross domestic product of the relevant country. ρ and π are the elasticities of export and import with respect to income respectively. φ and α denote the export and import elasticities to demand respectively. Since pd and pf represent domestic and world prices then (pd − pf) represents relative prices. Eqs. (1) and (2) are the export and import equations and Eq. (3) is the current account balance. Here, the sizeable impact of differences between the elasticities of export and import to income on the economic growth is taken into consideration (McCombie and Thirlwall, 1997). If Eq. (3) is solved for GDP, the following equation can be written as
1992
ð3Þ
Real exports and real income have been moving together, which reveals that these series may be cointegrated. An empirical confirmation of the Harrod–Thirlwall model requires the account of balance to be consistent with data. In the long-run output should be cointegrated with export, where (1/π) is the cointegration coefficient. In this study, the objective is to test the presence of long term relationship between the variables in Eq. (6) using Johansen (1991, 1995) cointegration method. Here, (1/π) is a cointegration parameter as mentioned previously. Johansen's methodology ascribes to the fundamentals of VAR methodology and uses maximum likelihood ratio test. In the first step, the order of cointegration of the series is determined with the augmented Dickey–Fuller (ADF) test. When the long-term equilibrium relationship is revealed by the Johansen cointegration method, the hypothesis of the Thirlwall model will not be rejected and the validity of the model for Turkish Economy will be proved. The Thirlwall model is estimated for the Turkish economy using the annual data for 1968–2011 period. The Johansen cointegration analysis is performed between GDP and export for this period. The Johansen cointegration methodology is employed in order to show the long-run relationship between GDP and export. GDP and export series are used at their current values in million dollars. The series are in their natural logarithmic forms. The data taken from the World Bank shows the movements of lnGDP and lnexport in time on Graph 1.
1989
X t þ P dt ¼ Mt þ pft :
4. Data, model, and methodology
1986
ð2Þ
Eq. (6) shows Harrod foreign-trade multiplier relation, where (1/π) is a foreign-trade multiplier. The economic growth model with the balance of payments constrained is called Thirlwall model. The model is a different version of Harrod's foreign trade multiplier. The Thirlwall model shown in Eq. (6) indicates that the growth rate with the constrained balanced of payments in the long-run is obtained by dividing the export (or the export growth rate) by the income elasticity of demand for imports.
1983
Mt ¼ α P dt −P ft þ πY t
ð6Þ
1980
ð1Þ
Y t ¼ ð1=πÞX t :
1977
X t ¼ φ P dt −P ft þ ρZ t
ð5Þ
When relative prices are measured in the same monetary units, they will be constant and their difference will be equal to zero according to the Marshall–Lerner condition. Hence, the Eq. (5) can be rewritten as:
1974
Thirlwall model (1979) expresses the long-term economic growth via the dynamic Harrod foreign trade multiplier. According to the model, demand side factors are primary actors on economic growth and the dominant constraint on demand is the balance of payments. The primary aim of the Thirlwall model (1979) is to bring a light on how the balance of payments may affect the countries' performances on economic growth. Thirlwall model is expressed by the following three equations:
Y t ¼ ½ð1=πÞð1−α Þ P dt −P ft þ ð1=πÞX t :
1971
3. Theoretical framework
arranging Eq. (1) for Z and replace it in Eq. (4) gives
1968
determined by Thirlwall's model. The capital flows will not be longer than the duration determined by Thirlwall either. Later, Elliot and Rhodd (1999) and Thirlwall and Hussain (1982) showed that more advanced estimations can be obtained including the effect of borrowing using the same countries and time period. Moreno-Brid (1998–99) contributed to the extended BPC growth model developed by Thirlwall and Hussain in 1982 by including the restriction that the current account deficit is constant in the long run. If the capital flows are permitted but the current deficit relative to domestic income remains constant, then Thirlwall's basic principles will still be valid. Similarly, McCombie and Roberts (2002), argued that under reasonable assumptions related to sustainable net foreign capital inflows as the rate of national income, the capital inflows in the BPC growth model do not make a great contribution in loosening the balance of payments restriction. However, according to Barbosa-Filho (2001), the contribution of Moreno-Brid (1998–99) has two limitations; namely, the model with the BPC is not necessary to be stable and it does not distinguish the interest payments from nonfactor services and good imports. So, Barbosa-Filho (2001) extended the model to allow a sustainable foreign borrowing by taking into account the effects of interest rates. Moreno-Brid (2003) argued that Thirlwall's principle does not take the interest payments to borrowed countries into account without referring to the studies done by Elliot and Rhodd (1999) and Barbosa-Filho (2001). They developed a BPC model that contained interest payments. The model was implemented for the Mexican economy and the results were found to be supportive of the model. The Thirlwall model has still been investigated for various countries. There is an increasing number of empirical studies on this topic.
141
Graph 1. lnGDP and lnexport for the Turkish Economy (1968–2011).
142
A. Gökçe, E. Çankal / Economic Modelling 35 (2013) 140–144
As it can be seen on Graph 1, there is a steadily increase in export. The effect of European sovereign-debt crisis can also be clearly seen on the Turkish export after 2009. The path of export seems to grow more steadily compared to that of GDP. Two break tests of Lee and Strazicich (2003) are applied to lnGDP and lnexport series. However, the breaks that are statistically significant could not be found. Eviews 7.0 and Gauss 6.0 programs are used in order to determine the breaks and to obtain the Johansen cointegration estimations, and to perform the other time series analyses. 4.1. Johansen methodology Johansen's methodology takes its starting point in the vector autoregression (VAR) of order p given by yt ¼ μ þ A1 yt−1 þ ⋯ þ Ap yt−p þ εt where yt is an n × 1 vector of variables that is integrated of order one, which is denoted as I(1) and εt is an n × 1 vector of innovations. This VAR can be rewritten as Δyt ¼ μ þ Πyt−1 þ
p−1 X
Γt Δyt−1 þ εt
i¼1
where Π = ∑ pi = 1Ai − I and Γi = − ∑ pj = i + 1Ai. If the coefficient matrix Π has reduced rank r b n, then there exist n × r matrices α and β each with rank r such that Π = αβ′ and β′yt is stationary. r is the number of cointegrating relationships, the elements of α are known as the adjustment parameters in the vector error correction model and each column of β is a cointegrating vector. It can be shown that for a given r, the maximum likelihood estimator of β defines the combination of yt − 1 that yields the largest canonical correlations of Δyt with yt − 1 after correcting for lagged differences and deterministic variables when they present. Johansen proposes two different likelihood ratio tests of the significance of these canonical correlations and thereby the reduced rank of the Π matrix: the trace test and maximum eigenvalue tests are shown in Eqs. (7) and (8) respectively. λtrace ¼ −T
n X
^ ln 1−λ i
ð7Þ
i¼rþ1
^ λmax ¼ −T ln 1−λ rþ1
ð8Þ
^ i is the ith largest canonical correlaHere, T is the sample size and λ tion. The trace test tests the null hypothesis of r cointegrating vectors against the alternative hypothesis of n cointegrating vectors. The maximum eigenvalue test, on the other hand, tests the null hypothesis of r cointegrating vectors against the alternative hypothesis of r + 1 cointegrating vectors. Neither of these test statistics follows a chi square distribution in general; asymptotic critical values can be found in Johansen and Juselius (1990).
Table 2 The determination of time lag length of the VAR model. Lags logL 0 1 2 3 4 5 6 7 8
−65.45654 39.68680 40.78217 41.66481 42.43430 47.75517 54.92190 55.61844 60.09057
LR
FPE
AIC
SCI
HQ
NA 192.7628a 1.886472 1.422030 1.154232 7.390099 9.157492 0.812632 4.720581
0.145418 0.000528a 0.000622 0.000745 0.000901 0.000853 0.000736 0.000920 0.000947
3.747585 −1.871489a −1.710121 −1.536934 −1.357461 −1.430843 −1.606772 −1.423247 −1.449476
3.835559 −1.607569a −1.270254 −0.921121 −0.565702 −0.463137 −0.463120 −0.103648 0.046069
3.778290 −1.779374a −1.556595 −1.321999 −1.081116 −1.093087 −1.207607 −0.962672 −0.927491
logL: logarithmic likelihood, FPE: final prediction error, AIC: Akaike information criteria, SIC: Schwarz information criteria, and HQ: Hannan–Quinn criteria. a Optimum lag lengths are shown in bold.
It is known that most of the time series are not stationary at their own levels and that the cointegration can occur at different orders. Empirical studies have shown that economic series are usually integrated at order one. Before starting the Johansen cointegration method, the order of cointegration of the series has to be known. However, two series are integrated of different orders, they cannot be cointegrated. Therefore, the first step in testing a time series model is to determine the order of integration by means of testing for unit roots. Hence, ADF unit root test is employed and its results are presented in Table 1. 5. Findings According to ADF test, while H0 is accepted at the log levels of GDP and export series, H0 is rejected at first differences at 1% significance level. Based on this result, the first differences of the series are stationary and integrated of order one. In this situation, the long-run relationship of the series can be investigated. The structure of I(1) of the series represents the growth rates of the variables and consistent with the Thirlwall rule. A crucial determination in using the Johansen procedure is the lag length. The first step of the Johansen cointegration analysis is to estimate unconstrained VAR (p) model and determine the lag length. Hence, the VAR model is estimated and the lag lengths are summarized in Table 2. All the criteria have shown that the appropriate lag-length is 1, namely, the model has VAR (1) structure. The goodness of fit tests for residuals are performed following VAR (1) estimation. Breusch– Godfrey Lagrange Multiplier (LM) is used to test for autocorrelation in residuals and Jarque–Bera tests for normality. Based on the test results, autocorrelation does not exist for 12 lags in residuals (Appendix 1). The normality test shows that the variables have normal distributions both individually and jointly (Appendix 2). Whether the model is stable or not have also been investigated in addition to the tests. For the VAR model to have a stable structure, inverse roots of characteristic polynom of AR should be within unit circle. That all AR roots are in the unit circle shows that the estimated model is stable (Appendix 3 and Appendix 4).
Table 3 Johansen cointegration test. λtrace statistics
Table 1 Augmented Dickey–Fuller test results.
Hypothesis
Variables
k
ADF test statistics (τ) (intercept)
k
ADF test statistics (τ) (intercept with trend)
ln Yt ln Xt Δ ln Yt Δ ln Xt
0 0 0 0
−0.352691 −1.507157 −6.464508 −6.050955
0 0 0 0
−2.387948 −1.848831 −6.385545 −6.266660
[−3.592462] [−3.592462] [−3.596616]a [−3.596616]a
[−4.186481] [−4.186481] [−4.192337]a [−4.192337]a
Notes: Y and X represent GDP and export respectively. H0: the relevant series has unit root. The numbers in brackets are t statistics that are significant at 1% level. k denotes the appropriate lag order according to Schwartz information criteria. a Stationary at 1% level.
H0 : r = 0, H1 : r ≥ 1 H0 : r ≤ 1, H1 : r ≥ 2
Eigenvalues 0.542104 0.085246
λtrace
0.05
p
37.41915 3.831316
20.26184 9.164546
0.0001 0.4378
λmax
0.05
p
15.89210 9.164546
0.0000 0.4378
a
λmax statistics Hypothesis H0 : r = 0, H1 : r = 1 H0 : r ≤ 1, H1 : r = 2
Eigenvalues 0.542104 0.085246
a
33.58784 3.831316
a Denotes rejection of the hypothesis at 5% level based on MacKinnon et al. (1999) p-values. Trace and max-eigenvalue tests indicate one cointegrating equation both 5% level.
A. Gökçe, E. Çankal / Economic Modelling 35 (2013) 140–144 Table 4 The results of Johansen cointegration analysis with normalized cointegrating coefficients. Sample period
Intercept
lnexport
1968−2011
10.0973 [5.6650]a
0.3839 [2.0808]b
Notes: lnGDP is the dependent variable. No deterministic trend in the data in the model 2. a The numbers in brackets are the t values, significant at 1% level. b The numbers in brackets are the t values, significant at 5% level.
Table 5 Thirlwall law: country implications. Countries
(1/π)
π
Turkey (1968−2011) Brazil (1955−1998) Mexico (1976−1996) Argentina (1965−1996) Netherlands (1953 −1976) Sweden (1953−1976) USA (1950 −1994) Bolivia (1953−2002) Colombia (1960 −2005) India (1950−1999) S. Korea (1973−1995)
0.3839 0.4200 0.3780 0.4100 0.5494 0.5681 0.4880 0.4641 1.7000 0.3140 1.4285
2.6048 2.3800 2.6455 2.4390 1.8200 1.7600 2.0491 2.1547 0.5882 3.1847 0.7000
143
deviate its long-run equilibrium growth rate. According to Thirlwall, the most important factors in obtaining the balance in the globalized world are export and import. The growth rate in the long-run is determined by the growth rate in export and the income elasticity of import. One of the most crucial factors that affect the growth in an economy is the changes in growth rate of export. There is an inverse relationship between the income elasticity of import and the volume of export. In other words, as the income elasticity of import increases, the positive impact of export on GDP growth declines. The Thirlwall model has been estimated using the data for 1968– 2011 period for the Turkish economy. In order to do this, Johansen cointegration analysis between the GDP and export is performed. Based on the estimation results, statistically significant positive relationship has been found between lnGDP and lnexport. The findings have proven that the Thirlwall's balance-of-payments-constrained growth model is valid for the Turkish economy. The income elasticity of import for the Turkish economy is estimated at 2.6048. The reductions in this value of the elasticity will accelerate the growth in GDP. This will clearly occur not because of the rises in import but the rises in domestic supply. So, this may arise if the domestic demand increases can be fulfilled not by rises in import but rises in domestic production (supply) in an increasing rate. This study verifies the validity of Harrod–Thirlwall growth model for the Turkish economy.
Appendix 1. VAR Residual Serial Correlation LM Tests* To determine the number of cointegrating vectors and Π matrix, λtrace and λmax statistics, which are given Eqs. (7) and (8), are used based on Johansen (1991, 1995).2 Table 3 exhibits the Johansen cointegration test results. By looking at Table 3, we conclude that the null hypothesis of no cointegration between two variables that enter in Eq. (6) can be rejected at the 5% level of significance by both λtrace and λmax tests in 1968–2011 period. So, the rank of Π matrix is one and lnGDP and lnexport have one cointegrating vector. Table 4 presents the results of Johansen cointegration analysis for lnGDP and lnexport. Statistically significant and positive relationship is found between lnGDP and lnexport based on the estimation results. These findings have proved the validity of Thirlwall's BPC growth model for the Turkish economy. The coefficient of lnexport gives the long-term elasticity of GDP with respect to export as shown in Eq. (6) [(1/π) = 0.3839]. This coefficient is called as the Harrod foreign-trade multiplier. The estimated long-run elasticity is finally used to calculate the income elasticity of demand for import ðπ^ ¼ 2:6048Þ. According to the result, a percentage rise in GDP will increase imports by nearly 2.6%. This result concludes that demand for imports is highly sensitive to output growth. The results of the earlier studies of Thirlwall's BPC growth model for some selected countries are exhibited in Table 5. The findings of this research show similarities for the countries that have similar economic structures. It is clear from the results that increase in income elasticity of demand for imports will reduce the positive effect of export on GDP growth. 6. Conclusion Thirlwall's balance-of-payments-constrained growth model and the resulting Thirlwall rule has adopted the post Keynesian theory and created a policy model that has suggested controls for export and import. Based on Thirlwall model, different growth rates amongst nations can be attributed to the differences in demands. The principal factor that limits growth in an open economy is the balance of payments. It emphasizes that a country's sustainable growth should not
Lags
LM-stat
p
1 2 3 4 5 6 7 8 9 10 11 12
2.179815 1.850948 0.571607 7.848113 6.198471 1.766792 0.208449 6.279008 3.199476 1.201392 3.316029 3.113744
0.7027 0.7631 0.9662 0.0973 0.1848 0.7786 0.9949 0.1793 0.5250 0.8779 0.5064 0.5390
*H0: no serial correlation at lag order k.
Appendix 2. VAR residual normality tests*
Component
Jarque–Bera
df
p
1 2 Joint
2.314792 0.029346 2.344138
2 2 4
0.3143 0.9854 0.6727
*H0: residuals are multivariate normal. Orthogonalization: Cholesky (Lutkepohl).
Appendix 3. Roots of characteristic polynomial
Root
Modulus
0.980343 0.831783
0.980343 0.831783
2
The five separate models have been tried based on Pantula principle in conducting the Johansen cointegration test and decided the model 2 to be the most appropriate (no deterministic trend but intercept).
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A. Gökçe, E. Çankal / Economic Modelling 35 (2013) 140–144
Appendix 4. Inverse roots of characteristic polynomial
Inverse Roots of AR Characteristic Polynomial 1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5 -1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
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