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Journal of Chinese Economic and Foreign Trade StudiesThe relationship between international trade openness and economic growth in

the developing economies: Some new dimensionsMuhammad Tahir Toseef Azid

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The relationship between

international trade openness andeconomic growth in thedeveloping economies

Some new dimensionsMuhammad Tahir

Department of Management Sciences, Comsats Institute of InformationTechnology, Abbottabad, Pakistan, and

Toseef Azid Department of Finance and Economics, College of Business and Economics,Qassim University, Qassim, Kingdom of Saudi Arabia

Abstract

Purpose – This paper aims to establish a relationship between trade openness and economic growthin the context of the developing countries. This study has proposed a new measure of trade openness tothe literature, as the available measures are awed.

Design/methodology/approach – Empirical analyses are carried out with the help of paneleconometric techniques.

Findings – The main nding of the paper is that the relationship between trade openness andeconomic growth is positive and statistically signicant for developing countries. Besides tradeopenness, other determinants of economic growth such as investment and labour force are alsosignicantly related with economic growth and carry expected coefcients. Further, it is found thatfrequent uctuations in prices are detrimental to long-run economic growth.

Practical implications – Therefore, the developing countries are suggested to speed up the processof trade liberalization and also pay favourable attention to other determinants of economic growth toachieve high economic growth.

Originality/value – The authors have used a new measure of trade openness apart from theconventional trade volume measure of trade openness.

Keywords Economic growth, Panel data, Trade openness, Education, Fixed effects

Paper type Research paper

1. IntroductionWhile economies are striving hard to achieve high economic growth, it becomes moreimportant to answer the question what actually determines their economic growth.Trade openness has recently been considered as an important determinant of economicgrowth. It has been witnessed during the past couple of decades that international tradeopenness has played a signicant role in the growth process of both developed anddeveloping countries. International organizations such as World trade organization,International Monetary Fund and World Bank are constantly advising, especiallydeveloping countries, to speed up the process of trade liberalization to achieve high

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Tradeopenness and

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Vol. 8 No. 2, 2015pp. 123-139

© Emerald GroupPublishing Limited1754-4408

DOI 10.1108/JCEFTS-02-2015-0004

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economic growth. High economic growth is the ultimate goal of all economic activitiesbecause it improves the standard of life of people which is desirable. The generalperception is that high trade openness leads to high economic growth ( Anderson and

Babula, 2008; Tahir and Norulazidah, 2014 ).Rodriguez and Rodrik (2001) have casted doubt on the earlier literature ( Dollar, 1992;

Sach and Warner, 1995; Edwards, 1998; Frankel and Romer, 1999 ) by highlightingissues related to the measures of trade openness and used methodologies.Huchet-Bourdon et al. (2011) have reported recently that the measures of trade opennessused in the earlier studies and the methodologies used to estimate models that linkopenness to growth are still open to doubt. Researchers have used various tools of analysis on different objective and subjective indices of openness over the years to ndthe link between trade openness and economic growth Tahir and Norulazidah (2014).These consequent efforts in the literature have further made it difcult for theresearchers to select appropriate measures of openness and choose the best

methodology of estimation. According to Greenaway et al. (2002), the use of diverseindices of liberalization coupled with the problem of miss-specication could beresponsible for the inconsistent evidence regarding the growth effects of liberalization.Hallak and Levinsohn (2004) have suggested that the future research efforts shall focuson identifying the mechanisms by which trade openness inuences economic growth.On the contrary, Fiestas (2005) has argued that, despite methodological issues, there isno evidence that trade liberalization is harmful for economic growth.

Corresponding to this remark, the main objective of this paper is to test whether hightrade openness is associated with high economic growth in the context of the developingcountries. If trade openness really matters for achieving high economic growth, then theprocess of trade liberalization shall speed up to grow fast. The study proposes a new

measure of trade openness to the existing trade–growth literature and also paysattention to address the endogeneity issue associated with the trade–volume measure of trade openness. The researchers have not come to a conclusion whether trade opennessleads to economic growth ( Matadeen et al., 2011; Ulasan, 2012; Dava, 2012 ). Therefore,the results of our study might be useful for policymakers in the developing countries.

The current paper has demonstrated a positive and statistically signicantrelationship between trade openness and economic growth using different measures of trade openness with the help of panel econometric techniques. The analysis also ndsthat labour force and domestic investment are the key determinants of economic growthfor developing countries. In addition, it is found that human capital has not contributedsignicantly to the economic growth of the sampled countries. Further, the study found

that ination volatility has adversely inuenced the economic growth, indicating thatthe developing countries should ensure macroeconomic stability to grow faster in thelong run.

The reminder of the paper is organized as following. In Section 2, we have brieyreviewed the literature on the relationship between trade openness and economicgrowth to provide a prelude for subsequent discussions. Discussion on the measures of trade openness is provided in Section 3. The specication of the model, variablesspecication, data sources and the issue of endogeneity are discussed in Section 4.Section 5 includes methodology of estimation. Results of the study are analyzed inSection 6. In the penultimate section, the robustness issue of the results is addressed.Conclusions are drawn and policy recommendations are advised in Section 8.

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2. Literature reviewContemporary studies have focused on the relationship between trade openness andeconomic growth. For example, inuential studies conducted by Dollar (1992), Sach and

Warner (1995), Edwards (1998) Frankel and Romer (1999) and Ezeani (2013) haveprovided concrete evidence regarding the positive relationship between trade opennessand economic growth. Rodriguez and Rodrik (2000), however, have reservations on themethodologies applied and the way trade openness is measured in the mentionedstudies. Again, Rodriguez (2007) has critically evaluated recent studies carried out byDollar and Kraay (2002), Warner (2003) and Wacziarg and Welch (2003) and hasconcluded that standard measures of trade policy are not associated with economicgrowth. In a recent paper, Abbas (2014) empirically found that trade opennessdeteriorates economic growth. The author demonstrated that one unit increase in tradeliberalization will decrease economic growth by US$280.86 million for developingcountries.

Panagariya (2004), however, has analyzed the criticism made by Rodriguez andRodrik (2000) and concluded that the evidence from cross-country growth regression isnot weak, and therefore, outward-oriented policies cannot be rejected. Further, theauthor has argued that controversies arise because of our inabilities to measure theprotective effects of a given set of trade barriers. Bhagwati and Srinivasan (2001)have also analyzed the criticism Rodriguez and Rodrik (2000) have made about thepositive relationship between trade openness and economic growth and commented thatthe criticism is unpersuasive. More to the point, Warner (2003) has commented that thecrucial evidence is ignored, and, indeed, there was a negative relationship between traderestrictions and economic growth.

In the context of the developing countries, Dollar (1992) found that the relationshipbetween trade liberalization and economic performance is positive. Sach and Warner(1995) empirically demonstrated that open developing economies grew at 4.49 per centper year, while closed developing economies grew at 0.69 per cent per year. Dewan andHussein (2001) have also provided evidence in favour of a positive relationship betweenopen trade policies and economic growth for a sample of 41 middle-income developingcountries over the period 1965-1997.Yanikkaya (2003) showed that the relationshipbetween trade restrictions and economic growth is positive. A recent study conductedby Ackah (2008) shows that trade liberalization seems to inuence economic growth inrelatively richer economies and not in low-income economies. Dufrenot et al. (2009)argued that low-growth economies can benet the most from trade openness in the longrun, while in the short run, they are also likely to suffer. These controversies may beexplained by our inabilities to correctly measure the protective effects of traderestrictions ( Panagariya, 2004 ).

The literature has also paid attention to examine the impact of trade openness oneconomic growth for the developed countries. For example, Ugurlu (2010) has focusedon economies belonging to the European Union organization and reported a weaknegative relationship between trade openness and economic growth. On the other hand,Dowrick and Golley (2004) commented that most of the benets of trade liberalizationhave occurred in the developed countries after 1980. Ackah (2008) also reached the sameconclusion regarding the impact of trade liberalization and economic growth and arguedthat trade liberalization inuences economic growth in relatively richer economies. In a

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recent study, Sarkar (2007) found that higher real growth is associated with higher tradeshare for only richer and trade-dependent economies.

Recent literature believes that the debate on the trade–growth relationship is still

alive. Stensnes (2006) rightly argued that a robust relationship between trade opennessand economic growth has yet to be established. In addition, the author argued that thetrade–growth relationship shall be determined empirically because of the ambiguitiesin theoretical models of trade and growth. In addition, Dava (2012), for example, haveargued the debate on the trade–growth connection did not reach a convincingconclusion. A similar point has been raised by Ulasan (2012) by documenting that thedebate on trade– growth relationship is controversial, and the available literature hasnot provided convincing and robust evidence. Moreover, the author argued that theorydoes not provide a decisive answer about the trade–growth relationship.

3. Measures of trade openness

In this paper, we use the conventional trade–volume measure of trade openness. Thetrade–volume measure, however, is endogenous. Therefore, we follow the strategy of instrumentation to address the issue of endogeneity. We also approximate the degree of trade openness of an economy using industrial output as a ratio of gross domesticproduct (GDP). The industrial output as a ratio of GDP also measures the degree of tradeopenness of an economy. To our understanding of the empirical literature, the ratio of industrial output to GDP has not been used for measuring the degree of trade openness.In the following paragraph, a brief explanatory note on why industrial output as a ratioof GDP is used for measuring the degree of trade openness is provided.

3.1 The ratio of industry output to GDP

It is believed that open economies are in a better position to import investment andintermediate goods than closed economies. The import of investment and intermediategoods from the developed countries is important for the development of domesticindustrial sector of the developing countries. This is because such imports containadvanced technologies. The imports of intermediate and capital goods will ourishmanufacturing activities in the economy. Consequently, they increase the contributionof industrial sector to GDP. Alternatively, trade openness increases the manufacturingactivities in the economy. In other words, the share of industrial output to GDP increaseswith the degree of trade openness of a country. The manufacturing activities aredependent on trade openness in the sense that only open economies can import requiredimportant capital goods, such as machinery and technologies, from abroad. Foreign

capital and intermediate goods, which embody superior technology, enhanceproductivity growth in the sector which uses this product ( Das, 2002; Dollar, 1992 )argued that outward-oriented policies provide opportunities to economies to useexternal capital for development purpose. As the industrial sector is a more dynamicand productive sector than the other sectors of the economy, therefore, the contributionof industrial sector towards GDP would increase signicantly. This shows that there isa close link between the opening of the economy and the contribution of the industrialsector. For this reason, industrial output as a ratio of GDP could be used as a measure of trade openness because of its close relationship with the outward-oriented policies.

This proposed measure of trade openness could help researchers avoid the problemof endogeneity issue which is associated with the trade–volume measure openness. The

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trade–volume measure of openness is endogeneous because it can be affected bypopulation, while there is no direct link between population and industrial output as aratio of GDP. In other words, the proposed measure of trade openness will help

researchers in the trade–growth literature to avoid the problem of endogeneity whileexamining the impact of trade openness on economic growth. In the developingcountries, most of the manufacturing industries are linked with agricultural sector; theyneed capital equipments from the developed countries. Hence, we argue that if thedeveloping countries want to achieve the better growth performance, they need topursue open trade policies to import the capital and technological goods from theadvanced economies.

4. Model, data sources and endogeneity4.1 The model The main objective of the paper is to link trade openness to economic growth. However,

economic growth is indeed a complex process and may be inuenced by variousdeterminants. Econometric modelling in growth literature usually starts with thetraditional model of Solow (1956). The Solow (1956) growth model demonstrates that, inthe presence of exogenous technology, output could be accelerated by labour force andphysical capital stock. However, this model does not explain how technology changesovertime. Mankiw et al. (1992) have introduced the augmented growth model byincluding human capital in the traditional Solow model of economic growth. The role of human capital is also emphasized in the new growth literature, such as Romer (1986) andLucas (1988). Focusing only on a single determinant, such as trade openness, andignoring other determinants may be misleading. Other determinants of economicgrowth, such as investment, labour force, education and macroeconomic stability, are

also equally important for achieving high economic growth ( Barro, 2003; Dewan andHussein, 2001 ). We have a sample of 50 developing countries over the period 1990-2009.The list of sampled developing countries is provided in the Appendix 1. Data areconverted to ve-year averages to avoid short-run uctuations that could affect therelationship between the independent variables and economic growth ( Harrison, 1995 ).The following model is specied for the empirical analysis:

grgdpchit b0 b1lninvit b2lnopenit b3glabf it b4lteduit

b5lnsdninflit Uit(1)

The subscript i represents the cross-sectional dimension of the data and t stands for thetime dimension of the data. Uit is the usual error term. The term grgdpchit stands for thedependent variable, and it measures the growth of real per capita GDP. Domestic capitalformation is denoted by lninvit, as it is used as a proxy for investment. Trade opennessis denoted by lnopenit and is calculated by dividing the sum of exports and imports onGDP. Further, the ratio of industrial output to GDP lnindsit is also used for measuring thedegree of trade openness. The term glabf it stands for the growth of labour force which iscalculated as the growth rate of population ageing between 15 and 64 years. lnsdinflitrefers to the standard deviation of ination. Equation ( 1 ) can be re-written as below:

grgdpchit b0 bk(X)it Uit (2)

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Equation ( 2 ) is the nal growth regression specied for the empirical analysis. The term X it includes all our independent variables, which are dened in equation ( 1 ).

4.2 Data and measurementsThis section provides information on the variables included in the model and datasources. For economic growth, the growth of real per capita GDP in purchasing powerparity is used, and data are taken from the Penn World Tables version 7. Domesticinvestment in the economy is approximated by the gross xed capital formation as aratio of GDP. Labour force is measured by the growth of population ageing between 15and 64 years. The ratio of exports imports to GDP and the ratio of industrial outputare used for measuring the degree of trade openness. Ination rate is approximated bythe annual growth of GDP deator in percentage, and its volatility is calculated by thestandard deviation of the ination. Data on domestic investment and industrial outputas a ratio of GDP are obtained from World development indicators 2012. Human capital

in the economy is measured by the gross enrolment ratios at secondary level. Thisvariable is calculated by the ratio of total enrolment, regardless of age, to the populationof the age group that ofcially corresponds to the secondary level. Educational data areobtained from CANA database. Detailed information on variables, data sources and thelists of countries are provided in the Appendix 1.

4.3 The endogeneity problemThe conventional measure of trade openness (exports imports as a ratio of GDP)which is also used in this study is endogenous. It is because of the fact that foreign tradepattern of a country can also be affected by its size regardless of its trade policy.Renowned researches have highlighted the endogeneity issue associated with the

measure of trade openness ( Frankel and Romer, 1999;Winters, 2004; Romalis, 2007;Tahir, 2013; Tahir et al ., 2013 ). Therefore, the strategy of instrumentation shall be usedto obtain unbiased results.

This study assumes that size of a country measured by population may affect itsforeign trade. However, the point want to make here is that the relationship between sizeof a country (population) and its foreign trade also depends on the productive capacityof the domestic economy. To put it differently, a country with even a high populationmay trade more if it is incapable to produce enough to meet up the demands of domesticconsumers and producers. It could trade less if it produces sufcient to full thedomestic demands of both consumers and producers. In other words, the productivecapacity of an economy plays a signicant role in determining the pattern of foreign

trade. To remove the impact of size of a country on its foreign trade, we regressed 20years of data on trade openness on 20 of years data on total population for each countryincluded in the sample. The tted values are collected and converted to ve-yearaverages. These averages are, in turn, used as an instrument for trade openness in thegrowth regression. The simple correlation coefcient between the actual trade opennessand the tted values is 0.93, which shows the strength of the instrument. Actual tradeopenness is plotted against the constructed instrument trade in the following Figure 1.

In Figure 1, actual trade openness is plotted on the horizontal axis, while theconstructed trade openness is plotted on the vertical axis. Both the quantities are inpercentages. The gure displays a strong positive relationship between the actual tradeopenness and constructed trade openness. Both the quantities are moving in the same

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direction. Most of the data points are overlapping, indicating the validity of theinstrument. In other words, the adopted approach is appropriate and the constructedinstrument for trade openness is valid.

5. Estimating methodologyThe panel is balanced and covers 50 developing countries over a period of 1990-2009.Data are converted to ve-year averages. Fixed and random effects models are powerful

techniques for analyzing panel data. The xed-effects model is appropriate if thecross-section specic error term and the explanatory variables are correlated, andthe random effects model is appropriate if the cross-section specic error term and theexplanatory variables are uncorrelated ( Gujarati, 2004 ). The heteroscedasticity problemis suspected owing to the cross-sectional dimension of the data. In the presence of heteroscedasticity, the usual standard errors are wrong which ultimately invalidates thetest of signicance and leaving no impact on coefcients of the variables. Theheteroscedasticity problem is corrected by estimating models with White (1980) robustestimator. The Hausman (1978) specication test is conducted, and its results providedevidence in favour of xed-effects model, and hence, random effects model is ignored.Therefore, models are estimated with xed effects. The results for the estimated models

are provided in Table I.

6. Results and discussionThe regression results based on the pooled least squares estimation are reported in therst three columns of Table I. The results show that the relationship between tradeopenness and economic growth is statistically insignicant. The relationship betweentrade–volume measure and economic growth is even negative but statisticallyinsignicant. On the other hand, domestic investment and volatility of ination rate aresignicantly related with economic growth and carry expected coefcients. The impactof the growth of labour force on economic growth is not only negative but alsostatistically signicant. However, the data are not poolable, and hence, results with the

2.5

3.0

3.5

4.0

4.5

5.0

5.5

0 40 80 120 160 200 240

Actual trade openness

I n s t r u m e n t e d t r a d e o p e n n e s s

Figure 1.The relationship

between actual tradeopenness and

instrumented tradeopenness

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Table I.Main regressionresults

M e t h o d o f

e s t i m a t i o n

P o o l e d r e g r e s s i o n m o d e l s

P a n e l x e d - e f f e c t s m o d e l s

l n i n v i t

0 . 1 8 ( 4 . 9 3

) * * *

0 . 1 8 ( 4 . 9

2 ) * * *

0 . 1 5 ( 4 . 1

7 ) * * *

0 . 1 0 ( 3 . 3

3 ) * * *

0 . 0 9 ( 4 . 1

2 ) * * *

0 . 1 2 ( 6 . 6

7 ) * * *

g l a b f i

t

0 . 6 5 ( 2 . 8

8 ) * * *

0 . 6 5 ( 2 . 8 6 ) * * *

0 . 6 0 ( 3 . 0 8 ) * * *

0 . 6 0 ( 3 . 0

8 ) * * *

0 . 4 8 ( 2 . 5

1 ) * *

0 . 6 5 ( 4 . 1

2 ) * * *

l n e d u i t

0 . 0 1 ( 0 . 7

8 )

0 . 0 1 ( 0 . 7 7 )

0 . 0 2 ( 1 . 1 4 )

0 . 1 2 ( 1 . 6

6 ) *

0 . 1 2 ( 1 . 5

7 )

0 . 0 9 ( 1 . 5

2 )

l n o p e n i t

0 . 0 2 ( 1 . 4

1 )

0 . 0 8 ( 1 . 7

0 ) *

l n o p e n 1 0 i t

( I n s t r u m e n t )

0 . 0 3 ( 1 . 3 9 )

0 . 1 5 ( 8 . 7

7 ) * * *

l n i n d s i t

0 . 0 4 ( 1 . 2

8 )

0 . 1 1 ( 1 . 8

2 ) *

l n s d i n f l i t

0 . 0 3 ( 3 . 8

9 ) * * *

0 . 0 3 ( 3 . 8 8 ) * * *

0 . 0 3 ( 4 . 0 6 ) * * *

0 . 0 5 ( 4 . 4 3 ) * * *

0 . 0 5 ( 4 . 4 8 ) * * *

0 . 0 5 ( 4 . 4 6 ) * * *

C

0 . 1 4 ( 0 . 9

9 )

0 . 1 4 ( 0 . 9 9 )

0 . 0 7 ( 0 . 4 7 )

0 . 9 8 ( 2 . 4 9 )

1 . 2 6 ( 3 . 8 8 )

0 . 4 7 ( 3 . 7 7 )

S t a t i s t i c a l c r i t e r i a

R 2

0 . 2 7

R 2 ( A d j )

0 . 2 4

F

1 0 . 6 5

R 2

0 . 2 7

R 2 ( A d j )

0 . 2 4

F

1 0 . 6

3

R 2 0 . 2 6

R 2 ( A d j )

0 . 2 4

F

1 0 . 5

6

R 2

0 . 6 8

R 2 ( A d j )

0 . 4 9

F

3 . 5 8

R 2

0 . 6 8

R 2 ( A d j )

0 . 5 0

F

3 . 6 7

R 2 0 . 6

8

R 2 ( A d j )

0 . 4 9

F 3 . 5

6

N o t e s : T h e d e p e n d e n t v a r i a b l e i s t h e g r o w t h o f r e a l p e r c a p i t a G D P i n

p u r c h a s i n g p o w e r p a r i t y ; t - S c o r e s a r e b a s e d o n W h i t e ( 1 9 8 0 ) r o b u s t s t a n d

a r d e r r o r s ;

( * * * ) , ( * * ) a n d ( * ) r e p r e s e n t s 1 , 5

a n d 1 0 % l e v e l o f s i g n i c a n c e , r e s p e c t i v e l y .

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pooled least squares estimation are less important. Therefore, we do not discuss themfurther. Next, we proceed to results of xed-effects estimation.

The results based on xed-effects estimation are reported in the last three columns.

The results show that the impact of actual trade openness (column 5) and instrumentedtrade openness (column 6) on economic growth is positive and also statisticallysignicant at standard level. The results regarding the impact of trade openness areconsistent with the research of Leyaro (2015), Tahir and Khan (2014) and Sarkar (2007).The last column of Table I shows that the relationship between trade openness which ismeasured by the ratio of industrial output of GDP and economic growth is also positiveand statistically different from zero at the 10 per cent level. It follows that industrialoutput as a ratio of GDP also measures the degree of trade openness. Therefore, the ratioof industrial output ratio to GDP can also be used as a measure of trade openness. Thesignicance of the measures of trade openness has conrmed that the relationshipbetween trade openness and economic growth is positive and also statistically

signicant. Therefore, the developing countries are required to speed up the process of trade liberalization to achieve high economic growth. They should not worry about theweak arguments favouring protectionism.

The results have also revealed that domestic investment has signicantly inuencedeconomic growth in the context of the developing countries. Efforts are required on thepart of policymakers to encourage more investment to enhance economic growth.Barro’s (2003) study on the determinants of economic growth, such as for investmentrate, has resulted in a similar conclusion. The impact of education on economic growthis marginally signicant in one of the specications. It is hard to pin down the reasonbehind the insignicant role of human capital in the process of economic growth. Theimpact of education, however, may be realized through lagged effects and also the

relationship may be non-linear. Benhabib and Spiegel (1992) have also found aninsignicant role of human capital on economic growth as a separate independentvariable in the growth regression. They have explained that human capital caninuence economic growth indirectly through attracting physical capital, and it can alsowork as a determinant of Solow residuals in the production function. Moreover, theresults also show that the sampled developing countries have been benetedsignicantly from the growth of labour force. Majority of the developing countries arerich in labour force. Dewan and Hussein (2001) have also showed a positive relationshipbetween labour force and economic growth. The developing countries in particular cantake advantage of their huge population by bringing more people to the labour force.The results also show that volatility of ination rate is detrimental to the long-run

economic growth. Judson and Orphanides (1996) have disclosed that volatility of ination has a signicant and negative impact on economic growth. The studyconducted by Bassanini and Scarpetta (2001) also shows that the variability of inationrate is harmful for economic growth. Therefore policymakers are required to take stepsto avoid frequent uctuation in prices. Such an exercise would improve economicgrowth.

The xed-effects estimation procedure has improved the results signicantly ascompared to the pooled least squares estimation techniques. The insignicantrelationship between trade openness and economic growth using the pooled leastsquares becomes signicant in the xed-effects estimation procedure. Similarly, thexed-effects estimation has also turned the negative relationship between the growth of

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labour force and economic growth into positive. Further, the explanatory power of themodels with xed effects is also high as compared to the pooled least squares models.

It should be noted that the estimated growth equation explains variation in the

dependent variable quite well. The explanatory power of the equations is 0.49 and 0.50with actual trade openness and instrumented trade openness, respectively. Theexplanatory power of 0.49 is observed for the equation where industrial output as a ratioof GDP is used as a measure of trade openness. Also, the overall test of signicance( F -test) is also statistically signicant at 1 per cent level for all the estimated equations.The overall test of signicance ( F -test) has conrmed that the estimated equations areefcient and ts well to the data.

7. Robustness testingIn this section, we proceed to carry out robustness testing for the results. In the rstinstance, the two stages least squares (2SLS) is used to estimate the model to examine

whether the results reported in Table I are sensitive to the alternative method of estimation or not. Further, some institutional variables, such as the index of democracy,political right index and electoral self determination index, are introduced into the modelto examine their impact on the observed results reported earlier. Results are provided inthe following Table II.

The results presented in Table II have provided sound support to the earlier resultsin Table I. The rst column of Table II contains results with the 2SLS. The results showthat the relationship between trade openness, investment, education, growth of labourforce and economic growth is not only positive but also statistically signicant.Similarly, the results regarding the impact of ination volatility on economic growth isnegative. It implies that the results of Table I are robust to the alternative method of

estimation. Similarly, the results reported in the remaining column of Table II showsthat the basic results reported in Table I have not change with the inclusion of institutional variables. However, the results show that democracy and electoral

Table II.Robustness testing(2SLS, inclusion of institutionalvariables)

Variables 2SLSFixedeffects

Fixedeffects

Fixedeffects

lninv it 0.07** 0.09** 0.09*** 0.09*** glabf it 0.57*** 0.59*** 0.55*** 0.54** lnedu it 0.12* 0.12* 0.14* 0.11 lnopen it 0.17*** 0.08* 0.10** 0.08* lnsdinfl it 0.05*** 0.05*** 0.05*** 0.05***dem it 0.0004

pright it 0.02***esd it 0.03C 1.25 0.98 1.14 0.89Diagnostictests

R 2 0.68Adjusted

R 2 0.48

R 2 0.68Adjusted

R 2 -0.49

R 2 0.69Adjusted

R 2 0.50

R 2 0.69Adjusted

R 2 0.49 F 3.67 F 3.49 F 3.61 F 3.55

Notes: Thedependent variable is thegrowth of real percapita GDP in purchasing power parity. ( ***),( **) and ( * ) shows 1, 5 and 10% level of signicance, respectively

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self-determination indices have not inuenced the economic growth of the sampleddeveloping countries signicantly. Further, the political right index has inuenced theeconomic growth negatively and signicantly which was not expected. The weak and

inefcient form of governments in the developing countries may explain the observedinsignicant relationship between the mentioned indices and economic growth. Ingeneral, we can conclude from Table II that the results reported in Table I are robust tothe method of estimation and the inclusion of additional variables. The adjusted R -square value is approximately 0.50 in almost all cases, showing that the tted modelsexplain the variation in the dependent variable reasonably well. Further, the jointsignicance test ( F -test) shows that the estimated models t the data well.

8. ConclusionsThis paper has examined the trade– growth relationship for the sampled developing

countries. Panel data xed-effects models are estimated and two measures of tradeopenness are used in the empirical analysis. The 2SLS method is also used, and someinstitutional variables are included in the model step by step to check the robustnessof the results. The data range from 1990 to 2009 and cover 50 developing countries.

The results show that trade openness has inuenced economic growth positivelyand signicantly in the context of the developing countries. The positive impact of both the openness measures (the ratio of exports imports to GDP and industrialoutput as a ratio of GDP) on economic growth indicates that indeed trade opennessimproves economic growth. Industrial output as a ratio of GDP which is used as analternative measure of trade openness has performed well in the empirical analysisand, therefore, could be used in the future studies. The developing countries are

suggested to speed up the process of trade liberalization to accelerate the rate of economic growth and improve the living standard of the masses. However, thedeveloping countries should also focus on the imports of new technologies andcapital goods instead of consumable items.

Other determinants of growth such as domestic investment and labour force havealso played a vital role in the growth process of the developing countries. Majority of thedeveloping countries do not have enough capital due to resource constraints, but, atthe same time, they are quite rich in terms of labour force. Increased investment in thedomestic economy would not only remove the deciency of capita stock but would alsoprovide jobs opportunities for the growing labour force. The lesser role of education inthe growth process of the sampled developing countries may be due the lagged effect ornon-linearity that exists between human capital and economic growth. Moreover, it isfound that ination volatility has adversely affected economic growth of the developingcountries. Frequent uctuations are harmful indeed for a growing economy because of its adverse impact on the condence level of all stakeholders of the economy. In otherwords, stable economic environment is a prerequisite for a growing economy. Theinstitutional variables used in the model have not inuenced the economic growth rateof the sampled countries signicantly in most of the cases. In conclusion, the developingcountries are suggested to speed up the process of trade liberalization and also payfavourable attention to other determinants of economic growth to achieve higheconomic growth.

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8.1 Policy recommendations

• Policymakers in the developing countries are suggested to speed up the process of trade liberalization if they want to grow faster in the long run. The remarkable

growth experience of the Asian tigers over the years and the recent positivegrowth experiences of some of the developing countries, such as China and India,indeed indicate the superiority of outward-oriented policies over theinward-oriented policies. However, the process of trade openness could beenforced step by step.

• The developing countries are advised to invest both in physical and humancapital. Moreover, it is admitting the fact that majority of the developing countriesare rich in labour force due to their high population. Therefore, policymakers arerequired to generate employment opportunities for the growing labour force. Theemployment opportunities could be created using domestic sources as well as

encouraging foreign direct investment. In normal circumstances, foreign directinvestment brings employment opportunities to the host countries.

• Finally efforts are required on the part of policymakers to ensure that themacroeconomic remains stable. Stable macroeconomic environment willencourage other stakeholders to play their part in the growth process. Economicinstability can damage the whole structure of the economy and will shatter thecondence of all stakeholders leading to an overall economic decline.

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Appendix 1. Variables and data sources

Appendix 2. List of sampled countriesList of countries:

• Albania;

• Algeria;

• Angola;

• Bangladesh;

• Brazil;

• Bulgaria;

• Chile;

Table AI.Variables and their

specications

Variable Data sources and specications of the variables

Dependent variable grgdpch it The growth of real per capita GDP is used as a dependent variable and

the data are obtained from Penn World Tables (PWT, 7.0). The growthrate is calculated by taking the log differences.

Independent variables

lnopen it Data on trade openness are obtained from Penn World Tables (PWT,7.0). This variable is denoted by (openk) in the database.

lnopen10 it The instrumented trade openness is constructed by regressing thecrude measure of trade openness (openk) on population. The ttedvalues are collected and are converted into ve-year averages. Such

values are in turn used as an instrument for openness. lninds it Industrial output as a ratio of GDP is used for measuring the degree of

trade openness and the relevant data are obtained from WorldDevelopment Indicators.

lninv it Gross xed capital formation is used for capturing investment anddata are collected from World Development Indicators.

lnedu it For education, gross enrolment ratio at primary, secondary andtertiary is used regardless of age group. The data are taken fromCANA database provided by Castellacci and Natera (2011). Onlinelink: https://portal.ucm.es/web/grinei/cana-data

glabf it Labour force is approximated by the growth of population ageingbetween 15 and 64 years and the data are obtained from World

development indicators. lnsdinfl it The volatility of ination rate is approximated by the standarddeviation of ination rate.

dem it This index ranges from10 (Democratic) to 10 (Autocratic) anddata are collected from CANA Database.

Pright it This index ranges from10 (Democratic) to 10 (Autocratic) anddata are collected from CANA Database.

esd it It indicates to what extent citizens enjoy freedom of political choiceand the legal right to change the laws and ofcials through free andfair elections. It ranges from 0 (no freedom) to 3 (high freedom) anddata are collected from CANA Database.

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• China;

• Colombia;

• Cote d’Ivoire;

• Dominican Republic;

• Egypt;

• EI Salvador;

• Ethiopia;

• Fiji;

• Gabon;

• Guatemala;

• Guyana;

• Honduras;

• Indonesia;• India;

• Kenya;

• Lesotho;

• Malawi;

• Malaysia;

• Mauritania;

• Mauritius;

• Mexico;

• Mongolia;

• Morocco;

• Namibia;

• Pakistan;

• Panama;

• Paraguay;

• Peru;

• Philippines;

• Romania;

• Russia;

• Senegal;

• South Africa;

• Sri Lanka;

• Sudan;

• Tanzania;

• Thailand;

• Tunisia;

• Turkey;

• Uganda;

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• Uruguay;

• Uzbekistan; and

• Zambia.

About the authorsMuhammad Tahir has completed his PhD in economics recently and has joined COMSATSInstitute of Information Technology Abbottabad as Assistant Professor of Economics. His area of specialization is international trade, economic issues of developing countries and econometricmodelling. Dr Tahir has published in refereed international journals, such as Journal of Chinese Economic and Foreign Trade Studies, Contemporary Economics and Asian Social Sciencesrecently. Muhammad Tahir is the corresponding author and can be contacted at:[email protected]

Toseef Azid has published one book and more than 50 articles in refereed international journals besides contributing numerous conference papers in different international conferencesheld in Canada, Australia, Iran, Bahrain, Indonesia, China, Malaysia, Pakistan and Saudi Arabia.

One of his papers entitled “The Role of Technology Spillovers in Convergence” won EmeraldLiterati Network 2011 Awards for Excellence.

For instructions on how to order reprints of this article, please visit our website:www.emeraldgrouppublishing.com/licensing/reprints.htmOr contact us for further details: [email protected]

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