TRADEOPENNESS AND ECONOMIC GROWTH A STUDY FROM DEVELOPED STATES Abstract The paper aims to study the realisticrelationship between trade openness and economic growth of different countries.The year we are dealing from 1980 to 2010.For this paper we have worked andmaintain secondary data. The methodologies that have been used are related topanel data. Specific test has been taken to diagnose result about thedependency of variable.
In the study our results proved that trade openness andeconomic are significant. The proxies that we used for our variable were asfollows. Trade openness is a multi-dimensional concept and hence measures ofboth trade barriers and trade volumes have been used as proxies for opennessand some other proxies of trade openness, we were used such as ImportPenetration ratio (IPR): This is a measure of trade intensity calculated astotal imports as percentage of GDP.
Data is founded from World DevelopmentIndicators (WDI). Trade share (TS) % GDP: This isdefined as total trade as percentage of GDP. Data is from world development indicator.
Export of goods and services/Export penetration ratio: its means total exportas percentage of GDP, Data obtained from world development indicator. Foreconomic growth we were used GDP annual growth as proxy. It means annualpercentage growth rate of GDP at market price on constant of local currency. Keywords: Trade Openness, EconomicGrowth, Penal Data, Import Penetration Ratio (IPR), Trade Share (TS), ExportPenetration Ratio (EPR), World Development Indicator (WDI) INTRODUCTION Researchers have employed variouseconometric tools on different objective and subjective measures of tradeopenness during the last few decades in order to ascertain a robustrelationship between trade openness and economic growth. The compelling messagefrom literature is that indeed there is positive relationship between tradeopenness and economic growth(Frankel & Romer, 1999). The amazingperformances of the Asian Tigers (Singapore, Taiwan, Hong Kong, South Korea)unrestraint the duration and the old store future of the whacking big economiesof India and Wed work significant changes in policies especially in thedeveloping world regarding foreign trade. Lovett(1993) argues that the last fifty years of experience provides sound support tothe case of free trade.
Various issues, however, still exist in the currentliterature, which need appropriate approach to handle them, in order toestablish an explicit relationship between trade openness and economic growth.. However, the existence of such issues does not indicate that the observedrelationship between trade openness and economic growth is delicate Winters).Winters (2004)) states in his study that despite methodological issues, thereis no evidence that trade liberalization is harmful for economic growth. Thebenefits associated with outward-oriented policies are visible & have beenwidely accepted by both researchers & owner makers.
In general, there isoptimism among most economic policy planners in favor of trade openness(Ruggie,1982). Reviewing the existing literature on trade and growth shows that thereis not a clear definition of trade openness. For lots of author’s tradeopenness implicitly refers to trade policy owner orientation and what they havean interest in is to evaluate the impact of trade policy owner or tradeliberalization on economic growth. For other authors however, trade openness isa more complex notion, covering not only the trade policy owner orientation ofcountries but and a set of other domestic policies (such as macroeconomicpolicies or institutional ones) which altogether make the country more or lessoutward oriented.
In such a case, what the authors have an interest in is to measure the impact of global policyowner orientation on economic growth. Finally, may adopt an even more globalview of trade openness covering not only the policy owner dimension but alsoall other non-policy factors that clearly have an impact on trade and on theoutward orientation of countries. Factors such as geography andinfrastructures, for example, do affect trade and the outward orientation ofcountries, whatever their policy owner orientation is. On the one hand,endogenous growth theory has provided a framework for a positive growth effectof trade through innovation incentives, technology diffusion and knowledgedissemination (Grossman & Helpman, 1993). However,the theoretical considerations and the empirical evidence whether tradeopenness accelerates growth is quite ambiguous(Lawrence & Weinstein, 1999).The purpose of this paper is to examine empirically, using a time serieseconometric approach, the relationship between trade openness and growth ofselected countries for the time period 1980 to 2010.
The selected countries areArgentina, Australia, Belgium, Chile, Canada, Denmark, Germany, Greece, Israel,Hungary, France, Italy, New Zealand, Norway, Portugal, Singapore, UnitedKingdom, Sweden and United States, the period before 1970 could not be includedbecause of data limitations for some of the openness indices. The paper usesmeasures of both trade volume and trade restrictions as a proxy for tradeopenness. The paper is structured as follows. The next section presents reviewsthe literature trade openness and economic growth. And the theoreticalframework of the econometric model while next one reports the results andconclusion. LITERATURE REVIEW Trade openness and economic growth isa quite debated topic within the boom and progress literature.
But, thisdifficulty is some distance from being resolved. Theoretical growth researchrecommend at quality a completely complex and ambiguous relationship betweentrade restrictions and boom. The endogenous increase literature has been numerousenough to offer a exceptional array of models in which trade restrictions canlower or increase the worldwide rate of increase(Yanikkaya, 2003).
note that iftrading companions are uneven countries within the experience that they havegot drastically one of a kind technology and endowments, even supposingfinancial integration increases the global increase fee, it may adversely havean effect on person international locations(Shamsadìni, Moghaddasi, , 2010). It’s far worthwhile to note that the theoretical growthliterature has given more attention to the relationship between alternateregulations and boom rather than the connection among exchange volumes andgrowth. Consequently, the conclusion approximately the connection betweenalternate barriers and growth can’t be immediately applied to the results ofchanges in alternate volumes on increase. Eventhough those standards, change volumes and exchange regulations, are veryclosely related, their relationship with boom can also differ substantially.This is due to the fact there are numerous other very crucial factors that havean effect on a country’s outside area, together with geographical factors, uselength, and profits. In otherwords, one must be as clear as possible about which openness degree he makesuse of and what are the precise mechanisms thru which it impacts the increase(Stulz & Williamson, 2003). we shall speak each openness measure used onthis look at later in the section within the theory of worldwide change, thestatic profits from alternate and losses from exchange restrictions wereexamined very well.
Yet, exchange principle affords little guideline as to theresults of global exchange on increase and technical development. On thecontrary, the brand new exchange theory makes it cleans that the gains fromexchange can rise up from several fundamental assets: differences incomparative advantage and economy-extensive growing returns. However,over time, the definition of openness has evolved considerably from one extremeto another. Even today it is not unambiguous as to what describes ”openness”(Stiglitz& Charlton, 2005). Kohlberg and Mertens (1989) narrated that how changeliberalization may be performed by using employing guidelines that decrease thebiases in opposition to the export area. it is even extra striking thataccording to her definition one us of a will have an open economy with the aidof using a positive exchange price policy in the direction of its export regionand on the identical time can use alternate obstacles to protect its uploadingsector. Edwards (1993) Stated in his study that “regime may be completelyliberalized and yet appoint particularly high price lists in order to encourageimport substitution” On the other side Edwards (1993); (Yanikkaya, 2003) statedin his study that he concept of openness, applied to trade policy, could besynonymous with the idea of neutrality.
Neutrality means that incentives areimpartial between saving a unit of foreign exchange through import substitutionand incomes a unit of forex through exports surely, a pretty export orientedfinancial system won’t be neutral on this experience, particularly if it shiftsincentives in choose of export production thru gadgets together with exportsubsidies. It’s also feasible for a regime to be impartial on common, and yetinterfere in particular sectors. A very good degree of exchange coverage wouldseize differences between neutral, inward oriented, and export-selling regimes. These days,the meaning of ”openness” has end up much like the belief of ”unfastenedchange”, that could be a change gadget in which all trade distortions areremoved(Kiberd, 1997). Consequently, it is critical to apprehend thisdefinition problem because diverse openness measures have extraordinarytheoretical implications for boom and distinct linkages with increase. Wong (2005)stated in his study that “the literature on the subject has not always been successful in dealing withprecise definitions of trade regimes, nor has it been able to handlesuccessfully the difficult issue of measuring the type of trade orientationfollowed by a particular country”.
A huge range of empirical studies have made useof a variety of cross-united states boom regressions to check endogenous boomtheory and the importance of change regulations (Bloom & Van Reenen, 2006). A greatdegree of a rustic’s openness could be an index that includes all of thebarriers that distort global exchange inclusive of common tariff rates andindices of non-tariff limitations. Stiglitz and Charlton (2005) explained that”trade restrictiveness index”, which in principle incorporates the effects ofboth tariffs and non-tariff barriers. However, it is not available for a largesample of countries. We divide the present openness measures into 5 classes andoverview each category one at a time in the rest of the section.
First, themost basic measure of openness is the simple trade shares, which is exportsplus imports divided by GDP. “In addition, export shares and import shares inGDP are also used and enter positively in cross-country growth regressions. Ourresults for these variables are consistent with these existing studies. Hence, webelieve that the inclusion of export and import shares in the growthregressions has been an important step towards understanding of therelationship between international trade and growth proposed by the new growthand new trade theories” Figure 1. Research Framework TRADE OPENNESS TS:Trade share (% of GDP) IPR: import Penetration ratio ERP:export penetration ratio ECONOMIC GROWTH(GDP annual growth) RESEARCH METHODOLOGY The sources of the data collection forthe selected set of the major dependent and independent variables are throughofficial websites is world development indicators (WDI).
The time period forthe study is from the year 1980 to 2010. Econometric Model In our Present study analysis, thevarious measures of economic growth as dependent variables and trade opennessas independent variable. The easy way to understand regression equation for thepanel data sets of 20 countries over 1980 to 2010 which is quite clear andhighly flexible havingdistinct slope coefficients and parameters for each period of the studyobserved our cross sectional units over time series period is as under:= 0 + 1 1 + 2 2 …. . Where,denotes the dependent variable or respond variable of the present study whichis related with economic growth and the x is used for predictor or independentvariables and the term B stand for beta. ANALYSIS AND DISCUSSIONS OF RESULTS Theresults describe the statistical analysis and discussion of our report forwhich we have used descriptive statistics, regression analysis, regressionoutcomes Housman test and Breusch and Pagan Langrangian multiplier test forrandom effects (LM) results. Table 1: Descriptive Statistics Variable obs Mean Standard deviation min Max GAG 620 2.
682735 3.126161 0 21.82889 TS 620 74.60603 70.56195 0 439.6567 IPR 620 37.
00597 33.8166 0 209.3877 EPR 620 38.22464 36.87831 0 230.269 Tableabove describe the outcomes of descriptive statistic of the study. Here we cansee that the mean value for trade share (total trade as % of GDP) is maximumwhich 74.
60602901 is and GDP annual growth has a minimum value of mean which is2.682734625. The value for the standard deviation is min for GDP annual growthwhich is 3.126160614. The min value for majority of the variables is zero whilethe maximum value is 439.6566811.
Table 2: Correlation Matrix GAG TS IPR EPR GAG 1 TS 0.3167 1 0.0000*** IPR 0.
3225 0.9966 1 0.0000*** 0.0000*** EPR 0.3051 0.9941 0.9843 1 0.0000*** 0.
0000*** 0.0000*** *, **, *** demonstrate that correlation is significant at 10, 05 and 01 % respectively Before going for the further analysisit is going obvious to check the level of correlation between the selected setof variables; the problem of multicollinearity. Table above describe the correlationmatrix between all the major variables which were selected for the presentstudy analysis.
From the above table it can be seen that the relationshipbetween trade share and GDP is positive and moderate and it is highlysignificant. IN the next variable the relationship of import with GDP ismoderate with trade is good and they show highly highly significant. Therelationship of export with GDP is low, trade is high, and with import is alsoand they all show highly significant.
After this we have selected all thevariables for the further analysis. Table3: Regression Analysis SS Df MS MS Model 659.1519 3 219.7173 219.7173 Residual 5390.
261 616 8.750424 8.750424 Total 6049.413 619 Number of obs = 620 F (3, 616) = 25.11; Prob > F = 0.0000 R-squared = 0.1090 Adj R-squared = 0.1046 Root MSE = 2.
9581 Table 4: Regression Outcome GAG Coef. Std. Err. t P>|t| 95% Conf. interval TS 0.0164 0.048181156 0.
340462754 0.733624141 -0.078215 0.11102 IPR 0.
04567 0.061771968 0.739373848 0.459961671 -0.075637 0.
16698 EPR -0.0466 0.042947049 -1.084067761 0.278758866 -0.130898 0.03778 cons.
1.54839 0.186579885 8.
298812512 6.65553E-16 1.1819817 1.9148 Inthe above table are the different results of panel data analysis for thedependent variable which TS, IPR, EPR of the currently GAG in selectedcountries.
. The results shows that among all models, the coefficient value oftrade openness and economic growth are significant at 05%. These results areshowing that all these variables have a significant impact on trade opennessand economic growth. Table 5: Fixed or Random: Housman test Results Fixed Random difference S.E.
TS -.795442 -.0088698 -.
0706744 .1937878 IPR .1684274 .0877418 .0806856 .1919227 EPR .0282154 -.0360172 .
0642326 .1977171 b = consistent under Ho and Ha;obtained from xtreg B = inconsistent under Ha, efficientunder Ho; obtained from xtreg Test: Ho: difference in coefficients notsystematic Chi2 (3) =(b-B)'(V_b-V_B)^(-1)(b-B) = 0.65 Prob>chi2 = 0.
8849 Housman test Results for fixed orrandom effect model shows that the value 0.8849 is not less than 0.05 whichconcludes that we should use the (random effect model). Meaning in the model wewill control the effects on variables.
Table6: Breusch and Pagan Lagrangian Multiplier Test For Random Effects (LM): Var Sd Sqrt(var) GAG 9.77288 3.126161 E 8.02764 2.833309 U .
9215856 0.9599925 Test: Var (u) = 0 chibar2 (01) = 59.36Prob > chibar2 = 0.0000 According to result we acceptalternative hypothesis as the entities are not zero. The probability outcome is0.000 so it means there 99% level of confidence that are dependent variablesare highly affected by independent variable.
CONCLUSION From the discussion it could beconcluded that trade openness is effected by other factors and is notindependent in nature. The factors that have major contribution in tradeopenness are ipr and epr, we get no confirmation that openness is straight andvigorously linked with economic growth in the long run. We further evaluatevarious individual measures of openness, namely, current openness, realopenness, the fraction. It turnsout that our main finding is strong to these alternative measures of opennessand none of them is robustly correlated with long-run economic growth. The lackof statistically robust association between trade openness and long-run growthsuggest that policymakers should not follow trade-openness-enhancing policiesbased purely on growth objectives. The data evidence also indicates thateconomic institutions and macroeconomic uncertainties related to inflation andgovernment consumption are key determinants of long-run economic growth. Afailure to go after sound and steady fiscal and monetary policies and to put upgood institutions is detrimental to long-term growth prospects.
Employing bothcurrent openness and real openness as a dependent variable, we estimate thismodel by OLS. The link between trade openness and economic growth has beenproven to be difficult in analyzing since they exist many studies thatcontradict each other regarding the positive or negative effect of tradeopenness on economic growth. However, the majority of these studies advocatepositive impact of openness in economic growth. Consideringthat this is the first attempt of establishing a causal linkage between tradeand GDP per capita growth for this set of countries, the findings are crucialfor the current discourse for this region as they underpin the importance ofregional and international trade related development.
In spite ofthe limited size of the sample, the model performs well for this analysis.However we contend that our study provide only a promising step towards developinga more comprehensive empirical research which will capture more variablestypical for this issue and also by extending the size of the sample.