ROMANIA-EU ACTUAL AND POTENTIAL TRADE

Transcription

1 Annals of the University of Petro ani, Economics, 5 (2005), ROMANIA-EU ACTUAL AND POTENTIAL TRADE ANNA FERRAGINA, GIORGIA GIOVANNETTI, FRANCESCO PASTORE * ABSTRACT: This is a companion paper to Ferragina, Giovannetti and Pastore (2005) and focuses on Romania-EU actual and potential trade. The Romanian trade potential with five EU members (France, Germany, Italy, Spain and UK) is computed using an out-ofsample methodology for the period The coefficients are taken from panel estimators of the gravity equation relative to intra-eu15 trade. The analysis suggests the existence of an important unexploited trade potential with Romania, which, nonetheless, is not different in size from that of other CEECs. The potential to actual trade ratio ranges from 2.2 to 2.7 and is sharply declining, suggesting that further dramatic economic integration is to be expected in the near future. # KEY WORDS: Romania; Europe Agreements; Eastward Enlargement; Gravity Equation; Trade Potential 1. INTRODUCTION In the last decade, gravity models have been extensively used to forecast potential bilateral trade relations and integration effects between EU (or OECD) countries and the former CMEA members 1. The aim of this paper is to compare the degree of integration of Romania with a sample of EU countries (France, Germany, * Corresponding author, ISSM-CNR, Italy University of Florence, Department of Economics, and Italian Foreign Trade Commission, Italy Ass.Prof.Ph.D., Second University of Napoli, Department of Law and Economics, Italy # Previous versions of Ferragina, Giovannetti and Pastore (2005) have been presented at the ETSG, University of Nottingham; at a CNR Study Group on International Trade, Università Commerciale Luigi Bocconi; and in a seminar held at the Romanian Academy of Science in We thank Paolo Epifani, Rodolfo Helg, Lelio Iapadre, Paolo Malanima, Mariana Nicolae, Lucia Tajoli and one anonymous referee for useful comments. 1 Section two reports the results of the existing literature (see also Brenton and Gros, 1997).

2 118 Ferragina, A.; Giovannetti, G.; Pastore, F. Italy, Spain, UK), indirectly providing an assessment of the relative success of the Romanian Europe Agreements (REA), also in view of the coming EU accession of the country 2. This study uses gravity analysis, which is the best alternative when intertemporal extrapolation of trade patterns is not feasible, as it is the case of CEECs, due to their past economic isolation, distorted pricing structures and recent transition from a planned to a market economy. A panel data specification of the gravity model and an out-of-sample methodology have been adopted to estimate trade potential. In other words, the parameters extracted from a gravity equation of intra-eu bilateral trade flows are used to predict trade between Romania and several EU members. This analysis aims at answering the following main questions: 1) What degree of trade integration could have been achieved if the trade elasticity with respect to economic and geographic variables (relative mass, physical distance, common language, common land border, colony links) had been like those achieved in intra-eu trade? 2) Has the REA induced a reduction of the gap between potential and actual trade via trade creation and diversion activated by the liberalisation process? 3) How much additional trade could be created if integration would be pushed further (trade enhancing effect)? From an econometric point of view, this study differs from previous works on CEECs, which have hardly used panel analysis, and even more rarely coupled panel analysis with out-of-sample methods 3. The analysis provides evidence of substantial unexploited trade, which is in contrast with previous results relative to EU trade with CEECs: many studies predicted that trade potential was almost fully exploited already in The differences between our and previous results might depend on three factors. This study a) focuses on intra-eu trade, rather than on trade with a larger, but less homogeneous group of countries, as a reference to estimate the elasticity of trade 2 The Europe Agreements (EAs) were initiated by the EU with each CEEC separately. The first agreements with Poland, Hungary and Czechoslovakia were signed in December 1991 and came into force only in On 1 st February 1993, similar agreements were signed with Bulgaria, Romania as well as the newly established countries of the Czech Republic and Slovakia. They came into force in In 1998, EAs were implemented with the three Baltic States, followed by Slovenia on 1st February The EAs were aimed at fostering trade integration, but also the political dialogue and cultural and economic cooperation between the partners, while providing a basic outline for the gradual EU accession of CEECs. Over the period before the agreements came into force, Interim Agreements provided for an anticipated and temporary application of trade provisions. Their aim was to establish a free trade area for industrial goods for ten years on a reciprocal, but asymmetric basis: the EU had to remove its trade barriers more quickly than the CEECs. This led to the total removal of all tariff barriers on industrial products from the EU on 1 st January However, for some sensitive industrial sectors a special discipline was created, in particular for textiles, iron and steel, car industry (only for Poland) and a much more gradual liberalization was applied to agricultural goods and fisheries. 3 To our knowledge, only Baldwin (1994), Gros and Gonciarz (1996), Mathyas (1997) and Egger (2000; and 2002) use panel analysis, while Gros and Gonciarz (1996) use both panel analysis and an out-of-sample method.

3 Romania-Eu Actual and Potential Trade 119 determinants; b) applies an out-of-sample method to compute potential trade; c) concentrates on a later period, , when GDP in CEECs in general and in Romania, in particular, was rapidly increasing. The results are remarkably stable across different specifications and estimation methods. The work is organised as follows. Section 2 contains a survey of the literature. Section 3 discusses the methodology adopted and the results of the gravity model. Section 4 provides measures of the ratio between potential and actual trade. Some concluding remarks follow. 2. A SURVEY Gravity models have been widely used over the past decade or so to evaluate EU-CEE trade potential, and to compare it with the actual level of trade. More specifically, gravity equations have been estimated relative to the already integrated EU15 to obtain the coefficients of the main determinants of bilateral trade, namely national income and population size of the two countries involved, distance, common land border and common language. These coefficients have been used in similar equations, but with variables relative to EU-CEECs, in order to assess trade potential. The aim of these exercises has been to determine whether the integration process was already completed before accession, or whether one can expect further trade integration, which may continue to affect the labour markets in the two areas concerned. The results of such exercises available in the literature are mixed, and they depend closely on the period considered, specification and estimator, as well as on the computation method used to calculate trade potential. Wang and Winters (1992) find that East-East trade was large in 1985, while East-West trade was only a fraction of what it would have been in an integrated Europe. Hamilton and Winters (1992) adopt a similar approach, finding that trade within the former Soviet Union and the Eastern Europe bloc (SUEE) was static or falling, while trade with Western Europe may increase by up to five times. Baldwin (1994) finds that potential EU12-CEE exports and imports are twice the actual 1989 exports and imports. All the studies which have used data on the early transition period in order to estimate trade potential support a different conclusion. Most of them suggest that a level of integration between Eastern and Western countries which is high and above the potential level has long since been reached. This indicates that adjustment is complete and that there is no need for special protection in Western countries (Gros and Gonciarz, 1996; Brenton and Di Mauro, 1999; Nilsson, 2000). For instance, Gros and Gonciarz (1996) correct Baldwins estimates on the grounds that he used a GDP which was overvalued because it was calculated on pre-transition data (the per capita GDP used by Baldwin was much higher than the 1992 GDP for CEECs). Combining the parameters from Baldwin (1994) with the 1992 data on GDP, Gros and Gonciarz end up with a downward revision of Baldwins projections of CEEC-EU trade, and their results suggest that the adjustment is complete.

4 120 Ferragina, A.; Giovannetti, G.; Pastore, F. Two recent studies on trade integration measured by gravity models (Egger, 2000; 2002) have cast doubt on the results of the above-cited literature. They make 3 main criticisms: 1. most of these results are based on cross-section gravity models which are mis-specified because they do not take account of exporter and importer effects, while only few authors make use of panel econometrics; 2. those authors who do use panel analysis to compute potential trade adopt a random effect model (the exception is Egger) which may be affected by the problem of correlation between the explanatory variables and the unobserved time invariant effects; 3. most analyses obtain information on trade potentials using the in-sample prediction approach; that is, the residuals of the estimated equation are interpreted as the difference between potential and actual bilateral trade relations, but this is in contrast with the fact that, in the case of proper specification, the estimators are consistent and efficient and therefore should exhibit white-noise residuals, rather than identifying large systematic differences between observed and in-sample predicted values among country groups. 3. METHODOLOGY This contribution combines a panel data analysis of intra-eu15 trade with an out-of-sample calculation of potential EU-Romania trade relative to the period In other words, we estimate the parameters of a gravity model for intra-eu15 trade 4 and then plug them into the regression of trade between Romania and her main European trade partners (Italy, Germany, France, UK, and Spain) to obtain potential trade. This potential or normal trade is then compared to actual trade volumes to assess the dimension of trade potential not exploited in the short run. As Ferragina, Giovannetti and Pastore (2005) discuss in more detail, the following specification has been used to analyse the determinants of intra-eu15 trade. X ijt 5 D ij i 6 1 POP CLB ij it 7 2 GDPPC CL ij ijt it 3 POP jt 4 GDPPC jt (1) where: i are the countries of origin, j are the destination countries and t = is the period under examination 5 ; X ij are exports of country i to country j in real terms; is the bilateral constant; POP it and POP jt are the populations at time t of country i and j respectively; GDPPC it and GDPPC jt are per capita GDP of country i and j at time t in real terms; D ij is the geographical distance in Km between the capital city of country i and of country j; CLB is a dummy equal to one, if the two countries share a common land border and/or have ex-colony links and zero otherwise. CL is a dummy 4 We include 13 EU countries in the empirical analysis, since for Belgium and Luxembourg data were missing for some years. 5 Notice that while the gravity equation has been estimated over the period , potential trade is computed over the years This is because some observations for the year 2002 were missing. They have been substituted by average values relative to the previous three years.

5 Romania-Eu Actual and Potential Trade 121 for common language taking a value of one if the trade partners speak the same 2 language and zero otherwise and IID 0, All the variables in our equation, ijt except for the dummies, are in natural logarithms and therefore the estimated parameters can be interpreted as elasticities. According to Feenstra et al (2001, p.432) the constant term should represent the impact of world income on bilateral trade within the sample. Bilateral exports are expected to be positively influenced by: a) the importer demand and exporter supply, as proxied by their population (POP) and per capita income (GDPPC), respectively. A higher per capita income means a higher import demand and export supply, as it is a proxy of the economic development of the country. The effect of population is more ambiguous: a larger population means a large domestic market, a higher degree of self-sufficiency and less need to trade. At the same time, a large population entails a deeper labour division and scale economies in production which are generally associated in the theoretical models with a larger need for trading. Therefore, the effects of this variable are ambivalent. b) dummies such as sharing a land or a sea border, ex-colony links, common language capture the geographical closeness, the better information, the lower cultural differences, the lower home bias and research and communication costs associated with proximity (familiarity with custom regime, institutions, legal system). Conversely, bilateral exports are expected to be negatively influenced by: c) distance which can be expressed as geographical distance, but also by the surface of hosts markets, the level of trade costs, the presence of a home bias effect and of time and search costs. As detailed in Ferragina, Giovannetti and Pastore (2005, Table 2), all the available test statistics support the adoption of a REM with exporting and importing countries and years dummies. This model has consistent coefficients like the fixedeffect model, while being more efficient. In the preferred specification, the variables have the expected sign and are highly significant. The explanatory power of the model is also high. The statistical significance of distance in explaining the trade intensity of EU countries suggests that transport costs still have an important impact on the export performance. The estimated parameter for distance is stable across different specification and is in line with that typically found in earlier studies (- 0,7). Also the coefficients are reasonable. Similar to previous studies, the coefficient for the per capita GDP of the exporting country is lower than that of the importing country. This is to be expected, considering that exports are more related to the income level of the importing, rather than of the exporting country. The coefficient of the per capita GDP of the importing country is slightly greater than 1, which is what one would expect if the propensity to import from EU countries was constant over time and the share of EU over total imports was constant. 4. ROMANIA-EU TRADE POTENTIAL A short discussion of the recent evolution of Romania-EU trade patterns seems useful to put the discussion about trade potential into context. Romania is not much

6 122 Ferragina, A.; Giovannetti, G.; Pastore, F. different under this respect from other CEE countries. Asymmetric trade with the EU afflicts CEECs. In 2003 exports to CEECs as a share of total EU exports had become more than 12% from only 5% in 1990 and, for imports, the share was above 10%. The average share of exports and imports that CEECs devote to EU is more than 60 and 55% respectively. In few years exports to the EU as a share of total exports have become on average more than 60% of CEECs total exports (according to Eurostat they range from a minimum of 48% for Lithuania to a maximum of 70% for Poland with some impressive increases over the period from 4 to 70% in the case of Estonia, from 6 to 55% in the case of Bulgaria from 5 to 48% in the case of Lithuania). The average share was only 30% in Imports are on average more than 55%, starting from an average of 32% in 1990, with some peaks like Poland and the Czech Republic (more than 60%), followed by Romania (57%). As already noted, to check whether Romania-EU trade approached its potential level in the period under consideration, we apply the estimated coefficients from the gravity equation of intra-ue15 trade to the same specification for CEE-EU trade flows. These parameters are used as a benchmark to estimate the potential integration that CEECs and Romania, in particular, might obtain if the elasticity of trade determinants were the same as those observed in the case of intra-eu15 trade. Trade volumes are then considered normal trade, which could be obtained with a deeper integration according to the predictions of the gravity model. We applied the same procedure to EU-CEE trade. Figure 1 contains the trends in the trade ratio between potential trade (i.e. the normal trade estimated in the way described above) and actual trade between each of five EU main trade partners (France, Germany, Italy, Spain and UK) and Romania over the period A ratio of one suggests that potential trade equals actual trade. The higher is the ratio, the higher is the gap that has to be filled and therefore the possibility to create new trade. A decreasing (increasing) trend of this ratio over time suggests that trade is increasing (decreasing) and tends to approach its potential level. It is worth mentioning that the results contained in Figure 1 are robust to different estimation methods, with only some small variations. The analysis suggests the existence of an important unexploited trade potential with Romania. The potential to actual trade ratio ranges from 2.2 to 2.7 from one country to the other, suggesting that further dramatic economic integration is to be expected in the near future. This is also confirmed by the clear downward trend of the potential to actual trade ratio. The decline is especially clear in the case of trade with Italy and Germany, which already had the lowest ratio at the beginning of the period considered. This suggests in turn that there is no catching up in the trade relationships between Romania and EU countries, but rather a strengthening of existing trade links. The existence of large unexploited trade potential is typical also of other CEECs. Ferragina, Giovannetti and Pastore (2005) report similar results for other nine CEECs. The trend is marked by a large decline of the ratio in all cases: they start from a ratio of around 2 and further close the gap (especially in the case of countries which started from the worst positions such as the Baltic Republics and Bulgaria, which show

7 Romania-Eu Actual and Potential Trade 123 R om ania-eu : R atio of potential to actual trade (1995-'02) France G erm an y Italy Sp ai n UK Rom an ia E xpo rt Im po rt G raphs by eu Figure 1. Ratio of potential to actual trade ( ) the most dynamic trend). The trade potential between EU and CEECs is quite close to being exploited in 2002: the ratio is between 1 and 2.5 (for instance in the case of Italy is between 2.2 and 2.6 for exports and 1.7 and 2.4 for imports). This suggests a tendency to close the gap. However, the gap should not be underrated. Without external positive shocks, the analysis carried out here suggests that much time is still necessary to Romania to close the gap. In fact, assuming a constant population of the countries considered and taking for realistic the World Bank forecast of a 5% rate of per capita GDP growth for Romania over the period , the EU export to Romania will increase by about 6.4 and the EU imports from Romania by 5.3 per year. Spain and the UK should perform slightly well, essentially because of their faster GDP growth rate. This means that even if Romania grows at the same rate also in the years after 1997, ten years are still insufficient to close the gap. The projected/actual ratio of imports systematically exceeds that of exports. Only in the case of Romania-Spain trade, the two lines cross each other. This result is consistent with the EU trade surpluses with the CEECs. It indicates also that there is wide scope for an increase in imports more than in exports and might also suggest that the CEECs within the EAs have not benefited of a total and preferential opening for their exports to the EU. 5. CONCLUDING REMARKS The results of our gravity analysis confirm that there is still a large trade potential between EU and Romania, though the trend is towards a dramatic decline. If

8 124 Ferragina, A.; Giovannetti, G.; Pastore, F. the World Bank optimistic predictions regarding Romanias economic growth will come true, the catching up will happen in not less than ten years. Considering also the low growth rate of the EU, a decline in Romanian growth is bound to cause also a decline in economic integration with the EU. These results, in turn, are worrisome if one thinks of the possible further adjustment process, which might take place in the labour market of EU members and of associate countries in the next few years. The result that trade potential is still not exhausted is in line with Baldwin, but not with other studies. Gros and Gonciarz (1996), for instance, suggest that the trade potential had been already reached in But they base their analysis on a very negative period for the CEECs, unlike Baldwin. In the first half of the 1990s, the CEECs were in the descending part of the J-curve of transition. GDP was much lower than the current level suggesting that potential had already been exploited. Baldwin considers the much higher income level of the pre-transition period and obtains results quite similar to ours. In all CEECs, GDP almost doubled between 1992 and 2002, which translates into a progressive reduction in the potential and a trend towards convergence with actual trade. REFERENCES: [1]. Baldwin, R.E. - Towards an Integrated Europe, Centre for Economic Policy Research, London, 1994 [2]. Brenton, P.; Gros, D. - Trade reorientation and recovery in transition economies, Oxford Review of Economic Policy, 1997, vol. 13, n. 2, [3]. Brenton, P.; Di Mauro, F. - The potential magnitude and impact of FDI flows to CEECs, Journal of Economic Integration, 1999, Vol. 14, n. 1, March, [4]. Egger, P. - A note on the proper econometric specification of the gravity equation, Economic Letters, 2000, 66, [5]. Egger, P. - An econometric view on estimation of gravity models and the calculation of trade potential, The World Economy, 2002, 25, 2, [6]. Feenstra, R.C.; Markusen, J.R.; Rose, A.K. - Using the gravity equation to differentiate among alternative theories of trade, Canadian Journal of Economics, 2001, Vol. 34, n. 2, p [7]. Ferragina, A.M.; Giovanetti, G.; Pastore, F. - EU Actual and Potential Trade with Mediterranean and Central and Eastern European Countries. A Gravity Study, ICE, mimeo, 2005 [8]. Gros, D.; Gonciarz, A. - A note on the trade potential of Central and Eastern Europe, European Journal of Political Economy, 1996, 12, [9]. Hamilton, C.B.; Winters, A.L. - Opening Up International Trade with Eastern Europe, Economic Policy, 1992, 14, [10]. Mathyas, L. - Proper econometric specification of the gravity model, The World Economy, 1997, vol. 20, [11]. Nilsson, L. - Trade integration and the EU economic membership criteria, European Journal of Political Economy, 2000, 16, [12]. Wang, Z.; Winters, A.L. - The Trading Potential of Eastern Europe, Journal of Economic Integration, 1992, 7, [13]. Eurostat - Statistics in focus, various issues, 2003