Trade Liberalization and Employment Effects in Ukraine

Christev, Atanas; Kupets, Olga; Lehmann, Hartmut Working Paper Trade Liberalization and Employment Effects in Ukraine Quaderni - Working Paper DSE, No. 552 Provided in Cooperation with: University of Bologna, Department of Economics Suggested Citation: Christev, Atanas; Kupets, Olga; Lehmann, Hartmut (2005) : Trade Liberalization and Employment Effects in Ukraine, Quaderni - Working Paper DSE, No. 552, Alma Mater Studiorum - Università di Bologna, Dipartimento di Scienze Economiche (DSE), Bologna, https://doi.org/10.6092/unibo/amsacta/4737 This Version is available at: https://hdl.handle.net/10419/159393 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc/3.0/ Trade Liberalization and Employment Effects in Ukraine Atanas Christev Department of Economics and CERT, Heriot-Watt University, Edinburgh; and IZA Bonn Olga Kupets Department of Economics, National University-Kiev Mohyla Academy, Ukraine; and IZA, Bonn Hartmut Lehmann Department of Economics, University of Bologna; IZA Bonn; CERT, Heriot-Watt University, Edinburgh; and Labor Group, EROC, Kiev School of Economics First Draft: June 2003 This Version: October 2005 ___________________ We would like to thank John Haltiwanger and Peter Wright and the participants at the GEP Conference, Nottingham, June 2003, and the IZA-Upjohn-WDI conference on “Microeconomic Aspects of Labor Reallocation”, Kalamazoo, Michigan, August 2003, for valuable comments and insightful discussions. This paper is partially financed by the CERT-RWI project “Analysis of Labor Markets in Transition Countries Using Large Micro Data Sets.” Kupets is grateful to the “INTAS” program for facilitating her stay in Edinburgh, during which this first version of the paper took shape. Abstract This paper addresses the important issue of the effects of trade liberalization on labor market job flows. It studies the case of Ukraine where we view the sudden openness of the economy to trade as a quasi-natural experiment. We use disaggregated data on manufacturing industries and customs data on trade flows taking account of shifting trade patterns after the disintegration of CMEA trade regime. We provide some first evidence that 3-digit NACE sector job flows are predominantly driven by idiosyncratic factors within industries. Other things equal, there is increased labor shedding as larger non-state share in industry relates to less job creation and more job destruction. Trade openness does affect job flows in Ukrainian manufacturing disproportionately according to trade orientation. We find that while trade with CIS decreases job destruction, trade with the EU increases excess reallocation mainly through job creation. JEL Classification Numbers: E24, F14, J63, P23. Key Words: Job Creation; Job Destruction; Ukraine; Trade Flows and Trade Liberalization 1 2 I. Introduction The flexibility of labor markets is an important feature of well-functioning market economies. Davis and Haltiwanger (1999, 1992) and Baldwin, Dunne and Haltiwanger (1998) report that in the U.S. and in Canada roughly one in every ten jobs is created and one in every ten jobs is destroyed each year. Flexibility of the labor market is important because it permits the rapid reallocation of resources to the most efficient uses and thus it may be vital for economic growth. Labor reallocation is to a large extent driven by job creation and job destruction. Businesses react continuously to shocks by changing output and input levels at a high pace leading to substantial destruction and creation of jobs at high frequencies. Job creation and job destruction are thus intimately linked to productivity growth. Firms (sectors) that engage in restructuring destroy low productivity jobs and create high productivity ones, leading to large job turnover, an increase in labor productivity and better general performance. A high degree of job reallocation, while beneficial for an economy as a whole, can, however, have large negative effects for those workers who are displaced from their jobs. There is ample evidence, in particular from Anglo-Saxon labor markets, that the average displaced worker faces prolonged non-employment spells and longterm earnings losses (see e.g. Kuhn (2002) and Jacobson, Lalonde and Sullivan (1993)). Labor reallocation, brought on by the reallocation of jobs across firms and sectors, is an especially pertinent issue in transition economies. The reallocation of labor from inefficient firms (usually non-restructured state and privatized firms) to efficient ones (usually new private and restructured state and privatized firms) increases overall 3 labor productivity and enhances efficiency during the transition from plan to market (Blanchard (1997)). How job creation and destruction have contributed to this reallocation process across businesses and sectors has been the subject of a growing literature on job gross flows in Central Europe and the CIS, which is summarized in Haltiwanger, Lehmann and Terrell (2003). Like in mature capitalist economies, the welfare gains generated by the ongoing process of labor reallocation are, however, not distributed evenly. Many low-skilled and older workers who are displaced from their jobs incur large costs above all in the form of long spells of non-employment, as Lehmann, Philips and Wadsworth (2005) and Lehmann, Pignatti and Wadsworth (2005) have shown for Estonia and Ukraine where data on displacement are available. Beneficial and detrimental outcomes of labor reallocation induced by changing trade patterns have been widely discussed in the literature on the impact of globalization on Western domestic labor markets. However, there are only a few papers that look at how trade affects job creation and job destruction directly. While Klein, Schuh and Triest (2003) estimate the effects of real exchange rates on job creation and job destruction for the US manufacturing industry, Lewinsohn (1999) investigates the influence of trade liberalization on job creation and destruction in Chile. With respect to the impact of shifting trade patterns on domestic labor markets, transition economies provide something of a quasi-natural experiment. Under central planning the state had a foreign trade monopoly. Firms were not in principle acting autonomously in export markets. At the same time, enterprises were sheltered from import competition. Firms in most centrally planned economies were completely 4 isolated from world markets.1 With the start of transition the foreign trade state monopoly was abolished and trade was liberalized. As a consequence of trade liberalization, we see a strong re-orientation of trade away from the defunct CMEA trade area to Western markets, in particular to the EU. In addition, trade liberalization implies that many firms engage autonomously in fast growing Western export markets. The same firms or other firms have to deal themselves with import competition. Firms’ engagement in export markets and the abrupt exposure to import competition imply that some sectors of industry in transition countries open up to the world economy over a short time horizon at a very rapid pace. Industrial sectors in mature capitalist economies have opened up much more gradually over the eighties and nineties, making it difficult to isolate the effect of changing trade patterns on employment adjustment in domestic labor markets. We try to take advantage of the rapid opening up of one transition country, Ukraine. As we shall show in the next section, Ukrainian trade flows to and from areas outside the Commonwealth of Independent States (CIS) have increased dramatically over the last decade. We exploit this dramatic increase and investigate whether and how trade liberalization causally affects job creation and destruction in three-digit industrial sectors. The sectoral gross job flows are based on establishmentlevel data from the Ukrainian registry data for the years 1993-2000. In an earlier study, two of the authors used Ukrainian establishment level data from the Amadeus data base to look at the impact of trade liberalization on job gross flows at the establishment level in the late nineties (Konings, Kupets and Lehmann (2003)). The 1 In Poland and Hungary, economic reforms of the central planning system gave some autonomy to state-owned enterprises in the eighties. Some of the Hungarian and Polish enterprises did have trade relationships with Western firms already in the eighties as a consequence of these reforms (see e.g. Repkine and Walsh (1999) who study Polish enterprises). In the Soviet Union, on the other hand, where the Classical Planning System was less affected by economic reform throughout the Communist 5 present paper is complementary insofar as it extends the analysis to the sectoral level and augments the time dimension to nearly the entire last decade. With data that have a substantial time series dimension we hope to better control for cyclical and idiosyncratic shocks. Using a generalized method of moments (GMM) estimator we thus might be able to better isolate the effect of trade liberalization on gross job flows. The following section gives a short account of the developments of the industrial sector in Ukraine over the nineties and looks at the evolution of trade flows over the same period. In the subsequent section we describe our data sources, briefly review the job flow measures that we employ in the analysis and sketch the construction of indices of trade openness at the sector level. This is followed by a discussion of the raw correlations of the trends of job flows and of trade orientation of sectors. Section four develops the estimation framework and reports results from our GMM estimations. The final section offers some conclusions. II. Ukrainian Industry and Trade in the Nineties Reform efforts to transform the Ukrainian economy have been either nonexistent or very inconsistent in the nineties of the last century, which is the analyzed period in this paper. The capture of the state by a few oligarchic groups, the exclusion of the majority of the population from the decision making process and weak property rights resulted in stagnancy, corruption and a collapse in output for most of the decade (Aslund, 2002). In the first half of the nineties runaway inflation, bordering for a prolonged period on hyperinflation, was one of the manifestations of the poor economic policies that brought Ukraine on the brink of collapse. Only towards the regime, the foreign trade monopoly of the state was not touched until the implosion of the centrally planned economy. 6 end of the nineties were serious reforms undertaken that loosened the grip of the oligarchs and that spurned robust and unabated growth for the first time since the collapse of the Soviet Union. Figure 1, which shows the trends of production and employment, makes the point quite forcefully that the nineties were a lost decade for Ukraine. After an extremely sharp contraction of industrial output in 1993 (the year of the hyperinflation) we see a five-year trough until some recovery in 1999 and 2000 occurs. By the end of the decade industrial output had “recovered” to only about 60% of the pre-transition level, which points to a dismal performance in comparison with all those Central and East European transition countries that have not been affected by armed conflict. It is also striking that employment shows a steady decline hinting at substantial labor shedding throughout the period. This labor shedding was driven by large job destruction as Table 1 makes clear. Throughout the decade we see job destruction rates at levels that are observed in Western economies with rather flexible labor markets (Davis and Haltiwanger (1999)), while job creation rates are small in international perspective. What is interesting, though, is that job creation does take place at all during this period and that it does gather pace in 1999 and 2000 when industrial output grows. Despite the enormous fall in industrial output and the cumulative employment contraction of roughly 40%, jobs are continuously reallocated at an increasing pace as the secular rise of the excess job reallocation demonstrates. How much trade contributes to this reallocation is the focus of the paper. A first cursory look at Ukrainian trade flows (Figures 2 and 3) yields two striking facts. First, the above-mentioned re-orientation from CIS to Western economies that one 7 generally observes for transition countries is clearly revealed by the shifting trade patterns in Ukraine. Both exports and imports are re-directed away from the CIS to the EU and the rest of the world (ROW represents all those areas that are not in the EU and in the CIS). Second, we see a spectacular rise of EU and ROW trade flows throughout the decade, while CIS trade flows decline in the second half of the nineties. This large increase in trade flows will be exploited in the analysis that follows. III. The Data The empirical analysis is based on industry-level data for a panel of 95 threedigit NACE mining and manufacturing industries in Ukraine over the 1994-2000 period, containing information from three diverse sources. The panel is restricted to the subset of Ukrainian industries for which data on job and trade flows are available over the whole period. In unreported results, we have used bootstrap techniques to perform tests of the null hypothesis that gross job flows of all firms (including entry and exit) and gross job flows of continuous firms are determined by the same data generation process. In all cases over the sample period, we were not able to reject the null hypothesis, which implies that entry and exit do not influence our results. Annual sectoral data on job creation, destruction and reallocation are constructed from the establishment-level registry data set from 1993 to 2000 provided by the State Statistical Committee of Ukraine (“Derzhkomstat”).2 Although the initial registry data also cover establishments from some non-industrial sectors (4.84% of the initial sample), we restrict our analysis of job flows to firms in mining, manufacturing 14 destruction. Trade theory provides little explanation as to the links, causes and effects of adjustment costs associated with job and worker reallocation. As discussed earlier, previous work has generally focused on the effects of trade on net employment change and neglected other aspects of this process, namely gross job creation and destruction (Gourinchas, 1999 and Klein, et. al. 2003a). We expect that job destruction will be both more volatile and larger than job creation following trade liberalization in Ukraine. Job destruction caused by increased trade flows may exacerbate unemployment if workers do not reallocate to new jobs or exit the labor force (Lehmann, et al., 2005). Job creation, on the other hand, may be constrained by the lower competitiveness of Ukrainian industries, and especially those industries that are initially either closed to trade with the EU or ROW or that have maintained strong trading ties to former CMEA area (CIS) countries. Open trade policies and flexible exchange rates increase excess job reallocation and stimulate growth as shown by Gourinchas (1999) and Greenway, et. al. (2002). The latter authors point also to the importance of the existence of a credible counterfactual in evaluating the effects of trade liberalization on growth. In the sample period we observe such counterfactuals since while some industries rapidly opened up to trade as transition progresses, others remained closed throughout the period (Figure 4). In addition, we expect that job flows are affected differently by the dispersion of trade openness across industries and trading areas. Higher openness towards the EU, for example, is more likely to increase job creation and decrease job destruction, which is dominant in the initial stage of transition, and thus affects excess job reallocation. Real appreciation of the exchange rate may increase job destruction and decrease job creation. Finally, we anticipate that the privatization processes and ownership 8 Where possible, in addition to predetermined variables, we use the lagged differences and levels of 15 structure in industries with different trade exposure will influence job creation and job destruction propitiously. While we consider trade liberalization in its various realizations an important determinant of job reallocation, we anticipate that industry-specific shocks will dominate the determination of gross job flows in the studied period. Our first results confirm this as the four sectoral job flow measures appear to be mainly driven by the lagged values of job creation and destruction. Net employment growth is consistently dominated by job destruction, while excess job reallocation is propelled by job creation. This finding indicates that idiosyncratic factors within industries explain most of the variation of costly employment adjustment in the Ukrainian manufacturing sectors which is in line with the evidence found in Davis, et. al. (1996). In addition, ownership structure seems to be strongly correlated with job flows, as revealed by the significant and large coefficients on the variable PRIV SHARE in both Tables 5 and 6. A larger private share in an industry is associated with less job creation and more job destruction resulting in an increased labor shedding. There is also weak evidence that an industry with a larger private share exhibits less excess job reallocation. In our interpretation of the coefficients on PRIV SHARE we are careful not to suggest a causal effect of ownership structure of industries on employment adjustment since the variable we have constructed PRIV SHARE does not capture the evolving ownership distribution in industrial sectors over time. It is instead an end- of-period variable controlling for the cumulative ownership changes that have occurred in the industrial sectors in Ukraine over the intervening years. Does trade liberalization affect sectoral job flows in Ukrainian manufacturing? In Table 5, we report a significant positive coefficient on the lagged openness index real industrial output as instruments in our regressions. 16 for EU trade in the job creation and excess job reallocation regressions. This asserts that as industries become more exposed to trade and competition in EU markets over time, they reallocate jobs faster. On the other hand, sectors engaging in more trade with the rest of the world show increased job destruction rates. To account for different productivity and relative price shocks over time, we interact proxies for the industry-specific real exchange rate with the openness indices and report the results in Table 6. While it is more difficult to disentangle the effects of trade on job flows using these new variables, the results suggest that openness and an appreciation of the real exchange rate affect job creation and job destruction disproportionately due to trade by country of origin and destination. The estimates of Table 6 show a small positive effect on increased job destruction rates for sectors trading with the rest of the world. Our data indicate that for the average sector a real depreciation within the CIS trading area is reflected by a real appreciation of relative prices towards the EU and ROW and vice versa. We, therefore, establish that sectors with more trade to CIS countries have declining job destruction rates primarily because of a depreciation of the real exchange rate within the ruble zone over the sample period. The positive effect of increased openness to the EU trading area does not disappear when the index is interacted with the real exchange rate. We take this result as evidence that increased restructuring and job reallocation are brought about by stiffer competition in EU markets. Finally, net employment growth occurs only in sectors that maintain strong trade ties in the CIS area. 17 VI. Conclusions This paper addresses an important issue: the effects of trade liberalization on gross job flows, an area that has been relatively neglected in the trade liberalization as well as in the job flows literature. It studies the labor market of Ukraine where we view the sudden opening up of the economy to world markets as a quasi-natural experiment. We provide some evidence that 3-digit NACE sector job flows in Ukrainian manufacturing are mainly driven by idiosyncratic factors within industries. Trade is a factor of some but of minor importance in the determination of gross job flows, a finding well established in Western studies. 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(2005). “The Incidence and Cost of Job Loss in a Transition Economy: Displaced Workers in Estonia, 1989-1999”, Journal of Comparative Economics, Vol.33 (1), pp.59-87. 20 Lehmann, H., Pignatti, N. and Wadsworth, J. (2005). “The Incidence and Cost of Job Loss in the Ukrainian Labor Market, IZA Discussion Paper No. 1770, Bonn: September. Levinsohn, J. (1999). “Employment Responses to International Liberalization in Chile”, Journal of International Economics, Vol. 47 (2), pp. 321-344. Repkine, A. and Walsh, P. (1999). “Evidence of European Trade and Investment U- Shaping Industrial Output in Bulgaria, Hungary, Poland and Romania”, Journal of Comparative Economics, Vol.27 (4), pp.730-752. 21 TABLES Table 1. Gross Job Flows in Manufacturing Year pos neg gross net exc N 1993-94 0.009 0.108 0.118 -0.099 0.019 7768 1994-95 0.016 0.098 0.114 -0.082 0.033 8023 1995-96 0.019 0.105 0.123 -0.086 0.037 7897 1996-97 0.018 0.113 0.132 -0.095 0.037 8163 1997-98 0.022 0.091 0.113 -0.069 0.045 7670 1998-99 0.030 0.094 0.124 -0.064 0.060 9066 1999-2000 0.041 0.081 0.122 -0.041 0.081 8077 Table 2. Distribution of Annual Employment Growth Rates: Firm level Year 1% 5% 10% 25% 50% 75% 90% 95% 99% Mean StDev N 93-94 -0.547 -0.332 -0.255 -0.158 -0.078 -0.007 0.043 0.086 0.304 -0.091 0.159 7768 94-95 -0.579 -0.321 -0.239 -0.137 -0.052 0.000 0.059 0.104 0.323 -0.073 0.164 8023 95-96 -0.750 -0.378 -0.273 -0.161 -0.068 0.000 0.061 0.108 0.347 -0.093 0.196 7897 96-97 -1.012 -0.405 -0.280 -0.163 -0.078 -0.004 0.055 0.121 0.522 -0.101 0.234 8162 97-98 -0.957 -0.386 -0.272 -0.145 -0.059 0.006 0.090 0.204 0.852 -0.071 0.254 7670 98-99 -1.283 -0.541 -0.333 -0.164 -0.063 0.014 0.131 0.300 1.077 -0.082 0.320 9066 99-00 -1.267 -0.588 -0.358 -0.167 -0.050 0.037 0.157 0.297 0.777 -0.082 0.309 8077 Table 3. Distribution of Annual Sectoral Job Creation Rates Year 1% 5% 10% 25% 50% 75% 90% 95% 99% Mean StDev 93-94 0 0 0 0.001 0.004 0.012 0.030 0.071 0.226 0.013 0.029 94-95 0 0 0 0.002 0.008 0.023 0.045 0.061 0.156 0.016 0.024 95-96 0 0 0 0.003 0.009 0.024 0.048 0.087 0.318 0.023 0.046 96-97 0 0 0 0.002 0.010 0.021 0.038 0.086 0.143 0.018 0.027 97-98 0 0.001 0.002 0.008 0.018 0.032 0.045 0.067 0.104 0.023 0.020 98-99 0 0 0.002 0.008 0.025 0.046 0.070 0.090 0.428 0.034 0.049 99-00 0 0.003 0.011 0.019 0.033 0.060 0.090 0.120 0.219 0.044 0.038 Table 4. Distribution of Annual Sectoral Job Destruction Rates Year 1% 5% 10% 25% 50% 75% 90% 95% 99% Mean StDev 93-94 0 0.018 0.038 0.064 0.113 0.146 0.184 0.212 0.263 0.111 0.057 94-95 0 0.007 0.017 0.045 0.085 0.130 0.193 0.222 0.405 0.095 0.071 95-96 0 0.008 0.026 0.050 0.106 0.156 0.215 0.286 0.404 0.116 0.080 96-97 0.011 0.022 0.033 0.075 0.114 0.160 0.196 0.241 0.369 0.121 0.067 97-98 0.006 0.022 0.035 0.060 0.100 0.144 0.171 0.199 0.555 0.107 0.070 98-99 0 0.012 0.017 0.069 0.111 0.148 0.212 0.301 0.433 0.118 0.080 99-00 0 0.011 0.028 0.070 0.103 0.135 0.179 0.207 0.335 0.104 0.060 Figure 1. Employment and Production in Ukrainian Industry, 1992-2000 (1992=100) 22 FIGURES 0 20 40 60 80 100 120 1998 1999 20001992 1993 1994 1995 1996 1997 Real industrial production Employment in industry Source: Derzhkomstat, TACIS Source: Commonwealth of Independent states in 2001 (2002) Figure 2. Dynamics of Ukrainian Exports, 1992-2001 (1996=100) 0 20 40 60 80 100 120 140 160 180 200 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 CIS ROW EU Source: Commonwealth of Independent states in 2001 (2002) 23 0 20 40 60 80 100 120 140 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Figure 3. Dynamics of Ukrainian Imports, 1992-2001 (1996=100) CIS ROW EU APPENDIX 1 Definitions of variables used in estimation Variable Description Definition Source JCit Job creation rate in industry i in year t )EmpEmp(2/1 Emp )1t(iit Mp pit − ∈ + ∆ ∑ +, where M+ = {p│∆Emppit > 0} Derzhkomstat registry of industrial enterprises, 1993- 2000 JDit Job destruction rate in industry i in year t )EmpEmp(2/1 Emp )1t(iit Mp pit − ∈ + ∆ ∑ −, where M– = {p│∆Emppit < 0} Derzhkomstat registry of industrial enterprises, 1993- 2000 JFit Job flow rates in industry i in year t {JCit, JDit, JRit, JNit, JEit} Derzhkomstat registry of industrial enterprises, 1993- 2000 OI_EUit Openness index with EU countries in industry i in year t ititit itit odPrEU_pImEU_Exp EU_pImEU_Exp ++ + where Exp_EU denotes exports to EU countries (nominal USD), Imp_EU denotes imports from EU countries (nominal USD), and Prod denotes sectoral production in nominal USD (converted from UHA using official average annual exchange rate) Derzhkomstat registry of industrial enterprises for production, Ukrainian Customs Committee data on import and export volumes by countries of origin and destination OI_CISit Openness index with CIS countries in industry i in year t ititit itit odPrCIS_pImCIS_Exp CIS_pImCIS_Exp ++ + where Exp_CIS denotes exports to CIS countries (nominal USD), Imp_CIS denotes imports from CIS countries (nominal USD), and Prod denotes sectoral production in nominal USD (converted from UHA using official average annual exchange rate) Derzhkomstat registry of industrial enterprises for production, Ukrainian Customs Committee data on import and export volumes by countries of origin and destination OI_ROWit Openness index with countries from the rest of the world in industry i in year t itit itit o PrROW_pImROW_Exp ROW_pImROW_Exp ++ + where Exp_ROW denotes exports to ROW countries (nominal USD), Imp_ROW denotes imports from Derzhkomstat registry of industrial enterprises for production, Ukrainian Customs Committee data on import and 30 ROW countries (nominal USD), and Prod denotes sectoral production in nominal USD (converted from UHA using official average annual exchange rate) export volumes by countries of origin and destination Eit Multilateral real exchange rate ∑ = − 3 1j jt)1t(ij Ew , where j indexes 3 trading areas (EU, CIS, ROW), Ejt denotes bilateral real exchange rate (UHA to Euro, Russian Ruble and USD correspondingly) defined as [ln(nominal exchange ratejt) +ln(ukrppit)-ln(ppijt)], and wij(t-1) denotes industry-specific trade share weights in the previous year National Bank of Ukraine (http://www.bank.gov .ua) for the official exchange rates, OECD Economic Trends for PPI in EU countries, Russia in Figures for PPI in Russia, Ukrainian Economic Trends for PPI in Ukraine, BLS data base for US PPI PrivshareiShare of non-state firms in sector i in 2000 Derzhkomstat firmlevel data on ownership in 2000 31 APPENDIX 2 Institutional Changes and Trade Regime Institutional changes in international trade regime in Ukraine Time Event November 1994 The system of export quotas and licenses, which had covered 40% of exports, was narrowed to include only grain, ferrous and nonferrous scrap, cast iron, and coal, in addition to goods subject to voluntary export restraint or other international agreements. A new system of export contract pre-registration was adopted; 20 categories of goods were originally subject to the registration requirement, in addition to all goods traded under barter arrangements December 1994 The state orders and contracts systems for foreign trade were eliminated January 1995 Export quotas and licenses on all above products except grain were eliminated March 1995 The scope of export contract pre-registration was limited to goods subject to the special export regime, voluntary export restraint, and actual or potential antidumping actions. A system of minimum indicative prices for a range of export products covering one-half of total exports was instituted December 1995 Indicative export prices were removed for all good except for goods subject to actual and prospective antidumping actions and voluntary export restraints. January 1996 Licensing requirement for grain exports was abolished. Import tariffs on many agricultural goods were raised to 30 %. April-May 1996 Export taxes, once fully eliminated, were reapplied to animals and skins in April 1996 and to ferrous and nonferrous metals and scrap in May 1996 June 1996 Import duties of about 15% on coal and refined petroleum products were introduced. Specific or mixed ad-valorem /specific tariffs have been introduced for numerous food products, motor vehicles, tires, textiles and clothing, alcohol, tobacco, furs, and radio equipment. June 1997 Export surrender requirement was revoked March 1998 Limits on auto imports were imposed September 1998 Foreign exchange restrictions were re-introduced. Limits were imposed on the making of advance import payments. A 50% surrender requirement was introduced. July 1999 A uniform, nondiscriminatory import surcharge of 2% was introduced. The restriction on advance import payments was eliminated. September 1999 An export duty on sunflower seeds was introduced. January 2000 A uniform, nondiscriminatory import surcharge of 2% was eliminated. The number of excisable imported goods has decreased from 20 to 5 categories (alcohol, tobacco, oil products, automobiles, jewelry). Sources: EBRD Transition Report 2002, IMF annual report on exchange arrangements and exchange restrictions (several issues) 32