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- (2006, ACF).53 For LP and ACF estimations, the Wooldridge (2009) IV procedure is applied.54 This method has several advantages with respect to two-step semi-parametric procedures. In particular, it does not require bootstrapping standard errors, allowing accounting for serial correlation and heteroskedasticity in the errors (Ornaghi and Van Beveren 2011). Moreover, it is more easily adaptable to more complex function forms such as the trans-log function presented in equation (6).
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- • Destination’s GDPdt and GDP per capitadt: GDP and GDP per capita of country d in constant 2000 US dollars from World Bank national accounts data.
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- • Number of past CV measuresjdt: The number of final CVD measures imposed by country d against South Korea affecting product j between 1994 and t − 1. • Safeguard measuresjdt: Dummy equals one if safeguard measures are in place in year t and country d involving product j. Other control variables. • UN Trains ad valorem tariffsjdt: It is the level of ad valorem duties normally faced by South Korean exports of product j to country d applicable in time t, as reported by UN Trains. The information was gathered from the World Integrated Trade Solution (WITS) database, which reports information on world tariffs at the same level of disaggregation as UN Comtrade data, i.e. by importer, exporter and product at 6-digit HS. Since the objective of this variable is to consider the level of protection normally in place, I use the effective applied tariff as reported in WITS.
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- • Real exchange ratedt: Real effective exchange rate index (2005 = 100) for country d from the International Monetary Fund’s International Financial Statistics.
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Ackerberg, Daniel A., Kevin Caves, and Garth Frazer, “Structural Identification of Production Functions,†UCLA, mimeo, 2006.
- Antidumping filings and measures. Information on AD cases comes from the World Bank’s Temporary Trade Barriers Dataset (TBBD) ranging from 1992 to 2009. In order to verify the completeness of this dataset, the information contained in it was compared to data on AD notifications from the WTO.49 Table B.3 shows the number of AD cases and measures against South Korean exporters by imposing country from these two sources.
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- Elasticity of substitution from Broda and Weinstein (2006). b Calculated at the 2-digit HS level.
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- F.o.b. unit values. Export unit values are calculated using UN Comtrade data for South Korea on export values and quantities ranging from 1994 to 2009, as follows: UVjdt = EVjdt Xjdt (B.1) where UVjdt is the unit value of South Korean exports of product j to destination d in year t, EVjdt is the f.o.b. value of exports and Xjdt is their quantity. Products are defined at 6-digit HS, which is the maximum level of disaggregation available in UN Comtrade and comparable across countries.
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- Finally, an additional control variable is introduced measuring economic activity in the region where the firm is located: • Regional manufacturing GDP growth rateit: Growth rate of real GDP (2005 prices) of the manufacturing sector in the region where firm i is located, obtained from South Korea’s Statistic Department. Regions are identified on the basis of firms’ zip codes reported in Oriana. Summary statistics of the variables used in the analysis on firms’ markups are presented in table B.5. Table B.5: Descriptive statistics of variables used in the analysis on firms’markups Firm-level variables Mean Median St. dev. Min. Max. No. obs.
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Ganguli, Bodhisattva, “The Trade Effects of Indian Antidumping Actions,†Review of International Economics, 2008, 16 (5), 930–941.
- Gross output 11076.91 2586.82 84929.78 3.19 12390519 80224 Material costs 8707.08 1961 63027.46 0.12 5854400 80224 Labour costs 412.72 134.05 1951.12 0.00 117131.10 80224 Capital 3689.06 636.64 37606.70 0.00 3798350 80224 Labour expenditure share 0.062 0.048 0.084 0.000 11.837 80224 Materials expenditure share 0.761 0.788 0.149 0.001 9.767 80224 The set of instruments used for the LP and ACF was chosen following De Loecker 53 For an in-depth discussion of these methods see Van Beveren (2012) and Ornaghi and Van Beveren (2011). 54 The programs used to perform production function estimations are extensions of Van Beveren (2012), Ornaghi and Van Beveren (2011) and Konings and Vanormelingen (2009).
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- Import penetration 0.3215 0.2388 0.3859 0.0023 5.0388 13536 Export intensity 0.3953 0.3410 0.3066 0.0015 1.8409 13536 Log number of plants 5.3068 5.3423 0.9390 1.3863 7.5192 13536 Log industry observable markup 0.4572 0.4664 0.1451 0.1253 0.8785 13536 Industry GDP growth rate 0.0886 0.0741 0.2187-0.7683 1.3584 13536 Log number of workers 8.9626 8.9347 0.7413 5.8201 11.0985 13536 Import growth 0.0700 0.0976 0.1771-0.9414 0.7806 13536 Export growth 0.0478 0.0627 0.1853-1.1092 0.7465 13536 Regional manufacturing GDP growth rate 0.0649 0.0539 0.0734-0.0964 0.2261 13536 C Appendix: Estimation of production functions and markups The trans-log production function presented in equation (6) is estimated using alternatively OLS, fixed effects (FE), Levinsohn and Petrin (2003, LP) and Ackerberg et al.
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- Initiations Measures Initiations Measures Imposing country WTO TTBD WTO TTBD Imposing country WTO TTBD WTO TTBD India 45 43 34 36 Colombia 7 3 0 0 Chinaa 31 32 25 26 Thailand 5 5 3 3 United States 29 29 14 13 Brazil 5 5 2 2 European Union 28 28 12 10 Chinese Taipeia 4 6 3 3 Australia 21 20 11 10 Egypt 4 4 4 4 South Africa 15 13 16 13 Chile 3 3 0 0 Indonesia 11 12 3 5 Mexico 2 2 1 1 Argentina 11 11 10 7 Philippines 2 2 1 1 Canada 8 8 5 5 Japan 1 1 1 1 Malaysia 7 7 5 5 Ukrainea 1 1 1 1 Pakistan 7 7 3 6 Israel 1 1 0 0 New Zealand 7 7 3 3 Peru 1 1 0 0 Turkey 7 6 7 6 Venezuela 1 1 0 0 Notes: a These countries were not members of the WTO until 2001 (China), 2002 (Chinese Taipei) and 2008 (Ukraine).
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- Log ADD tariff factor 0.3056 0 0.5255 0 2.5449 13536 Log ADD tariff factor squared 0.3695 0 1.1048 0 6.4765 13536 Log preliminary ADD tariff factor 0.0297 0 0.2114 0 2.5445 13536 Log final ADD tariff factor 0.2766 0 0.4966 0 2.5449 13536 Other AD measures 0.0026 0 0.0053 0 0.0502 13536 AD initiations 0.0055 0 0.0315 0 0.3293 13536 Average effect 0.4286 0 0.4949 0 1 13536 Number of past AD measures 0.0400 0.0008 0.1092 0 1.0807 13536 Log CVD tariff factor 0.0033 0 0.0261 0 0.3418 13536 Number of past CV measures 0.0004 0 0.0064 0 0.1286 13536 Safeguard measures 0.0000 0 0.0001 0 0.0023 13536 Log UN Trains tariff factor (for exports) 1.8760 1.8923 0.4485 0.5975 2.8350 13536 Trade measures imposed by South Korea Mean Median St. dev. Min. Max. No. obs.
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- Log(ˆ OLS) 0.0831 0.0731 0.1048-0.2270 1.2652 13536 Log(ˆ FE) 0.0967 0.0908 0.1279-1.1483 1.2982 13536 Log(ˆ LP ) 0.0883 0.0908 0.1240-0.4542 1.2013 13536 Log(ˆ ACF ) 0.0920 0.1048 0.2857-6.9459 1.5702 13536 Log capital/sales ratio-1.6620-1.4002 1.4064-11.6437 3.6178 13536 Log labour costs/sales ratio-3.1840-3.1099 0.8820-9.1830 0.7105 13536 Trade measures in export markets Mean Median St. dev. Min. Max. No. obs.
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- more serious problem is presented by the last two cases where a given old HS code matches into several HS 2007 codes. For these trade lines, the construction of continuous series is not feasible since it is not possible to split exported values and quantities between the different new codes. 46 It should be pointed out that these numbers included all codes reported in the concordance tables and not just those considered in the study. 47 This summation was performed after adjusting the data for inconsistencies in the units of quantity reported as described later in this appendix.
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- Past AD cases against South Korea are positively correlated with the difference in AD duties and other measures, which may be the reflection of retaliation motives. Also export intensity is negatively correlated with the presence of AD measures consistent with the retaliation threat hypothesis by Blonigen and Bown (2003). Export growth presents a positive correlation, on the other hand. Import penetration present the expected positive correlation with AD initiations. However, its coefficient is negative for the first difference in AD measures. The growth rate of imports also presents a negative coefficient for AD duties and initiations, while the coefficient is positive for other AD measures. The log of the number of workers presents the expected positive correlation with the first difference in AD initiations, but a negative correlation with the first difference of AD duties and other measures. Table D.2: First stages of markups instrumental variables estimations, part I.
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- Regarding the second issue mentioned above, 68.44% of the data points report systematically the same unit of quantity across years and trading partners within the same HS 2007. For the remaining, I used instead the weight in kilograms as measure of quantity.48 After these adjustments, and summing up values and quantities by HS 2007 for each partner and year, I was able to retrieve information on exported values and quantities for 99.62% of all observations for which concordance across HS versions was possible. 48 Note that these numbers are not only affected by inconsistencies contained in the original dataset, but also the substitution of quantities by weight in kilograms for observations with zero or not reported quantities may have affected the continuity of a given measure of quantity. Table B.2: Units reported in UN Comtrade for South Korean export data.
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- The period of analysis covers several revisions of the HS classification. As table B.1 shows, four different versions of HS are used in Comtrade to report South Korean export data between 1994 and 2009. In order to construct continuous series for the entire period, the 2007 HS classification was taken as reference, matching other versions with it. The reason for choosing this particular HS version is that the concordance table used to match trade and industry and firm-level data, as discussed below, is only available for HS 2007. Table B.1: HS versions reported in UN Comtrade for South Korean export data.
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