Policy Research Working Paper 10237 Scarcity Nationalism during COVID-19 Identifying the Impact on Trade Costs Peter H. Egger Gerard Masllorens Nadia Rocha Michele Ruta Macroeconomics, Trade and Investment Global Practice November 2022 Policy Research Working Paper 10237 Abstract During the COVID-19 pandemic, many countries used 2020 and December 2021 for most COVID-19 critical export and import policy as a tool to expand the availability medical products, particularly garments (for example, face of scarce critical medical products in the domestic market masks) and ventilators. The exception is vaccines, which (scarcity nationalism). This paper assesses the direct and saw a reduction in trade costs, which, however, was driven indirect (via trade in intermediates) increases in trade costs by the reduction in indirect trade costs for high-income of critical medical goods resulting from these uncooper- countries, consistent with the view of a COVID-19 vaccine ative policies. The results show that scarcity nationalism production club. led to substantial increases in trade costs between February This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at nrocha@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Scarcity Nationalism during COVID-19: Identifying the Impact on Trade Costs , Gerard Masllorens‖ Peter H. Egger¶ , Michele Ruta†† , Nadia Rocha∗∗ Keywords: Covid-19; protectionism; trade; Global Trade Alert JEL codes: F13; F14 1 Introduction During the COVID-19 pandemic, we witnessed a reemergence of trade protectionism. However, while traditionally protectionism is something that is pursued on the part of importers to shield domestic producers from what they deem to be excessive competition from foreign suppliers, the protectionism applied during the current pandemic aimed at maximizing the availability of sensitive, foremost medical, products in the domestic market through a mix of trade facilitation and export controls (Evenett et al., 2022). We refer to this mix of export and import policy as ”scarcity nationalism” to distinguish it from traditional trade protectionist measures. This study empirically investigates the impact of these trade policies during COVID-19 on trade costs of critical medical goods. The analysis relies on the Global Trade Alert (GTA) data on policy measures that have been adopted by countries at the HS6-traded-product level for medical products that have been critical ¶ ETH Zurich, CEPR, CESifo, WIFO; Email: pegger@ethz.ch; Address: Leonhardstrasse 21, 8092 Zurich, Switzer- land. ‖ ETH Zurich. Email: gmasllorens@ethz.ch; Address: Leonhardstrasse 21, 8092 Zurich, Switzerland. ∗∗ World Bank; Email: nrocha@worldbank.org; Address: World Bank, 1818 H Street, Washington DC, USA. †† International Monetary Fund; Email: mruta@imf.org ; Address: International Monetary Fund, 700 19th st NW, Washington, DC 20431, USA to deal with the COVID-19 pandemic, such as face masks and ventilators, and for vaccines and vaccine inputs. After merging these data with bilateral product-level trade data, we measure the impact of trade policies on trade margins. We disentangle the effect of trade measures (restricting and facilitating) on medical products using monthly data for a span of time from January 2018 (prior to the pandemic, when no such measures were used) up until December 2021. We also look into product, time and geographic heterogeneity and provide a general picture of the impact on trade-cost of trade policies motivated by scarcity nationalism during COVID-19. In doing so, we separate between the direct effects of trade policy on trade costs and the indirect effects, as these measures affect the cost of trade in intermediate goods. Interest in the effects of trade protectionism has increased in recent years as tensions in the world trade system have emerged. Our work relates to the recent literature on the economic effects of trade policy (Goldberg and Pavcnik, 2016; Handley et al., 2020; Amiti et al., 2019; Fajgelbaum et al., 2020). Differently from these studies, the focus in this paper is not on the consequences of the re-emergence of tariffs but on the broader set of trade policy measures that have targeted medical products during the COVID-19 pandemic. Moreover, we study both the direct effects of trade policy on trade costs and its indirect effects through the intermediate trade channel. 2 Data We use data from three sources. First, we construct binary indicators reflecting whether a country utilizes import or export policy measures or not. With import and export measures that can be restricting or facilitating, there are four indicators. The source of these data is the Global Trade Alert (GTA), and the data vary by country j , product k , and month t. We use them at monthly frequency between January 2018 and December 2021, and we employ export measures in a way so that they are on the exports of a product to country j . Note that the policy measures do not vary much across partner countries so that we make them importer-country-product-time-specific for both import and export (towards the importer) policies upfront. We call them dm jk,t for import policies, a scalar for the mth (of two: restraining and facilitating) import measures. Similarly, we refer to export measures importer j is faced with in k by dx jk,t , a scalar for the mth (of two: restraining and facilitating) export measures. Stacking these measures for all importers J and products K in year t obtains the JK × 4 matrix ∆t in month t. A typical row of ∆t may be referred to by ∆jk,t . Second, we use bilateral export data from country i to j and product k , xijk,t for 180 products indexed by k on a monthly basis between January 2018 and December 2021. As the monthly trade data are available for the European Union, the United States, and China, we treat those three as partner countries (exporters or importers) of J = 247 countries and consider all possible bilateral relations between the mentioned three and all other countries in the exporting and importing directions. These data will be used to estimate parameters revealing the ad-valorem-equivalent trade costs associated with the policy variables in ∆t . Third, we use cross-sectional bilateral export data for 180 + 1 products and J (J − 1) country pairs from UNCTAD. These cross-sectional data are obtained from averaging annual export data for the period 2017-2019. Then, we construct a (J × J )(K + 1) matrix of bilateral trade flows,1 We combine these data with the S (sector-by-sector) input-output matrix for the United States in 1 Note that we consider K + 1 products here, in order to account for the bulk of products (a residual category) beyond the 180 sensitive ones in focus here. 2 the year 2012, which is available from the BEA. From the latter we impute a K × K matrix by using product-sector concordance tables from UNCTAD. The obtained matrix will serve to compute input-output-repercussion indirect effects of trade policies on sensitive products. 3 Effects of pandemic-related trade policy measures on trade costs and imports We are interested in distinguishing between direct and indirect effects (i.e. through imported inputs) of the trade policy measures of interest during the time period January 2018-December 2021. For this, let us use gjk,t to denote the import-value equivalent for importing country j , product k , and month t. We will establish later how to estimate it. We postulate that gjk,t is linearly composed of the direct effects associated with the four import- and (partner-)export-related policy measures which are collected in ∆jk,t , and with as many corresponding indirect effects. Suppose a JK × JK input-output matrix H exists. This matrix is obtained from H = O⋆ ◦ M ⋆ , where M ⋆ is a JK × JK (block-diagonal) expenditure-shares matrix consisting of J × J blocks of expenditure shares for each product k (Eaton and Kortum, 2002; Caliendo and Parro, 2014). For this, start with M , a JK × J imports matrix. The diagonal elements (expenditure on domestic produce) can be predicted from exporter and importer fixed effects in a gravity equation per product, assuming domestic sales frictions are zero. The matrix M is then row-normalized (dividing by aggregate expenditure by product) to obtain M ⋆ . O⋆ , a JK × JK input-output matrix is obtained after row-normalizing O ˆ = COC ′ , where O in our case is the S × S input-output matrix of the United States with sector number S < K , and C is a K × S conversion matrix which associates products with sectors.2 Assuming that an estimate of the (global country-product-pair) Leontief- type (at least pseudo-)inverse (IJK − H )−1 exists, where IJK is a (JK × JK ) identity matrix, we can define Λt = (IJK − H )−1 ∆t . (1) ∞ The latter is nothing else than ∆t + ( q=1 H q )∆t , where the first term captures the indirect relevance of the application of policy measures in ∆t for each importer j and product k from other units (the same or other importers and the same or other products) in month t. As ∆t is JK × 4, so is Λt , and the latter has typical row Λjk,t . Using ηk and ξk for the 4 × 1 parameter vectors on the columns of ∆jk,t and Λjk,t , respectively, we can define gjk,t = ∆jk,t ηk + Λjk,t ξk . (2) Direct effects Direct plus indirect effects Conditional on the direct effects ∆jk,t ηk , Λjk,t ξk measures the indirect effects of the policy measures in ∆jk,t ηk on gjk,t . We can estimate gjk,t from bilateral product-level data on exports or imports xijk,t , assuming a customary level-multiplicative or log-additive gravity model of product-level sales of country i to j in month t: xijk,t = exp(αik,t + βijk,t + γjk,t ), (3) 2 Conversion tables for traded products and various sector classifications are available from the United Nations Conference on Trade and Development. 3 where αik,t , βijk,t , and γjk,t are parameters capturing sales/supply-potential factors of k in i, the trade freedom of k between i and j , and the demand/consumption potential of k in j , all in logs and at time/month t. When only trade but no domestic sales data are available, the unilateral frictions on k enter γjk,t only. We proceed in two steps to identify the parameters ηk and ξk of interest: (i) estimate γjk,t as importer-product-month fixed effects from monthly bilateral product-level export data xijk,t on 180 sensitive products; (ii) estimate the impact of unilateral trade frictions on product k from γjk,t ˜jk + λγ = gjk,t + γ γ t + uik,t , (4) where gjk,t is defined as in (2), and γ˜jk , λγ γ t and uik,t are importer-product-fixed, month-fixed, and importer-product-month residual effects, respectively. As all ∆jk,t are binary indicators, all parameters η measure (direct) semi-elasticities of imports. Note that under the assumption of a constant-elasticity-of-substitution model with (direct) trade elasticity (1 − σk ),3 one can scale γjk,t by (1 − σk ) to obtain 1 τjk,t = exp gjk,t − 1, (5) 1 − σk the iceberg-trade-cost increment associated with pandemic-related policies alone by product, im- porter, and month. E.g., τjk,t = 0.02 then means that trade costs are (directly plus indirectly) raised by pandemic-related policies for product k and country j in month t by about two percent- age points. Apart from reporting on τjk,t , we (trade-weighted) aggregate these trade costs effects for each of the 247 countries and each month t to obtain τj,t . Finally, we aggregate the same trade-cost effects across countries j to obtain τt for the average country and sensitive product. 4 Results In the following, we first display the evolution of τk,t for selected sensitive products – namely, garments, ventilators, vaccines and tests. The results are summarized in Figure 1. 3 The e et al. (2022). values of σk are obtained from Fontagn´ 4 (a) Garments (b) Vaccines (c) Ventilators (d) Tests Figure 1: Trade costs of sensitive products Figure 1 illustrates the evolution of import trade costs expressed as iceberg-surcharge costs over mill prices. For garments such as face masks (Figure 1a) those appeared to be very low (in the 1% range) for the period before the pandemic. We observe a slight increase in trade costs already in January of 2020, and by April of 2020 the costs peaked at more than 140%. They came down again only to levels below 5% after June of 2021. Interestingly, indirect effects on trade costs account for most of the increase during March and April 2021, but later become negative, perhaps suggesting a change in the production process of garments. We see a sharp facilitation of the trade of the COVID-19 vaccines from the time that such vaccines became available in the first quarter of 2021 both in terms of direct and indirect costs (Figure 1b). This result is not in contrast with the ”vaccine nationalism” view. It simply reflects the fact that these products were invented and introduced during the pandemic and they required trading in inputs that were not much traded before. Much of this trade took place within the set of economies that were producing vaccines, which were mostly high-income countries, with limited trade with non-producing countries (Evenett et al., 2021). For ventilators (Figure 1c), trade costs increased from virtually zero to about 10% even as early as the beginning of 2019 – obviously unrelated to the COVID-19 pandemic. Frictions increased sharply with a slight delay relative to garments but similarly peaking in the middle of 2020, at somewhat higher than 10%. Unlike garments, frictions on ventilators came down at the end of the sample period to the level they had prior to the COVID-19 pandemic. Policy-induced trade frictions on tests (Figure 1d) increased gradually prior to the outbreak of the pandemic, but there was a sharp increase from the beginning of the pandemic, especially in terms of indirect trade costs. The total costs experienced a more moderate increase thanks to the 5 negative contribution of the direct trade costs. Upon aggregating trade-cost increases for the average month during the period after February 2020 until the end of 2021 for the (trade-weighted) average product, we obtain the following insights. First, import frictions were increasing at high levels in the average month in particular for the United States, T¨urkiye, India, Japan, China and the Russian Federation followed by other countries, mostly in the northern hemisphere and in South America. Second, when considering changes between the period from February 2020 until the end of our sample coverage relative to the period from the beginning of 2018 to January 2018, we see that the change in the uptake of restraining policies was quite significant and widespread with important peaks in Russia, Indonesia, China and Argentina for the average sensitive product. Finally, in Table 1, we aggregate the information on changing trade frictions into country groups by income bracket and report the change in percentage points between the period after February 2020 and the period before up until January 2020 in the average month.4 The table is organized in three parts vertically: combined direct and indirect components of trade-cost levels and their policy-induced changes are at the top; the two panels underneath pertain to the direct (own-cost) and indirect components only. The numbers in the same cell of the two panels at the bottom sum up to the corresponding one at the top. The numbers suggest that the biggest trade cost increases happened for upper-middle-income countries (through partner export or own import policies) for the imports of ventilators and for high-income countries for the ones of garments. The biggest trade cost reductions occurred for vaccines in high-income countries (consistent with the findings in Figure 1). The indirect effects tend to soften the direct ones for tests, ventilators, and garments, whereas they reinforce the (negative) direct effects for vaccines. The indirect effects are particularly large and dominant for upper-middle- and high-income countries in the case of vaccines, whereas the direct effects tend to dominate in other cells. Interestingly, the indirect effects are of relatively large importance in comparison to the direct effects throughout the table pointing to the fact that the indirect costs of trade policy are key. 4 We list the associations of countries with country groups in the table footnote. 6 Table 1: Trade-cost change before and after February 2020 by country income group in percentage points Total costs Tests Ventilators Vaccines Garments Low income −0.06 − 0.43 − Lower-middle income 0.85 1.75 −39.27 1.15 Upper-middle income 0.38 2.77 −98.71 3.68 High income −0.10 2.39 −1111.40 13.38 Direct costs Tests Ventilators Vaccines Garments Low income − 0.06 −0.09 − Lower-middle income −0.83 2.24 −20.59 1.75 Upper-middle income −0.71 3.67 −8.78 6.47 High income −3.62 2.88 −36.76 11.23 Indirect costs Tests Ventilators Vaccines Garments Low income − 0.04 0.52 − Lower-middle income 1.68 −0.49 −18.68 −0.61 Upper-middle income 1.10 −0.91 −89.92 −2.79 High income 3.52 −0.48 −1074.64 2.15 Low income includes: AFG, BFA, BDI, CAF, TCD, COD, ERI, ETH, GMB, GIN, GNB, PRK, LBR, MDG, MWI, MLI, MOZ, NER, RWA, SLE, SOM, SSD, SDN, SYR, TGO, UGA, YEM. Lower-Middle income includes: AGO, DZA, BGD, BLZ, BEN, BTN, BOL, CPV, KHM, CMR, COM, COG, CIV, DJI, EGY, SLV, SWZ, GHA, HTI, HND, IND, IDN, IRN, KEN, KIR, KGZ, LAO, LSO, MRT, FSM, MNG, MAR, MMR, NPL, NIC, NGA, PAK, PNG, PHL, WSM, STP, SEN, SLB, LKA, TZA, TJK, TLS, TUN, UKR, UZB, VUT, VNM, PSE, ZMB, ZWE. Upper-Middle income includes: ALB, ASM, ARG, ARM, AZE, BLR, BIH, BWA, BRA, BGR, CHN, COL, CRI, CUB, DMA, DOM, GNQ, ECU, FJI, GAB, GEO, GRD, GTM, GUY, IRQ, JAM, JOR, KAZ, UNK, LBN, LBY, MYS, MDV, MHL, MUS, MEX, MDA, MNE, NAM, MKD, PAN, PRY, PER, ROU, RUS, SRB, ZAF, LCA, VCT, SUR, THA, TON, TUR, TKM, TUV. High income includes: AND, ATG, ABW, AUS, AUT, BHS, BHR, BRB, BEL, BMU, VGB, BRN, CAN, CYM, CHL, HRV, CUW, CYP, CZE, DNK, EST, FRO, FIN, FRA, PYF, DEU, GIB, GRC, GRL, GUM, HKG, HUN, ISL, IRL, IMN, ISR, ITA, JPN, KOR, KWT, LVA, LIE, LTU, LUX, MAC, MLT, MCO, NRU, NLD, NCL, NZL, MNP, NOR, OMN, PLW, POL, PRT, PRI, QAT, SMR, SAU, SYC, SGP, SXM, SVK, SVN, ESP, KNA, MAF, SWE, CHE, TWN, TTO, TCA, ARE, GBR, USA, URY, VIR. 7 References Amiti, Mary, Stephen J Redding, and David E Weinstein, “The impact of the 2018 tariffs on prices and welfare,” Journal of Economic Perspectives, 2019, 33 (4), 187–210. Caliendo, Lorenzo and Fernando Parro, “Estimates of the Trade and Welfare Effects of NAFTA,” The Review of Economic Studies, 11 2014, 82 (1), 1–44. Eaton, Jonathan and Samuel Kortum, “Technology, Geography, and Trade,” Econometrica, 2002, 70 (5), 1741–1779. Evenett, Simon, Bernard Hoekman, Nadia Rocha, and Michele Ruta, “The Covid-19 Vaccine Production Club : Will Value Chains Temper Nationalism?,” Technical Report, World Bank 2021. , Matteo Fiorini, Johannes Fritz, Bernard Hoekman, Piotr Lukaszuk, Nadia Rocha, Michele Ruta, Filippo Santi, and Anirudh Shingal, “Trade policy responses to the COVID- 19 pandemic crisis: Evidence from a new data set,” The World Economy, 2022, 45 (2), 342–364. Fajgelbaum, Pablo D., Pinelopi K. Goldberg, Patrick J. Kennedy, and Amit K. Khan- delwal, “The Return to Protectionism,” The Quarterly Journal of Economics, February 2020, 135 (1), 1–55. Fontagn´ e, Lionel, Houssein Guimbard, and Gianluca Orefice, “Tariff-based product-level trade elasticities,” Journal of International Economics, 2022, 137, 103593. Goldberg, P.K. and N. Pavcnik, “Chapter 3 - The Effects of Trade Policy,” in Kyle Bagwell and Robert W. Staiger, eds., Kyle Bagwell and Robert W. Staiger, eds., Vol. 1 of Handbook of Commercial Policy, North-Holland, 2016, pp. 161–206. Handley, Kyle, Fariha Kamal, and Ryan Monarch, “Rising import tariffs, falling export growth: when modern supply chains meet old-style protectionism,” Technical Report, National Bureau of Economic Research 2020. 8 Appendix (intended for online publication only) In this appendix, we report a table containing the coefficients associated with the estimates of equation (4) in the main text and consistent with the results reported in Table 1 and Figure 1. Note that equation (4) is estimated for each 6-digit product category separately. In each category, the direct and the indirect effects in equation (4) involves four observable protectionist measures and the associated coefficients. Hence, altogether there are eight regression coefficients of interest per product. These are the use of: (i) import-restricting policies implemented by the importing country; (ii) import-facilitating policies implemented by the importing country; (iii) export-restricting policies implemented by the importing country’s partner country; and (iv) export- facilitating policies implemented by the importing country’s partner country. In the table, we put for each product in the first row the coefficient point estimate and underneath (in parentheses) the corresponding standard error. In each estimation, we employ the fixed effects as listed in equation (4). With 180 sensitive products considered which are of interest in the context of the COVID-19 pandemic, there are 180 vectors of coefficient point estimates and associated standard errors. The ones highlighted in the text are four particularly important ones. Given the large number of point estimates, we have to refrain from an in-depth discussion of their magnitude but restrict our focus to the results emphasized in the main text. 9 Table A1: Estimated trade policy coefficients by product Direct effects Indirect effects Product Import-restricting Import-facilitating Export-restricting Export-facilitating Import-restricting Import-facilitating Export-restricting Export-facilitating 170199 −1.946 −6.313 0.013 0.181 1.908 6.134 −0.029 −0.115 (2.532) (3.642) (0.098) (0.074) (2.479) (3.585) (0.088) (0.085) 220710 −0.735 0.083 0.196 0.212 0.789 0.049 −0.209 −0.051 (0.999) (0.063) (0.103) (0.134) (0.966) (0.061) (0.078) (0.079) 220720 −6.278 0.249 0.285 0.346 6.286 −0.069 −0.131 −0.235 (2.716) (0.117) (0.111) (0.129) (2.669) (0.072) (0.069) (0.088) 220890 2.691 −0.782 −0.967 2.736 −1.857 0.885 0.333 −1.34 (10.556) (0.47) (1.259) (1.358) (10.455) (0.392) (1.256) (1.321) 250100 0.008 0.099 0 0 0.003 −0.105 1.019 1.716 (0.027) (0.033) ( .) (.) (0.02) (0.039) (1.759) (2.532) 280610 −1.553 −2.279 0 0 1.555 2.318 −1.606 −0.032 (0.713) (0.811) ( .) (.) (0.694) (0.8) (1.556) (0.016) 281121 1.455 −0.037 −4.976 −0.052 −1.462 0 5.001 −0.023 (1.61) (0.043) (1.924) (0.094) (1.588) (0.042) (1.907) (0.044) 281511 1.223 0.011 0 0 −1.207 0.017 −0.045 0.025 (0.635) (0.024) ( .) (.) (0.62) (0.045) (0.017) (0.033) 281512 0.111 0.349 −0.892 −0.077 −0.098 −0.387 0.836 0 (0.437) (1.095) (1.434) (0.024) (0.432) (1.085) (1.399) (0.017) 282510 −0.019 −0.915 0 0 −0.007 0.913 −0.02 0.004 (0.022) (0.549) ( .) (.) (0.004) (0.544) (0.267) (0.005) 282731 −0.014 −0.05 0 0 0.013 0.047 −0.254 0.005 (0.008) (0.014) ( .) (.) (0.006) (0.018) (0.417) (0.008) 283330 −0.43 0.983 0 0 0.49 −0.914 0.067 0.051 (0.78) (0.828) ( .) (.) (0.758) (0.79) (1.496) (0.035) 283522 0.007 0.029 0 0 −0.011 −0.042 −0.193 −0.003 (0.018) (0.012) ( .) (.) (0.013) (0.017) (0.613) (0.007) 283524 −0.007 0.05 0 0 0.017 −0.032 −0.004 −0.016 (0.026) (0.807) ( .) (.) (0.024) (0.798) (1.254) (0.018) 284700 −0.016 −1.049 0.021 0 −0.007 1.041 −0.005 −0.02 (0.017) (0.379) (0.014) (.) (0.015) (0.37) (0.011) (0.019) 290512 0.011 0.006 −2.945 0.47 −0.001 −0.018 2.919 −0.465 (0.01) (0.005) (0.831) (1.025) (0.009) (0.01) (0.821) (1.01) 290544 0.015 1.675 0 0 0.023 −1.612 0.389 −5.728 (1.486) (1.812) ( .) (.) (1.485) (1.784) (2.773) (3.762) 290613 −0.008 −1.192 0 0 −0.006 1.245 5.679 −1.565 (0.026) (4.246) ( .) (.) (0.025) (4.098) (1.68) (6.02) 291211 0.041 0 0 0 0.049 1.684 −2.554 2.822 (0.043) (.) ( .) (.) (0.022) (2.598) (2.792) (3.151) 291521 −0.028 0.067 0 0 0.027 −0.13 1.226 1.831 (0.015) (0.025) ( .) (.) (0.014) (0.033) (1.242) (2.646) 291529 0.015 −1.193 0 0 −0.005 1.138 1.154 −1.436 (0.009) (0.655) ( .) (.) (0.012) (0.633) (1.046) (2.163) 291814 −0.008 −0.093 0 0 0.007 0.078 1.702 −3.41 (0.009) (0.018) ( .) (.) (0.01) (0.023) (0.948) (1.194) 291815 −0.001 0.055 0 0 0.01 −0.048 −0.742 0.616 (0.012) (0.007) ( .) (.) (0.011) (0.009) (0.89) (0.867) 292219 0.29 −1.101 −0.376 0 −0.291 1.084 0.358 −0.052 (0.321) (0.442) (0.584) (.) (0.319) (0.437) (0.587) (0.734) 292249 0.276 0.044 −0.037 0.056 −0.274 −0.046 0.05 −0.066 (0.228) (0.006) (0.028) (0.702) (0.226) (0.011) (0.028) (0.694) 292250 −0.21 −0.11 0.24 0 0.205 0.091 −0.232 0.316 (0.321) (0.062) (0.489) (.) (0.316) (0.062) (0.49) (0.755) 292320 0.225 −0.468 −2.407 2.738 −0.236 0.442 2.397 −2.729 (0.533) (0.623) (1.046) (1.932) (0.53) (0.613) (1.045) (1.929) 293329 −0.181 −0.167 0.119 0 0.179 0.169 −0.137 −0.012 (0.317) (0.37) (0.605) (.) (0.311) (0.367) (0.603) (0.723) 294190 0.265 −0.007 0.005 0 −0.251 −0.002 −0.006 0.428 (0.19) (0.005) (0.016) (.) (0.182) (0.005) (0.017) (0.332) 300220 0.004 −0.013 0.001 −0.012 −0.001 −0.003 0 −0.009 (0.013) (0.01) (0.008) (0.015) (0.008) (0.008) (0.008) (0.012) 300310 0.01 0.006 0.123 0 0.002 −0.005 −0.007 −0.034 (0.025) (0.027) (0.031) (.) (0.025) (0.011) (0.015) (0.022) 300320 0.034 0 0.007 −0.035 −0.044 0.001 0.015 0.037 (0.016) (0.021) (0.006) (0.013) (0.017) (0.011) (0.007) (0.013) 300331 0 0 0 0 7553.155 0.787 211.679 151495.4 (.) (.) ( .) (.) (.) (.) (.) (.) 300339 −0.003 −0.016 0.012 0 0.014 −0.002 −0.015 0.025 (0.019) (0.029) (0.019) (.) (0.018) (0.013) (0.017) (0.017) 300390 −0.061 0.014 −0.039 −0.03 0.051 −0.004 0.025 0.038 (0.014) (0.022) (0.019) (0.027) (0.015) (0.018) (0.019) (0.025) 300410 0.02 −0.005 0.003 0.009 −0.012 0 −0.003 −0.004 (0.009) (0.008) (0.007) (0.014) (0.007) (0.014) (0.007) (0.013) 300420 0.015 0.008 −0.002 0.011 0 −0.011 0.003 −0.004 (0.006) (0.003) (0.005) (0.008) (0.005) (0.007) (0.005) (0.009) 300431 −0.008 −0.04 0.021 0.022 0.01 0.039 −0.03 −0.005 (0.006) (0.011) (0.015) (0.013) (0.005) (0.007) (0.013) (0.008) 300432 0.005 −0.017 0.017 0.001 0.002 0.013 −0.023 −0.002 (0.019) (0.011) (0.008) (0.017) (0.009) (0.007) (0.007) (0.015) 300439 0.005 −0.003 −0.007 0.008 −0.001 0.006 0.004 −0.001 (0.014) (0.009) (0.012) (0.014) (0.012) (0.007) (0.012) (0.013) 300450 0.01 −0.025 0.004 −0.049 −0.034 0.02 −0.006 0.04 (0.02) (0.02) (0.02) (0.026) (0.018) (0.022) (0.019) (0.018) 300490 0 −0.008 0 0 0.002 0.003 0 −0.002 (0.004) (0.005) (0.003) (0.004) (0.003) (0.005) (0.003) (0.005) 300510 −0.017 0.033 −0.034 −0.086 0.024 −0.008 0.006 −0.013 (0.018) (0.02) (0.016) (0.064) (0.017) (0.011) (0.013) (0.023) 300590 0.011 0.003 0.011 −0.04 0.006 −0.01 0.02 −0.002 (0.012) (0.016) (0.018) (0.045) (0.012) (0.011) (0.011) (0.018) 310420 0.168 0.138 0 0 −0.235 −0.009 −0.563 2.494 (0.563) (0.035) ( .) (.) (0.543) (0.008) (1.413) (2.407) 340111 0.003 0.007 0.029 −0.028 0.01 0 −0.015 0.028 (0.012) (0.012) (0.048) (0.048) (0.013) (0.009) (0.049) (0.052) 340119 −0.024 0.013 0.003 0.039 0.027 −0.014 0.025 0.008 (0.015) (0.022) (0.033) (0.024) (0.013) (0.017) (0.019) (0.012) 340120 0.001 −0.773 0.062 0 0.02 0.691 −0.022 −0.023 (0.027) (0.343) (0.044) (.) (0.022) (0.326) (0.027) (0.025) 340130 −0.002 (0.008) −0.031 (0.025) −0.002 (0.029) 0 (.) 10 0.005 (0.006) 0.021 (0.021) −0.015 (0.024) 0.004 (0.009) Table A1: Estimated trade policy coefficients by product (continued) Direct effects Indirect effects Product Import-restricting Import-facilitating Export-restricting Export-facilitating Import-restricting Import-facilitating Export-restricting Export-facilitating 340213 0.015 −0.052 0.02 0 0 0.039 −0.005 0.013 (0.014) (0.011) (0.016) (.) (0.013) (0.012) (0.017) (0.014) 340220 0.022 −0.015 0.01 −0.012 −0.022 0.015 −0.01 0.012 (0.043) (0.008) (0.006) (0.007) (0.042) (0.011) (0.007) (0.007) 350300 −0.964 −0.892 3.107 −0.111 0.928 0.947 −3.083 0.012 (1.365) (1.268) (1.532) (0.063) (1.331) (1.208) (1.527) (0.028) 350510 0.013 1.349 −6.011 0.542 −0.028 −1.308 5.928 0.037 (0.1) (7.786) (5.897) (0.151) (0.087) (7.617) (5.838) (0.152) 350790 0.667 −0.039 −0.039 −0.024 −0.639 0.065 0.042 0.013 (0.984) (0.014) (0.051) (0.051) (0.965) (0.03) (0.05) (0.048) 380894 −0.048 0.02 −0.057 0.114 0.022 −0.006 0.011 −0.006 (0.027) (0.059) (0.048) (0.065) (0.025) (0.059) (0.051) (0.058) 382100 −1.285 −0.045 0.083 0.013 1.246 −0.055 −0.028 0.001 (0.728) (0.018) (0.04) (0.041) (0.7) (0.035) (0.037) (0.034) 382200 0.349 −0.039 −0.021 0.034 −0.32 0.051 0.016 −0.011 (0.367) (0.044) (0.017) (0.018) (0.348) (0.044) (0.019) (0.014) 390210 0.01 −0.008 −1.18 −0.011 −0.006 −0.006 1.171 0.006 (0.011) (0.007) (0.439) (0.011) (0.011) (0.01) (0.43) (0.009) 390421 0.514 −0.775 0.253 0.009 −0.539 0.822 −0.27 0.009 (0.469) (0.361) (1.021) (0.016) (0.465) (0.35) (0.998) (0.017) 390720 −0.053 −0.004 0.003 0.022 0.047 −0.007 0.015 −0.038 (0.018) (0.013) (0.011) (0.013) (0.017) (0.014) (0.012) (0.012) 391610 −0.162 0.442 0 0 0.111 −0.468 0.876 0.014 (0.628) (0.069) (.) (.) (0.606) (0.074) (0.646) (0.02) 391620 0.859 0.293 0.855 −0.084 −0.855 −0.258 −0.779 0.001 (0.495) (0.058) (1.219) (0.02) (0.474) (0.061) (1.178) (0.019) 391690 −0.011 0.103 0 0 0.028 −0.085 −0.082 0.017 (0.321) (0.032) (.) (.) (0.303) (0.033) (0.409) (0.012) 391740 0.074 0.05 0.027 −0.009 −0.047 −0.025 0.003 0.001 (0.441) (0.042) (0.017) (0.035) (0.433) (0.018) (0.016) (0.024) 392310 0.085 0.226 0.017 0.009 −0.043 −0.243 −0.002 0.036 (0.041) (0.068) (0.029) (0.02) (0.024) (0.07) (0.026) (0.018) 392321 −0.355 −0.087 0.018 −0.047 0.337 0.087 −0.001 0.002 (0.235) (0.005) (0.019) (0.033) (0.232) (0.009) (0.012) (0.011) 392329 −0.185 0.021 −0.071 0.026 0.207 −0.04 0.017 0.007 (0.32) (0.049) (0.038) (0.015) (0.315) (0.049) (0.014) (0.014) 392330 0.006 0.036 0.008 −0.016 0.007 −0.035 −0.004 0.01 (0.177) (0.012) (0.013) (0.015) (0.172) (0.014) (0.011) (0.01) 392390 0.009 0.14 −0.03 −0.002 −0.013 −0.145 0.02 0.004 (0.026) (0.005) (0.018) (0.028) (0.019) (0.015) (0.023) (0.027) 392620 −0.029 −0.016 0.031 0.036 0.048 0.01 −0.03 −0.012 (0.03) (0.06) (0.035) (0.042) (0.027) (0.063) (0.038) (0.03) 392690 0.069 −0.019 −0.032 0.032 −0.042 0.001 0.046 −0.027 (0.024) (0.037) (0.026) (0.032) (0.02) (0.037) (0.027) (0.032) 401511 0.075 −0.014 −0.186 −0.384 0.016 0.036 0.096 −0.091 (0.78) (0.051) (0.034) (0.062) (0.76) (0.031) (0.041) (0.042) 401519 −0.078 0.044 −0.084 −0.032 0.029 −0.037 0.022 −0.028 (0.026) (0.028) (0.038) (0.037) (0.023) (0.023) (0.027) (0.025) 401590 0.399 0.02 −0.054 0 −0.38 0.01 0.044 0.053 (0.475) (0.042) (0.047) (.) (0.461) (0.026) (0.049) (0.037) 401699 −0.13 0.043 −1.581 −0.091 0.134 −0.018 1.602 0.019 (0.413) (0.027) (0.748) (0.024) (0.405) (0.014) (0.734) (0.014) 481810 −0.112 −0.053 −0.01 0 0.114 0.025 −0.01 −0.04 (0.075) (0.005) (0.012) (.) (0.073) (0.023) (0.01) (0.01) 481890 0.026 0.011 0 0 −0.026 0.014 0.006 −0.005 (0.024) (0.016) (.) (.) (0.023) (0.013) (0.023) (0.025) 482110 0.011 0.012 −0.847 0.125 −0.008 0.008 0.761 −0.004 (0.011) (0.015) (0.715) (0.011) (0.011) (0.011) (0.703) (0.011) 482190 0.016 0.007 0 0 −0.014 −0.005 0.325 −0.008 (0.013) (0.019) (.) (.) (0.013) (0.017) (0.48) (0.009) 530310 0 0 0 0 0.311 1.697 −0.173 −0.006 (.) (.) (.) (.) (0.462) (0.47) (0.374) (0.003) 530390 0 0 0 0 −0.399 −0.019 0.187 −0.008 (.) (.) (.) (.) (0.661) (0.115) (0.495) (0.005) 551311 0.001 0.105 0 0 −0.007 −0.082 −0.308 0.008 (0.015) (0.26) (.) (.) (0.008) (0.252) (1.157) (0.018) 551312 −1.098 0.548 0 0 0.995 −0.464 1.161 −0.015 (0.693) (0.824) (.) (.) (0.656) (0.801) (3.252) (0.047) 551313 −0.439 −0.815 0 0 0.398 0.817 −0.598 0.057 (0.829) (0.763) (.) (.) (0.783) (0.741) (2.534) (0.045) 551319 0 −11.961 0 0 −1.118 11.739 −4.541 0.023 (.) (5.914) (.) (.) (2.535) (5.751) (6.45) (0.125) 551321 −0.887 0.552 0 0 0.908 −0.525 0.169 0.009 (0.358) (0.654) (.) (.) (0.343) (0.647) (1.132) (0.032) 551323 0.194 2.377 0 0 −0.105 −2.28 5.032 0.091 (0.719) (0.837) (.) (.) (0.703) (0.812) (3.268) (0.031) 551329 −0.15 1.81 0 0 0.11 −1.736 5.598 0.004 (1.11) (0.873) (.) (.) (1.047) (0.851) (2.725) (0.018) 551331 −0.072 0.922 0 0 0.043 −0.87 −1.477 0.021 (0.58) (0.383) (.) (.) (0.555) (0.373) (2.063) (0.017) 551339 −0.033 2.869 0 0 0.174 −2.825 −1.12 0.013 (0.937) (1.163) (.) (.) (0.882) (1.137) (3.606) (0.027) 551341 0.365 0.721 0 0 −0.451 −0.737 0.474 0.028 (0.36) (0.711) (.) (.) (0.34) (0.693) (1.841) (0.014) 551349 0.965 −1.427 0 0 −0.742 1.31 −0.067 0.129 (1.297) (1.77) (.) (.) (1.256) (1.716) (4.435) (0.041) 560311 −0.033 0.011 0.023 0.002 0.034 −0.018 −0.004 −0.01 (0.026) (0.036) (0.023) (0.02) (0.024) (0.041) (0.02) (0.017) 560312 −0.038 −0.181 0.088 −0.006 0.033 0.176 −0.069 −0.031 (0.037) (0.163) (0.041) (0.041) (0.035) (0.159) (0.041) (0.037) 560313 0.01 −0.01 0.283 0 0.004 0.03 −0.253 −0.001 (0.019) (0.018) (0.716) (.) (0.018) (0.02) (0.703) (0.01) 560314 −0.001 0.009 0.004 −0.024 −0.004 −0.007 −0.012 −0.016 (0.02) (0.019) (0.043) (0.024) (0.019) (0.025) (0.041) (0.02) 560391 −0.008 −0.208 −0.061 0 −0.004 0.246 −0.071 −0.002 (0.032) (0.075) (0.101) (.) (0.03) (0.083) (0.04) (0.024) 560392 −0.01 (0.023) −0.027 (0.04) −0.032 (0.042) 0.029 (0.058) 11 0.012 (0.022) 0.043 (0.041) 0.017 (0.041) −0.015 (0.016) 560393 0.016 0.546 0.295 0 −0.024 −0.519 −0.307 0.002 (0.021) (0.453) (0.751) (.) (0.021) (0.441) (0.74) (0.014) 560394 0.03 0.047 −0.296 0 −0.021 −0.035 0.266 0.018 (0.027) (0.03) (0.968) (.) (0.026) (0.035) (0.958) (0.019) Table A1: Estimated trade policy coefficients by product (continued) Direct effects Indirect effects Product Import-restricting Import-facilitating Export-restricting Export-facilitating Import-restricting Import-facilitating Export-restricting Export-facilitating 560410 −0.013 0.33 0 0 0.036 −0.301 −0.035 0.001 (0.033) (0.613) ( .) (.) (0.033) (0.593) (1.227) (0.025) 560600 −0.028 0.782 0 0 0.03 −0.747 −0.206 −0.017 (0.024) (1.08) ( .) (.) (0.022) (1.046) (1.041) (0.019) 590700 0.047 0.043 −0.257 0 −0.056 −0.006 0.557 −0.005 (0.032) (0.059) (0.996) (.) (0.031) (0.059) (0.991) (0.019) 600240 −0.059 0.943 0 0 0.078 −0.902 0.917 0.017 (0.076) (0.741) ( .) (.) (0.073) (0.721) (1.865) (0.02) 600290 −0.755 0.052 0 0 0.8 −0.017 3.317 −0.007 (0.804) (0.6) ( .) (.) (0.801) (0.588) (2.089) (0.045) 611300 −0.115 0.003 −1.386 −0.321 0.114 −0.006 1.585 0.021 (0.055) (0.041) (0.925) (0.034) (0.053) (0.023) (0.927) (0.029) 611420 0.039 −0.069 0.251 −0.064 −0.014 −0.027 −0.386 0.124 (0.1) (0.08) (0.146) (0.096) (0.091) (0.064) (0.143) (0.077) 611430 0.053 0.002 0.053 −0.084 −0.051 −0.023 −0.064 0.011 (0.028) (0.025) (0.038) (0.033) (0.027) (0.017) (0.033) (0.022) 611490 0.021 −0.161 1.073 0 −0.123 0.09 −1.164 0.056 (0.104) (0.068) (2.502) (.) (0.098) (0.063) (2.507) (0.097) 611610 −0.533 −0.026 0.037 −0.028 0.573 0.028 −0.027 −0.001 (0.193) (0.022) (0.02) (0.026) (0.19) (0.015) (0.02) (0.023) 621010 0.002 −0.044 0.086 −0.176 −0.003 0.054 −0.059 0.026 (0.028) (0.04) (0.059) (0.055) (0.027) (0.028) (0.049) (0.037) 621020 0.017 0.059 −0.64 0 −0.034 −0.051 0.618 0.05 (0.062) (0.057) (2.05) (.) (0.058) (0.042) (2.043) (0.046) 621030 −0.006 −0.042 0 0 −0.086 0.013 3.246 0.105 (0.041) (0.041) (.) (.) (0.042) (0.017) (1.544) (0.166) 621040 −0.028 0.02 0.053 0.05 0.037 −0.008 −0.072 −0.041 (0.031) (0.037) (0.049) (0.038) (0.027) (0.031) (0.049) (0.021) 621050 −0.036 0.009 0.053 −0.157 0.026 −0.013 −0.055 0.051 (0.049) (0.035) (0.064) (0.047) (0.046) (0.026) (0.064) (0.03) 621132 0.223 0.048 0.064 −0.028 −0.177 −0.008 −0.129 0.04 (0.065) (0.047) (0.068) (0.074) (0.063) (0.039) (0.064) (0.057) 621133 0.009 −0.013 0.099 0.026 −0.005 0.003 −0.086 −0.042 (0.02) (0.025) (0.046) (0.034) (0.019) (0.021) (0.038) (0.02) 621139 0.025 −0.012 −4.218 −0.156 −0.054 0.057 4.136 0.004 (0.087) (0.07) (3.645) (0.12) (0.081) (0.065) (3.653) (0.093) 621142 0.023 0.073 −0.019 −0.129 0.062 −0.003 −0.006 0.006 (0.07) (0.073) (0.07) (0.084) (0.063) (0.052) (0.07) (0.07) 621143 0.054 0.044 −0.032 −0.101 −0.035 −0.04 −0.121 0.014 (0.058) (0.067) (0.108) (0.048) (0.056) (0.039) (0.11) (0.042) 621149 0.069 0.121 0.15 −0.317 −0.109 −0.011 −0.017 0.06 (0.057) (0.066) (0.156) (0.124) (0.054) (0.047) (0.114) (0.039) 621600 −0.085 −0.015 0.061 0.24 0.074 0.011 −0.036 0.052 (0.551) (0.046) (0.065) (0.083) (0.538) (0.033) (0.055) (0.063) 621790 0.224 1.948 5.537 0 −0.115 −1.816 −5.514 0.117 (0.075) (2.197) (3.045) (.) (0.061) (2.164) (3.015) (0.054) 630790 0.069 0.042 0.106 0.055 −0.056 0.008 −0.06 −0.075 (0.029) (0.124) (0.036) (0.046) (0.032) (0.124) (0.038) (0.032) 650610 −0.009 0.04 0 0 −0.009 −0.014 1.039 −0.004 (0.013) (0.032) (.) (.) (0.012) (0.03) (0.864) (0.01) 701090 −0.16 −0.16 0.355 0.04 0.171 0.148 −0.295 0.006 (0.441) (0.013) (0.851) (0.022) (0.426) (0.014) (0.838) (0.02) 701710 −0.041 −0.01 0 0 0.034 −0.015 −0.023 0.034 (0.841) (0.042) (.) (.) (0.823) (0.033) (0.031) (0.044) 701720 1.324 −0.021 0 0 −1.316 0.014 0.007 0.011 (0.823) (0.03) (.) (.) (0.796) (0.021) (0.025) (0.027) 701790 −0.498 −0.001 0.031 0 0.468 0.001 −0.04 0.055 (0.589) (0.027) (0.019) (.) (0.572) (0.015) (0.019) (0.02) 721790 0.021 0.07 −3.108 0 −0.009 −0.07 3.095 0.04 (0.019) (0.824) (1.408) (.) (0.028) (0.784) (1.399) (0.034) 732690 0.002 0.036 −0.926 −0.045 0.007 −0.05 0.947 0.008 (0.022) (0.011) (0.901) (0.017) (0.022) (0.014) (0.892) (0.01) 760410 −1.067 −0.209 0 0 1.042 0.197 −1.453 −0.015 (0.438) (0.607) (.) (.) (0.433) (0.597) (0.831) (0.012) 760429 0.057 −0.81 0 0 −0.049 0.788 1.916 −0.001 (0.026) (0.62) (.) (.) (0.026) (0.608) (0.787) (0.01) 761699 0.121 −0.154 −2.024 −0.043 −0.089 0.162 2.028 0.014 (0.08) (0.016) (2.219) (0.028) (0.079) (0.028) (2.167) (0.026) 830990 0.104 0.044 0.273 0.042 −0.099 −0.052 −0.277 −0.001 (0.01) (0.014) (1.114) (0.016) (0.012) (0.017) (1.096) (0.014) 841391 0.043 −0.308 0.037 −0.046 −0.022 0.305 −0.031 0.017 (0.021) (0.05) (0.041) (0.034) (0.019) (0.053) (0.036) (0.016) 841830 0.003 0.061 0 0 −0.008 −0.057 1.364 0.007 (0.016) (0.021) (.) (.) (0.015) (0.031) (0.685) (0.012) 841840 −0.019 −0.668 0 0 0.01 0.613 −1.818 0.026 (0.012) (0.416) (.) (.) (0.007) (0.397) (1.753) (0.011) 841869 0.01 0.015 0.413 −0.034 −0.016 −0.006 −0.383 0.014 (0.012) (0.011) (0.242) (0.01) (0.012) (0.008) (0.237) (0.01) 841920 −0.895 −0.468 −0.062 0 0.887 0.486 0.061 −0.06 (0.398) (0.103) (0.029) (.) (0.389) (0.105) (0.029) (0.026) 841989 −0.015 −0.198 −3.304 −0.026 0.003 0.196 3.278 0.008 (0.02) (0.096) (1.819) (0.039) (0.023) (0.094) (1.787) (0.018) 842129 −0.005 0.008 0.076 0 −0.009 0.013 −0.072 0.028 (0.011) (0.009) (0.436) (.) (0.011) (0.011) (0.431) (0.01) 842139 −0.076 0.198 −2.179 0 0.027 −0.155 2.179 0.025 (0.027) (0.023) (1.163) (.) (0.022) (0.028) (1.148) (0.015) 842199 −0.016 0.029 −0.557 −0.023 −0.004 −0.005 0.557 0.011 (0.016) (0.015) (0.779) (0.02) (0.012) (0.017) (0.768) (0.01) 842230 0.473 0.138 0.027 −0.063 −0.449 −0.105 −0.05 0.04 (0.608) (0.047) (0.036) (0.039) (0.59) (0.049) (0.023) (0.034) 847982 0.006 0.072 −0.694 −0.044 −0.005 −0.054 0.623 0.005 (0.018) (0.011) (1.24) (0.018) (0.017) (0.017) (1.202) (0.015) 847989 0.003 −0.012 0.037 −0.017 0.004 0.011 −0.012 −0.001 (0.019) (0.018) (0.026) (0.045) (0.019) (0.02) (0.012) (0.019) 854370 0.014 0.011 −0.623 −0.085 −0.023 −0.004 0.636 0.045 (0.015) (0.014) (0.558) (0.764) (0.015) (0.016) (0.545) (0.747) 12 Table A1: Estimated trade policy coefficients by product (continued) Direct effects Indirect effects Product Import-restricting Import-facilitating Export-restricting Export-facilitating Import-restricting Import-facilitating Export-restricting Export-facilitating 900490 −0.034 −0.017 0.104 −5.211 0.008 0.057 −0.082 5.104 (0.053) (0.306) (0.041) (3.215) (0.029) (0.3) (0.04) (3.182) 901812 −0.035 −0.026 0.027 −0.015 0.055 0.004 −0.009 0.029 (0.465) (0.028) (0.019) (0.037) (0.451) (0.014) (0.016) (0.034) 901819 0.884 0.004 0.003 0.07 −0.881 0.006 0.008 −0.035 (0.642) (0.038) (0.021) (0.056) (0.624) (0.014) (0.016) (0.04) 901831 0.01 0.001 −0.077 0.022 −0.012 −0.009 0.066 −0.025 (0.024) (0.022) (0.019) (0.032) (0.02) (0.018) (0.018) (0.029) 901832 −0.017 0.069 −0.019 0.051 0 −0.047 0.018 −0.082 (0.023) (0.051) (0.02) (0.051) (0.022) (0.053) (0.017) (0.043) 901839 0.013 −0.026 −0.019 −0.001 0.003 0.036 0.016 −0.017 (0.016) (0.046) (0.013) (0.026) (0.013) (0.046) (0.014) (0.024) 901890 0.035 −0.014 0.003 −0.034 −0.048 0.031 −0.001 0.019 (0.016) (0.027) (0.013) (0.029) (0.022) (0.031) (0.016) (0.027) 901920 0.045 −0.01 0.055 0.986 −0.012 0.002 −0.031 −1.003 (0.015) (0.017) (0.023) (0.832) (0.014) (0.009) (0.017) (0.83) 902000 −0.108 0.057 −0.019 0.921 0.129 −0.043 0.01 −0.926 (0.29) (0.024) (0.015) (0.74) (0.279) (0.026) (0.015) (0.735) 902212 −0.392 −0.011 0 1.63 0.426 0.02 0.068 −1.554 (0.293) (0.021) (.) (0.727) (0.287) (0.019) (0.024) (0.725) 902214 0.121 0.01 −0.026 0.036 −0.071 −0.032 −0.01 −0.057 (0.169) (0.015) (0.01) (0.418) (0.164) (0.014) (0.01) (0.411) 902511 0.216 −0.32 0 0 −0.198 0.319 −0.008 −0.977 (0.231) (0.384) (.) (.) (0.228) (0.371) (0.016) (0.563) 902519 −0.301 0.031 0.014 0 0.284 −0.027 −0.029 2.364 (0.19) (0.005) (0.02) (.) (0.186) (0.009) (0.015) (0.523) 902720 0.014 −0.061 −0.445 0 −0.011 0.059 0.44 −0.807 (0.198) (0.296) (0.427) (.) (0.197) (0.296) (0.426) (0.524) 902780 0.13 −0.008 −0.002 0.01 −0.121 0.019 0.006 −0.007 (0.118) (0.005) (0.004) (0.258) (0.117) (0.006) (0.003) (0.256) 902790 0.049 −0.069 −0.371 −0.66 −0.054 0.062 0.384 0.666 (0.258) (0.02) (0.373) (0.441) (0.255) (0.021) (0.37) (0.439) 903289 −1.355 0.008 −0.579 −0.048 1.413 0.04 0.677 0.047 (0.773) (0.012) (1.735) (0.027) (0.771) (0.017) (1.677) (0.026) 13