The Economic Effects of Potential EU Tariff Sanctions on Russia – A Sectoral Approach

Latipov, Olim; Lau, Christian; Mahlstein, Kornel; Schropp, Simon Article The Economic Effects of Potential EU Tariff Sanctions on Russia – A Sectoral Approach Intereconomics Suggested Citation: Latipov, Olim; Lau, Christian; Mahlstein, Kornel; Schropp, Simon (2022) : The Economic Effects of Potential EU Tariff Sanctions on Russia – A Sectoral Approach, Intereconomics, ISSN 1613-964X, Springer, Heidelberg, Vol. 57, Iss. 5, pp. 294-305, https://doi.org/10.1007/s10272-022-1074-1 This Version is available at: https://hdl.handle.net/10419/267129 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/4.0/ Intereconomics 2022 | 5 294 Sanctions DOI: 10.1007/s10272-022-1074-1 Intereconomics, 2022, 57(5), 294-305 JEL: F1, F51 Olim Latipov, Christian Lau, Kornel Mahlstein and Simon Schropp* The Economic Eff ects of Potential EU Tariff Sanctions on Russia – A Sectoral Approach As part of its sanctions regime, the United States recently announced the imposition of punitive import tariff s on 570 product groups from Russia. The European Union may follow suit and enact sanctions on Russia that mirror the US sanctions in scale and scope. Using a sector-specifi c partial-equilibrium model, we quantify the impact of such mirror sanctions. We fi nd they would infl ict on Russia welfare losses of at least $996 million per year – at an overall cost of $150 million to EU consumers. Breaking down these totals in a sectoral analysis, we fi nd that mirroring the US action would produce mixed results from the EU’s perspective. On the one hand, tariff sanctions cover a number of sectors whose inclusion would infl ict particularly large welfare losses for Russia and/or high welfare gains for the EU. On the other hand, mirror sanctions would bring signifi cant ineffi ciencies for the EU. For example, in 72 sectors, higher tariff s would infl ict greater harm on the EU than on the Russian economy, causing EU losses in excess of $560 million. Thus, consistent with the spirit of international coordination and alignment, the EU may consider adjusting the suite of tariff sanctions rather than simply adopting the US package. Olim Latipov, Sidley Austin LLP, Geneva, Switzerland. Christian Lau, Sidley Austin LLP, Geneva, Switzerland. Kornel Mahlstein, Sidley Austin LLP, Geneva, Switzerland. Simon Schropp, Sidley Austin LLP, Washington, DC; and The George Washington University, Washington, DC, USA. © The Author(s) 2022. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). Open Access funding provided by ZBW – Leibniz Information Centre for Economics. * All opinions expressed in this paper are the authors’ and refl ect neither the views of their employers nor the clients they represent. The authors would like to thank Anson Soderbery for guidance and support. At the 2022 G7 Summit in Germany, leaders agreed to “coordinate” and “align” actions involving extra tariff measures on imports from Russia in response to Russia’s invasion of Ukraine. G7 members pledged to “continue our targeted use of coordinated sanctions for as long as necessary, acting in unison at every stage” (G7 Research Group, 2022a).1 During the G7 Summit, the United States announced plans to signifi cantly increase tariff rates on hundreds of Russian products (White House, 2022). Effective 27 July 2022, Presidential Proclamation 10420 raised applicable tariff s on 570 product groups2 imported from Russia to 35% ad valorem (Federal Register, 2022). Given the stated intention of “alignment”, “acting in unison at every stage” and “unprecedented coordinated sanction measures” pervading the G7 Summit (G7 2022a; 2022b), it appears likely that other countries will follow the United States’ lead and soon impose steep tariff increases on Russian import products. This paper engages in a thought experiment. We examine the eff ects of the European Union, as one of the United States’ closest allies on Russia sanctions, aligning itself with the United States not just by enacting similar tariff measures, but by imposing “mirror” sanctions, i.e. applying the same 35% ad valorem tariff on the same 570 prod1 This proposed action by G7 is the latest in a growing list of economic sanctions imposed on Russia by a coalition of over 40 countries in response to its aggressive war on Ukraine. For an up-to-date overview of Russia-related sanctions, see, e.g. the resources maintained by Sidley Austin LLP (n.d.). 2 In this paper, we use the terms “product group” and “sector” interchangeably. ZBW – Leibniz Information Centre for Economics 295 Sanctions uct groups.3 Using a sector-by-sector partial-equilibrium framework, we quantify the economic eff ects that such mirror sanctions would have on the Russian economy, as well as on the EU economy itself.4 We then assess the sanctions list at the product level and evaluate the consequences of including certain sectors in the EU mirror sanctions package. This paper is purely descriptive in that we analyse tariff increases on the same 570 product groups initially selected by the United States. Our results should not be read as recommendations on adding or dropping certain product groups, or as suggestions for designing an alternative EU retaliation package, which always involves additional, non-economic considerations.5 Methodology of the model and its application to potential mirror sanctions by the EU We apply a proprietary model and software designed by the Economic Analysis Unit of Sidley Austin LLP.6 The tool consists of a series of bilateral partial-equilibrium models between (groups of) exporters and (groups of) importers. The model is based on a standard Armington-type framework of international trade in which products are diff erentiated by source country, and consumers view products from diff erent countries as imperfect substitutes. The model also considers exporter and importer market power (the “large-country” assumption), thus enabling us to quantify potential terms-of-trade gains for the sanctioning country. For each product group included in the latest US tariff sanction package (and therefore in the hypothesised EU mirror sanctions), a system of equations can be solved with information on (i)pre-sanction trade data, (ii)the size of the extra tariff shock (in percentage points) and (iii)the relevant elasticities. The model is implemented by using 2021 trade fl ow data from the World Bank’s World Integrated Trade Solution System as the pre-sanction base3 We do not opine on the probability of the EU enacting import sanctions that exactly mirror in scale and scope those imposed by the United States. We take note of the above-quoted pledges to act “in unison at every stage” by the seven most powerful democracies (G7 Research Group, 2022a), but are not aware of any offi cial statement as to what such coordination among the G7 and with other allies would look like in practice. In that sense, our assumption of the EU imposing mirror sanctions is one of many policy scenarios. 4 This paper does not engage in an analysis of the eff ects of the new US tariff sanctions on the US and Russian economies. The interested reader is referred to a previous paper by the authors on that issue (Latipov et al., 2022). 5 Our assessment is guided purely by economic considerations. We appreciate that the issue of sanction design may equally be driven by political exigencies and opportunities. However, a discussion of political rationales is beyond the scope of this article. 6 Further details about the model, its methodology and data sources used are available in Latipov et al. (2022). line.7 As usual for this class of models, the quality of the results is critically determined by the quality of the elasticity estimates. We use elasticity estimates for import demand and export supply compiled by Soderbery (2018), which are particularly comprehensive and also available for specifi c country pairs. Since Soderbery (2018) does not provide for elasticity estimates for the EU as a bloc, we apply estimates for Germany (as the largest EU economy and Russia’s largest European trading partner). This implies that economic eff ects on Russia reported in this paper are likely underestimated, while welfare losses (gains) to the EU are likely overestimated (underestimated).8 The following economic metrics are of particular interest to our analysis: Trade aff ected: This metric describes the pre-sanction trade value that is impacted by the tariff increase. This metric is not an expression of economic eff ects per se, but it can be seen as an approximate measure of the economic relevance that a certain product group has both for the EU and for Russia. Blocked trade/decoupling: This metric captures the import value (as a percentage of pre-sanction imports) that is interrupted as a result of the tariff increases. While it is not an expression of welfare eff ects, it is a useful metric to express the level of economic decoupling between the EU and Russia that occurs in a given product group as a result of the new tariff sanctions. Terms-of-trade gains: Whenever the importer (EU) has a suffi cient degree of market power vis-à-vis an exporter, the exporter (Russia) must absorb part of the tariff incidence by lowering its prices. Such lowering of export prices (“pass-through”) improves the importing country’s terms of trade (i.e. the relative price at which the countries exchange goods and services) to the same degree that it worsens the exporting country’s terms of trade. Multiplied with post-sanction import values, Russia’s terms-of-trade losses measure the reduced export value of those Russian sales that still occur after the tariff increase has gone into eff ect. Compared to the pre-sanction situation, export 7 Our model treats the EU as one trade bloc. We appreciate that economic integration with Russia diff ers signifi cantly between the individual EU members. Analyses on the country level are available, but not presented here. 8 The EU as an economic bloc is more powerful than Germany is on its own. Moreover, depending on the specifi c tariff lines, certain EU members may have more importer power than Germany. Consequently, EU members collectively constitute a larger and more powerful export region (from Russia’s perspective). Hence, Russian export supply elasticities vis-à-vis all EU members are likely steeper, and EU import demand elasticities vis-à-vis Russia fl atter than Germany’s alone. Higher welfare losses to Russia, and higher welfare gains to the EU are then a likely consequence. Intereconomics 2022 | 5 296 Sanctions sales occur at a lower price. These “income eff ects” represent a pure net wealth transfer from Russia to the EU. Tariff revenue: Tariff revenue is the tariff rate times the import value that still enters the ally’s market after the sanction has been imposed.9 One part of tariff revenues constitutes the share of tariff revenue paid by Russian exporters on account of its terms-of-trade losses (see previous paragraph), while another is a domestic net wealth transfer between consumers and the government of the sanctioning country. Total welfare eff ect to the EU: Importer welfare eff ects are quantifi ed as the diff erence between the potential termsof-trade gains (described above) and effi ciency losses suff ered by the importing economy from ineffi ciently small import volumes. Total welfare eff ects to the EU can be positive or negative, depending on the market power of the EU for the specifi c import good, the importance of the good to the EU economy, and the size of the tariff hike. Total welfare losses to Russia: Russia as the exporting country is certain to lose from higher EU import tariff s. Economic harm to Russia is calculated as the sum of terms-of-trade losses (described above) and effi ciency losses stemming from ineffi ciently low export volumes and the unfavorable resource reallocation within the Russian economy that ensues. Our model is operationalised on the sectoral level, either on the 4or 6-digit aggregation level of the Harmonized System (HS). The US tariff increases (and thus the EU mirror sanctions) are, however, defi ned for 570 sectors at the HS8-digit level. This requires us to aggregate the US target list to the HS 6-digit level. The aggregation reduces the number of distinguishable sectors from 570 9 Note that this metric measures total tariff revenues collected by the EU after the imposition of its new tariff sanctions. This is diff erent from additional, or extra tariff revenues, a fi gure that results from subtracting pre-sanction tariff revenues from those collected after the new sanctions are imposed. to 393 individual product groups. The inevitable reduction in granularity likely makes our model over inclusive of reported trade fl ows, because the model may include product groups that would not be actually subject to the EU mirror sanctions on the HS 8-digit level, but are swept into a particular product group on the HS 6-digit level. Moreover, we lack reliable elasticity estimates for 83 further sectors and so are able to apply the model (i.e. quantify welfare results) to a total of 310 individual product groups.10 Due to these missing observations (and despite the over-inclusiveness that results from the aggregation of target sectors to the HS 6-digit level mentioned above), the economic eff ects we report throughout will most likely underestimate the overall economic impacts of the new EU sanctions, discussed below. Results Table 1 summarises the aggregate economic eff ects that would result from the application of the described tariff increases on hundreds of product groups. In total, EU mirror tariff s would aff ect trade worth $10.8billion per year (column (1)), which represents roughly 6.1% of all 2021 EU imports from Russia (or 20.4% of all non-energy imports). We estimate that these tariff s would reduce trade in aff ected sectors by 63% (column (2)). Moreover, they would cause annual terms-of-trade losses of $596million and welfare losses of $996million to Russia (columns (3) and (6), respectively). At the same time, they would cost EU consumers $150million (column (5)), and generate tariff revenue amounting to $883million per year (column (4)). The second row of Table 1 summarises the economic effects of the original US tariff sanctions on the US and Russian economies. Overall, US tariff increases are estimated to aff ect trade worth $2.68billion per year, and reduce trade in the aff ected sectors by 62%. Furthermore, across 10 The 83 “missing” product groups together accounted for pre-sanction (2021) imports from Russia worth $666million (or roughly 6% of all targeted imports). Table 1 Total economic eff ects of tariff sanctions on Russia, the European Union and the United States Source: Authors’ own calculation. (1) (2) (3) (4) (5) (6) Ally imposing sanctions Trade aff ected (ally’s imports from Russia) (US $1000) Blocked trade/Decoupling (% of pre-sanction imports of aff ected product groups, weighted average) Terms-of-trade gain to ally (US $1000) Tariff revenue (based on 35% tariff , US $1000) Welfare eff ect on ally (US $1000) Welfare loss for Russia (US $1000) EU 10,842,398 63 596,521 883,420 -150,111 -995,976 US 2,677,683 62 97,632 205,066 -97,701 -184,901 Total EU and US 13,520,081 694,153 1,088,486 -247,812 -1,180,877 ZBW – Leibniz Information Centre for Economics 297 Sanctions the universe of target sectors, new US sanctions will infl ict Russian welfare losses amounting to $185million per year and cause welfare losses to the United States’ own economy of $98million. Comparing the economic impact generated by (actual) US versus (hypothetical) EU sanctions, we note that mirror sanctions by the EU would have more “bite”, on account of the much larger trade relationship between Russia and the EU. Aff ected trade and welfare losses to Russia are nearly four times those of the US sanctions. The “cost share” of sanctions – the ratio of self-harm (column (5)) to harm on Russia (column (6)) – is nearly 53% for the United States, while it is only 15% for the EU.11 In other words, the United States pays a signifi cantly higher price, in relative terms, for its sanctions than the EU would pay. The last row of Table 1 summarises the economic eff ects reported for the EU and the United States. Concerted action by the United States and the EU would infl ict welfare losses to Russia of at least $1.18 billion. Estimates for 11 Mathematically, the cost share is strictly positive and only works for situations in which both Russia and the sanctioning country incur negative wealth eff ects. The closer the cost share is to zero percent, the more preferable for the sanctioning ally. combined harm on Russia must be seen as the lower end of the actual eff ects. First, the eff ects reported in Table 1 are estimated for individual, not joint, action by the United States and the EU, respectively. If both allies were to combine forces and become one large export region (from Russia’s perspective), they would exercise even higher purchasing power vis-à-vis Russian exports.12 However, in the current model we have not modifi ed supply and demand elasticity estimates that would refl ect such joint market power. Second, as mentioned, we are unable to report eff ects for all 393 product groups on account of missing elasticity data. Evidently, results for any additional sector would only increase Russian welfare losses.13 Given that potential mirror sanctions by the EU would signifi cantly boost the effi ciency of US action, one might expect the United States to have a keen interest in convincing the EU to join it in imposing sanctions. But would following suit by imposing mirror sanctions also be in the EU’s best interest? This question cannot be answered merely by looking at the aggregate eff ects presented in Table 1. Totals can mask important dynamics that occur 12 For an explanation of underlying economic mechanisms, see footnote 8. 13 See footnote 10. Table 2 Top ten economically signifi cant sectors and their eff ects Note: The list contains top ten product groups in terms of trade aff ected. Source: Authors’ own calculation. (1) (2) (3) (4) (5) (6) (7) (8) (9) HS 6-digit code Description (abbreviated) Trade aff ected (US $1000) Passthrough to EU consumers (%) Blocked trade (%) Tariff revenue (US $1000) Terms-oftrade gains to EU (US $1000) Welfare eff ect on EU (US $1000) Welfare eff ect on EU (%) Welfare loss for Russia (US $1000) Welfare loss for Russia (%) 720712 Semi-fi nished products of iron or non-alloy steel 3,092,181 71 100 0 0 -385,624 -12 -155,507 5 440712 Fir (Abies spp.) and spruce (Picea spp.) 845,467 33 32 153,482 133,573 117,647 14 -165,487 20 390210 Polypropylene, in primary forms 633,094 36 37 93,126 72,991 61,043 10 -94,295 15 401110 New pneumatic tyres, of rubber, of a kind used for motor cars 523,019 47 37 84,299 52,892 38,907 7 -68,452 13 440719 Coniferous wood 384,160 33 32 69,739 60,693 53,456 14 -75,193 20 440131 Wood pellets 297,461 72 74 24,497 7,585 -20,144 -7 -18,336 6 760612 Plates, sheets and strip, of aluminium alloys 273,314 55 43 37,870 19,418 10,622 4 -26,598 10 440711 Pine (Pinus spp.) 262,338 33 32 47,624 41,446 36,504 14 -51,349 20 400219 Styrene-butadiene rubber 216,592 80 98 1,186 258 -29,477 -14 -7,789 4 400220 Butadiene rubber BR 216,528 80 98 1,186 258 -29,468 -14 -7,786 4 Subtotal (top ten product groups) 6,744,154 513,007 -146,534 -670,792 Total (all 570 product groups) 10,842,398 883,420 -150,111 -995,976 Share (%) 62 58 98 67 Intereconomics 2022 | 5 298 Sanctions at the sectoral level. Below, we therefore present several observations resulting from our product-level analysis that can shed light on whether, and to what degree, the EU may wish to sign on to the United States’ selected sanctions package. Comment1: Top ten target sectors generate nearly twothirds of total economic eff ects As a matter of fi rst impression, we note that despite the fact that the sanctions package selected by the United States covers 570 product groups (which we model as 393 HS 6-digit line items), only a handful of targeted product groups generate the bulk of economic eff ects. Table 2 lists the top ten product groups in terms of “trade aff ected” by EU mirror sanctions. These ten sectors collectively would cover 62%, or $6.7billion, of all aff ected EU imports (column (1)), cause $670million, or 67%, of total Russian welfare losses (column (8)), and generate self-harm to the EU of $147million, or 98% of total damages (column (6)).14 The fl ipside of this observation then is that the remaining product groups together cover considerably fewer imports from Russia and generate smaller total eff ects than the ten sectors listed in Table 2. Comment2: Certain target sectors infl ict particularly high welfare losses on Russia The EU mirror sanction package contains various product groups, the inclusion of which causes particularly large welfare losses to Russia. Table 3 lists all those product groups for which EU mirror sanctions would infl ict Rus14 The high fi gure of 98% of total EU welfare losses can be explained by the fact that mirror tariff s on several other sectors induce welfare gains for the EU economy. See Comment3. (1) (2) (3) (4) (5) (6) (7) (8) (9) HS 6-digit code Description (abbreviated) Trade aff ected (US $1000) Passthrough to EU consumers (%) Blocked trade (%) Tariff revenue (US $1000) Terms-oftrade gains to EU (US $1000) Welfare eff ect on EU (US $1000) Welfare eff ect on EU (%) Welfare loss for Russia (US $1000) Welfare loss for Russia (%) 440712 Fir (Abies spp.) and spruce (Picea spp.) 845,467 33 32 153,482 133,573 117,647 14 -165,487 20 720712 Semi-fi nished products of iron or non-alloy steel 3,092,181 71 100 0 0 -385,624 -12 -155,507 5 390210 Polypropylene, in primary forms 633,094 36 37 93,126 72,991 61,043 10 -94,295 15 440719 Coniferous wood 384,160 33 32 69,739 60,693 53,456 14 -75,193 20 401110 New pneumatic tyres, of rubber, of a kind used for motor cars 523,019 47 37 84,299 52,892 38,907 7 -68,452 13 440711 Pine (Pinus spp.) 262,338 33 32 47,624 41,446 36,504 14 -51,349 20 760612 Plates, sheets and strip, of aluminium alloys 273,314 55 43 37,870 19,418 10,622 4 -26,598 10 401120 New pneumatic tyres, of rubber, of a kind used for buses 163,556 47 37 26,362 16,540 12,167 7 -21,406 13 440910 Coniferous wood, incl. strips and friezes for parquet fl ooring 134,489 40 66 12,650 9,686 3,540 3 -19,055 14 440131 Wood pellets 297,461 72 74 24,497 7,585 -20,144 -7 -18,336 6 720421 Waste and scrap of stainless steel (excluding radioactive) 154,115 55 55 20,591 11,044 2,959 2 -17,701 11 760429 Bars, rods and solid profi les, of aluminium alloys 153,769 50 42 20,998 12,307 7,873 5 -16,825 11 392020 Plates, sheets, fi lm, foil and strip, of non-cellular polymers of ethylene 91,693 33 40 12,704 10,464 8,725 10 -13,948 15 442199 Articles of wood 98,374 49 56 12,204 7,561 3,076 3 -12,276 12 291612 Esters of acrylic acid 133,953 61 44 19,063 8,291 3,157 2 -11,533 9 Subtotal (selected product groups) 7,240,983 635,207 464,493 -46,091 -767,962 Table 3 Sectors with high absolute welfare losses to Russia Note: The list contains product groups for which EU mirror tariff increases result in Russian welfare losses in excess of $10 million. Source: Authors’ own calculation. ZBW – Leibniz Information Centre for Economics 299 Sanctions sian welfare losses in excess of $10million.15 These sectors together aff ect $7.2billion in 2021 trade (column (1)) and cause losses of $768million to the Russian economy (column (8)).16 At the same time, mirror tariff s on these products cost the EU economy $46million (column (6)). This results in a highly favorable EU cost share of6%. 15 This threshold of $10million in Russian welfare losses is somewhat arbitrary, as are other thresholds introduced below. Their selection is mainly driven by our intention to keep the number of rows in the tables manageable. A Data Appendix, which is available from the authors upon request, contains a full set of sectors and economic eff ects. 16 Note that this list contains some product groups whose inclusion may be seen as problematic (see Comments 4 to 7). Note also that there is signifi cant overlap between this list and that in Table 5 (sectors in which the EU generated particularly high welfare gains). Table 4 contains all product groups for which EU mirror tariff s cause high relative welfare losses to the Russian economy, which we defi ne as losses in excess of 20% of presanction imports to the EU. While nearly half of the product groups listed in Table 4 concern small import volumes of less than $1million (column (1)), total Russian welfare losses for these products amount to a sizable total of $301million (column (8)). Including these sectors even yields total welfare gains for the EU of $214million (see column (6)). Comment 3: Certain target sectors generate positive welfare eff ects for the EU Indeed, the EU mirror sanction package includes numerous sectors for which tariff increases result in substantial welfare (1) (2) (3) (4) (5) (6) (7) (8) (9) HS 6-digit code Description (abbreviated) Trade aff ected (US $1000) Passthrough to EU consumers (%) Blocked trade (%) Tariff revenue (US $1000) Terms-oftrade gains to EU (US $1000) Welfare eff ect on EU (US $1000) Welfare eff ect on EU (%) Welfare loss for Russia (US $1000) Welfare loss for Russia (%) 846229 Bending, folding, straightening or fl attening machines 659 0 0 146 219 219 33 -219 33 840690 Parts of steam and other vapour turbines 1,738 0 0 380 557 557 32 -558 32 491110 Trade advertising material, commercial catalogues and the like 373 19 14 81 91 89 24 -98 26 491191 Pictures, prints and photographs 619 19 14 134 151 148 24 -163 26 381519 Supported catalysts 1,556 14 9 328 388 386 25 -407 26 871680 Vehicles pushed or drawn by hand 2,108 22 20 417 440 425 20 -494 23 844391 Parts and accessories of printing machinery 370 25 39 59 60 54 15 -79 21 490191 Dictionaries and encyclopaedias, and serial instalments thereof 194 24 41 29 31 27 14 -41 21 490110 Printed books, brochures and similar printed matter, in single sheets 735 24 41 111 116 103 14 -156 21 490199 Printed books, brochures and similar printed matter (excluding those in single sheets) 14,361 24 41 2,164 2,259 2,015 14 -3,051 21 846693 Parts and accessories for machine tools for working metal 2,081 25 42 309 309 272 13 -419 20 950510 Christmas articles 495 33 24 98 85 78 16 -98 20 870110 Pedestrian-controlled agricultural tractors 755 29 27 136 126 116 15 -149 20 440711 Pine (Pinus spp.) 262,338 33 32 47,624 41,446 36,504 14 -51,349 20 440791 Oak (Quercus spp.) 15,088 33 32 2,739 2,384 2,099 14 -2,953 20 440712 Fir (Abies spp.) and spruce (Picea spp.) 845,467 33 32 153,482 133,573 117,647 14 -165,487 20 440719 Coniferous wood 384,160 33 32 69,739 60,693 53,456 14 -75,193 20 Subtotal (selected product groups) 1,533,097 277,975 242,928 214,197 -300,915 Table 4 Sectors with high relative welfare losses to Russia Note: The list contains product groups for which EU mirror sanctions result in Russian welfare losses in excess of 20% of pre-sanction imports. Source: Authors’ own calculation. Intereconomics 2022 | 5 300 Sanctions (1) (2) (3) (4) (5) (6) (7) (8) (9) HS 6-digit code Description (abbreviated) Trade aff ected (US $1000) Passthrough to EU consumers (%) Blocked trade (%) Tariff revenue (US $1000) Terms-oftrade gains to EU (US $1000) Welfare eff ect on EU (US $1000) Welfare eff ect on EU (%) Welfare loss for Russia (US $1000) Welfare loss for Russia (%) 440712 Fir (Abies spp.) and spruce (Picea spp.) 845,467 33 32 153,482 133,573 117,647 14 -165,487 20 390210 Polypropylene, in primary forms 633,094 36 37 93,126 72,991 61,043 10 -94,295 15 440719 Coniferous wood 384,160 33 32 69,739 60,693 53,456 14 -75,193 20 401110 New pneumatic tyres, of rubber, of a kind used for motor cars 523,019 47 37 84,299 52,892 38,907 7 -68,452 13 440711 Pine (Pinus spp.) 262,338 33 32 47,624 41,446 36,504 14 -51,349 20 401120 New pneumatic tyres, of rubber, of a kind used for buses 163,556 47 37 26,362 16,540 12,167 7 -21,406 13 760612 Plates, sheets and strip, of aluminium alloys 273,314 55 43 37,870 19,418 10,622 4 -26,598 10 392020 Plates, sheets, fi lm, foil and strip, of non-cellular polymers of ethylene 91,693 33 40 12,704 10,464 8,725 10 -13,948 15 760429 Bars, rods and solid profi les, of aluminium alloys 153,769 50 42 20,998 12,307 7,873 5 -16,825 11 440796 Birch (Betula spp.) 45,490 33 32 8,214 7,099 6,281 14 -8,739 19 440890 Sheets for veneering 35,673 35 29 6,429 5,241 4,643 13 -6,329 18 854430 Ignition wiring sets and other wiring sets for vehicles, aircraft or ships 36,773 34 31 6,329 5,220 4,609 13 -6,382 17 Subtotal (selected product groups) 3,448,346 567,174 437,884 362,478 -555,003 Table 5 Sectors with high absolute welfare gains for the EU Note: The list contains top ten product groups in terms of welfare gains for the EU. Source: Authors’ own calculation. gains to the EU economy. Welfare gains to the EU economy emerge in those sectors in which (i)the EU enjoys market power vis-à-vis Russia (refl ected by low levels of pass-through; column (2)), and (ii)pre-sanction most-favoured-nation tariff s that were set at ineffi ciently low levels as far as Russian imports are concerned. Tariff increases are then economically benefi cial, because the EU can shift much of the economic costs of tariff increases on Russian exporters via terms-oftrade eff ects.17 Table 5 lists the top ten product groups for which EU mirror sanctions result in economic gains (column (6)). These product lines aff ect imports worth $3.45billion and generate welfare gains to the EU economy of $362million, as well as Russian welfare losses of roughly $555million. Comment4: Mirror sanctions would result in blocked trade for 19 sectors Another interesting feature of the EU mirror sanctions is that the application of a 35% tariff would lead to a complete 17 This, of course, is the application of the “optimal tariff ” theory fi rst espoused by Johnson (1953). interruption of import activity from Russia (“blocked trade”) in a number of sectors (Table 6, column (3)). The 19 relevant product groups together aff ect an amount of $3.16billion in EU imports (column (1)). Notable on this list of sectors is one product group (HS720712 Semi-fi nished products of iron or non-alloy steel) for which imposition of EU mirror sanctions would cut off imports worth $3.09billion. If achieving a decoupling of the EU economy from Russian imports were one of the policy objectives pursued by EU policymakers (possibly with the aim of reducing dependency from Russian sources), then the inclusion of these 19 sectors could make sense. However, as Table 6 illustrates, such decoupling comes at a steep economic cost to the EU, resulting in signifi cant absolute welfare losses of $397million (column (6)). At the same time, decoupling also generates relatively high welfare losses (i.e. relative to those in Russia; columns (8) and (9) of Table 6). Full decoupling often results from perfectly elastic (horizontal) Russian export supply curves facing the EU. A horizontal supply curve in a given sector implies that the EU is a “small” import market with no mar- ZBW – Leibniz Information Centre for Economics 301 Sanctions ket power. This enables Russian exporters to fully pass on the EU tariff increase to EU consumers (see “100%” entries in column (2) of Table 6), or to export their goods elsewhere. Russian exporters experience no effi ciency losses. EU consumers, on the other hand, are priced out of the market, thus resulting in zero post-sanction imports (and thus zero tariff revenues for EU members), coupled with signifi cant effi ciency losses to EU consumers. This results in a highly unfavorable EU cost share of 255% across the 19 sectors at issue. Comment5: Targeting economically insignifi cant sectors produces negligible results As mentioned in Comment1, the hypothetical EU mirror sanctions contain hundreds of product groups for which Table 6 Sectors in which EU sanctions result in blocked trade Note: The list contains product groups for which EU mirror sanctions result in full decoupling (100% blocked trade). Source: Authors’ own calculation. (1) (2) (3) (4) (5) (6) (7) (8) (9) HS 6-digit code Description (abbreviated) Trade aff ected (US $1000) Passthrough to EU consumers (%) Blocked trade (%) Tariff revenue (US $1000) Terms-oftrade gains to EU (US $1000) Welfare eff ect on EU (US $1000) Welfare eff ect on EU (%) Welfare loss for Russia (US $1000) Welfare loss for Russia (%) 720712 Semi-fi nished products of iron or non-alloy steel 3,092,181 71 100 0 0 -385,624 -12 -155,507 5 680610 Slag-wool, rock-wool and similar mineral wools 27,182 100 100 0 0 -4,757 -17 0 0 890399 Outboard motorboats, for pleasure or sports 13,332 100 100 0 0 -2,200 -16 0 0 731029 Tanks, casks, drums, cans, boxes 9,790 100 100 0 0 -1,581 -16 0 0 680620 Exfoliated vermiculite, expanded clays, and similar expanded mineral materials 4,999 100 100 0 0 -875 -17 0 0 681099 Articles of cement, concrete or artifi cial stone 4,494 100 100 0 0 -748 -17 0 0 930630 Cartridges for smooth-barrelled shotguns, revolvers and pistols 2,613 100 100 0 0 -426 -16 0 0 392490 Household articles and toilet articles, of plastics 2,228 100 100 0 0 -317 -14 0 0 731010 Tanks, casks, drums, cans, boxes and similar containers, of iron or steel 1,940 100 100 0 0 -313 -16 0 0 480610 Vegetable parchment 1,834 100 100 0 0 -321 -17 0 0 430219 Tanned or dressed furskins 551 100 100 0 0 -93 -17 0 0 400811 Plates, sheets and strip of cellular rubber 275 100 100 0 0 -44 -16 0 0 293299 Heterocyclic compounds with oxygen hetero-atom[s] only 237 65 100 0 0 -22 -9 -12 5 870310 Vehicles for the transport of persons on snow; golf cars 209 75 100 0 0 -22 -10 -7 3 293219 Heterocyclic compounds with oxygen hetero-atom[s] only 95 65 100 0 0 -9 -9 -5 5 680221 Marble, travertine and alabaster articles thereof, simply cut 25 100 100 0 0 -4 -17 0 0 680291 Marble, travertine and alabaster, in any form (excluding tiles) 20 100 100 0 0 -3 -17 0 0 930621 Cartridges for smooth-barrelled shotguns 11 100 100 0 0 -2 -16 0 0 870600 Chassis fi tted with engines, for tractors, motor vehicles 9 7 100 0 0 0 -1 -1 12 Subtotal (selected product groups) 3,162,025 - - -397,361 -155,532