metadata: authors: 0: author: Kee,Hiau Looi
1: author: Nicita,Alessandro
count: World,European Union,United Kingdom
docna: 0: docna: Quantifying Economic Impacts of Trade
            Agreements with Heterogeneous Trade Elasticities
docty: Policy Research Working Paper
abstracts: cdata!: Bilateral trade relationships between
            countries vary across products. Such heterogeneity poses
            challenges when assessing the economic impacts of trade
            agreements. This paper estimates bilateral trade
            elasticities at the product level and explores these impacts
            using a hypothetical no-deal Brexit as an example. The
            findings indicate that the European Union&#x2019;s
            demand for the United Kingdom&#x2019;s products is often
            less elastic compared to products from other trading
            partners. The findings also show substantial heterogeneity
            in the elasticities across products and a negative
            correlation between these elasticities and tariffs. These
            factors mitigate the extent of trade welfare losses compared
            to a scenario using homogeneous elasticities.
display_title: Quantifying Economic Impacts of
            Trade Agreements with Heterogeneous Trade Elasticities
listing_relative_url: /research/2023/12/34212577/quantifying-economic-impacts-trade-agreements-heterogeneous-trade-elasticities
topicv3: Trade Policy and Integration m1327407 775
publishtoextweb_dt: 2023-12-11T00:00:00Z
dois: 10.1596/1813-9450-10634
no_of_pages: 51
author_keys: 0: author_key: 559677
1: author_key: 437023
model_extractions: Policy Research Working Paper 10634 Quantifying Economic Impacts of Trade Agreements with Heterogeneous Trade Elasticities _Hiau Looi Kee Alessandro Nicita_ Development Economics Development Research Group December 2023
Policy Research Working Paper 10634

# **Abstract**

Bilateral trade relationships between countries vary across products. Such heterogeneity poses challenges when assessing the economic impacts of trade agreements. This paper estimates bilateral trade elasticities at the product level and explores these impacts using a hypothetical no-deal Brexit as an example. The findings indicate that the European Union’s demand for the United Kingdom’s products is often less elastic compared to products from other trading partners. The findings also show substantial heterogeneity in the elasticities across products and a negative correlation between these elasticities and tariffs. These factors mitigate the extent of trade welfare losses compared to a scenario using homogeneous elasticities.

This paper is a product of the Development Research Group, Development Economics. 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 hlkee@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
Quantifying Economic Impacts of Trade Agreements with Heterogeneous Trade Elasticities<sup>∗</sup>

**Keywords:** Welfare gains from trade, trade elasticities, Brexit **JEL Classification Numbers:** F10, F14

> ∗We thank James Anderson, David Baqaee, Chad Bown, Lorenzo Caliendo, Alonso de Gortari, Svetlana Deminova, Rob Feenstra, Penny Goldberg, Beata Javorcik, Aaditya Mattoo, Paul Romer and participants in the World Bank’s Policy Research Talk for feedback and comments. Alejandro Feraros provides excellent research assistance. Research for this paper has in part been supported by the World Bank’s Multidonor Trust Fund for Trade and Development. The authors declare that they have no relevant or material financial interests that relate to the research described in this paper. The results and opinions presented in this paper do not represent the views of our institutions, the Executive Directors, or the countries they represent.

> †Development Research Group, The World Bank; 1818 H ST NW, Washington, DC 20433. Tel: 1-202-473 4155; Fax: 1-202-522 1159; Email: hlkee@worldbank.org.

> ‡United Nations Conference on Trade and Development, Switzerland. Email: Alessandro.Nicita@un.org
# **1 Introduction**

One of the reasons for a country to join a trade agreement is the potential welfare gains from trade.<sup>1</sup> Trade agreements may also foster deeper ties among the partnering countries, which may further amplify the welfare gains from trade.<sup>2</sup> On the flip side, do we expect larger welfare loss when countries with closer ties withdraw from existing trade agreements or face higher tariffs? Quantifying the potential impacts of existing trade agreements requires detailed knowledge of how trade may respond to trade policy changes given the specific trading relationship of these partnering countries in different industries. In other words, to study the trade and welfare impacts of existing trade agreements, we need partner country specific trade elasticities. These estimates do not exist.

The objective of this paper is to fill the gap in the literature regarding the productlevel trade elasticities with bilateral variations. As an application, this paper studies a hypothetical No-Deal Brexit. We first estimate the detailed bilateral trade elasticities of the European Union (EU) with respect to imports from its top 100 trading partners, including the United Kingdom (UK), at the HS 6-digit level.<sup>3</sup> We then evaluate the welfare and trade impacts, based on these trade elasticity estimates. While the actual Brexit is governed by the Trade and Cooperation Agreement between the EU and the UK, which came into effect in 2022 and provides for free trade in goods, findings based on a No-Deal Brexit are still informative as they provide a clean policy experiment to isolate the impacts of sudden tariff hikes on trade and welfare losses of countries that are closely linked through existing

> 1Standard trade models have emphasized that when countries specialize in producing and exporting products according to their comparative advantage, there may be efficiency and consumption gains. See Krugman, Obstfeld and Melitz (2022) for a textbook treatment.

> 2See World Bank (2020) and Fernandes, Kee and Winkler (2022).

> 3In this paper we estimate import demand elasticities, which is the percentage change in quantity imported with respect to a one percent change in import price. The (negative) import demand elasticity equals trade elasticity when prices and quantities of other products are held fixed. See Section A1 of the Appendix for the proof. Throughout this paper, we use the terms import demand elasticities and trade elasticities interchangeably when there is no confusion.

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trading relationships. In addition, the findings could be timely and relevant in other similar instances, such as in quantifying the trade effects of the ongoing US-China trade tensions, or the current Russian Federation-Ukraine war.

To assess the economic impacts of trade agreements, this paper adapts the partial equilibrium approach of Feenstra (1995), which is a simplification of Anderson and Neary (1992). This approach is rich in product and country level heterogeneity, and does not depend on the modeling choices, preference and production structures. We show that trade and welfare impacts depend on the size of the country specific trade elasticities, as well as the correlation between the elasticities and the tariffs. Our approach complements a general equilibrium gravity framework, which takes into account substitution of products and changes in income. These models are rich in the general equilibrium effects, often assume homogeneous trade elasticites across countries, with some models also assume heterogeneous elasticities across industries.<sup>4</sup> Our analysis shows that in a No-Deal Brexit, the exports from the UK to the EU would decrease by 6.4 percent while the welfare losses to both the EU and the UK, measured in terms of their GDPs, would be less than 1 percent. These impacts are tapered by the relatively low EU-UK specific trade elasticity estimates, as well as the negative correlation between the EU-UK specific trade elasticities and the EU’s tariffs. Without accounting for heterogeneous elasticities, the trade losses would have been higher, resulting in approximately a 7.8% decline.

Our findings of heterogeneous elasticities collaborate well with some recent studies. The heterogeneous elasticity estimates across products are consistent with the findings of Imbs and Mejean (2017). The low EU-UK elasticity estimate is consistent with the findings of Chen and Novy (2022) and de Gortari (2019), who show that bilateral trade is less sensitive

> 4For general equilibrium models with industries heterogeneity, see Melitz and Redding (2015), Caliendo and Parro (2015).

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to trade costs if the exporting country provides a larger share of the destination country’s imports, and the trading of specialized inputs which are less elastic. The inherent market power of the EU as it pertains to the UK’s products may also contribute to the low bilateral demand elasticity, as shown in Juarez (2023), based on evidence from Colombia. Soderbery (2021) takes a similar general approach as this paper, except his focus is on heterogeneous pass-through rates across countries and how trade impacts are shaped by importer market power. The result of negative correlation between tariffs and elasticities speak to Caliendo and Feenstra (2022) and the classic optimal tariff models showing that the relationship between tariffs and elasticities could affect the welfare gains from trade.<sup>5</sup> In addition, our results are validated by several robustness checks. First, we find larger trade and welfare losses when we replace the heterogeneous elasticities with the homogeneous elasticities. This is because the estimated EU-UK trade elasticities are about 30 percent lower than the homogeneous EU elasticities across all trading partners. Ex ante, smaller elasticities imply smaller losses, and the homogeneous elasticities remove the negative correlation between tariffs and trade elasticities, which pushes up losses. Next, we find that using different elasticity estimates from the existing literature does not qualitatively change our results. Then, we reshuffle the heterogeneous elasticities in such a way that there is no correlation between tariffs and elasticities. In this case, the welfare and trade impacts are much larger, demonstrating the importance of considering the possibility of correlation between tariffs and elasticities. We also further break down the trade and losses to the industry level. The results suggest lower losses for the machinery and transport equipment sectors, which are more integrated between the EU and the UK.<sup>6</sup>

> 5Empirical evidence supporting the optimal tariff theory can be found in Broda, Limao and Weinstein (2008), who estimate export supply elasticities at a disaggregated level and find strong evidence that importing countries set higher tariffs on products that face inelastic export supply. Here in this paper we focus on estimating import demand elasticities and studying how the correlation between these elasticities and tariffs may affect the calculations of the gains from trade.

> 6In the Appendix, we further extend our analysis to include some general equilibrium forces such as the

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This paper contributes to several strands of trade literature. First, it builds on the theoretical framework of Anderson and Neary, to show that heterogeneous trade elasticities affect welfare and trade calculations when there is any correlation between trade elasticity and tariffs.<sup>7</sup> Second, this paper relates to the empirical literature on quantifying the impact of trade agreements, by focusing on the micro-level evidence of tariffs and elasticities and building the overall impacts from the ground up.<sup>8</sup> Third, this paper contributes to the optimal tariffs literature by estimating the empirical relationship between tariffs and elasticities.<sup>9</sup> Finally, this paper contributes to research analyzing the trade impacts of trade agreements, such as Brexit.<sup>10</sup> Rather than predicting trade by using gravity models, this paper uses bilateral trade elasticity estimates to quantify the impacts, which prove to be relevant.

The paper proceeds as follows. Section 2 presents the trade elasticity estimations. Section 3 provides a description of the data used in the analysis. Section 4 presents the results of the elasticity estimation. Section 5 describes the theoretical framework. Section 6 presents the trade and welfare impacts of a No-Deal Brexit, while Section 7 presents the robustness checks. Section 8 concludes. Mathematical derivations and details are in the Appendix.

availability of substitutes, input-output linkages, as well as the positive income effects due to the increase in tariff revenues. Including these general equilibrium channels do not alter the overall results of this paper which lend credibility to our partial equilibrium approach for our current context.

> 7Anderson and Neary (1992, 1994, 1996, 2003 and 2007), Feenstra (1995).

> 8Melitz and Redding (2015), Caliendo and Parro (2015) and Ossa (2015).

> 9Broda, Limao and Weinstein (2008); Bagwell and Staiger (2011).

10Baldwin (2016), Bloom and Mizen (2017), Dhingra, Huang, Ottaviano, Sampson and Van Reenen (2016), Gudgin, Coutts, Gibson and Buchanan (2017), and Lawless and Morgenroth (2019). Specifically, for general equilibrium models, Dhingra, Huang, Ottaviano, Pessoa, Sampson, and Van Reenen (2016) find that Brexit could lower the UK’s income by 2.3 percent. The partial equilibrium approach taken by Lawless and Morgenroth (2019), based on sector level median elasticity estimates from Imbs and Mejean (2017), finds that Brexit may result in significantly different impacts across countries and sectors.

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# **2 Estimating Trade Elasticities**

## **2.1 Translog GDP Function Approach**

The estimating framework of this paper is based on the translog GDP function approach.<sup>11</sup> This approach has the following advantages. First, it allows the construction of bilateral trade elasticities at the product level for each trading partner. The differences in market power across countries may cause differences in trade elasticities. This implies that trade elasticities could have bilateral variations and may be partner country specific. We can thereby evaluate the trade impact of Brexit without imposing homogeneous trade elasticities across trading partners. The second advantage is that the translog GDP function relies not only on the variations in tariffs, but also the variations in unit values to estimate trade elasticities. Nearly 25 percent of HS 6-digit products imported by the EU face zero MFN tariff throughout the sample period which provides neither time series nor cross sectional variations in data. By taking into account the variations of the unit values, this approach permits the retention of these products in the estimation of trade elasticities. Finally, this approach allows to correct for the potential selection and endogeneity biases using a multistep methodology developed in Semykina and Wooldridge (2010).

The translog GDP function was first derived by Diewert (1974) and was adapted to an international setting by Kohli (1978, 1991) to estimate the US aggregate import demand and export supply functions. Harrigan (1997) incorporated productivity into the GDP function to study the impact of productivity and endowment in affecting the international specialization of the OECD countries at a sectoral level. Subsequently, Kee, Nicita and Olarreaga (2008) built on these works to estimate import elasticities at a disaggregate HS 6-digit product level

> 11 Alternatively, one could run a cross sectional gravity regression of bilateral imports on bilateral tariffs, controlling for importer and exporter fixed effects. The estimated coefficient on tariffs is the aggregate trade elasticity. See ACR (2012) for details.

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for a wide range of countries. For the current application, we explicitly introduce the ad valorem tariffs into the GDP function, and thus allow tariffs to affect the imports of products in GDP through product prices.<sup>12</sup> Let’s denote ln _G_<sup>_t_</sup> ( _p_<sup>_t_</sup> _, v_<sup>_t_</sup> ) as the translog GDP function of a small open economy, facing ad valorem tariff-inclusive price, _p_<sup>_t_</sup> _,_ factor endowment, _v_<sup>_t_</sup> _,_ with _n_ and _k_ index goods, and _m_ and _l_ index factors:<sup>13</sup> For each period, _t,_ the net output vector _q_<sup>_t_</sup> = ( _q_ 1<sup>_t, q_</sup> 2<sup>_t, ..., q_</sup> _N_<sup>_t_) is chosen to maximize GDP, with</sup> positive elements denoting outputs, which include exports, and negative numbers denoting inputs, which include imported goods as in Kohli (1991).

To reduce the number of translog parameters, we apply a semiflexible functional form developed by Diewert and Wales (1988) to reparametrize ln _G_<sup>_t_</sup> ( _p_<sup>_t_</sup> _, v_<sup>_t_</sup> ) so that ln _G_<sup>_t_</sup> ( _p_<sup>_t_</sup> _, v_<sup>_t_</sup> ) satisfies homogeneity and symmetry restrictions, with respect to prices and factor endowments. The Envelope theorem implies that, at the equilibrium, the share of good _n_ in GDP at period _t_ is Note that if good _n_ is an input, as in the case of imports, then _s_<sup>_t_</sup> _n_<sup>_<_0isthenegativeshare</sup> of _n_ in GDP, while if good _n_ is an output, such as exports, then _s_<sup>_t_</sup> _n_<sup>_>_0isthepositiveshare</sup>

> 12Please refer to Feenstra (2015) for standard textbook treatments of the GDP function approach.

> 13The exposition below closely follows Kee, Nicita and Olarreaga (2008). Please refer to Section A4 of the Appendix.

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of _n_ in GDP. In Equation (2) _,_ ln _p_<sup>_t_</sup> _k_<sup>=�</sup> _k_ = _n_ ~~∑~~ _ka_ = _<u>kn</u>_<sup>_ak_ln</sup><sup>_p_</sup> _k_<sup>_t_isaweightedaverageofthelog</sup> prices of all non- _n_ goods. For every good _n,_ ln _p_<sup>_t_</sup> _k_<sup>can be constructed using the GDP deflator</sup> net of the price of good _n,_ adjusted by the share of non- _n_ goods,<sup>14</sup> This approximation introduces an additive error term to reflect measurement error in each share equation, _κ_<sup>_t_</sup> _n_<sup>:</sup> Equation (4) forms the basis to estimate the translog parameter, _ann_ , which is used to construct the own-price elasticity, _εnn,_ Please note that _εnn_ is also the (negative) trade elasticity when the prices and quantities of other goods are held constant.<sup>15</sup> Likewise, the cross-price elasticity for good _−n_ is:

> 14Caves, Christensen and Diewert (1982).

> 15Please refer to Section A1 of the Appendix for the proof.

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# **2.2 Econometric Issues**

There are a number of issues that needs to be addressed. The first involves the endogeneity of tariff-inclusive relative prices. Following Equation (4), we regress the share of each good _n_ on their tariff-inclusive relative prices and the endowments of the EU, where the share of each good _n_ is constructed based on the trade value of each HS 6-digit good from each trading partner, relative to the GDP of the EU. In this specification, the tariff-inclusive relative prices of HS 6-digit products, ln _pp−_<sup>_<u>tt</u>_</sup> _<u>ndn</u>_<sup>_,_couldbeendogenoustotheshareofeach</sup> good, _s_<sup>_t_</sup> _nd_<sup>,whichcouldleadtoinconsistentestimates.Moreover,ifthesmallopeneconomy</sup> assumption is violated, an increase in tariffs may also cause foreign prices to change and affect ln _<u>p</u>_<sup>_t_</sup> _<u>nd</u>_<sup>Toaddresstheseendogeneityissues,weusethetariff-inclusiverelativepriceofthe</sup> _p−_<sup>_<u>t</u>_</sup> _n_<sup>.</sup> United States (US), ln _pp−_<sup>_<u>tt</u>_</sup> _ndn,US,US_<sup>_,_astheinstrumentinaFixedEffectsTwoStageLeastSquare</sup> (FE-2SLS) regression. The identification assumption is that relative prices are affected by common shocks: while the price of a product in the EU and the US could be correlated due to the world market conditions, the share of each good in the GDP of the EU should not be correlated with the trade policy and prices of the US a priori. One of the reasons the US prices and the EU prices are correlated is because they faced the common exogeneous shocks, such as productivity/technology, and climate/weather/natural disaster/pandemic, as well as China shocks and the wars in other countries. These exogeneous events affect product prices in the world markets hence caused the US and EU prices to move together. At the same time the US prices should not be affecting or influenced by the share of UK products in the EU’s imports; hence, they are consistent with the exclusion restrictions and acceptable as 8
an instrumental variable for the EU prices: _p_<sup>_t_</sup> _<u>nd p</u>_<sup>_t_</sup> _<u>nd</u>_ where ln<sup>�thepredictedvalueoflnthefirststageregression,Equation</sup> _p−_<sup>_<u>t</u>_</sup> _n_<sup>denotes</sup> _p−_<sup>_<u>t</u>_</sup> _n_<sup>from</sup> (8) _._ The dependent variable in the second stage regression is the share of the imported product in the GDP of the EU (which is by construction negative or zero). The right-hand side variables include the predicted tariff-inclusive relative price of this product, the relative endowments of the EU, together with year fixed effects _a_<sup>_n_</sup> _t_<sup>and exporting country fixed effects</sup> _a_<sup>_n_Equation(9)formsthebase-lineforourelasticityestimates.</sup> 0 _d_<sup>.</sup> The second econometric issue is the potential selection bias due to EU imports being not random. In fact, it is well documented that international trade is often highly concentrated (Helpman, Melitz and Rubinstein, 2008). Within our sample of bilateral imports of the 5000 HS 6-digit level products between the EU and its top 100 partners, nearly 75 percent of the product-exporting country observations are zeros, while the UK exports nearly all but 200 products to the EU. The issue of sample selection bias cannot be ignored. To correct for sample selection, we use a multi-step sample selection model for panel data, developed in Semykina and Wooldridge (2010). This approach is particularly suitable for panel data with endogenous right-hand-side variables and unobserved heterogeneity that can be controlled by panel fixed effects. Semykina and Wooldridge (2010) also provide a selection bias test which allows us to identify products that need such corrections.

To test for selection bias, we define a dummy variable, _Dnd_<sup>_t_thatindicatesthepresence</sup> 9
of trade for each HS 6-digit product, _n,_ in year _t,_ from exporting country, _d,_ In other words, _Dnd_<sup>_t_=1ifcountry</sup><sup>_d_exportsproduct</sup><sup>_n_totheEU;and</sup><sup>_D_</sup> _nd_<sup>_t_=0ifcountry</sup> _d_ does not export product _n_ to the EU.<sup>16</sup> We then apply the following procedure: First, for each HS 6-digit product _n_ and each year _t_ , we run a cross sectional probit regression: where the dependent variable equals one if there is non-zero trade between the EU and the partner country in that year, and zero otherwise. The right-hand-side variables of this probit regression include _znd_<sup>_t,_and</sup><sup>_z_ ̄</sup><sup>_nd._Matrix</sup><sup>_z_</sup> _nd_<sup>_t_represents all the exogenous right-hand-side</sup> variables and instruments, which are the tariff-inclusive relative price of the product in the US and the relative endowments. The variable _z_ ̄ _nd_ represents the cross years averages of the tariff-inclusive relative price of the US for product _n_ coming from partner country _d,_ and the cross years average relative endowments of the EU. The resulting estimates are used to obtain the inverse Mills ratio, _λ_<sup>ˆ</sup><sup>_t_</sup> _nd_<sup>=</sup><sup>_λ_</sup> � _znd_<sup>_tδ_ˆ</sup><sup>_t_+ ̄</sup><sup>_zndζ_ˆ</sup><sup>_t_�</sup> = _φ_ � _znd_<sup>_tδ_ˆ</sup><sup>_t_+ ̄</sup><sup>_zndζ_ˆ</sup><sup>_t_�</sup> _/_ Φ � _znd_<sup>_tδ_ˆ</sup><sup>_t_+ ̄</sup><sup>_zndζ_ˆ</sup><sup>_t_�</sup> _,_ with _φ_ ( _._ ) and Φ ( _._ ) denoting the pdf and cdf of a normal distribution.

Second, for _Dnd_<sup>_t_=1</sup><sup>_,_thetariff-inclusiverelativepriceoftheproductintheUSandthe</sup> inverse Mills ratio are then used as instruments to estimate the following FE-2SLS regression 16Please refer to Section A5 of the Appendix on how relative prices could determine zero trade.

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for every product, _n_ : Third, we use the t-statistic with heteroskedasticity robust standard error to test _H_ 0 : _ρ_ = 0. Selection bias is present if _ρ_ is tested to be statistically significant.

For the products that have non-zero trade and for which the selection bias has tested positive, we correct for such bias by using the tariff-inclusive relative price of the US, the partner country average tariff-inclusive relative price of the US, and average relative endowments as instruments in the following Pooled 2SLS regression: where _x_ ̄ denotes the average value of _x._ Note that in this pooled 2SLS specification, partner country fixed effects are replaced with country averages in both the first and second stages.

Finally, given the assumption that products from different exporting countries are differentiated, each of these HS 6-digit-exporter pairs should have unique translog parameters, _ann_ and _cnm_ . However, there are only 8 years of data for each HS 6-digit-exporter pair, which is too limited in terms of degrees of freedom. Thus, for each HS 6-digit product, we pool 11
across all exporting countries and years to implement the above specification, by estimating the average _ann_ and _cnm_ for all exporting countries. Specifically, let each _n_ represent an HS 6-digit product, and _n_<sup>_′_</sup> represent the same HS 6-digit product from an exporting country. Then each country’s unique _an′n′_ is _ann_ plus a mean-zero error term, _κ_<sup>_t_</sup> 2 _n_<sup>_′_.Likewise,</sup><sup>_cn′m_is</sup> _cnn_ plus a mean-zero error term, _κ_<sup>_t_</sup> 3 _n_<sup>_′_:17</sup> The above specification is possible because the error terms _κ_<sup>_t_</sup> 2 _n_<sup>_′_and</sup><sup>_κt_</sup> 3 _n_<sup>_′_arenotcorrelated</sup> with relative prices and endowments.

# **3 Data**

The analysis of this paper uses HS 6-digit panel data sets which consist of the EU’s MFN ad valorem tariffs and trade with its 100 top trading partners for the period between 2010 and 2017. Using panel data allows elasticities estimates to be based on variation both across countries and across time. One advantage of using panel data is that it allows us to obtain estimates in cases where there is insufficient tariffs’ variation in the cross section setup or for HS-6 digit products with no consistent trade throughout the sample period.

Trade and tariff information originate from the World Bank World Integrated Trade Solution (WITS). The World Bank’s World Development Indicators provides the data on endowments and GDP. Table 1 presents some summary statistics of the EU trade policies with respect to products from the UK, under the assumption of MFN ad valorem tariffs

> 17 The error terms are mean-zero because we are estimating the average _ann_ for each product _n_ .

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between the EU and the UK.<sup>18</sup>

# **4 Results: Bilateral Elasticity Estimation**

This section discusses bilateral trade elasticity, constructed from the estimated translog � parameter, _ann_ : We restrict the estimated elasticities to be non-positive as well as winsorize to drop the outliers. Missing elasticity estimates are replaced with the averages within the exporting partner country and product groups.<sup>19</sup> Overall, the bilateral trade elasticities for the UK appear to be well estimated. The average first stage F-statistic is 12.38, while the average t-statistic for the estimated bilateral elasticity is -2.60. Table 2 summarizes the results for the exports from the UK. The sample average import elasticity estimate for an HS 6-digit product imported from the UK to the EU is -13.9, with a sample median of -1.76 and a standard deviation of 38.8. This indicates that there is a wide range of trade responsiveness across all products, which highlights the importance of allowing trade elasticities to vary across products when calculating trade

> 18The EU MFN tariff schedule includes ad valorem tariffs and specific duties. The conversion from specific duties to ad-valorem tariffs is automated in WITS and relies on reference prices (world prices) and price elasticities, both of which may not be representative of EU-UK trade. Therefore, the analysis of this paper discards the products subject to specific duties (about five percent of HS-6 digits products).

> 19Thus, for each product _n,_ the difference in bilateral elasticities across trading partners is due to the difference in the share of these partners in the GDP of the EU, _snd_ . However, this does not imply that partner countries with a larger share will face a less elastic import demand in the EU, since _a_ � _nn_ could be positive or negative empirically. Specifically,

> If _a_ � _nn > s_<sup>2</sup> _nd_<sup>_,_then</sup><sup>_<u>∂ε</u>_</sup> _∂s_<sup>_<u>nnd</u>_</sup> _nd_<sup>_<_0</sup><sup>_,_implyingthatanexportingcountrywithasmallershareinmagnitude(given</sup> that _snd <_ 0) will face a more elastic demand in the EU (given that _εnnd <_ 0) _._ The converse is also true. If _a_ � _nn < s_<sup>2</sup> _nd_<sup>_,_then</sup><sup>_<u>∂ε</u>_</sup> _∂s_<sup>_<u>nnd</u>_</sup> _nd_<sup>_>_0</sup><sup>_,_whichimpliesthatanexportingcountrywithasmallersharein</sup> �<sup>magnitude</sup> (given that _snd <_ 0) will face a less elastic demand in the EU ( given that _εnnd <_ 0) _._ The size of _ann_ depends on the regressions and could be positive or negative empirically.

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impacts and the welfare gains from trade. For comparison purposes, our import weighted average elasticity is 3.9, similar to the trade elasticity estimate of Simonovska and Waugh (2014) of 4.

The results also indicate heterogeneity of elasticities across trading partners, with a median elasticity of -20 and standard deviation of 70. In fact, relative to the rest of the exporting countries, the import demand for UK products is found to be less elastic. Column (1) of Table 3 formally tests the hypothesis that all partner countries have the same elasticity for each HS 6-digit product and the hypothesis was rejected with high t-statistics. On average, the elasticity of the UK is 30 percent lower than that of the other exporting countries for the same HS 6-digit product. This differential is statistically and economically significant, which highlights the importance of estimating bilateral trade elasticities, rather than imposing the same elasticities across all trading partners. UK-EU relatively small trade elasticities are consistent with Novy (2013) and Chen and Novy (2022) who find that bilateral trade is less sensitive to trade costs if the exporting country provides a larger share of the destination country’s imports.<sup>20</sup> In addition, the inherent market power of the EU as it pertains to UK’s products could also lead to lower bilateral demand elasticities.<sup>21</sup>

> 20As a robustness check for the results of substantially lower elasticities for the UK we run a series of gravity regressions excluding one exporting country at a time. Results show that excluding the UK from the regression significantly increases the magnitude of the coefficient on distance, implying that the UK faces a lower elasticity in the EU than other exporting countries. Please refer to Section A6 of the Appendix for details.

> 21Soderbery (2021) takes a similar general approach as this paper, except his focus is on heterogeneous pass-through rates across countries and how trade impacts are shaped by importer market power. Please also refer to Juarez (2023) for evidence relating importer market power to low pass-through elasticity, based on evidence from Colombia.

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# **5 Theoretical Framework**

## **5.1 The Bilateral Trade Restrictiveness Index**

To show how heterogeneous elasticities may affect welfare calculations, we build on the Trade Restrictiveness Index (TRI) framework developed by Anderson and Neary (1994, 1996). For any importing country, with different trade policies on different products, the TRI is the uniform tariff equivalent that would generate welfare or dead-weight loss at the observed levels. Feenstra’s (1995) simplification of TRI is a linear approximation around the equilibrium without imposing any preference structure which proves to be convenient. Kee, Nicita and Olarreage (2007) adapt Feenstra’s approach to construct the multilateral-TRI for a wide range of countries. In Section A2 of the Appendix, we derive the bilateral-TRI of the EU (indexed by _c_ ) with respect to imports from the UK (indexed by _d_ ). Then with some algebraic manipulations, we show that the bilateral-TRI can be decomposed into the following 3 terms:<sup>22</sup> where _τ_ ̄ _cd_ , _σcd_<sup>2and</sup><sup>_ρ_2</sup> _cd_<sup>aretheaveragetariff,thevarianceoftariffs,andthecovariance</sup> between tariffs and trade elasticity, respectively.<sup>23</sup> Equation (15) indicates that the TRI will be higher if the bilateral tariffs have a higher average, a large variance or a high correlation with the bilateral trade elasticity. Thus, if trade elasticity is homogeneous, then the TRI only depends on import weighted average tariffs and the variance of tariffs.<sup>24</sup> It is straightforward to write the deadweight loss (DWL) of trade policy in terms of the

> 22Both the tariff and the TRI are expressed in ad valorem terms as x/(1+x). See Section A2 of the Appendix for details.

> 23Please refer to Section A2 of the Appendix for the definitions of these variables.

> 24Please note that in this paper, we used the term heterogeneity to refer to the differences in the bilateral product level import demand elasticities. This is in contrast to the existing papers which often use a single homogeneous elasticity for all products and all trading partners. Differences in tariffs will affect DWL and welfare calculations through _σcd_<sup>2,whichisthevarianceoftariffs.</sup>

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decomposition of the TRI:<sup>25</sup> where _Mcd ≡_<sup>�</sup> _n_<sup>_pncdqncd_isthetotalimportsof</sup><sup>_c_from</sup><sup>_d,_and</sup><sup>_ε_ ̄</sup><sup>_cd_istheimportweighted</sup> average import elasticity, which is negative by definition. Therefore, the higher is the average tariff, or the variance of tariffs, or the covariance between tariffs and elasticity, the larger is the magnitude of the DWL. Conversely, if the average tariff is lower, or the variance of tariffs is lower, or if higher tariffs are levied on less elastic products, then an increase in tariffs will generate a smaller welfare loss.<sup>26</sup> Equation (16) shows that heterogeneous trade elasticity will affect the welfare calculation through its correlation with the tariffs, _ρ_<sup>2</sup> _cd_<sup>.Let’sdefinethefirsttermof(16)asthe</sup> Tariff-Induced DWL, and the second term of (16) as the Heterogeneity-Induced DWL. If trade elasticities are homogeneous, then the DWL equals the Tariff-Induced DWL, and the Heterogeneity-Induced DWL is zero. If trade elasticities are positively correlated with tariffs, then the DWL is larger than the Tariff-Induced DWL in magnitude, and the HeterogeneityInduced DWL is negative. Conversely, if trade elasticities are negatively correlated with tariffs, then the DWL is smaller than the Tariff-Induced DWL in magnitude, and the Heterogeneity-Induced DWL is positive.<sup>27</sup>

> 25See Section A2 of the Appendix.

> 26Please note that a positive deadweight loss is a welfare loss. It effectively measures the price effect of a tariff increase.

> 27Please refer to the Proposition 1 in Section A2 of the Appendix for the relationship between DWL and the heterogeneity in trade elasticities.

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# **5.2 The Bilateral Overall Trade Restrictiveness Index**

To show how heterogeneous elasticities may affect trade impact calculations, we build on the multilateral Overall Trade Restrictiveness Index (OTRI) framework, developed by Kee, Nicita and Olarreaga (2009), based on the Mercantilist Trade Restrictiveness Index of Anderson and Neary (2003). For any importing country, with different trade policies on different products, the OTRI is the uniform tariff equivalent that would generate imports at the observed levels. Here, we define the OTRI as the uniform ad valorem tariff of country _c_ (the EU) with respect to imports from country _d_ (the UK), facing bilateral tariff _τcd._ In Section A3 of the Appendix, we derive and decompose the bilateral-OTRI into the following two terms: where _τ_ ̄ _cd_ and _ρcd_ are the average tariff and the covariance of tariffs and the negative trade elasticity, respectively.<sup>28</sup> From Equation (18), it is evident that the OTRI is higher when the bilateral trade policy of _c_ on products from _d_ has a higher average or a high correlation with the bilateral trade elasticity. Unlike the TRI, the OTRI is not affected by the variance of tariffs.

It is straightforward to write the trade impact of trade policy in terms of the decomposition of the OTRI:<sup>29</sup> Thus, the higher is the average tariff, or the covariance between tariffs and trade elasticity,

> 28Please refer to Section A3 of the Appendix for the definitions of these variables.

> 29See Section A3 of the Appendix.

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the greater is the magnitude of the trade impact of the restrictive trade policy. Conversely, if the average tariff is lower, or if tariffs and trade elasticities are negatively correlated, then moving from free trade to restrictive trade between _c_ and _d_ will generate a smaller trade loss. Equation (19) shows the trade impact for the UK is affected by the correlation between heterogeneous trade elasticities and tariffs. Let’s define the first term of (19) as the Tariff-Induced trade impact, and the second term of (19) as the Heterogeneity-Induced trade impact. If trade elasticities are homogeneous, then the trade impact equals the Tariff-Induced trade impact, and the Heterogeneity-Induced trade impact is zero. If trade elasticities are positively correlated with tariffs, then the trade impact is larger than the Tariff-Induced trade impact in magnitude, and the Heterogeneity-Induced trade impact is negative. Conversely, if trade elasticities are negatively correlated with tariffs, then the trade impact is smaller than the Tariff-Induced trade impact in magnitude, and the Heterogeneity-Induced trade impact is positive.<sup>30</sup> In the empirical section, we construct TRI and OTRI to calculate the DWL and trade impact resulting from the increase in tariffs between the EU and the UK in the event of a NoDeal Brexit. Moreover, we decompose the DWL and trade impact into various components to assess how the presence of heterogeneous elasticities may affect the results.

# **6 Trade and Welfare Impacts of a No-Deal Brexit**

Based on the heterogeneous elasticity estimates, the first column of Table 4 presents the potential TRI, welfare change, OTRI and trade impact on the EU of a No-Deal Brexit. Moving from no tariff to the MFN ad valorem tariff will result in the bilateral TRI to be about 4.41 percent, and may cause the welfare of the EU to drop less than 1 percent, the 30Please refer to the Proposition 2 in Section A3 of the Appendix for the relationship between trade impact and the heterogeneity in trade elasticities.

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equivalent of a loss of US$ 0.55 billion. Likewise, moving from no tariffs to the MFN tariffs will increase the EU’s OTRI with respect to the UK’s products to 2.29 percent, and may cause the EU-UK trade to decrease by 6.38 percent, equivalent to a loss of about US$ 10.2 billion, or less than 1 percent of the UK’s GDP.

The second and third columns of Table 4 present the decompositions of DWL and trade impacts post-Brexit into the part that is induced by tariffs and the part that is induced by the heterogeneity of trade elasticities, according to (16) and (19). The Tariff-Induced DWL and trade impact are found to be larger in magnitude relative to the overall DWL and trade impact, while the Heterogeneity-Induced DWL and trade impact are positive. This is because, for the EU, the covariance between tariff and trade elasticity is negative, meaning higher tariffs are placed on less elastic products, while lower tariffs are placed on more elastic products.<sup>31</sup> The resulting positive heterogeneity-induced impacts reduce the overall sizes of welfare and trade loss. This case nicely provides the empirical support for Propositions 1 and 2 of Sections A2 and A3 of the Appendix when _ρcd <_ 0 _._ Ignoring the Heterogeneity-Induced welfare change and trade impact leads to biases in the overall changes.

Finally, the EU’s relatively inelastic import demand for products from the UK implies that other countries, including developing or transition economies, may not be affected in a significant way. The EU in the short run will continue to import products from the UK despite the higher tariffs, so there may not be large trade diversion to other countries. However, in the long run, firms may relocate to countries that face lower or no tariffs in the EU market, such as Ireland and Poland. That may result in larger trade and welfare

> 31This is an empirical finding with good theoretical justifications rooted in the optimal tariff model: in order to minimize deadweight loss, countries with market power will levy higher tariffs on products that have lower elasticities, leading to the negative correlation. However, this negative correlation between tariff and elasticity does not always hold empirically. Regression results show that, controlling for exporter fixed effects and HS 6-digit product fixed effects, the partial correlation between the EU’s bilateral applied tariffs and the estimated bilateral elasticities is positive. This implies that the EU tends to impose lower tariffs on less elastic products across trading partners. This is likely due to the EU’s preferential tariffs for developing countries, which tend to export agriculture products that have low elasticities.

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impacts.

# **7 Robustness Checks**

## **7.1 Homogeneous Elasticities**

The first robustness test is to compute trade and welfare effects assuming homogeneous elasticities across the EU’s trading partners. This is done by setting the UK elasticities equal to the mean across all countries within the same HS 6-digit product. The results are presented in Table 5. Given that on average, the elasticity facing the UK’s exports to the EU is 30 percent smaller than the sample mean, this results in larger trade and welfare losses and highlights the important of using UK specific bilateral trade elasticities.

The second robustness check is to compare the resulting trade and welfare effects with those obtained using homogeneous elasticities across products. The results are presented in Table 6. In Column (1), we assume that for all products, the elasticity is equal to the import weighted average elasticity of the sample, which is -3.85. In this case, the TRI and OTRI are 4.60 percent and 2.81 percent, respectively. Because of the homogeneous trade elasticity, there is no covariance between tariffs and elasticity, the overall welfare and trade changes are exactly equal to the Tariff-Induced welfare and trade changes of Table 4.<sup>32</sup> Columns (2) and (3) of Table 6 show the results by setting the homogeneous trade elasticity to -4 and -8, values commonly assumed in the existing literature. In both cases, the levels of TRI and OTRI remain the same as the first column, despite differences in the levels of homogeneous elasticity. This is because with the homogeneous elasticities, the

> 32This finding provides the empirical support for Propositions 1 and 2 of Sections A2 and A3 of the Appendix. The result further demonstrates the upward bias (in magnitude) for the calculations of the overall welfare and trade impacts assuming homogeneous trade elasticities when in fact there is a negative correlation between tariff and elasticity.

20
levels of TRI and OTRI only depend on tariffs, according to Equations (15) and (18).<sup>33</sup> However, welfare and trade changes are larger in magnitude because they increase with size of the average elasticities, according to Equations (16) and (19). This shows that the upward biases are even larger (in magnitude) for the calculations of the overall welfare and trade impacts when the assumed homogeneous trade elasticity is larger.

# **7.2 Different Elasticity Estimates**

As an additional robustness check, we substitute our trade elasticity estimates with the estimates from Caliendo and Parro (2015) and then of Ossa (2015). There are some fundamental differences between these trade elasticity estimates. First, their estimates are at more aggregated sectoral levels: 2-digit ISIC Rev. 3 for Caliendo and Parro (2015) with 20 sectors, and 3-digit SITC for Ossa (2015) with 200 industries. Our elasticity estimates are at the HS 6-digit level for about 5000 products. Second, their elasticity estimates are homogeneous across countries, while ours are specific to each bilateral importer-exporter pair.<sup>34</sup> Finally, the elasticity estimates from Caliendo and Parro (2015), denoted as _θ,_ capture the percentage change in the trade value of a sector with respect to a one percent increase in the tariff, while the elasticity estimates of Ossa (2015), denoted as _σ,_ are defined as the elasticity of substitution from the CES aggregate. Our elasticities, denoted as _ε,_ measure the percentage change in the imported quantity of a product with respect to a one percentage increase in its price. The following relationship holds for these elasticities (ignoring the differences in

> � 2

> 33Equations (15) and (18) can be verified empirically when elasticities are homogeneous: TRI = (0 _._ 046 _/_ 1 _._ 046)<sup>2</sup> = 0 _._ 0019 _. τ_  ̄<sup>2</sup> = (0 _._ 027)<sup>2</sup> = 0 _._ 0007 is the square of the import weighted average of tariff/(1+tariff); _σ_<sup>2</sup> = 0 _._ 0012 _,_ and _ρ_ = 0 _._ Thus, TRI does not depend on the levels of the average homoegeneous  ̄ elasticity. Likewise, OTRI<sup>�</sup> = (0 _._ 028 _/_ 1 _._ 028) = 0 _._ 027 = _τ,_ suggesting that OTRI does not depend on the levels of the average homogeneous elasticity.

> 34For example, Caliendo and Parro (2015) have one elasticity estimate for “Auto” industry for all countries, while we have an elasticity estimate for HS 870332, which is “Vehicles principally designed for the transport of persons (excl. of 87.02 & 8703.10-8703.24), with C-I internal combustion piston engine (diesel/semi-diesel), of a cylinder capacity >1500cc but not >2500cc” imported by the EU from the UK.

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product aggregation and country bilateral variations):<sup>35</sup> To compare the results obtained using these different elasticities, we first aggregate the EU MFN tariff schedule, from the HS 6-digit level to both the corresponding ISIC and SITC levels. We then use these elasticities to calculate TRI, deadweight loss, OTRI and trade impact accordingly, with adjustments based on (21). Columns (4) and (5) of Table 6 present the results. Overall, while these elasticities are fundamentally different, the results are remarkably consistent with trade losses of 5 to 8 percent, and welfare losses of less than 1 percent.

Column (6) of Table 6 presents the result when we purposely reshuffle the heterogeneous trade elasticities to minimize the correlation between trade elasticities and tariffs. This is to show that even with heterogeneous elasticities, if there is no negative correlation between tariffs and elasticities, the welfare and trade impacts calculations will be larger in magnitude: the UK’s potential trade loss from Brexit is around 33 percent, and the EU’s welfare loss is about 1.2 percent. Both of these impacts are larger than the results presented in Table 4 when the empirical negative correlations between tariffs and elasticities are allowed.

# **7.3 Sectoral Impacts**

In this robustness check we show how heterogeneous elasticities result in very diverse sectoral effects. Table 7 presents the sectoral breakdown of the trade impact post-Brexit. The first two columns show the composition of the UK’s exports to the EU by SITC sectors. Nearly 60 percent of the UK’s exports to the EU are in the Machinery and Transport Equipment

> 35Please refer to Section A1 of the Appendix for the proof.

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sector, and the Chemical sector. If these sectors were to face MFN tariffs of about 3 percent, the drop in their exports would be about 1.6 percent to 2.8 percent. These two sectors also have relatively low import elasticities (around -1.6). Across all sectors, there is a negative correlation between MFN tariffs and trade elasticities, which is the reason why the aggregate trade impacts of a No-Deal Brexit are not larger. Thus the sectoral results presented in Table 7 are consistent with the aggregate results presented in Table 4.

# **8 Concluding Remarks**

This paper presents a way to quantify the trade and welfare impacts of trade policy changes, taking into account the heterogeneity in trade elasticities. This is motivated by the empirical observations that bilateral trade between countries tend to respond differently facing trade policy shocks, in part due to the varying trading relationships between these countries. Our partial equilibrium approach is rich in product and country heterogeneity, and complements the existing general equilibrium gravity framework, which often assumes homogeneity across countries in evaluating trade and welfare impacts.

As an illustration, this paper studies a hypothetical No-Deal Brexit, in which the EU was to impose MFN tariffs on products imported from the UK. Trade elasticities are estimated at the detailed product level that vary across the EU’s top 100 trading partners, including the UK. The results show that exports from the UK to the EU would decrease by 6.4 percent, while both the EU and the UK would experience short-run welfare losses of less than 1 percent, measured in terms of their GDP. The impacts would be larger if the trade elasticities are homogeneous. This is because of the low bilateral EU-UK trade elasticities. The negative correlation between the elasticities and the EU’s tariffs further tapers the impacts of a No-Deal Brexit. The findings suggest that an increase in trade barriers between 23
highly interconnected economies may result in lower short-term welfare losses than those suggested by trade models using aggregated data with homogeneous trade elasticities. In this vein, our results would suggest that the current US-China trade disputes with tariff hikes may not impact trade significantly in the short run due to their existing trading relationship. Long-term impacts may involve relocation of firms, which is beyond the scope of the current paper.

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Table 1: Summary Statistics of Trade Policies of EU for a No-Deal Brexit

|MFN ad valorem tarif|%|
|---|---|
|Maximum|74.9|
|Minimum|0|
|Import weighted average|2.95|
|Import weighted variance|15.17|

Table 2: Summary Statistics of the Estimated Trade Elasticities of the EU

||UK|All|
|---|---|---|
|Mean|-13.90|-47.80|
|Median|-1.76|-20.55|
|Standard Deviation|38.81|70.28|
|Maximum|-0.004|-0.000|
|Minimum|-427.60|-444.38|
|Observations|5,050|417,580|

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Table 3: Dependent Variables: Estimated Trade Elasticities

||(1)|
|---|---|
|UK|34.42***|
||(0.57)|
|Constant|-48.21***|
||(0.01)|
|HS 6-digit product FE|Yes|
|Observation|417,580|

Table 4: Potential Short-Run Impact of Brexit

||Overall|Tarif-|Heterogeneity-|
|---|---|---|---|
|||Induced|Induced|
|EU’s Bilateral-TRI wrt the UK (%)|4.41|||
|Welfare change of the EU (%)|-0.34|-0.37|0.03|
|Welfare change of the EU ($B)|-0.55|-0.60|0.05|
|EU’s Bilateral-OTRI wrt the UK (%)|2.29|||
|Trade impact of the UK (%)|-6.38|-7.81|1.43|
|Trade impact of the UK ($B)|-10.2|-12.5|2.28|

Table 5: Robustness Check Using Homogeneous Elasticities Across All Partner Countries

||Overall|Tarif-|Heterogeneity-|
|---|---|---|---|
|||Induced|Induced|
|EU’s Bilateral-TRI wrt the UK (%)|5.20|||
|Welfare change of the EU (%)|-5.52|-4.36|-1.17|
|Welfare change of the EU ($B)|-8.83|-6.97|-1.86|
|EU’s Bilateral-OTRI wrt the UK (%)|3.26|||
|Trade impact of the UK (%)|-139.38|-120.76|-18.62|
|Trade impact of the UK ($B)|-223|-193|-29.8|

<u>Table 6: Robustness Checks with Diferent Elasticities</u>

||Ho|mogene|ous|Elasticities fr|om|Reshufed|
|---|---|---|---|---|---|---|
||E|lasticit|y|Caliendo-Parro|Ossa|Elasticities|
||-3.85|-4|-8|(2015)|(2015)|w/ no Correlation|
||(1)|(2)|(3)|(4)|(5)|(6)|
|EU’s Bilateral-TRI wrt the UK (%)|4.60|4.60|4.60|2.91|4.01|4.48|
|Welfare change of the EU (%)|-0.37|-0.39|-0.77|-0.15|-0.20|-1.22|
|Welfare change of the EU ($B)|-0.60|-0.62|-1.23|-0.26|-0.31|-1.95|
|EU’s Bilateral-OTRI wrt the UK (%)|2.81|2.81|2.81|2.35|2.23|2.77|
|Trade impact of the UK (%)|-7.81|-8.20|-19.1|-8.13|-5.68|-33.0|
|Trade impact of the UK ($B)|-12.5|-13.1|-30.6|-14.48|-8.69|-52.7|

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Table 7: Potential Short-Run Impacts of Brexit by Sectors

||SITC Rev 4|Exp|ort|Import Weighte|d Average|OTRI|Trade|Impact|
|---|---|---|---|---|---|---|---|---|
|Sector|Description|$Bil.|%|MFN Tarif (%)|Elasticity|%|$Bil.|%|
|0|Food and live animals|4.39|2.74|8.51|-13.33|6.09|-3.10|-70.79|
|1|Beverages and tobacco|2.57|1.61|1.93|-1.14|14.37|-0.05|-1.76|
|2|Crude materials|3.03|1.89|0.47|-18.63|0.05|-0.03|-0.91|
|3|Mineral fuels|19.29|12.06|0.75|-10.69|0.16|-0.30|-1.56|
|4|Animal and veg. oils|0.37|0.23|5.64|-26.56|7.80|-0.69|-185.02|
|5|Chemicals|28.75|17.97|2.65|-1.69|4.21|-0.80|-2.80|
|6|Manufacturing material|16.42|10.27|2.60|-4.59|3.52|-2.01|-12.21|
|7|Machinery and transport|67.00|41.89|3.38|-1.60|2.67|-1.04|-1.56|
|8|Misc. manufacturing|17.20|10.75|3.82|-2.95|6.95|-2.18|-12.69|
|9|Other Commodities|0.93|0.58|0.00|-0.49|0.00|0.00|0.00|

30