The US solar panel anti-dumping duties versus uniform tariff

The US solar panel anti-dumping duties versus uniform tariff

Energy Policy 127 (2019) 523–532 Contents lists available at ScienceDirect Energy Policy journal homepage: www.elsevier.com/locate/enpol The US sol...

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Energy Policy 127 (2019) 523–532

Contents lists available at ScienceDirect

Energy Policy journal homepage: www.elsevier.com/locate/enpol

The US solar panel anti-dumping duties versus uniform tariff☆ Ly Nguyen , Henry W. Kinnucan ⁎

T

Department of Agricultural Economics, Auburn University, 312 Comer Hall, Auburn, AL 36849, USA

ARTICLE INFO

ABSTRACT

Keywords: Solar panels Discriminatory tariff Uniform tariff Welfare Unemployment Environment

The US switched its China and Taiwan anti-dumping duties to uniform tariffs on all imports of solar panels in January 2018. This research uses an Equilibrium Displacement Model (EDM) to determine the relative effects of these two tariffs on domestic consumer and producer welfare, employment, government revenue, and environmental costs. The results indicate that uniform tariffs are more effective than the specific-country tariffs because of higher welfare for domestic manufacturers and higher government revenue. However, the uniform tariffs hurt American consumers, employees, and the environment more than the other because of higher domestic price and larger domestic demand reduction. Therefore, if a policy aims to create more jobs and have less effect on consumers and the environment, a specific-country tariff might be preferable. However, uniform tariffs are better if the administration intends to support domestic manufacturers and increase government revenue.

1. Introduction

China and Taiwan accounted for only 11%, whereas the imports from Malaysia, Korean, and Vietnam accounted for 56% (US EIA, 2018). Because of a higher demand for cleaner energy, most developed and developing countries have implemented energy policies to promote solar power research and its development, production, and consumption. These policies include feed-in-tariffs, investment tax credits, subsidies, favorable financing, mandatory access and purchase, renewable energy portfolio standards, and public investment (Timilsina et al., 2012; Oliver and Jackson, 1999). The US is one of the leading countries in the world to invest in solar energy at both federal and state levels. The installation of residential solar panel systems in most cities mainly is based on tax and cash incentive policies (Lee et al., 2016; Liu et al., 2014). One of the important policies in the US solar energy market is the Investment Tax Credit (ITC). This policy reduces the tax liability for individuals and businesses that purchase qualifying solar energy technologies. As a result, the domestic consumption of solar energy has increased approximately 400% per year on average in the last one and a half decades from 0.24 gigawatts (GW) in 2002–14 GW in 2016 (Appendix A Table A.1). In the same period, solar cell and module prices have decreased 21% annually from $2.9 (2002) to $0.7 (2016) per kilowatt (kW). However, according to Timilsina et al. (2012), the development of solar energy still has three major barriers: (1) technology, (2) economics, and (3) institutions. Technology is a critical factor differentiating solar cell and module efficiencies and prices among countries. The share of domestic production and imports of solar cells and modules in the US

The world solar energy market has been significantly expanding and accelerating because: (1) the costs of solar cells and modules have been rapidly decreasing, (2) government supportive policies have been increasing, and (3) it has been one of the most abundant, largest potential, and cleanest energy sources (Sahu, 2015; Oliver and Jackson, 1999). Although the markets for solar panels are numerous, most solar photovoltaic (PV) cells and modules are produced where they are not consumed. For instance, China, the world’s largest producer of solar panels, exports over 90% of their production to the EU, the US, and Asian markets. The China solar industry, an entirely export-focused industry, produces over 70% of the world’s solar panels. Whereas, the US is the second largest net importer after Germany for solar cells and modules produced in China, Japan, and Malaysia (Table 1). The US is a major importer of many products from global market, including energy. However, the US energy import patters change over time. Particularly, in 2005, approximately 30% of total energy used in the US was imported, however, this import proportionate decreased to 7.3% in 2015 (World Bank Database, 2018). Asian countries are the major suppliers of the US energy imports such as solar panel from China and Taiwan. Specifically, in 2011, the US imported approximately 7 billion solar panels, in which, 51% of import value was from the dominants, China and Taiwan. Over the past five years, however, the dominant suppliers have moved away from China and Taiwan toward Malaysia, Korean, and Vietnam. In 2017, the share of US imports from

Responsibility for any remaining errors of judgment, logic, or fact rests strictly with the authors. Corresponding author. E-mail address: [email protected] (L. Nguyen).

☆ ⁎

https://doi.org/10.1016/j.enpol.2018.11.048 Received 17 May 2018; Received in revised form 23 October 2018; Accepted 26 November 2018 0301-4215/ © 2018 Elsevier Ltd. All rights reserved.

Energy Policy 127 (2019) 523–532

L. Nguyen, H.W. Kinnucan

Table 1 The world top net exporters and net importers of solar panels (Billion US$) from 2002 to 2016. Source: US International Trade Commission Database, 2018. No.

Net Exporter

Import

Export

Net Export

Net Importer

Import

Export

Net Import

1 2 3 4 5 6

China Japan Malaysia Philippines Singapore Other countries

84.7 43.0 7.5 1.1 10.1 17

143.4 69.6 23.8 8.0 14.1 54

58.8 26.6 16.3 6.9 3.9 37

Germany USA Italy Spain Hong Kong Other countries

82.7 64.9 33.6 18.7 37.5 188

45.9 29.1 2.7 5.6 25.2 86

36.8 35.8 30.9 13.1 12.3 103

market has changed during the last few years, with the US switching from a net exporter of solar energy to a net importer since 2010. In particular, in 2002, the domestic production accounted for 85% of total domestic consumption. Then, in 2016, imports accounted for 83% of total domestic consumption (Appendix A Table A.1). The increased global production of solar panels has depressed prices and made it difficult for American producers to compete. Consequently, in 2011 US solar manufactures filed a petition with the Department of Commerce (DOC) claiming unfair trade of foreign solar panel producers; specifically, the illegal dumping of solar cells by Chinese manufacturers. In 2012, the US International Trade Commission (ITC) issued orders to place duties on PV cells manufactured in China. In 2014, the ITC issued new tariffs for PV cells manufactured in both China and Taiwan after determining that Chinese PV producers moved their manufacturing operations to Taiwan to avoid the tariffs. However, the effects of the tariffs on imports were lessened since most of the manufacturing companies located in both China and Taiwan outsourced their production to other countries not covered by the anti-dumping duties. As a result, the US began to see increased imports primarily from Malaysia, as well as from South Korea, Singapore, and Germany. On January 22, 2018, the current US administration levied a 30% tariff on solar equipment made abroad. This policy exempts the first 2.5 GW of imported solar cells and the tariffs will be applied for four years that start at 30% the first year and gradually drops to 15% by 2021. The tariff instituted in 2018 is called a uniform tariff because it applies to all exporters of solar panels to the United States. It is an upgraded version of the tariff instituted in 2012, hereafter referred to as a “discriminatory tariff” because it applied only to China and Taiwan. A uniform tariff addresses outsourcing and thus should be more effective at protecting the domestic industry than the discriminatory tariff it replaces. Theoretical analysis, however, is not fully consistent with this conjecture. In their analysis of uniform and discriminatory tariffs under third-degree price discrimination with linear demand, Yang et al. (1996) find that the domestic welfare gain from a uniform tariff does indeed exceed the gain from a discriminatory tariff. As an instrument of protection, however, Dinlersoz and Dogan (2010) find that under certain conditions an AD duty is more effective than a uniform tariff. Whether either of these instruments actually stimulates job growth depends on the nature and extent of partner retaliation (Magee, 1972). Also, whether the home or the foreign country is hurt more by tariffs depends on the relative elasticities of demand and supply (Tokarick, 2006). Although tariffs are the centerpiece of trade policy in a market system, results of empirical research on their effectiveness are mixed. In the case of solar panels, Hughes and Meckling (2017) and Meckling and Hughes (2017) find the effects on the domestic economy of a rise in US protectionism are uncertain. This is because international supply chains for solar panels are highly integrated. For instance, in order to build big factories that produce solar panel exports to the US market, China has bought equipment from American manufacturers. Therefore, the US solar panel tariff indirectly causes a negative influence on the domestic equipment manufacturers. Although a tariff could possibly support domestic production expansion, innovation, and job creation (Kreickemeier, 2005), it has the potential to increase production costs,

increase prices, and create loses for the market segment of the solar industry (Zheng and Kammen, 2014). The higher prices associated with the tariffs lead to lower rates of solar PV installation because of demand reduction (Algieri et al., 2011; Iychettira et al., 2017). A tariff increase not only reduces the tariff-raising country’s trade balance, but also threatens the jobs of this industry. Shum (2017) estimates that under the current tariff structure the US demand for PVs will decrease 60%, resulting in a loss of 88,000 jobs between 2018 and 2021. A discriminatory tariff targeted at a specific country such as China causes more imports from other countries, and lowers domestic demand instead of stimulating American manufacturing (Dixon, 2017). In addition to reducing the problem of trade diversion, Tarr (2000) argues that a uniform tariff is more efficient in that it reduces the industry’s incentive to lobby for protection and for this reason is the preferred choice in practice. However, the actual experience with tariffs worldwide suggests that most developed and developing countries differentiate their tariffs substantially. Therefore, the purpose of this research is to determine the relative effectiveness of uniform and discriminatory tariffs as instruments of protection using the U.S. tariffs on solar panels as a case study. The purpose of this research is to determine the relative effects of discriminatory and uniform tariffs on the US economy using solar panels as a case study. The analysis is based on a residual demand model. Goldberg and Knetter (1999) argue that residual demand models are sufficiently flexible to represent alternative market structures and perceived product differentiation. The residual demand model is similar to the market segmentation model developed by Venables (1985) and extended by Brown and Stern (1989) to analyze tariffs in a situation where the product is homogeneous yet price differs across countries. In this model, firms play a Cournot game and perceived demand is market demand net of the supply of other firms. Domestic firms charge the same price in the home market, but different prices in export markets due to perceived market segmentation. In applying the residual demand model we follow Blonigen and Haynes (2002) and focus on the passthrough elasticity (PTE), i.e., the elasticity that indicates the sensitivity of domestic price to the duties. Blonigen and Haynes’s (2002) analysis of the PTE is extended to include the effects of trade diversion, i.e., the propensity of exporting countries not named in the trade dispute to redirect their exports to the country imposing the duties to take advantage of the price rise. This extension exposes under what conditions a uniform tariff on all imports might be a more effective instrument of protection than a discriminatory tariff on a portion of the imports. This study fills a gap in the literature in that the two studies most closely related to the present study, namely Yang et al. (1996) and Dinlersoz and Dogan (2010), trade diversion is not considered. All simulations in this research only consider the effects of changes in the tariffs by the US, holding the foreign country’s trade policy constant. In the next section, the theoretical model and calibration are presented. Then, the total welfare effects of both specific-country and uniform tariffs are simulated, compared, and analyzed for sensitivity. The study concludes with a summary of key findings and discussions of policy implications.

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2. Methodology and hypotheses

where X * = dX / X is the relative change in variable X ; ( < 0) and 1 ( > 0) are domestic demand and supply elasticities for solar panels, respectively; 2 ( > 0) and 3 ( > 0) are import supply elasticities for solar panels from China/Taiwan and ROW, respectively; and k1 = Q1s/ Q1d , k2 = Q2/ Q1d and k3 = Q3/ Q1d are quantity shares that sum to one. This model contains seven endogenous variables (Q1*d , Q1*s , Q2* , Q3* , * , P2* and P3* ) and two exogenous variables (T A* and TB*). Other exoPUS genous variables that affect supply and demand are suppressed.

This research adopts the Equilibrium Displacement Model (EDM)1 to analyze the effects of US import tariffs on solar panels. This model assumes there is a three-country market including the US as a net importer and two net exporters are China and Taiwan2 and Rest-of-World country (ROW). There are two regimes: the tariff before January 22, 2018 that was applied on the imports from China and Taiwan only (Regime A), and the tariff after January 22, 2018 that was applied to all imports (Regime B). The model to simulate the effects of tariffs under the two regimes on prices, domestic production, domestic consumption, and imports is as follows:

Q1d = D (PUS )

(1)

Q1s = S1 (PUS )

(2)

Q2 = S2 (P2)

(3)

import supply from ROW

Regime AQ3 = S3 (PUS )

(4A)

import supply from ROW

Regime BQ3 = S3 (P3)

(4B)

China/Taiwan price – Regime AP2 = PUS / TA

(5A)

China/Taiwan/ROW price – Regime BP2 = P3 = PUS / TB

(5B)

Q1d = Q1s + Q2 + Q3

2.1. Pass-through elasticities To derive the pass-through elasticity (PTE) implied by the model under regime A, we first derive the residual demand curve for imports from China and Taiwan by dropping Eqs. (3′), (4B′) and (5B′) and solving the remaining equations simultaneously to yield

(1′)

Q1*s =

* 1 PUS

(2′)

Q2* =

2 P2*

(3′)

Q3* =

* 3 PUS

(4A′)

Q3* =

3 P3*

(4B′)

* P2* = P3* = PUS

TB*

3

k2

(P2* + T A* )

(7)

i , k i >0 i , and Under the stated restrictions ( <0 , i 0 ki = 1), the residual demand curve for imports from China and Taiwan is downward sloping, and an increase in the discriminatory tariff shifts the curve inward. The curve flattens as domestic demand or supply becomes more price elastic (larger or 1), and as supply from the non-tariffed source becomes more price elastic (larger 3 ). The PTE is derived by setting Eq. (7) equal to Eq. (3′) and reusing Eq. (5A′) to yield PTEA

* PUS = T A*

2 2

(

1

(8)

2

k1 1 k2

k3 3

)

< 0 is the residual demand elasticity for US where 2 = imports of solar panels from China and Taiwan. Eq. (8) reflects the principle that the less elastic side of the market bears the greater incidence of the tariff. If import supply of solar panels from China and Taiwan is perfectly elastic US buyers bear the full incidence and PTEA = 1 (its upper limit); if import supply is perfectly inelastic China/Taiwan exporters bear the full incidence and PTEA = 0 (its lower limit). A discriminatory tariff becomes more effective as demand for the dutied good becomes less price elastic (smaller 2 ), and as supply of the dutied good becomes more price elastic (larger 2 ). The PTE under regime B is derived in a similar fashion. First, drop Eqs. (3′), (4A′) and (5A′) and solve the remaining equations simultaneously to yield the residual demand curve Q2* =

*+(

2 P2

2

(8′)

+ A) TB* k1 1 <0. k2

k3 3 >0 k2

where A = and ( 2 + A) = A uniform tariff reduces US demand for solar panels from China and Taiwan, but to a lesser extent than a discriminatory tariff. (The coefficient of T A* in Eq. (7) is 2 , which is more negative than the coefficient of TB* in Eq. (8).) Next, set Eq. (8) equal to Eq. (3′) and reuse (5B′) to yield:

PTEB

* PUS = TB*

2 2

+A

1 2

(9)

The PTE for a uniform tariff is similar to the PTE for a discriminatory tariff in that it is bounded between 0 and 1.3 However, within these limits PTEB > PTEA and thus the uniform tariff provides more protection for the domestic industry. The added protection provided by a uniform tariff increases as ROW exporters become more responsive to the US price. In particular, as 3 the PTE for the discriminatory tariff approaches its lower limit of zero, and the PTE for the

(5A′)

T A*

k3

1

3 i=1

(6)

* Q1*d = PUS

k1

Q2* =

where Q1d and Q1s represent domestic consumption and production, respectively; Q2 and Q3 are the US imports from China and Taiwan and ROW, respectively; PUS is domestic price inclusive of the tariff; P2 and P3 are prices exclusive of the tariff; TA = (1+ 2) is the tax wedge under Regime A (the discriminatory tariff) where 2 is the ad valorem tax rate that is applied to China and Taiwan’s exports: and TB = (1 + ) is the tax wedge under Regime B (uniform tariff) where is the ad valorem tax rate that applied to all imports. In the analysis to follow we assume = 2 . Since the discriminatory tariff is applied only to China and Taiwan imports, under regime A other exporters (ROW) to the US respond to PUS , which is higher than P2 . Thus, the tariff provides an implicit subsidy to ROW exporters who have access to the US market. This encourages trade diversion, which, as is shown later, has an important bearing on the relative effectiveness of the two regimes. The model assumes domestic and imported solar panels are perfect substitutes, and the domestic market is integrated with world markets such that the law of one price holds. Taking the total derivative of each equation and expressing partial derivatives as elasticities, the model can be expressed in terms of relative changes in the variables as follows:

* P2* = PUS

(6′)

Q1*d = k1 Q1*s + k2 Q2* + k3 Q3*

(5B′)

1 EDM models, also known as “hat calculus models” (Bhagwati et al., 2001) have proved useful as a tool for analyzing and wide range of issues related to resource and trade policy. For a good overview of this modeling approach, see Wohlgenant (2011). For a recent application to a problem in international trade, see Rickard et al. (2018). 2 Since the same tariff applies to imports from China and Taiwan, this model treats imports from these two countries as coming from a single country.

3 That PTEB has an upper limit of 1 can be seen by noting that Eq. (9) can be P* k +k = k +2k 2 +3k 3 rewritten as TUS . Taking the limit of this expression as 2 1 1 2 2 3 3 B* or as 3 yields PTEB = 1.

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Table 2 Reduced-form elasticities for two types of tariffs. Indicators

Discriminatory

US price (pass-through elasticity) China/Taiwan price Rest of World price US production

2 2

2 2

2

2 2

2

2 1 2

2

US consumption

2 1 2

2

US imports from China & Taiwan US Imports from ROW Trade-diversion term

2 22

2

2

3 2 2



2

>0 <0 >0 >0 <0 <0

>0

Table 3 Uniform 2+A 2 2 2+A 2

2 2+A

2

2

2

<0

2

A=

2 k3 3 k2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

>0

<0 <0 <0 0

=

1

k1 1 k2

k3 3

= US residual demand elasticity for solar panels from China

and Taiwan. 1= US demand elasticity for domestically-produced solar panels. 1= US supply elasticity for domestically-produced solar panels. 3= US import supply elasticity for solar panels from Rest of World. k1= share of US consumption of solar panels produced domestically. k2= share of US consumption of solar panels imported from China and Taiwan. k3= share of US consumption of solar panels imported from ROW.

uniform tariff approaches its upper limit of one. This result is consistent with the analysis of Kinnucan et al. (2017) who show that trade diversion, which undermines the effectiveness of an antidumping duty, is an increasing function of 3 . A uniform tariff prevents free riding by non-named exporters, the Achilles’ heel of antidumping duties, which are akin to a discriminatory tariff.

and uniform

Model parameters

k1

<0

2 ( 2 + A) 2 2 3 ( 2 + A) 2

Row

>0

1 ( 2 + A) 2 2 1 ( 2 + A)

TA *

alternative values of model parameters.

Definitions:. 2= US import supply elasticity for solar panels from China and Taiwan. 2

PUS *

Pass-through elasticities for discriminatory

0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.17

k2 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.25

TB *

tariffs for

PTE

k3 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58

PUS *

1

− 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65 − 0.65

2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7

2

1 1 1 1 1 5 5 5 5 5 10 10 10 10 10 100 100 100 100 100 ∞ ∞ ∞ ∞ ∞

3

1 5 10 100 ∞ 1 5 10 100 ∞ 1 5 10 100 ∞ 1 5 10 100 ∞ 1 5 10 100 ∞

PUS * TA *

PUS * TB*

0.129 0.059 0.035 0.004 0.000 0.425 0.238 0.153 0.021 0.000 0.597 0.384 0.266 0.041 0.000 0.937 0.862 0.783 0.297 0.000 1.000 1.000 1.000 1.000 1.000

0.428 0.740 0.845 0.981 1.000 0.623 0.789 0.864 0.982 1.000 0.735 0.830 0.882 0.982 1.000 0.598 0.962 0.965 0.987 1.000 1.000 1.000 1.000 1.000 1.000

Since estimated demand elasticity for solar panels is not available in the literature, this research uses the average demand elasticity for residential solar PV cells estimated by Gillingham and Tsvetanov (2018) to represent the US domestic demand elasticity for solar panels. This value is equal to −0.65. Accordingly, we set = 0.65. There are no supply elasticity estimates available for solar panels; hence we set the US supply elasticity to 2.7. This value is based on the price elasticity for supply of renewable energy generation estimated by Johnson (2011). This is a long-run elasticity of supply. It is treated as a “best-bet” value in the stochastic simulations described later. No empirical estimates exist for import supply elasticities from China ( 2 ) and ROW ( 3 ). Intuitively, these elasticities should be more larger than the domestic supply elasticity ( 1 ) (Kinnucan and Myrland, 2005; Kinnucan, 2003). Consequently, we set 2 and 3 equal to 3. Numerical values for the quantity-share parameters (ki ) were computed based on data obtained from government sources. Data for US imports were obtained from the US International Trade Commission (USITC) Interactive Tariff and Trade DataWeb Version 3.1.0. Data for US production and the price of solar panels were obtained from the US Energy Information Administration (EIA). These data are presented in Appendix A Table A.1 for selected years between 2002 and 2016. The simulations in this research use data for 2016. In that year US solar energy production was 2475 megawatts (MW), equal to 17% of domestic consumption (14,155 MW); imports from China and Taiwan was 3451 MW, equal to 25% of domestic consumption, and imports from other countries was 5441 MW, equal to 58% of domestic consumption. Accordingly, in the simulations we set k1 = 0.17 , k2 = 0.25, and k3 = 0.58. To account for uncertainty in parameter values, stochastic simulations are performed with , 1, 2 , and 3 treated as random variables that follow a triangular distribution. The triangular distribution requires specification of minimum, most likely, and maximum values. The parameters’ most likely values are set to their best-bet values, and the minimum and maximum values are set to 0.5 and 1.5 times the mostlikely values. Mean values and 90% confidence limits for the reduced-

2.2. Hypotheses The import supply elasticity for solar panels from ROW is a critical parameter in the relative effectiveness of discriminatory and uniform tariffs. The PTEs converge only if the ROW import supply elasticity is zero. The same is true for the remaining reduced-form elasticities implied by the model, which are summarized in Table 2. A discriminatory tariff increases the US and ROW price, reduces the China/Taiwan price, increases domestic production and imports from ROW, and reduces domestic consumption and imports from China/ Taiwan. A uniform tariff differs qualitatively from a discriminatory tariff in that it reduces (rather than increases) ROW price and imports. The conclusion that a uniform tariff is more effective than a discriminatory tariff at protecting domestic producers is predicated on the assumption that the supply curve for imports from China/Taiwan is upward sloping ( 2 < ). If both import supply curves are flat, the two tariffs are equally effective. This is shown in Table 3 (rows 21–25) where the PTEs attain their upper limits of 1 when 2 = . But this scenario implies the US is a too small an importer of solar panels to influence price, which is not plausible. For the considered parameter values in Table 3, the PTE for a uniform tariff is substantially larger than the PTE for the discriminatory tariff. This suggests domestic producers should not be indifferent about which policy instrument is used. This hypothesis is explored in the simulations to follows. 3. Parameterization This research assumes all solar panels are homogeneous products. To determine the effects of the tariffs on U.S. price, production, consumption and imports, numerical values for the parameters in Eqs. (1′) to (6′) need to be specified. 526

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Table 4 Reduced-form elasticities for discriminatory and uniform tariffs implied by the model. Endog. variable

Short run Disc tariff

Long run – Disc. tariff Uniform tariff

5% limit

Long run – Uniform tariff

Mean value

95% limit

5% Limit

Mean value

95% limit

* PUS

0.24

0.79

0.17

0.21

0.23

0.61

0.69

0.71

Q1*s Q1*d

− 0.16

− 0.52

− 0.07

− 0.14

− 0.18

− 0.30

− 0.45

− 0.60

Q2* Q3*

0.72

− 0.62

0.50

0.63

0.84

− 0.61

− 0.92

− 1.24

0.00

− 2.28

0.00

− 0.62

0.29

− 1.64

0.56

− 2.37

0.76

− 3.19

1.22

− 0.61

1.87

− 0.92

2.51

− 1.24

* = US price, Q1*s= US production, Q1*d= US consumption, Q2*= US imports from China and Taiwan, Q3*= US imports from Rest of World. The long-run Definitions: PUS elasticities were obtained by simulating text Eqs. (1′)–(6′) with parameters set to the following “best-bet” values: k1 = 0.17 , k2 = 0.25, k3 = 0.58, = 0.65, 1 = 2.7, and 2 = 3 = 3. The short-run elasticities are based on the same values except 1 is set to zero.

form elasticities implied by the model are computed based on 5000 random draws using Simetar, an Excel add-In developed by Richardson et al. (2008). To distinguish between short-run and long-run effects, deterministic simulations are performed with the domestic supply elasticity set to zero.

For the considered parameter values, a uniform tariff is three times more effective at raising domestic price and production than a discriminatory tariff. None of the 90% confidence intervals includes zero, which suggests the elasticity “estimates” given in Table 4 are reliable. The response of domestic production to a discriminatory tariff is inelastic (Q1*s / T A* [0.29,0.76]) and elastic for a uniform tariff Q1*s / TB* [1.22, 2.51]) . A uniform tariff is much more effective at increasing domestic production than a discriminatory tariff, as might be expected because its effect on domestic price is much larger. Both tariffs cause imports from China and Taiwan to decrease, with the discriminatory tariff about twice as effective (Q2*/T A* [ 1.64, 3.19]) as the uniform tariff (Q2*/TB* [ 0.61, 1.24]) ).

4. Simulation results and discussion 4.1. Reduced-form elasticities The relative effects of discriminatory and uniform tariffs on domestic welfare, employment, government revenue, and the environment depends crucially on their relative effects on equilibrium prices and quantities in the domestic economy. To determine that in the context of our partial equilibrium model, we simulated the model to obtain reduced-form elasticities as shown in Table 4. Focusing first on the short-run effects, an increase in either tariff has no effect on domestic production because domestic supply is assumed to be perfectly inelastic. A 1% increase in the uniform tariff has about three times the effect on domestic price and consumption as a 1% increase in the discriminatory tariff. Both tariffs cause imports from China and Taiwan to decrease, with the discriminatory tariff about 3.5 times more effective at reducing imports from those countries as a uniform tariff. The two tariffs have opposite effects on imports from ROW, with the uniform tariff reducing imports from ROW, and a discriminatory tariff increasing imports. The positive effect of the discriminatory tariff (0.72) is almost as large the negative effect of the uniform tariff (-0.62), which helps explain why the uniform tariff is so much more effective at raising the domestic price. Overall, with the exception of Q2*/ T A* = 2.28 (the reduced-form elasticity of imports from China and Taiwan with respect to a discriminatory tariff), the short-run responses are inelastic. Turning to long-run effects, permitting domestic production to respond to price alters the magnitude of the elasticities but not their signs.

4.2. Welfare effects The effects of the tariffs on domestic welfare are presented in Figs. 1 and 2. With the maintained hypothesis that the US is a large importer, a change in US import policy on solar panels impacts the world price. In a perfectly competitive market, there is no difference between modeling tariffs as a demand or as a supply shifter (Felbermayr et al., 2015). In this study, therefore, the effects are modeled as a demand shifter. Focusing first on the discriminatory tariff (Fig. 1), the tariff causes a simultaneous decrease in demand for solar panels from China and Taiwan and an increase in the demand for solar panels from ROW. With upward sloping supply, the price received by domestic and ROW producers increases (panels (a) and (c)), and the price received by Chinese/ Taiwanese producers decreases (panel (b)). A per-unit tariff equal to T places a wedge between the world price and the price received by Chinese/Taiwanese producers price equal to P1 P2 where P1 = P3 under the maintained hypothesis that the LOP holds. The increase in domestic price from P10 to P1 in panel (a) causes domestic consumer surplus to fall by the area P1 bfP10 and domestic producer surplus to increase by the area P1 aeP10 . The higher domestic price causes domestic

Fig. 1. a Effects on domestic welfare of a tariff on the imports from China/Taiwan only. 527

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Fig. 2. Effects on domestic welfare of a uniform tariff on all imports. Table 5 Relative effects of 30% discriminatory and uniform tariffs on solar panels on the US economy. Item

CS PS Tariff rev. Subtotal Employ Envir. Costs Total gain

Discriminatory tariff

Uniform tariff

Uniform/Disc.

5% limit

Mean value

95% limit

5% limit

Mean value

95% limit

5% limit

Mean value

95% limit

− 610 114 410 − 86 − 481 − 56.3 − 623

− 607 117 221 − 269 − 731 − 115 − 1115

− 603 121 33 − 449 − 981 − 154 − 1584

− 1963 425 1843 305 − 522 − 253 − 470

− 1918 460 1630 172 − 788 − 383 − 999

− 1872 495 1417 40 − 1054 − 391 − 1405

3.22 3.73 4.50 – 1.09 − 197 − 185

3.16 3.93 7.38 – 1.08 − 268 − 253

3.10 4.09 42.9 – 1.07 − 237 − 186

Definitions: CS = change in domestic consumer surplus, PS = change in domestic producer surplus. Tariff rev. = government revenue from the tariff, Envir. costs = environmental costs associated with the tariff, Employ = employment costs associated with the tariff. All values are in million US dollars.

uniform tariff generates about four times the benefit to domestic producers as the discriminatory tariff. Thus, if the goal is to protect domestic producers, the uniform tariff is clearly preferred.

production to increase to Q1S , domestic consumption to decrease to Q1D , and imports to decrease to Q1S Q1D . The tariff revenue is the area abcd. The dead-weight loss due to the trade restriction is the sum of areas ade and bfc. Turning to the uniform tariff (Fig. 2), the welfare effects are the same as described above except magnified. The reason is that a uniform tariff reduces imports from ROW as well as from China and Taiwan. The import demand curves in panels (b) and (c) both shift down. With less quantity in the US market, the domestic price effect is larger, which results in a larger gain to domestic producers and the US treasury, and a larger loss to domestic consumers and economic efficiency a measured by deadweight loss.

4.4. The effect of a 30% tariff on domestic employment Although people argue that the uniform tariffs are necessary to prevent further losses in domestic solar manufacturing jobs (Matt et al., 2014), the US Solar Energy Industries Association (SEIA) indicates that the tariffs will eliminate American manufacturing jobs (SEIA, 2018). This occurs because 85% of jobs in solar manufacturing are tied to making something other than the production of solar cells and panels, such as the manufacture of metal racking systems, high-tech inverters, machines that improve solar panel output by tracking the sun and other electrical products. Therefore, this section estimates the employment effect based on workforce data for the whole sector4 provided by The Solar Foundations’ National Solar Jobs Census in 2016. The historical data of employment for subsectors in the solar industry from 2010 to 2017 (Appendix A Fig. A.5) show that tariffs in 2012 caused total employment in solar manufacturing to increase although there was a decrease in solar panel manufacturing between 2010 and 2011. Obviously, the tariff could create additional jobs for Americans in the various manufacturing subsectors. However, employment for the subsector of panel production accounts for only 15% of the total jobs in 2017 created by solar energy employment. Importantly, employment in the installation subsector increases significantly through this 2010–2017 period (by approximately 10% per

4.3. Welfare and treasury effects of a 30% tariff The welfare and treasury effects of the US administration’s proposed 30% tariff on solar panels based on the long-run elasticities in Table 4 are presented in Table 5. These effects are computed using the US solar domestic production, consumption, imports, and prices for 2016 given in Appendix A Table A.1. Results suggest a 30% uniform tariff is welfare increasing in the sense that the gains to domestic producers ($425–$495 million) and the US treasury ($1.42–$1.84 billion) are sufficient to offset the loss to domestic consumers ($1.87–$1.96 billion) to yield a net gain to the domestic economy of between $40 and $360 million. In contradistinction, a 30% discriminatory imposes a net loss on the domestic economy of between $86 and $449 million. The uniform tariff generates about 7.4 times more revenue for the treasury (evaluated at the mean of the stochastic simulations) than the discriminatory tariff, which explains this result. In addition to being welfare increasing, the

4 The whole sector employment for the solar industry includes installation, manufacturing, sales and distribution, project development, and others.

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year), and the employment in this subsector accounts for 52% of the total jobs in the industry. The employment effects in this research are estimated by classifying the numbers of employees per domestically produced energy unit (gigawatt, GW) for domestic production and the employees per imported energy unit for imports. Based on data from 2010 to 2017, the average number of employees needed in the manufacturing sector per unit of domestic production was determined. The aggregate employee needs of other subsectors was determined by dividing total domestic consumption by the average needed employees per unit US consumption. The effect on total employment in the sector is the sum of the effect on domestic production growth and overall reduction in consumption induced by the tariff. This analysis indicated that domestic production needs 16 employees per GW, while imports need 16 laborers per GW as well. These data are combined with the effects on domestic production and imports obtained from the model to estimate the employment effects for each year. Results suggest tariffs reduce rather than increase employment in the sector. According to model simulations, a 30% discriminatory (uniform) tariff causesan estimated loss on average of 16,995 (18,311) jobs per year. The discriminatory tariff creates 6749 jobs due to increased domestic production, but this is more than offset by the reduction in installation type jobs of 23,744. Although the uniform tariff adds approximately 22,402 new jobs in domestic manufacturing, 40,713 jobs in other subsectors are lost. According to the the US Bureau of Labor Statistics, the mean annual wage in this industry is $43,010. Based on this wage rate, 90% confidence intervals suggest a 30% discriminatory (uniform) tariff could impose an annual cost on the economy due to reduced employment in the sector of between $481 and $981 million ($522 and $1.1 billion) per year. Overall, the employment benefits from domestic manufacturing do not compensate for income lost due to the reduction from installation, sales and distribution, project development, and the other components of the solar energy industry. A caveat in interpreting the foregoing results is that they do not take into account interaction effects. For example, if the government revenue from the tariffs is used to support technology development or other subsidy programs to solar consumers and producers, the production costs will be lower and consequently the prices to consumers will be cheaper. Therefore, the costs of tariffs due to higher price and higher unemployment in this instance areapt to be overestimated.

cause 1910 MW of energy from electrical power to be substituted for solar power at a cost to the environment of approximately $383 million in 2017 dollars. The 90% confidence intervals for these estimates are [$-56 million, -$154 million] for the discriminatory tariff and [$-253 million, $391 million] for the uniform tariff. When environmental and employment costs are considered a 30% uniform tariff is no longer welfare increasing. In fact, when all costs are considered the 30% uniform tariff generates a loss in the domestic economy of between $470 million and $1.4 billion per year. The corresponding loss from a 30% discriminatory tariff is between $623 million and $1.58 billion per year. Because the 90% confidence intervals overlap, when all costs are considered there is little to choose between the two tariffs. This research assumes if the tariffs are removed, the increase in domestic consumption associated with the decrease in domestic price would be fulfilled by imports. Consequently, the environmental costs to the domestic economy from tariff removal are assumed to be zero. 5. Conclusions and policy implications In January 2018 the United States switched its tariff policy on solar panels from a discriminatory tariff against imports from China and Taiwan to a uniform tariff against imports from all countries. Study results suggest the efficacy of the policy switch depends on the goal. If the goal is to increase the production of solar panels in the United States, the uniform tariff is three to four times more effective than the discriminatory tariff. The reason is that the uniform tariff is three to four times more effective at raising the US price of solar panels than the discriminatory tariff, and thus provides both a larger welfare gain to domestic producers, and a stronger incentive to expand production. If the goal is to enlarge domestic welfare (defined as the sum of economic surplus and tariff revenue), the policy switch is particularly effective as the gain in tariff revenue from the uniform tariff is about seven times larger (valued at the mean of the stochastic simulations) than the gain from the discriminatory tariff. Indeed, while the discriminatory is welfare decreasing from the perspective of the domestic economy, thanks to the large gain in treasury revenue the uniform tariff is welfare increasing. If the goal of the policy switch is expanded to include its effects on employment and the environment inferences are less clear cut. Both tariffs are shown to decrease employment. The reason is that more than 85% of the local employees are working on installation, sales and distribution, and project development instead of actual manufacturing of solar panels. Less than 10% of all solar energy-related jobs in the United States are created by the domestic manufacturer. The higher domestic price caused by the tariffs discourages consumers from buying solar panels and paying for their installation. Given that most of the employment in the industry occurs beyond the plant gate, the added jobs in the manufacture of solar panels induced by the tariffs are more than offset by the loss in jobs associated with reduced installation and other services. Model simulations suggest the cost of the reduced employment associated with a 30% tariff might run as high as $1 billion per year, with the discriminatory tariff only slightly less costly than the uniform tariff. A reduction in the quantity demanded of solar panels associated with the tariffs implies greater usage of conventional electricity, which has implications for the environment. Our analysis suggests the increased CO2 emissions associated with the reduced use of solar energy induced by a 30% tariff would impose an annual cost on the domestic economy of up to $1.58 billion in the case of the discriminatory tariff and $1.41 billion for the uniform tariff. When the environmental costs are added to the costs of job losses, the 90% confidence intervals for the net gains from the two types of tariffs overlap. This suggests when all costs are considered and parameter uncertainty is taken into account, there is little to choose between the two policy instruments.

4.5. Environmental costs due to reduced use of solar energy The environmental costs of the tariffs are estimated under the assumption that the decreased domestic consumption of solar energy induced by the tariffs is completely replaced by conventional electricity. According to the U.S. Environmental Protection Agency (EPA), the US electricity power sector in 2016 emitted 1928 million metric tons of carbon dioxide (CO2), equal to about 35% of the total US energy-related CO2 emissions in that year. Total US production of electrical power in 2016 was 4076,674,984 Megawatthours (MWh). Therefore, the amount of CO2 emissions from producing electrical power in 2016 was 0.47 MT/MWh. Multiplying this ratio by 8784 h (the total hours in 2016) yields 4155 metric tons of CO2 per MW of electricity generated. According to model simulations, the 30% discriminatory tariff caused 575 MW of energy from conventional electricity to be substituted for solar power. This is equivalent to an increase in CO2 emissions of 2389,125 metric tons (= 575 MW x 4155 metric tons/MW) The average technical estimation of social cost per metric ton of CO2 emissions in 2015 (in 2007 dollars) was $36 (EPA, 2016). Therefore, the total cost of switching energy from solar power to conventional electricity in 2016 was approximately $115 million in 2017 dollars. A similar set of calculations indicates the 30% uniform tariff would 529

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Appendix A See Tables A.1 and A.2. See Figs. A.1–A.5. Table A.1 US solar panel imports, production, consumption, and price. Variable

Q2 Q3 Q1 s Q1d k1 k2

k3 PUS

Definition

Value

Net imports from China and Taiwan Net imports from ROW US production of solar cells and modules US consumption (= Q1s + Q2 + Q3) US quantity share (= Q1s/ Q1d) China’s and Taiwan’s quantity share (= Q2/Q1d) ROW’s quantity share (= Q3/Q1d Market price of solar cells and modules

2002

2006

2011

2016

26 8 201

105 − 31 401

2767 514 2389

3451 5441 2475

235 0.85 0.12

474 0.85 0.22

5670 0.42 0.49

14,155 0.17 0.25

0.03 2.9

−0.07 2.8

0.09 1.3

0.58 0.7

Note: Quantity unit is megawatts and price unit is dollars per peak watt. Table A.2 Employment, production, and imports in the US solar panel sector, 2010–2016e. Item

Unit

2010

2011

2012

2013

2014

2015

2016

Average

Manufacturing employees Installation & their employees Domestic production Imports Employee/domestic production Employee/imports

Person Person GW GW Person/GW Person/GW

24,916 68,586 2411 2803 10 24

24,064 76,173 2389 5650 10 13

29,742 89,275 1471 6627 20 13

29,851 112,846 1658 7518 18 15

32,490 141,317 1397 7336 23 19

30,282 178,576 1920 11,940 16 15

38,121 221,954 2475 14,884 15 15

36,885 213,386 1960 8108 16 17

Fig. A.1. US solar panel exports and imports from 2002 to 2016. Source: the US Environment Protection Agency, 2018

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Fig. A.2. Annual total demand of renewable and solar energy in the US from 1984 to 2016. Source: the US Environment Protection Agency, 2018

Fig. A.3. Annual exports and imports of solar modules, solar cells, and trading prices for the US from 1999 to 2016. Source: the US Environment Protection Agency, 2018

Fig. A.4. Import values of solar cells and modules from major countries ($) from 2002 to 2016. Source: the US Environment Protection Agency, 2018

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Fig. A.5. Solar Industry employment growth from 2010 to 2017. Source: The Solar Foundations’ National Solar Jobs Census 2017

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