This study aims to investigate whether the trade deflection and creation effects exist in Taiwanese air freight under the U.S.-China trade war. In order to examine the effects, the air freight volume is included. The import and export volume are classified into 38 air freight categories over the period of April, 2010 to November, 2019 through three channels, i.e., Taoyuan International airport (TPE), Kaohsiung airport (KHH) and both airports (the aggregation of TPE and KHH). With the weighted average unit prices, the trade value is also calculated as the dependent variable. Under the U.S.-China trade war, several tariffs lists were implemented by Trump’s administration, including list 1 (L1) in July, L2 in Aug, L3 with 10% tariffs in Sep during 2018, L3 modified to 25% in May and L4A in Sep during 2019. The tariffs rates ranging from 15% to 25% affect, according to the office of the U.S. Trade Representative, estimated total trade value of
$550 billion from China to the U.S. Because of high correlation between the L1 and L2, the latter is dropped for an unbiased estimation. This study also controls the REER of NTD for the value of the currency and the real GDP of Taiwan and the U.S. for the scales of the economies. As for methodology, I use the OLS model (model (1)) and the fixed effect models (model (2)) as well as several extensions, including the specific effect of the five main category (model (3)), the 1-month lagged dependent variable as dynamic setting variable (model (4)), the leading variables of the policy dummies (model (5)), and the category specific time trend effect (model (6)).
I find that the actual empirical results in this study are somewhat different from expected. For the imports (trade deflection), the implementation of the first tariffs list (L1) has a significant increase on the import volume through both airports by 129.7%
and the import value by 154.7%. For the specific effect of the five main categories, the part A of the fourth tariffs list (L4A) increases the import value by 76.5% for the five
‧
main categories. But most of the results are insignificant. Furthermore, the implementations of L3_25 and L4A result in decrease of the import volume through both airports by 98.7% and 67.6%, as well as the import value by 100% and 55.4% to 65.4%, respectively. Besides, the leading policy dummy shows a significant decrease on both approaches for the import side when the first tariffs list (L1) is in practice.
For the exports (trade creation), with the implementation of the third tariffs list with 10% additional tariffs rates (L3_10), the export value significantly increases by 60.1%. And, when L4A takes effect, the export volume through both airports and the export value significantly increase by 61.7% and 122%, respectively. As for the specific effect of the five main categories, I find all results are insignificant. The leading policy variable of L3_10 significantly stimulates the export volume through both airports.
Throughout these results, all dynamic panel settings with the 1-month lagged dependent variables have positive effects on the dependent variables. From the results above, I conclude that the U.S.-China trade war results in a statistically significant trade deflection effect of the imports from China to Taiwan with the implementation of the first tariffs list (L1). In addition, the trade creation effect is observed especially with the implementation of L3_10 and L4A, resulting in a statistically significant increase on the export volume through both airports and the export value from Taiwan to the U.S.
The lead of the L3_10 implementation also induces a significant growth for the export volume through both airports. However, the results above could not explain those insignificant or even negative estimations, hence, the limitations of this study need to be discussed in the following paragraph.
The potential limitations of this study are as follows. First, inevitably, because of limitations on the data, this study is not able to separate the trade flow belonging to the trade deflection and creation effects from general trading volume. What the data presents is a mixed trade flow for all kinds of usages and goals, namely, in either trade
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
30
deflection or creation, the trade flow of trade deflection is blended with the trade flow that regards Taiwan as a destination or a transshipment place. Therefore, without the
“clear and pure” data, the change of the dependent variable may not truly reflect the effect of trade deflection and creation. The difficulty in pure data accessibility is, hence, one of the limitations for further research on international trade barriers. Secondly, the matching between the air freight category and HS code may not accurately identify the exact commodity targeted in the lists. In the tariffs lists, not all the commodities with 4-digits HS code are targeted. However, due to the limitation on classification of the air freight category, the category could only be corresponded on the level of 2-digits HS code. Hence the whole group of the category is considered as the target of the tariffs lists. Consequently, the results might possibly be biased. Lastly, as mentioned by Steinbock (2019), to expand the power of the country, more and more unilateral policies may be implemented globally. Hence, China, Taiwan or the third country may take various counter actions or responses into practice. The failure to consider the reactions of the third country or China, especially for retaliation trade policies, is a possible explanation for the inconsistent results. With the consideration of the trade barriers and responses from other trading partners, further research on the formal relationship between the effects of trade deflection and creation and the counter action to the implementation of tariffs could be a possible field to study.
‧
Tariffs on Prices and Welfare. The Journal of Economic Perspectives, 33(4), 187-210. doi:10.2307/26796842[2]. Baltagi, B. H. (2005). Econometric analysis of panel data / Badi H. Baltagi (3rd ed. ed.). Chichester, West Sussex, England ;: J. Wiley & Sons.
[3]. Bown, C. P., & Crowley, M. A. (2007). Trade deflection and trade depression.
Journal of international economics, 72(1), 176-201.
doi:10.1016/j.jinteco.2006.09.005
[4]. Geloso Grosso, M., & Shepherd, B. (2011). Air cargo transport in APEC:
Regulation and effects on merchandise trade. Journal of Asian Economics, 22(3), 203-212. doi:https://doi.org/10.1016/j.asieco.2011.02.004
[5]. Giles, D. E. (2011). Interpreting dummy variables in semi-logarithmic regression models: Exact distributional results. University of Victoria Department of
Economics Working Paper EWP, 1101, 1-24.
[6]. Industry High Level Group (IHLG). (2019). Aviation Benefits Report 2019.
Retrieved from https://www.icao.int/sustainability/Documents/AVIATION-BENEFITS-2019-web.pdf
[7]. International Air Transportation Association (IATA). (2018). How would a global trade war affect aviation? Retrieved from
https://www.iata.org/contentassets/59f6c514672d4900b4d30895d8170f4f/trade2 0wars20note.pdf
[8]. Kennedy, P. E. (1981). Estimation with Correctly Interpreted Dummy Variables in Semilogarithmic Equations. The American economic review, 71(4), 801-801.
[9]. Nicita , A. (2019). Trade and trade diversion effects of United States tariffs on
‧
China. UNCTAD Research Paper No. 37.
[10]. Office of the United States Trade Representative. China Section 301-Tariff Actions and Exclusion Process. Retrieved from https://ustr.gov/index.php/issue-areas/enforcement/section-301-investigations/tariff-actions
[11]. Shibata, H. (1967). The Theory of Economic Unions: A Comparative Analysis Fiscal Harmonization in Common of Customs Unions, In C. S. Shoup (Eds.).
264.
-, 145 kets, Volume I:Theory Mar
[12]. Skoglund, L. (2018). Evidence of Trade Deflection: Investigating the Impact of US Antidumping on EU Imports. Retrieved from
[13]. Steinbock, D. (2019). U.S.-China Trade War and Its Global Impacts. China Quarterly of International Strategic Studies, 04(04), 515-542.
doi:10.1142/s2377740018500318
[14]. Taoyuan International Airport Corporation. (2018). The analysis of the air freight competitivity and development strategy planning for Taoyuan International Airport. Retrieved from
https://www.taoyuanairport.com.tw/upload/cont_att/173696b1-d951-4625-a521-873dcb9061a6.pdf
[15]. Tu, X., Du, Y., Lu, Y., & Lou, C. (2020). US-China Trade War: Is Winter Coming for Global Trade? Journal of Chinese Political Science. doi:10.1007/s11366-020-09659-7
[16]. Wooldridge, J. M. (2016). Introductory econometrics : a modern approach / Jeffrey M. Wooldridge (Sixth edition. ed.). Boston: Cengage Learning.
[17]. Yang, S., & Martinez-Zarzoso, I. (2014). A panel data analysis of trade creation and trade diversion effects: The case of ASEAN–China Free Trade Area. China Economic Review, 29, 138-151. doi:https://doi.org/10.1016/j.chieco.2014.04.002
‧ 國
立 政 治 大 學
‧
Na tiona
l Ch engchi University
33
Figure 1. Dynamic Changes in the Size of Trade Flows Following an Establishment of an Antidumping Duty(illustrated by the author according to Bown and Crowley (2007))
‧ 國
立 政 治 大 學
‧
Na tiona
l Ch engchi University
34
Figure 2. The Trend of Aggregated Air Freight Volume over Time
Note: Y-axis is logged air freight volume (kg) through both airports. And X-axis is month, i.e., 2010 Apr. is April, 2010.
‧ 國
立 政 治 大 學
‧
Na tiona
l Ch engchi University
35
Table 1. The Implementation of Tariffs Lists (organized from the Office of the United States Trade Representative) Value of U.S. Imports Date of Notice of Action
Released
Date of Implementation Rate of Tariffs
List 1 $34 bn June 6, 18 July 6,18 25%
List 2 $16 bn August 16, 2018 August 23, 2018 25%
List 3 $200 bn
September 21, 2018 September 24, 2018 10%
May 9, 2019 May 10, 2019 Modified to 25%
List 4 $300 bn August 20, 2019 September 1, 2019 15%
‧
Table 2. The List of Variables
*Notes: The expected signs of the main independent dummy variables (𝐿𝐿1𝑗𝑗𝑗𝑗, 𝐿𝐿2𝑗𝑗𝑗𝑗, 𝐿𝐿3_10𝑗𝑗𝑗𝑗, 𝐿𝐿3_25𝑗𝑗𝑗𝑗 and 𝐿𝐿4𝑙𝑙𝑗𝑗𝑗𝑗) for average unit price may be ambiguous since the effect of implementation of tariffs list on the price is unclear.
Variables Notations Expected signs Description
Trade volume
𝑙𝑙𝑙𝑙𝑗𝑗𝑗𝑗
𝑙𝑙𝑄𝑄𝑗𝑗𝑗𝑗
𝑙𝑙𝑙𝑙𝑗𝑗𝑗𝑗
Dependent variable. Imports or exports volume of China or the U.S. for air freight category 𝑗𝑗 in month 𝑡𝑡 including TPE ( 𝑙𝑙), KHH ( 𝑄𝑄) and their aggregation ( 𝑙𝑙). (Unit: kg)
Trade value 𝑙𝑙𝑗𝑗𝑗𝑗 Dependent variable. Value of trade of air freight category 𝑗𝑗 in month 𝑡𝑡. (Unit: US$) List 1* 𝐿𝐿1𝑗𝑗𝑗𝑗 + Dummy variable. It shows whether the air freight category 𝑗𝑗 is subjected to the tariffs list 1 in
month 𝑡𝑡.
List 2* 𝐿𝐿2𝑗𝑗𝑗𝑗 + Dummy variable. It shows whether the air freight category 𝑗𝑗 is subjected to the tariffs list 2 in month 𝑡𝑡.
List 3_10* 𝐿𝐿3_10𝑗𝑗𝑗𝑗 + Dummy variable. It shows whether the air freight category 𝑗𝑗 is subjected to the tariffs list 3 with 10% tariff rates in month 𝑡𝑡.
List 3_25* 𝐿𝐿3_25𝑗𝑗𝑗𝑗 + Dummy variable. It shows whether the air freight category 𝑗𝑗 is subjected to the tariffs list 3 with 25% tariff rates in month 𝑡𝑡.
Real effective exchange rate of Taiwan in month 𝑡𝑡.
GDP 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑖𝑖𝑗𝑗
𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑖𝑖𝑗𝑗
+ Country 𝑖𝑖 (Taiwan or the U.S.)’s gross domestic product in month 𝑡𝑡. (Unit: US$1 billion)
‧ 國
立 政 治 大 學
‧
Na tiona
l Ch engchi University
37
Table 3. Descriptive Statistics
Variables Notations Mean Median Standard Deviation Observations
Imports Exports Imports Exports Imports Exports Imports Exports
Trade volume
𝑙𝑙𝑙𝑙𝑗𝑗𝑗𝑗 219081.3 349090.9 8959.5 0 778374.1 1352304 4408 4408
𝑙𝑙𝑄𝑄𝑗𝑗𝑗𝑗 11195.1 8478.5 0 0 42938.6 34220.76 4408 4408
𝑙𝑙𝑙𝑙𝑗𝑗𝑗𝑗 230276.4 357569.4 9552 1 818831.4 1384078 4408 4408 Trade value 𝑙𝑙𝑗𝑗𝑗𝑗 1740889 7886238 36052.2 .9141421 6314744 7886238 3709 3520
List 1 𝐿𝐿1𝑗𝑗𝑗𝑗 .0269964 0 .1620911 4408
List 2 𝐿𝐿2𝑗𝑗𝑗𝑗 .0326679 0 .177786 4408
List 3_10 𝐿𝐿3_10𝑗𝑗𝑗𝑗 .0490018 0 .2158963 4408
List 3_25 𝐿𝐿3_25𝑗𝑗𝑗𝑗 .0428766 0 .2026018 4408
List 4A 𝐿𝐿4𝑙𝑙𝑗𝑗𝑗𝑗 .0197368 0 .1391103 4408
Real effective exchange rate 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑗𝑗 102.2103 101.3 2.921844 4408
GDP 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑖𝑖𝑗𝑗 44.80823 44.40108 4.325221 4408
𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑖𝑖𝑗𝑗 6000.513 5984.151 660.4428 4408
‧
Table 4. Air Freight Categories Matching
Code Air Freight Category HS code Relevant Tariffs Lists
1 Total All N/A
2 Agricultural Products 06、07、08、09、10、
11、12、13、14、15 L3 L4
11 Processed Food 16、17、18、19、20、
21、23 L3 L4
14 Textile’s Accessories 61、62、64、65 L3 L4
15 Hides& Leather 41、42、43 L3 L4
19 Chemical Products 29、30、31、32、33、
34、35、36、37、38 L2 L3 L4
20 Plastic& Rubber 39、40 L1 L2 L3 L4
21 Non-Metal Mineral
Products 68、69、70 L2 L3 L4
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
39
Table 4. Air Freight Categories Matching (cont.)
Code Air Freight Category HS code Relevant Tariffs Lists 22 Base Metals
7106~15、7108、72、
73、74、75、76、77、
78、79、80、81
L2 L3 L4
23 Metal Products 82、83 L3 L4
24 Machines 84 L1 L2 L3 L4
25 Electronics 85 L1 L2 L3 L4
26 Transportations 86、87、88、89 L1 L2 L3 L4
27 Precision Instruments 90、91、92 L1 L2 L3 L4
28 Others 94、96、66、67 L3 L4
29 Arts& Antiques 97 L4
30 Special Goods
31 Baggage
32 Diplomatic Mails 33 Jewelry& Valuables
34 Toys 9501-9503
35 Educational
Equipment 9608-9612 L4
36 Sports Equipment 9504-9508 L4
37 Airliners Cargo
38 Military Supplies 93 L4
‧ 國
立 政 治 大 學
‧
Na tiona
l Ch engchi University
40
Table 5. The Results of the Wooldridge Test
Note: P-values is presented in parentheses. ***, **, and * denote the statistical significance at 1, 5, and 10% levels, respectively.
Approach (a) (b) (c) (d) (e)
Trade Deflection 3.579 9.084*** 3.333* 0.119 1.405
(Exports) (0.07) (0.01) (0.08) (0.73) (0.24)
Trade Creation 1.684 0.006 4.881** 0.035 4.630**
(Imports) (0.21) (0.94) (0.04) (0.85) (0.04)
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
41
Table 6. The Results of the OLS and Baseline Fixed Effect Mode
Note: Clustered standard errors are presented in parentheses. ***, **, and * denote the statistical significance at 1, 5, and 10% levels, respectively.
‧
Table 7. The Results of the Import Side Fixed Effect Models
Note: Clustered standard errors are presented in parentheses. ***, **, and * denote the statistical significance at 1, 5, and 10% levels, respectively.
Approach
Model 3 4 5 6 3 4 5 6
0.08 -0.08 0.90** -0.01 0.04 -0.08 1.05** 0.20 (0.35) (0.21) (0.37) (0.34) (0.45) (0.26) (0.48) (0.41)
-1.21 -0.76 -1.12 -0.47 -1.44 -0.80 -1.94 -0.67 (1.15) (0.71) (0.91) (1.06) (1.49) (1.07) (1.53) (1.47)
-1.60 -1.07 -3.33** -0.78 -2.14 -1.60 -5.60** -1.25 (1.31) (0.78) (1.42) (1.16) (1.52) (0.99) (2.69) (1.49)
-0.11 -0.19 0.03 -1.02** -0.58 -0.51 -0.95** -0.78***
(0.67) (0.41) (0.65) (0.46) (0.66) (0.47) (0.47) (0.23)
L1×Top5 -0.42 -0.60
‧
Table 7. The Results of the Import Side Fixed Effect Models (cont.)
Note: Clustered standard errors are presented in parentheses. ***, **, and * denote the statistical significance at 1, 5, and 10% levels, respectively.
Approach
Constant 8.32*** 5.49*** 8.32*** 24.86*** 8.97*** 6.36*** 8.97*** 28.58***
(0.38) (0.58) (0.38) (3.01) (0.48) (0.56) (0.48) (3.95)
Observation 3712 3680 3680 3712 3593 3559 3562 3593
R-sq 0.058 0.173 0.060 0.229 0.058 0.132 0.062 0.169
Cat. Dummy Yes Yes Yes Yes Yes Yes Yes Yes
Month dummy Yes Yes Yes Yes Yes Yes Yes Yes
(b) (a)
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
44
Table 8. The Results of the Export Side Fixed Effect Models
Note: Clustered standard errors are presented in parentheses. ***, **, and * denote the statistical significance at 1, 5, and 10% levels, respectively.
‧ 國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
45
Table 8. The Results of the Export Side Fixed Effect Models (cont.)
Note: Clustered standard errors are presented in parentheses. ***, **, and * denote the statistical significance at 1, 5, and 10% levels, respectively.