Outline

1. Three Chapters
   • Chapter 1: Computable General Equilibrium (CGE) Model Analysis of Taiwan Joins RCEP
   • Chapter 2: How China and WTO Impact Labor Welfare across Industries in Taiwan?
   • Chapter 3: How Open-Border to Chinese Tourists Realign Ideology?
     • Originally Circulated under the Title: “Distance is the Soul of Beauty: How Open-Border Policy Realign Ideology?”
2. To-do List
3. Conclusions
4. Q & A
   • Asynchronous Q & A, please email to jeffkuo@gwu.edu

Overview

1. Theme
   • China Syndrome
     • This terms is borrowed from international trade literature
     • Autor, David H., David Dorn, and Gordon H. Hanson. 2013. “The China Syndrome: Local Labor Market Effects of Import Competition in the United States.” American Economic Review, 103 (6): 2121-68.
   • From the view of Taiwan…
     • Microscope China-Taiwan Economic and Political Relationship
     • Theoretical and Counter-factual Analysis
       • Computable General Equilibrium (CGE) Models
       • Database & Software -> GTAP / RunGTAP
     • Empirical and Applied Econometric Studies
       • Use data published by Taiwanese governments
       • Instrumental Variables (IV) and 2SLS, Difference-in-Differences (DiD), Regression Discontinuity Design (RD)

Overview

2. Contributions
   • Thoroughly Analyze China Syndrome / China Shock from Taiwanese Perspectives
   • Comprehensively Examine China-Taiwan Economic-political Relationship in WTO Era
   • Includes Both Theoretical and Empirical Approaches

Chapter 1 | CGE and Regional Integration

• Main Question
  • If Taiwan joins RCEP (Regional Comprehensive Economic Partnership), how does it affect China, the U.S., and the rest of world?
• Data & Methodology
  • GTAP / RunGTAP
• CGE Models

  • General equilibrium recognizes that there are many markets and that they interact in complex ways so that loosely speaking, everything depends on everything else.

  • A key component of GTAP is a CGE model known as the GTAP Model, which is briefly documented in the GTAP book (Hertel, 1997). Another component of this project is the GTAP Data Base which underlies the GTAP Model.

Chapter 1 | GTAP Setting - Region Aggregation

GTAP Region Aggregation

Chapter 1 | GTAP Setting - Shock Experiment

Policy Shock - Set Target Import Tariff = 0

Chapter 1 | Simulation Results - VGDP

Value of GDP Change

Chapter 1 | Simulation Results - EV

Welfare Change in EV (US $ in Millions)

Chapter 1 | Simulation Results - Export

Volume of Merchandise Export (%)

Chapter 2 | Labor Markets and China Shock

Trade Openness Trend, source: DGBAS

Taiwan GDP Trend, source: World Bank

Chapter 2 | Main Question & Data

• How does trade volume affect the sector’s return of factors and profits?
  • Does China Shock and joining WTO play a part?
• Which Sector was affected the most:
  • Agriculture, Manufacture, Service, or Information and Communications Technology (ICT)?
• Aggregate Level Data
  • Trade Volume = Export + Import
  • Total Profits of Firms
  • Total Return of Production Factors
• Trade Volume
  • Source
    • Directorate General of Budget, Accounting and, Statistics

Chapter 2 | Variables & Identifications

• Two main dependent variables

  • Total Profits of the firms
  • Total Returns of the production factors

• Benchmark OLS model \[\begin{align} \text{Total Profits}_\text{i,t} &= \nonumber \beta_0 + \beta_1 \text{Trade}_\text{i,t} +\beta_2\text{China}_\text{i,t} +\beta_3\text{WTO}_\text{i,t}+ \varepsilon_\text{t} \\ \text{Total Returns of Factors}_\text{i,t} &= \nonumber \beta_0 + \beta_1 \text{Trade}_\text{i,t} +\beta_2\text{China}_\text{i,t} +\beta_3\text{WTO}_\text{i,t}+ \varepsilon_\text{t} \end{align}\] \[\text{i} = \text{Agriculture(A), Manufacture(M), and Services (S)},\quad\text{t} = \text{Year 1981--2015}.\quad (\text{T}=35) \]

  • \(\text{China}_{it}\) and \(\text{WTO}_{it}\) are the binary dummy variables 0,1
  • I also explore the per capita level of data (divided by the total labor and firms)
  • IV and 2SLS results are the core of this chapter

• Instrument

  • CO2 permission per year in Taiwan
    • Source U.S. Energy Information Administration

Chapter 2 | 2SLS Results Summary

2SLS Model Result, Aggregate Data

• Note
  • WTO and China do NOT have a significant effect on both profits and returns
  • After adding the instrument, the Trade volume could explain both returns and profits.
  • Service sector surprisingly is the one affected the most by the trade.

Chapter 3 | Chinese Tourists and Ideology

• Introduction
  • Old wisdom: Free Trade Agreement -> Economic Integration -> Political Integration
  • ECFA is a counter-example of this process
• Motivation
  • People tend to like each other when they are NOT familiar with each other.
  • This is also the case of China-Taiwan economic integration.

    • “…because of misunderstands unifies, because of understood that separates.”

• Main Questions
  • Question 1: “Do open border policies help the political integration?”
  • Question 2: “Does China-Taiwan case violate the progressive integration theory?”
  • Question 3: “Does the heterogeneous exposure to Chinese visitors realign the ideology?”
• Result Preview
  • Answer 1: No / Answer 2: Yes / Answer 3: Yes (The treatment effects in RD models become more significant after the shock)

Chapter 3 | Literature & Contribution

Chapter 3 | Policy Shock in Chinese Tourists

• In 2008,
  • Cross-strait Economic Cooperation Framework Agreement was rectified (ECFA Full Text)
  • Chinese Visitors to Taiwan dramatically increased

Chapter 3 | Ideological Realignment: Pre- v.s. Post - ECFA

• Fact
  • Bipartisanship. Blue: KMT, pro-China party; Green: DPP, against-China party
  • Pattern? Which regions switch their party recognition the most?
  • Main outcome variables in RD model is pro-China Margin (KMT vote - DPP vote)

Chapter 3 | Data Sources

Chapter 3 | Identification

• Methodology: Sharp Regression Discontinuity Design
  • cutoff (c): sample mean of the distances
• Identification
  • Sharp RD Design (Lee 2008; Lee and Lemieux 2010)

\[Y_{i} = D_i\tau + W_i \delta_1 + U_i \tag{RD1} \] \[D_i = 1[X_i \ge c] \tag{RD2} \] \[X_i = W_i\delta_2 + V_i \tag{RD3}\]

• Variables
  • \(Y_i\) : Outcome variables. K-D Margin, K%-D%
  • \(D_i\) : Treatment. The district is exposed to tourists or not.
  • \(X_i\) : Assigning variable. The travel time to TPE airport.
  • \(W_i\) : Unobserved endogenous variable. The real tourist numbers; which is assumed to have the effect on the result of election \(Y_i\).
  • According to tourist trade literature that distance negatively correlates with the number of tourists, so that \(\delta_2\) \(\neq 0\).

Chapter 3 | Algorithm

1. Calculate the distance between the municipalities and the tourists attractions.
2. Calculate the mean of distances, set the municipalities into control and treatment group.
3. Set the mean of the distance as the cutoff to the close and away regions.
4. Run the regression discontinuity using the 2004, 2008, 2012, 2016, 2020 presidential electoral data.
5. Compare the treatment effects across the different elections.
6. Regression those treatment effects on the importing number of the Chinese tourists. \[ \text{Treatment Effect}_t = \beta_0 + \Sigma_{s=0}^3 \beta_s \text{Chinese Tourist}_{t-s} + \varepsilon_t \]

Chapter 3 | Result Preview: RD Graphs

• Different local polynomial assumptions

Future work / To-do List

• Chapter 1 - CGE and Regional Integration
  • Look into in the different production sectors
  • Expand it into the context of CPTPP
• Chapter 2 - Labor Market China Shocks
  • Make IV and 2SLS become more convincing
  • Run Unit-root Test and try a time-series approach
• Chapter 3 - Open Policy to Chinese Tourists, Ideological Realignment
  • Construct a trade theoretical model and explore the potential mechanism
  • Add the other electoral results
• Thank YOU!
  • It’s really nice to see you, (though it’s on Zoom).
  • I really appreciate TERP’s research support.
  • Happy The End of Semester, Spring 2022.
  • Hope to see you in NATSA’s Annual Meeting in July!