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The Effect of Political Leaders ’ Educational and Professional Background on Trade Liberalization

The Effect of Political Leaders ’ Educational and Professional Background on Trade Liberalization. Evidence from Tariff Rates, 1988-2005. Marek Hlav áč , MPP. Harvard University. Political Economy and Government hlavac @fas.harvard.edu. Bratislava Economic Meeting June 8 th , 2012.

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The Effect of Political Leaders ’ Educational and Professional Background on Trade Liberalization

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  1. The Effect of Political Leaders’ Educational andProfessional Background on Trade Liberalization Evidence from Tariff Rates, 1988-2005 MarekHlaváč, MPP Harvard University Political Economy and Government hlavac@fas.harvard.edu Bratislava Economic Meeting June8th, 2012 Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 1 / 18

  2. Overview I examine the effect of political leaders’ educational and professional backgrounds on trade liberalization, as measured by the level of tariff ratesimposed on imported goods and services. I find that, during the timeperiod from 1988 until 2005, countries with university-educated chiefgovernment executives imposed lower tariffs than countries whose leadersdid not have a university education. Leaders’ educational background ineconomics is associated with greater reductions in tariff rates than abackground in law. A professional background in the military or as a unionleader is associated with higher tariff rates. These results suggest that theeducational and professional backgrounds of government leaders can haveimportant effects on trade policy. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 2 / 18

  3. Section 1: Hypotheses and Theoretical Background Three Hypotheses Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 3 / 18

  4. Section 1: Hypotheses and Theoretical Background Three Hypotheses Hypothesis 1: A government leader’s university-level educationalqualification will be associated with a reduction in the level of tariffrates, compared to the baseline of not having a university education. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 3 / 18

  5. Section 1: Hypotheses and Theoretical Background Three Hypotheses Hypothesis 1: A government leader’s university-level educationalqualification will be associated with a reduction in the level of tariffrates, compared to the baseline of not having a university education. Hypothesis 2: A government leader’s educational background in economics will be associated with a lower level of tariff rates than aneducational background in law. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 3 / 18

  6. Section 1: Hypotheses and Theoretical Background Three Hypotheses Hypothesis 1: A government leader’s university-level educationalqualification will be associated with a reduction in the level of tariffrates, compared to the baseline of not having a university education. Hypothesis 2: A government leader’s educational background in economics will be associated with a lower level of tariff rates than aneducational background in law. Hypothesis 3: A government leader’s professional background in scientific economics will be associated with a lower level of tariff ratesthan a professional background in law. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 3 / 18

  7. Section 1: Hypotheses and Theoretical Background Hypothesis 1 Hypothesis 1: A government leader’s university-level educationalqualification will be associated with a reduction in the level of tariffrates, compared to the baseline of not having a university education. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 4 / 18

  8. Section 1: Hypotheses and Theoretical Background Hypothesis 1 Hypothesis 1: A government leader’s university-level educationalqualification will be associated with a reduction in the level of tariffrates, compared to the baseline of not having a university education. Stolper-Samuelson Theorem (1941): gain/loss from trade based onfactor abundance (e.g., Mayda, 2005; Mayda and Rodrik, 2005) Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 4 / 18

  9. Section 1: Hypotheses and Theoretical Background Hypothesis 1 Hypothesis 1: A government leader’s university-level educationalqualification will be associated with a reduction in the level of tariffrates, compared to the baseline of not having a university education. Stolper-Samuelson Theorem (1941): gain/loss from trade based onfactor abundance (e.g., Mayda, 2005; Mayda and Rodrik, 2005) Reevaluation by Hainmueller and Hiscox (2006) Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 4 / 18

  10. Section 1: Hypotheses and Theoretical Background Hypothesis 1 Hypothesis 1: A government leader’s university-level educationalqualification will be associated with a reduction in the level of tariffrates, compared to the baseline of not having a university education. Stolper-Samuelson Theorem (1941): gain/loss from trade based onfactor abundance (e.g., Mayda, 2005; Mayda and Rodrik, 2005) Reevaluation by Hainmueller and Hiscox (2006) Lack of labor market pressures for government leaders: Ideationalchannel more likely Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 4 / 18

  11. Section 1: Hypotheses and Theoretical Background Hypotheses 2 and 3 Hypothesis 2: A government leader’s educational background in economics will be associated with a lower level of tariff rates than aneducational background in law. Hypothesis 3: A government leader’s professional background in scientific economics will be associated with a lower level of tariff ratesthan a professional background in law. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 5 / 18

  12. Section 1: Hypotheses and Theoretical Background Hypotheses 2 and 3 Hypothesis 2: A government leader’s educational background in economics will be associated with a lower level of tariff rates than aneducational background in law. Hypothesis 3: A government leader’s professional background in scientific economics will be associated with a lower level of tariff ratesthan a professional background in law. Economics: survey experiment by Hiscox (2006); consensus about efficiency benefits of trade liberalization; experiments about the effectof economics education on attitudes and behavior Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 5 / 18

  13. Section 1: Hypotheses and Theoretical Background Hypotheses 2 and 3 Hypothesis 2: A government leader’s educational background in economics will be associated with a lower level of tariff rates than aneducational background in law. Hypothesis 3: A government leader’s professional background in scientific economics will be associated with a lower level of tariff ratesthan a professional background in law. Economics: survey experiment by Hiscox (2006); consensus about efficiency benefits of trade liberalization; experiments about the effectof economics education on attitudes and behavior Law: This needs work. So far, Murphy, Shleifer and Vishny (1991) onrent-seeking and growth. Looking for survey data about lawyers’attitudes towards trade, regulation in general. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 5 / 18

  14. Section 2: Data and Empirical Strategy Dependent Variable: Tariff Rates Most Favored Nation (MFN) vs. Applied RatesSimple vs. Import Share-Weighted Product Coverage: All, Manufacturing, Primary Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 6 / 18

  15. Section 2: Data and Empirical Strategy Independent Variable of Interest: Leader’s Background set of dummies from Dreher et al. (2008) Education: 7 categories Profession: 11 categories Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 7 / 18

  16. Section 2: Data and Empirical Strategy Control Variables Level of Economic Development: real GDP per capita Rate of Economic Growth: lagged real GDP growth Political Regime: democracy dummy based on Polity IV Government Idelogy: omitted due to data availability: suggestions? Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 8 / 18

  17. Section 2: Data and Empirical Strategy List of Countries Included in the Sample Algeria China India Mexico Portugal Switzerland Moldova Romania SyriaNetherlands Russian Federation Tanzania Argentina Colombia Ireland Australia Costa Rica Israel Austria Czech Republic Italy New Zealand Saudi Arabia Thailand Bangladesh Denmark JapanBelgium Ecuador Kenya Nicaragua Singapore TogoNorway Slovakia Tunisia Bolivia Egypt Lebanon Panama Slovenia Turkey Brazil Finland Madagascar Paraguay South Africa United Kingdom Bulgaria France Malaysia Peru Spain United States Canada Germany Mali Philippines Sri Lanka Uruguay Chile Greece Mauritius Poland Sweden Venezuela Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 9 / 18

  18. Section 2: Data and Empirical Strategy Summary Statistics Variable Source Unit Observations Mean Standard Deviation GDP per capita WDI (2011) constant 2005 inter- 1,181 13.817 11.207 national dollars, PPP, thousands GDP growth ratet−1 WDI (2011) percent, annual 1,169 3.168 4.531 Democracy Polity IV (2011) dummy (0/1) 1,152 0.759 0.428 Education Dreher et al. (2008) dummy (0/1) — Unknown 1,174 0.054 0.225 — Not University 1,174 0.193 0.395 — Economics 1,171 0.180 0.385 — Law 1,174 0.252 0.434 — Politics 1,174 0.062 0.242 — Natural Science 1,174 0.035 0.184 — Other University 1,174 0.213 0.410 Profession Dreher et al. (2008) dummy (0/1) — Unknown/None 1,174 0.013 0.112 — Entrepreneur 1,174 0.018 0.133 — White Collar 1,174 0.120 0.325 — Blue Collar 1,174 0.017 0.129 — Union Executive 1,174 0.027 0.163 — Science (Economics) 1,174 0.043 0.202 — Science (Other) 1,172 0.074 0.262 — Law 1,174 0.112 0.316 — Military 1,174 0.152 0.360 — Politician 1,174 0.342 0.474 — Other 1,174 0.072 0.258 Note: One observation represents a country-year. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 10 / 18

  19. Section 2: Data and Empirical Strategy Empirical Model Ordinary Least Squares (OLS) with the following specification: TariffRatei ,t = αControlsi,t + βBackgroundi,t + γYeart + ϵi ,t , (1) where Controlsi ,t is a vector of control variables, Backgroundi ,t is a vectorof education or professional background dummies, and ϵ is a well-behavedstochastic error term. The subscripts iand t index countries and years,respectively. In all specifications, a set of year dummies (Yeart ) is included to accountfor changes to tariff rate levels that affect all countries in a given year:attitudes towards governance, multilateral trade negotiation rounds? Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 11 / 18

  20. Section 3: Estimation Results Estimation Results: All Products, Education Dependent Variable: Tariff Rate, All Products Most Favored Nation, Most Favored Nation, Applied, Applied, simple weighted simple weighted −0.790∗∗∗ −0.527∗∗∗ −0.953∗∗∗ −0.610∗∗∗ GDP per capita (0.132) (0.107) (0.127) (0.108) (GDP per capita)2 0.013∗∗∗ −0.008∗∗∗ 0.016∗∗∗ 0.010∗∗∗ (0.003) (0.002) (0.003) (0.002) 0.160∗ 0.193∗∗ GDP growth ratet−1 0.102 0.136 (0.094) (0.088) (0.092) (0.089) −4.451∗∗∗ −2.861∗∗∗ −4.284∗∗∗ −3.365∗∗∗ Democracy (1.128) (1.013) (1.008) (1.015) Education −3.172∗∗∗ −5.219∗∗ −2.915∗∗∗ −4.965∗ — Economics (0.685) (2.593) (0.638) (2.597) −2.285∗∗∗ −4.243∗ −2.233∗∗∗ — Politics −3.985 (0.639) (2.460) (0.586) (2.463) — Law −0.893 −2.862 −0.137 −2.723 (0.709) (2.435) (0.686) (2.438) −2.485∗∗∗ −4.764∗ −2.376∗∗∗ — Natural Science −4.549 (0.768) (2.752) (0.803) (2.769) −3.197∗∗∗ −4.297∗ −2.509∗∗∗ −3.930∗ — Other University (1.003) (2.204) (0.917) (2.209) 23.154∗∗∗ 19.291∗∗∗ 22.430∗∗∗ 18.997∗∗∗ Constant (1.697) (1.857) (1.504) (1.861) Year effects Yes Yes Yes Yes Observations 698 698 698 698 Adjusted R-squared 0.385 0.118 0.456 0.134 Notes: Statistically significant at the ***1, **5, *10 percent level. Heteroskedasticity-robust standard errors are in parentheses. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 12 / 18

  21. Section 3: Estimation Results Estimation Results: All Products, Profession Dependent Variable: Tariff Rate, All Products Most Favored Nation, Applied, Applied, Most Favored Nation, simple weighted simple weighted −0.913∗∗∗ −1.092∗∗∗ −0.728∗∗∗ GDP per capita −0.645∗∗∗ (0.160) (0.118) (0.152) (0.119) (GDP per capita)2 0.016∗∗∗ 0.011∗∗∗ 0.019∗∗∗ 0.013∗∗∗ (0.004) (0.003) (0.003) (0.003) 0.180∗∗ 0.210∗∗ GDP growth ratet−1 0.110 0.145 (0.091) (0.088) (0.088) (0.089) −3.189∗∗∗ −2.647∗∗∗ −2.966∗∗∗ −3.035∗∗∗ Democracy (1.116) (0.824) (1.025) (0.824) Profession — Entrepreneur 1.079 1.051 1.245 1.401 (1.132) (1.006) (1.406) (1.097) — White Collar 0.216 0.288 0.459 0.399 (0.712) (0.710) (0.648) (0.690) 2.981∗ 3.364∗∗ — Blue Collar 2.213 1.977 (1.624) (1.607) (1.687) (1.511) 3.709∗∗∗ 2.138∗∗ 3.677∗∗∗ 2.191∗∗ — Union Executive (0.863) (1.008) (0.871) (1.009) −1.426∗∗ — Science (Economics) −1.033 −0.483 -0.243 (0.791) (0.877) (0.760) (0.880) — Science (Other) −0.619 0.339 −0.394 0.612 (0.732) (0.855) (0.799) (0.880) 1.439∗∗ 1.982∗∗∗ 2.456∗∗∗ 1.796∗∗∗ — Law (0.661) (0.642) (0.668) (0.637) 5.358∗∗∗ 4.541∗∗∗ 5.001∗∗∗ 4.887∗∗∗ — Military (1.561) (1.423) (1.376) (1.419) 3.025∗∗∗ 3.231∗∗ 3.058∗∗∗ 3.529∗∗ — Politician (0.733) (1.392) (0.696) (1.389) Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 13 / 18

  22. Section 3: Estimation Results Estimation Results: Manufactured Products, Education Dependent Variable: Tariff Rate, Manufactured Products Most Favored Nation, Most Favored Nation, Applied, Applied, simple weighted simple weighted −0.835∗∗∗ −0.994∗∗∗ −0.719∗∗∗ GDP per capita −0.619∗∗∗ (0.138) (0.114) (0.130) (0.116) (GDP per capita)2 0.013∗∗∗ 0.009∗∗∗ 0.017∗∗∗ 0.011∗∗∗ (0.003) (0.003) (0.003) (0.003) 0.205∗∗ 0.154∗ GDP growth ratet−1 0.160 0.115 (0.100) (0.087) (0.097) (0.089) −4.620∗∗∗ −3.767∗∗∗ −4.425∗∗∗ −4.237∗∗∗ Democracy (1.179) (0.959) (1.036) (0.966) Education −2.794∗∗∗ −2.410∗∗∗ −2.726∗∗∗ −2.161∗∗∗ — Economics (0.698) (0.537) (0.656) (0.546) −2.108∗∗∗ −1.676∗∗∗ −2.160∗∗∗ −1.473∗∗∗ — Politics (0.659) (0.543) (0.608) (0.551) — Law −0.084 0.133 0.340 0.253 (0.748) (0.564) (0.713) (0.576) −2.191∗∗∗ −1.528∗∗ −2.182∗∗∗ −1.355∗ — Natural Science (0.784) (0.700) (0.842) (0.757) −2.507∗∗ −1.879∗∗ −2.134∗∗ −1.516∗ — Other University (1.087) (0.867) (0.958) (0.881) 22.853∗∗∗ 18.749∗∗∗ 22.259∗∗∗ 18.495∗∗∗ Constant (1.845) (1.474) (1.567) (1.485) Year effects Yes Yes Yes Yes Observations 698 698 698 698 Adjusted R-squared 0.394 0.403 0.459 0.431 Notes: Statistically significant at the ***1, **5, *10 percent level. Heteroskedasticity-robust standard errors are in parentheses. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 14 / 18

  23. Section 3: Estimation Results Estimation Results: Manufactured Products, Profession Dependent Variable: Tariff Rate, Manufactured Products Most Favored Nation, Most Favored Nation, Applied, Applied, simple weighted simple weighted −0.994∗∗∗ −0.782∗∗∗ −1.150∗∗∗ −0.882∗∗∗ GDP per capita (0.167) (0.146) (0.156) (0.147) (GDP per capita)2 0.017∗∗∗ 0.013∗∗∗ 0.020∗∗∗ 0.015∗∗∗ (0.004) (0.003) (0.004) (0.003) 0.178∗ 0.221∗∗ 0.174∗∗ GDP growth ratet−1 0.135 (0.097) (0.084) (0.092) (0.085) −3.186∗∗∗ −2.478∗∗∗ −3.015∗∗∗ −2.848∗∗∗ Democracy (1.172) (0.956) (1.057) (0.961) Profession 1.974∗ 2.273∗∗ — Entrepreneur 1.449 1.499 (1.205) (1.064) (1.495) (1.158) 1.056∗ 1.102∗ — White Collar 0.756 0.820 (0.658) (0.585) (0.647) (0.582) 3.311∗∗ 3.292∗∗ — Blue Collar 2.471 1.963 (1.659) (1.369) (1.768) (1.314) 4.215∗∗∗ 3.729∗∗∗ 3.765∗∗∗ 3.753∗∗∗ — Union Executive (0.802) (0.666) (0.805) (0.682) −1.324∗ — Science (Economics) −0.833 −0.453 −0.253 (0.763) (0.708) (0.773) (0.720) — Science (Other) −0.223 0.693 −0.201 0.894 (0.758) (0.734) (0.838) (0.776) 2.541∗∗∗ 3.196∗∗∗ 3.091∗∗∗ 2.949∗∗∗ — Law (0.656) (0.597) (0.690) (0.617) 5.497∗∗∗ 5.216∗∗∗ 5.060∗∗∗ 5.457∗∗∗ — Military (1.667) (1.400) (1.426) (1.397) 3.487∗∗∗ 3.061∗∗∗ 3.295∗∗∗ 3.300∗∗∗ — Politician (0.708) (0.610) (0.701) (0.615) Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 15 / 18

  24. Section 3: Estimation Results Estimation Results: Primary Products, Education Dependent Variable: Tariff Rate, Primary Products Most Favored Nation, Most Favored Nation, Applied, Applied, simple weighted simple weighted −0.631∗∗∗ −0.415∗∗∗ −0.801∗∗∗ −0.475∗∗∗ GDP per capita (0.152) (0.148) (0.129) (0.147) (GDP per capita)2 0.012∗∗∗ 0.009∗∗∗ 0.015∗∗∗ 0.011∗∗∗ (0.004) (0.003) (0.003) (0.003) 0.157∗ 0.136∗ GDP growth ratet−1 0.032 0.060 (0.085) (0.118) (0.079) (0.118) −3.895∗∗∗ −4.194∗∗∗ Democracy −0.648 −1.321 (1.313) (1.615) (1.356) (1.606) Education −4.459∗∗∗ −10.162∗ −4.202∗∗∗ −9.798∗ — Economics (0.958) (5.825) (0.951) (5.826) −2.886∗∗∗ −2.745∗∗∗ — Politics −9.002 −8.574 (0.872) (5.548) (0.810) (5.546) −3.674∗∗∗ −9.016∗ −3.265∗∗∗ — Law −8.710 (0.900) (5.448) (0.897) (5.447) −3.383∗∗ −10.985∗ −3.571∗∗∗ −10.483∗ — Natural Science (1.317) (6.153) (1.077) (6.159) −5.578∗∗∗ −8.910∗ −5.008∗∗∗ −8.474∗ — Other University (1.161) (4.775) (1.229) (4.776) 24.222∗∗∗ 20.459∗∗∗ 24.644∗∗∗ 20.069∗∗∗ Constant (1.770) (3.431) (2.053) (3.427) Year effects Yes Yes Yes Yes Observations 698 698 698 698 Adjusted R-squared 0.241 0.029 0.298 0.030 Notes: Statistically significant at the ***1, **5, *10 percent level. Heteroskedasticity-robust standard errors are in parentheses. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 16 / 18

  25. Section 3: Estimation Results Estimation Results: Primary Products, Profession Dependent Variable: Tariff Rate, Primary Products Applied, Applied, Most Favored Nation, Most Favored Nation, simple weighted simple weighted −0.629∗∗∗ −0.420∗∗∗ −0.827∗∗∗ −0.479∗∗∗ GDP per capita (0.165) (0.130) (0.142) (0.129) (GDP per capita)2 0.012∗∗∗ 0.009∗∗∗ 0.016∗∗∗ 0.011∗∗∗ (0.004) (0.003) (0.003) (0.003) 0.184∗∗ 0.158∗∗ GDP growth ratet−1 0.030 0.059 (0.083) (0.128) (0.076) (0.128) −3.208∗∗ −2.601∗∗∗ −3.448∗∗∗ −3.053∗∗∗ Democracy (1.266) (0.931) (1.312) (0.928) Profession — Entrepreneur −0.120 −3.166 −0.401 −2.614 (1.446) (2.191) (1.268) (2.180) −3.584∗ −3.235∗ — White Collar −1.539 −1.670 (1.317) (1.894) (1.021) (1.815) — Blue Collar 1.936 2.425 0.777 0.283 (1.760) (3.035) (1.502) (2.790) — Union Executive 2.050 −2.016 3.011 −1.891 (1.534) (3.218) (1.965) (3.165) −1.872∗ — Science (Economics) −1.651 −2.524 −2.180 (1.225) (1.981) (0.993) (1.933) −1.910∗ −1.574∗ — Science (Other) −2.583 −2.116 (1.146) (1.952) (0.946) (1.914) −2.313∗∗ −3.170∗ −3.159∗∗ — Law −1.260 (1.119) (1.683) (0.893) (1.598) 4.986∗∗∗ 5.375∗∗∗ — Military 0.817 1.446 (1.772) (2.435) (1.785) (2.397) — Politician 1.489 0.560 1.517 1.002 (1.155) (3.237) (0.942) (3.200) Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 17 / 18

  26. Conclusion Conclusion Product Coverage Hypothesis Manufactured Primary All yes yes yes 1: university-level education leads to lower tariff rates 2: economics education associated with lower tariff rates than law education yes yes no 3: economics profession associated with lower tariff rates than law profession yes yes no Avenues for future research: What is special about primary products? Other outcome variables: bound rates, binding coverage, etc. Marek Hlavac (Harvard) Leader Background & Trade Liberalization June 8, 2012 18 / 18

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