Very preliminary Comparative Advantage and the Effects of Place-Based Policies: Evidence from China’s Export Processing Zones Zhao Chen #, Sandra Poncet.

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Presentation transcript:

very preliminary Comparative Advantage and the Effects of Place-Based Policies: Evidence from China’s Export Processing Zones Zhao Chen #, Sandra Poncet *, Ruixiang Xiong # # China Center of Economic Studies, Fudan University * Paris School of Economics (University of Paris 1) and CEPII

I. Introduction Industry policies, place-based policies and Economic Zones in China No conclusive conclusions about the effectiveness of place-based policies (Moretti, 2010, Busso et al., 2013) Difficulties in evaluation of industry policies (Krugman, 1983) –How to measure industry policy –How to identify the causality

I. Introduction In this paper –The effects of export-processing zones (EPZs) Clear policy purpose The role of comparative advantage –DID estimation using a quasi-experiment of EPZs in China

II. Brief literature review The effect of industry policies (Cai, Harrison and Lin, 2011) – Tariff policy has positive impact on TFP of industries with comparative advantage – Comments: Tariff policy & TFP Comparative advantage: exporting firms Policy of protection vs. policy of promotion

II. Brief literature review Policy evaluation of Economic Zones City-level data (Wei, 1995; Wang, 2013; Alder et al., 2013) Firm-level data (Head and Ries, 1996; Schminke and Van Biesebroeck, 2013) Comments: – policy at city-level, no within city difference – Few concern about the heterogeneous impact This paper: – Policy difference at city-industry level – Comparative advantage

III. Background of China’s EPZs Aim: promote exports by preferential policies Establishment : Establishment yearNumber of EPZs total57

III. Background of China’s EPZs Only some industries chosen as key industries could enjoy preferential policies Preferential policies  in EPZs ： free VAT, free trade for imported components; facilitate firm’s exporting  outside ： tax reimbursement when providing firms in EPZs with intermediate goods

IV. Data Data source –China annual survey of manufacturing firms from 1998 to 2007 Sample –To make the cities more comparable, we only include the cities having EPZs by

3. Data Data cleaning  Basic cleaning (Brandt et al., 2012, Nie et al., 2012)  Industry classification adjustment (Yang et al., 2013)  Administrative division adjustment (Bao et al., 2013)  Price deflator  Exporting firms ( )  Matching key industries

4. Empirical Results

4. Empirical Results How to define comparative advantage (CA): – Q ci = 1, if location entropy for industry i in city c > 1 before EPZ establishment, otherwise 0 Regression –Full sample –Subsample with CA –Subsample without CA –Triple-interaction term with Q ci

4.1 Basic model (1)(2)(3)(4)(5)(6) Full-sample Without CA With CA Full- sample Without CA With CA OLS FE T ** * *** (0.0326)(0.0344)(0.0360)(0.0191)(0.0291)(0.0217) K (0.0337)(0.0364)(0.0394) T*K ** ***0.104*** *** (0.0255)(0.0299)(0.0283)(0.0157)(0.0303)(0.0169) Constant-0.909***-1.388*** * (0.232)(0.143)(0.283)(0.243)(0.169)(0.313) Cluster-CityYES Obs338,21197,966240,245338,21197,966240,245 R-squared Number of panelid 75,19722,46452,

4.2 long-run effects Reference group: n = - 5 [-7, -6, -5] (n=-4) * K ci (n=-3) * K ci …… (n= 4) * K ci (n= 5) * K ci

4.2 long-run effects: full sample

4.2 long-run effects: sub-sample w/o CA

4.2 long-run effects: sub-sample with CA

5. Robustness checks

5.1 Using interaction terms （ FE ） T (0.0325) T*K (0.0319) T*Q * (0.0330) T*K*Q ** (0.0333) Constant (0.240) Cluster-cityYES Observations338,211 R-squared0.919 Number of panelid75,

5.2 Considering firm’s relocation (1)(2)(3) full-sampleWithout CAWith CA T ** ** (0.0194)(0.0282)(0.0225) T*K0.108*** *** (0.0159)(0.0287)(0.0172) Constant ** (0.217)(0.162)(0.276) Cluster-CityYES Observations277,61079,517198,093 R-squared Number of panelid56,09016,55539,535

5.3 Omitted governance abilities （ FE ） (1)(2)(3) Full-sampleWithout CAWith CA T (0.0347)(0.0441)(0.0378) T*K *** *** (0.0281)(0.0434)(0.0311) Constant (0.269)(0.147)(0.364) Cluster-CityYES Observations158,34045,687112,653 R-squared Number of panelid34,56910,23324,

5.4 Higher export intensity firms （ FE ） Prologis （ 2008 ） (1)(2)(3) Full-sampleWithout CAWith CA T ** ** (0.0256)(0.0354)(0.0266) T*K 0.110*** *** (0.0215)(0.0457)(0.0231) Constant ** (0.436)(0.225)(0.554) Cluster-CityYES Observations166,80947,361119,448 R-squared Number of panelid38,76611,51227,

6. Conclusions and implications Conclusions  Average effects Overall: 10.4% Industries with CA ： 12.3%; otherwise no effects  Long-run effects Industries with CA ： from 9.8% to 24.4% Otherwise no effects Policy implication ：  local initial conditions are important when making place-based policies

Thank You ！