Special Economic Zones 20 Years Later

Jensen, Camilla; Winiarczyk, Marcin

doi:10.2139/ssrn.2394547

Cited by 17 publications

(10 citation statements)

References 19 publications

(9 reference statements)

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“…For decades, countries like China [52] dominated industrialization because of the availability of cheaper and skilled labor [26]. Experts give symmetrical preferences to the level of skill of labor that was considered critical [28,34,36,37]. The Chinese model of development using labor-intensive and low tech is suitable for countries like Pakistan because of its ability to accommodate local manufacturing without hefty trade deficit or unbearable debts that are undesirable consequences of heavy industrialization [83].…”

Section: Discussionmentioning

confidence: 99%

“…For the main factor labor (LO) the Symmetry 2020, 12, 242 9 of 23 authors selected three sub-criteria, i.e. wage rate (LO1) in the particular region [30,31], unemployment rate (LO2) of surrounding localities [24,28,59], and their level of skill (LO3) [28,34,36,37]. Market orientation (MA) determines the objectivity of the SEZ.…”

Section: Factor Identification and Enrichment By Delphi Methodsmentioning

confidence: 99%

“…The successful SEZs share certain characteristics that make them successful. The first and most important factor is the location [27][28][29]. Its level of accessibility fosters the cost associated with the acquisition of location and its proximity to inputs and markets.…”

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confidence: 99%

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Sustainable and Special Economic Zone Selection under Fuzzy Environment: A Case of Pakistan

et al. 2020

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The establishment of Special Economic Zones (SEZs) is a lengthy, expensive, and long-term orientated endeavor. Proper selection of SEZs is indispensable to meet the objectives of export-led growth and value up-gradation. Consideration of sustainability issues in such planning under the Zone 3.0 paradigm is critical to achieve Sustainable Development Goals (SDGs) by 2030. Multiple key factors such as location, linkages, labor force, suitability of industries, incentives and facilitation, and market orientation are important in decision-making process of establishing SEZs. Furthermore, environmental conditions and resource availability need to be considered in the planning and policy making processes to keep symmetry in the natural environment and ecosystem of the areas under consideration for SEZs. The present study uses Multi-Criteria Decision Analysis (MCDA) methods in the perspectives of green industrial zone planning and development in Pakistan under the flagship project of China-Pakistan Economic Corridor (CPEC) of China’s Belt and Road Initiative (BRI). This research uses Delphi method, Analytical Hierarchy Process (AHP), and the Fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). The Delphi method has been used to identify the main criteria, sub-criteria, and their weights for 3 SEZs under consideration. The results of AHP analysis unfolded that the majority of the experts believe the location and land aspect is the most pivotal criteria in setting SEZs followed by linkages, subsidies, and facilities criteria. Finally, the results of Fuzzy VIKOR analysis considering environmental sustainability reveals that Faisalabad SEZ is the best suited under given criteria and sub-criteria.

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Section: Discussionmentioning

confidence: 99%

Section: Factor Identification and Enrichment By Delphi Methodsmentioning

confidence: 99%

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Sustainable and Special Economic Zone Selection under Fuzzy Environment: A Case of Pakistan

et al. 2020

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“…Research on location decisions finds that the quality of infrastructure and service and industry agglomeration are the main factor attracting foreign firms, while special economic zones have no effect (Cieślik, 2005). Jensen and Winiarczyk (2014), on the other hand, find a positive effect of special economic zones on business creation that comes mainly from FDI, while the effects on employment, investment and income generation are small or insignificant, suggesting that the policy has not been successful in creating a sustainable, positive dynamic, helping poorer regions to catch up. This finding is in contrast to Cizkowicz et al's (2015) work.…”

Section: Agglomerations With Strong Firm Network Training and Coachmentioning

confidence: 99%

Strengthening innovation in Poland

Brandt¹

2018

OECD Economics Department Working Papers

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JT03434115This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. 27 Unclassified English -Or. English 27 2 OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the author.Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works.Comments on Working Papers are welcomed, and may be sent to OECD Economics Department, 2 rue André Pascal, 75775 Paris Cedex 16, France, or by e-mail to eco.contact@oecd.org.All Economics Department Working Papers are available at www.oecd.org/eco/workingpapers. This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.On 3 May 2018, the OECD Council invited Lithuania to become a Member. At the time of publication the deposit of Lithuania's instrument of accession to the OECD Convention was pending and therefore Lithuania does not appear in the list of OECD Members and is not included in the OECD zone aggregates.On 25 May 2018, the OECD Council invited Colombia to become a Member. At the time of publication the deposit of Colombia's instrument of accession to the OECD Convention was pending and therefore Colombia does not appear in the list of OECD Members and is not included in the OECD zone aggregates. © OECD (2018)You can copy, download or print OECD content for your own use, and you can include excerpts from OECD publications, databases and multimedia products in your own documents, presentations, blogs, websites and teaching materials, provided that suitable acknowledgment of OECD as source and copyright owner is given. All requests for commercial use and translation rights should be submitted to rights@oecd.org 27 3 ABSTRACT/RÉSUMÉ Strengthening innovation in PolandPoland's catch up with other OECD country has been largely based on productivity growth resulting from restructuring towards more productive sectors and foreign technology absorption. The economy's own innovation capacity is relatively weak, with low investment in research and development, no tradition of commercialising research and very limited innovation activity within firms. The government plans a higher education reform to strengthen the quality of research output, science-industry cooperation and international collaboration, which are...

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“…Another study by Ambroziak (2015) suggests that there was no impact of the zones policy on the unemployment rate at the level of poviats. A study by Jensen and Winiarczyk (2014) using a simple difference-in-difference estimator showed that there was a small but positive effect of the zones policy on employment at the gmina (LAU2 -see footnote 1 further below) level. While the study by Cizkowicz et al is biased as a de facto policy evaluation in view to its emphasis on spillovers from only those zones that exhibit a positive development in terms of direct employment effects, the other available more traditional policy evaluation studies have in common that the policy variable lacks variability in the time dimension of its application.…”

Section: Previous Findings On Employment Effects Of Zones Type Policiesmentioning

confidence: 99%