Tempo de leitura: 5 minutos
Special Economic Zones (SEZs) have become an increasingly popular instrument to promote economic development. Over the last two decades, in particular, SEZs have proliferated in emerging and transition economies. States promoting zones have sought to stimulate economic development both within and outside the zone. Within the zone, states aim to attract investment that will lead to new firms and jobs, and to facilitate skills and technology transfers. Outside the zone, states aim to generate synergies, networks, and knowledge spillovers to foster additional economic activity.
However, whether SEZs have achieved their objectives is unclear. Most existing studies of SEZs have taken a case study approach, focusing on a limited group of zones in a select number of countries. Many of these investigations provide interesting insight into what makes a zone dynamic and successful. However, the majority of research has focused on the most successful cases. The tendency to focus on “success-only” analyses raises questions about the validity of generalizing the factors behind the success of a specific SEZ, which is embedded in specific economic, social, political, and legal contexts. Replicating policy and incentive models involves significant risk.
The aim of this report is to analyze both the factors driving SEZ performance in emerging market economies, and the extent to which SEZ performance drives economic growth in surrounding areas. Lack of comparable cross-country data on the performance of SEZs has been a fundamental barrier to this type of study. To conduct broader empirical analysis, this study relied on the increasingly widespread use of nightlights data in economics to overcome the lack of reliable information on the performance of individual SEZs.
Comparable information also is missing about the characteristics of the zones and about the zone-specific and regional and/or national policy programs from which zones originate. The authors created a bespoke dataset from scratch. It encompasses: i) SEZ program factors including the incentives packages, requirements, and program characteristics that underlie setting up and operating a zone; ii) SEZ-specific factors including the size of the zone, the type of operator of the zone, years in opera- tion, and distance to major cities and infrastructure; and iii) indicators about the zones’ regional and national contexts including proximity to large markets, GDP per capita, years of schooling,
This report also reviews World Bank-financed SEZ projects to assess how they have performed, drawing on World Bank project documentation current at the time of each project. The review assesses the development objectives of individual projects; the extent to which these objectives were achieved; the challenges faced; and the lessons learned that could inform the scope and design of subsequent projects.
Typically, the success of a zone and its impact depend on factors both within and outside the zone: (1) the SEZ program and its characteristics; (2) the structure and layout of the zone; and (3) regional and country contexts.
Within the zone, the SEZ program and its characteristics generally include a combination of fiscal and non fiscal incentive packages, a number of investment and ownership requirements, and a series of factors linked to the organizational set-up of the zone. These last factors include the degree of independence of the regulator and the date of the establishment of the zone.
Similarly, the characteristics relating to the structure and layout of the zone are key drivers of the zone’s performance. Characteristics include maturity, size, type of operator, specific location, industry focus, infrastructure endowment, and specific services offered.
The regional and country contexts in which a zone operates are crucial for its economic dynamism. The skills, infrastructure, institutions, and external and agglomeration economies at the zone’s disposal can help shape its performance.
Data on all these factors have been sourced from the newly gathered Competitive Industries and Innovation Program (CIIP) dataset on Special Economic Zones, which totals 553 zones in countries and South Korea.
To conduct broader empirical analysis regarding zone performance, this study relied on the increasingly widespread use of nightlights data in economics to overcome the lack of reliable information on the performance of individual SEZs. This approach requires its SEZ sample to comply with five criteria: (1) a differentiating regulatory framework and/or incentive scheme applicable to firms within the zone; (2) focus on manufacturing or services; (3) presence of clear territorial boundaries; (4) minimum size of 50 ha and a maximum size of 1000 ha to ensure an optimal fit of the nightlights proxy as an SEZ performance indicator and to increase the comparability of the zone; and (5) operational by 2007 to enable a minimum of 5 years of activity. The resulting sample includes 346 zones in 22 countries.
The main analytical period is 2007 to 2012, for which all variables are available. To nuance these findings, two complementary sets of results are presented. First, regressions were run on the same cross-country dataset to look at the growth performance of each SEZ in the 5 years after the zone had become operational (but not 2007–12). e aim of this exercise is to uncover the factors that facilitated the success of SEZs during their initial years of operation, regardless of when they were founded. Second, the results of a “deep dive” into the performance of the Vietnamese zones are presented.
As SEZ performance proxies, two variations of the nightlights indicator are used: (1) the growth rate of the nightlights emitted from the SEZ during the analytical period, and (2) the ratio of the change of the nightlights emissions within the zone compared to the change in nightlights in the entire country. The first indicator, the growth of nightlights in the zone, indicates absolute growth. The second indicator is a relative performance measure and captures whether a zone has grown faster than the national average. The second indicator teases out differences in national growth across countries. As a consequence of the overall dynamism of these countries, less dynamic zones in rapidly growing countries often have higher rates of growth than very dynamic zones in low-growth countries.
Finally, to assess whether and to what extent SEZs contribute to growth in surrounding areas, the impact of SEZ performance on the surrounding regions up to 50 kilometers (km) from the zone is analyzed.