However, a few zones, which are located in rural areas or areas with low population density for example some Tibetan cities, are left out. Moreover, as the number of urban agglomerations is much larger than the number of districts , the agglomerations that are not able to match with districts are left out when merging the two data sets. Figure 1. Creation of EDZs over time and according to their territorial status. The earliest development zones in the dataset were established in Shanghai in , and in Qinghuangdao, Suzhou, Nantong, Lianyungang, Yantai, Guangzhou, Zhanjiang, Qingdao and Tianjin in With the only exception of Kunshan Industrial Park located in Suzhou, all the other 9 zones established in and are located in the Coastal Open Cities 4 , a series of cities that were given similar status as the earlier 5 cities of Special Economic Zones and opened to oversee investment in There was a rapid increase of decadal amount of newly-established development zones from to , respectively 18, 89, and 37 zones were established in , and However, this rapidly increased fever proved to be only short-lived, because the decadal number of newly-established development zones dropped again to no more than 10 from to However, very few researches have thoroughly investigated the distribution between regions.
Thanks to their inclusion in GIS, the EDZ were georeferenced at the barycenter of the districts and urban agglomeration where they were located, and a first map of their spatial distribution was drawn as seen in figure 2 , according to the date of creation.
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Here we can test the hypothesis that after concentrating at first in the eastern part of China the EDZs development gradually diffused to the central and western regions, following the state policy. On figure 2 the EDZs are categorized into 6 groups according to their establishment year: , , , , , The map shows that earliest zones are largely located in the Open Coastal Cities and major provincial capitals, both in eastern regions and other parts of China; however, the total number of the zones is limited.
However, the newest zones, especially the ones that are established after are much more widely dispersed across the whole country. Figure 2. Districts including at least one EDZ according to establishment year. Table 2. Average longitude of EDZs according to establishment year.
Chongqing, one of the most important city in the western region, has established 38 development zones. Among the 27 zones in Chongqing that are recorded in our dataset, 24 zones were established after Using the ChinaCities database, some analyses that link to our result can also be performed. For the table 2 giving average longitude, the result would be more robust if adding a null model giving for example the location of synthetic EDZs if they depend on population only under a controlled form.
In the simplest setting, if the probability of adding a new EDZ in a given city is proportional to a power law of its population , then in the large number of EDZs limit, we should have a proportion of EDZs in the corresponding city and thus an expected longitude given by. In the exponents corresponding to the activities considered, we naturally observe also a shift to the West, but far lower than the one observed for EDZs in the paper, justifying the claim of an actual shift to the West, independently of population.
Further work is possible, as a more robust null model should also take into account the actual number of EDZs in time, and simulate drawings using these. These results reinforce the feeling of trust about results of the paper 5. Table 3. Values of average longitude for synthetic systems of EDZs. The average number of EDZ per city is regularly growing with urban size class and there is a noticeable gap isolating urban agglomerations above 10 million inhabitants as ten times more attractive locations than the other million plus cities.
Table 4. Repartition of EDZ according to size of urban agglomerations. However, some western and central regions, although not as dense, show evident clustering effect as well, and the total numbers of EDZs located in these areas are also considerable. These regions include Cheng-Yu Metropolitan Area around western cities Chengdu and Chongqing , Middle Yangtze metropolitan area around central cities Wuhan and Changsha , and Central plain metropolitan area around Taiyuan and Zhengzhou.
Some more discrete clusters appear in the western regions of Yunnan, Xinjiang, Shaanxi, Gansu-Qinghai, and coastal region of Shandong, and North-Eastern region. The result might be affected by the small number of zones created in some years.
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For example, the 34 zones that were established between and are largely located in Beijing, Tianjin, and Shanghai. The fact that the three largest cities established a number of zones at the same time might bias the result. However, when counting only the years during which large number of zones were established, a declining trend of the size of urban agglomerations where EDZs are located can be observed.
This result both tends to validate the geographical theory of hierarchical diffusion of that innovation and confirms the deliberate policies intending to favor the economic development of medium size cities in China. Table 5. Average population size of urban agglomerations according to year of establishment. However, as accompanied by the policy of unique child, the demographic transition has been very rapid and despite the growing urbanization rate, the growth of urban populations has become rather low.
The figure of Chinese annual growth rate in is significantly lower than that of India 1. Figure 3. Our data are covering a large part of China, but they are too coarse grained to enable a detailed analysis of the direction of causality. For the sake of simplicity, we computed urban growth rates at district and agglomeration levels, between and and compared them with the location of EDZs, whatever their date of creation.
Whereas the average growth rate of the population in all districts is 0. The variation of growth rates, that is usually high, is also reduced among the districts that were equipped with EDZs.
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Moreover, the increase of urban population is growing with the number of EDZs created locally: according to a simple regression, one additional economic zone increases the annual population growth rate by 1. Table 7 Parameters for growth rates categorised by decision level of EDZs. Merging the district file with the Chinacities data base provide information about whether EDZ location had or not a significant impact on the expansion of these urban areas.
Indeed, the urban agglomerations are the relevant geographical entities for exploring a number of questions concerning the rationale of EDZ in the economic development and urbanization processes when thinking of the Chinese territory at national scale. Table 8. This could be interpreted either as a direct impact of investment on urban growth, or as a selection effect, if zones where investment occurred were already more dynamic.
The variation of the growth rate is largely increasing with the number of the zones in each type. Table 9. Figure 4.
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We assume that EDZ s with higher status should have bigger positive impact on population growth of the urban agglomeration where it locates. To simplify the model, we consider only the administrative level when the zone started operating, which corresponds to the decision level for creating the zone.
Interestingly, contrary to our assumption, the municipal-level zones correspond to the highest growth rate of 5. And the agglomerations where provincial-level zones are located correspond to the lowest growth rate 2. An ANOVA test confirms that different administrative levels have evidently different effects on the urban growth, although it is not an effect that would strictly increase with the administrative level. Table It is likely that more economic zones will bring more economic growth and more employment opportunities, which lead to more migration and population growth.
It shows that one additional economic zone increases the annual population growth rate by 0. Figure 5.
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Regression analysis of urban agglomeration growth rate on number of zones. In other words, the earlier one urban agglomeration started to establish economic zones, the more it is likely to benefit from the economic activities in the economic zones, which can be translated into higher annual population growth rate. As our data of annual growth rate is calculated from and census, the zones established after might not be accurately represented, therefore in this part only the zones established before are considered in the model. Figure 6 shows a graphic presentation of the correlation between the two variables.
It is evident that the establishment year of the first zone is negatively correlated to the annual population growth rate. The regression analysis shows that to delay one year of the establishment of first economic zone, decreases 0. Therefore, if one urban agglomeration starts the establishment 10 years later, the growth rate drops by 0. And the p value of the model is between 0. Therefore, it can still be concluded that the correlation coefficient is significant.
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Figure 6. Regression analysis of growth rate on the establishment year of the first zone in each agglomeration. Another assumption frequently made about the effect of diversity of urban activities on urban growth also revealed insignificant at district level. The slight added value of our paper is in offering, for the first time to our knowledge, a geographically disaggregated analysis of EDZs location and differential impact on urban growth.