What urban public services do immigrant entrepreneurs with different educational backgrounds most value?

Descriptive statistics

Table 2 shows that the average educational level of urban immigrant entrepreneurs is 1.9039, indicating that immigrant entrepreneurs entering cities generally have a moderate level of education. The average number of low-educated immigrant entrepreneurs is 29.6703, the average number of medium-educated immigrant entrepreneurs is 121.7246, and the average number of highly educated immigrant entrepreneurs is 13.7899. This finding indicates that among the immigrant entrepreneurs flowing into cities, the number of moderately educated immigrant entrepreneurs is the highest, followed by low-educated immigrant entrepreneurs, with highly educated entrepreneurs being the lowest. The average value of urban higher education services is 0.5922 (the maximum value is 6.9715), of urban primary education services it is 1.8016 (the maximum value is 12.0458), of urban cultural services it is 34.4806 (the maximum value is 777.3), and of urban transportation services it is 5.6496 (the maximum value is 51.4538), indicating that the level of urban higher education and primary education services, cultural services, and transportation services in each city is relatively low. The maximum value of urban vocational education, communication services, and medical services is approximately seven times greater than average, indicating a significant difference in the average level of vocational education, communication, and medical services among cities.

Baseline regression analysis

To reveal the kinds of urban public services that attract urban immigrant entrepreneurs of different educational levels, this paper analyses their impact on attracting urban immigrant entrepreneurs from seven subdimensions of urban public services. Table 3 shows the regression results between urban public services and immigrant entrepreneurs of various educational levels.

Column (1) in Table 3 shows a significant correlation between the educational background of urban immigrant entrepreneurs and urban higher education, vocational education, primary education, cultural services, and medical services. Columns (2) to (7) show that a significant and positive correlation between the number of urban low-educated immigrant entrepreneurs and the level of urban higher education; a significant and positive correlation between the number of urban medium-educated immigrant entrepreneurs and the level of urban higher education, primary education, and medical services; and a significantly negative correlation with urban communication services and transportation services. There is a significant and positive correlation between the influx of urban highly educated immigrant entrepreneurs and the level of urban higher education, primary education, and cultural services, whereas there is a significantly negative correlation with urban communication services and transportation services. Moreover, there is a significantly positive correlation between the number of urban immigrant entrepreneurs low, medium and high levels of education with the wage level, economic development level, and industrial structure of the city. This indicates that urban public services and economic factors attract immigrant entrepreneurs of different educational backgrounds. Therefore, Hypothesis H1 is verified.

Group regression analysis

Due to regional differences, there are differences in government revenues and expenditures among cities, resulting in differences in the attractiveness of public services to entrepreneurial talent. To examine the attractiveness of urban public services to urban immigrant entrepreneurs in a more detailed manner, this paper further conducts group regression analysis based on regional differences and city classification. The aim is to identify the different attractiveness effects of urban public services on urban immigrant entrepreneurs with low, medium and high education levels and on urban immigrant entrepreneurs under different circumstances.

Grouping regression based on regional differences

Urban public services are provided mainly by the government. Due to differences in government transfer payments among different cities, the level of urban public services varies, leading to differences in their attractiveness to immigrant entrepreneurs. To reveal the attractiveness of public service levels in different regions and cities to immigrant entrepreneurs, this paper further conducts a grouped regression analysis by economic region where entrepreneurs flow.

Table 4 shows a significantly positive correlation between urban higher education and vocational education in the eastern region and between the number of urban low-educated and medium-educated immigrant entrepreneurs based on the grouping regression results of the economic regions where they migrate. Urban cultural services only have a significantly positive correlation with the number of highly educated immigrant entrepreneurs in urban areas. There is a significantly negative correlation between urban transportation services and the number of immigrant entrepreneurs educated in urban areas and highly educated immigrant entrepreneurs in urban areas. Second, urban moderately educated immigrant entrepreneurs flowing into the eastern region focus mainly on the high level of local intellectual capital and professional technology, as well as the impact of urban transportation services. Finally, the urban highly educated immigrant entrepreneurs flowing into the eastern region mainly value the cultural services of cities and their satisfaction, whereas the urban transportation services in this region have a significant inhibitory effect on attracting urban highly educated immigrant entrepreneurs.

There is no significant correlation between urban public services in the central region and the number of urban low-educated immigrant entrepreneurs; there is a significant and positive correlation between urban higher education and cultural services and the number of urban immigrant entrepreneurs with medium and high levels of education, whereas there is a significantly negative correlation between urban vocational education and the number of urban immigrant entrepreneurs with medium education. Second, immigrant entrepreneurs educated in the central region of China focus on the positive impact of urban higher education and cultural services on their entrepreneurship, as well as the inhibitory effect of urban vocational education on their entrepreneurship. Finally, the influx of highly educated immigrant entrepreneurs to cities in the central region focuses on the impact of knowledge spillovers caused by urban higher education and cultural services on entrepreneurship and the ability to cultivate an entrepreneurial spirit.

There is a significant and positive correlation between urban medical services in the western region and the number of urban immigrant entrepreneurs with low education levels, whereas there is a significantly negative correlation between urban communication services and the number of urban immigrant entrepreneurs with low education levels. There is a significant and positive correlation between urban higher education, primary education, and medical services and the number of urban immigrant entrepreneurs with medium education, whereas there is a significantly negative correlation between urban communication services and the number of medium-education urban immigrant entrepreneurs. There is a significant and positive correlation between urban higher education and the number of highly educated immigrant entrepreneurs from urban areas, whereas there is a significantly negative correlation between urban vocational education and the number of urban highly educated immigrant entrepreneurs.

In the northeast region, there is only a significantly positive correlation between urban cultural services and the number of urban immigrant entrepreneurs with low education levels. Urban higher education and cultural services have a significantly positive correlation with the number of urban medium-educated immigrant entrepreneurs. Urban higher education and medical services have a significantly positive correlation with the number of highly educated immigrant entrepreneurs in urban areas.

In summary, from the eastern to the central regions and then to the western region, the economic aggregate and per capita GDP of urban agglomerations decrease. The increasing concentration of population and industry in better cities has led to uneven urban development. For example, eastern coastal urban agglomerations, such as the Beijing‒Tianjin‒Hebei, the Yangtze River Delta and the Pearl River Delta urban agglomerations, are located in the central and western regions and have good resource endowments and economic foundations.

Grouping regression based on city classification

Larger cities have more convenient infrastructure and better living conditions (Desmet and Rossi-Hansberg 2013), which have a differential effect on attracting immigrant entrepreneurs with different educational backgrounds. Therefore, this paper further analyses the impact of urban public services on attracting urban immigrant entrepreneurs with different educational backgrounds based on urban classification.

The results of Table 5 show that the higher the level of higher education and health care in (new) first-tier cities, the more they attract highly educated immigrant entrepreneurs. The higher the level of education in second- and third-tier cities, the more they attract low-educated immigrant entrepreneurs, moderately educated immigrant entrepreneurs, and highly educated immigrant entrepreneurs. The higher the level of urban vocational education, the greater the outflow of immigrant entrepreneurs from various educational backgrounds. The higher the level of education in fourth- and fifth-tier cities, the more they attract low-educated, moderately educated, and highly educated immigrant entrepreneurs. Moreover, the higher the level of urban communication services, the greater the outflow of medium-educated and highly educated immigrant entrepreneurs. This indicates that highly educated immigrant entrepreneurs who flow into (new) first-tier cities, as well as immigrant entrepreneurs with different educational backgrounds who flow into second-, third-, fourth- and fifth-tier cities, all focus on the positive impact of urban higher education levels on their entrepreneurial enterprises, families, and individuals. Additionally, immigrant entrepreneurs with low, medium and high levels of education who flow into different levels of cities focus on differences in public service categories beyond urban higher education.

In summary, first-tier cities generally are international cities with extremely large scales and great international influence. Second-tier cities are generally regional-level cities with large scales and regional influence. Third-tier cities are generally provincial-level cities with a certain scale and regional influence, and local prefecture-level cities have a relatively large scale and some degree of influence. Therefore, the heterogeneity regression analysis based on city classification reveals that the public service level of first-, second-, third-, fourth-, and fifth-tier cities has both positive and negative effects on migrant entrepreneurs with different educational levels.