Spatial Econometric Analysis of the Relationship between Urban Land and Regional Economic Development in the Beijing–Tianjin–Hebei Coordinated Development Region

Abstract

Against the background of coordinated development of the Beijing–Tianjin–Hebei region, it is of great significance to quantitatively reveal the contribution rate of the influencing factors of urban land for optimizing the layout of urban land across regions and innovating the inter-regional urban land supply linkage. However, the interaction effects and spatial effects decomposition have not been well investigated in the existing research studies on this topic. In this study, based on the cross-sectional data in 2015 and using the spatial lag model, spatial error model and spatial Durbin model, we analyzed the relationship between urban land and regional economic development at the county level in the Beijing–Tianjin–Hebei region. The results show that: (1) there are endogenous interaction effects of urban land, and the growth of urban land in a county will drive the corresponding growth of urban land in neighboring counties; (2) the local population, average wages, highway mileage density, and actual utilization of foreign capital have positive effects on the scale of urban land in local and neighboring counties; local GDP in the secondary/tertiary sector and the urbanization rate have positive effects on local urban land scale, but negative effects on the urban land scale of neighboring counties; (3) the contribution degree of the direct effect is ranked as follows: GDP in the secondary/tertiary sector > total population > urbanization rate. The order of factors with a significant spatial spillover effect on the scale of urban land in neighboring counties is as follows: average wages > total population > highway mileage density. The GDP in secondary/tertiary sector, population, and urbanization rate are the main influencing factors for the scale of urban land at the county level in the Beijing–Tianjin–Hebei region. It is an important finding that average wages are the most prominent among the spatial spillovers. We should attach importance to the spillover effect of geographic space and construct an urban spatial pattern coordinated with economic development.

University‐industry‐government triple helix relationship and regional innovation efficiency in China

“…The contribution of this paper lies in the following: first, in research theory and method, it integrates the triple helix theory and regional innovation theory into one research framework, explaining differences of regional innovation efficiency from the unique perspective of triple helix, which helps to expand the application scope of triple helix theory, and provide some preliminary empirical evidence for the influence of cooperation among innovation organizations on regional innovation efficiency. Second, different from previous studies which mostly focus on the evolution trend of university‐industry‐government relationship and the regional comparison (Kang et al., 2019; Shin et al., 2012; Tang et al., 2020), this paper further explores the impact of relationship among innovation entities on innovation efficiency. The results show that different cooperation forms and collaboration degrees have different effects on regional innovation efficiency, thus, showing which cooperation link is most conducive to improving innovation efficiency, and provide references for further research on regional collaborative innovation.…”

Spatial Evolution of Urban Expansion in the Beijing–Tianjin–Hebei Coordinated Development Region

“…The comprehensive index was used to classify the types of urban expansion in prefecture-level cities, and the spatial distribution difference of urban expansion types in each city was analyzed. (3) Although many scholars have used linear regression [41], ridge regression [42], a geographic detector [43], a spatial econometric model [44], and other methods to quantitatively study the influence of multiple factors on urban land, the existing research pays little attention to the temporal coevolution of urban land area with urban population and GDP. Using the power scaling law, Fei and Zhao [45] calculated the scaling coefficient of urban population and urban land area, as well as that of urban GDP and urban land area.…”

Coupling and Coordination Level of the Population, Land, Economy, Ecology and Society in the Process of Urbanization: Measurement and Spatial Differentiation

“…Since the reform and opening-up, China's urbanization rate increased from 17.90% in 1978 to 58.52% in 2017 (Table 1). According to the S curve of urbanization proposed by Northam, China is in a period of rapid development, with rates of 30-70% [1]. The reasons for the rapid urbanization are as follows: First, the reform and opening-up allowed China to enter the globalized market, and rapid economic development has directly accelerated the urbanization process.…”