County has long been the basic unit of national governance in China. Yet, only limited policy attention has been paid to counties. Recently, the central government proposed to carry out county-level urbanization to further deepen the people-centered new urbanization strategy. In this situation, counties need to provide enough jobs and decent income for rural emigrants. However, this is only the case for a small fraction of counties with prosperous local economies, and most of the rest counties need to enhance their industrial development to absorb the rural emigrants. Since China's industrialization process is largely influenced by the government, boundary adjustment, such as turning counties into urban districts, may also influence the local industrial development in various ways. Relying on the National Annual Survey of Industrial Firms Database (1998-2015), this paper constructs a county manufacturing industry dataset with 1110 counties and 376 four-digit level industries. With an Evolutionary Economic Geography approach, this paper explores the causal impacts of turning counties into districts on counties' manufacturing upgrading by employing difference in differences in differences method (DID). The empirical results show that, first, after turning counties into districts, counties have higher probabilities to enter more complex industries and exit less complex industries. And in both cases, the impacts of turning counties into districts has a time lag. Second, at the macro county level, turning counties into districts could benefit manufacturing upgrading through population agglomeration, economic development, infrastructure construction, and public service improvement; at the micro firm level, turning counties into districts could upgrade manufacturing industries by promoting output, intermediate inputs, profit, innovation, and tax reduction. Turning counties into districts has the largest impact on manufacturing upgrading in the eastern region and has negative impact in the central region. These findings could not only provide empirical support for the future implementation of turning counties into districts, but also enrich the institutional perspective of Evolutionary Economic Geography on regional industrial evolution.

The real-time interaction between human behavior and geographic context is becoming varied and dynamic. Understanding the interaction between human activity and environment has become a frontier in geographical research. Space-time prism provides a spatiotemporal integration method to understand the interaction, but its classical model is still a static model. In this study, we utilize the space-time prism model to investigate how individual decision-making relates to their potential activity space and real-time accessibility. We enhance the classical space-time prism model by introducing the concept of decision points, resulting in an improved conceptual model of real-time reachable space that accounts for both the real-time changes of environment and the dynamics of individual decisions. We apply time slices and isochronous circles to measure real-time reachable space quantitatively. Additionally, we propose a methodology for comparing real-time accessibility across different decision points to facilitate a detailed analysis of the real-time dynamics and accessibility of human behavior within geographic space. Furthermore, to expand the model's applicability under different real-world scenarios, we introduce a real-time reachable space model that considers specific path selection and time budget as input constraints. Dynamic measurement of an individual's real-time reachable space holds great potential for understanding how geographic space influences human behavior. By quantifying variations in real-time reachable space, we can gain valuable insights into the ways geographic factors shape individual behavior. These insights will greatly contribute to evaluating and optimizing facility and service resource allocation, thereby enhancing the fitness, support, and guidance of the geographic environment for individual behavior in the modern life.

The rapid expansion and accumulation of local government debt has become one of the critical and difficult issues affecting the sustainable development of regional economies and societies. Using economic and social attribute data such as county-level urban construction and investment bonds and public budget revenue and expenditure, this study employed methods such as spatial autocorrelation and Tobit model to investigate the spatio-temporal development characteristics and heterogeneous causes of public debt at the county level in China. The results show that: (1) From 2007 to 2020, the issuance amount of urban construction and investment bonds at the county level in China tended to expand, showing distinct characteristics of "policy debt" with obvious regional disparities and industry clusters. Throughout the study period, the distribution area of urban construction and investment bonds at the county level showed an expansion trend with clear spatial clustering characteristics, with hotspots and coldspots concentrated in the counties east of the Hu Huanyong Line. (2) Under the current local tax and levy system in China, grassroots financial operations in counties are facing challenges, among which fiscal pressure and development pressure are the key factors for the expansion of urban construction and investment bonds at the county level. (3) The proliferation mechanism of urban construction and investment bonds at the county level shows significant regional and sectoral differences. Fiscal pressure significantly encourages the proliferation of these bonds in underdeveloped districts, e.g. outside municipal jurisdictions and provincial capitals, development pressure particularly stimulates bond issuance in districts of the eastern region and districts within competitive urban clusters. Fiscal pressure has a negative impact on bond issuance in the real estate and infrastructure sectors, while development pressure favours bond issuance in the real estate and construction sectors. This study provides a new perspective for understanding the expansion of local government debt at the county level and serves as a reference for controlling the disorderly expansion of government debt at the county level and avoiding risks associated with local government debt.

The mutual empowerment and coordination of digital economy and green development is an inherent requirement for high-quality development. On the basis of deconstructing the coupling coordination mechanism of digital economy and green development, this paper analyzes the spatio-temporal characteristics of the coupling coordination between digital economy and green development in China, as well as the driving mechanism of spatial differences from 2010 to 2019 by using the vertical and horizontal scatter degree method, coupling coordination degree model, and quadratic assignment procedure (QAP). The results show that: (1) In terms of temporal evolution, the coordination degree of China's digital economy and green development has experienced a process of "reluctant coordination - primary coordination - intermediate coordination" during the investigation period, but high-quality coordinated development is far from being achieved, and most provinces are in the primary coordination stage characterized by the lagging digital economy. (2) In terms of spatial change, the spatial differences of coordination are obvious, showing an overall pattern of "multi-core" radiation, a "concave" interregional pattern of "eastern leading, central collapsing, and western catching up", as well as an evolution pattern of coordination levels of "highly coordinated transformation in eastern China, and imbalanced separation in central and western China". (3) In terms of spatial correlation, the regional coordination has gradually changed from "polarization effect" to "diffusion effect", and the spatial characteristics have changed from agglomeration to equilibrium. (4) In terms of spatial differences and decomposition, regional differences are the main source of overall differences in coordination degree. (5) Analysis of driving mechanism shows that narrowing regional differences in digital economy is the fundamental driving force to promote the coupling and coordination of digital economy and green development, while the narrowing of external differences such as economic development, industrial structure and technological innovation fails to play a positive role.