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Using the annual data of Chinese manufacturing firms over the period of 1998–2007, this paper applies the Cox proportional hazards model and analyzes the impact of inter‐provincial market segmentation on the exit hazard of firms in China. This study shows that market segmentation increases the risk of enterprises exiting the market in China. Moving from the 10th percentile of the distribution of market segmentation (score of 0.0995) to the 90th percentile (score of 0.7084) would increase the exit probability of firms by 7.5 percentage points. An analysis of the mechanisms involved shows that market segmentation benefits are often outweighed by lower productivity and less incentive to innovate. Our study also demonstrates that inter‐provincial market segmentation facilitates the likelihood that state‐owned enterprises (SOEs) will survive, but not for non‐SOEs in China. A one unit increase in the degree of regional market segmentation will reduce the probability that SOEs withdraw from the market by 19.5% while increasing the probability that non‐SOEs will leave the market by 5.80%. [ABSTRACT FROM AUTHOR]

With rising environmental regulations and trade disputes, Chinese industries are facing tremendous pressures to restructure and relocate, and pollution‐intensive industries (PIIs) are undergoing particularly significant location adjustment. Scholars have proposed various location theories and econometric models to explain the investment location dynamics of PIIs. However, there are still some deficiencies in the analysis of effective factors, such as macroeconomic changes, uneven development, and enterprise heterogeneity. This paper aims to explore the influencing factors of PIIs location choice from multiple dimensions by integrating multiple location factors and incorporating the variables of temporal, spatial, firm heterogeneity and their interaction items into an econometric model. Based on the capacity investment database for Chinese listed chemical companies, we find that: (a) the investment of chemical firms in the central and western regions has significant regional proximity, while the investment in the eastern region shows a significant north‐south difference. (b) The macroeconomic situation measured by the industry climate index has the greatest effect, magnifies the influence of environmental regulation (ER) and expands the differences of investment location preferences between non‐stated‐owned enterprises (non‐SOEs) and state‐owned enterprises (SOEs), due to SOEs' have undertaken more social responsibilities. (c) The agglomeration economy significantly increases the probability of investment in all regions, especially in the eastern region; non‐SOEs are more inclined to invest in the central and western regions than SOEs. We conclude that PIIs use a location strategy to adapt to the changing environment and that the effect of ER is mediated through ownership structure and local context. [ABSTRACT FROM AUTHOR]

This paper examines the changing spatial distribution of electronic information manufacturing (EIM) industry in China by focusing on the location choice of new firms. A three‐pronged "global‐regional‐local" nexus framework was proposed to identify the factors that influence firm location choice. Tobit regression analysis was performed to evaluate the impacts of these factors. The study reveals the spatial concentration of the EIM industry and a trend of westward diffusion. The regression analyses stratified by time period and by region demonstrate spatial and temporal variabilities in the influence of many factors, especially the regional advantage factors (e.g., labor cost, localization economies, and urbanization economies). Meanwhile, some factors, such as foreign direct investment, the presence of state‐owned enterprises, and local government policies, show stable effects over time and across regions. [ABSTRACT FROM AUTHOR]

Over the last two decades, China's outward foreign direct investment (OFDI) has expanded rapidly. The country is now the world's second‐largest source of OFDI. China is often viewed as a monolithic investor, however, without sufficient attention to the differences between investments by state‐owned enterprises (SOEs) and private enterprises (PEs). To shed light on the internal complexity and heterogeneity of Chinese OFDI, we construct a panel dataset of investments in the U.S. across the 50 states and Washington, D.C. from 2005 to 2017, which we analyze using a spatial autoregressive model. We find clear evidence that the ownership structure of Chinese firms affects investment strategy and entry mode. Statistical analysis indicates that SOEs are more likely to pursue greenfield investment motivated by market‐seeking and resource‐seeking objectives, while PEs pursue mergers and acquisitions in order to obtain strategic assets. We also detect a positive and significant relationship between the presence of Chinese overseas communities and OFDI, with the strength of the correlation depending on ownership structure. Finally, we find that Chinese OFDI is spatially dependent, meaning that investments flow to states where they are already concentrated nearby. [ABSTRACT FROM AUTHOR]

The rapid expansion of self-employment has accompanied the rise of a market economy in urban China. According to the National Bureau of Statistics of China, the state-owned enterprises' share of the country's gross domestic product has declined from over 90 percent in 1978 to below 50 percent in 2005. Urban entrepreneurship and self-employment is an emerging force that is shaping the economic and physical form of Chinese cities but is understudied in the academic literature. Using the 2007 Chinese Household Income Project ( CHIP) data, we investigate the rate and scale of urban entrepreneurship across Chinese cities, as well as the characteristics and earnings associated with self-employment as compared to wage employment. We pay particular attention to the financial capital, human capital, and social capital factors underlying entrepreneurial entry and distinguish between 'necessity entrepreneurs' and 'opportunity entrepreneurs' and their respective socioeconomic characteristics. [ABSTRACT FROM AUTHOR]