This research explores the impact of China's high-speed railway (HSR) network on the income of urban residents, focusing on the spatial spillover effects. The introduction of HSR, alongside the increased speed of regular rail services, has dramatically altered China's transportation landscape and economic geography. The study is motivated by the widening income gap between Chinese cities, a consequence of uneven economic development and industrial structure. The spatial concentration of economic activity influences productivity and regional income; however, China's unique urbanization process, characterized by the migration of rural laborers to cities, complicates this relationship. The lifting of institutional barriers to labor mobility and the subsequent development of a unified national labor market further highlight the need to understand the role of transportation infrastructure in shaping income distribution. The study specifically aims to analyze how improvements in regional accessibility, facilitated by HSR, influence labor market income, both directly within a city and indirectly through spatial spillover effects on neighboring cities. The research is crucial for understanding how to leverage HSR to reduce regional income inequality and promote balanced economic development in China.

Existing economic theories often oversimplify the spatial aspects of factor flows, neglecting the impact of transportation costs. New Economic Geography, however, recognizes the significant role of transportation infrastructure in influencing economic development. The development of transport infrastructure can lead to both spatial agglomeration (siphon effect) and diffusion effects. Agglomeration occurs when developed areas attract resources from less developed areas, while diffusion represents a positive spillover effect where development spreads to less developed regions. The literature also highlights the role of transportation costs and labor flow in shaping regional economic development and income gaps. HSR's impact on economic distribution stems from its effect on spatial spillover, which is often overlooked in traditional econometric models that assume independence between regions. The study emphasizes the importance of considering spatial correlations, as transportation infrastructure acts as a social public good with externalities and network characteristics, influencing regional accessibility and labor market efficiency across interconnected regions.

The study employs a spatial econometric approach to analyze data from 286 Chinese prefecture-level cities between 2000 and 2018. A weighted average travel time method is used to calculate a regional accessibility coefficient, incorporating railway travel time, population size, and GDP. The analysis considers both spatial adjacency and inverse distance matrices to capture spatial correlations. Moran's I index is used to assess spatial autocorrelation of accessibility and income, both individually and bivariately. A spatial Durbin panel data model (SDM) is then employed to estimate the spatial spillover effects, controlling for variables such as economic structure, consumption scale, government size, human capital, and resources and environment. The SDM accounts for both direct and indirect effects of regional accessibility on income, allowing for the estimation of spatial lag and spatial error effects. Robustness tests are conducted using a double-weight matrix SDM model. Data sources include the China City Statistical Yearbook, Statistical Bulletin of National Economic and Social Development, and other relevant yearbooks. The study employs both spatial adjacency and spatial inverse distance matrices to construct the spatial weight matrices. Missing data are handled using linear interpolation to create a balanced panel dataset.

The study reveals several key findings. First, HSR development and increased regular rail speeds significantly improved urban regional accessibility from 2000 to 2018. Second, a strong positive spatial correlation exists between regional accessibility and labor market income, indicating spatial clustering of similar income levels. Moran's I index values consistently show significant positive spatial autocorrelation. Third, a siphon effect is observed, where cities with higher accessibility attract resources and income from neighboring areas, resulting in a negative impact on local income in these surrounding areas in the spatial Durbin model, this is reflected in the negative direct and total effects of regional accessibility improvements on local income in the baseline model. Fourth, the labor market income between cities is interdependent; income in a city is positively influenced by its neighboring cities and those with similar income levels. Finally, between 2012 and 2018, HSR construction and labor market transformation resulted in a significant positive spatial spillover effect on income. The analysis of the time trend shows that after 2011, there was a considerable increase in the positive spatial spillover effect. The double-weight matrix model reinforces these findings, highlighting the combined influence of spatial adjacency and distance on income spillover. The effects of accessibility on income are shown to be negative from 2000-2011, but significantly positive from 2012-2018, indicating a potential lag effect.

The findings demonstrate that HSR development significantly impacts urban residents' income, not just through direct effects within a city, but also through indirect spatial spillover effects on neighboring cities. The positive spatial correlation between accessibility and income reflects the agglomeration advantages of improved connectivity. However, the siphon effect highlights the potential for uneven development, where wealthier cities draw resources from less developed areas. The positive spatial spillover effect observed after 2012 suggests that HSR can contribute to more balanced regional development, particularly when combined with labor market reforms. The time trend analysis indicates that the positive impacts of HSR on income become more pronounced after the introduction of major HSR lines. These findings contribute to the ongoing debate about the spatial dynamics of economic development and the role of infrastructure in promoting regional convergence. The results underscore the importance of considering both direct and indirect effects of infrastructure investment on income distribution.

This research highlights the significant impact of HSR development on urban residents' income in China, demonstrating both direct and indirect spatial spillover effects. The findings emphasize the importance of strategic planning to harness the positive spillover effects of HSR while mitigating potential negative consequences, such as the siphon effect. Future research could explore the long-term impacts of HSR on income inequality, the role of specific policy interventions in shaping spatial spillover effects, and the impact of HSR on various income groups within cities.

The study is limited by the availability of data, focusing on prefecture-level cities and a specific time period. The model relies on certain assumptions about the spatial weight matrices and the inclusion of control variables. The linear interpolation for missing data may introduce some uncertainty into the results. Future research should address these issues by incorporating a wider range of data, exploring alternative spatial weight matrices and econometric models, and using more sophisticated methods for handling missing data.