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The ripple effect of housing price movements between cities has been extensively investigated, but there are relatively few studies on this topic within a metropolitan context, especially at the submarket level. This paper describes the use of ripple effect theory to examine the diffusion process and convergence of intra-urban housing prices at the submarket level in Shanghai, an emerging global city in China. The analysis is based on directed acyclic graphs, local indicators of spatial association time-paths, and a recently developed convergence test. The empirical results of grouping analysis identify 25 submarkets in Shanghai, and the diffusion of housing prices between these submarkets is found to be caused by both geographical and economic proximities. There is also a complex recursive process of price spillovers from high- to low-priced submarkets, and vice versa, which contributes to the spiraling local housing prices. Housing prices diverge across all submarkets, and the whole market can be divided into three convergence clubs. Finally, these convergence clubs have a circular structure with a degree of continuity. This study broadens our knowledge of the price interrelationship among housing submarkets at the intra-urban level. These findings have profound implications for urban planners, policy makers, and local residents.

Transportation is an important factor affecting the balance of regional economic pattern. The construction of high-speed railway enhances the mobility of population, capital, technology and information resources between urban and rural areas. Will it further affect the income gap between urban and rural areas? Based on the nonlinear time-varying factor model, this paper analyzes the convergence of urban-rural income gap with the angle of high-speed railway. After rejecting the assumption of overall convergence in the traditional four economic regions, three convergence clubs of urban-rural income gap were found. For these ordered logit regression model is used to explore the initial factors that may affect the formation of &ldquo, convergence club&rdquo, Empirical results show that the construction of High-speed railway has effectively narrows the urban-rural income gap in China, but it is not the cause of the formation of the three convergence clubs. The convergence effect of High-speed railway on the urban-rural income gap in China is still relatively weak.

The cross-country convergence hypothesis is one of the central topics of long-run macroeconomics. This paper revisits this hypothesis in a context beyond GDP. It uses a novel welfare index that incorporates measures of consumption, leisure, life expectancy, and inequality. Based on a sample of 128 countries over the 1980&ndash, 2007 period, the lack of global sigma and beta convergence is first documented. Next, the paper incorporates some recent developments from the unsupervised machine learning literature to evaluate the existence of local convergence. In particular, the application of a distribution-based clustering algorithm suggests the formation of three local convergence clubs. Under this classification, beta convergence is recovered for each club. However, only the core members of the richest club appear to be reducing their welfare differences in a way that is consistent with the strong notion of sigma convergence. Overall, these results re-emphasize the finding that beta convergence is necessary, but not sufficient for sigma convergence, even within convergence clubs and in a context beyond GDP.

China is the largest carbon dioxide emitter in the world, and reducing China&rsquo, s transportation carbon emissions is of great significance for the world. Using the Chinese provincial data from 2005&ndash, 2015, this article analyzes the convergence characteristics of per capita transportation carbon emissions in China. It employs the log t regression test method and the club clustering algorithm developed by Phillips and Sul (2007) to separate the provinces and municipalities in China into three convergence clubs with different transportation carbon emission levels and one divergent group. Among them, the divergent group consisted of Beijing and Liaoning, the high carbon emission club consisted of Shanghai and Inner Mongolia, the low carbon emission club consisted of Jiangxi, Henan, Shandong, Hebei, and Sichuan, the medium carbon emission club consisted of the remaining 21 provinces and municipalities. On this basis, this article adopts the Ordered Logit model to explore factors influencing the formation of the convergence clubs. The regression results showed that the per capita transportation carbon emissions in the provinces with a high energy intensity of the transportation sector, a high urbanization level, or a high fixed assets investment intensity of the transportation sector tended to converge into the high carbon emission club.