Growth and Change最新文献

This study examines how institutional varieties at the subnational (state) level influence firm-level innovation in an emerging economy—India. Knowledge of how institutional varieties influence firm-level innovation is derived principally from country-level studies involving multiple developed countries. Research on emerging economies is sparse and tends to follow country-level approaches involving multiple countries. Research involving a single emerging economy where there are substantial institutional varieties between regions is thin. The institutional varieties of some emerging countries are so striking that they can be viewed as several countries within a country, for example, India, China. This study contributes to the innovation literature on the role of institutional varieties on firm-level innovation by focusing on a different level of analysis—a single, emerging economy with substantial institutional varieties across the different states of India. Innovation in emerging economies is a topic of increasing academic interest. A multilevel study involving regional- and firm-level factors is employed. Firm-level data are from the World Bank Enterprise Survey and regional-level data are from statistical agencies in India. The results confirm that institutional varieties have major impacts on firm-level innovation. The research, policy, and managerial implications are discussed.

A substantial amount of research has examined the collaborations within technology-based industries, but how technological intensity relates to the evolution of interregional research collaboration is less well understood. This paper investigates the dynamic changes of spatial structure and determinants of intercity research collaborations in the sectoral innovation networks of high-tech industries contrasting to low and medium technology (LMT) industries in the Greater Pearl River Delta (GPRD), China. Using the sectoral patent application data over the period 2008–2016, the social network analysis results confirm a higher level of triangles in the co-invention network of high-tech industries than within LMT industries. Moreover, the empirical results through Exponential Random Graph Model (ERGM) show that, compared to LMT industries, collaboration in the co-invention network of high-tech industries is less sensitive to geographical and linguistic distance, while more subject to economic distance, regional educational level and government support with time. In addition, cognitive proximity and regional R&D intensity are both important prerequisite in the formation of these two collaborative networks.

The Minimal Living Standard Allowance System (MLSAS), established by the Chinese central government in the late 1990s, was intended to provide basic needs for urban and rural low-income populations. Although the subsidy standards of MLSAS have increased rapidly over the years, its distributions in time and space were found imbalanced. Using the per capita subsidy income (PCSI) data of 338 Chinese cities from 2008 to 2016, this study quantified the spatiotemporal patterns of the urban-rural gap and regional differences of MLSAS throughout China and identified the major influential socioeconomic factors of the observed patterns. The results showed that the PCSI of China's low-income populations increased rapidly but with large variations between urban and rural residents and between geographic regions. The PCSI in rural areas was much lower than that in urban areas, whereas the Gini coefficient of PCSI in urban areas was lower than that in rural areas, indicating the allowance from MLSAS was more unequal among rural residents. Additionally, the higher PCSI was concentrated mainly in three urban agglomerations in eastern China. Most cities in central and western China lagged in terms of PCSI. Correlation analysis between PCSI and socioeconomic factors indicated that the income and GDP per capita were the most important influencing factors. With a better understanding of the overall situation of the urban-rural gap and regional differences in implementing MLSAS, the current study should help improve the subsistence subsidy policies in China.

Using micro merged data of China's customs transaction and National Bureau of Statistics Annual Surveys of Industrial Firms data, this paper analyzes the effect of industrial agglomeration on domestic value-added in exports to gross exports (DVAR). It is found that industrial agglomeration significantly improves DVAR. Mechanism tests show that industrial agglomeration promotes DVAR by increasing the relative price of imported intermediate inputs and domestic inputs (relative price effect), as well as restrains DVAR by restraining cost markup of firm (cost markup effect). However, the promotion effect of the “relative price effect” is greater than the restraint effect of the “cost markup effect”. In addition, accession to the World Trade Organization and exchange reform strengthen the promotion effect of industrial agglomeration. The result of dynamic decomposition shows that 74.62% of the industry's DVAR increase is attributed to the resource re-allocation effect, which is an important channel for industrial agglomeration to promote DVAR.

International trade in environmental goods (EG) provides a market-based solution to balance the development–environment relationship. How can developing economies gain new growth opportunities through trade liberalisation in the EGs? This study investigates the structural features of products and firms during the early development of China's EG trade. This study defines the import–export nexus as the product relatedness between imports and exports at the firm level, which may promote the technology spill overs and firm cooperation. This study combines two nationwide data sets and constructs a data panel covering 334 prefectures and 248 EGs during 2001–2012. The conditional logit model with fixed effects is used for coefficient estimation. Empirical results reveal that the import–export nexus promotes new EGs in domestic sectors and export baskets, primarily supported by domestic private firms. The import–export nexus allows state-owned firms, which only represent a small market share, to enrich export baskets. It also helps foreign firms to develop new EGs in domestic sectors. These findings suggest revisiting the role of state-owned firms in industrial policy and developing a broad list of EGs to make use of the product relatedness. These will make developing economies like China gain new growth opportunities from the EG trade.

An extensive economic growth mode leads to resource depletion and environmental degradation. Green development is the best way to solve this problem. We analyzed the sample data of 41 cities in the Yangtze River Delta of China from 2007 to 2019. We used the spatial Durbin model and interaction term model to study the effects of regional financial agglomeration (FA) on green development and the moderating role of green technology innovation. The results show that FA promotes local green development but inhibits the green development of neighboring areas. Because the polarization effect of the growth pole is greater than its dispersion effect, cities with high levels of FA have a strong “siphon effect” on the surrounding areas. Green technology innovation positively moderates the promoting effect of FA on green development; the higher the level of green technology innovation and the degree of emphasis on it, the stronger the promoting effect. The government should encourage green finance to promote green technology innovation and promote the green development of the regional economy. These findings provide new insights for developing countries to achieve sustainable development under environmental constraints.

Under the system of political centralization and economic decentralization, the expanding scale of land finance and the increasingly severe environmental pressure have jointly become crucial features of China's urban development. Therefore, it is of great practical significance to study the intrinsic mechanism of land finance on haze pollution for China's economy to achieve kinetic energy transformation and green development. This paper empirically analyzes the impact of land finance on haze pollution using a dynamic spatial Durbin model based on panel data of 269 prefecture-level cities in China from 2004 to 2017. The statistical results show that haze pollution has a significant “snowball effect” and space spillover effect. Land finance has a significant positive effect on haze pollution. Land transfer both by agreement and by bid invitation, auction, and listing have significant positive effect on haze pollution. However, the promoting effect of land transfer by agreement on haze pollution is significantly higher than that of land sale by bid invitation, auction, and listing. Furthermore, regional heterogeneity implies that for cities in the eastern region, land finance is conducive to alleviating haze pollution. In contrast, for cities in the central and western regions, land finance significantly promotes haze pollution.

Research at the biophysical level constitutes the main approach to study the path through which climate influences infectious diseases, but the influence of socioeconomic factors on climate change and the spread of infectious diseases also cannot be ignored. In the current context, with its emphasis on carbon emission reduction, countries have begun to adopt “total control and trading” methods to reduce greenhouse gas emissions. This paper is based on the monthly relevant data of various provinces and cities from 2015 to 2019, adds the moderating variable of “carbon emission trading volume” based on current research results, establishes a static model of unbalanced panel fixed effects and a dynamic panel model, and deeply analyzes the impact of climate change on infectious disease popularity and the moderating effect of the carbon trading market. The study found that climate warming, frequent precipitation, and shortened sunshine duration will lead to an increase in the number of infectious disease cases and that the “carbon emission trading volume” variable plays a negative role in the positive correlation between climate change (temperature/precipitation) and the number of infectious disease cases. There are seasonal differences, and the moderating effect in summer/autumn is more obvious than that in winter/spring.

The advancing global urbanization puts great pressure on the society and ecosystem, especially in developing countries. Reasonable land-use policies adapted to local conditions are the key issues to prevent disordered urban expansion. Multi-scenario simulation provides a new perspective for differentiated policy formulation based on regional heterogeneity. Regarding the Shaanxi Province, a rapid urbanized area with high spatial heterogeneity in western China, as the study case, we tracked its past land-use changes and predicted the characteristics of urban expansion using the Future Urban-Regional Environment Simulation model. We found that (1) during the past 35 years, built-up land evidently increased accompanied by the loss of cropland, grassland, and unused land. (2) The urban expansion mainly will occur in the areas with flat terrain under three scenarios. (3) The urban expansion will transit into the “requiring land from mountains” pattern in the future, which means that it will gradually spread to areas with higher slopes. (4) Differentiated and optimal development patterns are proposed for different subregions by accounting the loss of ecosystem service in the procedure of urban expansion. This research can help local governments formulate differentiated future macro control of territorial spatial planning to optimize subregional land development.

Existing studies on the global expansion of banks have been mostly based on the experience of the banks from more developed economies, while little is known about the geographies of internationalization of banks from less developed countries. The expansion of Chinese banks, with state-owned commercial banks in the lead, has been accelerating since the Belt and Road Initiative (BRI) was proposed in 2013. This study contributes to existing research by providing new evidence and explanations based on the case of expansion of Chinese banks along the BRI routes. Chinese banks started to expand from Hong Kong and Macao, then expanded to Southeast Asia and the Arabian Peninsula, and finally reached Central Asia and other regions. The branches of Chinese banks are mainly clustered in Southeast Asian countries rather than other regions. Similar to their Western counterparts, Chinese bank branches are inclined to agglomerate in international or regional financial hubs. The regression analysis shows that two factors are crucial in explaining the spatial distribution of Chinese banks along the routes of the BRI. First, Chinese banks are likely to follow their customers, namely, state-owned firms from the non-financial sectors making direct investments in overseas regions. Second, Chinese banks are more inclined to open branches in countries that have good geopolitical relations with China reflecting the challenging international environment for Chinese banks to seek global expansion.