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This study offers additional evidence on the self-employment of rural-to-urban migrants from the perspective of cultural barriers in China. By employing seven waves of the China Migrants Dynamic Survey data from 2010 to 2016, we find that cultural distance has a negative and significant effect on the self-employment of rural-to-urban migrants in eight subdivision industries. In particular, such negative effect is greater in the service sectors. [ABSTRACT FROM AUTHOR]

It is widely recognized that the tourism industry is susceptible to crisis or natural disaster. Although some literature has studied the consequences of the crisis and disaster, there remains a lack of study on the effect of COVID‐19. Against this background, this paper investigates the tourist flow forecasting by adopting an advanced nonparametric mixed‐frequency vector autoregressions model using Bayesian additive regression trees. This is particularly suitable for forecasting the presence of extreme observations, for example, the COVID‐19 pandemic. We investigate tourism demand forecasting using a large number of predictors, including industrial production index, CPI, exchange rate, economic policy uncertainty, Google trends index, and COVID‐19 infection rate. The data used for this study relate to tourist flows in Chinese Hong Kong, Japan, and South Korea. Empirical study demonstrates that this novel model significantly outperforms the traditional mixed‐frequency vector autoregressions model to quarterly tourist flow forecasting. Therefore, this model can significantly enhance tourism forecast accuracy in the face of extreme events. This study contributes to the literature on tourism forecasting and provides policymakers with policy implications. [ABSTRACT FROM AUTHOR]

The digital economy has a significant influence on the financial behavior of enterprises. According to the panel data of A-share listed enterprises in the manufacturing industry from 2010 to 2020, we discuss how manufacturing enterprises allocate their financial assets in the process of digitalization from the perspective of operating profit and risk taking. The results reveal that ICT investment significantly reduces financial asset allocation, while digital transformation improves the financial asset allocation of manufacturing enterprises. Because ICT investment increases operating profit from the main business, manufacturing enterprises reduce the allocation of short-term and long-term financial assets. We thus propose two phenomena: precautionary saving and substitutional investment. As digital transformation increases risk taking, financial assets are elevated by manufacturing enterprises for the precautionary saving motivation, boosting the short-term financial assets in their portfolios. These findings are further supported by the heterogeneity of innovation characteristics and ownership. [ABSTRACT FROM AUTHOR]

The digital transformation of global economic and social activities brought about by advanced information and communication technology (ICT) may have a profound impact on sustainable economic development. This research measures the digitalization of the economy and society in cities of China based on Internet-related indicators and digital financial development and investigates the economic and environmental effects of their digitalization. The empirical results show that digitalization has significantly improved green economic efficiency (GEE), and this finding remains valid after a series of robust analyses. However, there is regional heterogeneity in the improvement effect of GEE. The green effect of digitalization is significant only in the cities with a high degree of economic servitization, capital-abundant cities, and eastern cities. Although digitalization has promoted the green development of the urban economy, it also has a negative spatial spillover effect on the GEE of neighboring cities. One explanation is that cities are shifting polluting industries to other areas during the process of digital transformation. [ABSTRACT FROM AUTHOR]

Environmental degradation is a major challenge facing the world. Our view is that a country's productive structure, reflected through its knowledge content and technical capabilities (economic complexity), is strongly correlated with its environmental performance. To empirically confirm this view, the link between economic complexity and environmental performance in member countries of the Organization for Economic Co‐operation and Development (OECD) was examined within a modified version of the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model incorporating two alternative measures of economic complexity. The model was estimated using the fixed effects extension proposed by Driscoll and Kraay (DK‐FE) and Generalized Method of Moments (GMM) estimation techniques. Granger causality testing in frequency domain was also employed to examine country‐specific relationships. The sample period extended from 2007 to 2016. The study findings provided reliable empirical justification for our position. The coefficients for economic complexity in the long‐run estimations revealed that economic complexity positively impacted on environmental performance in the OECD countries. Granger causality outcomes also indicated economic complexity as a meaningful predictor of environmental performance in most of the OECD countries. [ABSTRACT FROM AUTHOR]

This study investigates the impact of the COVID-19 pandemic on economic uncertainty and its spillover network based on social network analysis. The study constructs the inter-provincial Chinese economic uncertainty spillover network using a mixed frequency dataset and the provincial social network using microblog user data. Furthermore, the temporal exponential random graph model is used to analyze the impact of COVID-19 and social network during three periods. The results show that the COVID-19 pandemic significantly affects China's provincial economic uncertainty and social network significantly hinders economic uncertainty spillover networks. The inhibitory effect of social networks on uncertainty spillover network has regional heterogeneity, which is more significant in provinces severely affected by the pandemic and strictly controlled. [ABSTRACT FROM AUTHOR]