Revisiting the Relationship Between Tourism and Crime Based on a Dynamic Spatial Durbin Model

To determine the extent to which tourism development affects crime rate, this study uses a dynamic spatial Durbin model (DSDM) to examine the spatial effect of tourism on crime. Based on a panel data set of 21 cities in Sichuan Province, China, over the 2008 to 2018 period, and after controlling for the interactive effect, the results reveal that tourism exerts a significantly negative impact on crime. This implies that tourism development can reduce crime. Moreover, tourism has a negative spatial spillover effect; thus, increased tourist arrivals decrease crime in neighboring cities. Per capita GDP, wages, unemployment, population density, hotels, scenic spots, and travel agents generate various direct and spillover effects. Finally, we provide policy suggestions.

Research on the Impacts of Heterogeneous Environmental Regulations on Green Productivity in China: The Moderating Roles of Technical Change and Efficiency Change

Due to the publicly owned resource attributes of the ecological environment, the treatment and governance of the environment should be guided by governments, which are mainly represented as environmental regulations. However, whether environmental regulations affect green productivity and what effects heterogeneous environmental regulations have on green productivity are still implicit. In addition, the moderating roles of technical change and efficiency change are ignored. To examine these issues, this study investigated the impacts of heterogeneous environmental regulations on green productivity and the moderating roles of technical change and efficiency change using the dynamic spatial Durbin model based on the panel data of 30 Chinese provinces from 2000 to 2018. The results show the following: compared with efficiency change, technical change has a stronger promotion effect on green productivity in China; considering the spatial spillover effects and the temporal lag effects of green productivity simultaneously, the negative path-dependent feature is not supported any longer, while the spatial spillover effect is still the power source for promoting green productivity in China; the moderating roles of technical change and efficiency change for the nexus between heterogeneous environmental regulations and green productivity in China are partly and conditionally supported at national and regional levels; the direct and indirect effects of heterogeneous environmental regulations on green productivity at the regional level have a feature of spatial heterogeneity. This study provides both theoretical and practical implications, in particular for China, to promote green productivity from the dual perspectives of space and time.

Effects of Forestry on Carbon Emissions in China: Evidence From a Dynamic Spatial Durbin Model

Research has proved the significance of forests in controlling carbon emissions, however, our research sheds light on the management of existing forests to combat climate change. To examine the role of forestation and forest investment activities, dynamic spatial techniques are used for 30 provinces of China. The results suggest that forest investment and management not only reduce carbon locally but also in neighboring provinces. Furthermore, the findings of the current study confirmed that forest investment is the most viable practice to control carbon emissions in China instead of just increasing total forest area. Reforms regarding the management of forests would be a good policy for both pollution reduction and employment generation.

Entrepreneurship and Income Inequality: A Spatial Econometric Approach

This paper extends research on the link between entrepreneurship and income inequality by introducing spatial considerations. Following a battery of specification tests, we model the relationship between entrepreneurship and inequality using a dynamic spatial Durbin model. Using data from the 48 continental U.S. states, we obtain strong evidence that entrepreneurship within a state not only affects inequality within that state, but has cross-state effects, as well.

Low-carbon Innovation, Economic Growth and CO2 Emission: Evidence from a Dynamic Spatial Panel Approach in China

Low-carbon technology innovation plays an essential role in carbon emission reduction worldwide. This study investigates how low-carbon innovation affects carbon emissions by the Dynamic Spatial Durbin Model based on the panel data of 30 Chinses provinces from 2007 to 2017. The empirical results show that: Firstly, low-carbon innovation decreases carbon emissions from local and neighbor, the decreasing effects are significant mainly in the short term. Secondly, the results of the heterogeneity test indicate that the weakening effect of low-carbon innovation in central regions is consistent with the national results. The weakening effects are shown in long-term indirect and short-term direct in eastern regions. Thirdly, there is an inverted-U curve between economic development and carbon emissions, confirming the environmental Kuznets curve (EKC) hypothesis. However, the inflection point is insurmountable under the current level of technology in China. Finally, The results also show the “Pollution Paradise” effect.

Empirical Study of the Spatial Spillover Effect of Transportation Infrastructure on Green Total Factor Productivity

Transportation infrastructure promotes the regional flow of production. The construction and use of transportation infrastructure have a crucial effect on climate change, the sustainable development of the economy, and Green Total Factor Productivity (GTFP). Based on the panel data of 30 provinces in China from 2005 to 2017, this study empirically analyses the spatial spillover effect of transportation infrastructure on the GTFP using the Malmquist–Luenberger (ML) index and the dynamic spatial Durbin model. We found that transportation infrastructure has direct and spatial spillover effects on the growth of GTFP; highway density and railway density have significant positive spatial spillover effects, and especially-obvious immediate and lagging spatial spillover effects in the short-term. We also note that the passenger density and freight density of transportation infrastructure account for a relatively small contribution to the regional GTFP. Considering environmental pollution, energy consumption, and the enriching of the traffic infrastructure index system, we used the dynamic spatial Durbin model to study the spatial spillover effects of transportation infrastructure on GTFP.

Change in China’s SRB: A Dynamic Spatial Panel Approach

There has been some research on factors affecting China’s rising sex ratio at birth (SRB), but the spatial dependence has been largely neglected. With China’s census and sample survey data and the dynamic spatial Durbin model; we analyzed the changes in SRB in China. We found that SRB and its influencing factors were spatially correlated at the provincial level. For direct effects; urbanization significantly reduced SRB in this region; while strict family planning policies increased SRB in the local region. For indirect effects; the increase in per capita Gross Domestic Product and urbanization led to an increase in the SRB of the neighboring regions through population mobility. By comparison; educational improvement in one region benefited the neighboring provinces and reduced SRB.

Bad or good neighbours: a spatial financial contagion study

Purpose The purpose of this paper is to study the evolution of financial contagion between Eurozone banks, observing the credit default swaps (CDSs) market during the period 2009–2017. Design/methodology/approach The authors use a dynamic spatial Durbin model that enables to explore the direct and indirect effects over the short and long run and the transmission channels of the contagion. Findings The results show how contagion emerges through physical and financial market links between banks. This finding implies that a bank can fail because people expect other related financial institutions to fail as well (self-fulfilling crisis). The study provides statistically significant evidence of the presence of credit risk spillovers in CDS markets. The findings show that equity market dynamics of “neighbouring” banks are important factors in risk transmission. Originality/value The research provides a new contribution to the analysis of EZ banking risk contagion, studying CDS spread determinants both under a temporal and spatial dimension. Considering the cross-dependence of credit spreads, the study allowed to verify the non-linearity between the probability of default of a debtor and the observed credit spreads (credit spread puzzle). The authors provide information on the transmission mechanism of contagion and, on the effects among the largest banks. In fact, through the study of short- and long-term impacts, direct and indirect, the paper classify banks of systemic importance according to their effect on the financial system.