Differences in Distance and Spatial Effects on Cross-Border E-Commerce and International Trade

Distance and space are important factors affecting international trade, but they have different effects on cross-border e-commerce (CBE) due to the creation of the Internet. This study utilizes spatial autocorrelation, the multi-dimension gravity model and the Spatial Durbin model to conduct an comparative analysis of international trade and CBE within one-belt one-road (BR) countries. Our study obtained several key findings. Firstly, the spatial autocorrelation effect which exists in international trade does not exist in CBE. Secondly, the geographical distance effect of CBE is not significant, which is different from that of international trade. Thirdly, CBE is affected by GDP, culture, policy and institution distances which is not entirely consistent with international trade. Finally, the Spatial Durbin model shows that the spillover effect of CBE and international trade are both significant in the inverse distance weight matrix. These findings provide not only important theoretical contributions but also a practical guide for Government policy makers of the BR and CBE.

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.

The Impact of Foreign Direct Investment on Income Convergence in China - A Spatial Panel Data Analysis

After taking into account the spatial dependence effects in the panel data consisting of all 31 provinces, direct-controlled municipalities, and autonomous regions in China between the years 1998 and 2017, it found significant spatial autocorrelation effects in both traditional absolute and conditional β income convergence models. At the national level, using the spatial econometric models (Spatial Error Model for absolute convergence and Spatial Durbin Model for conditional convergence), the analysis shows that in the past 19 years from 1999 to 2017, there is no absolute β income convergence. However, there is conditional β income convergence after controlling for all growth factors, while the positive effect of fixed asset investment on regional economic growth is significant, and the effect of population growth is significantly negative. The other growth factors such as FDI inflow, export, and higher education enrollment were surprisingly found no statistically significant effects on regional economic growth. From regional level (Spatial Durbin Model and Spatial Lag Model), there is no conditional β income convergence within each four economic regions. Nonetheless, the northeast region showed an income divergence trend, where only the fixed asset investment is positively significant. This study results imply that China should continue to improve fixed asset investment and control population growth to stimulate regional economic growth and income convergence.

How Do Chinese National Scenic Areas Affect Tourism Economic Development? The Moderating Effect of Time-Limited Rectification

Based on panel data on 124 prefecture-level and above cities from 2003 to 2018, this study investigated the impact of CNSAs on tourism economic development and the moderating effect of time-limited rectification by comprehensively using the quasi-DID model, the static spatial Durbin model, and the dynamic spatial Durbin model. The results showed that the impact of CNSAs on tourism economic development has a heterogeneous characteristic in terms of tourists and revenue. In addition, the spatial spillover effect and the path dependence have effectively promoted tourism economic development. Furthermore, the effectiveness of time-limited rectification has been proved in this study, while the “beggar-thy-neighbor” effect has, to some extent, weakened the promotional effect of CNSAs on tourism economic development, especially in terms of international tourists and international tourism revenue. Finally, relevant policy implications for the superior department in charge, local governments, and the management department of CNSAs are outlined to provide a practical reference for promoting the high-quality development of the tourism economy in China.

METODE SPATIAL DURBIN MODEL UNTUK ANALISIS DEMAM BERDARAH DENGUE DI KABUPATEN BANTUL

Dengue Hemorrhagic Fever (DHF) is an infectious disease caused by the dengue virus which is transmitted through the bite of the Aedes aegepty and Aedes albopictus mosquitoes which are widespread in homes and public places throughout the territory of Indonesia. The high number of DHF cases in Bantul Regency, Indonesia is an indication that eradication of Aedes aegepty mosquitoes and Aedes albopictus mosquitoes has not succeeded in the Bantul Regency. Spatial Regression is an analysis that evaluates the relationship between one variable with several other variables by providing spatial effects in several locations that are the center of observation. Three type of models are Spatial Autoregressive Model (SAR), Spatial Error Model (SEM), and Spatial Durbin Model (SDM). This study uses secondary data in 2017 in Bantul Regency, Special Region of Yogyakarta, Indonesia. The dependent variable is DHF cases and the independent variables are medical personnel and health facilities in each sub-district. The spatial model used is SDM. Based on Moran’s I test, there was a spatial autocorrelation about DHF among sub-district, so the spatial model can be used. The durbin spatial model gives the result that all estimation parameters in SDM model have P value less than α = 5%, so that medical personnel and health facilities significantly affect dengue cases in Bantul Regency. Keywords: dengue hemorrhagic fever, moran’s I test, spatial durbin model.

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.