Modeling Diffusion through Statistical Network Analysis: A Simulation Study and Empirical Application to Same-Sex Marriage

The study of international relations by definition deals with interdependencies among countries. One form of interdependence between countries is the diffusion of country-level features, such as policies, political regimes, or conflict. In these studies, the outcome variable tends to be categorical, and the primary concern is the clustering of the outcome variable among connected countries. Statistically, such clustering is studied with spatial econometric models. This article instead proposes the use of a statistical network approach to model diffusion with a binary outcome variable. Using a statistical network instead of spatial econometric models allows for modeling autocorrelation in policy outcomes rather than the corresponding latent variable, and it simplifies the inclusion of temporal dynamics, higher level interdependencies, and interactions between network ties and country-level features. In our simulations, the performance of the Stochastic Actor-Oriented Model (SAOM) estimator is evaluated. Our simulation results show that spatial parameters and coefficients on additional covariates in a static binary spatial autoregressive model are accurately recovered when using SAOM. To demonstrate this model, the paper applies SAOM to original data on the international diffusion of same-sex marriage and gives practical instructions for using such models.

Understanding Public Attention towards the Beautiful Village Initiative in China and Exploring the Influencing Factors: An Empirical Analysis Based on the Baidu Index

The implementation of China’s Beautiful Village Initiative was an extraordinary achievement and aroused extensive public attention. However, existing research mostly focuses on the construction and seldom on public attention towards the Beautiful Village Initiative. For this reason, this paper investigated the spatiotemporal characteristics of public attention based on the Baidu index using time-constrained clustering and the spatial autocorrelation test. Our results showed that the evolutionary process can be divided into three stages: very little national attention (2011–2012), injection of a strong impetus (2013–2015), and rooted in the people’s minds (2016–2020). Spatially, provincial public attention demonstrated obvious spatial differentiation and stable spatial autocorrelation, with Low–Low clusters in Northwest China and High–High Clusters in East, Central, and North China. Spatial econometric models were further utilized to quantify the effects of socioeconomic factors on public attention. The results of the SEM model proved the existence of spatial spillover effects and indicated that the urbanization rate, population density, education level, and network popularity rate all positively affected public attention. The relationship between Beautiful Village construction and public attention was uncoordinated and, in most provinces, advances in public attention were ahead of the construction level. Our findings contribute to the understanding of public attention towards the Beautiful Village Initiative, and policy suggestions we proposed would be applied to increasing public awareness and participation.

The Spatial Difference of “Internet Plus Tourism” in Promoting Economic Growth

The “Internet plus Tourism” mode, which is the coordination of the internet and tourism, has become a new driving force for regional economic growth. In order to investigate the mechanism and superiority of “Internet plus Tourism” in terms of economic growth compared with the independent effects of the internet and tourism on economic growth, this paper uses the DEA model to calculate the tourism efficiency of 30 provinces in China from 2011 to 2019 and three spatial econometric models to comparatively analyze the independent effects of the internet and tourism with the synergized effect of “Internet plus Tourism” on economic growth. The results show that (1) the overall pattern of the internet is that coastal areas are ranked higher; (2) tourism efficiency presents a polarized hierarchical structure; (3) The effect of “Internet plus Tourism” on economic growth is significantly positive and is significantly greater than the independent effects of the internet and tourism on economic growth; (4) the internet, tourism, and “Internet plus Tourism” have different effects on economic growth in different regions. Therefore, the paper suggests that China should accelerate the integration of “Internet plus Tourism” and realize sustainable economic development.

A Study of Internet Development and Enterprise Financing in China

The development of the Internet has changed many traditional commercial models of enterprises. Therefore, the term Internet development is increasingly drawing attention from scholars. However, we are not certain whether the development of the Internet improves the problem of difficult financing of enterprises and enhances enterprise financing efficiency. This paper analyzes whether Internet development can promote enterprise financing efficiency. First, the Data Envelopment Analysis- Slack Based Measure (DEA-SBM) model is applied to measure the enterprise financing efficiency values of 31 provinces in China. The measurement results indicate that the enterprise financing efficiency in the eastern regions is higher than that of central and western regions. Then, this paper further tests if Internet development can contribute to enterprise financing efficiency based on an econometric model. The analysis results indicate that Internet development has an obvious promoting effect on enterprise financing efficiency. Later, spatial econometric models are adopted in this paper to further analyze if Internet development has a spatial overflow effect on enterprise financing efficiency. The results indicate that Internet development indeed has a spatial overflow effect on enterprise financing efficiency.

Spatial Effect of Crime on Peer-to-Peer Lodging Performance

Safety is a major factor impacting consumers’ participation in peer-to-peer (P2P) economies. Using spatial econometric models, this study examined crime effects on the performance (RevPAR) of P2P lodgings at three spatial ranges: property, community, and destination level. The performance of P2P lodgings is negatively associated with crime densities, while the degree of the association varies by crime types and room types. Crime can “spill over” to the neighborhood and have the strongest impact at the community level, followed by the destination level and the property level. The study provides a way to understand tourism risks using criminology theories and the concept of social uncertainty. Empirically, the study provides implications to the governance of community-based lodging business. We suggest that the effect of crime on P2P lodging performance was more conditioned by the safety environment in its neighborhood and the whole destination, rather than individual business operations.

RESEARCH OF HEALTH AS A COMPONENT OF LABOR POTENTIAL OF THE COUNTRY BY METHODS OF ECONOMETRIC ANALYSIS

The population health indicator, which has an impact on the development of labor potential and its demographic component, has been studied. A correlation analysis of the factors influencing the state of health of the population was performed. It has been proven that there is a strong relationship between life expectancy as an indicator of health and the factors that characterize the health care system, economic development of the state, quality of food and lifestyle. Spatial econometric models of the relationship between effective variable life expectancy and factor characteristics of different nature based on statistical material from 38 European countries were created. The obtained models have high values of adequacy and accuracy criteria, as well as satisfactory predictive quality.

Market Integration and Regional Green Total Factor Productivity: Evidence from China’s Province-Level Data

The development of market integration has an important effect on regional green total factor productivity (GTFP). Based on the panel data of 30 provinces in China from 2008 to 2017, this paper studies the spatial effect and transmission mechanism of market integration on regional green total factor productivity by calculating the Malmquist–Luenburger index and using spatial econometric models. It was found that market integration can promote the improvement of regional green total factor productivity. This positive effect is not only directly reflected in the region, it also indirectly promotes the growth of GTFP in nearby regions. In addition, market integration has shown significant positive effects on efficiency improvement and technological progress, and market integration has affected regional green total factor productivity through them. The above conclusions are of great significance for China to develop a green economy and promote high-quality economic transformation.

Spatial Automated Valuation Model (sAVM) – From the Notion of Space to the Design of an Evaluation Tool

Assuming that it is not possible to detach a dwelling from its location, this article highlights the relevance of space in the context of housing market analysis and the challenge of capturing the key elements of spatial structure in an automated valuation model: location attributes, heterogeneity, dependence and scale. Thus, the aim is to present a spatial automated valuation model (sAVM) prototype, which uses spatial econometric models to determine the value of a residential property, based on identification of eight housing characteristics (seven are physical attributes of a dwelling, and one is its location; once this spatial data is known, dozens of new variables are automatically associated with the model, producing new and valuable information to estimate the price of a housing unit). This prototype was developed in a successful cooperation between an academic institution (University of Aveiro) and a business company (PrimeYield SA), resulting the Prime AVM & Analytics product/service. This collaboration has provided an opportunity to materialize some of fundamental knowledge and research produced in the field of spatial econometric models over the last 15 years into decision support tools.