Minimum distance quantile regression for spatial autoregressive panel data models with fixed effects

This paper considers the quantile regression model with individual fixed effects for spatial panel data. Efficient minimum distance quantile regression estimators based on instrumental variable (IV) method are proposed for parameter estimation. The proposed estimator is computational fast compared with the IV-FEQR estimator proposed by Dai et al. (2020). Asymptotic properties of the proposed estimators are also established. Simulations are conducted to study the performance of the proposed method. Finally, we illustrate our methodologies using a cigarettes demand data set.

Exploring the Effects of Urban Built Environment on Road Travel Speed Variability with a Spatial Panel Data Model

Road traffic congestion is a common problem in most large cities, and exploring the root causes is essential to alleviate traffic congestion. Travel behavior is closely related to the built environment, and affects road travel speed. This paper investigated the direct effect of built environment on the average travel speed of road traffic. Taxi trajectories were divided into 30 min time slot (48 time slots throughout the day) and matched to the road network to obtain the average travel speed of road segments. The Points of Interest (POIs) in the buffer zone on both sides of the road segment were used to calculate the built environment indicators corresponding to the road segment, and then a spatial panel data model was proposed to assess the influence of the built environment adjacent to the road segment on the average travel speed of the road segment. The results demonstrated that the bus stop density, healthcare service density, sports and leisure service density, and parking entrance and exit density are the key factors that positively affect the average road travel speed. The residential community density and business building density are the key factors that negatively affect the average travel speed. Built environments have spatial correlation and spatial heterogeneity in their influence on the average travel speed of road segments. Findings of this study may provide useful insights for understanding the correlation between road travel speed and built environment, which would have important implications for urban planning and governance, traffic demand forecasting and traffic system optimization.

Analysis on the Spatial Effect of Talent Supply of Vocational Education and Economic Growth of Tobacco Industry from the Perspective of Human Capital

Objectives: Human capital plays an important role in the economic growth of tobacco industry. Education is the direct way to form human capital. At the same time, vocational education is a part of the education system. Vocational education is mainly to cultivate skilled human capital. From the perspective of human capital, this paper studies the impact of talent supply of vocational education on tobacco economic growth. A combination of qualitative and quantitative analysis was used. This paper analyzes the current situation of talent supply of vocational education and tobacco economy in China. It also analyzes the correlation between talent supply of vocational education and tobacco economy. Based on the theoretical model of human capital economic growth. Establish the theoretical model of talent supply in vocational education and tobacco economic growth. Comprehensively consider the spatial interaction of economic growth. Using the spatial panel econometric model, this paper makes an empirical analysis on 29 provinces and cities in China. Use Geoda, MATLAB and other software for empirical calculation. The results show that the supply of vocational education talents and the growth of tobacco economy are on the rise. However, the regional distribution is uneven. And vocational education is positively correlated with tobacco economic growth. The empirical results show that the regional tobacco economic growth in China has negative spatial auto-correlation. Employment, lifetime number of vocational education and human capital level in the tobacco industry significantly promote the economic growth of the tobacco industry. The results provide a reference for the regulation of China's tobacco industry.

Contribution of on-road transportation to PM2.5

Fine particulate matter (PM2.5) mainly originates from combustion emissions. On-road transportation is considered one of the primary sources of PM2.5 emission. The relationship between on-road transportation and PM2.5 concentration varies temporally and spatially, and the estimation for this variation is important for policymaking. Here, we reveal the quantitative association of PM2.5 concentration with on-road transportation by the spatial panel Durbin model and the geographical and temporal weighted regression. We find that 6.17 billion kilometres (km) per km2 on-road transportation increase is associated with a 1-μg/m3 county-level PM2.5 concentration increase in the contiguous United States. On-road transportation marginally contributes to PM2.5, only 1.09% on average. Approximately 3605 premature deaths are attributed to PM2.5 from on-road transportation in 2010, and about a total of 50,223 premature deaths ascribe to PM2.5 taking 6.49% from 2003 to 2016. Our findings shed light on the necessity of the county-level policies considering the temporal and spatial variability of the relationship to further mitigate PM2.5 from on-road transportation.