An expanded knowledge production function

This paper uses a theoretical motivation for an Expanded Knowledge Production Function(EKPF) that encompasses both path dependence and spatial spillovers to search for evidences inBrazil using a Dynamic Spatial Panel Data approach. The purpose is to identify the determinantsof knowledge production in the 2005-2015 period as well as its temporal evolution, usinginnovation patents as proxies. Regarding its spatial distribution, we identified a North-Southdisparity for the knowledge production in Brazil, with Southeast and South producing alarge part of the country’s patents. Based on the EKPF, we confirmed the importance ofpath dependence and knowledge spillovers to explain the Brazilian innovation. In addition,population density, which generates Jacobian externalities and economies of agglomeration, isan important structural feature in the short run while the number of researchers in universitiesand an increased economic scale are essential to knowledge production in the long run.

Spatial Panel Data Analysis on the Relationship between Provincial Economic Status and Enrolment in the Social Security Scheme amongst Migrant Workers in Thailand, 2015–2018

Background: Thailand has a large flow of migrants from neighbouring countries; however, the relationship between economic status at the provincial level and the insured status of migrants is still vague. This study aimed to examine the association between provincial economy and the coverage of the Social Security Scheme (SSS) for migrants. Methods: Time-series data were analysed. The units of analysis were 77 provinces during 2015–2018. Data were obtained from the Social Security Office (SSO). Spatiotemporal regression (Spatial Durbin model (SDM)) was applied. Results: Migrant workers were mostly concentrated in Greater Bangkok, the capital city and areas surrounding it, but SSS coverage was less than 50%. However, the ratio of insured migrants to all migrants seemed to have positive relationship with the provincial economy in SDM. The ratio of insured migrants to all migrants was enlarged in all regions outside Greater Bangkok with statistical significance. Conclusions: Low enforcement on employment law in some areas, particularly Greater Bangkok, can result in lesser SSS coverage. The provincial economic prosperity did not guarantee large SSS coverage. Interventions to ensure strict insurance enrolment are required.

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.

The environmental Kuznets curve for Turkish provinces: a spatial panel data approach

This paper aims to test the existence of the environmental Kuznets curve (EKC) hypothesis using SO2 measurements in Turkish provinces between 2004 and 2019. The existing studies concerning the EKC hypothesis for Turkey either use a country-level analysis or panel data techniques covering provincial data that do not account for the spatial dimension. To account for the spatial dependence and overcome the biases resulting from the existence of such spatial spillovers, this paper combines the traditional panel data methodology with the recent advances in spatial econometrics. Our findings confirm the presence of a non-linear link between regional economic prospects and environmental degradation. However, unlike the core expectations of the EKC hypothesis, our results demonstrate a U-shaped relationship between economic development and SO2 levels. Moreover, these findings are robust to the inclusion of a spatial battery which highlights the existence of regional spillovers. Overall, our results show that the post-2000 epoch calls for a different action plan to mitigate the rising impact of environmental degradation in Turkey.

Research on Labor Market Institutional Environment and Labor Agglomeration—Analysis Based on Dynamic Spatial Panel Data

The institutional environment not only has a great impact on economic development but also has a certain impact on labor agglomeration. This paper explains the phenomenon of labor agglomeration from the perspective of the labor market institutional environment. Taking the labor market institutional environment including social contract environment and labor contract environment as the premise, it is considered that a good labor institutional market can promote labor agglomeration and technological progress can stimulate the agglomeration of highly-skilled talents through theoretical analysis. Based on the provincial panel data from 2001 to 2017, the empirical analysis is conducted to verify the relevant factors through the dynamic spatial Durbin model. The paper finally puts forward some policy suggestions to maintain a good institutional environment of the labor market, including that the local government should continue to improve the labor dispute settlement system, strengthen the protection of labor rights and interests, and enhance the institutional environment of the regional labor market.

Environmental Regulation, Outward Foreign Direct Investment, and Low-Carbon Innovation: An Empirical Study Based on Provincial Spatial Panel Data in China

The low-carbon transformation has turned out to be a challenging task faced by government agencies, enterprises, and society because of the global warming. Endorsing the expansion of the low-carbon revolution is considered as an essential measure for low-carbon alteration and advancement. Therefore, articulating realistic environmental control strategies intended to enhance the motivation level of low-carbon innovation, though outward foreign direct investment (OFDI) can produce direct and indirect influences on the growth of low-carbon innovation. According to the data of 30 provinces of China from 2004 to 2017, the relationship among environmental regulation, OFDI, and low-carbon innovation was analyzed using the spatial econometric model. Based on the analyzed data, the following conclusions were drawn. (i) From the national and regional perspectives, China’s low-carbon innovation takes understandable agglomeration features in the longitudinal dimension. In addition, environmental regulation plays a key role in promoting low-carbon innovation and regional heterogeneity. (ii) Environmental regulation might force enterprises outward foreign direct investment efficiently and increase the level of OFDI that will be capable of promoting low-carbon innovation. (iii) OFDI acts as an intermediary in the relationship between environmental regulation and low-carbon innovation, and this role has regional heterogeneity. (iv) There are significant spatial spillover effects of environmental regulation and OFDI on low-carbon innovation, environmental regulation on OFDI, and the intermediary effect of OFDI on environmental regulation and low-carbon innovation. This study supplements our understanding of the relationship between environmental regulation and OFDI, in addition to low-carbon innovation, which provides illumination for enterprise practice, as well as decision-makers.