Does economic growth and energy consumption drive environmental degradation in China’s 31 provinces? New evidence from a spatial econometric perspective

The panel data analysis points to economic and social factors contributing to NO_x, PM_2.5, PM₁₀, SO₂, and VOCs in China’s 31 provinces. The spatial correlation analysis using Global and Local Moran’s I values indicates the existence of a significant and positive spatial autocorrelation with respect to environment, economy and energy, and the high spatial correlation is evident in the eastern region, covering the northern part of Yangtze River Delta, Huaihai Economic Zone, and the lower reaches of the Yellow River Economic Belt. The empirical estimation is performed through spatial lag and spatial Durbin models. All emitted air pollutants in 31 provinces have significant spatial dependence and strong spillover effects. There is an inverted U-shaped relationship between emitted air pollutants (NO_x, PM₁₀, VOCs, and PM_2.5) and per capita GDP, which follows the EKC hypothesis. The relationship between SO₂ and per capita GDP does not follow the EKC hypothesis. There is a positive relationship between pollutant emissions and coal consumption, which is consistent with current studies for various countries like Canada, Denmark, UK and US and regions like New York State. However, the effects of science and technology investment on air pollutants are mostly positive, which is not as policy expected.     

Do Indian States Mimic,Compete or Interact in Local Public Spending? A Spatial Econometric Analysis

This paper analyses spatial interaction in public spending decisions across 22 Indian states during the period 1980–1981 to 2014–2015. In particular, we estimate interactive hypotheses for different proximities of states using a spatial panel data approach. The empirical results support strong spatial interaction and yardstick competition in public spending. Interactive behavior among the states has been found to be consistent and conditional on per capita income, fiscal transfers, infrastructure, literacy and population density. Interaction arising from yardstick competition significantly affects public spending decisions. The present study realizes the need for a well‐developed and comprehensive network to strengthen the interdependence in public spending among the states for higher welfare gain.     

Corruption in space: A closer look at the world's subnations

Corruption levels differ not only between but also within countries. In this paper we analyze spatial interdependencies in corruption levels for a large sample of 1232 subnational regions from 81 countries. Based on a spatial autoregressive model, which controls for country-fixed effects and corrects for spatial autocorrelation in the error term, we find that a subnational region's corruption level is positively correlated with neighboring subnational regions' corruption levels. Extending the core model and allowing for heterogeneous spatial effects, we find that most spillovers among subnational regions occur within national borders. Moreover, in particular high income subnational regions and subnational regions with relative low corruption levels tend to spill in space. This is due to their high degree of connectivity in terms of economic, sociocultural and political exchange with other subnational regions. Our estimation results underline the importance to consider not only a subnational region's own characteristics, but also spatial interdependencies when implementing efficient anti-corruption policies at the local level.     

Heteroskedasticity-consistent covariance matrix estimators for spatial autoregressive models

In the presence of heteroskedasticity, conventional test statistics based on the ordinary least squares (OLS) estimator lead to incorrect inference results for the linear regression model. Given that heteroskedasticity is common in cross-sectional data, the test statistics based on various forms of heteroskedasticity-consistent covariance matrices (HCCMs) have been developed in the literature. In contrast to the standard linear regression model, heteroskedasticity is a more serious problem for spatial econometric models, generally causing inconsistent extremum estimators of model coefficients. This paper investigates the finite sample properties of the heteroskedasticity-robust generalized method of moments estimator (RGMME) for a spatial econometric model with an unknown form of heteroskedasticity. In particular, it develops various HCCM-type corrections to improve the finite sample properties of the RGMME and the conventional Wald test. The Monte Carlo results indicate that the HCCM-type corrections can produce more accurate results for inference on model parameters and the impact effects estimates in small samples.     

Industry risk transmission channels and the spillover effects of specific determinants in China’s stock market: A spatial econometrics approach

This paper uses a spatial econometrics approach to study the industry risks in China’s stock market. We comprehensively consider the real linkage and information risk transmission channels and analyze the risk spillovers of specific determinants. Our empirical results show the following: 1) The real linkage channel and information channel are both effective transmission channels for driving spillover effects, and the information channel is of the utmost importance. 2) The spillover effects of specific determinants exist and are persistent. The superposition of spillover effects may lead to extreme risk. 3) The transmission channels and spillover effects are asymmetric in different regimes.     

城镇群空间结构与要素集聚

依据城镇化发展过程中要素空间集聚理论，展开区域经济发展的空间经济结构研究。通过城市引力、克鲁格曼指数计算，比较分析城镇群内部城市吸引力和城市产业分布的差异性，通过人口与生产空间分布集中度指标和不一致系数的测算，分析了山西省城镇群空间要素集聚效应。研究表明，山西省的城镇群规划与要素空间集聚趋势整体一致，城市间产业分工体系基本形成，城镇群的要素集聚效应明显，但人口与生产分布仍存在不一致性。研究认为，山西省城镇群发展应该继续明确各城市的产业分工和特色，引导劳动力和资本要素的合理流动，实现人口与生产空间分布的一致。     

农作物面积抽样单元空间变异性及其对抽样外推效率的影响

［目的］联合遥感和传统抽样方法的空间抽样技术是进行大区域农作物面积监测的有效手段。但传统抽样要求抽样单元间相互独立，并未考虑到区域农作物空间变异性的存在对农作物面积空间抽样效率是否有影响及其影响程度如何，从而限制了农作物面积监测的效率和精度。［方法］文章以吉林省德惠市为研究区，利用变异函数分别对10种抽样单元尺度内玉米和水稻种植面积的空间变异性进行定量评价。选择3种空间抽样方案（简单随机抽样、系统抽样、分层抽样），分别计算不同空间变异程度下的样本容量（n）、抽样相对误差（Re）和总体总值估计量的变异系数（CV（Y︿））作为空间抽样效率的评价指标，定量分析空间变异性对农作物面积空间抽样效率的影响，提出适宜空间变异农作物的空间抽样优化方案。［结果］(1)玉米和水稻面积的空间变异性（反映为基台值C0+C）均随着抽样单元尺度的增加逐渐而减小，其中500m×500m和2 500m×2 500m抽样单元尺度下农作物面积的空间自相关程度相对最小。(2)相同抽样比下，农作物面积在3种抽样方法下的相对误差和变异系数均随着空间变异性的减小（抽样单元尺度增加）逐渐增大，其中玉米和水稻在分层抽样条件下的相对误差和变异系数具有相对最小值，分别限制在10%和20%以内，其次为系统抽样（Re<40%，CV（Y︿）<88%）和简单随机抽样（Re<50%，CV（Y︿）<75%）。 在抽样方法被选定的情况下，两种农作物的分层抽样相对误差变化率随着抽样比的增加迅速降低，当抽样比增至5%时，其相对误差和变异系数的变化率基本趋于稳定，继续增加抽样比来提高抽样精度的效果甚微。 在3 500m×3 500m抽样单元尺度内，按5%抽样比确定的样本容量对玉米和水稻面积进行分层抽样时，可达到95%的抽样精度（Re<5%）。 综合农作物在不同抽样单元尺度下的空间变异特征和空间抽样效率，基于2 500m×2 500m的抽样单元尺度和5%抽样比进行分层抽样的空间变异性农作物空间抽样方案是一种高精度、低成本、代表性强的空间抽样方案。［结论］该研究为区域农作物面积抽样调查方法的改善和抽样效率的提高提供技术支持和参考依据。     

中国旅游景区功能演变与用地分类构想

研究目的:基于中国旅游景区功能演变、用地特征及问题分析,构建旅游景区用地分类体系,以期为旅游景区用地纳入区域土地利用提供理论基础,为旅游景区规划的深度编制提供实践依据。研究方法:通过调研和问卷厘清现状景区用地情况,对比借鉴相关用地分类体系,基于此构建旅游景区用地分类方案。研究结果:分析并阐明了旅游景区的功能演变、用地特征和现状问题,构建了2大类、9中类、28小类的景区用地分类体系,并与《土地利用现状分类》进行衔接。研究结论:建立可衔接且具可操作性的旅游景区用地分类体系,是实现旅游景区健康可持续发展与用地规范化管控的关键。     

Technological leadership and sectorial employment growth: A spatial econometric analysis for U.S. counties

This paper studies the determinants of technological catch‐up considering spatial and sectoral aggregation of industries. We investigate how geographical and technological proximity to the technology leader impact regional employment growth. We model technological progress by means of a hierarchical process of catch‐up to the technology leader. We also incorporate measures for knowledge spillover effects to test the roles of competition, specialisation, and diversity at the industry level. Empirical results using data at the county level for different economic sectors (2‐dig NAICS) for the United States indicate that human capital plays a crucial role in promoting sectoral employment growth. The association between technological/geographical distance to the technology leader and employment growth varies across sectors.     

线性文化遗产的特征及其对旅游利用模式的影响——基于《世界遗产名录》的统计分析

线性文化遗产是一种特殊的遗产类型,随着人们对遗产完整性不断深入的理解以及遗产活化利用理念的发展,线性文化遗产旅游的重要性日益显现。因此,树立线性文化遗产意识,把握线性文化遗产特征,是推进线性文化遗产旅游利用和可持续发展的重要问题。本文以《世界遗产名录》中收录的线性文化遗产为基础数据,对线性文化遗产的类别与列入标准、资源组合模式和核心区与缓冲区等典型特征进行深入分析,并从旅游空间演化和旅游活化路径两方面总结其对旅游利用模式的影响,以期为线性文化遗产旅游的可持续发展提供科学参考。研究结果表明,线性文化遗产旅游空间结构发展过程遵循“增长极”演化规律,并在遗产文化分层上表现出不同的利用方式和活化路径。