IS SPATIAL BOOTSTRAPPING A PANACEA FOR VALID INFERENCE?

Bootstrapping methods have so far been rarely used to evaluate spatial datasets. Based on an extensive Monte Carlo study we find that also for spatial, cross‐sectional data, the wild bootstrap test proposed by Davidson and Flachaire ( 2008 ) based on restricted residuals clearly outperforms asymptotic as well as competing bootstrap tests, like the pairs bootstrap.     

WHEN AND HOW DOES COMMUTING TO CITIES INFLUENCE RURAL EMPLOYMENT GROWTH?

This paper estimates the influence that rural‐to‐urban commuting has on rural employment growth, and whether the strength and spatial reach of this effect depend on commuters’ levels of education. A main finding is that rural‐to‐urban commuting has a robust positive impact on rural employment growth in services and retail. There is no significant difference in how far these effects reach into rural Sweden for commuters with different levels of education. These results suggest that a viable policy for local employment growth in rural areas with reasonable commuting times to urban centers is to improve the commuting to urban centers.     

THE FUTURE TRAJECTORY OF U.S. CO2 EMISSIONS: THE ROLE OF STATE VS. AGGREGATE INFORMATION*

ABSTRACT This paper provides comparisons of a variety of time‐series methods for short‐run forecasts of the main greenhouse gas, carbon dioxide, for the United States, using a recently released state‐level data set from 1960–2001. We test the out‐of‐sample performance of univariate and multivariate forecasting models by aggregating state‐level forecasts versus forecasting the aggregate directly. We find evidence that forecasting the disaggregate series and accounting for spatial effects drastically improves forecasting performance under root mean squared forecast error loss. Based on the in‐sample observations we attempt to explain the emergence of voluntary efforts by states to reduce greenhouse gas emissions. We find evidence that states with decreasing per capita emissions and a “greener” median voter are more likely to push toward voluntary cutbacks in emissions.     

Evaluating the Temporal and Spatial Heterogeneity of the European Convergence Process, 1980–1999*

Abstract. In this paper, we suggest a framework that allows testing simultaneously for temporal heterogeneity, spatial heterogeneity, and spatial autocorrelation in β‐convergence models. Based on a sample of 145 European regions over the 1980–1999 period, we estimate a Seemingly Unrelated Regression Model with spatial regimes and spatial autocorrelation for two sub‐periods: 1980–1989 and 1989–1999. The assumption of temporal independence between the two periods is rejected, and the estimation results point to the presence of spatial error autocorrelation in both sub‐periods and spatial instability in the second sub‐period, indicating the formation of a convergence club between the peripheral regions of the European Union.     

江苏省县域经济集聚和收敛的空间计量分析

通过探索性空间数据分析和空间计量分析方法,以实际人均GDP为测度指标,对江苏省65个县市的经济空间集聚、增长收敛性以及收敛机制进行讨论。研究发现1993-2009年实际人均GDP显示出越来越高的全局正相关,局部空间相关性也有增强的趋势。空间计量分析结果表明江苏省县域经济存在着β收敛,分时段研究为不同研究时段选择恰当的空间收敛模型后,收敛速度加快。技术扩散收敛机制和资本收敛机制分别在研究区间的前期和后期占主导作用,收敛机制的转变与江苏省在20世纪90年代末开始实行的区域协调发展政策密切相关。     

THE POLITICAL TRADE‐OFF BETWEEN ENVIRONMENTAL STRINGENCY AND ECONOMIC DEVELOPMENT IN RURAL AMERICA*

ABSTRACT We examine the impact of the political trade‐off between rural economic development and environmental quality on the determination of environmental regulations in the U.S. intensive livestock industry. The political economy model, adapted from Fredriksson (1997) , is tested empirically, using state‐level data on environmental regulation of the U.S. livestock sector. We find that state governments respond to greater potential for water pollution with more stringent environmental regulations. Consistent with our political economy model, we also find that states with lower recent growth in per capita income implement less stringent environmental regulations.     

基于GIS的蔚县乡村聚落空间格局演化与驱动机制分析

以蔚州志和蔚县地名资料汇编为数据源,借助GIS核密度估计方法研究了蔚县乡村聚落商周时期至清朝3000多年间的空间格局演化特点。总体演化过程呈现由集中分布趋向随机分布的特征;演化过程中形成了四个不同阶段的区域空间格局:"缓慢增长的壶流河一侧‘一’字形‘双核’分布模式"、"普遍增长的壶流河下游‘多核’分布模式"、"快速增长的壶流河两侧大范围增长带的空间扩展模式"、"稳定增长的壶流河两侧带状‘多核’空间分布模式"。根据演化特点和历史文化资料分析,总结了蔚县乡村聚落演化的自然条件、军事历史条件、人口迁移和经济贸易发展四个方面驱动因素。研究表明核密度估计法可以较好的表现聚落空间格局,方便历史聚落演化不同阶段的对比分析。     

Destination choices of Chinese rural–urban migrant workers: Jobs,amenities, and local spillovers

Using the 2014 China Migrants Dynamic Survey, we analyze rural–urban migrant workers’ destination choices after the global financial crisis, with an emphasis on jobs, amenities, and local spillovers. By using an equilibrium‐sorting model, this paper disentangles local spillovers from local attributes in the estimation process. We employ both an artificial instrumental variable and the provincial highway passenger flow in 1979 to tackle the endogeneity issue. After controlling for the network effects of migrants from the same origin, we find a separate and strong preference for colocating with a large population of migrants, regardless of origin. The results remain robust when we take into account labor supply‐driven migration, spatial autocorrelation between provinces, different industry definitions, and regional differences within provinces. Our results imply that due to institutional barriers, the rural‐migrant community will still be a very important factor in the foreseeable future. In addition, as the ongoing industrial upgrading and transfer policies in China may lead to a westward movement of rural–urban migrants, the movement will be expedited when the older, less educated, or lower income migrants relocate.     

Gaussian Process Regression and Bayesian Model Averaging: An Alternative Approach to Modeling Spatial Phenomena

Gaussian Process Regression (GPR) is a nonparametric technique that is capable of yielding reliable out‐of‐sample predictions in the presence of highly nonlinear unknown relationships between dependent and explanatory variables. But in terms of identifying relevant explanatory variables, this method is far less explicit about questions of statistical significance. In contrast, more traditional spatial econometric models, such as spatial autoregressive models or spatial error models, place rather strong prior restrictions on the functional form of relationships, but allow direct inference with respect to explanatory variables. In this article, we attempt to combine the best of both techniques by augmenting GPR with a Bayesian Model Averaging (BMA) component that allows for the identification of statistically relevant explanatory variables while retaining the predictive performance of GPR. In particular, GPR‐BMA yields a posterior probability interpretation of model‐inclusion frequencies that provides a natural measure of the statistical relevance of each variable. Moreover, while such frequencies offer no direct information about the signs of local marginal effects, it is shown that partial derivatives based on the mean GPR predictions do provide such information. We illustrate the additional insights made possible by this approach by applying GPR‐BMA to a benchmark BMA data set involving potential determinants of cross‐country economic growth. It is shown that localized marginal effects based on partial derivatives of mean GPR predictions yield additional insights into comparative growth effects across countries.     

Stochastic Efficiency of Bayesian Markov Chain Monte Carlo in Spatial Econometric Models: An Empirical Comparison of Exact Sampling Methods

Spatial econometric specifications pose unique computational challenges to Bayesian analysis, making it difficult to estimate models efficiently. In the literature, the main focus has been on extending Bayesian analysis to increasingly complex spatial models. The stochastic efficiency of commonly used Markov Chain Monte Carlo (MCMC) samplers has received less attention by comparison. Specifically, Bayesian methods to analyze effective sample size and samplers that provide large effective size have not been thoroughly considered in the literature. Thus, we compare three MCMC techniques: the familiar Metropolis‐within‐Gibbs sampling, Slice‐within‐Gibbs sampling, and Hamiltonian Monte Carlo. The latter two methods, while common in other domains, are not as widely encountered in Bayesian spatial econometrics. We assess these methods across four different scenarios in which we estimate the spatial autoregressive parameter in a mixed regressive, spatial autoregressive specification (or, spatial lag model). We find that off‐the‐shelf implementations of the newer high‐yield simulation techniques require significant adaptation to be viable. We further find that the effective sizes are often significantly smaller than nominal sizes. In addition, we find that stopping simulation early may understate posterior credible interval widths when effective sample size is small. More broadly, we suggest that sample information and stopping rules deserve more attention in both applied and basic Bayesian spatial econometric research.     

POPULATION DISPERSION VS. CONCENTRATION IN A TWO‐REGION MIGRATION MODEL WITH ENDOGENOUS NATURAL AMENITIES*

ABSTRACT Contrary to the predictions of the basic spatial equilibrium model, the long‐run distribution of population across rural U.S. counties with high‐valued natural amenities has become relatively more concentrated versus dispersed. We provide an explanation by developing a two‐region model with mobile labor, production externalities and endogenous natural amenities. We find that strong preferences for natural amenities generally foster population dispersion. However, such preferences can also lead to population concentration when ecological degradation is low and man‐made capital is a relatively scarce input into natural amenity production. Investments that enhance natural amenities are found to reduce the divergence between the steady state and optimal outcomes.     

发达地区的乡村集镇空间扩展差异与模型研究——以锡山市为例

长江三角洲是我国经济发展最迅速、乡镇企业成长最快的地域。从1970到1998近30年的时间中,尤其是从1978到1998年,锡山市域乡村集镇发生了巨大变化,其发展经历了数量由多到少,规模由小到大的过程。数量的变化本身体现了无锡市区空间和集镇规模的扩大和功能的增强。本文首先从1970年的地形图和1984、1991、1998三年的遥感影像上提取锡山市乡村集镇的空间扩展变化信息,在地理信息系统软件中进行叠置分析,然后建立乡村集镇扩展的模型,为乡村集镇空间扩展趋势的预测、规划提供依据。论文提供了三种乡村集镇扩展的模型:线型模型、幂函数模型和指数函数模型,而幂函数模型是预测今后集镇发展规模较理想的模型。     

FRAGMENTATION AND CLUSTERING IN VERTICALLY LINKED INDUSTRIES*

ABSTRACT This paper models the location of two vertically related firms in a low labor cost country and in a country with a large market. The upstream industry is more labor intensive than the downstream industry. We find that spatial fragmentation occurs for low values of the input‐output coefficient and intermediate values of the transport rate, particularly if the countries are very asymmetric in size. Otherwise, we obtain agglomeration either in the low cost country (when the transport rate is low) or in the large market (when the transport rate is high). Multiple agglomerated equilibria arise when the transport cost of the intermediate good is significant.     

REGIONAL LABOR PRODUCTIVITY IN THE NETHERLANDS: EVIDENCE OF AGGLOMERATION AND CONGESTION EFFECTS*

ABSTRACT This paper studies the impact of localization, urbanization, and diversification on regional labor productivity levels and growth. We find substantial effects, accounting for roughly half of the explained variation in the labor productivity differences within the Netherlands in the 1990s. Diversification, urbanization, and localization effects are significant and positive for productivity levels. These levels appear cointegrated. The error correction specification of productivity growth surprisingly reflects negative agglomeration effects. From the theoretical model it follows that congestion effects must have taken precedence over agglomeration effects during this period. Both agglomeration and congestion effects are dampened by job density in neighboring regions. Finally, policy simulations with the estimated model show that spatial concentration is more harmful to national productivity growth than spatial dispersion.     

COAL MINING AND THE RESOURCE CURSE IN THE EASTERN UNITED STATES

We measure the effect of resource‐sector dependence on long‐run income growth using the natural experiment of coal mining in 409 Appalachian counties selected for homogeneity. Using a panel data set (1970–2010), we find a one standard deviation increase in resource dependence is associated with 0.5–1 percentage point long‐run and a 0.2 percentage point short‐run decline in the annual growth rate of per capita personal income. We also measure the extent to which the resource curse operates through disincentives to education, and find significant effects, but this “education channel” explains less than 15 percent of the apparent curse.     

AGGLOMERATION,CONGESTION, AND U.S. REGIONAL DISPARITIES IN EMPLOYMENT GROWTH

Wide regional disparities exist in U.S. employment growth. To identify the causes of this disparities, we assess the relative contribution of locational characteristics to regional employment growth in the United States from 2001 to 2010 by estimating an employment growth model with the spatial‐lag effect. Results show that, at the margin, congestion effects dominate localized scale externalities in urban counties. A diverse industrial structure and rich human capital are the main factors that contribute to regional disparities in employment growth. Significant spatial‐lag effects indicate that spatial targeting and regional coordination are necessary to maximize the effectiveness of employment growth policies.     

大都市双核廊道结构空间增长过程研究——以美国华盛顿-巴尔的摩地区为例

本文以华盛顿-巴尔的摩地区200年都市化发展史为例,通过Mapinfo7.0得到两城市内、外接圆半径值①,以Logistic模型为基础计算出其半径增长速率并进行对比分析。研究表明,巴尔的摩和华盛顿城市化区的扩展表现为核心与廊道的共同增长,但二者的增长速率不具有同步增长过程;1962年前华盛顿城市化区的空间形态要优于巴尔的摩,随后则相反。传统的双核廊道结构空间增长研究多以整体为对象研究其增长过程,本文的创新特色在于通过对比分析两个城市内、外接圆半径的变化,来揭示双核廊道结构空间增长的特殊规律。     

Model Uncertainty in Matrix Exponential Spatial Growth Regression Models

This article considers the most important aspects of model uncertainty for spatial regression models, namely, the appropriate spatial weight matrix to be employed and the appropriate explanatory variables. We focus on the spatial Durbin model (SDM) specification in this study that nests most models used in the regional growth literature, and develop a simple Bayesian model‐averaging approach that provides a unified and formal treatment of these aspects of model uncertainty for SDM growth models. The approach expands on previous work by reducing the computational costs through the use of Bayesian information criterion model weights and a matrix exponential specification of the SDM model. The spatial Durbin matrix exponential model has theoretical and computational advantages over the spatial autoregressive specification due to the ease of inversion, differentiation, and integration of the matrix exponential. In particular, the matrix exponential has a simple matrix determinant that vanishes for the case of a spatial weight matrix with a trace of zero. This allows for a larger domain of spatial growth regression models to be analyzed with this approach, including models based on different classes of spatial weight matrices. The working of the approach is illustrated for the case of 32 potential determinants and three classes of spatial weight matrices (contiguity‐based, k‐nearest neighbor, and distance‐based spatial weight matrices), using a data set of income per capita growth for 273 European regions.     

大都市双核廊道结构空间增长过程研——以究美国华盛顿-巴尔的摩地区为例

本文以华盛顿-巴尔的摩地区200年都市化发展史为例,通过Mapinf07．0得到两城市内、外接圆半径值。以Logistic模型为基础计算出其半径增长速率并进行对比分析。研究表明,巴尔的摩和华盛顿城市化区的扩展表现为核心与廊道的共同增长,但二者的增长速率不具有同步增长过程;1962年前华盛顿城市化区的空间形态要优于巴尔的摩,随后则相反。传统的双核廊道结构空间增长研究多以整体为对泉研究其增长过程,本文的创新特色在于通过对比分析两个城市内、外接圆半径的变化,来揭示双核廊道结构空间增长的特殊规律。     

Cellular Automata for Studying Historical Spatial Process of Traditional Settlements Based on Gaussian Mixture Model: A Case Study of Qiaoxiang Village in Southern China

ABSTRACT

The spatial evolution of traditional rural settlements is a natural process that occurs without professional development planning. With rural spatial organization now being stimulated by China’s economic structure adjustment, making top-down plans match bottom-up spatial principles is important for the continuity of rural communities. In this research, a Cellular automaton based model was introduced to describe the historical spatial rules of rural settlements based on a traditional village in Southern China. In order to reproduce the rural spatial characteristics and laws that were close to the actual situation truthfully and distinctly, in this model, we refined the growth process into three cyclical steps, and used a Multivariate Gaussian Mixture Model for the evaluation of spatial transition potential. Through historical simulation, evaluation of the current status, and future spatial predictions, results showed that: (1) the growth during the whole spatial process maintained logical consistency for optimal selection; (2) certain houses in the southeast region should be carefully protected as a core living culture exhibit, while the best utilization of other homes should be considered; and (3) the most probable region of growth for tourist services or new housing estates is scattered along the river in the central area of the village.