Spatial analysis of bureaucrats’ attempts to resist political capture in a developing democracy: The distribution of solar panels in Ghana

Can civil servants in a developing democracy successfully resist political capture in the distribution of public goods? Existing research tends to highlight political patronage logics of distribution, and scholarship focuses primarily on politicians’ motivations. But service decisions are often made by bureaucrats, who sometimes explicitly try to avoid capture and allocate on the basis of need. Using qualitative interviews and spatial regressions with geo-coded data from a solar panel program in Ghana, we examine such a situation. We show that, despite considerable efforts to thwart it, national-level civil servants were unable to fully resist political capture. While solar panel distribution partially corresponded to need for electricity, we find that panels also went to areas where voter turnout was historically inconsistent, likely to motivate voter turnout. The direction of these relationships was consistent across subnational space, but the magnitudes varied considerably and were strongest in districts adjacent to Lake Volta. Qualitative data analysis reveals that this subnational variation reflects the logistics of space and the historical politics of place. The article contributes to theories of distributive politics and of voting behavior, and highlights the need for subnational disaggregation across space.     

基于POI大数据的老工业区房价影响因素空间分异与实证

在采集沈阳市铁西区2017年住宅、工厂、地铁站等兴趣点数据的基础上,将工厂距离、房龄以及住宅密度三个变量与传统变量共同参与构建地理加权回归模型,揭示房价影响因素的空间异质性及形成机制。结果表明：在全区范围内,房龄、住宅密度、公共交通、公共配套设施等对房价有显著的提升作用,而工业企业等对房价有一定的抑制作用;新老城区对比来看,所筛选的影响因素与房价的相关性具有显著的空间非平稳性,具体表现在工厂距离、公交密度、商场距离等因素在新老城区的正负影响差异,以及住宅密度、地铁站距离等单向影响因子回归系数的强度渐变;从研究方法来看,基于POI与GWR集成分析,可以有效克服房价实时更新慢、准确度低及数据清洗困难等传统难题,从而为构建和发展新数据环境下的经济地理研究提供参考。     

Spatially varying relationships between municipal operating expenditure and its determinants: The case of South Africa

We apply the geographically weighted regression to investigate spatial variability (nonstationarity) in the relationships between municipal operating expenditure (in total and for a separate component thereof) and the determinants of this expenditure, in South Africa. The empirical findings indicate that some of these relationships are spatially varying for the period under consideration. The global model (i.e., least square regression) cannot take account of the unequal environment in which South African municipalities operate. One implication of our findings is that a “one-size-fits-all” approach in the design of policies targeting municipal finances may not be appropriate for municipalities in South Africa, and indeed in other contexts in which such heterogeneity is found. Instead, policy formulation should explicitly consider relevant differences in local conditions.     

基于GWR模型的合肥居住地价影响因素研究

以合肥市主城区为例,基于2010-2014年居住用地的出让数据,运用地统计法、GWR模型等方法,对合肥市居住地价的空间异质性及其影响因素进行研究。研究表明：①合肥市居住地价的空间分布呈现出显著的多中心的空间结构,地价的峰值区分别以老城区、政务区天鹅湖及滨湖新区塘西河公园为中心呈现圈层式分布;②不同的地价影响因素表现出不同的空间分布特征,其中容积率对居住地价的贡献度空间差异最大,其次是宗地面积,主干路次之,交通站点对居住地价的贡献度最小;③厘清各影响因素对地价的作用机制,建立动态的数字地价模型,不仅能促进土地资源的集约利用,重塑城市的空间结构,而且能为城市整体价值的发挥提供重要的理论支撑。