State‐Led Financial Regulation and Representations of Spatial Fixity: The Example of the Spanish Real Estate Sector

This article offers a bottom‐up contribution to the fixity–motion literature. It aims to unravel the apparent contradiction of real estate spatial fixity in Spain, which is portrayed both as a barrier to accumulation and as a unique source of investment by different capitalist actors. Empirically, it describes the shifts in real estate ownership and changes in profit‐making strategies that have taken place across the real estate sector during the crisis years, and the role of the state in these shifts. The article asserts that the idea of spatial fixity representing a spatial barrier for accumulation does not necessarily apply in the Spanish case. It further claims that the tensions in capital circulation through real estate are not only to be found in the action of time, but in different state strategies pursued by various actors. The opposing representations of fixity are the result of state regulation of interest rates, taxation and risk weighting. The state also increasingly promotes land rents as a source of liquidity creation.     

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.     

Size of nested cities

Models of cities based on conventional spatial market theory are unable to replicate a realistic size distribution. The stochastic process approach to size distribution, which assumes proportionate growth, does not provide an economic foundation for spatial trades. There is an apparent irreconcilability. We propose that since there is a continuum of equilibria in models of spatial markets with endogenous location, proportionate growth can work as equilibrium selection. We present computations for an urban configuration that has not been presented in the literature before. A small city locates inside a larger city's agricultural supply zone. This generates a larger variation in city size that may include a realistic size distribution.     

Integrating uncertain user-generated demand data when locating facilities for disaster response commodity distribution

This paper presents a new facility location problem variant with application in disaster relief. The problem is unique in that both verified data and unverified user-generated data are available for consideration during decision making. The problem is motivated by the recent need of integrating unverified social data (e.g., Twitter posts) with data from more traditional sources, such as on-the-ground assessments and aerial flyovers, to make optimal decisions during disaster relief. Integrating social data can enable identifying larger numbers of needs in shorter amounts of time, but because the information is unverified, some of it may be inaccurate. This paper seeks to provide a “proof of concept” illustrating how the unverified social data may be exploited. To do so, a framework for incorporating uncertain user-generated data when locating Points of Distribution (PODs) for disaster relief is presented. Then, three decision strategies that differ in how the uncertain data is considered are defined. Finally, the framework and decision strategies are demonstrated via a small computational study to illustrate the benefits user-generated data may afford across a variety of disaster scenarios.     

Past price ‘memory’ in the housing market: testing the performance of different spatio-temporal specifications

Recent methodological developments provide a way to incorporate the temporal dimension when accounting for spatial effects in hedonic pricing. Weight matrices should decompose the spatial effects into two distinct components: bidirectional contemporaneous spatial connections; and unidirectional spatio-temporal effects from past transactions. Our iterative estimation approach explicitly analyses the role of time in price determination. The results show that both spatio-temporal components should be included in model specification; past transaction information stops contributing to price determination after eight months; and limited temporal friction is exhibited within this period. These findings highlight the decidedly non-linear temporal patterns of such information effects.     

A Kaleckian Perspective on Financialisation and Distribution in Three Main Eurozone Countries before and after the Crisis: France,Germany and Spain

The purpose of this article is twofold. First, we examine if, and to what extent, a general Kaleckian analysis of the potential effects of financialisation on income shares in advanced capitalist economies is of relevance for the three Eurozone countries under investigation—France, Germany and Spain—in the period before the recent financial and economic crisis. Second, we study changes in the financialisation–distribution nexus that have occurred in the course of and after the financial and economic crisis. We find that the countries examined here have shown broad similarities regarding redistribution before the crisis, although there are some differences in the underlying determinants. These differences have continued during the period after the crisis and have led to different results in the development of distribution since then.     

普惠金融与县域资金外流：减贫还是致贫*——基于中国592个国家级贫困县的研究

本文利用全国592个国家级贫困县的数据，采用空间计量模型实证分析了普惠金融对县域资金外流的影响，并验证了贫困县资金外流是否会产生致贫效应。本文研究发现：如果普惠金融只注重解决贫困地区对金融机构的接触性排斥，会进一步加剧资金外流，对减贫产生负向影响，即存在显著的致贫效应。这种致贫效应具有明显的空间外溢性，邻近县域的贫困状况在很大程度上会彼此“传染”，并具有空间衰减特征的地理边界。因而需要客观认识普惠金融的本质，有针对性地选择恰当有效的实施载体，解决好对信贷产品等关键金融服务的使用性排斥问题。     

农村集体经营性建设用地流转模式再审视：基于产权让渡与市场化的视角

研究目的:厘清集体经营性建设用地流转模式,推进集体建设用地入市改革。研究方法:以产权让渡及市场化为视角,采用矩阵分类法划分集体经营性建设用地流转模式,剖析不同流转模式特征与演进路径。研究结果:基于本研究视角可将集体经营性建设用地流转划分为6种模式,不同模式具有不同特征、运行条件、优缺点及收益分配格局,且其存在关联并遵循一定的演进规律。研究结论:规范市场下农地发展权及使用权流转模式将是当前改革的方向,需从法律法规上明确农地发展权相关规定;不同地区需因地制宜地选择流转模式及类型,探索具体实施办法,循序渐进推进流转改革与创新。     

Pricing used books on Amazon.com: a spatial approach to price dispersion

This paper estimates a spatial autoregressive (SAR) model of price dispersion using publicly available internet bookselling data. It uses a semiparametric adaptive estimator that does not require the usual Gaussian assumption of maximum likelihood (ML) estimators. The results suggest that both price competition and seller heterogeneity are key drivers of the observed price dispersion. The paper finds that sellers with large sales volume, newly established sellers and US mainland states-based sellers tend to price lower. The identified significant spatial interaction is evidence of spatial price competition. Controlling for everything else, a seller asks a lower price when large sellers charge relatively high prices, which is also evidence of price-based selling and undercutting.     

Factor state–space models for high-dimensional realized covariance matrices of asset returns

We propose a dynamic factor state–space model for high-dimensional covariance matrices of asset returns. It makes use of observed risk factors and assumes that the latent integrated joint covariance matrix of the assets and the factors is observed through their realized covariance matrix with a Wishart measurement density. For the latent integrated covariance matrix of the assets we impose a strict factor structure allowing for dynamic variation in the covariance matrices of the factors and the residual components as well as in the factor loadings. This factor structure translates into a factorization of the Wishart measurement density which facilitates statistical inference based on simple Bayesian MCMC procedures making the approach scalable w.r.t. the number of assets. An empirical application to realized covariance matrices for 60 NYSE traded stocks using the Fama–French factors and sector-specific factors represented by Exchange Traded Funds (ETFs) shows that the model performs very well in- and out of sample.