Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.     

The geography of suppliers and retailers

In the last decades, supply chains have increasingly transcended national boundaries developing into global supply chains. Along with the many opportunities arising from international sourcing and the extended commercial presence over the world, the management of a globally dispersed supply chain is highly complex. A key issue to consider when dealing with the global supply chain design is the location of facilities, not only with respect to firms' owned facilities but also the supply and distribution side as factors that affect supply chain complexity and operational performance. This paper sets out a methodological framework to characterize the geographical configuration of a firm's suppliers and retailer networks. Quantitative indexes of network spatial concentration and relative proximity measures based on a nonparametric kernel density estimator are developed to identify both intra- and inter-firm patterns between the supply and point of sales' distributions. The method is first described by means of a series of theoretical-illustrative examples and exemplified by analyzing the geographical dispersion of four practical cases from the fashion-textile industry (i.e., Adidas, Benetton, C&A, and Puma). Subsequently, managerial implications and potential use of the metrics are discussed, showing how the proposed approach can support researchers and practitioners to improve supply chain location decisions and logistic integration, and evaluate changes in either the purchasing or distribution strategy.     

Relationship between city size and firm productivity – A new interpretation using the Chinese experience

This paper contributes to the literature on the relationship between city size and firm productivity by focusing on agglomeration, selection (market competition), and sorting (presence of firms with diverse productivity) effects using Chinese firm-level data for 1998–2013. Contrary to the existing literature, our parametric regression estimates from nearly two million firms show that when the selection effect is controlled, productivity advantage in big cities is reversed. This outcome is explained through a quantile regression showing the existence of left-sided sorting (inefficient firms sort themselves to larger cities) in big cities which is not captured in existing empirical literature. We further find that (1) left-sided sorting is stronger in exporters than non-exporters; (2) is also generated mainly in enterprises with high asset-liability ratios; and (3) selection has a positive effect on firm productivity, suggesting that market competition is key in an explanation of the rapid growth of big cities in China.     

Spatial and operational factors behind passenger yield of U.S. nonhub primary airports

Nonhub airports are an essential component in the National Plan of Integrated Airport Systems (NPIAS) of the United States in that they connect regional towns and small communities to the air transportation network. Understanding the interplay of operational and spatial factors in determining average passenger yield of nonhub airports provides airlines with valuable information for network planning and revenue management. This study examines factors contributing to the yield variation among nonhub airports in the U.S. Using ordinary least squares (OLS) based econometric models, this study captures the spatial dependence of passenger yield of nonhub airports, which tends to increase with a corresponding increase in distance to the nearest large hub airport. Nonhub airports surrounding large hub airports with higher passenger enplanements and higher average yields also have higher yields than other nonhub airports. In addition, this study finds the effect of Allegiant Airlines in lowering the average passenger yield of the nonhub airports served directly by the airline, which can be termed as ‘Allegiant Effect’. Findings of this study could provide valuable guidance for airlines to analyze network planning strategies and to identify future markets for growth and for policymakers when allocating resources to communities relying on these nonhub airports.     

Closeness matters. Spatial autocorrelation and relationship between socioeconomic indices and distance to departmental Colombian capitals

Socioeconomic indices that developing economies use to combat poverty may show a limited picture of all the variables related to the problem. This study analyzes spatial autocorrelation and clusters of three socioeconomic indices—living conditions, multidimensional poverty, and unsatisfied basic needs—in Colombia to explore the relation of the identified clusters with their physical distance from departmental capitals. Using a local index of spatial autocorrelation, it evaluates spatial patterns and the clustering of socioeconomic indices. Correlation analysis tests the relation between clusters and their distance from departmental capitals in three departments. The spatial patterns of indices in Colombia correspond to the model of economic development in the country and reveal the regions where socioeconomic characteristics form clusters of desirable/undesirable conditions and departments where the distance from main cities may be seen as a condition for a higher quality of life.     

Negotiating climate change responses: Regional and local perspectives on transport and coastal zone planning in South Sweden

Putting climate change policy-integration into practice is challenged by problems of institutional misfit, due to, inter alia, deficient vertical administrative interplay. While most focus within the field of climate change research has targeted the national–local interplay, less is known about the interface of regional and local perspectives. Here, the aim is to study that interface with a specific focus on the relation between regional and local spatial planning actors, through a case-study of transport and coastal zone management in a Swedish municipality. The article is based on interviews (focus group and single in-depth) and official planning documents. The material reveals a tricky planning situation, replete with conflict. In practice, various institutional frameworks, claims and ambitions collide. The attempts to steer the local spatial planning initiatives from the regional level led to conflicts, which in turn seems to have hampered the overall work for climate change management through spatial planning. Furthermore, there are few traces of prospects of a smooth vertical institutional interplay able to support the overall aims related to integrating climate change mitigation and adaptation in spatial planning.     

Implementing efficient conservation portfolio design

Modern tools for cost-effective conservation reserve site planning require the planner to have information about spatial distributions of conservation costs and benefits. Climate change creates unprecedented uncertainty about future land values and species habitat ranges, such that conservation scientists cannot map costs and benefits with certainty anymore. This paper contributes to the literature on the economics of conservation in the face of climate change uncertainty. It advances a new method for using modern portfolio theory to choose lands to protect that yield total conservation returns with less uncertainty. It explores the implications for portfolio recommendations of variation in the correlations between ecological and land-value responses to climate change. It also tests the robustness of the method to shortcuts that might be taken to simplify analysis, identifying problems that arise if conservation costs are ignored in portfolio analysis and demonstrating when portfolio recommendations are sensitive to how ecological benefits are quantified.     

The impact of flood dynamics on property values

There is evidence that environmental amenities and dis-amenities may be nonlinearly related to property valuation. This would bring inconsistency in estimating environmental variables of the hedonic price model. To explore the linearity of the relationship this study analyses spatial and temporal variation impacts of the 2011 Brisbane flood on property markets using semi-parametric estimation. The results show that most environmental variables impacts on property values nonlinearly, and in particularly distance to the river, indicating that the amenity value of being close to a river outweighs the flood risks. The estimation of the combined impact of elapsed time and neighbourhood income indicates that the flood risk impact on property markets disappears over time.     

House price determinants in Athens: a spatial econometric approach

In this paper, we try to identify the price determinants in the biggest real estate market of Greece, the metropolitan area of Athens. For that purpose, various spatial econometric models are used to explore their prediction ability and we are displaying the variations in property prices for the wider area of Athens. These models have been compared based on different criteria such as model fit, the Akaike information criterion and variance of the residuals. Our results indicate that, in our case, the spatial general model is the most appropriate simultaneous autoregressive model when dealing with spatially autocorrelated prices of housing properties data, in terms of our selection criteria.     

The influence of neighborhood environment and household travel interactions on school travel behavior: an exploration using geographically-weighted models

Professional and popular interest in active school transportation (walking and cycling) is matched by an emerging literature on this topic. This paper explores school travel behavior of 11-year old children in Toronto, Canada. In particular, the effects of the neighborhood environment and caregiver-child travel interactions on travel mode choice were studied. Results indicate that the built environment near both home and school locations was associated with the odds of walking. However, predicted built environment effects were less accurate in some neighborhoods. Availability of adults at the time of school travel likely encouraged driving. School transportation interventions that broadly consider school and neighborhood-oriented policies and enable independent mobility may increase walking rates. Presence of spatial autocorrelation in the prevalence of walking suggests that more research is required to understand inter-household similarities in behaviors that are spatially structured.