Energy price reform and food markets: the case of bread supply chain in Iran

Reforming energy price is the core of Iranian economic reform plan during 2010–2014. However, increasing price of energy may have adverse effects on the agricultural and food markets. This study was conducted to address these problems in the most important food of Iranian people “bread” by developing a spatial supply chain model. Results show that consumers’ welfare would experience a sharp decrease though the impacts on farmers are trivial. Also, results indicate that the key to success the reform without political backlash in the short‐run is the cash transfer program under which the government redistributes part of the reform's benefits among consumers. Per capita compensation payments would be equal to 51.50 and 46.09 US$ per year for a typical rural and urban person, respectively. Moreover, the results provide more detailed information about the market characteristics and the payments both in nationwide and regional scale as well as in different income groups.     

Spatial decomposition analysis of water intensity in China

The shortage of water resources has become a burning issue constraining China's sustained development with significant differences in water intensity among regions and provinces. Quantifying the driving effect of spatial differences in the country's water intensity is very important to the dual implementation actions of water resources and intensity in each region. Spatial analysis reveals the variations among regions, identifies contributing factors, and helps us to better understand the scope for improvement compared to temporal analysis. This paper constructs a Spatial Index Decomposition Analysis (S-IDA) model based on the conventional IDA model referenced in the literature and divides China into six regions according to The 13th Five-Year Plan of Water-Saving Society Construction. We mainly examine the following four parts. First, the driving factors of the spatial difference of water intensity in the six regions are decomposed into intensity effect and structure effect. Second, we measure three industrial differences of the intensity effect and the structure effect in the six regions. Third, we decompose the drivers of the spatial differences of water intensity for provinces within the six regions into the intensity effect and the structure effect. Fourth, we select the results in 2015 to point out the key task of reducing water intensity in the six regions and in all provinces of those regions. The results underscore that each region should formulate and implement a sound water resource policy with differentiation and relevance according to actual conditions and provide a quantitative basis and support system so that regions can learn from each other about specific water-saving measures. These findings provide an insightful understanding of the spatial difference of water intensity and also a quantifiable justification for making building-specific water resources policies, which are discussed at the end of the study.     

Optimal compatibility in systems markets

We investigate private and social incentives for standardization to ensure market-wide system compatibility in a two-dimensional spatial competition model. We develop a new methodology to analyze competition on a torus and show that there is a fundamental conflict of interests between consumers and producers over the standardization decision. Consumers prefer standardization with full compatibility because it offers more variety that confers a better match with their ideal specifications. However, firms are likely to choose the minimal compatibility to maximize product differentiation and soften competition. This is in sharp contrast to the previous literature that shows the alignment of private and social incentives for compatibility.     

How the spatial dispersion and size of country networks shape the geographic distance that firms add during international expansion

This study looks at the geographic distance that multinational enterprises add beyond the confines of their existing country network when they expand internationally. It remains unclear why we observe great variation in the amounts of geographic distance that firms add to their country networks even when they operate in similar industries and face comparable challenges in overcoming physical distance. Drawing on experiential learning theories and the literature on subsidiary network management, I argue that it is important to consider their geographic expansion decisions in relation to the firm-level spatial dispersion of country networks and the size of that network. Using Tobit models to analyse panel data that capture the expansion patterns of 217 large retailers from 26 countries over a seven year period, this study reveals that such firms add higher levels of geographic distance when they have experience in dealing with large networks and greater degrees of dispersion, but limit the distance added when both of these network characteristics need to be combined. The important finding that spatial network dispersion has divergent effects on added geographic distance, dependent on whether it is considered in isolation or together with network size, sheds interesting new light on firms’ international expansion decisions, and informs IB scholars as well as economic geographers.     

Choice sets for spatial discrete choice models in data rich environments

Failure to properly specify an agent's choice set in discrete choice models will generate biased parameter estimates resulting in inaccurate behavioral predictions as well as biased estimates of policy relevant metrics. We propose a method of constructing choice sets by sampling from specific points in space to model agent behavior when choice alternatives are unknown to the researcher, potentially infinite, and differ according to spatial and temporal factors. Using Monte Carlo analysis we compare the performance of this point-based sampling method to the commonly used approach of spatially aggregating choice alternatives. We then apply these alternative approaches to modelling location choice in the Pacific groundfish trawl fishery which has a complex spatial choice structure. Both the Monte Carlo and application results provide considerable support for the efficacy of the point-based approaches.     

Scenario farmland protection zoning based on production potential: A case study in China

Establishing farmland protection areas is an important measure for developing countries to protect limited farmland resources and guarantee food security. The general approaches lack the ability to simulate the farmlands’ production potential under different scenarios. This paper proposes a modified farmland protection zoning framework to demarcate farmland protection by coupling the Agro-Ecological Zone (AEZ) model with a state-of-the-art farmland protection zoning framework. The modified zoning framework was applied to China, a typical fast developing country. The results indicated that the average potential production of the entire country would increase by 2.96 % in the coming decade if the irrigation efficiency criteria of 55 % established by the National Program for Agricultural Water Conservation (2012–2020) can be fulfilled. Furthermore, the farmland protection area could also be reduced by 2.91 % (2.96 million ha) while the total production potential of the protected areas would remain unchanged. This study contributes two main aspects: (1) The AEZ model was used as a replacement for the general land-use suitability analysis (LUSA) or multi-criteria evaluation (MCE) based farmland assessment models in a farmland zoning framework, which can accurately assess the production potential of the farmland protection demarcation. (2) This farmland protection zoning approach can analyze and simulate a wide range of scenarios on the effect of environmental factors (climate, soil, terrain, etc.) and human production factors (irrigation condition, cropping system, etc.).     

Dynamic Spatial Discrete Choice Using One-step GMM: An Application to Mine Operating Decisions

Abstract

In many spatial applications, agents make discrete choices (e.g. operating or product-line decisions), and applied researchers need econometric techniques that enable them to model such situations. Unfortunately, however, most discrete-choice estimators are invalid when variables and/or errors are spatially dependent. More generally, discrete-choice estimators have difficulty dealing with many common problems such as heteroskedasticity, endogeneity, and measurement error, which render them inconsistent, as well as the inclusion of fixed effects in short panels, which renders them computationally burdensome if not infeasible. In this paper, we introduce a new estimator that can be used to overcome many of the above-mentioned problems. In particular, we show that the one-step (‘continuous updating’) GMM estimator is consistent and asymptotically normal under weak conditions that allow for generic spatial and time series dependence. We use our estimator to study mine operating decisions in a real-options context. To anticipate, we find little support for the real-options model. Instead, the data are found to be more consistent with a conventional mean/variance utility model.

RÉSUMÉ

Choix Discret Dynamique et Spatial: utiliser le GMM à une étape: Application aux Décisions Opérationnelles dans le Secteur Minier

Dans beaucoup d'applications spatiales, les agents font des choix discrets (c'est –à- dire prennent des décisions opérationnelles ou des décisions de production). La recherche appliquée a besoin de techniques économétriques pour modéliser ces situations. Malheureusement, la plupart des indicateurs de choix discret ne signifient rien, lorsque les variables et /ou les erreurs sont spatialement dépendantes. Plus généralement, les indicateurs de choix discret ne gèrent que difficilement la plupart des problèmes rencontrés couramment, comme l'hétéroscédasticité, l'endogénéité et les erreurs de mesure, ce qui les vide de leur sens. Il en est de même avec l'inclusion d'effets fixes dans des panels courts, qui les rend mathématiquement très lourds, si ce n'est irréalisables. Dans cet article, nous introduisons un nouvel indicateur qui peut surmonter les difficultés mentionnées plus haut. En particulier, nous montrons que l'indicateur du GMM à une étape (mise à jour continue) fonctionne et qu'il est normal de façon asymptotique, dans des conditions faibles, qui permettent de rendre dépendantes des séries spatialement et temporellement génériques. Nous utilisons notre indicateur pour étudier les décisions opérationnelles dans le secteur minier dans un contexte d'options réelles. Pour anticiper, nous avons trouvé peu d'arguments en faveur du modèle d'options réelles.Donc, les donnée sont plus parlantes avec un modèle d'utilité conventionelle moyenne/variance.

RESUMEN

Opción discreta espacial dinámica usando el método MGM de un paso: una aplicación a las decisiones operativas en las minas

En muchas aplicaciones espaciales, los agentes optan por elecciones discretas (ej., en las decisiones sobre operaciones o la producción en línea), y para la investigación aplicada se necesitan técnicas econométricas para poder modelar tales situaciones. Por desgracia, la mayoría de los estimadores de elecciones discretas no son válidos cuando las variables, los errores, o ambos, tienen una dependencia espacial. En general, los estimadores de elecciones discretas tienen dificultades para tratar con diferentes problemas tales como la heteroscedasticidad, la endogeneidad, y el error de medición que hacen que sean inconsistentes, así como la inclusión de efectos fijos en paneles cortos que resultan onerosos e incluso imposibles de calcular. En este artículo introducimos un nuevo estimador que puede servir para superar muchos de los problemas antes mentionados. En concreto, demonstramos que el estimador MGM (Método Generalizado de Momentos) de un paso (‘actualización continua’) es consistente y asintóticamente normal en condiciones débiles que permiten una dependencia genérica espacial y temporal. Utilizamos nuesto estimador para estudiar las decisiones operativas en las minas en un contexto de opciones reales. Anticipamos que hallamos poca evidencia a favor del modelo de opciones reales. En cambio, los datos son más consistentes con un modelo de utilidad convencional de media/varianza.     

Home bias in multimarket Cournot games

We explore the role of trade costs for the home bias in trade. In a series of Cournot duopoly experiments with a home and an export market, we compare output choices when firms face different levels of trade costs. We find that there is two-way trade in identical products and that firms hold the majority market share in their home market. The resulting home bias turns out to be, however, stronger than that predicted by theory, and it even occurs without trade costs. Tacit collusion contributes to the home bias observed in our experiment but does not offer a full explanation for the phenomenon.     

How do neighboring peer companies influence SMEs’ financial behavior?

Recent research into corporate finances has found that the financial decisions of peer companies are related. Companies tend to “kept an eye” on the decisions of other peer companies, among other things, trying to overcome the limitations caused by the lack of information. This paper further examines these interactions including geographical proximity among companies. With this aim, we use a heterogeneous Partial Adjustment Model on a sample of 12,444 small and medium Spanish manufacturing industrial companies. We find strong nonlinearities in the adjustment processes of liquidity, indebtedness and profitability ratios associated with basic characteristics of the companies such as size, technology, age or financial imbalances. Our results indicate that the influence of the environment on the financial behavior of each company, and its responsiveness, vary in function of neighbor firms’ characteristics.     

Increasing the resilience of air traffic networks using a network graph theory approach

Air traffic networks are essential to today’s global society. They are the fastest means of transporting physical goods and people and are a major contributor to the globalisation of the world’s economy. This increasing reliance requires these networks to have high resilience; however, previous events show that they can be susceptible to natural hazards. We assess two strategies to improve the resilience of air traffic networks and show an adaptive reconfiguration strategy is superior to a permanent re-routing solution. We find that, if traffic networks have fixed air routes, the geographical location of airports leaves them vulnerable to spatial hazard.