Modeling regional economic dynamics: Spatial dependence,spatial heterogeneity and nonlinearities

Spatial modeling of economic phenomena requires the adoption of complex econometric tools, which allow us to deal with important methodological issues, such as spatial dependence, spatial unobserved heterogeneity and nonlinearities. In this paper we describe some recently developed econometric approaches (i.e. Spatial Autoregressive Semiparametric Geoadditive Models), which address the three issues simultaneously. We also illustrate the relative performance of these methods with an application to the case of house prices in the Lucas County.     

道德哲学视域下的关公崇拜

在中国传统民间信仰之中,关公崇拜是俗文化兴起的产物,是社会道德情感社会潜意识孕育产生的一个道德模范,经典的三国演义为关公崇拜提供了有力的文本支撑,历代统治者的推波助澜也为这种崇拜发展起了重要作用。同时,关公崇拜背后有着深厚的道德内涵和社会价值,它所推崇的"义"是一种超越传统血亲关系的品德。这种品德即使在今天的商业社会也有着其存在发展的土壤,这也是关公崇拜得以延续至今的重要原因。     

Tales from tails: On the empirical distributions of forecasting errors and their implication to risk

When evaluating the performances of time series extrapolation methods, both researchers and practitioners typically focus on the average or median performance according to some specific error metric, such as the absolute error or the absolute percentage error. However, from a risk-assessment point of view, it is far more important to evaluate the distributions of such errors, and especially their tails. For instance, a lack of normality and symmetry in error distributions can have significant implications for decision making, such as in stock control. Moreover, frequently these distributions can only be constructed empirically, as they may be the result of a computationally-intensive non-parametric approach, such as an artificial neural network. This study proposes an approach for evaluating the empirical distributions of forecasting methods and uses it to assess eleven popular time series extrapolation approaches across two different datasets (M3 and ForeDeCk). The results highlight some very interesting tales from the tails.     

Steady state adjusting trends using a data-driven local polynomial regression

Economic variables usually follow a dynamic trend pattern. However, it is difficult to estimate this trend precisely as numerous economically- and statistically-based estimation methods exist. This contribution proposes a data-driven nonparametric trend that is local polynomial, to improve arbitrary trend estimations of commonly used methods concerning the selection of the smoothing parameter and the dependence structure. An iterative plug-in (IPI) algorithm determines the bandwidth endogenously and allows a theory-based interpretation of the length of growth processes. This length of the bandwidth reflects the lengths of the steady state periods. Consequently, the bandwidth identifies the time period of stable economic conditions and can detect economic changes. To demonstrate the power of this estimation approach, an extensive simulation study is performed. Furthermore, examples using US and UK GDP data along with a guide for the optimal choice of algorithms for empirical applications are provided. This proposed method yields new insights for growth dynamics, cyclical movements and their dependence.     

Pricing executive stock options with averaging features under the Heston–Nandi GARCH model

In this paper, we focus on the pricing issue of four types of executive stock options (ESOs) in the Heston–Nandi generalized autoregressive conditional heteroskedasticity option pricing model. Based on the derived benchmark strike prices in the proposed framework, we obtain the closed-form pricing formulae for four types of ESOs. In the numerical part, we investigate the sensitivity and cost efficiency of ESOs and suggest that systematic risk (stock β) and the fraction of wealth invested in restricted stock could impede the cost efficiency of ESOs.     

Modelo de gestión logística para pequeñas y medianas empresas en México

The market opening and the globalization of supply chains, demand a structural changes in which logistics has a strategic role. Nowadays, clients evaluate product quality, its value added and its availability in time and form, which implies a need to make the process efficient. Several experts have proposed some logistics management models to increase competitiveness in the market, but some of these models are too ambitious for small and medium sized enterprises (SMEs) due to their informal structure and their lack of technical knowledge; other models make indirect reference to the internal information flows, which include whole system disintegration because of the weak interrelation among the different areas. In Mexico, SMEs represent 4.2%, they generate 31.5% of employment and provide 37% of the gross domestic product; that is why it is important to reinforce their competitive position in the market. This research presents the design of a conceptual model of logistic management for SMEs which could provide comprehensive solution through control of the variables involved in the logistics process; to verify that the variables considered in each identified dimension are correct factor analysis was used.     

Are the kinship networks a resource or a curse for small firms in post-communist countries? The case of Albania

Cross-sectional data are compiled from the 2002, 2005, 2008 and 2012 World Bank Living Standards Measurement Study databases for Albania. Based on responses from 1169 firms, the entrepreneurs’ kinship networks are found to influence firm activity in a positive and negative way. The positive contribution occurs through employment, be it formal or informal. The persisting impact of the kinship networks fades away, and business and friendship networks have gained importance in recent years.     

Using quantitative influence diagrams to map natural resource managers’ mental models of invasive species management

Despite the significant effect that invasive species have on natural values, the number and extent of invasions continue to rise globally. At least three dominant reasons explain why policy development and implementation can fail: differences in managers’ mental models of invasive species management; cross-agency responsibility; and poor planning and management (i.e., planning–implementation gap). We used a case study of cross-agency management of gamba grass (Andropogon gayanus) in Australia to explore the differences in organizational staffs’ mental models of management. The gamba grass invasion in northern Australia is continuing to expand and associated effects are increasing; coordinated action across agencies is needed to manage the expansion. Our aim was to examine how staff would represent their mental models as a diagram that we could compare between individuals and groups. We used cognitive mapping techniques to elicit models of 15 individuals from across 5 organizations, represented as an influence diagram, which shows the interrelationships that define a system. We compiled the individual influence diagrams to create a team model of management that captures the common connections across participants’ diagrams. The team model revealed that education, science, legislation, enforcement and property management plans were perceived to be the most important management tools to control or eradicate gamba grass. The Weed Management Branch was perceived to have the most central role in gamba grass management, while other organizations were perceived to have specific roles according to their core business. Significant positive correlations (i.e., shared perceptions) were observed across half of the participants, indicating that the some participants have shared models that could be used as a starting point for discussing the team model, clarifying roles and responsibilities, and potentially building consensus around a shared model. Dominant opportunities for improvement identified by participants were better use of management tools, namely education and enforcement, better coordination and collaboration between agencies and increased resourcing. Our research demonstrates the value and validity of using influence diagrams to explore managers’ mental models and to create a team model that could serve as a starting point for improved cross-agency natural resource management.