Large panels with common factors and spatial correlation

This paper considers methods for estimating the slope coefficients in large panel data models that are robust to the presence of various forms of error cross-section dependence. It introduces a general framework where error cross-section dependence may arise because of unobserved common effects and/or error spill-over effects due to spatial or other forms of local dependencies. Initially, this paper focuses on a panel regression model where the idiosyncratic errors are spatially dependent and possibly serially correlated, and derives the asymptotic distributions of the mean group and pooled estimators under heterogeneous and homogeneous slope coefficients, and for these estimators proposes non-parametric variance matrix estimators. The paper then considers the more general case of a panel data model with a multifactor error structure and spatial error correlations. Under this framework, the Common Correlated Effects (CCE) estimator, recently advanced by Pesaran (2006), continues to yield estimates of the slope coefficients that are consistent and asymptotically normal. Small sample properties of the estimators under various patterns of cross-section dependence, including spatial forms, are investigated by Monte Carlo experiments. Results show that the CCE approach works well in the presence of weak and/or strong cross-sectionally correlated errors.     

Spatial stochastic frontier models: controlling spatial global and local heterogeneity

In the last decade special attention has been focused on estimating a firm’s efficiency and productivity; Stochastic Frontier Analysis (SFA) has been one of the most used techniques that allows the separation of inefficiency from stochastic noise, assuming homogeneous technology is available to all producers and that there is independence between observations. However, this second assumption is violated data are spatial auto-correlated, thus biasing statistical inference. Attention has, therefore, shifted to models that allow the controlling of heterogeneity introducing, in the model or in the error term, contextual variables correlated with inefficiency. In our paper we propose viewing the spatial external factors (natural or artificial) in a new way: instead of identifying ex-ante a multitude of determinants, often statistically and economically difficult to detect, we suggested using an original methodology that, following a classical SFA approach, splits efficiency into three components: the first one is linked to the spatial lag, the second one to the DMU’s specificities, and the third to the error term. Finally, we tested our method using simulated data and examined the Italian wine sector, testing the ability to control spatial, global and local heterogeneity.     

Enabling and inhibiting factors in adoption of Electronic-Reverse auctions: A longitudinal case study in grocery retailing

Abstract

The paper aims to explore the factors that enable or inhibit the use of Electronic-Reverse Auctions (E-RAs) in the buying process of a large food retail organization, through a category management perspective. Using a case-study analysis based on in-depth interviews, examination of internal documents, simulation and direct observation of some E-RAs, we studied the experience of an Italian-based retailer conducting E-RAs during a two-year period. This approach enabled us to propose an E-RAs development model in retail buying groups, discussing enabling and inhibiting factors such as product, market, organizational and strategic factors. Propositions are developed to stimulate thought and provide guidance for future research.     

Option Pricing in Stochastic Volatility Models of the Ornstein-Uhlenbeck type

Stochastic volatility models of the Ornstein-Uhlenbeck type possess authentic capability of capturing some stylized features of financial time series. In this work we investigate this class of models from the viewpoint of derivative asset analysis. We discuss topics related to the incompleteness of this type of markets. In particular, for structure preserving martingale measures, we derive the price of simple European-style contracts in closed form. Furthermore, the range of viable prices is determined and an empirical application is presented.     

The physics of the city: pedestrians dynamics and crowding panic equation in Venezia

In this paper we present the physics of the city, a new approach in order to investigate the urban dynamics. In particular we focus on the citizens’ mobility observation and modeling. Being in principle the social dynamics not directly observable, our main idea is that observing the human mobility processes we can deduce some features and characteristics of social dynamics. We define the automata gas paradigm and we write a crowding equation able to predict, in a statistical sense, the threshold between a selforganized crowd and a chaotic one, which we interpret as the emergence of a possible panic scenario. We show also some specific results obtained on the Venezia pedestrian network. Firstly, analyzing the network we estimate the Venice complexity, secondly measuring the pedestrian flow on some bridges we find significant statistical correlations, and by the experimental data we design two different bridges flow profiles depending from the pedestrian populations. Furthermore considering a reduced portion of the city, i.e. Punta della Dogana, we build up a theoretical model via a Markov approach, with a stationary state solution. Finally implementing some individual characteristics of pedestrians, we simulate the flows finding a good agreement with the empirical distributions. We underline that these results can be the basis to construct an E-governance mobility system.     

A multivariate jump-driven financial asset model

We discuss a Lévy multivariate model for financial assets which incorporates jumps, skewness, kurtosis and stochastic volatility. We use it to describe the behaviour of a series of stocks or indexes and to study a multi-firm, value-based default model. Starting from an independent Brownian world, we introduce jumps and other deviations from normality, including non-Gaussian dependence. We use a stochastic time-change technique and provide the details for a Gamma change. The main feature of the model is the fact that—opposite to other, non-jointly Gaussian settings—its risk-neutral dependence can be calibrated from univariate derivative prices, providing a surprisingly good fit.     

An integrated production–distribution model for the dynamic location and allocation problem with safety stock optimization

The design and management of a multi-stage production–distribution system is one of the most critical problems in logistics and in facility management. Companies need to be able to evaluate and design different configurations for their logistic networks as quickly as possible. This means coordinating the entire supply chain effectively in order to minimize costs and simultaneously optimize facilities location, the allocation of customer demand to production/distribution centers, the inbound and outbound transportation activities, the product flows between production and/or warehousing facilities, the reverse logistics activities, etc.Full optimization of supply chain is achieved by integrating strategic, tactical, and operational decision-making in terms of the design, management, and control of activities. The cost-based and mixed-integer programming model presented in this study has been developed to support management in making the following decisions: the number of facilities (e.g. warehousing systems, distribution centers), the choice of their locations and the assignment of customer demand to them, and also incorporate tactical decisions regarding inventory control, production rates, and service-level determination in a stochastic environment. This paper presents an original model for the dynamic location–allocation problem with control of customer service level and safety stock optimization. An experimental analysis identifies the most critical factors affecting the logistics cost, and to finish, an industrial application is illustrated demonstrating the effectiveness of the proposed optimization approach.     

From Consolidation to Segment Reporting in Local Government： Accountability Needs,Accounting Standards,and the Effect on Decision-Makers

Consolidated Financial Statements （CFSs） in the public sector represent useful financial tools to improve transparency and accountability toward internal and external users. This aggregate view is only a part of the information needed in order to give politicians, managers, employees, financial institutions, rating agencies, and citizens a whole view of a local government＇s financial performance. It emerges the need to have segment information, covering specific policy areas for which it is appropriate to separately report financial and non-financial information. This paper, after having discussed the need for accountability and decision-making in a theoretical framework, gives account of a pilot project realized by the municipality of Reggio Emilia, which introduced CFSs and segment reporting. The empirical study is based on an action research as a methodological approach to solving practical problems. Finally, the paper also offers some practical suggestions to contribute to the applicability of the segment reporting in the public sector.     

A new perspective on dynamic portfolio policies

The paper starts from the preceeding paper by L. Peccati in this issue. The original model is enriched with corporate taxes and reinvestment possibilities.The decomposition of NPV is used to study an optimal dynamic reinvestment policy.A generalization of the model is outlined and a numerical example is provided in an appendix.     

Rovina,assicurazione e scambi di attività finanziarie

Viene fornita la soluzione in forma chiusa di un problema di ottimizzazione dinamica stocastica, consistente nella scelta ottimale tra consumo e risparmio e nella composizione ottimale di portafoglio, in presenza di possibilità di rovina assicurabile.Dal punto di vista della teoria assicurativa, il lavoro amplia alcuni modelli recenti sull'assicurazione ottima, poiché segue un approccio del tipo «equilibrio generale» con due tipi di agenti eterogenei anziché parziale.Dal punto di vista della teoria di portafoglio, esso si discosta dai modelli tradizionali perché giustifica l'esistenza di scambi sui mercati finanziari e ne spiega l'entità.In questo senso il lavoro amplia alcuni contributi recenti sui flussi di capitale includendovi la possibilità di rovina e l'esistenza di una assicurazione contro di essa.

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Summary This paper provides an analytical solution for a multiperiod stochastic optimization problem, namely consumption and portfolio choice with partial risk insurance.An opposed to some recent optimal-insurance models a general-equilibrium approach —with two classes of heterogeneous agents—is adopted.Furthermore, the paper departs from traditional portfolio analysis in that it emphasises the dynamics of financial markets and justifies the existence of market trading.In this sense, it widens some recent general-equilibrium results on capital flows by including bankruptcy risk and insurance.