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In this paper we present a model of rational voting over redistribution where individual self-esteem and relative esteem for others are endogenously determined. Individuals differ in their productivities, and their behaviour and political views are influenced by moral standards concerning work. Agents determine what they take to be proper behaviour and they judge others, and themselves, accordingly, increasing their esteem (or self-esteem) for those who perform in excess of the standard and decreasing their esteem for those who work less. The desired extent of redistribution depends both on individual income and on individual attitudes toward others. The model has two types of equilibria. In a cohesive equilibrium, all individuals conform to the standard of proper behaviour, income inequality is low and social esteem is not biased toward any particular type. Under these conditions equilibrium redistribution increases in response to larger inequality. In a clustered equilibrium skilled workers work above the mean while unskilled workers work below. In such an equilibrium, income inequality is large and sentiments are biased in favor of the industrious. As inequality increases, this bias may eventually overtake the egoistic demand for greater taxation and equilibrium redistribution decreases. The type of equilibrium to emerge crucially depends on inequality. We contrast the predictions of the model with data on inequality, redistribution, work values and attitudes toward work and toward the poor for a set of OECD countries

Public & private sector decision making is studied with an experiment. The study compares decision making in a tax-supported general purpose governmental agency with that done by a business firm selling to a market, using a simulation to capture differences in the preferences & practices of mid-level managers working in the two sectors. The simulation calls for participating managers to assess the risk & prospect of adopting budgets tailored to match each sector. A cognitive culture that stresses analysis, speculation, bargaining, or networking is employed to fashion a budget appropriate for a public & a private sector organization, each with a controversial & a noncontroversial budget amount. The literature on public/private differences was consulted to make predictions, suggesting that public sector managers would favor bargaining & networking & private sector managers would favor analysis & speculation. The cognitive style literature suggests that managers favor budgets constructed with an approach that is consistent with their preferred cognitive style & see less risk in the choice, except in a public setting where risk would be unaffected. The study finds that private sector managers are more apt to support budget decisions made with analysis & less likely to support them when bargaining is applied. Public sector managers are less likely to support budget decisions backed by analysis & more likely to support those that are derived from bargaining with agency people. Tables, Appendixes, References. Adapted from the source document.

The establishment and spread of invasive or nonindigenous species has caused concern from stakeholders in affected areas, and has prompted many field and modeling studies. We used stochastic two species, circular three patch dynamic models to investigate the patterns of invasion and impacts upon the affected species. Both persistent and degradable toxicants were incorporated as parts of the model system to act as disturbance regimens. There is a clear series of patterns that result from these simulations. Competition increases population variability, but decreases the number of distinct outcomes possible from the same initial conditions. Isolation of the patch of the introduction was the main determinant of successful establishment through a process we call the beachhead effect. Coexistence of species was often possible in local patches, contrary to the analytical solutions of Lotka‐Volterra equations and numerous modeling studies. Contaminants and their resultant disturbances are important as contributors to the stochastic nature of models. The stochasticity leads to a variety of outcomes from some sets of initial conditions. Different outcomes have different probabilities of occurrence and are dependent upon the specific initial conditions of the simulation. A clear pattern that is apparent is the "beachhead effect," where the invasive establishes a population within a relatively remote patch before migrating to the remainder of the landscape. We make predictions and provide specific research hypotheses as to the causes and effects of invasive species establishment, spread, and impacts.

Abstract. The HYDROPTIMET Project, Interreg IIIB EU program, is developed in the framework of the prediction and prevention of natural hazards related to severe hydro-meteorological events and aims to the optimisation of Hydro-Meteorological warning systems by the experimentation of new tools (such as numerical models) to be used operationally for risk assessment. The objects of the research are the mesoscale weather phenomena and the response of watersheds with size ranging from 102 to 103 km2. Non-hydrostatic meteorological models are used to catch such phenomena at a regional level focusing on the Quantitative Precipitation Forecast (QPF). Furthermore hydrological Quantitative Discharge Forecast (QDF) are performed by the simulation of run-off generation and flood propagation in the main rivers of the territory. In this way observed data and QPF are used, in a real-time configuration, for one-way forcing of the hydrological model that works operationally connected to the Piemonte Region Alert System. The main hydro-meteorological events that affected Piemonte Region in the last years are analysed, these are the HYDROPTIMET selected test cases of 14–18 November 2002 and 23–26 November 2002. The results obtained in terms of QPF and QDF offer a basis to evaluate the sensitivity of the whole hydro-meteorological chain to the uncertainties in the numerical simulations. Different configurations of non-hydrostatic meteorological models are also evaluated.

Abstract
Religion plays an important role in the lives of many Americans, but there is relatively little study by economists of the implications of religiosity for economic outcomes. This likely reflects the enormous difficulty inherent in separating the causal effects of religiosity from other factors that are correlated with outcomes. In this paper, I propose a potential solution to this long standing problem, by noting that a major determinant of religious participation is religious market density, or the share of the population in an area which is of an individual's religion. I make use of the fact that exogenous predictions of market density can be formed based on area ancestral mix. That is, I relate religious participation and economic outcomes to the correlation of the religious preference of one's own heritage with the religious preference of other heritages that share one's area. I use the General Social Survey (GSS) to model the impact of market density on church attendance, and micro-data from the 1990 Census to model the impact on economic outcomes. I find that a higher market density leads to a significantly increased level of religious participation, and as well to better outcomes according to several key economic indicators: higher levels of education and income, lower levels of welfare receipt and disability, higher levels of marriage, and lower levels of divorce.

This paper discusses the time-series cross-sectional (TSCS) regression and the prediction ability of the artificial neural network (ANN) by examining the panel data of debt ratios of the high tech industry in Taiwan. We build models with these two methods and eight determinants of debt ratio and compare the forecast performances of five models, two ANN nonlinear models and three traditional TSCS linear models. The results show that the sign of each determinant in linear models is the same as that in ANN models. In addition, the insignificant determinants in linear models have low relative sensitivities in ANN models. It seems that these two methods show consistent results for the capital structure determinants. Researchers and practitioners can employ either ANN or traditional statistical model to analyze the important determinants of the capital structure of their firms. The results of comparing the out-of-sample forecasting capabilities of the two methods indicate that: (1) the proposed ANN with 1-year lag model shows better forecast performance than the other three linear models in spite of high or low debt ratio; (2) the debt ratios of the present year are highly related to those of the previous year; and (3) the ANN model is capable of catching sophisticated nonlinear integration effects. Consequently, the ANN method is the more appropriate one between the two methods to be applied to build a forecasting model for the high tech industry in Taiwan.

We examine the role of particularistic relationships (such as family and prior social ties) in business groups during institutional transition and test how particularistic ties between top leaders affect business group performance in Taiwan, where such ties have been central to the functioning of business groups. We propose that during market-oriented transition, family and prior social ties could improve group performance by providing informal norms that strengthen the intermediation within business groups and that family relationships could reduce strategic restructuring and generate performance benefits. Results of a longitudinal study over 24 years show that market transition enhanced the contribution of family and prior social relationships but not that of common-identity relationships, such as being from the same hometown, which do not involve prior direct personal contact. We also found that during transition, the positive contribution of family members would rise up to a threshold, after which additional family members tended to derail group performance, possibly due to informational disadvantages and a legitimacy discount in the eyes of foreign investors. The study helps to make sense of different predictions about the role of particularistic ties in business group performance and makes an initial attempt at revealing how social structure affects performance. Our findings have implications for research on the value of business groups in institutional transition, interorganizational relationships, and the contingencies of social relationships.

AbstractDecision making in environmental projects is usually complex because of heterogeneous stakeholder interests, multiple objectives, long planning and implementation processes, and uncertain outcomes. Conflicting stakeholder interests in particular are often an important impediment to the realization and success of projects. Multiple criteria decision analysis (MCDA) methods are potentially useful for facilitating conflict resolution among stakeholder groups. However, some studies that have applied MCDA methods indicate that users are often skeptical about the value of MCDA methods and prefer the freedom of unaided decision making. We examine whether and how multi‐attribute value theory (MAVT), a particular kind of MCDA, facilitates conflict resolution in environmental projects. Therefore, the MAVT method is applied to a specific river rehabilitation project in Switzerland (Thur River). The main questions are: (1) Can the MAVT method predict the final preferences of stakeholders and therefore anticipate conflicts at an early stage? (2) Do stakeholders reconsider and change their preferences after using the MAVT method? (3) If they do, does this result in more consensus‐oriented decisions? We find that the principal advantage of the method in our case was not the prediction of stakeholders' final preferences, but rather the methods' ability to facilitate more consensus‐oriented decisions. The paper discusses possible reasons for this finding and concludes with recommendations for future applications of the MAVT method in environmental decision making. Copyright © 2006 John Wiley & Sons, Ltd.

Abstract. The damages from climatic extremes have dramatically increased in the last decades in Europe, as likely outcomes of climate change: floods, droughts, heat waves and hailstorms have brought local as well as widespread damages to farmers, industry, infrastructures and society, to insurance and reinsurance companies; in this work we deal with the hailstorm hazard. The NCEP-NCAR Reanalysis (2.5 by 2.5° lat-lon) over the Italian area and the hailstorm reports at several sites are used to identify few forcings for hailstorms; statistical relationships linking forcings and hailstorm frequencies are derived. Such relationships are applied to the same forcings derived from the CGCM2-A2 climate scenario provided by the Canadian Centre for Climate modeling and analysis (CCCma; resolution approximately 3.75 by 3.75° lat-lon), to evaluate the expected changes of the frequency of hailstorms. The time series of the forcings from the NCEP-NCAR Reanalysis and the CCCma climate scenario in the past decades are compared in order to assess the reliability and accuracy of the predictions of the future hailstorm hazard. It is shown that the climate scenario provides a fairly faithful representation of the past trends of the forcings relevant to the hailstorms frequency and that such quantity, hence the hailstorm hazard, is growing and will likely grow in the future over the limited area taken into consideration in this study.

Classical liberals such as Kant argued that expanding political participation and increasing economic interdependence would promote peace among states. Recent empirical support for both propositions has led to a growing consensus on the power of the 'liberal peace'. This article challenges one pillar of the liberal peace. Using a dataset of international disputes from 1960 to 1988, the authors find that there is no statistical evidence of the pacifying effect of economic interdependence. Findings in the existing literature appear to be due to the improper use of the classic logit (or probit) method despite the existence of the 'simultaneity problem' between the use of force and interdependence (i.e. reciprocal causation). In this study, the authors employ a two-stage probit least squares method to control this problem. Although Kant's prediction with respect to regime type is supported by the analysis, the claim that economic interdependence will decrease conflict is not. The two-stage results reveal that international conflict reduces economic interdependence (rather than interdependence reducing conflict). The findings are robust using five alternative operationalizations of the economic interdependence variable. Finally, a re-analysis of the Russett & Oneal dataset using a two-stage probit model also indicates that the impact of economic interdependence evaporates after correcting for the simultaneity problem.

During the decade and a half since the collapse of communism in 1989, the four Central European states have achieved a remarkable degree of party system stability, confounding pessimistic predictions about unstable competition, weak parties and limited institutionalization. This stability, and variations within the region, raises important questions about party system stability and change. The present article explores the patterns of party competition in Hungary, Poland, the Czech Republic and Slovakia, and finds that party system stability is largely a function of party strategy. The broadly successful strategies of former communist and new social democratic parties have stabilized the left wing of the systems in the first three cases, whereas the Slovak left has struggled. However, while efforts to define and dominate the centre–right have yielded some stabilization in Hungary and the Czech Republic, similar efforts in Poland have been less decisive. In Slovakia, the struggle against Mec .iar has eclipsed other bloc-building strategies, and accounts for much of the instability. In both Poland and Slovakia, relatively open electoral systems in the early years worked against unitary strategies, at least for some parties. However, apart from this, constraints on party strategy were weak in the first decade, and many strategies were attempted. In such a context, party strategy therefore becomes a particularly powerful explanation of differences in patterns of party system stability.

We develop a model of one representative agent and one asset. The agent evaluates the earnings according to Prospect Theory and he does not know exactly the stochastic process generating earnings. While the earnings are generated by a random walk process, the agent considers a Markovian process, according to which firm's earnings move between two regimes, represented by a mean-reverting process and a trend process, as in Barberis, Shleifer and Vishny (1998). We study how an agent who is loss averse evaluates the price of a stock when she takes into account the wrong stochastic process. This twofold departure from rationality determines permanent effects on stock prices, even in long run. First, the model shows that agent who evaluates the asset according to Prospect Theory consistently underestimates the asset, due to loss aversion bias. This is shown under two different assumption regarding the functional form of utility. A kinked linear utility function (as in Bernatzi and Thaler, 1985) and the original and more general specification of Kahneman and Tversky (1979) are used. The model allows to explain observed phenomenon in the cross-section earnings return distribution. We solve this model and according to Barberis et all (1998), we evaluate the framework by using artificial data sets of earnings and prices simulated from the model. For plausible range of parameter values, it generates the empirical predictions of overreaction and underreaction observed in the data are explained.