A semi-parametric method for transforming data to normality

A non-parametric transformation function is introduced to transform data to any continuous distribution. When transformation of data to normality is desired, the use of a suitable parametric pre-transformation function improves the performance of the proposed non-parametric transformation function. The resulting semi-parametric transformation function is shown empirically, via a Monte Carlo study, to perform at least as well as any parametric transformation currently available in the literature.     

Testing generalized linear and semiparametric models against smooth alternatives

We propose goodness-of-fit tests for testing generalized linear models and semiparametric regression models against smooth alternatives. The focus is on models having both continous and factorial covariates. As a smooth extension of a parametric or semiparametric model we use generalized varying-coefficient models as proposed by Hastie and Tibshirani. A likelihood ratio statistic is used for testing. Asymptotic expansions allow us to write the estimates as linear smoothers which in turn guarantees simple and fast bootstrapping of the test statistic. The test is shown to have √ n -power, but in contrast with parametric tests it is powerful against smooth alternatives in general.     

Forecasting industrial production using structural time series models

Industrial production data series are volatile and often also cyclical. Hence, univariate time series models which allow for these features are expected to generate relatively accurate forecasts of industrial production. A particular class of unobservable components models — structural time series models — is used to generate forecasts of Austrian and German industrial production. A widely applied ARIMA model is used as a baseline for comparison. The empirical results show that the basic structural model generates more accurate forecasts than the ARIMA model when accuracy is measured in terms of size of error or directional change; and that the basic structural model forecasts better than the structural model with a cyclical component included on the basis of numerical measures, and tracking error for month-to-month changes.     

On the social stability of coalitional property rights regimes

We present a model of coalitional property rights (CPR) regimes– regimes in which ownership of a good is attributable to coalitions of various sizes. Specifically, for each good, we define a legal structure that specifies the legal coalitions of individuals that share a communal claim to that good. Generally, each legal coalition may use exclusionary rules to allocate its holdings internally. These rules allow eligible subcoalitions to recontract by expropriating some fraction of the legal coalition's endowment. We then ask: what types of CPR regimes are socially stable in the sense of having a nonempty core? We give conditions on the legal structure and the primitives of the economy that achieve social stability in this sense. We emphasize two cases of particular interest. ( I ) Unanimity. Unanimity is required for a legal coalition to recontract against (block) the status quo. In this case, the core is nonempty under standard assumptions. Each agent's ability to veto an alternative allocation allows a partial characterization in terms of the economies that are privatized by dividing up the communal endowment among the members of each legal coalition. We show that in some economies' collective vs private ownership matters in terms of social stability. ( II ) Exclusion. Many eligible subcoalitions can expropriate the legal coalition's entire endowment. An example is the collection of simple majorities. The presence of cycles can easily lead to social instability. We show that if endowment holdings are sufficiently “specialized” and each agent's “veto power” sufficiently large, then stability can be achieved despite the presence of cycles in some goods. Received: 30 June 1993/Accepted: 28 February 1998     

Squeezing or cuddling? The impact of economic crises on management control and stakeholder management

This paper analyzes the effects of economic crises on firms’ use of management control mechanisms and on their management of stakeholder relations. Moreover, the association between stakeholder management and management control system use is analyzed. In the wake of the economic crisis of 2008/2009, many firms were faced with severe threats that called for immediate short-term action to ensure firm survival. However, short-term action like massive cost-cutting and cash generation often are blamed for going at the expense of long-term health as key stakeholder relations may be irreversibly harmed. Hence, three interrelated questions are addressed theoretically and empirically: First, we analyze the impact of the recent economic crisis on firms’ control strategies. More specifically, we investigate whether a high crisis impact on firms is associated with a shortening of reporting cycles, a more interactive use of control-relevant information, restriction of employee autonomy and a focus on liquidity and cost-cutting. Second, we examine from the viewpoint of stakeholder theory how firms can make use of active stakeholder management for crisis management. Third, we explore whether firms can take short-term measures for ensuring liquidity and cutting costs and at the same time pursue a stakeholder strategy aiming at the long-term survival of the firm. Using survey data from 204 major Austrian corporations, we provide evidence that firms significantly adjusted their control systems as a response to the economic crisis. Our data do not indicate an immanent contradiction between a “short-term finance focus” and the pursuit of a sustainable stakeholder strategy.     

Moments of Special Normally Distributed Matrices

In solving systems of simultaneous random linear algebraic equations some approximating methods lead to the problem of determinating moments of special random matrices and vectors. In this article corresponding formulas are provided for moments of some normally distributed matrices. The deduced relations can be considered as a generalization of the known formulas for the central moments of normally distributed random variables.