Impact of intelligent decision aids on expert and novice decision-makers' judgments

Businesses have invested tremendous resources into intelligent decision aid development. A good match between user and aid may improve the expert decision‐maker's decision quality. However, novices may be prone to poorer decision‐making if intelligent decision aids are more expert than the user. The present paper provides an empirical test of the impact of decision aids on subjects with differential expertise levels. The results support the contention that intelligent decision aids aggravate bias in novices’ decision‐making but mitigate bias in experts’ decision‐making processes. Intelligent decision aids may be best viewed as complements to expert decision‐makers during complex problem analysis and resolution.     

Nonparametric maximum likelihood estimation in a non locally compact setting

Maximum likelihood estimation is considered in the context of infinite dimensional parameter spaces. It is shown that in some locally convex parameter spaces sequential compactness of the bounded sets ensures the existence of minimizers of objective functions and the consistency of maximum likelihood estimators in an appropriate topology. The theory is applied to revisit some classical problems of nonparametric maximum likelihood estimation, to study location parameters in Banach spaces, and finally to obtain Varadarajan’s theorem on the convergence of empirical measures in the form of a consistency result for a sequence of maximum likelihood estimators. Several parameter spaces sharing the crucial compactness property are identified. This research was supported by grants from the National Sciences and Engineering Research Council of Canada and the Fonds FCAR de la Province de Québec.     

Varieties of competitive parity

Strategy research explains why some firms outperform others, typically using profit rates, shareholder returns, and other continuous dependent variables. This paper investigates winning as the dependent variable, as measured by distributions of annual industry leadership in profits and returns to investors. This shift in dependent variable introduces alternative null models of competitive parity, including skew distributions derived from the natural sciences, and empirical distributions from nonbusiness domains such as chess, politics, sports, and beauty pageants. An empirical study of 20‐year leadership in U.S. industries shows that performance distributions in business follow statistical power laws resembling those in natural phenomena, and closely resemble distributions found in sports, politics, and other nonbusiness domains. The results support a presumption of persistent performance advantages in business, but show that business outcomes are indistinguishable from outcomes in the wider scientific and competitive landscape, and are amenable to explanation using relatively simple heuristics. The paper shows how the choice of null model shapes firm performance explanations, and explores the consequences of a more inclusive approach to null models in strategy research. Copyright © 2002 John Wiley & Sons, Ltd.     

On forward induction in money-burning games

Summary. We first consider money-burning games studied by Ben-Porath and Dekel [6]. We show that iterative weak dominance and extensive form rationalizability yield the same unique outcome in this class of games. This result suggests that weak dominance captures the forward induction logic implied by extenisve form rationalizability. Next, we consider an example of entry model by Arvan [1] to demonstrate the power of forward induction. In this example, despite the presence of multiple equilibria, forward induction chooses a unique outcome. Received: January 25, 2000; revised version: January 5, 2001     

Who Gets on the News? The relation between media biases and different actors in news reporting on complex policy processes

Abstract

Having a voice in media is important to gain power and legitimacy in policy processes. However, media are biased in transmitting information. Using a quantitative content analysis of ten years’ news reporting around water management policies in the Netherlands, we study how much media attention different groups of actors receive and how media biases relate to this attention. Executive politicians get on the news because of their authoritative position; less authoritative actors getting on the news is more related to information biases. Information biases can thus function as a form of checks and balances in news reporting on policy processes.     

Another look at risk apportionment

This paper presents a general result on the random selection of an element from an ordered sequence of risks and uses this result to derive additive and cross risk apportionment. Preferences favoring an improvement of the sampling distribution in univariate or bivariate first-order stochastic dominance are those exhibiting additive or cross risk apportionment. The univariate additive and multiplicative risk apportionment concepts are then related to the notion of bivariate cross risk apportionment by viewing the single-attribute utility function of an aggregate position (sum or product of attributes) as a 2-attribute utility function. The results derived in the present paper allow one to further explore the connections between the different concepts of risk apportionment proposed so far in the literature.     

Assessing the contribution of banks,insurance and other financial services to systemic risk

The aim of this paper is to contribute to the debate on systemic risk by assessing the extent to which distress within the main different financial sectors, namely, the banking, insurance and other financial services industries contribute to systemic risk. To this end, we rely on the $\mathrm{\Delta }\mathit{CoVaR}$ systemic risk measure introduced by Adrian and Brunnermeier (2011). In order to provide a formal ranking of the financial sectors with respect to their contribution to systemic risk, the original $\mathrm{\Delta }\mathit{CoVaR}$ approach is extended here to include the Kolmogorov–Smirnov test developed by Abadie (2002), based on bootstrapping. Our empirical results reveal that in the Eurozone, for the period ranging from 2004 to 2012, the other financial services sector contributes relatively the most to systemic risk at times of distress affecting this sector. In turn, the banking sector appears to contribute more to systemic risk than the insurance sector. By contrast, the insurance industry is the systemically riskiest financial sector in the United States for the same period, while the banking sector contributes the least to systemic risk in this area. Beyond this ranking, the three financial sectors of interest are found to contribute significantly to systemic risk, both in the Eurozone and in the United States.     

Do enlarged fiscal deficits cause inflation? The historical record

We survey the historical record for two centuries on the connection between expansionary fiscal policy and inflation. The relationship holds in wartime when fiscally stressed governments resorted to the inflation tax. In two peacetime episodes in the early twentieth century, bond‐financed fiscal deficits, unbacked by future taxes, may have contributed to inflation. Fiscal influence on monetary policy was important in the Great Inflation 1965–1983. Expansionary monetary and fiscal policy did not lead to inflation in the Global Financial Crisis of 2007–08 but, by contrast, the fiscal and monetary response to the COVID‐19 pandemic may involve risks of fiscal dominance and future inflation.     

A first-phase screening method for site selection of large-scale solar plants with an application to Italy

Increasing the exploitation of renewable energy sources (RES) is a key element for reducing the detrimental consequences of greenhouse-gases emissions and for satisfying the growing demand for energy. Solar power plays a central role having the potential to completely satisfy the world energetic needs. Locating optimal sites for installing solar plants is therefore an important task deeply affecting the long term profitability of such plants. The present paper proposes a filtering method to select a subset of efficient locations in order to reduce the dimensionality of the original problem when a large territory is screened for locating optimal sites for large-scale solar plants. It is based on the idea of preference relations and Pareto dominance and, avoiding to operate an inter-comparison of different locations’ attributes, it can be considered assumptions-free. Moreover, the paper applies such filtering method, together with an analysis of economic viability, to Italy, a country with relatively high potentials in terms of solar energy that currently lacks an optimal site selection analysis. Once applied, the filter reduces the original set of feasible locations by more than 99%. The resulting Pareto efficient locations, evaluated through five selected criteria, are concentrated in the southern part of Italy and, particularly, in the islands of Sicily and Sardinia, where also the economic viable locations are mostly found.