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Shallow meritocracy
(2023)
Meritocracies aspire to reward hard work and promise not to judge individuals by the circumstances into which they were born. However, circumstances often shape the choice to work hard. I show that people's merit judgments are "shallow" and insensitive to this effect. They hold others responsible for their choices, even if these choices have been shaped by unequal circumstances. In an experiment, US participants judge how much money workers deserve for the effort they exert. Unequal circumstances disadvantage some workers and discourage them from working hard. Nonetheless, participants reward the effort of disadvantaged and advantaged workers identically, regardless of the circumstances under which choices are made. For some participants, this reflects their fundamental view regarding fair rewards. For others, the neglect results from the uncertain counterfactual. They understand that circumstances shape choices but do not correct for this because the counterfactual—what would have happened under equal circumstances—remains uncertain.
Intrinsic motivation for honesty is perceived as an important determinant of large and persistent variation in cheating behavior. However, little is known about its actual role due to challenges in obtaining precise measures of motivation for honesty, as well as field outcomes on cheating. We fill these gaps using a unique setting of informal milk markets in India. A novel behavioral experiment, which combines a standard die roll task with Bluetooth technology, is used to measure motivation for honesty of milkmen at both extensive and intensive margins. We then buy milk from the same milkmen and show that cheating in the field, measured by the amount of water added to milk, widens significantly with a milkman’s degree of dishonesty. Additional analyses show that conventional binary measure of motivation for honesty suffers from measurement errors, resulting in underestimation of this association.
Despite a lot of re-structuring and many innovations in recent years, the securities transaction industry in the European Union is still a highly inefficient and inconsistently configured system for cross-border transactions. This paper analyzes the functions performed, the institutions involved and the parameters concerned that shape market and ownership structure in the industry. Of particular interest are microeconomic incentives of the main players that can be in contradiction to social welfare. We develop a framework and analyze three consistent systems for the securities transaction industry in the EU that offer superior efficiency than the current, inefficient arrangement. Some policy advice is given to select the 'best' system for the Single European Financial Market.
Serial correlation in dynamic panel data models with weakly exogenous regressor and fixed effects
(2005)
Our paper wants to present and compare two estimation methodologies for dynamic panel data models in the presence of serially correlated errors and weakly exogenous regressors. The ¯rst is the ¯rst di®erence GMM estimator as proposed by Arellano and Bond (1991) and the second is the transformed Maximum Likelihood Estimator as proposed by Hsiao, Pesaran, and Tahmiscioglu (2002). Thereby, we consider the ¯xed e®ects case and weakly exogenous regressors. The ¯nite sample properties of both estimation methodologies are analysed within a simulation experiment. Furthermore, we will present an empirical example to consider the performance of both estimators with real data. JEL Classification: C23, J64
The pricing of an ambiguous asset, whose cash flow stream is uncertain, may be affected by three factors: the belief regarding the realization likelihood of cash flows, the subjective attitude towards risk, and the attitude towards ambiguity. While previous literature looks at the total price discount under ambiguity, this paper investigates with laboratory experiments how much effect each factor can induce. We apply both non-parametric and parametric methods to cleanly separate the belief effects, the risk premiums, and the ambiguity premiums from each other. Both methods lead to similar results: Overall, subjects have substantial ambiguity aversion, and ambiguity premiums account for the largest price deviation component when the degree of ambiguity is high. As information accumulates, ambiguity premiums decrease. We also find that beliefs do influence prices under ambiguity. This is not because beliefs are biased towards either good or bad scenarios per se, but because subjects display sticky belief updating as new information becomes available. The clear separation performed in this paper between belief and attitude also enables a more accurate estimation of the parameter of ambiguity aversion compared to previous studies, since the effect of beliefs is partialled out. Overall, we find empirically that both factors, belief and attitude towards ambiguity, are important factors in pricing under ambiguity.
Tail-correlation matrices are an important tool for aggregating risk measurements across risk categories, asset classes and/or business segments. This paper demonstrates that traditional tail-correlation matrices—which are conventionally assumed to have ones on the diagonal—can lead to substantial biases of the aggregate risk measurement’s sensitivities with respect to risk exposures. Due to these biases, decision-makers receive an odd view of the effects of portfolio changes and may be unable to identify the optimal portfolio from a risk-return perspective. To overcome these issues, we introduce the “sensitivity-implied tail-correlation matrix”. The proposed tail-correlation matrix allows for a simple deterministic risk aggregation approach which reasonably approximates the true aggregate risk measurement according to the complete multivariate risk distribution. Numerical examples demonstrate that our approach is a better basis for portfolio optimization than the Value-at-Risk implied tail-correlation matrix, especially if the calibration portfolio (or current portfolio) deviates from the optimal portfolio.
Tail-correlation matrices are an important tool for aggregating risk measurements across risk categories, asset classes and/or business segments. This paper demonstrates that traditional tail-correlation matrices—which are conventionally assumed to have ones on the diagonal—can lead to substantial biases of the aggregate risk measurement’s sensitivities with respect to risk exposures. Due to these biases, decision-makers receive an odd view of the effects of portfolio changes and may be unable to identify the optimal portfolio from a risk-return perspective. To overcome these issues, we introduce the “sensitivity-implied tail-correlation matrix”. The proposed tail-correlation matrix allows for a simple deterministic risk aggregation approach which reasonably approximates the true aggregate risk measurement according to the complete multivariate risk distribution. Numerical examples demonstrate that our approach is a better basis for portfolio optimization than the Value-at-Risk implied tail-correlation matrix, especially if the calibration portfolio (or current portfolio) deviates from the optimal portfolio.
Security has become one of the primary factors that cloud customers consider when they select a cloud provider for migrating their data and applications into the Cloud. To this end, the Cloud Security Alliance (CSA) has provided the Consensus Assessment Questionnaire (CAIQ), which consists of a set of questions that providers should answer to document which security controls their cloud offerings support. In this paper, we adopted an empirical approach to investigate whether the CAIQ facilitates the comparison and ranking of the security offered by competitive cloud providers. We conducted an empirical study to investigate if comparing and ranking the security posture of a cloud provider based on CAIQ’s answers is feasible in practice. Since the study revealed that manually comparing and ranking cloud providers based on the CAIQ is too time-consuming, we designed an approach that semi-automates the selection of cloud providers based on CAIQ. The approach uses the providers’ answers to the CAIQ to assign a value to the different security capabilities of cloud providers. Tenants have to prioritize their security requirements. With that input, our approach uses an Analytical Hierarchy Process (AHP) to rank the providers’ security based on their capabilities and the tenants’ requirements. Our implementation shows that this approach is computationally feasible and once the providers’ answers to the CAIQ are assessed, they can be used for multiple CSP selections. To the best of our knowledge this is the first approach for cloud provider selection that provides a way to assess the security posture of a cloud provider in practice.
Die deutschen Hohlglashütten wurden im August 1933 zu einem Zwangskartell zusammengeschlossen . Die dabei zu überwindenden Schwierigkeiten bestanden vornehmlich in der Verschiedenartigkeit der erstellten Erzeugnisse und in dem besonders ausgeprägten Hang zur Selbständigkeit der in diesem Industriezweig weitaus überwiegenden Mittelbetriebe. Darüber hinaus stieß die Durchführung der Preisordnung infolge der Rückständigkeit des Rechnungswesens der einzelnen Hütten auf nahezu unüberwindbar erscheinende Widerstände. Es mangelte und mangelt noch heute durchweg an brauchbaren Kalkulationsunterlagen und damit an der Möglichkeit einer einwandfreien Ermittlung des Erfolges bzw . Verlustes und seiner Quellen...
Although the commoditisation of illiquid asset exposures through securitisation facilitates the disciplining effect of capital markets on the risk management, private information about securitised debt as well as complex transaction structures could possibly impair the fair market valuation. In a simple issue design model without intermediaries we maximise issuer proceeds over a positive measure of issue quality, where a direct revelation mechanism (DRM) by profitable informed investors engages endogenous price discovery through auction-style allocation preference as a continuous function of perceived issue quality. We derive an optimal allocation schedule for maximum issuer payoffs under different pricing regimes if asymmetric information requires underpricing. In particular, we study how the incidence of uninformed investors at varying levels of valuation uncertainty and their function of clearing the market effects profitable informed investment. We find that the issuer optimises own payoffs at each valuation irrespective of the applicable pricing mechanism by awarding informed investors the lowest possible allocation (and attendant underpricing) that still guarantees profitable informed investment. Under uniform pricing the composition of the investor pool ensures that informed investors appropriate higher profit than uninformed types. Any reservation utility by issuers lowers the probability of information disclosure by informed investors and the scope of issuers to curtail profitable informed investment. JEL Classifications: D82, G12, G14, G23