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Funder: Amazon Web Services (AWS) Imagine Grant, Funder: Kingston University (Kingston University, London); doi: https://doi.org/10.13039/100010049, Funder: Association Nationale de la Recherche et de la Technologie (National Association for Research and Technology); doi: https://doi.org/10.13039/501100003032, Funder: Association Nationale de la Recherche Scientifique and Pacifica (CIFRE grant 2017/0245), Funder: PRIMUS/20/HUM/009, Funder: UID/PSI/03125/2019 from the Portuguese National Foundation for Science and Technology (FCT)., Funder: PSA research grant ($285.59) for the PSACR projects data collection, Funder: The work of Dmitrii Dubrov was supported within the framework of the Basic Research Program at HSE University, RF, Funder: Agentúra na podporu výskumu a vývoja (Slovak Research and Development Agency) - APVV-17-0596, Funder: Progres Q18, Charles University, Funder: JSPS KAKENHI Grant Numbers JP18K12015 and JP20H04581, Funder: National Science Centre, Poland (2019/35/B/HS6/00528), Funder: Slovak Research and Development Agency - APVV-17-0596, Funder: Huo Family Foundation, Funder: The Japan Society for the Promotion of Science KAKENHI [19K14370], Funder: The Institute of Psychology, Jagiellonian University, Funder: Program FUTURE LEADER of Lorraine Université d’Excellence within the program Investissements Avenir (ANR-15-IDEX-04-LUE) operated by the French National Research Agency, Funder: Rubicon grant (019.183SG.007) from the Netherlands Organization for Scientific Research (NWO), Funder: Australian Research Council (DP180102384), Funder: HSE University Basic Research Program, Funder: Horizon 2020 grant 964728 (JITSUVAX) from the European Commission and was supported by a United Kingdom Research and Innovation (UKRI) Research Fellowship grant ES/V011901/1, Funder: Social Science and Humanities Research Council of Canada, Funder: Dominican University Faculty Support Grant, Funder: FONDECYT 1221538, Funder: Vicerrectoria de Investigaciones, Uniandes, Funder: Statutory funds of the Institute of Psychology, University of Wroclaw, Funder: University of Desarrollo, Faculty of Psychology, Funder: IDN Being Human Lab (University of Wrocław), Funder: ANID - Fondecyt 1201513, In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.

We analyze applications of biform games to linear production (LP) and sequencing processes. Biform games apply to problems in which strategic decisions are followed by some cooperative game, where the specific environment of the cooperative game is in turn determined by these strategic decisions. In biform LP-processes, we allow firms to compete for resources, rather than assuming the resource bundles are simply given. With strategy dependent resource bundles that can be obtained from two locations, we show that the induced strategic game has a (pure) Nash equilibrium, using the Owen set or any game-theoretic solution concept that satisfies anonymity to solve the cooperative LP-game. In biform sequencing processes, we no longer assume an initial processing order is given. Instead, this initial order is strategically determined. Solving the second-stage cooperative sequencing game using a gain splitting rule, we fully determine the set of Nash equilibria of the induced strategic game.

This paper studies the nucleolus of graph-restricted games as an alternative for the Shapley value to evaluate communication situations. We focus on the inheritance of properties of cooperative games related to the nucleolus: strong compromise admissibility and compromise stability. These two properties allow for a direct, closed formula for the nucleolus. We characterize the families of graphs for which the graph-restricted games inherit these properties from the underlying games. Moreover, for each of these two properties, we characterize the family of graphs for which the nucleolus is invariant

We investigate questions related to the set $\mathcal{SEP}_d$ consisting of the linear maps $\rho$ acting on $\mathbb{C}^d\otimes \mathbb{C}^d$ that can be written as a convex combination of rank one matrices of the form $xx^*\otimes yy^*$. Such maps are known in quantum information theory as the separable bipartite states, while nonseparable states are called entangled. In particular we introduce bounds for the separable rank $\mathrm{rank_{sep}}(\rho)$, defined as the smallest number of rank one states $xx^*\otimes yy^*$ entering the decomposition of a separable state $\rho$. Our approach relies on the moment method and yields a hierarchy of semidefinite-based lower bounds, that converges to a parameter $\tau_{\mathrm{sep}}(\rho)$, a natural convexification of the combinatorial parameter $\mathrm{rank_{sep}}(\rho)$. A distinguishing feature is exploiting the positivity constraint $\rho-xx^*\otimes yy^* \succeq 0$ to impose positivity of a polynomial matrix localizing map, the dual notion of the notion of sum-of-squares polynomial matrices. Our approach extends naturally to the multipartite setting and to the real separable rank, and it permits strengthening some known bounds for the completely positive rank. In addition, we indicate how the moment approach also applies to define hierarchies of semidefinite relaxations for the set $\mathcal{SEP}_d$ and permits to give new proofs, using only tools from moment theory, for convergence results on the DPS hierarchy from (A.C. Doherty, P.A. Parrilo and F.M. Spedalieri. Distinguishing separable and entangled states. Phys. Rev. Lett. 88(18):187904, 2002).

Sandwich algorithms are commonly used to approximate the Pareto front of a multiobjective (MO) convex problem by enclosing it between an inner and outer approximation. By iteratively improving the approximations, the distance between them is minimized which gives an estimate of how well the Pareto front is approximated. A wellexplainable type of sandwich algorithm is based on weighted sum scalarization (WSS), where the next set of weights is determined by the most promising inner normal of the inner approximation. As these normals can contain negative values, not every optimization will result in finding an efficient point. In order to reduce the number of searches towards the dominated part, we propose an elegant modification of the criterion space which is an advancement on the formulation of Solanki et al. In addition to being well-explainable and easy to integrate within an existing optimization procedure, this modification is theoretically able to obtain all nondominated points of an MO linear programming problem in a finite number of expansions of the inner approximation. Furthermore, we propose two heuristic approaches to determine the distance between the inner and outer approximation that can be used as an alternative for the distance calculation of Solanki et al. These heuristics incorporate the ideas of Solanki et al. And Craft et al. to obtain straightforward and faster methods.

We consider a model of influence over a network with finite-horizon opinion dynamics. The network consists of agents that update their opinions via a trust structure as in the DeGroot dynamics (De Groot (1974)). The model considers two potential external influencers that have fixed and opposite opinions. They aim to maximally impact the aggregate state of opinions at the end of the finite horizon by targeting one agent in one specific time period. In the case of only one influencer, we characterize optimal targets on the basis of two features: shift and amplification. Also, conditions are provided under which a specific target is optimal: the maximum-amplification target. In the case of two influencers, we focus on the existence and characterization of pure strategy equilibria in the corresponding two-person strategic zero-sum game. Roughly speaking, if the initial opinions are not too much in favour of either influencer, the influencers’ equilibrium behaviour is also driven by the amplification of targets.

This paper examines the corporate governance mechanisms in Sri Lanka, a country that only a little more than a decade ago emerged from a 30-year long civil war. We focus on the evolution of Sri Lanka’s corporate governance from historical, sociocultural, and institutional perspectives. Taking Sri Lanka as a case where inclusiveness and reconciliation at the board level is important, we aim to diagnose the key corporate governance issues which we then broaden towards other South Asia developing countries and provide a research agenda. Many Sri Lankan firms suffer from typical Asian-style agency problems; conflicts of interest between (i) minority and majority shareholders, (ii) shareholders and debtholders, and (iii) shareholders and stakeholders. The most prevalent agency problem is the expropriation of minority shareholders’ rights through ownership pyramids, cross-holdings, or intermediate private firms. Although creditor protection laws limit the expropriation of debtholders’ rights, firms’ widespread use of political connections forces banks to grant cheap credit at favorable terms. Poor stakeholder management creates agency problems following window dressing of ESG disclosures, corporate opacity, and ethnicity-and gender-based discrimination in the workplace. This study shows that social norms and ethical values play a non-negligible role in the functioning of the corporate governance regulation and in corporate culture in Sri Lanka.

This paper argues that corporate financial frictions can have an adverse effect on employee mental health, an important determinant of employee productivity. To identify the causal effects of financial frictions, we exploit variation in firms’ need to refinance their long-term debt in 2008, a period when refinancing became more difficult due to the credit crunch. Using administrative microdata, we find that antidepressant use grows significantly more among employees of firms in higher need of debt refinancing. Much of this effect occurs at employees keeping their jobs, pointing to decreased perceptions of job security as a transmission channel.

Let $$S \subseteq \mathbb {R}^n$$ S ⊆ R n be a compact semialgebraic set and let f be a polynomial nonnegative on S. Schmüdgen’s Positivstellensatz then states that for any $$\eta > 0$$ η > 0 , the nonnegativity of $$f + \eta$$ f + η on S can be certified by expressing $$f + \eta$$ f + η as a conic combination of products of the polynomials that occur in the inequalities defining S, where the coefficients are (globally nonnegative) sum-of-squares polynomials. It does not, however, provide explicit bounds on the degree of the polynomials required for such an expression. We show that in the special case where $$S = [-1, 1]^n$$ S = [ - 1 , 1 ] n is the hypercube, a Schmüdgen-type certificate of nonnegativity exists involving only polynomials of degree $$O(1 / \sqrt{\eta })$$ O ( 1 / η ) . This improves quadratically upon the previously best known estimate in $$O(1/\eta )$$ O ( 1 / η ) . Our proof relies on an application of the polynomial kernel method, making use in particular of the Jackson kernel on the interval $$[-1, 1]$$ [ - 1 , 1 ] .

In this paper, I study the macroeconomic effects of labor markets that feature both flexible and permanent contracts. I argue that the countercyclical nature of flexible contracts reduces the risk of unemployment fluctuations for permanent workers, resulting in a more stable aggregate demand and a more stable business cycle. Using a New Keynesian model with imperfect unemployment insurance and a two-sector search model that incorporates both permanent and flexible contracts, I quantify the role of flexible contracts in stabilizing the economy. I find that an economy with 15% flexible employment experiences lower volatility in output, inflation, and employment compared to one without flexible employment. However, this comes at a cost to flexible workers in terms of employment fluctuations, resulting in a decrease in aggregate welfare. These results underscore the importance of flexible contracts in stabilizing the business cycle, while also highlighting the need for policymakers to ensure that all workers benefit from them.

This paper provides a multi-actor perspective on the realization of new infrastructures, motivated by the necessity for infrastructures to support the ongoing climate and energy transition in general, and CO2 transport infrastructures for carbon capture, utilization and storage (CCUS) in particular. We develop a general model to represent infrastructures that allows for a unique decomposition into `elementary infrastructure components' based on heterogeneous user requirements. Notably, it incorporates a cost function with a very generic and adaptable structure, for which we can still explicitly determine the costs of each individual component. As a direct consequence an intuitive cost allocation rule is obtained: equal component cost sharing. This allocation rule is in line with existing game-theoretic concepts and satisfies the desirable properties of advantageous scaling and coalitional rationality. Advantageous scaling guarantees that the costs allocated to each existing user do not increase if the number of users grows larger and coalitional rationality ensures that there is no subgroup of infrastructure users that would have a financial reason to object to the cost allocation. Additionally, we examine the application of our model to a prospective CO2 transport infrastructure for CCUS in the port of Rotterdam and the adjoining industry area.

The graph partition problem (GPP) aims at clustering the vertex set of a graph into a fixed number of disjoint subsets of given sizes such that the sum of weights of edges joining different sets is minimized. This paper investigates the quality of doubly nonnegative (DNN) relaxations, i.e., relaxations having matrix variables that are both positive semidefinite and nonnegative, strengthened by additional polyhedral cuts for two variations of the GPP: the k-equipartition and the graph bisection problem. After reducing the size of the relaxations by facial reduction, we solve them by a cutting-plane algorithm that combines an augmented Lagrangian method with Dykstra's projection algorithm. Since many components of our algorithm are general, the algorithm is suitable for solving various DNN relaxations with a large number of cutting planes. We are the first to show the power of DNN relaxations with additional cutting planes for the GPP on large benchmark instances up to 1,024 vertices. Computational results show impressive improvements in strengthened DNN bounds.

This paper studies a search problem in which a consumer is initially aware of only a few products. At every point in time, the consumer then decides between searching among alternatives of which he is already aware and discovering more products. I show that the optimal policy for this search and discovery problem is fully characterized by tractable reservation values. Moreover, I prove that a predetermined index fully specifies the purchase decision of a consumer following the optimal search policy. Finally, a comparison highlights differences to classical random and directed search. This paper was accepted by Dmitri Kuksov, marketing.

This paper is an in-depth analysis of the generalized $\vartheta$-number of a graph. The generalized $\vartheta$-number, $\vartheta_k(G)$, serves as a bound for both the $k$-multichromatic number of a graph and the maximum $k$-colorable subgraph problem. We present various properties of $\vartheta_k(G)$, such as that the sequence $(\vartheta_k(G))_k$ is increasing and bounded from above by the order of the graph $G$. We study $\vartheta_k(G)$ when $G$ is the strong, disjunction or Cartesian product of two graphs. We provide closed form expressions for the generalized $\vartheta$-number on several classes of graphs including the Kneser graphs, cycle graphs, strongly regular graphs and orthogonality graphs. Our paper provides bounds on the product and sum of the $k$-multichromatic number of a graph and its complement graph, as well as lower bounds for the $k$-multichromatic number on several graph classes including the Hamming and Johnson graphs.

Recent research has documented that industry concentration has increased significantly over the past 25 years, with potentially negative consequences for productivity, innovation, and social welfare. Some have suggested that corporate tax planning, which has also increased over the same period, has contributed in part to this trend. We provide large-sample empirical evidence on whether tax planning is associated with industry concentration. We document five main results. First, we find that industry leaders engage in more aggressive tax planning relative to their closest competitors in only half of industries, and this percentage has not changed materially over our sample period. Second, we find that whether aggressive tax planning by industry leaders is associated with increased industry concentration depends critically on the extent to which their competitors are also engaging in aggressive tax planning. Third, we find that tax planning by industry leaders explains very little of the trend in increased industry concentration across the full sample. Fourth, we find that industries with plausibly tax planning-induced concentration generally do not exhibit lower productivity growth than other industries. Finally, we find that industries where leaders engage in more tax planning than competitors are not materially different from other industries in terms of key characteristics that are likely of concern to policymakers (such as industry capitalization or employment). Collectively, our findings suggest that corporate tax planning is not a material driver of increased industry concentration on average or in key industries, nor is corporate tax planning associated with reduced industry-level productivity .

This thesis studies topics in behavioral asset pricing. The proposed contributions are both theoretical and empirical in nature. First, Chapter 1 provides a brief introduction for the rest of the thesis. Next, Chapter 2 develops a new model of the effect of beta ambiguity in markets, both with and without non-ambiguous alternatives. The model predicts a drop in the premium of assets with an ambiguous beta once assets without ambiguity become available. We conclude the chapter by showing that inflation risk premium in the equity market drops once TIPS become available. Next, Chapter 3 presents a new model of information incorporation by an agent with a cost of updating beliefs. The model predicts both over- and under-reaction of prices to information. In addition, the model relates the strength of over- and under-reaction to signal extremeness and to beliefs variance. The chapter is concluded with empirical evidence of momentum and reversal that are manifested in the cross-section of equity. Finally, Chapter 4 proposes a new way of testing models of ambiguity aversion. We show theoretically that different models of ambiguity aversion generate different predictions in term of the preference for the timing and graduality of ambiguity resolution. We then develop an experimental framework and document preference for late and gradual resolution of ambiguity.

The three essays collected in this PhD dissertation concern agency costs, incentive contracts, mergers and acquisitions, and firm risk. The first essay demonstrates that manager sentiment, a managerial trait proxy for managerial optimism, can incur agency costs. The second and third essays state incentive contracts as an effective way to suppress agency problems and reduce agency costs. Specifically, the second essay demonstrates that firms using relative performance evaluation exhibit lower stock price crash risk and the third essay finds that relative performance evaluation increases long-term acquisition performance.

The four essays collected in this PhD thesis concern whether the market andnon-market solutions adopted by the Dutch government lead to a betterperformance of the energy efficient dwellings in the Dutch residential market. Inthe first essay we analyze the biggest information policy the energy performancecertificates (EPCs) and examine whether it has served as means to reduce theinformation asymmetry among market participants during the sale of homes.In the second essay I measure the extent to which energy efficiency benefits arepriced in the rental housing market, using a large dataset on the Dutch rentalmarket. In the third essay we establish whether energy performance certificationcan help banks to improve conventional mortgage risk models in predictingfuture arrears. And, in the fourth essay we evaluate the welfare effects of energyefficiency subsidies within the Dutch housing market.

The three essays collected in this dissertation relate to the microfoundations of audit quality. The first essay shows how auditors prioritize easy tasks and how this affects their judgment performance, and by extension audit quality. The second essay deals with how auditors learn in the workplace. The third essay investigates how auditors’ usage of automated tools and techniques affects their professional skepticism. Together, these essays shed light on how individual auditor behaviors, judgments, and decision-making can impact audit quality. By examining auditing from an operational perspective, these findings provide a more realistic understanding of the complexities of modern audit engagements and shed light on the microfoundations of audit quality. As regulators and policymakers continue to express concerns about audit quality, these studies offer actionable interventions that can help improve audit quality.

This dissertation contains three essays on different topics related to technology standards. The first essay studies the potential impact of unifying two incompatible standards for wireless networks on firms’ coverage investment choices, profits, prices, and consumer welfare in the U.S. wireless telecommunications market. The second essay exploits the patent policy change of a Standard Development Organization to quantify the effects of more restrictive (to technology developers) patent policies on the firms’ incentives to innovate in the context of technology standards. The third and final essay of the dissertation investigates the relationship between joining a standardization project and the firms’ patent portfolio choices.

The use of digital technologies for extracting information from various data sources can help organizations to reduce uncertainty and improve decision-making. The increasing availability in volume, velocity, and variety of data, however, can give rise to significant risks and challenges in ensuring a high level of information quality (IQ). Pre-digital organizations can be particularly susceptive to such challenges due to their limited experience with digital technologies and IQ governance. We adopt a theory-infused interventionist research approach to assist a pre-digital multinational military organization in navigating its digital transformation (DT) by focusing on IQ. We design and implement an IQ strategy (IQS) by drawing upon organizational information processing theory and examining how the level of IQ can affect the balance between information processing requirements and capacity. We demonstrate that an IQS that incorporates both technological, as well as IQ governance solutions, can support organizations in setting the scope of their DT, decreasing employees’ resistance to change, and increasing their satisfaction, while concurrently improving organizational efficiency. Our work stresses the importance of IQ in the digital era and delineates how pre-digital organizations can navigate DT by strategically addressing IQ.

This dissertation is a collection of four papers using non-standard preferences to better understand the behavior of asset prices and households. The first paper shows that present bias in an equilibrium model has the ability to explain multiple features of bond behavior. The second paper investigates the consequences of regret aversion for asset prices in an otherwise standard model of financial markets. The third paper combines experimentally elicited preferences with administrative microdata and explains actual annuitization decisions. The fourth paper demonstrates that risk and time preferences are time varying, and that they are related to trading behavior in an expected way.

Boekhouden in Balans - Belastingen, Omvorming en Consolidatie is speciaal samengesteld voor Tilburg University. Een deel komt uit bestaande boeken en een deel is samen met de docenten hiervoor ontwikkeld. In het deel Belastingen gaan we vooral in op de verschillen tussen de commerciële en fiscale jaarverslaggeving. Daarbij laten we de aangiftesoftware van de Belastingdienst zien. Deze is nodig voor de uitwerking van diverse voorbeelden en opgaven. Ook gaan we uitgebreid in op de verwerking van belastinglatenties in de commerciële jaarrekening. Bij het deel Omvorming nemen we enige voorkennis van de werking van de boekhouding van een handelsonderneming aan. We breiden deze uit naar ondernemingen met een omvormingsproces. Ook komt de projectadministratie van dienstverlenende ondernemingen aan de orde en vooral vanwege recente maatschappelijke ontwikkelingen gaan we uitgebreid in op de boekhouding van vrije beroepsbeoefenaars. We eindigen dit deel met een introductie van Enterprise Resource Planning. Het derde deel Consolidatie gaat over de ondernemingsrelaties. Veel ondernemingen bestaan uit een holding met een of meerdere werkmaatschappijen. Daarnaast bestaan nog allerlei verschillende structuren. De jaarrekeningen van de betrokken ondernemingen moeten soms wel of juist niet worden geconsolideerd. We bespreken zowel de situatie waarin een moedermaatschappij een 100%-belang heeft, als de situatie dat er geen 100%-belang is. De heldere schrijfstijl, vaste structuur, aanwezigheid van veel voorbeelden, volwaardige zelftoetsen en opgaven maken deze methode erg geschikt voor zelfstudie.

This dissertation contains three chapters on topics in experimental economics and the economics of crime. The first chapter studies gender and sex differences in uncertainty attitudes by following a broader and more inclusive concept of gender instead of the conventional binary approach. The second chapter investigates the extent to which the behavior of individuals is interrelated in terms of crime prevention. Specifically, it studies whether social contagion could explain why some visible crime prevention measures are highly popular in some areas but rarely used in others. The third chapter demonstrates the crime-reducing effect of private crime preventive measures. It studies the role of the "potential" victims and how their actions can deter crime.

Drawing on literature in auditing and workplace learning, this paper develops the Auditor Workplace Learning Framework. Based on a general workplace learning framework by Jacobs and Park (2009), the Auditor Workplace Learning Framework distinguishes auditor learning processes along three dimensions: the location of learning, the extent of planning involved in the learning process, and the role of the supervisor. We review the auditing literature, classifying papers that directly or indirectly improve our knowledge of auditor learning into our framework to identify gaps in our understanding of the auditor learning processes. Our study provides a comprehensive view of auditor learning processes and provides suggestions for future research aimed at improving auditor learning.

This thesis investigates how features of the tax system influence the behavior of business owners and their firms. The first chapter examines how differential taxation of personal and corporate income impacts firms’ legal form choice. The second chapter explores how closely held corporations and their owners respond to corporate tax incentives. Specifically, it investigates the main channels of adjustment, the main predictors of responsiveness, persistence in firms’ and director-owners’ behavior, and the link between personal and corporate taxable income optimization. Finally, the third chapter studies the effect of a fiscal stimulus policy that temporarily changed loss carry-back rules on small and medium corporations’ survival, employment, investments, and profits.

The present dissertation studies the effects of language and temporal focus on cognition, economic behaviour, and well-being. It mainly has three parts. In the first part, it investigates the direct relationship between language and temporal thinking as to whether users of different languages think about time differently. The results also show that, apart from linguistic influences, cultural and bodily experience can affect people’s conceptualisation of time. In the second part, it studies the relationship between temporal thought and various economic behaviour (e.g., pension planning, retirement savings, labour market performance), a healthy lifestyle (e.g., diet, smoking, disease) and overall wellbeing (financial satisfaction, happiness, life expectancy, financial wealth, etc.). Thirdly, it shows how language itself can be viewed as a form of capital that has a direct causal effect on economic and financial outcomes.

We investigate CEO power on corporate performance in Sri Lanka, characterized by ethno-linguistic and religious boundaries and complex power hierarchies, and by ethnic conflicts and a subsequent reconciliation process. We focus on a CEO’s social-dominance power, based on ethnicity, gender, and political connections. High social-dominance power (proxied by a lack of ethno-religious-linguistic and gender diversity) boosts agency conflicts and worsens corporate performance in the post-civil-war era. A firm’s financial performance also depends on ethno-linguistic board diversity. The paper demonstrates the importance of inclusiveness (in relation to ethnicity, religion, language, and gender) at the top decision and monitoring levels of corporations.

IntroductionLinear programming (LP) is often used within diet optimization to find, from a set of available food commodities, the most affordable diet that meets the nutritional requirements of an individual or (sub)population. It is, however, not always possible to create a feasible diet, as certain nutritional requirements are difficult to meet. In that case, goal programming (GP) can be used to minimize deviations from the nutritional requirements in order to obtain a near feasible diet. With GP the cost of the diet is often overlooked or taken into account using the ε-constraint method. This method does not guarantee to find all possible trade-offs between costs and nutritional deficiency without solving many uninformative LPs.MethodsWe present a method to find all trade-offs between any two linear objectives in a dietary LP context that is simple, does not solve uninformative LPs and does not need prior input from the decision maker (DM). This method is a bi-objective algorithm based on the NonInferior Set Estimation (NISE) method that finds all efficient trade-offs between two linear objectives.ResultsIn order to show what type of insights can be gained from this approach, two analyses are presented that investigate the relation between cost and nutritional adequacy. In the first analysis a diet with a restriction on the exact energy intake is considered where all nutrient intakes except energy are allowed to deviate from their prescription. This analysis is especially helpful in case of a restrictive budget or when a nutritionally adequate diet is either unaffordable or unattainable. The second analysis only relaxes the exact energy intake, where the other nutrients are kept within their requirements, to investigate how the energy intake affects the cost of a diet. Here, we describe in what situations the so-called more-for-less paradox takes place, which can be induced by requiring an exact energy intake.ConclusionTo the best of our knowledge, we are the first to address how to obtain all efficient trade-offs of two linear objectives in a dietary LP context and how this can be used for analyses.

Audit firms increasingly employ automated tools and techniques in auditing procedures. The premise of using automation is that it increases audit effectiveness and audit efficiency. For these effectiveness and efficiency gains to materialize, auditors need to use automation in an adequate manner. Regulators, however, have raised concerns that auditors may over- or under-rely on automation. I predict that auditors are subject to an automation bias and use cues from automated tools and techniques as a replacement for vigilant information seeking, thereby reducing professional skepticism when relying on automation. My findings are in line with my predictions. When auditors rely on work conducted by automated tools and techniques, they are less skeptical than when relying on the same work conducted by an audit team member. Based on psychology theory, I employ a counterarguing mindset intervention that alleviates the negative effects of automation on professionally skepticism. Finally, I also test whether a reduction in vigilance caused by automation usage spills over to subsequent tasks. I do not find evidence indicating a spillover effect. Implications for practice and theory are discussed.

Institutional investors’ exposure to private market funds exceeds 12 trillion US dollars. Despite this and contrary to public markets, little is known about the extent and determinants of ESG transparency in private markets. Using a novel dataset, we investigate ESG disclosures in the increasingly important private equity and debt markets. Consisting of 4150 private equity and private debt firms and capturing 82% of the global PE and PD funds raised over the past 10 years, our sample allows us to investigate 37 ESG disclosure indicators that are most relevant to the setting of private capital markets. We find an overall low and heterogeneous level of ESG disclosure. The median GP discloses only 8% of the available ESG indicators, implying that GPs are significantly less transparent than public firms. Larger, listed, older, and more recently fund-raising GPs, as well as GPs headquartered in Developed Europe are more transparent. Analyzing firm-, portfolio- and asset-level ESG transparency, we provide evidence that portfolio-level ESG characteristics as well as a GP’s investor base are each significantly associated with GPs’ ESG disclosures.

Smart Contracts enable the automated execution of exchanges on the blockchain. From an ontological perspective, smart contracts create and automate the fulfillment of social commitments between actors. Whereas traditional deontic logic is used to make a legal determination in contractual multi-actor interactions, this paper focuses on the consequences of these actions resulting from that determination, thereby shifting the focus from monitoring to execution. The interactions between actors and the consequences in terms of commitments have not yet been formalized for smart contracts. The perspective of smart contracts is interesting, since they are considered to be autonomous agents, able to generate automated actions. We use the Event Calculus as a formal logic to represent and reason about the effects of these automated actions and the resulting commitments. Since the Event Calculus deals with local events and the consideration of time, this approach enables the uniform representation of commitments, including their operations and reasoning rules.

We study how differential taxation of personal and corporate income impacts the corporate share of new firms for 31 countries over 1998–2018. We build a novel database that identifies the tax treatment of partnerships either as corporations or as passthrough entities. We find a tax elasticity of 0.07 for the period 1998–2007 and of 0.12 for 2008–2018. Estimates are larger for countries where the presence of partnerships is nonnegligible and where they are treated as passthrough for tax purposes, suggesting that the tax sensitivity of organizational-form choice interacts with the relevance of partnerships and their tax treatment.

We study the quadratic cycle cover problem (QCCP), which aims to find a node-disjoint cycle cover in a directed graph with minimum interaction cost between successive arcs. We derive several semidefinite programming (SDP) relaxations and use facial reduction to make these strictly feasible. We investigate a nontrivial relationship between the transformation matrix used in the reduction and the structure of the graph, which is exploited in an efficient algorithm that constructs this matrix for any instance of the problem. To solve our relaxations, we propose an algorithm that incorporates an augmented Lagrangian method into a cutting-plane framework by utilizing Dykstra’s projection algorithm. Our algorithm is suitable for solving SDP relaxations with a large number of cutting-planes. Computational results show that our SDP bounds and efficient cutting-plane algorithm outperform other QCCP bounding approaches from the literature. Finally, we provide several SDP-based upper bounding techniques, among which is a sequential Q-learning method that exploits a solution of our SDP relaxation within a reinforcement learning environment. Summary of Contribution: The quadratic cycle cover problem (QCCP) is the problem of finding a set of node-disjoint cycles covering all the nodes in a graph such that the total interaction cost between successive arcs is minimized. The QCCP has applications in many fields, among which are robotics, transportation, energy distribution networks, and automatic inspection. Besides this, the problem has a high theoretical relevance because of its close connection to the quadratic traveling salesman problem (QTSP). The QTSP has several applications, for example, in bioinformatics, and is considered to be among the most difficult combinatorial optimization problems nowadays. After removing the subtour elimination constraints, the QTSP boils down to the QCCP. Hence, an in-depth study of the QCCP also contributes to the construction of strong bounds for the QTSP. In this paper, we study the application of semidefinite programming (SDP) to obtain strong bounds for the QCCP. Our strongest SDP relaxation is very hard to solve by any SDP solver because of the large number of involved cutting-planes. Because of that, we propose a new approach in which an augmented Lagrangian method is incorporated into a cutting-plane framework by utilizing Dykstra’s projection algorithm. We emphasize an efficient implementation of the method and perform an extensive computational study. This study shows that our method is able to handle a large number of cuts and that the resulting bounds are currently the best QCCP bounds in the literature. We also introduce several upper bounding techniques, among which is a distributed reinforcement learning algorithm that exploits our SDP relaxations.

This paper considers sequencing situations with non-linear cost functions under optimal order consistency. Specifically, we study sequencing situations with discounting cost functions and logarithmic cost functions of the completion time. In both settings, we show that the neighbor switching gains are non-negative and non-decreasing for every misplaced pair of players. We derive new conditions on the time-dependent neighbor switching gains in a sequencing situation under optimal order consistency to guarantee convexity of the associated sequencing game. Furthermore, we define two types of gain splitting rules for the class of sequencing situations under optimal order consistency. Each one of them is based on a procedure that specifies a path from the initial order to an optimal order, dividing the neighbor switching gains in every step among the two involved players. We prove that these allocations are stable under the same conditions that are required for convexity. These requirements are fulfilled for discounting and logarithmic sequencing situations, as well as in other settings, such as in sequencing situations with exponential cost functions. Ministerio de Ciencia, Innovación y Universidades | Ref. MTM2017-87197-C3-2-P Ministerio de Ciencia, Innovación y Universidades | Ref. MTM2017-87197- C3-3-P Xunta de Galicia | Ref. ED431C- 2016-040 Xunta de Galicia | Ref. ED431C-2017/38 Xunta de Galicia | Ref. ED431C2020-03

This paper reports three studies examining easy task prioritization among auditors. The first study is a survey of auditors providing evidence that auditors perceive easy task prioritization to be a threat to audit quality, yet auditors do expect other auditors to prioritize easy tasks. In our first experiment, we find that auditors indeed prioritize easy tasks. Easy task prioritization is also exacerbated under time pressure. We further find that psychological ownership is only able to alleviate easy task prioritization in low time pressure conditions, but not in high time pressure conditions. In our second experiment, we find that prioritizing the easy task leads to lower judgment performance, and by extension, audit quality. The performance detriment of easy task prioritization manifests itself in the difficult task, and in particular in finding errors for which more cognitive processing is needed. Combined, our studies document easy task prioritization in auditing, the audit quality implications, and the role of time pressure and psychological ownership.

We estimate the causal effects of 334 different types of health shocks on medical expenses, mortality, disability, labor market participation, labor earnings, and the need for nursing home care using detailed data on 6.9 million people diagnosed by medical specialists between 2013 and 2017. We quantify the benefits of eliminating diseases with distinct consequences for people of different social strata by incorporating the estimates into a standard life-cycle model. Our results reveal substantial heterogeneity in welfare gains by types of disease for different people. We discuss the potential implications of our results for the financing of medical research.

Consider the problem of minimizing a polynomial $f$ over a compact semialgebraic set ${\mathbf{X} \subseteq \mathbb{R}^n}$. Lasserre introduces hierarchies of semidefinite programs to approximate this hard optimization problem, based on classical sum-of-squares certificates of positivity of polynomials due to Putinar and Schm\"udgen. When $\mathbf{X}$ is the unit ball or the standard simplex, we show that the hierarchies based on the Schm\"udgen-type certificates converge to the global minimum of $f$ at a rate in $O(1/r^2)$, matching recently obtained convergence rates for the hypersphere and hypercube $[-1,1]^n$. For our proof, we establish a connection between Lasserre's hierarchies and the Christoffel-Darboux kernel, and make use of closed form expressions for this kernel derived by Xu., Comment: v2: implemented minor changes based on reviewer comments. 22 pages, 3 figures

Corporate financial distress is fascinating, as in times of adversity, managers have an outsized impact on whether their organization will overcome its financial hardship, or if it is closer to bankruptcy. Although the management literature recognizes the importance of managers’ actions in shaping organizational outcomes, their behavior in the context of corporate financial distress is less understood. Besides contributing to a variety of academic literatures, practitioners benefit from the dissertation’s insights as it allows them to better aid organizations and their leadership to (potentially) respond to financial woes.This dissertation contains five chapters, out of which three empirical chapters. Each chapter is focused on the cognition, emotion, and/or behavior of CEOs which face organizational financial distress. Chapter two explores how mental schema affect organizations’ ability to shift their focus of attention in response to a crisis. The third paper contrasts formal ownership with psychological ownership, in which I examine the emotions managers display in response to a failure to meet aspirations, and how this relationship depends on formal ownership (e.g., owning shares) and feelings of ownership (i.e., psychological ownership). The fourth chapter investigates what verbal communication strategies TMT members use when they face a potential downgrade. I find that the incongruence between emotions in the tone of their voice and the sentiment in their wording affects the likelihood of receiving a downgrade.

While eigenvalues of graphs are well studied, spectral analysis of complex unit gain graphs is still in its infancy. This thesis considers gain graphs whose gain groups are gradually less and less restricted, with the ultimate goal of classifying gain graphs that are characterized by their spectra. In such cases, the eigenvalues of a gain graph contain sufficient structural information that it might be uniquely (up to certain equivalence relations) constructed when only given its spectrum. First, the first infinite family of directed graphs that is – up to isomorphism – determined by its Hermitian spectrum is obtained. Since the entries of the Hermitian adjacency matrix are complex units, these objects may be thought of as gain graphs with a restricted gain group. It is shown that directed graphs with the desired property are extremely rare. Thereafter, the perspective is generalized to include signs on the edges. By encoding the various edge-vertex incidence relations with sixth roots of unity, the above perspective can again be taken. With an interesting mix of algebraic and combinatorial techniques, all signed directed graphs with degree at most 4 or least multiplicity at most 3 are determined. Subsequently, these characterizations are used to obtain signed directed graphs that are determined by their spectra. Finally, an extensive discussion of complex unit gain graphs in their most general form is offered. After exploring their various notions of symmetry and many interesting ties to complex geometries, gain graphs with exactly two distinct eigenvalues are classified.

Millions of nanostores around the world face the prospect of digitization, which promises to create significant operational benefits. At the same time, however, digitization may be a risky endeavor. Through the application of a survey and vignette experiments in the field with hundreds of shopkeepers, we explain the perceptions and behavioral processes that shopkeepers incorporate in deciding whether to digitize their operations by adopting smartphone-based technology. We identify two main factors that influence shopkeepers' decision making: Tax Privacy Concerns and Cost. For the first one, given the informal status of nanostores, shopkeepers exhibit privacy concerns for their operational data vis-à-vis the government. Further, we show that the Cost of a technology represents a significant barrier. Both of these features reduce the likelihood that shopkeepers will digitize, thus overshadowing expected productivity gains. Nevertheless, shopkeepers seem willing to digitize, provided technology adds enough value. Finally, we find that both creating positive word of mouth that data are unlikely to be shared with tax authorities and reducing the price of digital technologies help boost digitization.

The Diet Optimization Problem is a classical Linear Programming problem which finds, from a set of available food commodities, the most affordable diet that meets an individual’s nutritional requirements. It is, however, not always possible to create a feasible diet, as certain nutritional requirements are difficult to be met (e.g. iron for adolescent females). In that case, Goal Programming is used to minimize nutritional deviations in order to obtain a near feasible diet. The cost of the diet is, however, often overlooked or neglected. Therefore, we focus in our paper on finding all tradeoffs between the cost and nutritional adequacy of a diet. To do so, we present a bi-objective approach based on the NISE method that is able to find all efficient tradeoffs between two linear objectives. To the best of our knowledge, this approach bridges the current gap between diet optimization and multicriteria optimization, as we are the first to address how to obtain all efficient trade-offs of two linear objectives in a dietary context. In order to show what type of insights can be gained from this approach, two analyses are presented using data collected in Ebonyi, Nigeria. In the first analysis a diet with a restriction on the exact energy intake is considered where all nutrient intakes except energy are allowed to deviate from their prescription. This analysis is especially helpful when one needs to make decisions in case there is a restrictive budget or when a nutritionally adequate diet is either unaffordable or unattainable. The second analysis only relaxes the exact energy intake, where the other nutrients are kept within their requirements, to investigate how the energy intake affects the cost of a diet. Here, we describe in what situations the so-called more-for-less paradox takes place, which can be induced by the exact energy intake.

The goal of a mathematical optimization problem is to maximize an objective (or minimize a cost) under a given set of rules, called constraints. Optimization has many applications, both in other areas of mathematics and in the real world. Unfortunately, some of the most interesting problems are also very hard to solve numerically. To work around this issue, one often considers relaxations: approximations of the original problem that are much easier to solve. Naturally, it is then important to understand how (in)accurate these relaxations are. This thesis consists of three parts, each covering a different method that uses semidefinite programming to approximate hard optimization problems. In Part 1 and Part 2, we consider two hierarchies of relaxations for polynomial optimization problems based on sums of squares. We show improved guarantees on the quality of Lasserre's measure-based hierarchy in a wide variety of settings (Part 1). We establish error bounds for the moment-SOS hierarchy in certain fundamental special cases. These bounds are much stronger than the ones obtained from existing, general results (Part 2).In Part 3, we generalize the celebrated Lovász theta number to (geometric) hypergraphs. We apply our generalization to formulate relaxations for a type of independent set problem in the hypersphere. These relaxations allow us to improve some results in Euclidean Ramsey theory.

Climate change policies are often met with resistance due to fears over the loss of competitiveness and employment. This paper studies the effect of energy prices, which are a proxy for a carbon tax, on the labor share of income and industry concentration. Using aggregated administrative data from 15 European countries and 56 sectors for the years 2000-2016, and applying a shift-share instrumental variable approach, we find that the energy price has a negative and quantitatively significant effect on the labor share. Exploring the potential mechanisms, we document strong evidence that the degree of substitution between energy and labor is lower than the substitution between energy and capital. Reallocation among firms, changes in aggregate markups or the value-added to output ratio induced by energy price shocks do not lead to sizable changes in the labor share. We find no robust evidence that energy prices affect industry concentration and markups. These results indicate sizable potential redistributional impacts of climate change policies, at least in the short-run, as the transitional costs differ across the primary factors.

De kwaliteit van wettelijke accountantscontroles in Nederland is al een aantal jaren onderwerp van een verhitte discussie. Zowel het kabinet, accountantsorganisaties, de Nederlandse Beroepsorganisatie van Accountants (NBA), als de Autoriteit Financiële Markten (AFM) hebben vergaande verbetermaatregelen aangekondigd om te werken aan een betere controlekwaliteit. Dit roept de vraag op hoe het met de controlekwaliteit in Nederland gesteld is en hoe deze zich in de afgelopen jaren heeft ontwikkeld. Controlekwaliteit is een complex en veelzijdig begrip dat bestaat uit een input-, proces-, en uitkomstniveau. In dit onderzoek richt ik mij op het uitkomstniveau van wettelijke controles: de verslaggevingskwaliteit van de gecontroleerde jaarrekening. Ik doe dit op basis van een veelgebruikte maatstaf uit de wetenschappelijke literatuur: discretionaire accruals. Resultaten tonen aan dat de uitkomstkwaliteit van wettelijke controles van beursvennootschappen in de periode 2000–2018 significant is gestegen.

Environmental, social and governance (“ESG”) scores have been widely touted as indicators of share price resilience during the COVID-19 crisis Contrary to this conventional wisdom, we present robust evidence that once industry affiliation, market-based measures of risk and accounting-based measures of performance, financial position and intangibles investments have been controlled for, ESG offers no such positive explanatory power for returns during the COVID crisis Specifically, ESG is insignificant in fully specified returns regressions for each of the Q1 2020 COVID market crisis period and for the full COVID year of 2020 By contrast, a measure of the firm's stock of investments in internally generated intangible assets is an economically and statistically significant positive determinant of returns during each of the Q1 market implosion and full 2020 COVID year periods Our results are robust to alternative measures of returns, as well as for using Refinitiv, Refinitiv II and MSCI data to capture ESG performance We conclude that ESG did not immunize stocks during the COVID-19 crisis, but those investments in intangible assets did © 2021 The Authors Journal of Business Finance & Accounting published by John Wiley & Sons Ltd

An important and widely used class of semiparametric models is formed by the varying-coefficient models. Although the varying coefficients are traditionally assumed to be smooth functions, the varying-coefficient model is considered here with the coefficient functions containing a finite set of discontinuities. Contrary to the existing nonparametric and varying-coefficient estimation of piecewise smooth functions, the varying-coefficient models are considered here under dependence and are applicable in time series with heteroskedastic and serially correlated errors. Additionally, the conditional error variance is allowed to exhibit discontinuities at a finite set of points too. The (uniform) consistency and asymptotic normality of the proposed estimators are established and the finite-sample performance is tested via a simulation study and in a real-data example.

In the past 50 years, almost one million U.S. students have been present on school grounds during a shooting. This paper examines the long-term and intergenerational effects of school shootings on earnings, educational attainment, and mobility. I find that exposure to a school shooting decreases survivors’ hourly wage by 20:8% and these effects persist over their lifetime. Furthermore, I show that the effect of school shootings lasts even beyond the initially treated and has detrimental effects on their children. I find that having shooting-exposed parents decreases children’s hourly wage by 18:8%.