Miracle-dz/UniFAR-FTUs huggingface dataset:
A General Framework for the Identification and Categorization of Risks - An Application to the Context of Financial Markets

Risk represents a significant part of humans' interaction and has to be considered in various decision-making processes across diverse business and research areas. Furthermore, the disregard or non-awareness of certain risks may result in inappropriate decision-making processes and inadequate risk management practices which may negatively influence firms' performances. Thus, to the best of our knowledge, this paper is the first to develop an algorithmic-based and generally applicable framework that generates an extensive and integrated identification and categorization scheme of certain risks, using text mining and machine learning approaches. To demonstrate the applicability of our framework, we exemplarily apply our derived approach to the context of financial markets. Hence, we identify 193 financial market risks and categorize them into five categories by using common machine learning techniques. To evaluate the general applicability, we additionally apply the derived framework to the context of information systems. Finally, we give strong indications regarding robustness and superiority of our derived framework by benchmarking it against more manual risk identification techniques and other clustering approaches.
Washington Consensus Reforms and Economic Performance in Sub-Saharan Africa: Lessons From the Past Four Decades

Over three decades after market-oriented structural reforms, termed "Washington consensus" policies, were first implemented, we revisit the evidence on policy adoption and the effects of these policies on socio-economic performance in sub-Saharan African countries. We focus on three key ubiquitous reform policies around privatization, fiscal discipline, and trade openness and document significant improvements in economic performance for reformers over the past two decades. Following initial declines in per capita economic growth over the 1980s and 1990s, reform adopters experienced notable increases in per capita real GDP growth in the post 2000 period. We complement aggregate analysis with four country case studies that highlight important lessons for effective reform. Notably, the ability to implement pro-poor policies alongside market oriented reforms played a central role in successful policy performance.
Overview and Inventory of French Funds' Liquidity Management Tools

This article constitutes a first presentation of the prospectus analysis tool developed through a cooperation between the Banque de France and the Autorité des marchés financiers (AMF). This work aims to identify the liquidity management tools (LMT) implemented funds regulated by the AMF under French law (“French funds”). This work is part of a logic to follow up on IOSCO recommendations (2018) to strengthen the overall liquidity risk management framework in line with the recommendations adopted by the FSB (2017). In order to better manage the liquidity risk of investment funds, numerous measures are provided for by international texts, and imposed at the level of European Directives and Regulations governing funds and management companies or recommended by ESMA. In addition to the rules for monitoring and managing liquidity, certain tools can be used in normal times or in times of stress, in order to limit the risks of fire-sales or to mitigate their impact. This paper presents these liquidity management tools as precisely as possible and describes the appropriation of these tools by French funds at the end of 2019, based on a textual analysis of the prospectuses.
Consumer Online Search with Partially Revealed Information

Modern-day search platforms generally have two layers of information presentation. The outer layer displays the collection of search results with attributes selected by platforms, and consumers click on a product to reveal all its attributes in the inner layer. The information revealed in the outer layer affects the search costs and the probability of finding a match. To address the managerial question of optimal information layout, we create an information complexity measure of the outer layer, namely orderedness entropy, and study the consumer search process for information at the expense of time and cognitive costs. We first conduct online random experiments to show that consumers respond to and actively reduce cognitive cost for which our information complexity measure provides a representation. Then, using a unique and rich panel tracking consumer search behaviors at a large online travel agency (OTA), we specify a novel sequential search model that jointly describes the refinement search and product clicking decisions. We find that cognitive cost is a major component of search cost, while loading time cost has a much smaller share. By varying the information revealed in the outer layer, we propose information layouts that Pareto-improve both revenue and consumer welfare for our OTA. This paper was accepted by Juanjuan Zhang, marketing.
When Are Sharks Dangerous? Timing of CVC Investments and Ventures’ Commercial Performance

The evidence on how corporate venture capital (CVC) investments affect investee ventures’ commercial performance is mixed. An examination of the timing of CVC investments can partially explain the effect’s variation. Previous studies showed that the timing of ventures’ resource acquisition is crucial for venture outcomes. However, these studies have overlooked the role of incumbents as a resource channel and the tradeoffs associated with timing. Building on resource dependence theory (RDT), we explore how the timing of CVC investments alters the power balance between investors and backed ventures, significantly influencing ventures’ commercial performance. We further examine how the timing of venture board seats obtained by CVC investors affects this relationship. Using a dataset of 294 Norwegian ventures active in knowledge-intensive industries from 2004 to 2015, we offer evidence for a differential effect of early- vs. late-stage CVC investments, showing that late-stage investments significantly increase commercial performance. We also find that associating a venture board seat with a CVC investment moderates this effect; ventures are associated with greater performance when late-stage investments come without board seats.
Value Investing: Requiem, Rebirth or Reincarnation?

For much of the last century, value investors considered themselves to be the winners in the investment world, a result they attributed to their patience, maturity and good sense. That view, at least on the surface, was backed up by evidence that “value” stocks, defined as stocks that trade at low multiples of earnings and book value, earned higher returns than “growth” stocks, defined loosely as companies that trade at high multiples of earnings or book value. It was reinforced by the mythology of great value investors, with Warren Buffett and Charlie Munger taking center stage, as deep thinkers, with profound insights on how markets work. In the last two decades, value investing lost its edge, and a debate has revolved around whether this is a temporary phase, and the result of an unusual macro environment, or a reflection of a permanent change in economies and markets. In this paper, we argue that value investing, at least as practiced today, has become rigid and ritualistic, and that while some of its failures can be attributed to external factors, many can be traced back to practices and rules of thumb that have outlived their usefulness. We argue that if value investing is to be successful in the future, it needs to develop a more dynamic view of value and a greater willingness to live with and invest in the face of uncertainty.
Does the Disclosure of Unrecognized Tax Benefits Affect Investor Uncertainty?

We examine whether the disclosure of tax-related uncertainty through unrecognized tax benefits (UTBs) resolves or exacerbates investors’ uncertainty about firm value based on evidence from investor trading behavior and information asymmetry around the time of the disclosure. We find that current year UTB additions are associated with reduced trading activity around the release of the 10-K and wider bid-ask spreads in the days following the 10-K release. Our results suggest that UTB additions increase investor uncertainty and investors impound the information contained in UTBs into prices with a delay. Moreover, we find that our results are concentrated in firms with weaker information environments and firms with less sophisticated investors, suggesting that UTBs are differentially informative for different groups of investors. Taken together, our results suggest that UTB disclosures increase short-term investor uncertainty about future firm value, particularly for less sophisticated investors, contrary to the FASB’s goal of increasing the relevance and transparency of accounting for uncertain tax positions.
Target Search in Product Displays: A Visual Crowding Perspective

Consumers often arrive at the point of purchase with a particular product to purchase in mind and must search for this target product in the product display. Drawing on visual crowding theory, we suggest that an individual’s ability to find a target product in a display varies according to the embeddedness of the target, which depends on the locations of the target and non-target products in the display. We refer to the visual impact of non-target products on target products that results in an inability to differentiate and recognize the target product as “target visual crowdedness (TVC). ” Across five experimental studies, we manipulate TVC and show that as TVC increases the duration of the visual search increases. Eye-tracking data provide evidence of how TVC affects attention and information processing in target product search tasks. We develop a visual crowdedness metric that quantifies TVC and can be used by researchers and practitioners to estimate the visual search effort needed to find a product in a display.
Service Delivery and Customers’ Satisfaction in Public Organizations: A Case of Registration Insolvency and Trusteeship Agency (RITA)

Provision of quality services which meet customers’ expectations is very crucial for every organization; it increases trust and loyalty of the services provided as well as organization competitiveness in the market. However, most of public organizations seem to offer low quality services by considering time taken to deliver the service, flexibility and transparency as well as cost effectiveness. Therefore, this study aimed at assessing the service delivery and customer’s satisfaction in public organizations in Tanzania drawing experience from Registration Insolvency and Trusteeship Agency (RITA). SERVQUAL model was employed using five dimensions; (tangibility, empathy, reliability, responsiveness and assurance) and primary data from 200 sampled respondents from four districts of Dar es Salaam region. The model summary of regression analysis shows that independent variable tangibility, reliability, and assurance are statistically significant to influence customer’s satisfaction (the significant value is below 5%). This indicates improvement of SERVQUAL dimension multi-items of the tangibility, reliability, and assurance such as working facilities and good personnel skills increases the level of customer satisfaction on the services provided by RITA. Though responsiveness and empathy has positive impact on customer’s satisfaction, they are not statistically significant to influence customers’ satisfaction. The study concludes that public organizations should do its best to improve customer’s satisfaction. The three broad areas that the study recommends includes improvement in services quality, reduction of services gap and increase customers’ awareness and accessibility to the services.
Blockchain-Powered New Generation of Global B2B Platforms: A Conceptual Approach

This paper lays out conceptual groundwork for the new generation of business-to-business (B2B) exchange platforms. Latest technological advances including blockchain, smart contracting, and digital currency force significant changes in the current state of the electronic commerce by offering solutions to numerous problems faced by B2B firms. We develop a conceptualization for the decentralized B2B platform that builds upon blockchain-related technological change. We show that the new B2B architecture can overcome frictions distorting the existing state of the B2B environment including: <br><br>(1) need for trust and relationship building for sustainability and survival, <br><br>(2) quality shirking, <br><br>(3) payment fraud, <br><br>(4) charge-backs, <br><br>(5) barriers to entry, <br><br>(6) post-sales disputes, and <br><br>(7) product recall. <br><br>An equally important aspect of our model is that the new generation of B2B platforms create substantial positive network externalities for the interconnected businesses globally. Overall, the proposed infrastructure should have positive revenue consequence for the B2B commerce worldwide, as well as positive externality value to the society at large.
When Aiyagari meets Piketty: Growth, Inequality and Capital Shares

We incorporate the division of income between capital and labor into analysis on the relationship between inequality and growth. Using historical data, we document that changes in the top 1 % income shares are positively associated with subsequent growth of per capita GDP when the capital share of income is low, whereas under high capital share, the association is negative. We show that these findings are compatible with a theoretical analysis that emphasises how changes in the distribution of income translate into the accumulation of capital and overall economic activity through the interplay between precautionary saving motives and consumption smoothing. We also investigate how accounting for financial frictions affects our main findings.
Do Firms' IT Applications Provide Insights that Help Investors Better Understand the Underlying Valuation Attributes of R&D Information?

Firm websites are among the most visible information technology (IT) applications and the primary platforms to conduct e-commerce or online strategy. This research examines the critical role of firm website usage in facilitating firm innovation success and market value. It also addresses the potential differential effects of firm characteristics. With a sample of 2,840 U.S. firms, we report that firm website usage can significantly moderate the firm R&D investment–performance relationship. In addition, the moderating effect is heterogeneous, depending on firm customer type and capital intensity, and is greater for business-to-consumer (B2C) firms and firms with higher capital intensity. Further clustering analysis identifies that these differential effects are more pronounced for small firms. The findings of this study suggest that firm website usage conveys valuation relevant information that can help investors better interpret the reported R&D expenditure for insights into firm innovation success and market value.
Beware of Toothless Tigers: Institutionalizing Whistleblowing May Crowd Out Compliance

Internal whistle-blowing systems are supposed to fight misconduct within organizations. Because it is difficult to study their efficacy in the field, scientific evidence on their performance is rare. This is problematic, because these systems bind substantial resources and might generate the erroneous impression of compliance in a company in which misconduct is prevalent. We therefore suggest a versatilely extendable experimental workhorse that allows the systematic study of internal whistle-blowing systems in the lab. As a first step, we tested the efficacy of whistle-blowing systems if internal punishment for misconduct is mild and hesitant which is usually the case in practice, as several fraud surveys confirm. Our results show that under these conditions almost nobody blew the whistle, and misconduct occurred even more frequently with than without a whistle-blowing system. The institutionalization of whistle-blowing seemed to crowd out the intrinsic motivation to act compliantly. Moreover, when a whistle-blowing system was either unavailable or not used, misconduct was highly contagious and spread quickly. Yet, when we implemented severe and ensured punishment for misconduct, whistle-blowing systems could deter wrongdoing. In such a setting, people were willing to blow the whistle and the prevalence of misconduct dropped substantially. Altogether, our results highlight the interaction between institutions and preferences and can support the design of compliance measures within organizations. For compliance managers a key takeaway is that if companies preach a zero-tolerance policy, they should practice it as well. Otherwise, they might even worsen the situation.
Bond Power Exchange Options

We study power exchange options written on zero-coupon bonds under a stochastic string framework. We obtain closed-form expressions for pricing and hedging bond power exchange options and, as particular cases, the corresponding expressions for call power options and constant underlying elasticity in strikes (CUES) options. Sufficient conditions for the equivalence of the European and the American versions of bond power exchange options are provided and the put-call parity relation for this kind of option is also stated. Finally, we consider several applications of our results including duration and convexity measures for bond power exchange options, pricing extendable/accelerable maturity zero-coupon bonds, options to price a zero-coupon bond off of a shifted term-structure, and options on interest rates and rate spreads.
A Machine Learning Approach to Price Indices: Applications in Real Estate

This paper proposes a methodology for using machine learning regression models to create price indices. In our study we developed six commercial real estate price indeces for the city of New York from year 2000 to 2019. The regression models used in this study are eXtreme Gradient Boosting Tree (XGBT), Support Vector Regression (SVR) and averaged Neural Networks (avNNet). The benchmark for comparison of the results is Ordinary Least Squares (OLS). <br><br>There are two main index methodologies, a chained, where the index is constructed using out-of-sample data, and a pooled, where the index is constructed using in-sample data. The two main index methodologies can be divided into sub categories that utilizes a Paasche and Laspeyres like index formulations. <br><br>Another important factor included in this study is the size, in years, of the optimal training window for building the index. The results show that the machine learning approach produced, overall, lower estimation errors. Nevertheless, these lower estimation errors not always constitutes a more stable index. Additionally, all models, including the benchmark, are sensitive to the training window size regarding the out-of-sample estimation error. <br>
Jumps in Commodity Prices: New Approaches for Pricing Options.

We present a new term-structure model for commodity futures prices based on Trolle and Schwartz (2009) which we extend by incorporating multiple jump processes. Our work explores the valuation of plain vanilla options on futures prices when the spot price follows a log-normal process, the forward cost of carry curve and the volatility are stochastic variables, and the spot price and the forward cost of carry allow for time-dampening jumps. We obtain an analytical representation of the characteristic function of the futures prices and, hence, also for plain vanilla option prices using the fast Fourier transform (FFT) methodology. We price options on WTI crude oil futures contracts using our model and extant models. We obtain higher accuracy than earlier models and save significantly in computing time. <br>
New Technologies, Automation, and Labor Markets

This paper demonstrates the causal effect of new technologies on the U.S. labor market. I employ information and communications technology, and robot penetration, as two proxy for new technologies to assess the effect of automation on 795 occupations across 450 industries between 2004 and 2016. New technologies reduce the annual growth rate of occupation at risk of automation by 1.8–2.8% relative to risk-less occupations. I demonstrate causality using the differential effect of technology capital, instrumented by E.U. capital, on occupations with different risks of automation. Sector-year dummies control for Chinese and Mexican imports, the Great Recession, and conventional capital. Trade evidence reassures my results.
The Welfare Costs of HIV/AIDS in Eastern Europe: An Empirical Assessment Using the Value-of-Life Approach

Rationale: International priority setting in the fight against global epidemics calls for new approaches to quantify the effects of diseases on entire economies and groups of countries. Objective: We aim to estimate the full social costs of HIV/AIDS in Eastern Europe, using the willingness-to-pay approach. Methodology: Based on the aggregation of individual willingness-to-pay for a statistical life without HIV/AIDS, we calibrate an intertemporal optimization model to determine the welfare losses from HIV/AIDS in 25 Eastern European countries. The calculations are based on the average per-capita income in each country, which explains why even in countries with a relatively low HIV-prevalence, the welfare losses from HIV/AIDS are already too big to be ignored. Results: Assuming a discount rate of three percent, we find a total welfare loss for the whole region of 1.2 trillion US-$ which amounts to approximately 16 percent of the region's annual GDP between 1995 and 2001. This probably underestimates the true welfare costs of HIV/AIDS, because the calculation does not include the suffering of HIV-positive individuals prior to death. Taking into account the high level of education in large parts of the population of Eastern European countries, we also calibrate a human-capital-scenario in which an individual's income is distributed unevenly across the lifecycle and assumed to peak at around 35 years. In this case, the welfare losses turn out to be even higher. Overall, prevalence and incidence rates diverge sharply between countries with Central Europe still far less affected than the major countries in the Commonwealth of Independent States and the Baltics. Conclusions: Prevalence rates of HIV/AIDS in Eastern Europe have been rising rapidly since 1994 and the epidemic is likely to spread to less affected countries unless a coherent strategy of prevention and treatment is backed up by substantial increases in health care investments. The sheer size of this task and the international nature of the epidemic render this one of the most important current challenges for all of Europe. Our estimates provide some evidence to inform policy makers about the likely social payoff from reductions in prevalence and infection rates that specific measures might achieve.