Research articles for the 2021-08-09

A Critical Examination of the Effect of Size on the Profitability of Insurance Brokerage Firms in Ghana
Kotey, Richard,Owusu-Sekyere, Franklin,Amponsah, Daniel
This paper takes a critical look at the effect of firm size on the profitability of Ghanaian Insurance brokerage firms. Specifically, the paper examined the effect of firm size (measured by total assets) on firm profitability (measured by ROA and ROE) from a lagged perspective (i.e. the lagged effect of size), non-linear perspective, and across quantiles, using fixed effects, random effects, robust and PCSE estimation techniques. Analyzing a unique data of 64 insurance brokers from 2007 to 2015, the findings show that firm size exhibited a significant and positive short term effect on firm profitability but the relationship turned negative in the long term showing a non-linear relationship of size on profitability, with an inflection point above the mean firm size. However, the non-linear effect was evident in the 50th and above percentile of brokers but not in the lower quantiles. The lagged values of size also significantly affected firm profitability but it was not as pronounced as the short-term effects. The study recommends larger Ghanaian insurance brokerage firms take a staggered and reflective approach in its growth measures.

A Tiering Rule to Balance the Impact of Negative Policy Rates on Banks
Girotti, Mattia,Nguyen, Benoît,Sahuc, Jean-Guillaume
Negative interest rate policy makes excess liquidity costly to hold for banks and this may weaken the bank-based transmission of monetary policy. We propose a rule-based tiering system for excess reserve remuneration that automatically adjusts for changes in the overall volume of excess reserves. This system is designed to reduce the burden of negative rates on banks while ensuring that the central bank keeps control of interbank rates. Using euro-area data, we show that under the proposed tiering system, the cost of holding excess liquidity when the COVID-19 monetary stimulus fully unfolds would be more than 30% lower than that under the ECB's current system.

Agricultural Growth Diagnostics: Identifying the Binding Constraints and Policy Remedies for Bihar, India
Elumalai Kannan,Sanjib Pohit

Agriculture plays a significant role in economic development of the underdeveloped region. Multiple factors influence the performance of agricultural sector but a few of these have a strong bearing on its growth. We develop a growth diagnostics framework for agricultural sector in Bihar located in eastern India to identify the most binding constraints. Our results show that poor functioning of agricultural markets and low level of crop diversification are the important reasons for lower agricultural growth in Bihar. Rise in the level of instability in the prices of agricultural produces indicates a weak price transmission across the markets even after repealing the agricultural produce market committee act. Poor market linkages and non-functioning producer collectives at village level affect the farmers motivation for undertaking crop diversification. Our policy suggestions include state provision of basic market infrastructure to attract private investment in agricultural marketing, strengthening the farmer producer organisations, and a comprehensive policy on crop diversification.

Anticipatory Trading Against Distressed Mega Hedge Funds
Agarwal, Vikas,Aragon, George O.,Nanda, Vikram K.,Wei, Kelsey D.
We examine the trading activity of institutional investors when mega hedge funds (MHFs)experience financial distress. In anticipation of a 1% drop in stock ownership by distressed MHFsnext quarter, other institutions reduce their stock ownership of the same stocks by 1.79% in thecurrent quarter. A one standard-deviation higher measure of anticipatory trading predicts 1.57%per year lower abnormal equity portfolio returns for distressed MHFs. Stocks that are anticipatedto be sold by distressed MHFs experience negative abnormal returns and subsequent returnreversals. We conclude that institutional investors front-run the distressed trades of MHFs anddestabilize stock prices.

Artificial Intelligence in Human Resources Management- A Critical Overview
The idea of Artificial Intelligence in Human Resources Management is still debatable and the experts are still on the midway to conclude whether Artificial Intelligence is boon or a bane to mankind as a whole. Initially, the HR departments were against the AI system due to the fear of unemployment and increased dependence on robots and machines. But, gradually situation changed, technologies and tools like e-recruitment, Human Resources Analytics, Cloud Computing, Management Information System, and Computerized performance monitoring have reduced the work burden of HR personnel, which enabled them to concentrate on other visions and missions of the organization. This paper has focused on various advantages and disadvantages of Artificial Intelligence and also has reviewed the overall impact of Artificial Intelligence in Human Resources Management.

Bank Lending and Corporate Innovation: Evidence from SFAS 166/167
Dou, Yiwei,Xu, Zhaoxia
Understanding the role of bank lending in corporate innovation is important to policymakers, practitioners, and academics. We provide new evidence on such a role by exploiting the implementation of SFAS 166/167, which removed the offâ€"balance sheet status of certain securitized assets of banks. The regulation affects bank lending and thus represents a credit supply shock to borrowing firms. We find that affected banks raise spreads and cut loan amounts after the regulation. Firms that borrow from affected banks reduce R&D investment and the number and quality of the patents they generate. The reduction is concentrated among firms whose banks experience more downward pressure on capital ratios and greater market discipline, and firms that are more dependent on external financing. Additional analyses reveal that information asymmetry between incumbent banks and outsiders with respect to borrowing firms prevent them from switching. The overall findings suggest that bank lending promotes borrowing firms’ innovation activities. Policies that restrict bank lending are likely to hurt innovation of borrowers.

Betting Against Quant: Examining the Factor Exposures of Thematic Indices
Blitz, David
We examine the performance characteristics of recently introduced thematic indices using standard asset pricing theory. We find that thematic indices generally have strong negative exposures towards the profitability and value factors, indicating that they hold growth stocks that invest now for future profitability. As such, investors in thematic indices are effectively trading against quant investors, who prefer stocks that are currently cheap and profitable. From an asset pricing perspective, the negative factor exposures of thematic indices imply low expected returns. As there is clearly a clientele for thematic indices, we discuss how investing in these strategies may be rationalized despite their unfavorable factor exposures.

Competition, Innovation and Crises: Evidence from 20 million securitized loans
Haslag, Peter H.,Srinivasan, Kandarp,Thakor, Anjan V.
This paper asks: why did innovation in securitized mortgages spike before the 2007-09 crisis? We propose that this innovation was driven by increased competition among sponsors who securitized and sold mortgages i.e., these sponsors demanded more innovative mortgages from originators who complied. We use a regulatory change in 2000 that generated plausibly exogenous variation in local sponsor competition, to empirically identify the effect of sponsor competition on loan innovation. By comparing cohorts of loans securitized during the same time, we show that sponsor-induced innovation led to riskier mortgages being packaged into Prime deals during the pre-crisis boom period. This evidence of riskier collateral backing lower-yielding MBS is consistent with the obfuscation motives of sponsors.

Credit-Informed Tactical Asset Allocation - 10 Years On
Klein, David
This paper takes a look back at the original Credit-Informed Tactical Asset Allocation paper published in June 2011 and extends the model to address some of the weaknesses identified in the original paper.

Cryptocurrency, Mining Pools' Concentration, and Asset Prices
Datta, Bikramaditya,Hodor, Idan
This paper studies the asset pricing implications of mining pools' concentration. We incorporate two features specific to cryptocurrencies into a traditional dynamic asset pricing model. First, we introduce the technological arms race between mining pools, and second, the interdependency between the cryptocurrency price and its transactional benefits, which we call services. Our continuous-time setup admits precise closed-form expressions. We find that an increase in mining pools' concentration decreases cryptocurrency price and increases its volatility, and the effects are amplified when there is more interdependency between the cryptocurrency price and its services. Empirical evidence from Bitcoin supports our model's predictions.

Dash for dollars
Cesa-Bianchi, Ambrogio,Eguren Martin, Fernando
Within-firm variation of corporate bond spreads around the Covid-19 outbreak shows that US dollar-denominated bonds experienced larger increases in spreads relative to non-dollar bonds, especially at short maturities. Differently, in the non-dollar sample it was the spreads of longer maturity bonds that widened more markedly. Price pressures arising from a liquidity-driven dash for cash alone cannot rationalize these findings. Instead, the patterns we uncover suggest a ‘dash for dollars’, in which investors sold their dollar-denominated assets first, with a consequent impact on prices. We link these dynamics to the dominant role of the US dollar in the international financial system.

Deep Order Flow Imbalance: Extracting Alpha at Multiple Horizons from the Limit Order Book
Kolm, Petter N.,Turiel, Jeremy,Westray, Nicholas
We employ deep learning in forecasting high-frequency returns at multiple horizons for 115 stocks traded on Nasdaq using order book information at the most granular level. While raw order book states can be used as input to the forecasting models, we achieve state-of-the-art predictive accuracy by training simpler "off-the-shelf" artificial neural networks on stationary inputs derived from the order book. Specifically, models trained on order flow significantly outperform most models trained directly on order books. Using cross-sectional regressions we link the forecasting performance of a long short-term memory network to stock characteristics at the market microstructure level, suggesting that "information-rich" stocks can be predicted more accurately. Finally, we demonstrate that the effective horizon of stock specific forecasts is approximately two average price changes.

Delegated asset management and performance when some investors are unsophisticated
Malliaris, Steven G.,Malliaris, A. (Tassos) G.
Households with limited financial expertise sometimes attempt to avoid investment mistakes by delegating the management of their investments to experts. However, evidence on the efficacy of delegation has been mixed. This paper contributes to understanding the question: why is the acquired expertise of asset managers a limited substitute for investors' lack of expertise? We consider an economy with investors (who vary in sophistication) and managers (who vary in skill). Unsophisticated investors' lack of expertise makes it hard for them to distinguish skilled managers from unskilled ones. In the equilibrium that follows, investors exert little effort when searching for managers, leading to a suboptimal composition of managerial types entering the market. When unsophisticated investors are endowed with weak signals, they attempt to time their entry and exit from the market for managers, but their actions are predictable, so performance continues to suffer.

Do Managers Walk the Talk on Environmental and Social Issues?
Chava, Sudheer,Du, Wendi,Malakar, Baridhi
We train a deep-learning based Natural Language Processing (NLP) model on various corporate sustainability frameworks in order to construct a comprehensive Environmental and Social (E&S) dictionary that incorporates materiality. We analyze the earnings conference calls of U.S. public firms during 2007-2019 using this dictionary. We find that the discussion of environmental topics is associated with higher pollution abatement and more future green patents. Firms reduced their air pollution even after the U.S. announced its withdrawal from the Paris Agreement. Similarly, the discussion of social topics is positively associated with improved employee ratings. Overall, our results provide some evidence that firms do walk their talk on E&S issues.

Do we want more NBFC's to fail? Learnings from the Indian Financial System
Mohanty, Shiba
Financial Intermediation plays an important role in the growth and development of the economy. The active participation of the non-banking financial companies' role is as crucial as the commercial banks in India. The repeated failure of these entities posed numerous questions upon the potential functioning of the NBFC's in India.

Does a mutual fund's exposure to pollution influence its environmental engagements?
Foroughi, Pouyan,Marcus, Alan J.,Nguyen, Vinh
This paper studies the relationship between mutual fund management's direct experience with air pollution and the fund's engagements with portfolio companies on environmental issues. We find that higher air pollution in a mutual fund's headquarter county increases the propensity of the fund to vote in support of shareholders' environmental proposals and to liquidate its holdings of portfolio firms with lower environmental ratings. We also find that greater air pollution exposure of a mutual fund predicts better environmental performance at its portfolio companies. To establish causality, we use elevated air pollution produced by large wildfires in a mutual fund's headquarter county as an instrument and identify similar effects on the outcome variables. These results suggest that a mutual fund's direct exposure to pollution can inform its environmental engagements at its portfolio companies.

Economic Narratives and Market Outcomes: A Semi-supervised Topic Modeling Approach
Mai, Dat
I employ the seeded Latent Dirichlet Process (sLDA) model in natural language processing to extract the narratives discussed by Shiller (2019) from nearly seven million New York Times articles over the past 150 years. The estimation scheme is designed to avoid any look-ahead bias in constructing the monthly narrative weights. Among the narratives considered, the most important one is Panic, which encompasses various stress- and anxiety-related themes including economic downturns, wars, political tensions, and epidemics. I find that Panic and a narrative index that loads heavily on Panic are strong positive predictors of excess U.S. market return and negative predictors of both realized and implied market volatility. I document empirical support for Panic as a proxy for time-varying risk aversion, consistent with a univariate version of the intertemporal capital asset pricing model (ICAPM). The predictability of narratives over market returns holds at both market and portfolio level and at both monthly and daily interval, and importantly is increasing over time.

Electronic Bond Intermediation: Evidence from Corporate Bond ATSs
Kim, Abby,Nguyen, Giang
We examine trading and quoting behavior of dealers in the corporate bond market, using dealer quotation data from two major corporate bond ATSs. We find a clear pecking order of transaction costs in which central dealers offer the lowest transaction costs, followed by high-quoting dealers, then moderate-quoting dealers, and finally non-quoting dealers. We also find that ATSs provide a useful venue for inventory management, especially for dealers who do not possess extensive bilateral trading networks as central dealers. Overall, our study contributes to broadening our understanding of electronic trading channels beyond the traditional voice trading channel and their implications on customer transaction costs in an important OTC market.

Emerging Canadian Crypto-Asset Jurisdictional Uncertainties and Regulatory Gaps
Clements, Ryan
Canadian securities regulators recently advanced a novel jurisdictional claim over crypto-asset trading platforms (CTPs) that trade Bitcoin and other decentralized commodity crypto-assets (DCAs) which are not securities or derivatives on their own. The regulator asserted that a platform user’s “contractual right” to delayed delivery of a DCA creates either a security or a derivative - a position that no other international securities regulator has yet taken. This jurisdictional claim is a positive development in the evolution of crypto-asset regulation in Canada, but it is also incomplete. Third-party intermediaries, and custodial services, are a centralized point of risk transmission and investor transaction volume. As such, the regulator’s measures will bring certainty, stability, and credibility to a historically vulnerable segment of an industry surging in investor interest. Nevertheless, jurisdictional uncertainties, regulatory gaps and standards deficits remain in crypto assets, which could lead to investor harm and financial system instability. This article illustrates numerous crypto regulatory uncertainties including intermediated blockchain proof of stake validation rewards (crypto staking); decentralized finance (DeFi) passive income “yield farming” and non-fungible tokens (NFTs). Also, user controlled DCA and stablecoin wallets, and non-custodial DCA investment advice are currently unregulated with no standards, certifications, or safeguards. Nascent DeFi applications like peer-to-peer exchanges, lending protocols, smart contract-based prediction and derivatives markets, synthetic investments and lotteries also currently operate outside of meaningful supervision or standards, and in many cases without an intermediary due to automated smart contracts on a decentralized programmable blockchain. Ultimately, a legislative solution which brings DeFi under the supervision of the securities regulator for applications that resemble capital markets regulated products and services, aligned with consistent international standards and coordination with other financial market agencies, is necessary to fully support innovation in crypto assets while ensuring financial system stability and investor protection.

Enhancing Credit Exposure Management Through Graph Analytics
Venkataraman, Subramanian,Bhaumik, Kallol
Direct and indirect exposures to supply chains caused sizeable losses to credit, trading and investment portfolios of banks due to Covid-19. In this first of its kind paper, we argue that more than data inadequacies, lack of proper tools to analyze supply chain and similar linkages as the major cause. With graph analytics, various hidden concentrations and their sources can be identified in visually appealing and robust manner. We demonstrate this with our own scenarios and computations of risks caused by each scenario. By including other types of dependencies and third-party data sets, entire limit setting, exposure monitoring and stress testing can be strengthened to a great extent.

Errors in Learning from Others' Choices
Mohsen Foroughifar

Observation of other people's choices can provide useful information in many circumstances. However, individuals may not utilize this information efficiently, i.e., they may make decision-making errors in social interactions. In this paper, I use a simple and transparent experimental setting to identify these errors. In a within-subject design, I first show that subjects exhibit a higher level of irrationality in the presence than in the absence of social interaction, even when they receive informationally equivalent signals across the two conditions. A series of treatments aimed at identifying mechanisms suggests that a decision maker is often uncertain about the behavior of other people so that she has difficulty in inferring the information contained in others' choices. Building upon these reduced-from results, I then introduce a general decision-making process to highlight three sources of error in decision-making under social interactions. This model is non-parametrically estimated and sheds light on what variation in the data identifies which error.

Executive Equity Compensation Plans and Board of Director Discretion over Equity Grants
Cadman, Brian D.,Carrizosa, Richard
Executive equity compensation is granted out of an equity incentive plan that must be approved by shareholders. Equity incentive plans are an important precursor to equity grants because plan terms give boards of directors discretion over the amount and features of equity that can be granted without further shareholder approval. We predict and find that equity plan proposals give boards more discretion over grants when the firm faces greater labor market competition and more volatile stock returns and when shareholders have less influence over the board. Shareholders vote less favorably for plans that confer greater discretion to boards but that relation weakens with labor market competition and shareholder influence. We also find evidence of more discretion facilitating larger equity grants in response to stock price declines. Overall our findings provide insights into the determinants of equity compensation plan characteristics that affect board discretion over equity grants and illuminates how firms balance needs to respond to labor market pressure and volatile operating environments against the governance and oversight of executive equity compensation.

Expected Neediness and the Formation of Mutual Support Arrangements: Evidence from the Philippines
Lenel, Friederike
This paper studies the role of expected neediness for the formation of mutual support arrangements between households. I predict that under strategic link formation in the context of risk-sharing, households with fewer resources and thus a higher probability to become needy have a higher incentive to engage in informal support, yet mutual support arrangements should be less likely between households that differ in their expected neediness. The predictions are tested using census support network data of a fishing village on the Philippines. I show that households are indeed more likely to form mutual support arrangements with households that face a similar probability of neediness; yet, households with fewer resources are not necessarily more likely to engage in mutual support. Furthermore, I document substantial differences in the structure of reciprocated and unreciprocated support links that need to be accounted for in the analysis of support arrangements.

Financing Discretionary Payout via Debt or Equity â€" Evidence From India
Singh, Hardeep
The purpose of the paper is to examine financing payout behavior of Indian firms. Specifically, the reliance of Indian firms on capital markets to finance their discretionary payouts (DCP) is explored using data of S&P BSE 500 firms for the sample period from 2010 to 2020. This study reports several new findings for the payout policies followed by Indian firms. First, dividend payouts are not disappearing in India because dividend payout ratio and share repurchase ratio for Indian firms are found to increase during the sample period. Second, rupee magnitude of dividend payments and percentage of firms paying dividends are also increasing. Third, the financing of DCP shows that firms finance DCP mostly with debt and occasionally with equity. Fourth, firm characteristics namely size, excess leverage, excess cash, market-to-book ratio, R&D (only for debt financing), managerial ownership, cash flows, and credit rating influence financing of DCP with debt and equity issuance. Lastly, business cycle conditions are shown to influence debt financed DCP. Overall, the findings run counter to existing studies which state that dividends are disappearing because this study finds evidence of increasing dividends among Indian firms and provides insights to practitioners and academicians on the financing of payout policy in India.

Frontier Markets, Liberalization and Informational Efficiency: Evidence from Vietnam
Mateus, Cesario,Bao, Trung
This paper examines the equity market opening in Vietnam, a frontier market that has taken gradual steps of relaxing capital control, by analysing whether liberalization policies in the period 2009â€"15 have had an impact on informational efficiency. We applied time-varying Hurst exponent during the liberalization period and tested Adaptive Market Hypothesis. The results confirm the role of foreign investors in improving the local market’s efficiency, however, the findings show that the liberalization does not always result in the increase of foreign participation, which then has a limited impact on the efficiency. The study also indicates the importance of governance policies, along with liberalization policies, in completing market structure and market dynamics, that promote equity price reflects truly firm’s intrinsic value.

Grade Inflation and Stunted Effort in a Curved Economics Course
Alex Garivaltis

To protect his teaching evaluations, an economics professor uses the following exam curve: if the class average falls below a known target, $m$, then all students will receive an equal number of free points so as to bring the mean up to $m$. If the average is above $m$ then there is no curve; curved grades above $100\%$ will never be truncated to $100\%$ in the gradebook. The $n$ students in the course all have Cobb-Douglas preferences over the grade-leisure plane; effort corresponds exactly to earned (uncurved) grades in a $1:1$ fashion. The elasticity of each student's utility with respect to his grade is his ability parameter, or relative preference for a high score. I find, classify, and give complete formulas for all the pure Nash equilibria of my own game, which my students have been playing for some eight semesters. The game is supermodular, featuring strategic complementarities, negative spillovers, and nonsmooth payoffs that generate non-convexities in the reaction correspondence. The $n+2$ types of equilibria are totally ordered with respect to effort and Pareto preference, and the lowest $n+1$ of these types are totally ordered in grade-leisure space. In addition to the no-curve ("try-hard") and curved interior equilibria, we have the "$k$-don't care" equilibria, whereby the $k$ lowest-ability students are no-shows. As the class size becomes infinite in the curved interior equilibrium, all students increase their leisure time by a fixed percentage, i.e., $14\%$, in response to the disincentive, which amplifies any pre-existing ability differences. All students' grades inflate by this same (endogenous) factor, say, $1.14$ times what they would have been under the correct standard.

Guide on incentives for responsible investment in agriculture and food systems
Bulman, Anna,Cordes, Kaitlin Y.,Mehranvar, Ladan,Merrill, Ella,Fiedler, Yannick
This guide aims to provide policymakers and government technical staff with guidance on howinvestment incentives can be used (and how they should not be used) to enhance responsibleinvestment in agriculture and food systems.The guide identifies key policy challenges associated with investment incentives, and offersguidance on how to design, implement, monitor, and evaluate investment incentives that arealigned with national development priorities and that contribute to the realisation of the 2030Sustainable Development Agenda. By focusing on the full ambit of investorsâ€"domestic andforeign, small-, mid- and large-scaleâ€"the guide provides a unique contribution regarding theuse of incentives for responsible investment.The guide covers the following:• Part I explains what responsible investment in agriculture and food systems is and who thekey stakeholders are, as a starting point for understanding how incentives may be used inthis context.• Part II provides an overview of investment incentives and discusses some of the mostcommon types of incentives used.• Part III offers general considerations on how incentives can be usedâ€"as well as how theyshould not be usedâ€"to improve the quality and quantity of responsible investment inagriculture and food systems.• Part IV discusses how to plan for, design, monitor, and evaluate investment incentives forresponsible investment in agriculture and food systems.

Housing Expenditures of Social Security Beneficiaries, 2005â€"2018
Purcell, Patrick J.
This article uses data from the public-use files of the Census Bureau’s American Community Survey for selected years 2005â€"2018 to examine the annual housing expenditures of households that include at least one person who received income from Social Security. In all years, the median percentage of income spent on housing was higher in households that included at least one Social Security beneficiary than in households with no beneficiaries. In households with at least one Social Security beneficiary, the median share of income spent on housing varied by tenure. In the period 2005â€"2018, the median shares rose from 31.7 percent to 32.5 percent for renter households, declined from 27.3 percent to 25.1 percent for homeowner households with a mortgage, and declined from 13.9 percent to 12.4 percent for homeowner households without a mortgage.

Identification in Bayesian Estimation of the Skewness Matrix in a Multivariate Skew-Elliptical Distribution
Sakae Oya,Teruo Nakatsuma

Harvey et al. (2010) extended the Bayesian estimation method by Sahu et al. (2003) to a multivariate skew-elliptical distribution with a general skewness matrix, and applied it to Bayesian portfolio optimization with higher moments. Although their method is epochal in the sense that it can handle the skewness dependency among asset returns and incorporate higher moments into portfolio optimization, it cannot identify all elements in the skewness matrix due to label switching in the Gibbs sampler. To deal with this identification issue, we propose to modify their sampling algorithm by imposing a positive lower-triangular constraint on the skewness matrix of the multivariate skew- elliptical distribution and improved interpretability. Furthermore, we propose a Bayesian sparse estimation of the skewness matrix with the horseshoe prior to further improve the accuracy. In the simulation study, we demonstrate that the proposed method with the identification constraint can successfully estimate the true structure of the skewness dependency while the existing method suffers from the identification issue.

Imperfect pass-through to deposit rates and monetary policy transmission
Polo, Alberto
I document three salient features of the transmission of monetary policy shocks: imperfect pass-through to deposit rates, impact on credit spreads, and substitution between deposits and other bank liabilities. I develop a monetary model consistent with these facts, where banks have market power on deposits, a duration-mismatched balance sheet, and a dividend-smoothing motive. Deposit demand has a dynamic component, as in the literature on customer markets. A financial friction makes non-deposit funding supply imperfectly elastic. The model indicates that imperfect pass-through to deposit rates is an important source of amplification of monetary policy shocks.

Inflation Volatility Risk and the Cross-section of Corporate Bond Returns
Ceballos, Luis
As corporate bonds are primarily denominated in nominal terms, inflation uncertainty arises as a relevant source of risk. This paper analyzes the relevance of inflation volatility risk as an additional factor predicting the cross-section of corporate bond returns. I find a negative and significant inflation volatility risk premium (IVRP) obtained from the difference between high inflation and low inflation beta portfolios. Further, common risk factors in the equity and corporate bond markets do not explain the IVRP, it responds to ex-post inflation risk and is partially explained by market risk and monetary policy shocks. Lastly, I show that the IVRP is associated with firms incurring in debt maturity management to mitigate refinancing risks.

Insurance Companies and the Growth of Corporate Loans' Securitization
Fringuellotti, Fulvia,Santos, João A. C.
We show that insurance companies have almost nonupled their investments in collateralized loan obligations (CLOs) in the post-crisis period, reaching total holdings of $125 billion in 2019. The growth in CLOs’ investments has far outpaced that of loans and corporate bonds, and was characterized by a strong preference for mezzanine tranches rated investment grade over triple-A rated tranches. We document that these phenomena reflect a search for yield behavior. Conditional on capital charges, insurance companies invest more heavily in bonds and CLO tranches with higher yields. Preferences for CLO tranches derived from tranches’ higher yields relative to bonds with the same rating, and increased following the 2010 capital regulatory reform, resulting in insurance companies holding more than 40 percent of mezzanine tranches outstanding in 2019. In the process, insurance companies created the demand for the risky tranches that are critical to the CLO issuance.

Inter-linkage between Indian Stock, Commodity and Foreign Exchange Markets
Naik, Vasantha
Study of market inter-dependency helps the investors, financial managers, policy makers and other stake holders to formulate their financial strategies according to the direction and strength of dependence of one market with another market. In this study we analyse the integration and inter-relationship among commodity, stock and foreign exchange markets in India. This study extends other studies by including all indices of commodity market since their birth till recent days, major stock market indices of India and exchange rates of rupee against US dollar. We use cross- correlation, residual based co-integration tests, Granger causality test and AR-EGARCH (p, q) models to capture the inter-linkage between the markets. The study found bidirectional relation between some of the commodity indices and stock indices and strong unidirectional relationship between commodity and foreign exchange market.

Kalman Filter Estimation of the KNW Model
Pelsser, Antoon
This technical note gives implementation notes for estimating the Koijen-Nijman-Werker model from historical data based on a Kalman filter. We provide an independent derivation of the KNW model. We propose a different implementation of the state-space formulation of the KNW model and we test the impact of two different specifications for the initialisation of the Kalman filter maximum-likelihood estimation. By doing so, we provide an independent verification of the parameter estimations provided by DNB for the Committee Parameters. We find that the parameter estimates reported by DNB and our own parameter estimates are very similar.

Knowledge for a warmer world: a patent analysis of climate change adaptation technologies
Kerstin Hötte,Su Jung Jee,Sugandha Srivastav

Technologies help adapt to climate change but little systematic research about these technologies and their interaction with mitigation exists. We identify climate change adaptation technologies (CCATs) in US patent data to study the technological frontier in adaptation. We find that patenting in CCATs was roughly stagnant over the past decades. CCATs form two main clusters: (1) science-intensive CCATs related to agriculture, health and monitoring technologies; and (2) engineering-based for coastal, water and infrastructure adaptation. 25% of CCATs help in climate change mitigation, and we infer that synergies can be maximized through well designed policy. CCATs rely more on public R&D than other inventions, and CCAT patents are citing more science over time, indicating a growing relevance of research as a knowledge source for innovation. Policymakers can use these results to get greater clarity on where R&D support for CCATs can be directed.

Least Squares Monte Carlo and Pathwise Optimization for Merchant Energy Production
Yang, Bo,Nadarajah, Selvaprabu,Secomandi, Nicola
We study merchant energy production modeled as a compound switching and timing option. The resulting Markov decision process is intractable. Least squares Monte Carlo combined with information relaxation and duality is a state-of-the-art reinforcement learning methodology to obtain operating policies and optimality gaps for related models. Pathwise optimization is a competing technique developed for optimal stopping settings, in which it typically provides superior results compared to this approach, albeit with a larger computational effort. We apply these procedures to merchant energy production. Employing pathwise optimization requires methodological extensions. We use principal component analysis and block coordinate descent in novel ways to respectively precondition and solve the ensuing ill-conditioned and large scale linear program, which even a cutting-edge commercial solver is unable to handle directly. Both techniques yield near optimal operating policies on realistic ethanol production instances. However, at the cost of both considerably longer run times and greater memory usage, pathwise optimization leads to substantially tighter dual bounds compared to least squares Monte Carlo, even when specified in a simple fashion, complementing it in this case. Thus, it plays a critical role in obtaining small optimality gaps. Our numerical observations on the magnitudes of these bound improvements differ from what is currently known. This research has potential relevance for other commodity merchant operations contexts and motivates additional algorithmic work in the area of pathwise optimization.

Lenders’ Pricing Strategy: Do Neighborhood Risks Matter?
Agarwal, Sumit,Deng, Yongheng ,He, Jia,Wang, Yonglin
This paper explores the different pricing strategies of lenders who originate both government-sponsored enterprise (GSE) and non-GSE loans. We find that, conditional on loan and borrower characteristics and some observable local economic factors, mortgage rates on GSE loans vary significantly across regions. However, no sizable regional variation is observed in the loan amount or default risk. By contrast, the mortgage rates on non-GSE loans depend almost entirely on borrowers and loan characteristics. In addition, spatial variations in GSE mortgage rates are highly responsive to regional prepayment risk. The results are robust to various controls for neighborhood characteristics, including regional-level bank competition, household income, and racial composition. Overall, the findings offer a novel insight into how lenders adjust pricing strategies in response to a changing lending environment. It provides implications for the present and imminent dangers of housing bubbles predictions and the intensified refinancing wave following the COVID-19 pandemic.

Machine Learning, Corporate Bankruptcies and Variable Selection
Rossi, Ludovico
I employ a variety of machine learning techniques to predict corporate bankruptcies. I compare machine learning techniques' predictions with the ones of reduced-form regressions and structural models. To assess the performances of different models, I compute a range of scores both in-sample and out-of-sample. I show that neural networks produce better predictions than other machine learning methods, reduced-form regressions and structural models. I provide evidence that a small set of variables consistently predict bankruptcy for firms of different dimensions, over different periods and in different industries.

Multiple-Market Trading and Overnight Price Discovery: Evidence From American Depository Receipts
Hoang, Lai T.
This paper compares the overnight price discovery of American Depository Receipts (ADRs) and other common stocks traded in the U.S. stock market, and examines how trading activities of ADRs’ underlying shares in home markets affect the price discovery. We find that the efficiency of opening price and the price discovery during the overnight period is significantly higher than that of U.S. common stocks. Further analyses show that the price discovery of ADRs shifts from the trading day to the overnight and the opening prices of ADRs are more efficient if there are more trading activities of underlying shares in home markets. The results suggest that the trading of similar assets in multiple markets over non-overlapping hours improves the price efficiency.

Natural Disasters and Creative Destruction: Evidence from the Universe of Firms in China
Cheng, Hua,Lin, Tse-Chun
We investigate the “creative destruction” through the role of typhoon occurrence on existing firms’ innovation and firm creation for the universe of Chinese firms by utilizing novel administrative data. We find that typhoon occurrence during a firm’s early life reduces both patent quantity and quality in following years, which is not driven by the expectation of such natural disasters. The negative impact of typhoon occurrence is much stronger among firms with concentrated share ownership as well as single shareholder firms; therefore, insufficient risk-sharing is likely channeling the negative impact of typhoon occurrence. On the other hand, financial constraints do not have much explanatory power. Moreover, the typhoon-induced innovation decline increases the likelihood of firm death. Finally, in contrast with the impact of existing firms’ innovation and survival, typhoon occurrence in the previous year increases the total capital and employees of new firms and hence “creative destruction” happens.

Natural Disasters and the Role of Regional Lenders in Economic Recovery
Celil, Hursit,Oh, Seungjoon,Selvam, Srinivasan
We find that Chinese regional state-owned City-Commercial Banks (CCBs) landlocked by their remit to operate within a city respond to natural disasters more effectively by aggressively expanding credit, especially to corporate borrowers. The credit expansion is more remarkable in CCBs with high state ownership and those that are private. However, the additional lending does not sacrifice asset quality. Moreover, using satellite-based city night lights, we find post-disaster cities that experience greater CCB credit expansion enjoy stronger economic recovery. Overall, our findings highlight the critical role played by regional state-owned lenders in economic recovery from increasingly frequent natural disasters.

On Non-Negative Equity Guarantee Calculations with Macroeconomic Variables Related to House Prices
Badescu, Alexandru,Quaye, Enoch,Tunaru, Radu
This article investigates the impact of macroeconomic fundamentals on the valuation of non-negative equity guarantee (NNEG) of equity release mortgages. The house price returns are modelled within the family of multiplicative volatility processes using a two-component GARCH-MIDAS model. The pricing framework is constructed based on a general exponential linear pricing kernel, and the risk-neutral dynamics are derived assuming an autoregressive structure for the macroeconomic variables. Our numerical results indicate that the addition of macroeconomic variables improves the predictive performance of the house price returns and have a significant effect on the NNEG valuation

Opinions, Prices and Fibonacci Structures
Maloumian, Nicolas
In the financial markets, contradictory opinions generate a set of constraints which mediate information through a system of expected target prices. As a result, prices are a measure of value as much as they are an indication of how these expectations concerning value remain valid. Thus, path dependent negative and positive feedback loops modify price action, driving it away from random behavior. This study shows that complexity at work tends to be structured by Fibonacci numbers and ratios thus creating conditions for the emergence of constrained patterns which can lead to a renewed approach of forecasting and risk monitoring.

Predicting Credit Default Probabilities Using Bayesian Statistics and Monte Carlo Simulations
Dominic Joseph

Banks and financial institutions all over the world manage portfolios containing tens of thousands of customers. Not all customers are high credit-worthy, and many possess varying degrees of risk to the Bank or financial institutions that lend money to these customers. Hence assessment of credit risk is paramount in the field of credit risk management. This paper discusses the use of Bayesian principles and simulation-techniques to estimate and calibrate the default probability of credit ratings. The methodology is a two-phase approach where, in the first phase, a posterior density of default rate parameter is estimated based the default history data. In the second phase of the approach, an estimate of true default rate parameter is obtained through simulations

Probability-free models in option pricing: statistically indistinguishable dynamics and historical vs implied volatility
Damiano Brigo

We investigate whether it is possible to formulate option pricing and hedging models without using probability. We present a model that is consistent with two notions of volatility: a historical volatility consistent with statistical analysis, and an implied volatility consistent with options priced with the model. The latter will be also the quadratic variation of the model, a pathwise property. This first result, originally presented in Brigo and Mercurio (1998, 2000), is then connected with the recent work of Armstrong et al (2018, 2021), where using rough paths theory it is shown that implied volatility is associated with a purely pathwise lift of the stock dynamics involving no probability and no semimartingale theory in particular, leading to option models without probability. Finally, an intermediate result by Bender et al. (2008) is recalled. Using semimartingale theory, Bender et al. showed that one could obtain option prices based only on the semimartingale quadratic variation of the model, a pathwise property, and highlighted the difference between historical and implied volatility. All three works confirm the idea that while historical volatility is a statistical quantity, implied volatility is a pathwise one. This leads to a 20 years mini-anniversary of pathwise pricing through 1998, 2008 and 2018, which is rather fitting for a talk presented at the conference for the 45 years of the Black, Scholes and Merton option pricing paradigm.

Q2 2021 Silicon Valley Venture Capitalist Confidence Index Research Report
Cannice, Mark
The Silicon Valley Venture Capitalist Confidence IndexTM (Bloomberg ticker symbol: SVVCCI) is based on a recurring quarterly survey (since Q1 2004) of Silicon Valley/San Francisco Bay Area venture capitalists. The Index measures and reports the opinions of professional venture capitalists on their estimations of the high-growth venture entrepreneurial environment in the San Francisco Bay Area over the next 6 - 18 months. The Silicon Valley Venture Capitalist Confidence IndexTM for the second quarter of 2021, based on a June 2021 survey of 32 San Francisco Bay Area venture capitalists, registered 4.16 on a 5-point scale (with 5 indicating high confidence and 1 indicating low confidence). The Q2 2021 Index surged higher from the prior quarter’s reading of 3.82 and highlights the continuing strong recovery in the entrepreneurial economy since the pandemic low point confidence measure of 2.33 in the first quarter of 2020.

Quants, Strategic Speculation, and Financial Market Quality
Malikov, George,Pasquariello, Paolo
We study the effects of quantitative equity investing, an increasingly popular investment style, on financial market quality. Within a noisy REE model of strategic speculation with two informed market participants, we define discretionary investing as fully strategic trading and quantitative investing as partially or fully myopic via its reliance on a backtested trading strategy. Growth in quantitative investing is modeled as both the introduction of and the greater backtest adherence by an informed speculator. The introduction of an additional speculator generally benefits financial market quality. The effect of greater backtest adherence depends on whether it leads to more or less aggressive trading than discretion, the former improving, while the latter worsening market quality. If it is more aggressive, market quality broadly benefits with greater quantitative investing; if it is less aggressive, market quality deteriorates.

Reduced-form framework for multiple default times under model uncertainty
Francesca Biagini,Andrea Mazzon,Katharina Oberpriller

In this paper we introduce a sublinear conditional operator with respect to a family of possibly nondominated probability measures in presence of multiple ordered default times. In this way we generalize the results of [5], where a reduced-form framework under model uncertainty for a single default time is developed. Moreover, we use this operator for the valuation of credit portfolio derivatives under model uncertainty.

Regulatory Constraints for Money Market Funds: The Impossible Trinity?
Baes, Michel,Bouveret, Antoine,Schaanning, Eric
Despite substantial regulatory reforms, MMFs exposed to private assets experienced severe stress in March 2020. In the EU, Low Volatility Net Asset Value (LVNAVs) MMFs faced acute challenges to meet regulatory requirements while facing high redemptions. Such funds have to maintain their mark-to-market net asset value within 20 basis points of a constant net asset value, and their weekly liquidity asset above the 30% requirement. We provide a stylized model to show that under certain conditions related to outflows and market liquidity of their assets, LVNAVs may face difficulties in fulfilling both regulatory constraints at the same time. We calibrate the model to EU data to assess possible reforms to MMFs. Increasing the NAV deviation and improving the market liquidity of the assets MMFs invest in would substantially improve the resilience of MMFs. Introducing countercyclical liquidity buffers would also enhance their resilience especially in times of stress, and the effect is larger than increasing liquidity requirements.

Risky Asset Holdings during Covid-19 and Their Distributional Impact: Evidence from Germany
Menkhoff, Lukas,Schröder, Carsten
We present evidence from a repeated survey on risky asset holdings carried out on a representative sample of the German population six times between April and June 2020. Given the size of the Covid-19 shock, we find little evidence of portfolio rebalancing in April 2020. In May, however, individual investors started buying heavily, fueling market recovery. The cross-section shows large differences as young, educated, high income, and risk tolerant investors are net buyers throughout and, thus, benefit from the stock market recovery. Older individuals, parents of young children, and individuals affected by adverse liquidity shocks from Covid-19 are net sellers. Given the high risk of illness, older people are hit by dual blows to both health and finances.

Semimartingale price systems in models with transaction costs beyond efficient friction
Christoph Kühn,Alexander Molitor

A standing assumption in the literature on proportional transaction costs is efficient friction. Together with robust no free lunch with vanishing risk, it rules out strategies of infinite variation, as they usually appear in frictionless markets. In this paper, we show how the models with and without transaction costs can be unified.

The bid and the ask price of a risky asset are given by c\'adl\'ag processes which are locally bounded from below and may coincide at some points. In a first step, we show that if the bid-ask model satisfies "no unbounded profit with bounded risk" for simple strategies, then there exists a semimartingale lying between the bid and the ask price process.

In a second step, under the additional assumption that the zeros of the bid-ask spread are either starting points of an excursion away from zero or inner points from the right, we show that for every bounded predictable strategy specifying the amount of risky assets, the semimartingale can be used to construct the corresponding self-financing risk-free position in a consistent way. Finally, the set of most general strategies is introduced, which also provides a new view on the frictionless case.

Shareholder Democracy Under Autocracy: Voting Rights and Corporate Performance in Imperial Russia
Dayton, Amy,Gregg, Amanda G.,Nafziger, Steven
This paper investigates how the rules that corporations wrote for themselves related to their financing and performance in an environment characterized by poor investor protections, Imperial Russia. We present new data on detailed governance provisions from Imperial Russian corporate charters, which we connect to a comprehensive panel database of corporate balance sheets from 1899to 1914. We document how variation in votes per share and other shareholder rights provisions were related to corporate choices of using debt vs. equity and whether these governance provisions correlated systematically with performance measures on the balance sheet and in terms of the market-to-book ratio. This investigation reveals the tradeoffs weighed by Imperial Russian corporations and demonstrates the surprising flexibility that Russian corporations enjoyed, conditional on obtaining a corporate charter.

Short-Term Volatility Timing: A Cross-Country Study
Vidal-García, Javier,Vidal, Marta
In this paper, we examine how mutual fund managers behave to fluctuations in market volatility. We use a sample of daily return from countries around the world to evaluate how manager perform to publicly available information. There is a lack of empirical studies that examine the relation between conditional market returns and conditional volatility on a global scale; we provide evidence across countries to answer this question. Our study provides new evidence about conditional mutual fund performance across countries. We find that during periods of high market volatility mutual funds reduce market exposure across all countries; this implies that systemic risk is particularly sensitive to changes in market volatility around the world.

Solving high-dimensional optimal stopping problems using deep learning
Sebastian Becker,Patrick Cheridito,Arnulf Jentzen,Timo Welti

Nowadays many financial derivatives, such as American or Bermudan options, are of early exercise type. Often the pricing of early exercise options gives rise to high-dimensional optimal stopping problems, since the dimension corresponds to the number of underlying assets. High-dimensional optimal stopping problems are, however, notoriously difficult to solve due to the well-known curse of dimensionality. In this work, we propose an algorithm for solving such problems, which is based on deep learning and computes, in the context of early exercise option pricing, both approximations of an optimal exercise strategy and the price of the considered option. The proposed algorithm can also be applied to optimal stopping problems that arise in other areas where the underlying stochastic process can be efficiently simulated. We present numerical results for a large number of example problems, which include the pricing of many high-dimensional American and Bermudan options, such as Bermudan max-call options in up to 5000 dimensions. Most of the obtained results are compared to reference values computed by exploiting the specific problem design or, where available, to reference values from the literature. These numerical results suggest that the proposed algorithm is highly effective in the case of many underlyings, in terms of both accuracy and speed.

Tender offers and takeover bids in Italy from 2007 to 2019. Empirical evidence and discussion points
Picco, Federico,Ponziani, Valeria,Trovatore, Gianfranco,Ventoruzzo, Marco
This paper aims at providing a description of the impact of the Takeover Directive on the Italian capi-tal market by presenting an analysis of the tender offers and takeover bids launched in Italy in the period between 2007 and 2019.After a brief historical excursus on the genesis and evolution of the European and Italian frameworks, the study focuses on the characteristics of the participants in the offers and of the advisors who assist them; on the purposes for which takeover bids are promoted in Italy, with particular attention to the phenomenon of delisting; on the premiums, the acceptance rates, and the market performance of the target securities.The survey, based on a proprietary database of over 20,000 data, although it covers all the offers launched in the period, focuses particularly on offers concerning shares. It shows that less than half of all those offers involve a change of control and only a small minority are hostile offers. In most cases, the offers included a delisting program, either as their own purpose (voluntary delisting offers launched by the controlling share-holder) or as an objective "associated" with the acquisition/change of control. The data show a recent upward trend in the incidence of delisting, which has gone from 50% to 90% in the last 5 years of analysis. These data seem interesting not because of their absolute value, but in consideration of the increased average size of the companies whose shares have been delisted and, secondly, of the circumstance that this tendency to delist occurred in a market phase that was essentially not negative. The average premium paid to shareholders is approximately 13%, with higher values in offers aimed at a business combination and in voluntary offers. The returns, both absolute and relative to the index, of the target shares are on average negative in the 12/36 months following the bid. Notably, the relative return is equal to -5.9% after 12 months and -6.8% after 3 years. Differentiating the results on the basis of the voluntary or mandatory nature of the offers, it can be seen that all the ex-post return configurations are significantly lower in the case of mandatory offers.Without pretending to draw policy considerations or prospects for reform of the current regulations, the study proposes an analytical and objective framework that leaves, at the disposal of scholars, regulators and market operators, evidence potentially suitable for generating future research contributions.

The COVID-19 Emergency Bonds (C-19E-Bonds): Implementation and Performance
Ruiz Estrada, Mario Arturo
The idea to propose the COVID-19 Emergency Bonds (C-19E-Bonds) is to find a new financial source and resources to support the COVID-19 crisis with local funds to the government. This type of bond avoids more external debts and generates a national macroeconomic financial stability and sustainability in the short and long run. The main objective is to collect monetary resources from local citizens such as private domestic savings, employer’s providence funds, and local investors. The COVID-19 Emergency Bonds (C-19E-Bonds) mission is to generate micro-macro public financial stability of any government in the COVID-19 crisis to avoid a possible catastrophic economic recession in the short run and economic depression in the long run.

The Dark Side of Patents: Strategic Patenting, Product Market Entry and Competitor Innovation
Kurakina, Maria
This paper analyses how strategic patenting effects market concentration, entry, and competitor productivity and patenting. We introduce a new market-based classification of patent as strategic patenting and start by showing that this novel measure offers improvements over those in the extant literature. We find that when firms strategically patent, overall market concentration increases and entry is deterred. Further, competitor firms experience a decline in total factor productivity following a publication of a focal firm's strategic patent. These effects are more pronounced in capital-intensive firms and technological proximate peer groups. Overall these findings demonstrate the tensions inherent in designing patent policies that promote focal firm innovation, while preventing the stifling of competitor innovation.

The Origins of ESG in Pensions: Strategies and Outcomes
Lachance, Stephanie,Stroehle, Judith C.
As intergenerational stewards of capital, pension funds can have many good reasons to embrace environmental, social, and governance (ESG) issues in their investment practices. Yet the particular structure of pension funds creates both advantages and disadvantages for the integration of ESG. This paper reviews the historical origins, regulatory mandates, and fund structures of pensions, to tease out exactly which of these characteristics enable and which of them impede the inclusion of ESG at pension funds. We use the case of PSP Investments to lend depth to the application of the strategies that emerge in the pensions industry.

The Role of Audit Firms in Spreading Depositor Contagion
Beck, Matthew,Nicoletti, Allison,Stuber, Sarah B.
Auditor credibility is important in the banking industry due to the opacity of bank assets and the use of financial statements by external parties to facilitate monitoring. Depositors monitor and discipline bank behavior, but they can also contribute to the spread of shocks from one bank to another. We argue that depositors perceive bank failure as an audit failure, which reduces their assessment of auditor credibility. We document that exposure to failure through the audit firm is associated with lower uninsured deposit growth following the failure, consistent with depositors perceiving failures as a negative signal of auditor credibility. We further document that this association is stronger when depositors perceive connection to failure to reflect a pervasive issue within the audit firm. Collectively, our results suggest that depositors consider accounting signals at other banks in assessing financial reporting credibility.

The Structure and Incentives of a COVID related Emergency Wage Subsidy
Jules Linden,Cathal O'Donoghue,Denisa M. Sologon

During recent crisis, wage subsidies played a major role in sheltering firms and households from economic shocks. During COVID-19, most workers were affected and many liberal welfare states introduced new temporary wage subsidies to protected workers' earnings and employment (OECD, 2021). New wage subsidies marked a departure from the structure of traditional income support payments and required reform. This paper uses simulated datasets to assess the structure and incentives of the Irish COVID-19 wage subsidy scheme (CWS) under five designs. We use a nowcasting approach to update 2017 microdata, producing a near real time picture of the labour market at the peak of the crisis. Using microsimulation modelling, we assess the impact of different designs on income replacement, work incentives and income inequality. Our findings suggest that pro rata designs support middle earners more and flat rate designs support low earners more. We find evidence for strong work disincentives under all designs, though flat rate designs perform better. Disincentives are primarily driven by generous unemployment payments and work related costs. The impact of design on income inequality depends on the generosity of payments. Earnings related pro rata designs were associated to higher market earnings inequality. The difference in inequality levels falls once benefits, taxes and work related costs are considered. In our discussion, we turn to transaction costs, the rationale for reform and reintegration of CWS. We find some support for the claim that design changes were motivated by political considerations. We suggest that establishing permanent wage subsidies based on sectorial turnover rules could offer enhanced protection to middle-and high-earners and reduce uncertainty, the need for reform, and the risk of politically motivated designs.

Trust in Founders
Jagannathan, Murali,Myers, Brett W.,Niu, Xu
We document that labor relationships at founder firms are less acrimonious than at non-founder firms. Founder-firms are less likely to be unionized and employees at non-unionized founder-firms are less likely to attempt to unionize. Further, among firms that are unionized, labor at founder-firms are less likely to strike. Finally, employees of founder firms are much less likely to file unfair labor practice complaints with the NLRB. These results also hold for firms that are run by the family members of founders. Unobserved heterogeneity does not appear to drive the results. The results reveal the valuable role of employee trust in founders.

Visualizing Income Distribution in the United States
Sang Truong,Humberto Barreto

The distribution of household income is a central concern of modern economic policy due to its strong influence on life quality. Yet, non-expert audiences are unaware of the relationship between these two factors. To effectively communicate the effect of income inequality on the quality of life and among the strata, we have designed a novel technique for visualizing income distribution and inequality over time by using the U.S. household income microdata from the Current Population Survey. The result is a striking dynamic animation of income distribution over time, drawing public attention and further investigating economic inequality. Detailed implementation of this project is available at