What drives support for self-driving car technology in the United States?

Abstract

Recent advances in automotive technology have made fully automated self-driving cars technologically feasible. Despite offering many benefits such as increased safety, improved fuel efficiency, and greater disability access, public support for self-driving cars remains low. While previous studies find that demographic factors such as age and sex influence self-driving car support, limited research has examined variables that are well known to predict public attitudes toward emerging technology. Using self-report data from a quota sample of American adults (N?=?1008), we find that age and sex are not significantly associated with support for self-driving car policies when controlling for these other variables. Instead, significant predictors of support included trust in automotive institutions and regulatory bodies, recognition of self-driving car benefits, positive affect toward self-driving cars, and a greater perception that human-driven cars are riskier than self-driving cars. Importantly, we also find that individualism is negatively associated with support. That is, people who value personal autonomy and limited government regulation may perceive policies encouraging self-driving car use as threatening to their worldviews. Altogether, our results suggest strategies for encouraging greater public support of self-driving vehicles while also forecasting potential barriers as this technology emerges as a fixture in transportation policy.     

Using clustering ensemble to identify banking business models

The business models of banks are often seen as the result of a variety of simultaneously determined managerial choices, such as those regarding the types of activities, funding sources, level of diversification, and size. Moreover, owing to the fuzziness of data and the possibility that some banks may combine features of different business models, the use of hard clustering methods has often led to poorly identified business models. In this paper we propose a framework to deal with these challenges based on an ensemble of three unsupervised clustering methods to identify banking business models: fuzzy c‐means (which allows us to handle fuzzy clustering), self‐organizing maps (which yield intuitive visual representations of the clusters), and partitioning around medoids (which circumvents the presence of data outliers). We set up our analysis in the context of the European banking sector, which has seen its regulators increasingly focused on examining the business models of supervised entities in the aftermath of the twin financial crises. In our empirical application, we find evidence of four distinct banking business models and further distinguish between banks with a clearly defined business model (core banks) and others (non‐core banks), as well as banks with a stable business model over time (persistent banks) and others (non‐persistent banks). Our proposed framework performs well under several robustness checks related with the sample, clustering methods, and variables used.     

New Perspectives on Real Estate Valuation

The Journal of Real Estate Finance and Economics -     

A splitting strategy for the calibration of jump-diffusion models

Finance and Stochastics - We present a detailed analysis and implementation of a splitting strategy to identify simultaneously the local volatility surface and the jump-size distribution from...     

Is there a gender gap in CEO compensation?

The gender pay gap generates significant political and social debate. This study contributes to this discussion by examining if a gender pay gap exists at the highest level of corporate management, the CEOs. While previous studies have documented a gender pay gap for most levels of executives the findings with respect to CEOs are conflicting. In this paper we focus only on CEO's as it is the most homogenous of executive roles and does not require us to assume that executives with similar titles undertake identical roles. Our evidence is based on 291 US firm-years for the period of 1998–2010. We do not find any association between CEO pay and gender using both the total sample and a sample matched using propensity scores to control for firm characteristics. These insignificant results hold for total pay, salary and bonuses, and for different matching procedures and econometric specifications. Our results therefore indicate that women who rise through the “glass ceiling” to the level of CEO are remunerated at similar levels to their male counterparts.     

Determinants of Corporate Diversification: Evidence From the Property–Liability Insurance Industry

This article analyzes variations in line‐of‐business diversification status and extent among property–liability insurers. Our results show that the extent of diversification is not driven by risk pooling considerations; insurers operating in more volatile business lines do not diversify more. Diversification can rather be explained by the benefits of internal capital markets and barriers to business growth like market size and concentration. In our analysis, we distinguish between related and unrelated diversification. Using a measure of unrelated line‐of‐business diversification we find the first support for the diversification prediction of the managerial discretion hypothesis that mutual insurers should be less diversified than stock insurers. While mutual insurers tend to exhibit higher levels of total diversification, they engage in significantly less unrelated diversification than do stock insurers.     

A Dynamic Analysis of the Demand for Life Insurance

Prior research suggests that neither the choice to own life insurance nor the amount purchased is consistently related to the presence of children in the household. While these perplexing findings are based on a static framework, we alternatively examine life insurance demand in a dynamic framework as a function of changes in household life cycle and financial condition. Our results indicate both a statistically and economically significant relation between life events, such as new parenthood, and the demand for life insurance. We also provide new evidence in support of the emergency fund hypothesis: households in which either spouse has become unemployed are more likely than other households to surrender their whole life insurance.     

Competition for attention in the Information (overload) Age

The Information Age has a surfeit of information received relative to what is processed. We model multiple sectors competing for consumer attention, with competition in price within each sector. Sector advertising levels follow a constant elasticity of substitution (CES) form, and within‐sector prices are dispersed with a truncated Pareto distribution. The “information hump” shows highest ad levels for intermediate attention levels. Overall, advertising is excessive, although the allocation across sectors is optimal. The blame for information overload falls most on product categories with low information transmission costs and low profits.     

Mastering the management system

Companies have always found it hard to balance pressing operational concerns with long-term strategic priorities. The tension is critical: World-class processes won't lead to success without the right strategic direction, and the best strategy in the world will get nowhere without strong operations to execute it. In this article, Kaplan, of Harvard Business School, and Norton, founder and director of the Palladium Group, explain how to effectively manage both strategy and operations by linking them tightly in a closed-loop management system. The system comprises five stages, beginning with strategy development, which springs from a company's mission, vision, and value statements, and from an analysis of its strengths, weaknesses, and competitive environment. In the next stage, managers translate the strategy into objectives and initiatives with strategy maps, which organize objectives by themes, and balanced scorecards, which link objectives to performance metrics. Stage three involves creating an operational plan to accomplish the objectives and initiatives; it includes targeting process improvements and preparing sales, resource, and capacity plans and dynamic budgets. Managers then put plans into action, monitoring their effectiveness in stage four. They review operational, environmental, and competitive data; assess progress; and identify barriers to execution. In the final stage, they test the strategy, analyzing cost, profitability, and correlations between strategy and performance. If their underlying assumptions appear faulty, they update the strategy, beginning another loop. The authors present not only a comprehensive blueprint for successful strategy execution but also a managerial tool kit, illustrated with examples from HSBC Rail, Cigna Property and Casualty, and Store 24. The kit incorporates leading management experts' frameworks, outlining where they fit into the management cycle.     

International equity flows, marginal conditional stochastic dominance and diversification

The weak empirical evidence linking diversification and international equity flows calls into question the diversification paradigm at the international level and the analytical framework it implies. Using the concept of Marginal Conditional Stochastic Dominance (MCSD) to estimate the diversification opportunities, this paper reexamines the role that diversification opportunities play in the determination of international equity flows. It provides strong evidence that when diversification opportunities are measured in terms of MCSD, they are significant determinants of international equity flows. Capital flows into dominant markets and flees markets that are dominated. These results are robust with respect to a range of conventional control variables documented in the outstanding literature.