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We Do What We Are: Representation of the Self-Concept and Identity-Based Choice
Get PDFThe current research proposes a novel approach to identity-based choice that focuses on consumers’ representations of the self-concept, as captured by the perceived cause-effect relationships among features of an individual consumer’s self-concept. More specifically, the studies reported here test the proposal that the causal centrality of an identity—the number of other features of a consumer’s self-concept that the consumer believes influenced or were influenced by the identity—underlies identity importance and is a determinant of identity-based consumer behaviors. Across seven studies, using both measured and manipulated causal centrality, the current research provides evidence for the role of causal centrality in identity-based choice. Among consumers who share an identity (belong to the same social category), those who believe that the identity is more causally central perceive the identity as more important and are more likely to engage in behaviors consistent with the norms of the social category
Borrow Now, Pay Even Later: A Quantitative Analysis of Student Debt Payment Plans
No full textIn the U.S., student debt is currently the second largest component of consumer debt. Households are required to repay these loans early in their lifecycle, when marginal utility is particularly high. We study alternative contracts that offer partial or full payment deferral until later in life. We calibrate an economy with the current contracts, and then solve for counterfactual equilibria. The alternative contracts yield large welfare gains, which are robust to assumptions about the behavior of the lenders and borrower preferences. The gains are similar to those that could come from the debt relief program currently being considered in the U.S., but without its adverse fiscal implications
Real-time spatial-intertemporal dynamic pricing for balancing supply and demand in a ride-hailing network: near-optimal policies and the value of dynamic pricing
Get PDFMotivated by the growth of ride-hailing services in urban areas, we study a (tactical) real-time spatial–intertemporal dynamic pricing problem where a firm uses a pool of homogeneous servers (e.g., a fleet of taxis) to serve price-sensitive customers (i.e., a rider requesting a trip from an origin to a destination) within a finite horizon (e.g., a day). We consider a revenue maximization problem in a model that captures the stochastic and nonstationary nature of demands, and the nonnegligible travel time from one location to another location. We first show that the relative revenue loss of any static pricing policy is at least in the order of n−1/2 in a large system regime where the demand arrival rate and the number of servers scale linearly with n, which highlights the limitation of static pricing control. We also propose a static pricing control with a matching performance (up to a multiplicative logarithmic term). Next, we develop a novel state-dependent dynamic pricing control with a reduced relative revenue loss of order n−2/3. The key idea is to dynamically adjust the prices in a way that reduces the impact of past “errors” on the balance of future distributions of servers and customers across the network. Our extensive numerical studies using both a synthetic data set and a real data set from the New York City Taxi and Limousine Commission, confirm our theoretical findings and highlight the benefit of dynamic pricing over static pricing, especially when dealing with nonstationary demands. Interestingly, we also observe that the revenue improvement under our proposed policy primarily comes from an increase in the number of customers served instead of from an increase in the average prices compared with the static pricing policy. This suggests that dynamic pricing can be potentially used to simultaneously increase both revenue and the number of customers served (i.e., service level). Finally, as an extension, we discuss how to generalize the proposed policy to a setting where the firm can also actively relocate some of the available servers to different locations in the network in addition to implementing dynamic pricing
Status and Consensus: Heterogeneity in Audience Evaluations of Female - versus Male-Lead Films
Get PDFExtant research finds that status characteristics such as gender are frequently related to average quality evaluations by external audiences, but little is known about whether such characteristics are also related to consensus in quality evaluations. We examine 383 million film ratings by consumers to assess (1) whether female-lead movies elicit less consensus in quality evaluations than male-lead movies, and (2) the potential performance consequences for producers. We find that female-lead movies are rated lower on average, yet elicit ratings distributions with higher standard deviations. In split-sample analyses we find that male raters are more negative than female raters about female-lead titles, and that the two audiences differ on dispersion and skew. We also find that independent studios yield greater box office revenue from female-lead movies
Causal effects of closing businesses in a pandemic
Get PDFWe study whether state-level mandatory business closures implemented in response to the outbreak of the Covid-19 causally affect economic and health outcomes. Using plausibly exogenous variations in exposure to these restrictions, we find that they impose substantial losses to firms and workers, the former bearing approximately two thirds of the cost, consistent with firms partially insuring their workers. We show that mandatory business closures have a significant negative causal effect on mortality rates, particularly in areas featuring contact-intensive occupations. We discuss the assumptions under which the health benefits of business closures exceed their associated economic costs
Motivated counterfactual thinking and moral inconsistency: how we use our imaginations to selectively condemn and condone
Get PDFPeople selectively enforce their moral principles, excusing wrongdoing when it suits them. We identify an underappreciated source of this moral inconsistency: the ability to imagine counterfactuals, or alternatives to reality. Counterfactual thinking offers three sources of flexibility that people exploit to justify preferred moral conclusions: People can (a) generate counterfactuals with different content (e.g., consider how things could have been better or worse), (b) think about this content using different comparison processes (i.e., focus on how it is similar to or different than reality), and (c) give the result of these processes different weights (i.e., allow counterfactuals more or less influence on moral judgments). These sources of flexibility help people license unethical behavior and can fuel political conflict. Motivated reasoning may be less constrained by facts than previously assumed; people’s capacity to condemn and condone whom they wish may be limited only by their imaginations
The Asymptotic Equivalence of Ridge and Principal Component Regression with Many Predictors
No full textThe asymptotic properties of ridge regression in large dimension are studied. Two key results are established. First, consistency and rates of convergence for ridge regression are obtained under assumptions which impose different rates of increase in the dimension n between the first n1 and the remaining n−n1 eigenvalues of the population covariance of the predictors. Second, it is proved that under the special and more restrictive case of an approximate factor structure, principal component and ridge regression have the same rate of convergence and the rate is faster than the one previously established for ridge
Forecasting imbalance price densities with statistical methods and neural networks
No full textDespite the extensive research on electricity price forecasting, forecasting imbalance prices is a relatively new topic. Interest, however, is growing because of the greater uncertainties and costs involved in real-time balancing. Whilst there has been previous work on nonlinear statistical methods, this paper reports on a comparative study involving these and various neural network architectures including N-BEATS, fully connected, attention-based, and recurrent neural networks. To ensure valid comparability, these different neural networks were tested on the same data from Britain used in the previous point and density forecasting research. While there are only marginal improvements in point forecasts, we find that neural networks produce significantly more accurate density forecasts. Since the risks involved with exposure to imbalance prices are becoming a serious consideration for market participants, accurate density forecasts are crucial for risk management
Sexism, culture, and firm value: evidence from the Harvey Weinstein scandal and the #MeToo movement
Get PDFDuring the revelation of the Harvey Weinstein scandal and the re-emergence of the #MeToo movement, firms with a non-sexist corporate culture, proxied by having women among the five highest paid executives, earn excess returns of 1.3% relative to firms without female top executives. These returns are driven by changes in investor preferences towards firms with a non-sexist culture. Institutional ownership increases in firms with a non-sexist culture after the Weinstein/#MeToo events, particularly for investors with larger holdings and investors with a lower ESG focus ex-ante. Firms without female top executives improve gender diversity after these events, particularly in more sexist states and in industries with few women executives. Our evidence attests to the value of having a non-sexist corporate culture, and indicates that changes in societal norms towards women are permeating into capital markets and corporations
Sustainable power purchase contracts for local industries from floating-solar and pumped-hydro integration
No full textThis paper analyses the technical and business cases for a hybrid floating-solar and pumped-hydro facility to provide secure, baseload power to local industrial and commercial users through bilateral power purchase agreement contracting and private wire connections. Based upon a realistic hydrological setting with a range of assumptions for both the floating-solar and pumped-hydro installations, daily operations are optimized to provide different levels of secure baseload power purchase agreement contracts. This research shows how the premium for baseload contracts depends on the size of the contracts and the size of the solar installation. The premiums are the opportunity costs to the hydro operators from potential sales to the wholesale market. We find that the premiums are affordable to local users, and that the combination of solar and pumped storage thereby enables a hydro operator to offer higher levels of secure baseload power, throughout the year, to local industries where the national power resources are otherwise unreliable