Promotion,Turnover, and Compensation in the Executive Labor Market

This paper develops a generalized Roy model with human capital accumulation, moral hazard, and career concerns. We identify and estimate the model with a large panel that matches data on publicly listed firms to information on their executives. The structural estimates obtained are used to decompose the firm‐size pay gap. We find that although total compensation and incentive pay increase with firm size, certainty‐equivalent pay decreases with firm size. In larger firms, and for more highly ranked executives, weaker signal quality about effort results in higher risk premiums. This risk premium accounts for roughly 80 percent of the firm‐size gap in total compensation. Larger firms are also willing to pay more than smaller ones to attract executives. Finally, the estimated coefficients on human capital accumulation from formal education and experience gained from different firms are individually significant, but their collective effect on firm‐size pay differentials nets out.     

Feedback Mechanisms,Judgment Bias,and Trust Formation in Online Auctions*

Online markets, like eBay, Amazon, and others rely on electronic reputation or feedback systems to curtail adverse selection and moral hazard risks and promote trust among participants in the marketplace. These systems are based on the idea that providing information about a trader's past behavior (performance on previous market transactions) allows market participants to form judgments regarding the trustworthiness of potential interlocutors in the marketplace. It is often assumed, however, that traders correctly process the data presented by these systems when updating their initial beliefs. In this article, we demonstrate that this assumption does not hold. Using a controlled laboratory experiment simulating an online auction site with 127 participants acting as buyers, we find that participants interpret seller feedback information in a biased (non‐Bayesian) fashion, overemphasizing the compositional strength (i.e., the proportion of positive ratings) of the reputational information and underemphasizing the weight (predictive validity) of the evidence as represented by the total number of transactions rated. Significantly, we also find that the degree to which buyers misweigh seller feedback information is moderated by the presentation format of the feedback system as well as attitudinal and psychological attributes of the buyer. Specifically, we find that buyers process feedback data presented in an Amazon‐like format—a format that more prominently emphasizes the strength dimension of feedback information—in a more biased (less‐Bayesian) manner than identical ratings data presented using an eBay‐like format. We further find that participants with greater institution‐based trust (i.e., structural assurance) and prior online shopping experience interpreted feedback data in a more biased (less‐Bayesian) manner. The implications of these findings for both research and practice are discussed.     

A Dynamic Model of Demand for Houses and Neighborhoods

This paper develops a dynamic model of neighborhood choice along with a computationally light multi‐step estimator. The proposed empirical framework captures observed and unobserved preference heterogeneity across households and locations in a flexible way. We estimate the model using a newly assembled data set that matches demographic information from mortgage applications to the universe of housing transactions in the San Francisco Bay Area from 1994 to 2004. The results provide the first estimates of the marginal willingness to pay for several non‐marketed amenities—neighborhood air pollution, violent crime, and racial composition—in a dynamic framework. Comparing these estimates with those from a static version of the model highlights several important biases that arise when dynamic considerations are ignored.     

Identifying Latent Structures in Panel Data

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered—penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier‐Lasso (C‐Lasso) that serves to shrink individual coefficients to the unknown group‐specific coefficients. C‐Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C‐Lasso also achieves the oracle property so that group‐specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C‐Lasso is preserved in some special cases. Simulations demonstrate good finite‐sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented.     

Female Labor Supply,Human Capital,and Welfare Reform

We estimate a dynamic model of employment, human capital accumulation—including education, and savings for women in the United Kingdom, exploiting tax and benefit reforms, and use it to analyze the effects of welfare policy. We find substantial elasticities for labor supply and particularly for lone mothers. Returns to experience, which are important in determining the longer‐term effects of policy, increase with education, but experience mainly accumulates when in full‐time employment. Tax credits are welfare improving in the U.K., increase lone‐mother labor supply and marginally reduce educational attainment, but the employment effects do not extend beyond the period of eligibility. Marginal increases in tax credits improve welfare more than equally costly increases in income support or tax cuts.     

The Influence of Cost and Quality Priorities on the Propensity to Outsource Production*

Outsourcing of production has escalated over the past decade due to unprecedented competition and worldwide access to low‐cost labor markets. This article examines how cost and quality priorities—two key attributes of manufacturing strategy—influence a manufacturer's propensity to outsource. By doing so, we bridge the existing gap between research on manufacturing strategy and firm boundaries. We develop a theory‐based model that links a manufacturer's cost and quality priorities to its plans to outsource production. Our empirical analyses, based on survey data obtained from 867 manufacturing business units, control for firm‐specific factors previously shown to impact outsourcing, including asset specificity, uncertainty, and current capabilities in cost and quality. We found that the competitive priority placed on cost played an integral role in sourcing decisions, while, surprisingly, conformance quality priorities did not. The cost result is consistent with our expectations and observations in practice. The significant effect of cost priority on outsourcing shows that any theory of firm boundaries that fails to consider competitive priorities is incomplete. The finding regarding quality, which was counter to our expectations, may partially explain why there is an emergence of so many nonconforming products associated with outsourcing. Taken together, our results provide theoretical insights for future research into how manufacturing managers can improve their decision making on outsourcing production.     

A Dynamic Collaboration Capability as a Source of Competitive Advantage

The resource‐based view of the firm argues the essence of decision making is to determine how firm and supply chain resources can be configured to achieve inimitable advantage and superior performance. However, combining resources found among diverse members of a supply chain requires higher levels of coordination than exist at most companies. Manifest cross‐functional and interorganizational conflict impedes the relational advantages of collaboration. This research employs a multimethod—survey and interview—approach to evaluate collaboration's influence on operational and firm performance. Our findings show that collaboration, as a dynamic capability, mediates the conflict resulting from functional orientations, and improves performance. Specific structural enablers to enhance an organization's collaborative capability are identified and described, providing insight into how firms can exploit interfirm resources for competitive advantage.     

The Role of Contracts on Quality and Returns to Quality in Offshore Software Development Outsourcing

In this study, we examine how the different incentive structures inherent in two primary contract types—time and materials (T&M) and fixed price (FP)—influence the quality provided by the vendor in the software development outsourcing industry. We argue that the incentive structure of FP contracts motivates a vendor to be more efficient in the software development process, which results in higher quality as compared to projects executed under a T&M contract. We thus argue that vendors consistently staff FP projects with better trained personnel because they face the most risk on these contracts, resulting in better outcomes on these projects. We extend our analysis to propose that providing higher quality is associated with higher profit margins for the vendor only for FP contracts. We develop and test these hypotheses on data collected from 100 software projects completed by a leading Indian offshore vendor. The results provide strong support for our fundamental thesis that the drivers of and returns to quality vary by contract type. We discuss the implications of our research for both researchers and practitioners.     

Formal Infrastructure and Ethical Decision Making: An Empirical Investigation and Implications for Supply Management

Building on Rest's (1986) conceptual model of ethical decision making, we derive and empirically test a model that links an organization's formal ethical infrastructure to individuals’ moral awareness of ethical situations, moral judgment, and moral intention. We contribute to the literature by shedding light on the importance of a multifaceted formal ethical infrastructure—consisting of formal communication, recurrent communication, formal surveillance, and formal sanctions—as a crucial antecedent of moral awareness. In so doing, we discern how these four elements of a formal ethical infrastructure combine to collectively influence moral awareness based on a second‐order factor structure using structural equation modeling. We test our model based on survey data from 805 respondents with significant work experience across three separate ethical scenarios. Our results across the three scenarios provide overall support for our model. We found that a second‐order factor structure for the formal ethical infrastructure explains the variance among the four infrastructure elements and that a multifaceted formal ethical infrastructure significantly increases moral awareness. Our results further suggest a strong positive effect of moral awareness on moral judgment, which in turn was found to have a positive impact on moral intention. These results were substantiated when taking several individual and contextual control variables into account, such as gender, age, religiosity, work satisfaction, and a de facto ethical climate. Implications for theory, practice, and supply management are discussed.     

Aspirations and Inequality

This paper develops a theory of socially determined aspirations, and the interaction of those aspirations with growth and inequality. The interaction is bidirectional: economy‐wide outcomes determine individual aspirations, which in turn determine investment incentives and social outcomes. Thus aspirations, income, and the distribution of income evolve jointly. When capital stocks lie in some compact set, steady state distributions must exhibit inequality and are typically clustered around local poles. When sustained growth is possible, initial histories matter. Either there is convergence to an equal distribution (with growth) or there is perennial relative divergence across clusters, with within‐cluster convergence. A central feature that drives these results is that aspirations that are moderately above an individual's current standard of living tend to encourage investment, while still higher aspirations may lead to frustration.     

Examining the Impact of Pre‐Implementation Expectations on Post‐Implementation Use of Enterprise Systems: A Longitudinal Study

This article builds upon the technology acceptance model and theories of technology sensemaking to explore pre‐enterprise system adoption expectations and post‐enterprise system adoption outcomes in a longitudinal setting. Building on the exploitation and exploration paradigm, we propose that task productivity and task innovation expectations are the key drivers of users’ pre‐adoption enterprise system usage intention. Further, we argue that the enterprise system facilitates generation of a common knowledge base that may encourage a more integrated organizational culture and promote shared understanding among employees. Considering the distinction between mandatory and voluntary contexts, we propose that user acceptance of the enterprise system at the pre‐ and post‐adoption stages will mediate these relationships in a mandatory context. The results show that the influence of pre‐adoption expectations regarding task productivity and task innovation on intention to use an enterprise system is mediated by user acceptance of the enterprise system. Intention to use an enterprise system is positively related to actual use. At the post‐adoption stage, the influence of actual use on shared understanding is mediated by user acceptance of an enterprise system and enterprise system use has a direct negative impact on task efficiency in the initial period after implementation. Overall, the results highlight that user acceptance at both pre‐ and post‐adoption stages are critical factors when usage is mandatory. These findings suggest a number of important implications for research and for managerial action.     

Market‐Triggered Changes in Capital Structure: Equilibrium Price Dynamics

We analyze the internal consistency of using the market price of a firm's equity to trigger a contractual change in the firm's capital structure, given that the value of the equity itself depends on the firm's capital structure. Of particular interest is the case of contingent capital for banks, in the form of debt that converts to equity, when conversion is triggered by a decline in the bank's stock price. We analyze the problem of existence and uniqueness of equilibrium values for a firm's liabilities in this context, meaning values consistent with a market‐price trigger. Discrete‐time dynamics allow multiple equilibria. In contrast, we show that the possibility of multiple equilibria can largely be ruled out in continuous time, where the price of the triggering security adjusts in anticipation of breaching the trigger. Our main condition for existence of an equilibrium requires that the consequences of triggering a conversion be consistent with the direction in which the trigger is crossed. For the design of contingent capital with a stock price trigger, this condition may be interpreted to mean that conversion should be disadvantageous to shareholders, and it is satisfied by setting the trigger sufficiently high. Uniqueness follows provided the trigger is sufficiently accessible by all candidate equilibria. We illustrate precise formulations of these conditions with a variety of applications.     

Identifying Higher‐Order Rationality

Strategic choice data from a carefully chosen set of ring‐network games are used to obtain individual‐level estimates of higher‐order rationality. The experimental design exploits a natural exclusion restriction that is considerably weaker than the assumptions underlying alternative designs in the literature. In our data set, 93 percent of subjects are rational, 71 percent are rational and believe others are rational, 44 percent are rational and hold second‐order beliefs that others are rational, and 22 percent are rational and hold at least third‐order beliefs that others are rational.     

Consistency of Higher Order Risk Preferences

Risk aversion (a second‐order risk preference) is a time‐proven concept in economic models of choice under risk. More recently, the higher order risk preferences of prudence (third‐order) and temperance (fourth‐order) also have been shown to be quite important. While a majority of the population seems to exhibit both risk aversion and these higher order risk preferences, a significant minority does not. We show how both risk‐averse and risk‐loving behaviors might be generated by a simple type of basic lottery preference for either (1) combining “good” outcomes with “bad” ones, or (2) combining “good with good” and “bad with bad,” respectively. We further show that this dichotomy is fairly robust at explaining higher order risk attitudes in the laboratory. In addition to our own experimental evidence, we take a second look at the extant laboratory experiments that measure higher order risk preferences and we find a fair amount of support for this dichotomy. Our own experiment also is the first to look beyond fourth‐order risk preferences, and we examine risk attitudes at even higher orders.     

Shadow Insurance

Life insurers use reinsurance to move liabilities from regulated and rated companies that sell policies to shadow reinsurers, which are less regulated and unrated off‐balance‐sheet entities within the same insurance group. U.S. life insurance and annuity liabilities ceded to shadow reinsurers grew from $11 billion in 2002 to $364 billion in 2012. Life insurers using shadow insurance, which capture half of the market share, ceded 25 cents of every dollar insured to shadow reinsurers in 2012, up from 2 cents in 2002. By relaxing capital requirements, shadow insurance could reduce the marginal cost of issuing policies and thereby improve retail market efficiency. However, shadow insurance could also reduce risk‐based capital and increase expected loss for the industry. We model and quantify these effects based on publicly available data and plausible assumptions.     

Program Evaluation and Causal Inference With High‐Dimensional Data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data‐rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function‐valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced‐form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post‐regularization and post‐selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced‐form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment‐condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function‐valued) parameters within this general framework where any high‐quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high‐dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity‐based estimation of regression functions for function‐valued outcomes.     

First‐Price Auctions With General Information Structures: Implications for Bidding and Revenue

We explore the impact of private information in sealed‐bid first‐price auctions. For a given symmetric and arbitrarily correlated prior distribution over values, we characterize the lowest winning‐bid distribution that can arise across all information structures and equilibria. The information and equilibrium attaining this minimum leave bidders indifferent between their equilibrium bids and all higher bids. Our results provide lower bounds for bids and revenue with asymmetric distributions over values. We also report further characterizations of revenue and bidder surplus including upper bounds on revenue. Our work has implications for the identification of value distributions from data on winning bids and for the informationally robust comparison of alternative auction mechanisms.     

Search With Adverse Selection

This paper analyzes a sequential search model with adverse selection. We study information aggregation by the price—how close the equilibrium prices are to the full‐information prices—when search frictions are small. We identify circumstances under which prices fail to aggregate information well even when search frictions are small. We trace this to a strong form of the winner's curse that is present in the sequential search model. The failure of information aggregation may result in inefficient allocations.     

Why Competition from a Multi‐Channel E‐Tailer Does Not Always Benefit Consumers*

Empirical studies have delivered mixed conclusions on whether the widely acclaimed assertions of lower electronic retail (e‐tail) prices are true and to what extent these prices impact conventional retail prices, profits, and consumer welfare. For goods that require little in‐person pre‐ or postsales support such as CDs, DVDs, and books, we extend Balasubramanian's e‐tailer‐in‐the‐center, spatial, circular market model to examine the impact of a multichannel e‐tailer's presence on retailers' decisions to relocate, on retail prices and profits, and consumer welfare. We demonstrate several counter‐intuitive results. For example, when the disutility of buying online and shipping costs are relatively low, retailers are better off by not relocating in response to an e‐tailer's entry into the retail channel. In addition, such an entry—a multichannel strategy—may lead to increased retail prices and increased profits across the industry. Finally, consumers can be better off with less channel competition. The underlying message is that inferences regarding prices, profits, and consumer welfare critically depend on specifications of the good, disutility and shipping costs versus transportation costs (or more generally, positioning), and competition.     

Grouped Patterns of Heterogeneity in Panel Data

This paper introduces time‐varying grouped patterns of heterogeneity in linear panel data models. A distinctive feature of our approach is that group membership is left unrestricted. We estimate the parameters of the model using a “grouped fixed‐effects” estimator that minimizes a least squares criterion with respect to all possible groupings of the cross‐sectional units. Recent advances in the clustering literature allow for fast and efficient computation. We provide conditions under which our estimator is consistent as both dimensions of the panel tend to infinity, and we develop inference methods. Finally, we allow for grouped patterns of unobserved heterogeneity in the study of the link between income and democracy across countries.