Managing Multiple Facets of Risk in New Product Alliances*

The trend of forming alliances to develop new products continues; however, many of these new product alliances fail. As such we explore how key risk types intrinsic in new product alliances, performance, relational, and knowledge appropriation risks, influence alliance success. Further, we theorize that different alliance governance mechanisms can reduce the negative impact of risks on alliance success. To disentangle possible heterogeneous factors across firms that may affect the interplay of risk assessments and the use of governance mechanisms, we employ latent class regression analysis on survey data collected from 128 new product alliance firms and find support for a two‐regime solution. Longer alliance relationships and lower technological turbulence are factors for some firms (regime one), while the opposite are factors for other firms (regime two). These two regimes show different patterns in the interplay of risk assessments and governance for alliance success. Our theory and results support viewing risk as a multiple‐factor concept and by understanding the different impacts of the risk types in new product alliances and how governance mechanisms mitigate such effects, we aid managers' decision making regarding the balance of contractual versus normative governance in new product alliances. Understanding the heterogeneous factors inherent in these complex relationships enables managers to understand the conditions in which various governance mechanisms promote new product alliance success.     

Identifying Equilibrium Models of Labor Market Sorting

We assess the empirical content of equilibrium models of labor market sorting based on unobserved (to economists) characteristics. In particular, we show theoretically that all parameters of the classic model of sorting based on absolute advantage in Becker, 1973 with search frictions can be nonparametrically identified using only matched employer–employee data on wages and labor market transitions. In particular, these data are sufficient to nonparametrically estimate the output of any individual worker with any given firm. Our identification proof is constructive and we provide computational algorithms that implement our identification strategy given the limitations of the available data sets. Finally, we add on‐the‐job search to the model, extend the identification strategy, and apply it to a large German matched employer–employee data set to describe detailed patterns of sorting and properties of the production function.     

The Economics of Density: Evidence From the Berlin Wall

This paper develops a quantitative model of internal city structure that features agglomeration and dispersion forces and an arbitrary number of heterogeneous city blocks. The model remains tractable and amenable to empirical analysis because of stochastic shocks to commuting decisions, which yield a gravity equation for commuting flows. To structurally estimate agglomeration and dispersion forces, we use data on thousands of city blocks in Berlin for 1936, 1986, and 2006 and exogenous variation from the city's division and reunification. We estimate substantial and highly localized production and residential externalities. We show that the model with the estimated agglomeration parameters can account both qualitatively and quantitatively for the observed changes in city structure. We show how our quantitative framework can be used to undertake counterfactuals for changes in the organization of economic activity within cities in response, for example, to changes in the transport network.     

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.     

Supply Networks as a Complex Adaptive System: Toward Simulation‐Based Theory Building on Evolutionary Decision Making

In this article, we examine how the firms embedded in supply networks engage in decision making over time. The supply networks as a complex adaptive system are simulated using cellular automata (CA) through a dynamic evolution of cooperation (i.e., “voice” decision) and defection (i.e., “exit” decision) among supply network agents (i.e., firms). Simple local rules of interaction among firms generate complex patterns of cooperation and defection decisions in the supply network. The incentive schemes underlying decision making are derived through different configurations of the payoff‐matrix based on the game theory argument. The prisoner's dilemma game allows capturing the localized decision‐making process by rational agents, and the CA model allows the self‐organizing outcome to emerge. By observing the evolution of decision making by cooperating and defecting agents, we offer testable propositions regarding relationship development and distributed nature of governance mechanisms for managing supply networks.     

Altruism in Networks

We provide the first analysis of altruism in networks. Agents are embedded in a fixed network and care about the well‐being of their network neighbors. Depending on incomes, they may provide financial support to their poorer friends. We study the Nash equilibria of the resulting game of transfers. We show that equilibria maximize a concave potential function. We establish existence, uniqueness of equilibrium consumption, and generic uniqueness of equilibrium transfers. We characterize the geometry of the network of transfers and highlight the key role played by transfer intermediaries. We then study comparative statics. A positive income shock to an individual benefits all. For small changes in incomes, agents in a component of the network of transfers act as if they were organized in an income‐pooling community. A decrease in income inequality or expansion of the altruism network may increase consumption inequality.     

Sales Force and Competition in Financial Product Markets: The Case of Mexico's Social Security Privatization

This paper examines how sales force impacts competition and equilibrium prices in the context of a privatized pension market. We use detailed administrative data on fund manager choices and worker characteristics at the inception of Mexico's privatized social security system, where fund managers had to set prices (management fees) at the national level, but could select sales force levels by local geographic areas. We develop and estimate a model of fund manager choice where sales force can increase or decrease customer price sensitivity. We find exposure to sales force lowered price sensitivity, leading to inelastic demand and high equilibrium fees. We simulate oft proposed policy solutions: a supply‐side policy with a competitive government player and a demand‐side policy that increases price elasticity. We find that demand‐side policies are necessary to foster competition in social safety net markets with large segments of inelastic consumers.     

Consumption Dynamics During Recessions

Are there times when durable spending is less responsive to economic stimulus? We argue that aggregate durable expenditures respond more sluggishly to economic shocks during recessions because microeconomic frictions lead to declines in the frequency of households' durable adjustment. We show this by first using indirect inference to estimate a heterogeneous agent incomplete markets model with fixed costs of durable adjustment to match consumption dynamics in PSID microdata. We then show that aggregating this model delivers an extremely procyclical Impulse Response Function (IRF) of durable spending to aggregate shocks. For example, the response of durable spending to an income shock in 1999 is estimated to be almost twice as large as if it occurred in 2009. This procyclical IRF holds in response to standard business cycle shocks as well as in response to various policy shocks, and it is robust to general equilibrium. After estimating this robust theoretical implication of micro frictions, we provide additional direct empirical evidence for its importance using both cross‐sectional and time‐series data.     

Continuity,Inertia, and Strategic Uncertainty: A Test of the Theory of Continuous Time Games

The theory of continuous time games (Simon and Stinchcombe (1989), Bergin and MacLeod (1993)) shows that continuous time interactions can generate very different equilibrium behavior than conventional discrete time interactions. We introduce new laboratory methods that allow us to eliminate natural inertia in subjects' decisions in continuous time experiments, thereby satisfying critical premises of the theory and enabling a first‐time direct test. Applying these new methods to a simple timing game, we find strikingly large gaps in behavior between discrete and continuous time as the theory suggests. Reintroducing natural inertia into these games causes continuous time behavior to collapse to discrete time‐like levels in some settings as predicted by subgame perfect Nash equilibrium. However, contra this prediction, the strength of this effect is fundamentally shaped by the severity of inertia: behavior tends towards discrete time benchmarks as inertia grows large and perfectly continuous time benchmarks as it falls towards zero. We provide evidence that these results are due to changes in the nature of strategic uncertainty as inertia approaches the continuous limit.     

Parametric Inference and Dynamic State Recovery From Option Panels

We develop a new parametric estimation procedure for option panels observed with error. We exploit asymptotic approximations assuming an ever increasing set of option prices in the moneyness (cross‐sectional) dimension, but with a fixed time span. We develop consistent estimators for the parameters and the dynamic realization of the state vector governing the option price dynamics. The estimators converge stably to a mixed‐Gaussian law and we develop feasible estimators for the limiting variance. We also provide semiparametric tests for the option price dynamics based on the distance between the spot volatility extracted from the options and one constructed nonparametrically from high‐frequency data on the underlying asset. Furthermore, we develop new tests for the day‐by‐day model fit over specific regions of the volatility surface and for the stability of the risk‐neutral dynamics over time. A comprehensive Monte Carlo study indicates that the inference procedures work well in empirically realistic settings. In an empirical application to S&P 500 index options, guided by the new diagnostic tests, we extend existing asset pricing models by allowing for a flexible dynamic relation between volatility and priced jump tail risk. Importantly, we document that the priced jump tail risk typically responds in a more pronounced and persistent manner than volatility to large negative market shocks.     

WORKERS,WARRIORS, AND CRIMINALS: SOCIAL CONFLICT IN GENERAL EQUILIBRIUM

We incorporate appropriation activities (social conflict) into canonical models of trade and study how economic shocks and policies affect the intensity of conflict. We show that not all shocks that could make society richer reduce conflict: positive shocks to labor‐intensive industries diminish conflict, while positive shocks to capital‐intensive industries increase it. The key requirement is that conflict activities be more labor intensive than the economy as this determines how shocks affect the returns and costs of conflict. Our theory is consistent with several observed patterns of conflict and implies that empirical work should take into account the relative factor intensities of the productive and conflict sectors in each country. Incorporating appropriation into a canonic general equilibrium model affects what policies may be deemed desirable: in order to reduce conflict and generate Pareto‐improvements policy must be distortionary, while reforms that appear efficiency‐enhancing under the unrealistic assumption of perfect property rights may backfire. This offers one explanation for why reforms based on traditional models without appropriation may be delayed and become unpopular when implemented, and why societies may sympathize with seemingly inefficient redistribution.     

Knowledge Life Cycle,Knowledge Inventory,and Knowledge Acquisition Strategies*

For a knowledge‐ and skill‐centric organization, the process of knowledge management encompasses three important and closely related elements: (i) task assignments, (ii) knowledge acquisition through training, and (iii) maintaining a proper level of knowledge inventory among the existing workforce. Trade‐off on choices between profit maximization in the short run and agility and flexibility in the long term is a vexing problem in knowledge management. In this study, we examine the effects of different training strategies on short‐term operational efficiency and long‐term workforce flexibility. We address our research objective by developing a computational model for task and training assignment in a dynamic knowledge environment consisting of multiple distinct knowledge dimensions. Overall, we find that organizational slack is an important variable in determining the effectiveness of training strategies. Training strategies focused on the most recent skills are found to be the preferred option in most of the considered scenarios. Interestingly, increased efficiencies in training can actually create preference conflict between employees and the firm. Our findings indicate that firms facing longer knowledge life cycles, higher slack in workforce capacity, and better training efficiencies actually face more difficult challenges in knowledge management.     

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.     

Nonparametric Stochastic Discount Factor Decomposition

Stochastic discount factor (SDF) processes in dynamic economies admit a permanent‐transitory decomposition in which the permanent component characterizes pricing over long investment horizons. This paper introduces an empirical framework to analyze the permanent‐transitory decomposition of SDF processes. Specifically, we show how to estimate nonparametrically the solution to the Perron–Frobenius eigenfunction problem of Hansen and Scheinkman, 2009. Our empirical framework allows researchers to (i) construct time series of the estimated permanent and transitory components and (ii) estimate the yield and the change of measure which characterize pricing over long investment horizons. We also introduce nonparametric estimators of the continuation value function in a class of models with recursive preferences by reinterpreting the value function recursion as a nonlinear Perron–Frobenius problem. We establish consistency and convergence rates of the eigenfunction estimators and asymptotic normality of the eigenvalue estimator and estimators of related functionals. As an application, we study an economy where the representative agent is endowed with recursive preferences, allowing for general (nonlinear) consumption and earnings growth dynamics.     

Toward a Theory of Whistleblowing Intentions: A Benefit‐to‐Cost Differential Perspective*

In order to rescue information technology (IT) projects when they go awry, it is critical to understand the factors that affect bad news reporting. Whistleblowing theory holds promise in this regard and a number of salient factors that may influence whistleblowing intentions have been identified. However, an integrative theory that explains how they influence whistleblowing intentions has been conspicuously absent. In this research, we introduce and test a middle‐range theory of whistleblowing that can explain how and why a variety of factors may influence an individual's whistleblowing intentions. Drawing on the social information processing perspective, we propose that individuals holistically weigh the perceived “benefit‐to‐cost differential” and that this mediates the relationship between whistleblowing factors and whistleblowing intentions. Tests using data collected from 159 experienced IT project managers largely support our theoretical perspective, in which the central explanatory variable (benefit‐to‐cost differential) significantly mediates a majority of the proposed relationships. Implications of these findings for research and practice are discussed.     

Generalized Method of Integrated Moments for High‐Frequency Data

We propose a semiparametric two‐step inference procedure for a finite‐dimensional parameter based on moment conditions constructed from high‐frequency data. The population moment conditions take the form of temporally integrated functionals of state‐variable processes that include the latent stochastic volatility process of an asset. In the first step, we nonparametrically recover the volatility path from high‐frequency asset returns. The nonparametric volatility estimator is then used to form sample moment functions in the second‐step GMM estimation, which requires the correction of a high‐order nonlinearity bias from the first step. We show that the proposed estimator is consistent and asymptotically mixed Gaussian and propose a consistent estimator for the conditional asymptotic variance. We also construct a Bierens‐type consistent specification test. These infill asymptotic results are based on a novel empirical‐process‐type theory for general integrated functionals of noisy semimartingale processes.     

Sign Restrictions,Structural Vector Autoregressions,and Useful Prior Information

This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.     

Understanding the Price Effects of the MillerCoors Joint Venture

We document abrupt increases in retail beer prices just after the consummation of the MillerCoors joint venture, both for MillerCoors and its major competitor, Anheuser‐Busch. Within the context of a differentiated‐products pricing model, we test and reject the hypothesis that the price increases can be explained by movement from one Nash–Bertrand equilibrium to another. Counterfactual simulations imply that prices after the joint venture are 6%–8% higher than they would have been with Nash–Bertrand competition, and that markups are 17%–18% higher. We relate the results to documentary evidence that the joint venture may have facilitated price coordination.     

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.     

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.