We examine how strategic interaction in an industry influences the earnings expectations of financial analysts with regard to new product strategies. We find that following announcement of new products, analysts revise earnings forecasts upward more for announcing firms competing in low-strategic interaction industries than for firms competing in high-strategic interaction industries. For value-enhancing (value-reducing) product strategies, earnings forecast revisions are more favorable for rivals competing under a high (low) degree of strategic interaction than for rivals competing under a low (high) degree of strategic interaction. Overall empirical evidence indicates that the nature of strategic competition within the industry is important in assessing the market expectations of earnings for new product announcers and their rivals.

We decompose aggregate market variance into an average correlation component and an average variance component. Only the latter commands a negative price of risk in the cross section of portfolios sorted by idiosyncratic volatility. Portfolios with high (low) idiosyncratic volatility relative to the Fama-French (1993) model have positive (negative) exposures to innovations in average stock variance and therefore lower (higher) expected returns. These two findings explain the idiosyncratic volatility puzzle of Ang et al. (2006, 2009). The factor related to innovations in average variance also reduces the pricing errors of book-to-market and momentum portfolios relative to the Fama-French (1993) model. (JEL G12) In an influential study, Ang, Hodrick, Xing, and Zhang (2006, 2009; AHXZ hereafter) show that stocks with high idiosyncratic risk, defined as the standard deviation of the residuals from the Fama-French (1993) model, have anomalously low future returns.1 This finding is puzzling in light of theories that suggest that idiosyncratic volatility (denoted as IV) should be irrelevant or positively related to expected returns.2 If a factor is missing from the Fama-French model, the sensitivity of stocks to the missing factor times the movement in the missing factor will show up in the residuals of the model. Firms with greater sensitivities to the missing factor We thank Geert Bekaert (editor), two anonymous referees, and seminar participants at the Norwegian Business School (BI) and Texas A&M University for many valuable comments and suggestions. Chen acknowledges financial support from a Nanyang Technological University Start-up Grant. Send correspondence to Ralitsa

The authors study the impact of a powerful nonfinancial stakeholder—unionized workers—on the pricing of corporate debt. Firms in more unionized industries have lower bond yields. This relation is stronger in firms with weaker financial conditions and cannot be explained by the correlation of unionization with industry characteristics, governance mechanisms, or financial leverage. Firms in unionized industries implement less risky investment policies and are less likely targets of acquisitions. Unionization reduces yields by more when firms’ takeover barriers are lower. Hence, unions are viewed favorably in the bond market because, through their influence on corporate affairs, they protect bondholders’ wealth.

While firm-initiated compensation recovery (or clawback) provisions are gaining popularity and the recently enacted Dodd-Frank Act seeks to make the clawback of erroneously awarded compensation mandatory for all listed companies, little is known about their effectiveness. We find that the incidence of accounting restatements declines after firms initiate such provisions. In addition, we show that investors and auditors view such provisions as associated with increased accounting quality and lower audit risk. Specifically, we find that firms' earnings response coefficients increase after the adoption of clawback provisions. Further, for firms that adopt clawbacks, auditors are less likely to report material internal control weaknesses, charge lower audit fees, and issue audit reports with a shorter lag.

We study decisions to sell nonexcludable private information in the presence of a trading opportunity. Sell-side agents heighten competition among agents who buy their signals to combine with their own for proprietary trading purposes and thereby promote financial market efficiency. This result holds even when the sell-side production technology is not unique. But sell-side information is subject to underinvestment if producers do not internalize the benefits. The model suggests that fee-based compensation for corporate advisory services diminishes this problem and that market efficiency is undermined by forces steering investment-banking resources toward proprietary trading.

We develop results for the use of LASSO and Post-LASSO methods to form firststage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, p, that apply even when p is much larger than the sample size, n.We rigorously develop asymptotic distribution and inference theory for the resulting IV estimators and provide conditions under which these estimators are asymptotically oracle-efficient.In simulation experiments, the LASSO-based IV estimator with a data-driven penalty performs well compared to recently advocated many-instrument-robust procedures.In an empirical example dealing with the effect of judicial eminent domain decisions on economic outcomes, the LASSObased IV estimator substantially reduces estimated standard errors allowing one to draw much more precise conclusions about the economic effects of these decisions.Optimal instruments are conditional expectations; and in developing the IV results, we also establish a series of new results for LASSO and Post-LASSO estimators of non-parametric conditional expectation functions which are of independent theoretical and practical interest.Specifically, we develop the asymptotic theory for these estimators that allows for non-Gaussian, heteroscedastic disturbances, which is important for econometric applications.By innovatively using moderate deviation theory for self-normalized sums, we provide convergence rates for these estimators that are as sharp as in the homoscedastic Gaussian case under the weak condition that log p = o(n 1/3 ).Moreover, as a practical innovation, we provide a fully data-driven method for choosing the user-specified penalty that must be provided in obtaining LASSO and Post-LASSO estimates and establish its asymptotic validity under non-Gaussian, heteroscedastic disturbances.

This paper studies nonparametric estimation of conditional moment restrictions in which the generalized residual functions can be nonsmooth in the unknown functions of endogenous variables. This is a nonparametric nonlinear instrumental variables (IV) problem. We propose a class of penalized sieve minimum distance (PSMD) estimators, which are minimizers of a penalized empirical minimum distance criterion over a collection of sieve spaces that are dense in the infinite-dimensional function parameter space. Some of the PSMD procedures use slowly growing finite-dimensional sieves with flexible penalties or without any penalty; others use large dimensional sieves with lower semicompact and/or convex penalties. We establish their consistency and the convergence rates in Banach space norms (such as a sup-norm or a root mean squared norm), allowing for possibly noncompact infinite-dimensional parameter spaces. For both mildly and severely ill-posed nonlinear inverse problems, our convergence rates in Hilbert space norms (such as a root mean squared norm) achieve the known minimax optimal rate for the nonparametric mean IV regression. We illustrate the theory with a nonparametric additive quantile IV regression. We present a simulation study and an empirical application of estimating nonparametric quantile IV Engel curves.

In this study, we examine whether, for a sample of retail chains, high levels of employee compensation can deter employee theft, an increasingly common type of fraudulent behavior. Specifically, we examine the extent to which relative wages (i.e., employee wages relative to the wages paid to comparable employees in competing stores) affect employee theft as measured by inventory shrinkage and cash shortage. Using two store‐level data sets from the convenience store industry, we find that relative wages are negatively associated with employee theft after we control for each store's employee characteristics, monitoring environment, and socio‐economic environment. Moreover, we find that relatively higher wages also promote social norms such that coworkers are less (more) likely to collude to steal inventory from their company when relative wages are higher (lower). Our research contributes to an emerging literature in management control that explores the effect of efficiency wages on employee behavior and social norms.

The average cash holdings of Chinese-listed firms decreased significantly after the split share structure reform in China, which specified a process that allowed previously nontradable shares held by controlling shareholders to be freely tradable on the exchanges. The reduction in cash holdings is greater for firms with weaker governance and firms facing more financial constraints prior to the reform. The reform also significantly reduced the average corporate savings rate, as measured by cash-to-cash-flow sensitivity. These findings are consistent with the premise that the reform removed a significant market friction, which led to better incentive alignment between controlling shareholders and minority shareholders and relaxed financial constraints. Additional analyses show that the reform affects firms' cash management policies, investment decisions, dividend payout policies, and financing choices differently in private firms than in state-owned enterprises.

Nonlinearity is an important consideration in many problems of finance and economics, such as pricing securities and solving equilibrium models. This article provides analytical treatment of a general class of nonlinear transforms for processes with tractable conditional characteristic functions. We extend existing results on characteristic function-based transforms to a substantially wider class of nonlinear functions while maintaining low dimensionality by avoiding the need to compute the density function. We illustrate the applications of the generalized transform in pricing defaultable bonds with stochastic recovery. We also use the method to analytically solve a class of general equilibrium models with multiple goods and apply this model to study the effects of time-varying labor income risk on the equity premium.