ABSTRACT In this article I analyze the role of cooperation between firm divisions in the budgeting process. I study a setting in which cooperation is a necessary condition for information sharing among division managers, which in turn benefits the principal. The results in this article can help reconcile the differing views between practitioners and academic researchers on the desirability of cooperation in the budgeting process. The results also have implications for some common budgeting processes observed in practice, including bundling budgeting and bottom‐up budgeting.

We propose an estimation method for models of conditional moment restrictions, which contain finite dimensional unknown parameters (theta) and infinite dimensional unknown functions (h). Our proposal is to approximate h with a sieve and to estimate theta and the sieve parameters jointly by applying the method of minimum distance. We show that: (i) the sieve estimator of h is consistent with a rate faster than n-super--1/4 under certain metric; (ii) the estimator of theta is root-n consistent and asymptotically normally distributed; (iii) the estimator for the asymptotic covariance of the theta estimator is consistent and easy to compute; and (iv) the optimally weighted minimum distance estimator of theta attains the semiparametric efficiency bound. We illustrate our results with two examples: a partially linear regression with an endogenous nonparametric part, and a partially additive IV regression with a link function. Copyright The Econometric Society 2003.

This article proposes a formal model of migration in which workers are heterogeneous and markets are stochastically correlated. We derive and characterize the optimal migration pattern of a family. We show that migration can take place even when migrants earn less abroad and, surprisingly, when earnings in the foreign country are riskier for every member of the family. Moreover, it may well be an optimal arrangement to have only dependents migrate, thus rationalizing the recent dependent‐oriented migration flows from places like Hong Kong and Taiwan. We provide some evidence in support of our theory.

Chen, Sean Chen, and Harry Sharma. We also benefited from discussions with our colleagues Ivan Brick, Oded Palmon, Emilio Venezian, and John Wald. We are particularly indebted to the anonymous referee and the editor, Paul Malatesta, for their valuable suggestions that greatly improve the paper. All errors are our own.

ABSTRACT We argue that short sellers affect prices in a significant and systematic manner. In particular, we contend that speculative short sales contribute to the weekend effect: The inability to trade over the weekend is likely to cause these short sellers to close their speculative positions on Fridays and reestablish new short positions on Mondays causing stock prices to rise on Fridays and fall on Mondays. We find evidence in support of this hypothesis based on a comparison of high short‐interest stocks and low short‐interest stocks, stocks with and without actively traded options, IPOs, zero short‐interest stocks, and highly volatile stocks.

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some nonparametric estimators that can themselves depend on the parameters to be estimated. Our results extend existing theories such as those of Pakes and Pollard (1989), Andrews (1994a), and Newey (1994). We also show that bootstrap provides asymptotically correct confidence regions for the finite dimensional parameters. We apply our results to two examples: a ‘hit rate’ and a partially linear median regression with some endogenous regressors.

This paper empirically analyzes bidding behavior and information asymmetries of stock auctions using a discriminatory auction model framework. Analyzing stock auctions using auction theory is important because it provides a logical framework for explaining observable behaviors and a solid foundation for empirical testing. Because of limited availability of stock auction data, existing empirical research based on auction theory focus mainly on treasury auctions. Away from the treasury markets, however, there is a significant paucity of literature on this subject. In this study, we make use of a detailed stock auction data set from the Taiwan Stock Exchange to empirically examine the behaviors of the Taiwan stock auction market within the framework of the auction theory. Our results show that the level of competition, the dispersion of opinion among bidders, and the bidder’s risk aversion are significant in determining auction prices. Results also show that if the offering prices are set equal to the average offering prices, the first-day post-initial public offering abnormal return will be equal to zero. Additionally, we find institutional bidders possess superior bidding skills compared to small bidders and that underwriter’s characteristics influence the bidding results.

This paper examines the linkages between discretionary accruals (DAs), managerial share ownership, management compensation, and audit fees. It draws on the theory that managers of firms with high management ownership are likely to use DAs to communicate value‐relevant information, while managers of firms with high accounting‐based compensation are likely to use DAs opportunistically to manage earnings to improve their compensation. OLS regression results of 648 Australian firms show that (1) there is a positive association between DAs and audit fees; (2) managerial ownership negatively affects the positive relationship between DAs and audit fees; and (3) this negative impact is further found to be weaker for firms with high accounting‐based management compensation.

Applying a real-options-based valuation approach, we develop and test a model that addresses the incremental value relevance of segment data beyond firmlevel accounting data. Prior studies (e.g., Zhang 2000; Biddle et al. 2001) show that equity valuation requires accounting data (in part) because accounting provides signals that guide capital investments underlying value creation. In this study, we establish that the usefulness of segment data beyond aggregate data relates to heterogeneity of investment opportunities across segments, caused by divergences of segment profitability and growth potential. Empirical results are consistent with the model's predictions. We also assess the magnitude of the valuation impact of segment information relative to that of firm-level information.