This paper develops approximations of the Gram-Charlier type to the cumulative distribution function of the instrumental variables estimator on classical assumptions. In the special case where there are only two endogenous variables in the estimated equation, exact values of the cumulative distribution function are computed by numerical integration and compared with the approximations. Although the error in the approximation depends critically on the parameters of the stochastic model, the approximation is good for the special case even for small sample size over a wide range of values of the parameters. THIS PAPER was originally conceived as a study of the finite sample distribution of two stage least squares estimates. Since it was found that the distribution of a more general class of instrumental variables estimates can be discussed in the same way with a trifling complication of the algebra, the paper was modified to cover these estimates. The basic approach is somewhat similar to that of Nagar [15], since it involves expanding the formulae for the estimator as a series of terms of 0(1), O(T-+), O(T- 1), O(T- 1+), etc., and from this a similar expansion is found for the cumulative probability of the form

We find that firms with CFOs who have extensive social connections within the finance industry hold less precautionary cash. CFO connections matter more than CEO connections, reflecting the preeminence of CFOs among C-level executives in cash management and negotiating access to corporate finance. Firms reduce the proportion of assets held in cash by seven percentage points in the two years following CFO turnover and the appointment of a CFO with finance industry connections. The stock market valuation of incremental cash holdings of firms with well-connected CFOs is lower than for other firms, consistent with investor recognition of CFO social capital as an alternative means to address constraints on external capital.

The household production approach to consumer behavior, developed from the work of Gary Becker, William Gorman, and Kelvin Lancaster, has considerable descriptive appeal in modelling the decisions of households. The approach derives from the observation that households frequently purchase market goods that do not yield utility directly, but are combined to produce commodity service flows which the household values. Thus observed behavior is determined by household production technology as well as by tastes. The advantage of this distinction is that we can pose reasonable hypotheses about characteristics of technology, though we rarely possess useful a priori information regarding tastes. The putative advantages of the household production approach are questioned on empirical and conceptual grounds by Robert Pollak and Michael Wachter (1975). They show that jointness in production or nonconstant returns to scale cause implicit commodity prices to depend on both tastes and technology, raising serious econometric difficulties in the estimation of commodity demand functions. In addition, since commodity prices become functions of the commodity bundle consumed, the analogy to traditional demand theory breaks down. Joint production occurs when a good enters several production processes simultaneously, or, equivalently, when a good in one production process also enters directly into the individual's utility function. The most common example is time, which provides the context for all production processes and is often associated with the production of several commodities simultaneously. Since joint production in the household is likely to be pervasive, the critique by Pollak and Wachter cannot be ignored. In response to the comment by William Barnett, Pollak and Wachter (1977) suggest dispensing with the notion of commodity prices and treating the demand for commodities as a function of goods prices. This approach confounds tastes and technology, but it eliminates the troublesome concept of commodity prices as parameters when, in fact, they are likely to be endogenous. In this paper we show that results from positive analysis, such as the critique by Pollak and Wachter, have implications for the use of the household production framework for welfare analysis. The household production function approach has had considerable appeal for measuring welfare effects of public actions in the environmental and natural resource areas (Gardner Brown, John Charbonneau, and Michael Hay; Elizabeth Wilman). Yet traditional approaches to welfare measurement are frequently inapplicable. We argue that welfare measurement in this framework is complicated by the difficulties of unravelling tastes and technology. We extend Pollak and Wachter's results by demonstrating that Marshallian demand functions for commodities cannot be uniquely defined. Thus Marshallian functions cannot be used to derive exact compensated functions in the manner of Jerry Hausman, and of George McKenzie and I. F. Pearce, nor can compensating and equivalent variation measures be bounded by Marshallian consumer's surplus estimates following Robert Willig. In fact, duality results that normally allow us to move between Marshallian and Hicksian functions are not *Assistant and Associate Professors, respectively, Department of Agricultural and Resource Economics, University of Maryland, College Park, MD 20742. This paper is Scientific Article No. A3404, Contribution No. 6476, of the Maryland Agricultural Experiment Station. We wish to thank Darrell Hueth, James Opaluch, V. Kerry Smith, and Elizabeth Wilman for comments on an earlier draft.

We study managerial incentive provision under moral hazard when growth opportunities arrive stochastically and pursuing them requires a change in management. A trade‐off arises between the benefit of always having the “right” manager and the cost of incentive provision. The prospect of growth‐induced turnover limits the firm's ability to rely on deferred pay, resulting in more front‐loaded compensation. The optimal contract may insulate managers from the risk of growth‐induced dismissal after periods of good performance. The evidence for the United States broadly supports the model's predictions: Firms with better growth prospects experience higher CEO turnover and use more front‐loaded compensation.