Economic models of politics typically use the expected value of a candidate's vote share to proxy electoral probability. In this paper, the authors introduce a risk calculation to augment the evaluation of a candidate's (or party's) expected vote share and they divide this risk element into its systematic and unsystematic components. For the same reason that systematic risk is a primary focus of portfolio management, the authors discover that an analogous systematic risk component is central to presidential elections. Their approach accounts for correlations in vote swings among states, piercing the fiction of a state-by-state or 'local' campaign strategy. Copyright 1993 by MIT Press.

Efficient estimators of cointegrating vectors are presented for systems involving deterministic components and variables of differing, higher orders of integration. The estimators are computed using GLS or OLS, and Wald Statistics constructed from these estimators have asymptotic x2 distributions. These and previously proposed estimators of cointegrating vectors are used to study long-run U.S. money (Ml) demand. Ml demand is found to be stable over 1900-1989; the 95% confidence intervals for the income elasticity and interest rate semielasticity are (.88,1.06) and (-.13, -.08), respectively. Estimates based on the postwar data alone, however, are unstable, with variances which indicate substantial sampling uncertainty.

This paper proposes an estimator for discrete choice models that makes no assumption concerning the functional form of the choice probability function, where this function can be characterized by an index. The estimator is shown to be consistent, asymptotically normally distributed, and to achieve the semiparametric efficiency bound. Monte-Carlo evidence indicates that there may be only modest efficiency losses relative to maximum likelihood estimation when the distribution of the disturbances is known, and that the small-sample behavior of the estimator in other cases is good.

This paper analyzes dynamics of production and inventories at the General Motors Corporation during the 1920's and 1930's. We begin by examining anecdotal evidence on the nature of the production control system in force during that period. Motivated by that evidence, we then extend the conventional linear-quadratic model of production behavior to take account of annual shutdown. Finally, we apply the modified model to newly available data on monthly unit production, sales, and inventories during 1924-1940. GM appears to have been aiming to maintain a targeted level of inventory relative to expected sales and, secondarily, to smooth production.

We analyze incomplete contracts to induce efficient investment. With exogenous switching costs, fixed-price contracts are efficient, generate some rigidity in prices, are renegotiated intermittently by possibly small amounts, and when inflation is positive, generate asymmetric responses to shocks, all consistent with evidence on prices and wages. With two-sided specific investments, efficiency requires prices to have sufficient escalator clauses to avoid renegotiation, as observed in many long-term contracts. A third case, with one-sided specific investments, can generate "take or pay" contracts and explain why firms sometimes pay for specific investments that appear to benefit employees directly.

Use of disappearance data as proxies for actual consumption causes inconsistent estimates of own-price retail demand elasticities. A system of equations describing consumer, processor, and producer behavior is used to consistently estimate the retail demand elasticity for beef using available data while avoiding the restrictive assumption of fixed input proportions implicit in disappearance data. This approach yields an estimate of the own-price retail demand elasticity for beef of -0.45, which is more inelastic than the estimate (-0.66) obtained using a traditional approach. The methodology is applicable to other food commodities for which disappearance data serve as proxies for actual consumption. Copyright 1993 by MIT Press.

Abstract The performance of audit tasks has been modeled as a function of the auditor's ability, knowledge and experiences (Libby 1993). Thus, an important aspect of assigning audit tasks is identifying the levels of knowledge and types of experience an auditor must have to achieve a sufficiently high level of performance (Abdolmohammadi and Wright 1987). An objective of the current study is to determine whether auditors' knowledge of basic accounting principles and error frequencies improves over the course of their early careers so as to enhance performance of a common analytical procedure, ratio analysis. Research in psychology suggests that two characteristics of a task (say, analytical procedures) could diminish the accuracy with which auditors learn error frequencies from experience and apply their knowledge to a task. First, auditors' memories of financial statement errors are encoded while they perform other information-processing activities. These competing task demands could use enough of an auditor's information-processing capacity to diminish both the accuracy with which memory traces of errors are encoded and the accuracy of their knowledge of error frequency (Naveh-Benjamin and Jonides 1986). Second, auditors must consider a variety of evidence when performing analytical procedures. In diagnostic tasks like ratio analysis, inordinate attention is given to evidence that is highly diagnostic of low-frequency events, causing an "inverse base rate effect" in which auditors consider such events as more likely (Medin and Edelson 1988). Assessing the extent to which either of these characteristics of the analytical procedures context prevents auditors from learning and applying error frequency knowledge is a second objective of this study. To test hypotheses about these objectives, an experiment is conducted in which experienced auditors, accounting students, and nonaccounting students learn the frequencies of financial statement errors through their experience in solving a series of problems using ratio analysis. Subjects are then tested for their accuracy in using frequency information by having them diagnose novel combinations of the same evidence. Other subjects perform similar tasks for an abstract medical diagnosis to provide a benchmark for comparison. The results indicate that differences in accounting knowledge influenced the subjects' performance of ratio analysis, and that neither potential source of inaccurate learning of event frequency knowledge holds in this setting. That is, subjects learned frequencies in the presence of competing task demands, and the inverse-base rate effect was not observed. These results suggest that experienced, but not novice, auditors use both their superior knowledge of accounting and of error frequencies learned through experience. Another implication is that the performance of novice auditors may be improved by increasing their knowledge of basic accounting principles and error frequencies.