Robert A. Leitch

Solving nonlinear principal-agent problems using bilevel programming

While significant progress has been made, analytic research on principal-agent problems that seek closed-form solutions faces limitations due to tractability issues that arise because of the mathematical complexity of the problem. The principal must maximize expected utility subject to the agent’s participation and incentive compatibility constraints. Linearity of performance measures is often assumed and the Linear, Exponential, Normal (LEN) model is often used to deal with this complexity. These assumptions may be too restrictive for researchers to explore the variety of relationships between compensation contracts offered by the principal and the effort of the agent. In this paper we show how to numerically solve principal-agent problems with nonlinear contracts. In our procedure, we deal directly with the agent’s incentive compatibility constraint. We illustrate our solution procedure with numerical examples and use optimization methods to make the problem tractable without using the simplifying assumptions of a LEN model. We also show that using linear contracts to approximate nonlinear contracts leads to solutions that are far from the optimal solutions obtained using nonlinear contracts. A principal-agent problem is a special instance of a bilevel nonlinear programming problem. We show how to solve principal-agent problems by solving bilevel programming problems using the ellipsoid algorithm. The approach we present can give researchers new insights into the relationships between nonlinear compensation schemes and employee effort.

Balanced scorecard: evening the odds of successful BPR

To realize the benefits of costly business process reengineering, companies need a control mechanism that links performance evaluation to strategic objectives. Researchers have long addressed how to control, measure, and evaluate this business process reengineering (BRP), but many so-called solutions continue to focus almost exclusively on the technical aspects of change. In this article, we present a control and evaluation framework, BSC-IS (balanced scoreboard-information system) that integrates BSC and BPR in the context of an IS or ERP (enterprise resource planning) project. BSC-IS is viewed as the roots of a solid evaluation tool for companies struggling to make costly BPR pay off.

Simulation of Controlled Financial Statements

Many accounting and finance studies investigate the time-series properties of historical accounting records from corporate financial statements. Some of them have recognized the potential benefits of using disaggregated monthly accounting records. Disaggregated data are beneficial because one can use more data points within a relatively short period of time, thus reducing the chance of structural change. The added data points and reduction of the number of variables needed to accommodate potential structural changes can enhance the statistical power of any subsequent analysis. The use of disaggregated data may also improve the predictive ability of time-series analytic approaches. In order to systematically assess various financial indicators and investigate the effects of different organizational characteristics, a large number of monthly statements with certain predetermined characteristics are desirable. However, such statements are not readily available. At best, monthly statements can be obtained from a few volunteer companies. Under this circumstance, simulation of controlled financial statements seems to be a reasonable solution. This research explores a methodology for simulating complete monthly financial statements based on actual company quarterly financial statements. The methodology incorporates the interrelationships among accounting numbers and the effects of exogenous variables. To test the empirical validity and whether the monthly results derived from the quarterly data can accurately track the real monthly figures, we compare the results simulated by the proposed method and those generated by a naive random walk model. We test both complete financial statements for three companies and sales statistics from the retail industry. The results of both tests demonstrate the superiority of the method proposed by this study over a naive random walk model. The proposed simulation method provides an opportunity for researchers to examine the time-series properties of financial statement elements by using the monthly data of a large number of companies. In addition, the simulation approach allows researchers to perform cross sectional comparisons on companies with different characteristics (e.g., sales behavior patterns and degrees of stability) in their financial and economic activities. Moreover, it enables the researchers to manipulate some of these characteristics to test various hypotheses.

Accounting-based heuristics for order processing and review in a stochastic environment

As manufacturers evolve from make-to-stock to make-to-order strategies, they are forced to rely less on inventory to meet demands and more on the effective usage of existing capacity as they determine which orders to accept and schedule. Several accounting-based heuristics are used to identify and accept those jobs that maximize plant throughput. Accounting heuristics have been suggested as surrogates for approximating the opportunity costs of manufacturing one order instead of another order. Research results suggest that the best heuristic is dependent on the balance of the manufacturing resources. Moreover, these tendencies are affected by product mix and load.

Do experienced auditors have a bias for confirmatory audit evidence

In this study we experimentally test whether experienced auditors display a preference for confirmatory evidence when performing a routine part of a financial statement audit. We theorise that information auditors receive early during an audit leads them to form an initial belief about the correctness of an account balance. Subsequently, auditors may bias their evidence choices in a way that confirms their initial belief. We conducted a 2 × 2 between-subjects experiment with 97 experienced auditors. We manipulated whether early information came from a clients CFO or a firm partner and whether or not it supported the account balance as currently stated. We found that auditors selected more confirmatory evidence after receiving positive information from an audit partner compared to receiving the same information from a clients CFO. We found that experienced auditors selected more confirmatory evidence when the CFO provided negative information relative to when the CFO provided positive information.