Expected Opportunity Cost Research Articles

Efficient subset selection for the expected opportunity cost

A lot of problems in automatic control aim at seeking top designs for discrete-event systems. In many cases, these problems are most suitable to be modeled as simulation optimization problems, and a key question for solving these problems is how to efficiently and accurately select the top designs given a limited simulation budget. This paper considers the generalized problem of selecting the top m designs from a finite set of design alternatives based on simulated outputs, subject to a constraint on the total number of samples available. The quality of the selection is measured by the expected opportunity cost, which penalizes particularly bad choices more than the slightly incorrect selections and is preferred by risk-neutral practitioners and decision makers. An efficient simulation budget allocation procedure, called EOC-m, is developed for this problem. The efficiency of the proposed method is illustrated through numerical testing.

The expected opportunity cost and selecting the optimal subset

The expected opportunity cost and selecting the optimal subset

Appraising the Lender's Opportunity Cost Induced from the Foreclosure Lag of Defaulted Mortgages

Foreclosure is the most important tool to protect the mortgage lenders from excessive default losses. The goal of this paper is to present models that can help lenders and insurers calculate the length of the foreclosure period (referred to as the foreclosure lag) and the opportunity cost incurred during this period. Further, we apply the VaR method to estimate the loss scenarios for a given foreclosure lag at a given significance level. This can help lenders to accurately estimate their losses for different degrees of foreclosure lag. Using empirical foreclosure data, we find that the actual lag fits well with the exponential distribution after linear transformation, and we estimate that the expected opportunity cost per monetary unit of the outstanding mortgage balance is nearly twice the mortgage rate. Our results also reveal that different state foreclosure policies, the loan-to-value (LTV) ratio, and the loss rate significantly influence the foreclosure lag. In the real empirical case, the banks needed on average about two years to complete the foreclosure process. The lag increases 0.52 years if the state policy is judicial foreclosure and 0.1437 years if it is redemption. Both the LTV ratio and the loss rate are negatively related with the foreclosure lag. Our results can help lenders forecast their foreclosure costs and calculate their capital requirements based on the Basel Accord.

Can Spectrum Trading and Pricing Co-Exist?

There have been moves towards greater reliance on market mechanisms for spectrum management – auctions, trading, private band management and leasing – in North America, the EU and a number of other countries. Alongside these developments, regulators have applied administratively determined spectrum prices with the aims of recovering administrative costs and promoting spectrum efficiency through prices reflecting opportunity cost and or extracting producer surplus. A critical policy question is whether such pricing is compatible with the development of spectrum markets or whether the two policies are incompatible, in the sense that spectrum pricing may harm economic efficiency when spectrum is tradable. In this paper we identify circumstances in which spectrum pricing may increase efficiency but find that spectrum pricing may reduce the efficiency of spectrum markets even where spectrum prices are set below expected opportunity cost (obligations on spectrum license holders may have a similar impact by reducing potential gains from trade). The implication is that trading should in general be applied in preference to pricing (given its dynamic advantages). Spectrum pricing may, however, have a role in relation to spectrum utilised by government agencies where prices may provide stronger incentives than the opportunity to profit from trading (depending on the overall nature of incentives relating to government agencies including the process for setting and resetting their budgets).

Three-Stage Procedure and Expected Opportunity Cost for Selecting a Good Simulated Design

Three-Stage Procedure and Expected Opportunity Cost for Selecting a Good Simulated Design

Financial compensation and uncertainty: using mean-variance rule and stochastic dominance to derive conservation payments for secondary forests

The expected opportunity costs of conserving a specific land use are usually considered adequate as financial compensation. However, a “conservation premium” is sometimes proposed as an added incentive, i.e., compensation greater than the expected opportunity costs. This paper discusses various methodological opportunities for deriving effective compensation under uncertainty. Based on cumulative distribution functions of possible opportunity costs (a Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) plantation was considered the alternative to conserving a Chilean secondary forest), generated through Monte Carlo simulations, we derived an inclusive range of possible compensations from 77 up to 375 US$·ha–1·year–1. If we assumed that the two land-use alternatives were mutually exclusive and independent from other risky investments, a compensation of 375 US$·ha–1·year–1 was necessary to convince every decision maker to maintain the secondary forest. However, only 77 US$·ha–1·year–1 was enough for a risk-averse decision maker (given average opportunity costs of 113 US$·ha–1·year–1). Yet, it turned out that the greatest possible opportunity costs would already be compensated for with 199 US$·ha–1·year–1, given an error probability of 0.05. Compensating for the last 5% of possible opportunity costs would thus require an additional 176 US$·ha–1·year–1. Our approach had two main limitations, namely we did not consider portfolio effects, which would allow diversifying away unsystematic risks, and we did not take into account the different systematic risks of the compared alternatives. These limitations may have led to an overestimation of effective compensation.

The Option Value of Delay in Health Technology Assessment

Processes of health technology assessment (HTA) inform decisions under uncertainty about whether to invest in new technologies based on evidence of incremental effects, incremental cost, and incremental net benefit monetary (INMB). An option value to delaying such decisions to wait for further evidence is suggested in the usual case of interest, in which the prior distribution of INMB is positive but uncertain. of estimating the option value of delaying decisions to invest have previously been developed when investments are irreversible with an uncertain payoff over time and information is assumed fixed. However, in HTA decision uncertainty relates to information (evidence) on the distribution of INMB. This article demonstrates that the option value of delaying decisions to allow collection of further evidence can be estimated as the expected value of sample of information (EVSI). For irreversible decisions, delay and trial (DT) is demonstrated to be preferred to adopt and no trial (AN) when the EVSI exceeds expected costs of information, including expected opportunity costs of not treating patients with the new therapy. For reversible decisions, adopt and trial (AT) becomes a potentially optimal strategy, but costs of reversal are shown to reduce the EVSI of this strategy due to both a lower probability of reversal being optimal and lower payoffs when reversal is optimal. Hence, decision makers are generally shown to face joint research and reimbursement decisions (AN, DT and AT), with the optimal choice dependent on costs of reversal as well as opportunity costs of delay and the distribution of prior INMB.

Opportunity Cost and OCBA Selection Procedures in Ordinal Optimization for a Fixed Number of Alternative Systems

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Ordinal optimization offers an efficient approach for simulation optimization by focusing on ranking and selecting a finite set of good alternatives. Because simulation replications only give estimates of the performance of each alternative, there is a potential for incorrect selection. Two measures of selection quality are the alignment probability or the probability of correct selection (P{CS}), and the expected opportunity cost E[OC], of a potentially incorrect selection. Traditional ordinal optimization approaches focus on the former case. This paper extends Chen's optimal computing budget allocation (OCBA) approach, which allocated replications to improve P{CS}, to provide the first OCBA-like procedure that optimizes E[OC] in some sense. The procedure performs efficiently in numerical experiments. </para>

Expected Loss Interest-Adjustment Theorem

This paper proposes and analyses the following theorem: Every legal claim or award that includes interest rate adjustment also incorporates an implicit head of loss or counterclaim for the expected opportunity cost or time value of the underlying claim amount. This expected opportunity cost satisfies no-arbitrage when compared with the parallel interest rate market. The inflation and discounting of nominal damage awards forwards and backwards in time and the relationship between indemnity interest rates and equity are all examined.

Precaution Against Terrorism

Stunned by the terrorist attacks of September 11, 2001, the Bush administration adopted a new National Security Strategy in September 2002. The UK government took a similar stance. This new strategy calls for anticipatory attacks against potential enemies with uncertain capacities and intentions, even before their threat is imminent. Rather than wait for evidence of weapons of mass destruction, it shifts the burden of proof, obliging “rogue” states to show that they do not harbor weapons of mass destruction or terrorist cells, or else face the possibility of attack. This new strategy amounts to the adoption of the Precautionary Principle against the risk of terrorism. We offer two main conclusions about precaution against terrorism. First, any action taken to reduce a target risk always poses the introduction of countervailing risks. Moreover, a precautionary approach to terrorism is likely to entail larger, more expensive interventions, so the expected opportunity costs are likely to be higher. While considering worst‐case scenarios is important for the development of sound policy, taking action based only on worst‐case thinking can introduce unforeseen dangers and costs. We argue that a better approach to managing risk involves an assessment of the full portfolio of risks—those reduced by the proposed intervention, as well as those increased. We argue that decision makers developing counterterrorism measures need mechanisms to ensure that sensible risk analysis precedes precautionary actions. Such a mechanism currently exists to review and improve or reject proposed precautionary measures against health and environmental risks, but not, so far, for counterterrorism and national security policies. We urge the creation of such a review mechanism.

Precaution Against Terrorism

Stunned by the terrorist attacks of September 11, 2001, the Bush administration adopted a new National Security Strategy in September 2002. The UK government took a similar stance. This new strategy calls for anticipatory attacks against potential enemies with uncertain capacities and intentions, even before their threat is imminent. Rather than wait for evidence of weapons of mass destruction, it shifts the burden of proof, obliging rogue states to show that they do not harbor weapons of mass destruction or terrorist cells, or else face the possibility of attack. This new strategy amounts to the adoption of the Precautionary Principle against the risk of terrorism. We offer two main conclusions about precaution against terrorism. First, any action taken to reduce a target risk always poses the introduction of countervailing risks. Moreover, a precautionary approach to terrorism is likely to entail larger, more expensive interventions, so the expected opportunity costs are likely to be higher. While considering worst-case scenarios is important for the development of sound policy, taking action based only on worst-case thinking can introduce unforeseen dangers and costs. We argue that a better approach to managing risk involves an assessment of the full portfolio of risks - those reduced by the proposed intervention, as well as those increased. We argue that decision makers developing counterterrorism measures need mechanisms to ensure that sensible risk analysis precedes precautionary actions. Such a mechanism currently exists to review and improve or reject proposed precautionary measures against health and environmental risks, but not, so far, for counterterrorism and national security policies. We urge the creation of such a review mechanism.

Selection Procedures with Frequentist Expected Opportunity Cost Bounds

Selection procedures help identify the best of a finite set of simulated alternatives. Most work has measured the quality of a selection with the probability of correct selection, P(CS), but the expected opportunity cost of a potentially incorrect decision makes more sense in business contexts. This paper analyzes the first selection procedures that guarantee an upper bound for the expected opportunity cost, in a frequentist sense, of a potentially incorrect selection. The paper therefore bridges a gap between the indifference-zone approach (with frequentist guarantees, but for the P(CS)) and the Bayesian approach to selection procedures (which has considered the opportunity cost). We also provide “unexpected” expected opportunity cost guarantees for several existing indifference-zone selection procedures that were originally designed to provide P(CS) guarantees.

Corrigendum: New Selection Procedures

C and Inoue (2001b) presented new two-stage and sequential selection procedures to identify the best system, assuming independent observations are available. Chick and Inoue (2001a) used results from that paper to derive new two-stage procedures that allow for common random numbers and screening. Both articles contain a typographical error that requires correction. Let s and s be the density and cumulative distribution functions of the standard Student-t random variable with degrees of freedom. Chick and Inoue (2001b) defined an expected opportunity cost function s = ∫

New Procedures to Select the Best Simulated System Using Common Random Numbers

Although simulation is widely used to select the best of several alternative system designs, and common random numbers is an important tool for reducing the computation effort of simulation experiments, there are surprisingly few tools available to help a simulation practitioner select the best system when common random numbers are employed. This paper presents new two-stage procedures that use common random numbers to help identify the best simulated system. The procedures allow for screening and attempt to allocate additional replications to improve the value of information obtained during the second stage, rather than determining the number of replications required to provide a given probability of correct selection guarantee. The procedures allow decision makers to reduce either the expected opportunity cost associated with potentially selecting an inferior system, or the probability of incorrect selection. A small empirical study indicates that the new procedures outperform several procedures with respect to several criteria, and identifies potential areas for further improvement.

A distributed genetic algorithm for deterministic and stochastic labor scheduling problems

A recurring operational decision in many service organizations is determining the number of employees, and their work schedules, that minimize labor expenses and expected opportunity costs. These decisions have been modeled as generalized set covering (GSC) problems, deterministic goal programs (DGP), and stochastic goal programs (SGP); each a challenging optimization problem. The pervasiveness and economic significance of these three problems has motivated ongoing development and refinement of heuristic solution procedures. In this paper we present a unified formulation for these three labor scheduling problems and introduce a distributed genetic algorithm (DGA) that solves each of them. Our distributed genetic algorithm operates in parallel on a network of message-passing workstations. Separate subpopulations of solutions evolve independently on each processor but occasionally, the fittest solutions migrate over the network to join neighboring subpopulations. With its standard genetic operators, DGA frequently produces infeasible offspring. A few of these are repaired before they enter the population. However, most enter the population as-is, carrying an appropriate fitness penalty. This allows DGA to exploit potentially favorable adaptations that might be present in infeasible solutions while orienting the locus of the search near the feasible region. We applied the DGA to suites of published test problems for GSC, DGP, and SGP formulations and compared its performance with alternative solution procedures, including other metaheuristics such as simulated annealing and tabu search. We found that DGA outperformed the competing alternatives in terms of mean error, maximum error, and percentage of least cost solutions. While DGA is computationally intensive, the quality of its solutions is commensurate with the effort expended. In plots of solution quality versus CPU time for the various algorithms evaluated in our study, DGA consistently appeared on the efficient frontier.

Rational expectations estimation of money demand for south asian countries

In recent years, the demand for money function for some of the South Asian countries, namely India and Pakistan, has been estimated by many economists and econometricians alike [e.g., Fry, JDE, 1978; Gupta, JDS, 1970; Hu, JPE, 1971; Khan, PDR, 1980, 1982; and Wong, JME, 1977]. It is theoretically postulated that the amount of real money holdings by the economic agents depends on the level of real income and on the expected opportunity costs of the holding of real balances relative to other financial assets and goods. The opportunity costs of real balances and goods, in turn, depend upon their yields which are measured as the expected interest rate and the expected rate of inflation, respectively. The expected interest and inflation variables are generally unobservable and, therefore, in order to empirically estimate a money demand function that includes these variables, an assumption about the expectations formation is required. Most of the demand for money functions estimated for these South Asian countries assumed an adaptive form of expectations for the unobserved variables. The adaptive form of expectations is ad hoc and arbitrary and based only on the past information of the variable itself. To circumvent these problems, an alternative form of expectations has been suggested, known as the "Rational Expectations (RE) Hypothesis" [Muth, Econometrica, 1961]. The essential concept of rational expectations is fairly simple: economic agents form expectations efficiently using all available information. Although the demand for money functions under RE have been extensively estimated for developed eountries [Frenkel, AER, 1977; Khan, JPE, 1977; Salemi and Sargent, IER, 1979; Sargent, IER, 1977] and also for some Latin American countries [Liederman, IER, 1981], it appears that not much work has been done in estimating demand for money under RE for some of the economically and politically important countries in the South Asian region, namely India and Pakistan. This paper estimates the demand for money function for these two South Asian countries under RE using quarterly time series data covering the period from 1972-1 to 1985-4. The estimation technique used is a Full Information Maximum Likelihood Generalized Errors-in-Variables method proposed by Wickens [J. Eco. Studies, 1982] for RE models. The significance of this study is not limited to the methodology of rational expectations estimation of the money demand function for these countries but, more importantly, it is the empirical results which seem interesting and relevant for the conduct of monetary policies in developing countries. Some of the earlier empirical work by Gupta and Khan using the adaptive expectations approach found expected interest rates significant in the money demand function for these two developing countries. Contrary to these results, the FIML findings highlighted the importance of inflation rather than interest rate expectations in the money demand function. These results seem to be consistent for developing countries where the financial sector is relatively thin and heavily controlled; consequently, the interest rates are not competitively determined in the free markets.

Compensating balance requirements and the firm's demand for transactions balances

Previous analyses of the conditions for the rationality of the use of compensating balance requirements have been stated in terms of the relationship between the firm's normal transactions balance and the required compensating balance. However, these papers fail to recognize the interdependence between the required compensating balance and the firm's optimum transactions balance. Our paper incorporates a required compensating balance into the control limits model of Miller and Orr (1966). Our results demonstrate that the average level of transactions balances and the expected opportunity cost of maintaining these balances are non-decreasing functions of the required compensating balance, thus strengthening the case against their rationality.

COMPENSATING BALANCE REQUIREMENTS AND THE FIRM'S DEMAND FOR TRANSACTIONS BALANCES

Previous analyses of the conditions for the rationality of the use of compensating balance requirements have been stated in terms of the relationship between the firm's normal transactions balance and the required compensating balance. However, these papers fail to recognize the interdependence between the required compensating balance and the firm's optimum transactions balance. Our paper incorporates a required compensating balance into the control limits model of Miller and Orr (1966). Our results demonstrate that the average level of transactions balances and the expected opportunity cost of maintaining these balances are non-decreasing functions of the required compensating balance, thus strengthening the case against their rationality.

On Testing the Efficacy of Selective Credit Controls: Comment

In recent notes in this journal, Hamburger and Zwick [2] and Maris [3] presented empirical tests that were designed to determine the efficacy of selective credit controls on on consumer durables. The purpose of this comment is to argue that neither one of these tests is well suited to address the issue in question. Hamburger and Zwick estimate a version of the model of consumer durable expenditure developed by Mishkin [4] and argue that theirvresults suggest that i'selective credit policies are unlikely to have a significant effect on the composition of real expenditures [2, p. 107]. A close look at Mishkin's theoretical model indicates that the Hamburger and Zwick adaptation is inappropriate for testing the efficacy of selective credit policies. The empirical results obtained by Hamburger and Zwick are the only ones that are consistent with the theoretical model and should not be interpreted as evidence on selective credit policies. Mishkin specifies consumer durables expenditure as a function of transitory income, permanent income, the lagged stock of durable goods, total household debt, gross financial asset holdings of households,l and the user rental cost of consumer durable capital. The rationale for including debt and financial asset holdings as separate arguments in the expenditure function is that consumer durables are illiquid and the expected cost of holding such an illiquid asset is positively related to the probability of having to make a distress sale. Since a distress sale will take place whenever consumption plus debt service exceeds income plus financial assets, the probability of such a sale and the expected opportunity cost of holding consumer durables will be positively related to debt service and negatively related to financial asset holdings. A ceteris paribus rise in debt holdings will raise debt service and thereby the opportunity cost of holding consumer durables. This will tend to decrease expenditure on consumer durables. What should be stressed here is that the single linkage between household debt and expenditure is debt service.2 The Mishkin equation is reestimated by Hamburger and Zwick with two rather than one household debt explanatory variables. Total debt is decomposed into