Intertemporal Framing Issues in Management Compensation

ORGANIZATIONAL BEHAVIOR AND HUMAN DECISION PROCESSES

Vol. 66, No. 1, April, pp. 42–58, 1996 ARTICLE NO. 0037

Intertemporal Framing Issues in Management Compensation MARJORIE K. SHELLEY

AND

THOMAS C. OMER *

Department of Accountancy, University of Illinois at Urbana–Champaign; and *Department of Accounting, University of Illinois at Chicago

profit’’ organizations use some measure of accounting income to evaluate their profit center managers and business segments. Businesses may use reported income alone, or profitability measures based on reported income, to guide decisions about capital rationing, promotions, bonuses, firings, segment elimination, or segment adoptions. Because accounting income plays such an important role in most managers’ careers, it is important to understand the effect that income-based performance evaluation measures have on job-related decisions. Clearly, if a manager will be penalized, directly or indirectly, for spending money on employee training, for example, he will be reluctant to support employee training even when it is badly needed to implement changes in technology. Of course, failure to train employees to properly utilize new technology, or worse yet, failure to invest in new technology, will eventually take its toll on income, but the toll will be on future income affecting future bonuses or penalties. Today’s manager may be tempted to underinvest. Since the end of World War II, investment by U.S. companies in intangible assets, such as employee training, has fallen far short of what is required for competitiveness (Porter, 1992, p. 66).1 The Germans and the Japanese have done better.2 One important reason is that U.S. companies are not allowed to spread the cost of intangible assets over the periods benefited as they would the cost of tangible assets such as new equipment. This means that reported income will be lower in the year of the investment. Managers who control investment decisions and who are evaluated and rewarded based on each year’s reported income number may be reluctant to invest in intangibles.3

This study investigates whether manager–decisionmakers’ expectations about incentive compensation and environmental uncertainty influence investment decisions through their effect on the decision maker’s implied discount rate. This is, to our knowledge, a first attempt to manipulate implicit risk, the risk to future payoffs associated with environmental uncertainty. Both these factors and waiting time are expected to influence implied discount rates. The study investigates discount rate influences under both bonus and penalty incentive plans. The hypothetical bonuses are year-end cash bonuses; the penalties are opportunity costs. Responses were analyzed using both analysis of variance and regression. The regression analysis was used to separate time discounting from the other factors affecting implied discount rates. Subjects’ responses to proposed changes in the timing of cash bonuses were dramatic when an expanding economy was suggested. However, subjects’ responses to penalty provisions were less dramatic than corresponding responses to the out-of-pocket negative outcomes studied in previous research. In some situations, penalty provisions may be more effective for inducing investment than bonus provisions. In addition, the results suggest that efforts to change management decision making using deferred compensation may require more deferred compensation than time discounting alone would require. q 1996 Academic Press, Inc.

INTERTEMPORAL FRAMING ISSUES IN MANAGEMENT COMPENSATION

Company compensation boards attempt to link managers’ compensation to the welfare of the company as a way to encourage them to make decisions in the best interests of the company and its owners. Most ‘‘for

1

This is not a market efficiency problem. Among the positive features of the U.S. capital markets Porter (1992) cites is the speed with which investment dollars respond to changing conditions. 2 ‘‘Aggregate investment in property, plant and equipment, and intangible assets, such as civilian R&D and corporate training, is lower in the United States than in Japan and Germany’’ (Porter, 1992, p. 67). 3 German and Japanese managers receive less compensation overall than do U.S. managers; however, a smaller proportion of compensation is contingent and their job security tends to be greater.

We thank Lawrence Tomassini, Richard Young, Franc¸ois DeCosterd, John Shelley, and members of the workshops at the Ohio State University and the University of Connecticut for helpful comments on this paper. Address reprint requests to Marjorie K. Shelley, Department of Accountancy, College of Commerce and Business Administration, 360 Commerce West Building, University of Illinois, Champaign, IL 61820. 42

0749-5978/96 $18.00 Copyright q 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

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Investment at either the organizational or the capital market level is determined by the macroeconomic environment, internal and external capital allocation mechanisms, and the circumstances of the specific investment project (Porter, 1992). This study investigates the effect on investment decisions of (1) the macroeconomic environment and (2) internal capital allocation mechanisms. These two determinants of investment behavior affect investment decisions through their effect on decision makers’ personal discount rates. Expectations about the macroeconomic environment affect discount rates because they suggest possible rates of inflation and economic risk. Internal capital allocation mechanisms, such as divisional return on investment (ROI), are profitability measures used to allocate capital within firms and also to evaluate managers. They affect discount rates by suggesting a minimum rate of return that a potential investment must meet each year of its life. This study explores the effect of these two factors on discounting patterns reported in previous intertemporal choice research (Loewenstein, 1988; Shelley, 1993). The section that follows immediately provides an example of the potential dysfunctional effect on decision making of an internal allocation mechanism, such as ROI. It then discusses (1) conventional economic discounting, (2) intertemporal framing, and (3) macroeconomic uncertainty (the source of implicit risk manipulated in this study), and links those issues to a proposed descriptive discounting model for managers making internal investment decisions.4 The operational definition of implicit risk in this study is the state of the macroeconomy; different economic conditions are expected to produce different levels of risk for future rewards and penalties. Later sections describe the experiment conducted to test predictions about discounting patterns and model parameters, including expected responses to the implicit risk manipulation. The last two 4 Implicit risk is risk brought about because an outcome will occur in the future rather than immediately. It is risk associated with the outcome itself. That is, if the same outcome were to occur in the present, all its risk would disappear. For example, suppose a $1000 lottery has been held and the winner announced. There is no uncertainty with respect to who should receive the money or how much should be received. Nevertheless, a winner who will receive the payoff the night of the drawing will experience less risk than one who will be paid in several weeks. In general, the winner who is asked to wait will discount his/her $1000 prize for both time and the risk that something may happen in the future that will prevent his/her receipt of the prize. Empirically, the implicit risk discount tends to be a single lump sum rather than an amount that varies over time (Stevenson, 1986). In the current study, the level of a factor thought to influence implicit risk in the decision setting suggested in this study is varied systematically. The setting is business decision making and implicit risk is influenced by the state of the macroeconomy.

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sections discuss the results, conclusions, and directions for future research. THEORY DEVELOPMENT Background

Accounting conventions (in this study, immediate expensing of investments in human capital) influence managers’ investment decisions via their influence on measures of income and investment that are used to evaluate managers. If the manager is evaluated based on current income (or a similar measure of profitability), immediate expensing of capital employed to improve human performance reduces income and, hence perhaps, his/her compensation. Thus, the accounting convention, through its effect on the performance evaluation measure, affects investment decisions. Example: Suppose the manager of Division A is evaluated (for bonuses and promotion) based on his/her Division’s ROI number. Return on investment is measured as operating income divided by divisional investment. Division A has the following contribution and investment characteristics currently: Operating income ............................................. $20,000 Investment ...................................................... $100,000 Cost of capital ......................................................... 15% The Division’s cost of capital is the minimum rate at which its providers of capital (shareholders or creditors) expect to earn returns on their investment. It is the opportunity cost of their capital. If Division A does not earn at least the cost of capital (15%) from its activities, the providers of capital will take their capital elsewhere. Currently, Division A is making 20%, 5% more than the cost of capital, so providers of capital are happy. The manager of Division A is awarded bonuses and, possibly, promotions based on this measure. ROI is just an accounting measure of income divided by an accounting measure of investment. Suppose the manager of Division A is considering an investment that will optimize the long-run welfare of the firm. However, because of the way income will be measured, the investment will have an average annual ROI of 18%. Because 18% is higher than the opportunity cost of their capital, his providers of capital want him to take on this project. Will the manager adopt the project? All else constant, no. The project’s return will dilute his Division’s ROI, reducing or eliminating his current year’s bonus. On the other hand, if he avoids all investment projects that earn less than 20%, he will eventually be operating with plant and equipment too old to earn the cost of capital.

Two important questions addressed in this study are: (1) How big would a manager’s future bonus need to be to get him to invest in this desirable project if making the investment means he must forego this year’s bonus? (2) How does the stability of the macroenvironment change the answer to this question? In this setting, the reluctance to invest in an attractive project could be corrected several ways: (1) by

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changing the accounting treatment for intangible assets, (2) by switching from short- to long-term incentive contracts, or (3) by changing the nature of the performance measures used to evaluate managers. Businesses do not control the accounting conventions used for external reporting purposes.5 However, they can control the nature of incentive contracts and the performance measures used to implement them. If the intertemporal framing theory predictions tested in this study are correct, offering both short- and long-term incentive contracts (or switching from short- to longterm contracts) may be alarmingly expensive. The hypothetical decision described in this study concerned investments that could affect the timing of the manager’s compensation if undertaken. Previous intertemporal choice research suggests that decision makers are reluctant to change the timing of monetary receipts to which they have already psychologically adjusted (Loewenstein, 1988; Shelley, 1993). Conventional economic discounting theory predicts that managers will be indifferent regarding the timing of compensation if they can borrow and lend at their personal rates of time preference (Henderson & Quandt, 1980). However, empirically managers’ rates of time preference may be different for borrowing and lending situations and satisfying managers’ personal rates of time preference may be too costly for inducing investment for some firms. If so, solving the long-term investment problem will be more complicated than switching from short-term to long-term incentive systems. Conventional economic discounting theory also asserts that to maximize his/her own utility, a decision maker will adjust his/her rates of time preference to market rates, or to anticipated market rates which reflect the current or anticipated macroeconomic environment (Henderson & Quandt, 1980). Anecdotal evidence indicates that the stock market frequently falls in (presumed) response to the release of highly positive news about the economy’s rate of growth if that news is also taken to signal potential inflation or higher interest rates. Individual implied discount rates are also expected to respond to changes in the timing of expected compensation (delay or speed-up frames) and the domain of an incentive plan. That is, we predict discount

5

External reporting standards are set by the Financial Accounting Standards Board (FASB), a seven-member board appointed by the Financial Accounting Foundation. The members work full time for the FASB. Once appointed, members must sever their ties with firms for which they previously worked. Suggested standards or changes are released first as exposure drafts. The Board receives input from interested parties and revises the proposed standard as necessary before its release.

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rates will be influenced by whether expected compensation is computed from a bonus or a penalty plan. The next four subsections discuss conventional economic time discounting, intertemporal framing (delays and speedups), compensation domain, and environmental uncertainty and how they relate to managers’ investment decisions. Conventional Economic Time Discounting

The computation of present values (the value today of something that will be received in the future) allows meaningful comparisons of economic events that take place at different points in time. Individuals have their own personal rates of time preference (discount rates) that are independent of market rates of interest and borrowing and lending opportunities. The conventional continuous-time discounting model for money is P Å F[exp(0rt)],

(1)

where P is today’s value of a sum of money and F is its future value, the value that will make the owner of the sum indifferent between receiving P today or F, t years in the future. The time discount rate is r, which, along with the length of the delay (t), controls the difference between P and F. A positive rate of time preference (r ú 0) implies impatience, a preference for current over future receipts/consumption.6 Economic discounting theory predicts that r will follow market interest rates if consumers wish to optimize lifetime consumption (Henderson & Quandt, 1980). Discount rates may also reflect the decision maker’s response to the macroeconomic risk that they cannot diversify away. Macroeconomic risk represents what previous intertemporal choice researchers refer to as ‘‘implicit risk’’ (Stevenson, 1986; Benzion, Rapoport, & 6 The discrete-time model that business, calculus, and economics students learn is P Å F(1 / r/m)0(t ∗ m), where P and F are defined as above; r is an annual discount rate (e.g., an interest rate), t is the number of years in the future that F will be received (say 5), m is the number of periods (say twelve) in each year for which the discount (interest) will be computed and added to P. r/m is the discount rate per period (e.g., per month), and t∗m is the total number of periods (12∗5 Å 60) for which the discount will be computed. Thus, if one would like to know how much money must be deposited in an interest bearing account today (P) in order to have $1000 (F) 5 years from today, and the deposit is made into an account that pays 10% per year (r Å .10) compounded only annually (t Å 5 and m Å 1), the value of P is computed as $1000(1.10)05 ∗ 1 à $621. If interest is computed monthly and deposited into the account each month (i.e., it is compounded monthly) rather than annually, then m Å 12, r/m Å .10/12, and t∗m Å 5 1 12, so P Å $1000(1.00833)060 à $608. If interest is compounded continuously (i.e., if m is allowed to approach infinity) the discrete time model P Å F(1 / r/m)0(t ∗ m) becomes model (1) (Chiang, 1984).

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Yagil, 1989; Shelley, 1993). Relying on Stevenson’s (1986) results, we assume that the discount charge for implicit risk does not change with the value of t, but it will change with the amount of money at risk (i.e., with P). ‘‘Explicit risk’’ is the risk associated with a specific firm or investment project; discount rates that could change with the specific investment are not tested in this study. Intertemporal Framing Effects

The Frame Implied discount rates are also influenced by framing effects (i.e., the direction of proposed changes in compensation timing). Loewenstein (1988) describes three frames that can be used to induce discounting in an intertemporal choice setting: delay, speed-up, and neutral. He showed that the way an intertemporal comparison is framed influences the size of implied discount rates. In addition, outcome sign (e.g., bonus or penalty in this study) interacts with frame to induce a sense of a net gain or net loss whenever a decision that changes outcome timing is contemplated (Shelley, 1993). For example, suppose a manager who has earned a bonus every year for several years of about $1000 has been told this year’s bonus is available immediately; he/ she need only pick up the check from Payroll. However, upon arrival at Payroll he/she is asked to delay the bonus for 1 year.7 The manager will experience the delay as a $1000 immediate subjective loss, which is offset somewhat by the promise of a $1000 bonus in 1 year; the offset is the discounted subjective value of $1000 paid 1 year hence. Let v(x, t) represent the subjective value of x dollars received at time t; if x is negative, v(x, t) is negative, but the slope of v(r, r) for negative x is steeper than the slope of v(r, r) for positive x (See Tversky & Kahneman, 1991, for a discussion of the slope difference). The manager experiences a subjective net loss because the impact of the subjective value of a $1000 receipt 1 year hence (i.e., v($1,000; 1) is less than the immediate subjective loss of $1000 (i.e., Év(0$1000; 0)É). This is true for two reasons. The first reason is related to the timing of the two payments. Managers are not indifferent to the timing of compensation. In general, they are impatient (i.e., their discount rates are positive), which makes current receipts more valuable than future receipts of the same size. That is, v($1000; 0) ú v($1000; 1). The second reason is related to the change in the slope of v(r, r) at zero, which makes Év(0$1000; 0)É ú v($1000; 0). 7

This example is like one of the experimental conditions in Thaler (1981).

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Because of these two effects, the implied discount has at least two parts. That is, the difference between P and F, empirically, is due to both time discounting and the difference between the gain and loss slopes of the decision maker’s subjective value function, if the decision maker has framed his/her intertemporal choice in either the delay or speed-up frame. Referring to model (1), this means that if P Å $1000, the manager’s current (t Å 0) bonus, and F is the future bonus he/she would demand if P were delayed 1 year (t Å 1), then the difference between P and F is only partially captured by P Å F[exp(0rt)] in the delayed bonus setting. The part of the difference not captured is the part due to the manager’s experiencing the delay as an immediate loss. In order for the delay of a bonus to be experienced as a loss, the manager must already have incorporated the current bonus into his/her current wealth. The delay frame described above is induced when (1) the decision maker has adjusted psychologically to experiencing an outcome immediately and (2) a timing change postpones the expected outcome. In the example above, by incorporating the expected bonus into current wealth, part 1 is satisfied, which results in a reference point shift, which, in turn, results in the managers’ defining wealth including the bonus as the status quo (v(status quo, 0) Å 0). Then if the manager makes a decision that postpones his/her bonus, foregoing the bonus is experienced as an immediate loss, rather than maintenance of the status quo, because his reference point has already shifted. The speed-up frame is invoked when (1) a decision maker has adjusted psychologically to experiencing an outcome in the future and (2) a timing change that would speed up the outcome is suggested. For example, suppose a manager expects to receive a bonus of $1000 in 3 years. The manager may discover that he/she can save money on scheduled maintenances during the current year to obtain a bonus in the current year, but he/ she may also know that eliminating this year’s maintenance will prevent his/her receiving a bonus in 3 years. Choosing to eliminate scheduled maintenances will, in essence, speed up his/her current bonus; therefore, the manager would be expected to take a smaller bonus than $1000 to receive it sooner. A neutral intertemporal choice frame asks the decision maker for an intertemporal value comparison without suggesting that an expected outcome’s timing will change. An intertemporal choice ‘‘delay frame’’ is often induced by past compensation experience in the following way: Many U.S. firms pay annual bonuses to encourage managers to pursue profitability and growth objectives,

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which typically are measured annually or quarterly. Managers come to expect annual bonuses—to consider them part of regular compensation—and they will go to great lengths to ensure that the bonuses continue. Recently, some firms have also implemented long-term, or deferred, compensation plans which are tied to longer-range performance goals, in the hope of better aligning managers’ incentives with firm welfare. However, optimizing long-run firm welfare sometimes will mean sacrificing immediate reported earnings, especially if the contemplated investment includes an investment in intangible assets whose cost is expensed currently. Hence, if bonuses have always been awarded based on short-term reported performance, the decision to invest in employee training means sacrificing the current year’s bonus, which the manager now considers part of his regular compensation. The manager’s company expects to pay for the delay, but the company expects a discount rate that is consistent with market rates of interest—perhaps the manager’s borrowing rate (say, 5 to 15%). However, the delay frame effect may generate much greater rates (30% or more). This means that the manager could demand much more in the future than his employer is willing to pay to obtain the benefits of the investment. Recent intertemporal choice research indicates that managers may expect to be compensated for the loss of immediate compensation far in excess of the amount the time value of money would imply (Loewenstein, 1988; Benzion et al., 1989; Shelley, 1993). Managers making this sacrifice experience a subjective net loss that cannot be compensated by the time discount alone (Shelley, 1993). These managers are delaying a receipt to which they have already adapted. More concretely, managers may have made plans for the money or have already included it in wealth.8 If so, its delay will induce a sense of loss, and the future compensation required to compensate the loss will be surprisingly high. Compensation also can be ‘‘expedited’’ by an astute choice of short-term actions. If past experience sets up a timing expectation (present or future), then a decision that changes the timing will either delay or expedite it; hence, past experience may dictate the frame. Outcome Sign Intertemporal choice frames interact with outcome sign to generate subjective net gains and losses. Within the delay frame if the outcome of a decision is good (positive sign, a bonus in this study), the decision maker experiences a subjective net loss; if it is bad 8

That is, their value function reference point may reflect a bonus already received.

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(negative sign, a penalty in this study), he/she experiences a subjective net gain. Within the speed-up frame, if the outcome is good, the decision maker experiences a subjective net gain; if it is bad, he/she experiences a subjective net loss. Previous research has shown that when an outcome is desirable, the delay frame produces a much larger implied discount rate than the speedup frame; and when the outcome is undesirable, the opposite is true (Loewenstein, 1988; Shelley, 1993). The neutral frame produces implied discount rates that are intermediate to the other two frames (Shelley, 1993). The subjective net gain situations, in particular the postponed payment, not only generate lower implied rates than the delayed receipt situation, but they also occasionally generate negative implied rates because the immediate gain does not always more than offset the future loss (Shelley, 1993). The influence of sign– frame combinations on implied discount rates has been consistent across a number of studies (Loewenstein, 1988; Thaler, 1981; Benzion et al., 1989; Shelley, 1993). The part of an implied discount rate attributable to outcome sign–frame interaction must be separated from the part due to time discounting to accurately measure time discount rates (Loewenstein, 1988). But, the part due to the interaction is by its nature a onetime charge. It does not grow with the length of the delay. Thus, it can be estimated separately from the time discount rate as long as timing is varied systematically across all outcome sign by frame conditions. In model (2) below, let s represent the discount rate reflected in the one-time premium that compensates either an immediate net loss or an immediate net gain. Then, model (2) represents both time and sign by frame interaction discounting P Å F[exp(0s)exp(0rt)].

(2)

The total discount is produced both by time discounting (exp(0rt)) and by the adjustment due to the difference between the gain and loss slopes of the value function (exp(0s)). The sign–frame interaction rate, s, can be either positive or negative, depending in part on the frame (Shelley, 1993). If it is negative, it will imply ÉPÉ ú ÉFÉ, contrary to conventional discounting predictions.9 Empirically, this occurs most often in the delayed payment situation. People resist timing changes in general and they are particularly annoyed when

9 Conventional discounting predicts a smaller absolute magnitude for both positive and negative outcomes which implies impatience. A negative discount rate implies the opposite.

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asked to delay payments to which they have already psychologically adapted, especially small payments.10 Now, suppose s1 is the delayed receipt rate, s2 is the delayed payment rate, s3 is the expedited receipt rate, and s4 is the expedited payment rate. Then, given the discussion above, both s1 and s4 (subjective net losses) are predicted to be larger than s2 and s3 (subjective net gains). Typically, it has also been found that s1 ú s4 ú s3 ú s2 (Benzion et al., 1989; Shelley, 1993).

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often they are nearly the same (Benzion et al., 1989; Shelley, 1993). In the current setting, however, the ‘‘expedited penalty’’ rate may be substantially lower than the ‘‘delayed bonus’’ rate because the delayed penalties are opportunity costs. The ‘‘delayed penalty’’ rate is expected to be the lowest of the four outcome sign– frame interaction rates. Summary of Outcome Sign by Frame Interaction Effects

Outcome Sign: Bonus and Penalty Contracts

In the current setting of incentive compensation, a positive outcome is a bonus that can be either delayed or expedited. The negative outcome, a penalty, is more difficult to imagine. In theory, a penalty contract could be written with the same expected monetary value as a bonus contract. However, few penalty provisions are encountered in contracts within firms because managers are not indifferent between bonus and penalty provisions, even of equal expected monetary value.11 Penalty provisions are sometimes written into contracts between firms or between governmental bodies and contractors. Managers are not indifferent to penalty contracts, in part because penalties are valued on the loss portion of the subjective value function and bonuses are valued on the gain portion. Previous tests of intertemporal framing theory have used hypothetical out-of-pocket payments as the negative outcome when both positive and negative outcomes were studied. For example, Thaler’s (1981) instrument described a fine that subjects had to pay. He then suggested that the payment could be delayed for a period of time. Benzion et al. (1989) described a debt that was owed. In this study, the negative outcomes are in the nature of opportunity costs. The penalty contemplated in the penalty contracts is an amount that would be withheld from pay, not a cash payment to be made by the manager. Opportunity costs do not typically generate as strong a negative reaction as out-of-pocket costs, so one might expect less enthusiasm for delaying a penalty, and less aversion to expediting it, than an anticipated cash payment would generate (Thaler, 1981). The prospect of delaying a payment has never generated much enthusiasm (Thaler, 1981; Benzion et al., 1989; Shelley, 1993). Previous studies have shown that the ‘‘delayed receipt’’ and ‘‘expedited payment’’ rates are higher than rates in the other two scenarios and 10

Unfortunately, subjects also have more difficulty interpreting these scenarios in experimental settings than any of the other sign– frame combinations and this would also account for some of the negative rates encountered. 11 Penalty provisions are not uncommon in construction contracts, or other contracts, where specific performance can be judged.

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Crossing the delay and speed-up frames with bonus and penalty outcomes produces four outcome sign– frame scenarios. The following paragraphs describe the anticipated outcome sign–frame interaction effect on the kind of investment decisions used in this study: Delayed bonus scenario. A manager chooses to delay a current bonus if he chooses to invest in an asset that must be expensed immediately because the investment will reduce current reported income and will not pay off until sometime in the future. Managers are expected to be reluctant to delay bonuses. Overcoming their reluctance may require very large future bonuses that reflect higher implied discount rates than some firms may be willing to pay. If managers do not believe they will receive large enough future bonuses, they will not delay; hence, they will not invest. In this study, we ask subjects how large their future bonus would need to be to induce them to make the investment immediately and wait a specified period of time for a future bonus. Delayed penalty scenario. In this scenario, choosing to invest means incurring an immediate penalty. Based on previous research, managers are expected to be willing to incur a current penalty to which they have already adapted. More precisely, they tend to be reluctant to delay penalties. Their reluctance is reflected in low or negative implied discount rates. Their company would expect a larger penalty from the manager in the future than he will be willing to pay. Hence, managers will not delay either the penalty or the investment. In this study, we ask subjects how large a future penalty they would be willing to pay for the opportunity of delaying it a specified period of time. Expedited bonus scenario. A manager who has been paid in the past based on a long-term incentive contract may anticipate future bonuses resulting from a current investment. If his firm then implements a short-term bonus plan, he can expedite his anticipated bonus by foregoing the current investment. Managers tend not to be eager to expedite bonuses once they have adjusted to their future receipt. Therefore, they will not tolerate a high discount on the bonus to obtain it early. Nevertheless, companies would expect a reasonable discount to expedite a bonus. Thus, managers will not expedite and, hence, the investment would probably take place currently. In this experiment, subjects are asked to state how small a bonus they would be willing to accept to expedite a future bonus. Expedited penalty scenario. A manager who has been paid on a long-term penalty contract may anticipate a future penalty brought about by failing to invest in the current period. If his/ her company implements a short-term plan, the manager can expedite the penalty by investing currently, which would lower immediate reported income, triggering an immediate penalty. However, it would benefit future reported income and, hence,

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TABLE 1 Summary of Predictions for the Relative Sizes of Implied Discount Rates Scenario If the implied discount rate is (predicted relative size in bold)

Delayed bonus

Delayed penalty

Expedited bonus

Expedited penalty

High Low

No investment Investment

No investment Investment

No investment Investment

No investment Investment

prevent the future penalty. Managers require a large reduction in the penalty to incur it early. Companies may not expect so large a discount in the penalty and may be unwilling to pay the price. Hence, current investment is less likely in this scenario. In this scenario, subjects are asked how much smaller their immediate penalty would need to be for them to be willing to expedite it.

The investment decisions implied by high and low implied discount rates in each of the four scenarios described above are summarized in Table 1. The predicted result is shown in bold. These predictions are based on the theory developed by Loewenstein (1988) and extended by Shelley (1993). Crossing the delay and speed-up frames with positive and negative outcome signs gives four possible scenarios, two that are experienced as subjective net losses and two that are experienced as subjective net gains. We predict higher discount rates for the subjective net losses than for the subjective net gains, and we indicate in Table 1 the effect that could have on a manager’s decision to invest. The most commonly encountered of the four scenarios in the United States is the delayed bonus scenario, and the typical implied discount rate in that situation is very high. Hence, we expect to find that intertemporal framing effects contribute to the apparent bias against long-term investment. Implicit Risk: The Macroeconomic Environment

Any distant event is less certain than its more immediate counterpart. Delay imposes risk because of future uncertainty even for otherwise sure outcomes. Many decision makers discount future outcomes due to the implicit risk associated with the future. However, the source of the future uncertainty (and risk) must almost certainly vary with the decision setting. The future risk to a farmer’s crop may be associated with weather; the future risk to wealth or a fixed income may be due to inflation; and the future risk to a business may be due to changes in technology. The future cannot be perfectly predicted. This study makes a first attempt at manipulating the level of implicit risk felt by subjects in a particular setting. We manipulate the state of the macroeconomy which, we claim, induces predictable expectations

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about the future behavior of inflation and interest rates. If the manipulation is successful, we may be able to measure the impact of implicit risk on implied discount rates and determine whether it exists as a separate construct from time discounting. In previous studies implicit risk and time discounting have been confounded because implicit risk was not manipulated in a fully crossed design. In this study implicit risk is imposed on future outcomes by the macroeconomy. Most studies investigating the links between managers’ implied time horizons, their compensation plans, and company financial performance are based on archival data developed during the 1970s and early 1980s. However, that period of time was characterized by general economic expansion accompanied by erratic government economic policies, increasing effective tax rates for capital intensive industries, a consumptionbased tax code, and rapid inflation. These characteristics produced instability and uncertainty. A more stable and predictable economic environment might result in better long-range planning and more long-term investment. Macroeconomic uncertainty increases discount rates. Thus, a manager’s personal implied discount rate will be influenced by his/her expectations about the potential effect of the macroeconomy on his/ her wealth. We call this kind of environmental risk implicit risk to distinguish it from risk related to the company or to its investment project. Empirically, implicit risk has produced a single discount unchanged by the length of the decision horizon (Benzion et al., 1989), which means the implicit risk discount does not appear to change with the length of the delay. Benzion et al. (1989) and Shelley (1994) have attempted to estimate both implicit risk and time discount rates simultaneously using model (3) below, or its discrete-time counterpart. In both studies the time and implicit risk rates were confounded because implicit risk had not been separately manipulated.12 12

From about the eighteenth century until now, researchers have not been clear about whether discounting results entirely from implicit risk or from a combination of implicit risk and discounting attributable to economic impatience. Therefore, few empirical re-

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P Å F[exp(0s)exp(0s*)exp(0rt)].

(3)

In model (3), the implicit risk rate is represented by s* and the other variables are defined as in model (2). The magnitude of s* is predicted to change with the perceived level of uncertainty, or risk, in the environment. An individual’s entire implied discount rate consists of r / s / s*. The decisions of managers whose compensation depends on the performance of their firm may be influenced by the reported state of the economy and that influence may affect implicit risk discount rates. This study manipulates implicit risk by suggesting the state of the macroeconomy in which the events will play out. Three possible states were suggested, one for each of three treatment groups: stable, expanding, and deteriorating. (1) When the macroeconomy is stable, interest rates are stable and predictable, prices are steady, demand constant, and supplies reliable. In such an environment, forecasts of operational results will be credible, so the risk associated with the future will appear modest. In a stable environment, there is little cause for concern about either the investment return or the effect of delay on the value of future rewards. Inflation and interest rates are both modest. (2) When the economy is expanding, investments are more likely to succeed; however, in the United States, periods of rapid expansion have become identified with inflation and high interest rates, which diminish the value of future compensation. If managers focused only on their company’s potential for success with the investment, they might perceive an expanding economy as less risky than a stable or deteriorating one and lower their implied discount rates. However, managers are concerned about the effect of their decisions on their own wealth and they may worry more about their potential loss of purchasing power than about the success of the investment (especially if they believe their tenure with the company will be short). In an expanding economy, implied discount rates will increase due to economic uncertainty when managers contemplate delaying a bonus or expediting a penalty because inflation makes today’s dollars worth more than tomorrow’s. (3) When the economy is deteriorating, prices may decline, but firm income may also be in jeopardy. This situation is difficult to analyze. Low implied discount rates would follow from the prospect of declining prices (just as higher rates would follow from inflation), but the situation for the firm, and for the prospect of future employment, is more risky. In general, implied discount rates are expected to fall in a deteriorating economy because managers expect lower, or no, inflation and lower interest rates.

Let s*1 be the implicit risk rate when the economy is stable, s*2 the implicit risk rate when the economy is expanding, and s*3 the implicit risk rate when the economy is deteriorating. Then, if subjects react to descriptions of the macroeconomy as outlined above, the intusearchers have separated the two concepts. Bo¨hm-Bawrek (1923), a leading authority on discounting and interest rates in his time, argued that the implicit risk rate is independent of time discounting. Stevenson’s results are consistent with this idea (1986).

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ition that managers will demand compensation for increased uncertainty about their future wealth leads to the prediction that s*2 ú s*1 ú s*3 . METHOD Subjects

Subjects for this experiment were 84 upper division accounting majors at a large midwestern state university. All had previously received training in discounting either in finance or accounting courses. Responses from 15 of the subjects were dropped because they were incomplete or because the subject did not understand the task.13 Design

Factors and Levels Between group factor. Implicit risk was manipulated as a between groups factor. If the macroeconomic environment imposes substantial risk on the future wealth of managers who receive deferred compensation, then the implied discount rates of groups of subjects exposed to different macroeconomic environments should be different. Implicit risk has three levels, a stable economy and healthy industry, an expanding economy and high-growth industry, a deteriorating economy and low-growth industry. Manipulating implicit risk increases the number of experimental factors studied in previous intertemporal choice literature by one. This change was, of course, invisible to subjects because environmental uncertainty (implicit risk) was manipulated between subjects. Thus, subjects only assessed the effect of the environment once, then they considered the remaining four factors repeatedly. Within subject factors. Previous researchers have manipulated four factors: the frame (delay or speedup), outcome sign (bonus and penalty), outcome magnitude, and time (the length of the speed-up or delay). Frame and outcome sign were crossed to create four scenarios: delayed bonus, delayed penalty, expedited bonus, and expedited penalty. Time had three levels (2 years, 3 years, and 5 years); outcome magnitude (i.e., the size of the bonus or penalty) had three (1, 5, or 10% of reported income, which was given). Time and outcome magnitude were not central to 13 This is approximately the same rate of subject loss experienced in other intertemporal choice experiments in which subjects have been run in large groups with many stimuli. The experimental booklets are long and pages are missed occasionally unless subjects are run one at a time.

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this investigation; however, both have been shown to affect implied discount rates. Time was manipulated so that time and implicit risk discounting could be easily separated. Previous empirical results indicate that small outcomes can produce very large positive and negative mean rates with high variances. Unfortunately, ‘‘small’’ is relative. Thus, outcome magnitude is manipulated in this experiment so its effect can be measured and isolated from other effects. Three groups of subjects responded to 36 (3 1 3 1 2 1 2) scenario-type stimuli. Setting. Previous studies have been conducted in personal settings. Thus, the business setting presented in this study is a second change from previous research. The new setting is not expected to change the effect of the four factors previously studied. No change is expected because, even though the setting is changed, subjects’ primary focus is expected to be the effect of the decision on their personal well-being. In this experiment, investment decisions will affect the decision maker’s compensation and also his/her employer’s welfare. Task and dependent variable/subject response. The experimental instrument described an investment opportunity. Subjects were told that new equipment would improve earnings after the first year, and that the cost of the investment had two components: the cost of the equipment itself and the cost of training employees to use the equipment. Accounting rules do not permit capitalization of investments in human capital; they must be expensed immediately. If the subject/ manager chose to invest, the training costs would be subtracted from the current year’s income, eliminating the possibility of a bonus or triggering a penalty. The investment income would generate a future bonus or prevent a future penalty. It is the manager’s compensation preferences (with respect to time) that determine whether or not he/she will invest in the asset. Therefore, subjects were asked to provide their hypothetical compensation demands in response to experimental stimuli. Each of the 36 scenarios required a response in the form of an amount of money as follows: (1) In the case of delayed bonuses, subjects were asked to state how large their future bonus would need to be for them to be willing to undertake the investment and forego their current bonus. (2) In delayed penalty situations, subjects were asked to state how large a penalty they would be willing to pay in the future to avoid a penalty in the current year. (3) In expedited bonus situations, subjects were asked how much smaller a bonus they would be willing to take to speed up its payment from the future to the present. (4) In expedited penalty situations, subjects were asked how

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much smaller they would expect a penalty to be if it were moved from the future to the present.

Scenarios were randomized and combined with distractor tasks. Each subject completed the experiment twice in two sessions set several days apart. Each session had a different random order. The scenario descriptions were detailed enough to describe the economy, the working contract, and the investment decision that would trigger the change in outcome’s timing. Subjects were given course credit for their participation in the experiment. RESULTS Computation of Implied Discount Rates

The monetary values represented in model (4), P and F, were either subject responses or amounts that were given in the experimental stimuli as follows: (1) In the delayed bonus condition the present bonus (P) was given and subjects were asked to provide the compensating future bonus (F). (2) In the delayed penalty condition the present penalty (P) was given and subjects were asked to provide the compensating future penalty (F). (3) In the expedited bonus situation subjects were given the future bonus (F) and were asked to provide the compensating present bonus (P). (4) In the expedited penalty situation, subjects were given the future penalty (F) and were asked to provide the compensating present penalty (P).

These present and future values and the values of the manipulated factors were used to estimate the four components of the implied discount rates: the time discount rate (r), the implicit risk rate (s*), the frame by sign effect (s), and the outcome magnitude effect (r*). Both regression model fitting and variance analyses were conducted with reference to model (4): Pij Å Fij[exp(0s*i )exp(0sj )exp(0rt)exp(0r*x)], (4) where i indexes implicit risk (macroeconomic) conditions (s*i is the implicit risk rate for economic condition i), j indexes outcome sign by frame scenarios (sj is the rate for outcome sign–frame combination j), r is the time discount rate, t is a measure of continuous time, x is the rank of the bonus/penalty magnitude, and r* is the change in the implied discount rate that is due to changes in bonus/penalty magnitude.14 Previous research has shown that implied time discount rates vary inversely with outcome magnitude, so r* is expected to 14 Four outcome sign–frame scenarios were defined for the regression analyses. Sign and frame were treated as separate factors in the analysis of variance.

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TABLE 2 Analysis of Variance Results: Main Effects and Significant Interactions [Dependent Variable Å 0ln(P/F)] Effect

df

F value

p valuea

Implicit risk Beliefs about the economy Implicit risk 1 beliefs Outcome magnitude Time Frame Outcome sign Outcome magnitude 1 time Frame 1 outcome sign Frame 1 outcome sign 1 implicit risk

2 2 4 2 2 1 1 4 1 2

5.473 2.100 2.748 10.161 53.201 .200 6.486 3.152 4.749 3.463

.0066 .1316 .0364 .0007 .0001 .6564 .0135 .0275 .0333 .0378

a

These are Geisser–Greenhouse p values.

be negative (e.g., Thaler, 1981; Benzion et al., 1989; Prelec & Loewenstein, 1991; Shelley, 1993). The purpose of manipulating outcome magnitude was similar to the purpose of manipulating the length of delay or speed-up, that is, to help separate the effect of magnitude from those of the variables of interest.15 Mean (across sessions) subject responses were transformed as follows: Pij/Fij Å exp[0si 0 s*j 0 rt 0 r*x], so 0ln[Pij/Fij] Å si / s*j / rt / r*x.

(5)

The transformed values, 0ln[Pij/Fij], were the dependent measures used in both the analysis of variance and the regression model fitting. If a subject did not discount, F and P would be equal and 0ln[Pij/Fij] Å 0. Therefore, the regression model was fit without an intercept. Analysis of variance results were no different with or without the intercept, the results reported herein were computed using a multivariate repeated measures approach which includes an intercept but takes account of the interdependencies among the responses. Also, if implicit risk, outcome magnitude, and the outcome sign by frame scenarios have no effect on discounting, implied discount rates will be just r Å 0ln(P/ F)/t. However, if implied discount rates had been computed assuming this relation holds, and if r computed as 0ln(P/F)/t had been used as the dependent measure in analysis of variance or regression analyses (instead 15

It is also important that the magnitudes be neither too large nor too small to be relevant to student subjects. Providing a range of outcome magnitudes will help ensure that at least some values are relevant.

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of 0ln(P/F)), the transformation itself could create time interactions with implicit risk, outcome magnitude, frame and sign whenever those effects were nonzero. Therefore, the 0ln[Pij/Fij ] values were analyzed instead of the time discount rate, r (or an estimate of the whole implied discount rate) in the repeated measures analysis of variance. Analysis of variance results are shown in Table 2. Manipulation Checks

Implicit Risk For the manipulation of implicit risk to be successful, it was necessary to replace subjects’ current beliefs about the macroeconomy with the experimental representation of the economy. To check the effectiveness of the implicit risk manipulation, subjects were asked to state their own beliefs about the current state of the economy as part of a questionnaire that asked several questions about the economy, the job market, their university, and the courses the students were taking in the Summer of 1993. The information about economic beliefs was entered into an analysis of variance along with implicit risk (and the other manipulated effects), so the effect of the intended manipulation could be separated from subjects’ beliefs about the real U.S. economy. The main effect and significant interaction results from this analysis of variance are shown in Table 2. The manipulated state of the economy influenced responses significantly (p õ .05), but subjects’ prior beliefs about the economy did not. Apparently the implicit risk manipulation was successful. However, an interaction appeared between prior beliefs and experimental implicit risk conditions caused by the expanding economy level (p õ .05). Table 3A gives cell means and standard deviations for the implicit risk conditions; Table 3B gives cell means and

TABLE 3 Cell Means and Standard Errors for 0ln(P/F): Implicit Risk (A) and Outcome Sign by Frame (B)

Condition (A) Implicit risk conditions High growth/expanding Healthy/stable Low-growth/deteriorating (B) Outcome sign 1 frame conditions Delay bonus Delay penalty Expedite bonus Expedite penalty

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Standard error

.420 .363 .228

.014 .014 .008

.381 .295 .354 .346

.015 .014 .016 .015

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FIG. 2. Plot of outcome sign cell means. FIG. 1. Implicit risk by economic beliefs interaction plot.

standard deviations for the outcome sign by frame interaction conditions. High mean values of 0ln(P/F) imply high discount rates. Figure 1 is a plot of cell means for the implicit risk by prior economic belief interaction. On average, subjects in the expanding economy condition discounted most heavily. According to Fig. 1, when subjects believed the real economy was expanding and they were also assigned to the expanding economy condition, their discount rates were higher still. In fact, the U.S. economy at the time of the experiment was nearing the end of a prolonged recession, so there were only five subjects who believed the economy was expanding.

expected to be intermediate (no effect). As expected, subjects who had been told they were operating within a high growth industry in an expanding economy produced the highest cell means, which implies the highest discount rates. See Fig. 3, a plot of cell means by implicit risk condition. Cell means for the implicit risk conditions used are also shown in Table 3A. Subjects who were told that they were operating within a low growth industry in a deteriorating economy produced the lowest means. Planned comparisons indicate that the difference between the expanding economy and the stable economy means is significant (p Å .0365), as is the difference between the expanding and the deteriorating economy means (p Å .0020). Post Hoc Analyses

Tests of Predictions

The results reported in this section refer to tests conducted on subsets of the data used for the overall analy-

Main Effects The time and outcome magnitude main effects are significant. A significant time effect means only that subjects discounted and that they did so in proportion to the length of the delay. Subjects also discounted small amounts of money more quickly than large amounts as expected. Time is the most significant influence on the dependent variable, as expected, but implicit risk is also important. Outcome sign is also significant because of the low mean in the delayed penalty cell. See Fig. 2, a plot of the bonus and penalty cell means, and Table 3B. Macroeconomic Environment The information that the macroeconomy was expanding was expected to increase implied discount rates; the deteriorating economy was expected to reduce implied discount rates; the stable economy was

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FIG. 3. Implicit risk means plot.

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FIG. 4. Outcome sign by frame interaction plot: Stable implicit risk condition only. FIG. 6. Outcome sign by frame interaction plot: Deteriorating economy only.

sis of variance. The data were split by implicit risk condition, Stable, Expanding, or Deteriorating. The F values from these analyses were compared to critical F values for an alpha level of .025 because these were not the first tests conducted using these data. This is an approach suggested in Neter, Wasserman, and Kutner (1983) for reliably setting confidence levels when two or more tests are conducted using the same data. Stable Economy. The predicted outcome sign by frame interaction did not emerge for the stable economy condition (F(1,20) Å .639). Positive and negative outcomes were discounted at about the same rate regardless of frame (F(1,20) Å 1.756) and the frame effect was not significant (F(1,20) Å 4.068). The outcome sign by frame interaction is plotted in Fig. 4. Expanding economy. In the expanding economy condition, the outcome sign by frame interaction is highly significant (F(1,26) Å 10.344). Figure 5 is a plot

of this interaction. The outcome sign main effect was also significant for this group (F(1,26) Å 6.373); bonuses produced higher discount rates than penalties. Deteriorating economy. The outcome sign by frame interaction was not significant in the deteriorating economy condition. Figure 6 is a plot of that interaction; note the small numerical differences between the cell means for the deteriorating economy relative to the other implicit risk conditions. There also were no sign or frame main effects. Discount rates were low overall in this condition, and expedited penalties produced the lowest cell means, although they are not significantly different from the delayed penalty means. Penalties produced low means regardless of frame. Linear Regression Model Fitting

Aggregate Results Table 4 gives coefficient estimates from fitting a statistical model based on model (4) using all (69 1 36) observations. The time variable was treated as continuous. Outcome magnitude ranks were used rather than monetary values for two reasons: (1) changes in absolute magnitude, not changes in nominal values, generate changes in discount rates, and (2) using ranks of values minimized the scale differences between outcome magnitude and the other explanatory variables.16 All variables, other than outcome magnitude and time, were represented using dummy variables. Clearly, ei16

FIG. 5. Outcome sign by frame interaction plot: Expanding economy only.

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The regression was also run using monetary values. The results were not qualitatively different; however, using monetary values appears to add noise to the data set because the explanatory power of the model declined.

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TABLE 4 Coefficient Estimates from Linear Regression Model Fitting Dependent: 0ln(P/F) Model statistics:

Adj. R 2 Å .573

Count Å 2484

F Å 418.300

RMS Å .328

Variable

Coefficient estimate

Standard error

t Value

p Value

Stable economy b0 Å s*1 Time, b1 Å r Outcome magnitude, b2 Å r* Deteriorating economy, b3 Å s2 Expanding economy, b4 Å s3 Delayed bonus, b5 Å s*1 Delayed penalty, b7 Å s3 Expedited bonus, b6 Å s*2 Expedited penalty, b8 Å s*4

.105 00.29 0.131 .061 .133 .045 0.135 .128

.0053 .0040 .0170 .0160 .0270 .0270 .0290 .0290

20.000 07.276 07.768 3.821 4.923 1.666 4.660 4.415

õ.0001 õ.0001 õ.0001 .0001 õ.0001 .0958 õ.0001 õ.0001

ther one implicit risk condition or one outcome sign by frame scenario must be dropped when the model is fit. The regression model fit was Y Å b1 t / b2 x / b3 d1 / b4 d2 / b5 d3 / b6 d4 / b7 d5 / b8 d6 ,

(6)

where Y Å 0ln(P/F), t and x are time and outcome magnitude ranks, respectively; d1 and d2 are dummy variables representing the deteriorating and expanding macroeconomic conditions, and d3 through d6 are the four outcome sign by frame scenarios: delayed bonus, expedited bonus, delayed penalty, and expedited penalty, respectively. Model (6) implies the stable economic condition was omitted from the model. The model was fit with no intercept.17 Macroeconomic environment. On average, money was discounted over time at a 10.5% annual rate. This rate reflects time discounting alone in a stable economy. As the analysis of variance results indicated, a deteriorating macroeconomy had a dampening effect on discount rates (0.131), while an expanding economy increased discount rates (.061). When model fitting was restricted to the deteriorating economic condition (i.e., only a portion of the data set was used), the rate of time discounting diminished to .068; in an expanding economy it was .128. Outcome sign by frame. As expected, subjects were not especially eager to postpone an expected penalty (b7 had the smallest value of the outcome sign by frame scenarios at .045); the three remaining scenarios increased the discount rate more than the delayed pen17

Residuals from the regression employing aggregate data appear random and evenly distributed about zero.

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alty condition, although the rates reflected are not very different. A regression model was also fit with the data split by subjective net gain or loss. The subjective net loss scenarios are the delayed bonus and expedited penalty conditions. The subjective net gain scenarios are the expedited receipt and delayed payment conditions. Subjective net loss conditions produced higher discount rates than the subjective net gain scenarios (mean difference Å 0.079, t Å 02.773, p Å .0072, df Å 65). When a scenario described a subjective net loss condition, the overall implicit risk rate for a stable economy was zero as expected. The implicit risk rate decreases for a deteriorating economy (0.112, p õ .0001) and increases for an expanding economy. (.118, p õ .0001) (Adj. R 2 Å .610). In subjective net gain conditions, an expanding economy increases the implicit risk discount rate by .058 (p Å .0080). In subjective net gain conditions, a deteriorating economy reduces the implicit risk discount rate by 0.096 (p õ .0001). Only in the deteriorating economy were all four of the scenario coefficients significantly different from zero; all of them increase the overTABLE 5 Estimated Parameter Values for Regressions Split by Implicit Risk Condition Implicit risk condition

Expanding

Stable

Deteriorating

Adjusted R 2 Time, b1 Outcome magn., b2 Delay bonus, b5 Delay penalty, b7 Expedite bonus, b6 Expedite penalty, b8

.577 .128 0.022 .152 .005 .050 .071

.578 .114 0.041 .079 .015 .210 .182

.614 .068 0.028 .109 .073 .118 .094

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TABLE 6 Frame 1 Outcome Sign Cell Means (Standard Errors) Separated by Implicit Risk Category Implicit risk category Expanding Delayed bonus Delayed penalty Expedited bonus Expedited penalty

.514 .366 .389 .411

Stable

(.028) (.023) (.030) (.027)

.338 .280 .433 .401

(.023) (.032) (.029) (.028)

Deteriorating .252 .216 .234 .211

(.018) (.015) (.015) (.015)

all discount rate significantly over the relatively low time discount rate (r Å .068). In the stable economy, only the two expedite conditions change the time discount significantly; in the expanding economy, only the delayed bonus condition does so (see Table 5). These results are consistent with the analysis of variance results reported earlier18 (see Table 6). Discussion

Overall Analysis of Variance The results reported here are consistent with experiencing more uncertainty about future wealth in an expanding economy than in a deteriorating economy, which, in turn, is consistent with the fear that inflation will seriously erode purchasing power in an expanding economy. Subjects appear less concerned with their prospects for earning income than with the potential erosion of their wealth. An alternative explanation focuses more on interest rates than on purchasing power. Both the delayed bonus and the expedited penalty conditions can be interpreted as borrowing situations. Similarly, the expedited bonus and delayed penalty situations could be interpreted as lending situations (Benzion et al., 1989). Thus, concern about the effect of the economy on interest rates is also reasonable. In fact, the December 7, 1995, Wall Street Journal used the following headline to introduce the previous day’s market results, ‘‘Anticipation of Rate Cut Lifts Stocks.’’ The implied rates in both borrowing situations are high in the expanding economy, the one likely to induce high

interest rates. The lending situations produced lower rates. In the deteriorating economy, there were no differences among the implied rates for the four scenarios. Interest rates apparently were not a concern in either the deteriorating or the stable economies. The prospect of high interest rates and/or inflation increases the aversiveness of delaying bonuses and expediting penalties, but, presumably, increases the attractiveness of delaying penalties and expediting bonuses. Outcome Sign by Frame Interactions Incentive contracts in this experiment are characterized by whether they contain bonus or penalty provisions (outcome sign) and by whether they are paid based on short-term or long-term results, leading to opportunities to delay or expedite, respectively. Although the overall outcome sign by frame interaction is significant in this study, its shape is somewhat different from those reported in previous intertemporal choice research (Benzion et al., 1989; Shelley, 1993). See Fig. 7, which is the overall outcome sign by frame interaction plot. One difference between the outcome sign by frame interaction of this experiment and those of previous ones appears to be related to the implicit risk manipulation. However, it may also be related to the business setting. The three-way outcome sign by frame by implicit risk interaction is also significant (refer to Table 2). A very low delayed penalty cell mean is typical of previous experiments (Thaler, 1981; Benzion et al., 1989; Shelley, 1993), but the effect of delaying a penalty in this experiment is different in a deteriorating economy than under other economic conditions. Figure 8 is a plot of the three-way outcome sign by frame by implicit risk interaction. Note how low are all the cell means in the deteriorating economy condition.

18

Individual regressions were also split by implicit risk condition. Individual adjusted R 2 values ranged between .427 and .998. The mean R 2 is .857 (variance Å .015) and the median R 2 is .899. Residual plots for just under one-third of the subjects reflected some systematic variability that was not captured in the model. Some of that unexplained variability appears to be caused by a nonlinear relationship between the error and the model. This could be due to extremely nonlinear response functions that were ignored when analyzing this data. If that is the case, improved fits could be obtained by approximating the response functions of those subjects.

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FIG. 7. Outcome sign by frame interaction plot.

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FIG. 8. Outcome sign by frame by implicit risk plot.

Also, in previous studies the delayed positive outcome (bonus) and expedited negative outcome (penalty) scenarios produced approximately the same rates (Benzion et al., 1989; Shelley, 1993), but in this experiment the delayed bonus mean is substantially higher than the expedited penalty mean. This can be explained by the nature of the negative outcome in this setting. The penalty is an opportunity cost, not an out-of-pocket cost, so it would not be expected to produce as strong a reaction as the cash payments described in previous studies (Thaler, 1981). An expedited opportunity cost does not produce as great a sense of loss as an expedited out-of-pocket cost because people tend to underweight opportunity costs. It does not produce as strong an effect as the delayed cash bonus. Similarly, delaying the penalty does not produce as low an implied rate as did delaying cash payments in previous studies. Apparently, the level of implicit risk affects the way outcome sign by frame scenarios are experienced. The outcome sign by frame interaction produced by analyzing only responses from the expanding economy produced the interaction plot most like previous studies (see Fig. 5). The stable economy condition differs from the typical plot due to the relative positions of the two bonus cell means. They are reversed (see Fig. 4). Regression Model Fitting The expanding economy was interpreted by subjects as representing the greatest risk to their personal wealth. It produced a much higher implicit risk rate than the other two macroeconomic (implicit risk) conditions; the reason may be that subjects believed any

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wealth they would obtain in the future was at risk from loss of purchasing power. When the implicit risk conditions were analyzed separately, it became apparent that the delayed bonus condition produced its highest rate in the expanding economy condition and the delayed penalty condition its lowest. Subjects apparently interpreted the deteriorating economy as one with declining prices and interest rates. If a penalty is delayed, it may never be incurred if the firm goes out of business. This would explain the relatively high delayed penalty rate detected in the deteriorating economy. A high implied rate means that subjects were willing to pay a great deal in the future to delay an immediate penalty. In general, the deteriorating economy reduced discount rates, again, perhaps because interest rates or prices were expected to fall in that environment. A delayed bonus will ultimately be collected in dollars with more buying power if prices fall. Thus, if the deteriorating economy was interpreted in this way, an overall decline in implied discount rates would be predicted. Scenarios did not matter in the deteriorating economy probably because rates were so low overall (see Figs. 2 and 8). CONCLUSION

In the mid-1970s when U.S. business first noticed its competitive position dwindling relative to Japan and Germany, among the statistics quoted was the relative shortfall of long-term investment in the United States. One reason cited for the shortfall was U.S. managers’ short decision horizons, which were presumably induced by short-term bonus plans based on short-term accounting measures of performance. At that time, only a handful of the then Fortune 500 firms had any kind of long-term bonus plan; by the mid-1980s about 40% of the Fortune 500 firms had adopted long-term incentive plans (Louis, 1984). Typically, those plans were bonus plans that had been tacked onto the original short-term plans, but which were based on accounting measures averaged across 3 to 5 years (Louis, 1984). The longterm rewards were small relative to short-term rewards, so they were not attractive enough to resolve the tension between short- and long-term decisions in favor of the long-term. Subsequent to the mid-1980s, the problem was tackled by changing both the performance measure and the size of the long-term rewards. As of 1992, executives were rewarded more often with stock options that accumulated value with stock price appreciation, along with their usual base salaries and short-term bonuses. However, by 1992 both the House and the Senate had

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passed bills to prevent companies from taking tax deductions on ‘‘excess’’ executive pay, shareholders’ advocacy groups were holding hearings concerning executive pay, and complaints concerning executive pay excesses in the popular financial press had increased by an order of magnitude (Mallory, 1992; Lexis/Nexis, 1995). The average executive pay for the top job in a large corporation was $2 million by 1992; the highest paid executive in 1991 made over $75 million (Mallory, 1992). Of course, not everyone agrees that the executive pay described above is excessive. Good managers to run large companies are few. The market wage of such managers should be commensurate with their value to shareholders and with their own and their competitors’ reservation wages. Market forces may well explain the recent run-up in executive pay. Nevertheless, it is striking (and not inconsistent with the market argument) that the dramatic increase occurred at a time when companies were switching over to long-term incentive plans and that many shareholders, when informed, objected to the large deferred compensation amounts. Subjects in this experiment also demanded very high future compensation when asked to make a decision that would result in deferring current compensation. In this experiment, subjects reacted to economic uncertainty according to the effect they believed it would have on their own purchasing power. Subjects link a growing economy with possible inflation and rising interest rates. Since the 1970s, news about the health of the economy has nearly always been accompanied by speculation about the future path of interest rates and the prospect of inflation. The pain of delaying a bonus would be exacerbated by a loss of purchasing power. If managers borrow to replace bonuses, they may be subject to high interest rates. Subjects’ responses in this experiment indicated a desire to charge a premium for risking that prospect. The cost of expediting a penalty is also exacerbated by stronger present than future dollars, and subjects indicated a desire to be compensated for that as well. There are two implications of subjects’ responses to macroeconomic implicit risk: First, a high compensation charge for delaying a bonus or speeding up a penalty reduces the chance that a proposed investment will be undertaken except for companies that show a willingness to pay very high deferred compensation. Second, low implied discount rates for delayed penalties and expedited bonuses increase the chance that investment will be undertaken currently. If, in general, managers resist timing changes (as previous research indicates), two situations are likely to result in current investment: (1) A firm with an established deferred bo-

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nus contract, but no short-term bonus contract history, could implement a modest short-term bonus plan at little cost. (2) A firm with an established short-term penalty plan, could implement either a long-term bonus or long-term penalty plan at little cost. There are two clear organizational implications: First, in this study (and if Porter is correct, in many real world situations as well) the decision to invest or not depends in part on how income is computed. The current accounting treatment for intangible assets creates a bias against the kind of investment depicted in this study because short-term financial results are used to evaluate manager, division, and firm performance. Long-term results could be used instead for evaluation, but the results of this study indicate that such a change would be expensive. A change in accounting treatment (i.e., in how income is computed) would eliminate this particular investment bias. Second, as Porter (1992) suggests, the financial control system could be changed to one that depends less on measures of income and more on competitive position, or some set of nonfinancial measures of performance. Unfortunately, these accounting solutions would not solve the overall U.S. capital investment problem because the accounting issues, although important, are just a part of the problem (Porter, 1992). APPENDIX Experimental Instrument

A1B2C3D1 Cable Company Imagine that you manage Video Cable, a division of a major corporation operating successfully within a healthy industry and a stable economy. The corporation has been decentralized for several years with the separate operating units divided by product line. Because you are able to influence cost and sales levels and because you make investment and asset disposal decisions up to $1,000,000, you are evaluated based on a measure of return on investment (ROI). The numerator is your controllable contribution (income); the denominator is your division’s investment base. Cable Company has historically rewarded superior performance with a year-end bonus and for the past five years you have always received your share of the bonus pool. Your contract specifies a fixed salary of $45,000, plus a bonus of five percent of controllable contribution if your actual ROI meets your target ROI. If discretionary expenditures are carefully controlled for the next several weeks, this year’s bonus will be $10,900. However, the firm has just implemented a deferred

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bonus plan based on a five-year average ROI. Meeting the targeted average will require investing in at least one new project. If you invest $800,000 in new equipment and $200,000 to retrain employees, income and ROI will decline this year, but improve over the subsequent four years. Clearly, if you undertake this project, you must forego this year’s annual bonus. Whether you invest or not, you predict the usual annual bonus for the subsequent four years. In year five you expect to receive both the short-term and the deferred bonus if you choose to invest. You will, in essence, have delayed this year’s bonus for five years by choosing to undertake the investment. If you do not invest, you will not receive a bonus in year five. How large will your deferred bonus need to be so that you are just indifferent between collecting this year’s bonus of $10,900 and waiting for the bonus in year five? I would not be able to choose between a deferred bonus of $ in year five and this year’s $10,900 bonus. REFERENCES Benzion, U., Rapoport, A., & Yagil, J. (1989). Discount rates inferred from decisions: An experimental study. Management Science, 35(3), 270–284. Bo¨hm-Bawrek, E. V. (1923). The positive theory of capital. (W. Smart, Trans.). New York: G. F. Stechert. (Original work published in 1888). Chiang, A. C. (1984). Fundamental methods of mathematical economics, 3rd. ed. New York: McGraw–Hill. Coughlan, A. T., & Schmidt, R. M. (1985). Executive compensation, management turnover, and firm performance. Journal of Accounting and Economics, 7, 43–66. Eccles, R. G. (1991). The performance measurement manifesto. Harvard Business Review, January–February, 131–137. Henderson, J. M., & Quandt, R. E. (1980). Microeconomic theory: A mathematical approach, 3rd. ed. New York: McGraw–Hill.

Jensen, M. C., & Murphy, K. J. (1990a). Performance pay and topmanagement incentives. Journal of Political Economy, 98(21), 225–264. Jensen, M. C., & Murphy, K. J. (1990b). CEO incentives—It’s not how much you pay, but how. Harvard Business Review, May– June, 138–153. Johnson, H., & Kaplan, R. (1987). Relevance lost: The rise and fall of management accounting. New York: Harvard Business School Press. Kaplan, R. (1986). Must CIM be justified by faith along? Harvard Business Review, March–April, 87–95. Loewenstein, G. F. (1988). Frames of mind in intertemporal choice. Management Science, 34(2), 200–214. Louis, A. M. (1984). Business is bungling long-term compensation. Fortune, July 23, 64–69. Mallory, M. (1992). Executive pay: Compensation at the top is out of control. Business Week, March 30, 52–58. Murphy, K. J. (1986). Incentives, learning, and compensation: A theoretical and empirical investigation of managerial labor contracts. Rand Journal of Economics, 17(1), 59–76. Murphy, K. J. (1985). Corporate performance and managerial remuneration. Journal of Accounting and Economics, 7, 11–42. Neter, J., Wasserman, W., & Kutner, M. H. (1983). Applied linear regression models. Irwin: Homewood, IL. Porter, M. E. (1992). Capital disadvantage: America’s failing capital investment system. Harvard Business Review, 70(5), 65–82. Prelec, D., & Loewenstein, G. F. (1991). Decision making over time and under uncertainty: A common approach. Management Science, 37(7), 770–786. Shelley, M. (1993). Outcome signs, question frames, and discount rates. Management Science, 39(7), 806–815. Shelley, M. (1994). Gain/loss asymmetry in risky intertemporal choice. Organizational Behavior and Human Decision Processes, 59(1), 124–159. Stevenson, M. K. (1986). A discounting model for decisions with delayed positive or negative outcomes. Journal of Experimental Psychology: General, 115(2), 131–154. Thaler, R. (1981). Some empirical evidence on dynamic inconsistency. Economics Letters, 8, 201–207. Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A reference-dependent model. Quarterly Journal of Economics, 1039–1061.

Received: March 13, 1995

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