Balancing Incentive Weights and Difficulty of Performance Targets: Theory and Evidence

Transcription

1 Balancng Incentve Weghts and Dffculty of Performance Targets: Theory and Evdence MICA MATĚJKA W.P. Carey School of Busness, Arzona State Unversty KOROK RAY * Mays Busness School, Texas A&M Unversty November 2015 * Correspondng author: 460 Wehner Buldng, College Staton, TX E-mal: korok@tamu.edu. Ths research project has been supported by the Amercan Insttute of Certfed Publc Accountants (AICPA). We would also lke to gratefully acknowledge helpful comments of Shannon Anderson, Pablo Casas-Arce, Shane Dkoll, enry Fredman, Chrs Ittner, Andre Kovrjnykh, Ken Merchant, Mchael Rath, Dae-ee Yoon, as well as workshop partcpants at Boccon Unversty, George Washngton Unversty, Texas A&M Unversty, Yonse Unvsersty, Unversty of ouston, and the 2015 MAS Research Conference.

2 Balancng Incentve Weghts and Dffculty of Performance Targets: Theory and Evdence ABSTRACT We examne how frms balance the relatve mportance of multple performance measures n ther annual bonus plans. We present an analytcal model showng that manageral allocaton of effort s a functon of both relatve ncentve weghts and the dffculty of performance targets. We fnd that relatve ncentve weght and target dffculty can be ether complements or substtutes n motvatng effort dependng on the extent to whch managers have alternatve employment opportuntes. To test the predctons of our model we use survey data on the choce of performance targets n annual bonus plans. Our sample of 1,217 survey respondents conssts prmarly of fnancal executves n small- and medum-sze prvate companes where annual bonuses are the prmary ncentve nstrument. Consstent wth our model, we fnd that when companes are greatly concerned about manageral retenton, relatve ncentve weghts are negatvely assocated wth perceved target dffculty. Conversely, when retenton concerns are low, relatve ncentve weghts are postvely assocated wth target dffculty. Combned, our fndngs suggest that frms need to balance not only relatve ncentve weghts but also target dffculty when desgnng performance measurement systems.

3 1 Introducton A fundamental problem of ncentve contractng s that manageral performance s multdmensonal ncentvzng one dmenson of performance can come at the cost of neglectng other performance dmensons (olmström and Mlgrom [1991], Feltham and Xe [1994]). A large stream of lterature examnes how frms select performance measures and balance ther relatve mportance (e.g., Ittner, arcker, and Rajan [1997], Datar, Kulp, and ambert [2001]). Ths lterature has n part been motvated by the rsng popularty of comprehensve performance measurement models such as the Balanced Scorecard (Kaplan and Norton [1996a]) and the general trend n practce to augment tradtonal fnancal performance measures wth varous measures of nonfnancal performance (Ittner and arcker [2001]). Most of the analytcal lterature n ths area examnes the choce of relatve ncentve weghts on dfferent performance measures as the key ncentve nstrument wth whch frms nfluence allocaton of manageral effort over multple tasks (Banker and Datar [1989], Baker [1992]). owever, ncentve plans n practce specfy for each performance dmenson not only relatve weghts,.e., the percentage of total ncentve opportunty to be earned f performance on that dmenson s satsfactory, but also performance targets,.e., the standards defnng satsfactory performance (Mlgrom and Roberts [1992], Murphy [2001]). The choce of performance targets has largely been neglected n the lterature on performance measurement and mult-taskng, even though other streams of lterature consder target dffculty as an mportant determnant of effort choce (ocke and atham [2002], Webb, Wllamson, and Zhang [2013]). In the frst part of our study we develop an analytcal framework to model both the choce of relatve ncentve weghts and the choce of performance target dffculty when addressng mult-taskng ssues. Our model characterzes the relaton between ncentve weghts and target 1

4 dffculty n an equlbrum assurng both manageral retenton and optmal allocaton of effort. In the second part of our study, we test emprcal mplcatons of our model usng data on the choce of performance targets collected n two waves of onlne surveys admnstered n 2011 and n 2013 to members of the Amercan Insttute of Certfed Publc Accountants (AICPA) who are CEOs, CFOs, and other top managers at the corporate or busness unt levels. Our analytcal framework combnes nsghts from the tournament lterature as well as the lterature on mult-taskng (azear and Rosen [1981], olmström and Mlgrom [1991]). Specfcally, a rsk-neutral agent (manager) exerts effort on multple dmensons of performance whch can mperfectly be measured. The prncpal (frm) desgns a contract consstng of a fxed salary, a bonus opportunty, relatve ncentve weghts on multple performance measures, and performance targets determnng bonus payouts. Consstent wth the nsght of psychology-based research that optmal performance targets be nether too easy nor too dffcult (ocke and atham [2002]), we fnd that the desred level and allocaton of manageral effort can be elcted wth ether low (easy) or hgh (dffcult) targets. Although both types of targets are equally effectve n motvatng effort, the frm prefers dffcult targets when the manager s outsde employment prospects get weaker because downward adjustments to salary are costly. The emprcally testable mplcaton of our model s that optmal contracts put more ncentve weght on dffcult-to-acheve performance targets when retenton concerns are less mportant. Conversely, when retenton concerns are paramount, easy-to-acheve performance targets are more lkely to be weghted heavly n ncentve contracts. Thus, we predct that the assocaton between the lkelhood of achevng a target and the correspondng relatve ncentve weght s moderated by retenton concerns. 2

5 To test the predcton of our model, we collect extensve survey data on the choce of performance targets n annual bonus plans of 1,217 corporate and busness unt enttes. The typcal respondent s a fnancal executve from a small- or medum-sze prvate company who s elgble for an annual bonus but lttle or no long-term ncentve compensaton. We measure relatve ncentve weghts as the percentage of total bonus opportunty respondents can earn for meetng a performance target (ether a fnancal performance target or varous nonfnancal targets). To assess performance target dffculty, we ask respondents to estmate the lkelhood of achevng each of ther performance targets. Our emprcal analyss proceeds as follows. Frst, we provde novel descrptve evdence on how frms balance the dffculty of multple performance targets. We fnd that 55% of our sample enttes nclude only one performance target n ther bonus plans, 26% have two targets, 19% have three or more targets. We also show that performance targets vary n terms of ther dffculty easy targets n some areas are typcally combned wth dffcult targets n other areas. In partcular, we fnd that fnancal performance targets, whch on average account for the largest part of total bonus opportunty, are sgnfcantly more dffcult to acheve than non-fnancal performance targets. Second, we test our hypothess that the assocaton between the lkelhood of achevng a target and the correspondng relatve ncentve weght s moderated by retenton concerns. Our measure of retenton concerns reflects the extent to whch respondents beleve that retenton was the key objectve of ther bonus plan. We examne the assocaton between relatve ncentve weghts and perceved achevablty of fnancal performance targets (.e., one performance measure for each entty) for dfferent levels of retenton concerns. Consstent wth our theoretcal framework, we fnd that relatve ncentve weghts are postvely (negatvely) assocated wth the lkelhood of achevng targets when retenton concerns are hgh (low). 3

6 Our fndngs contrbute to pror lterature n a number of ways. Frst, although t s wellunderstood that the effectveness of compensaton contracts crtcally depends on the choce of performance targets (Murphy [2001], eone and Rock [2002], Anderson, Dekker, and Sedatole [2010]), there s very lttle theory and emprcal evdence on the economcs of target settng. Our study extends pror theoretcal work by explctly modellng the choce of performance targets. Moreover, our study uses one of the most comprehensve sources of data on target dffculty and relatve ncentve weghts avalable to date. Second, an extensve stream of pror work examnes how frms balance relatve ncentve weghts when they motvate managers to allocate effort among multple objectves (Feltham and Xe [1994], Ittner, arcker, and Rajan [1997], Core, Guay, and Verreccha [2003]). We extend ths lterature by provdng a theoretcal framework n whch msallocaton of effort arses not only f relatve ncentve weghts are unbalanced but also f performance targets are too easy or too hard on some dmensons. Thus, our study s the frst to consder target dffculty and relatve ncentve weghts as complementary performance measurement choces frms need to balance when addressng mult-taskng ssues. Fnally, we contrbute to pror lterature on compensaton choces that facltate manageral retenton. Smlar to pror work, our study suggests that ncentve provson s not the only goal of compensaton plans and that some ncentve choces can best be explaned by retenton concerns (Oyer [2004], Oyer and Schaefer [2005]). In contrast to much of pror work, our study focuses on the desgn of bonus plans as opposed to long-term equty compensaton plans (Ittner, ambert, and arcker [2003], Balsam and Mharjo [2007]). Our theory and emprcal evdence hghlghts that calbratng performance target dffculty s a flexble way to adjust expected compensaton to labor market fluctuatons. 4

7 2 Theory and ypotheses 2.1 PRIOR ITERATURE The broad popularty of performance measurement nnovatons such as the Balanced Scorecard (Kaplan and Norton [1996b], Kaplan and Norton [1996a]) has helped jump-start a trend towards redesgnng performance measurement systems to nclude not only standard measures of fnancal performance but also measures of nonfnancal performance such as market share or customer satsfacton (Neely [2002]). owever, many companes that started usng nonfnancal performance measures benefted from ther more comprehensve performance measurement systems only to a lmted extent (Ittner and arcker [2003]). These trends have ncreased the mportance of understandng how to choose performance measures and how to acheve balance n systems wth multple measures. The foundaton for much of the theoretcal work n ths area s olmström [1979] who shows that compensaton contracts should nclude all avalable performance sgnals that are ncrementally nformatve about manageral effort. Banker and Datar [1989] fnd that relatve ncentve weghts should be greater for measures that are relatvely more senstve to manageral effort and relatvely less nosy. A large stream of analytcal and emprcal lterature that follows bulds on these nsghts and examnes determnants of relatve ncentve weghts. Several analytcal papers hghlght that relatve ncentve weghts are ncreasng n performance measure congruty,.e., the extent to whch t helps algn the overall performance evaluaton wth the frm s goals (Feltham and Xe [1994], Datar, Kulp, and ambert [2001]), and decreasng n the extent to whch they are susceptble to nformaton asymmetry ssues (Baker [1992], Rath [2008]). A number of emprcal studes provdes evdence consstent wth the theoretcal results 5

8 (Ittner, arcker, and Rajan [1997], wang, Erkens, and Evans [2009], Indjejkan and Matějka [2012]). A separate stream of lterature hghlghts that ncentve compensaton n practce s contngent on performance relatve to a standard or target (Mlgrom and Roberts [1992], Murphy [2001]). owever, only a few theoretcal studes examne why compensaton contracts exhbt non-lneartes around some target levels and how frms should calbrate such target levels (Raju and Srnvasan [1996], Zhou and Swan [2003], Arnaz and Salas-Fumás [2008]). Emprcal studes suggest that performance targets are often hghly lkely to be acheved (Merchant and Manzon [1989]), performance relatve to target s serally correlated (Indjejkan and Nanda [2002], Indjejkan and Matějka [2006]), and performance targets are often ncreased followng favorable performance but rarely decreased followng unfavorable performance (eone and Rock [2002], Bouwens and Kroos [2011]). Thus, whle the former stream of economcs-based lterature emphaszes the mportance of relatve ncentve weghts but does not consder the choce of target levels, the latter stream of work examnes the choce of target levels but not n settngs wth multple performance measures. At the same tme, behavoral research n management control (e.g., Komns and Emmanuel [2007]) has long recognzed that manageral effort s a functon of both the magntude of extrnsc rewards (whch depend on ncentve weghts) and the probablty that rewards wll be acheved (whch depends on target levels). There s a broad consensus n ths lterature that targets should be dffcult but attanable. 1 1 For example, the expectancy theory predcts that manageral effort and performance ncrease n target levels up to a pont, after whch further ncreasng targets has a negatve effect on effort (Rockness [1977]). Also, studes motvated by the goal-settng theory document a postve relaton between performance and target dffculty up to a pont where the lmts of ablty were reached or when commtment to a hghly dffcult goal lapsed (ocke and atham [2002]: 706). 6

9 Fnally, whle the above lterature focuses on ncentve provson, a number of pror studes show that retenton concerns are also an mportant determnant of varous compensaton choces. Oyer [2004] argues that frms use some stock opton and proft sharng plans as a means of ndexng wages to market rates rather than to provde ncentves. Ittner, ambert, and arcker [2003] analyze data on compensaton practces n new economy frms and fnd that employee retenton ranks as the most mportant objectve of ther equty grant plans. Gao, uo, and Tang [2015] show that followng voluntary executve turnover frms dramatcally ncrease the value of equty-based grants to ther remanng executves. There s also evdence that restrcted shares and unvested stock opton grants reduce voluntary executve turnover and that frms commonly re-prce underwater stock opton grants to facltate retenton (Carter and ynch [2001], Chen [2004], Balsam and Mharjo [2007]). In the next secton, we combne nsghts from pror work and develop a model of target settng whch allows for a smultaneous choce of relatve ncentve weghts as well as target levels to motvate effort and assure retenton. We draw on the tournament lterature, poneered by azear and Rosen [1981], who provde the basc framework for the desgn of compensaton n settngs where agents compete aganst each other. Ray [2007] adapts the tournament model to a settng where a manager competes aganst a performance target set by the frm. Dahya and Ray [2012] employ a smlar model of performance targets n the context of venture captalsts fundng entrepreneurs n stages. All three models consder rsk-neutral agents, convex effort, and stochastc output. Ths paper extends ths work by allowng for multple performance measures, multple target levels, and multple perods. 7

10 2.2 TEORY Consder a rsk-neutral frm contractng wth a rsk-neutral manager who exerts effort e on multple dmensons, =1 m. The effort s unobservable but maps nto measurable dmensons of performance q e, where s a zero-mean nose term that s dentcally and ndependently dstrbuted across all performance dmensons. In partcular, has a contnuous dstrbuton functon G and symmetrc densty g such that g s ncreasng and G s convex only over ts negatve doman,.e., G 0 f and only f 0. Exertng effort ncreases gross frm profts V m vq but entals cost for the manager of 1 C m ce. 2 To compensate the manager for hs effort, the frm pays fxed salary s and performancecontngent bonuses wb, where b denotes the total bonus opportunty and w 0 s a weght representng the relatve mportance a performance dmenson such that m 1 w 1. The bonus payout wb s condtonal on meetng performance targets specfed as follows (see Fgure 1). Frst, the bonus s capped so that when performance meets or exceeds a maxmum performance target (.e., when q ), the manager earns wb for performance on dmenson. Second, when performance s below the maxmum but above a threshold (.e., when q ), the bonus s ncreasng and lnear n manager s performance. We refer to ths performance range as the ncentve zone and note that the mpled ncentve slope s wb ( ). Fnally, when performance s at or below the threshold ( q ), the manager earns no bonus. 2 2 Most companes use three levels of performance standards commonly referred to as the threshold, target, and maxmum, where the target s typcally the mdpont of the target range (e.g., Murphy [2001], Merchant, Strnger, and Shantapryan [2015]). As a smplfcaton, we ntroduce only the threshold and the maxmum n our notaton. Nevertheless, our results hold for all three levels of performance standards because the target s a lnear combnaton of the threshold and the maxmum. 8

11 The manager accepts the contract only f hs total expected utlty s weakly greater than hs reservaton utlty u. After acceptng the contract, the manager decdes how much effort to exert to maxmze hs expected utlty. The followng results descrbe the optmal choce of effort and propertes of performance targets (all proofs are n Appendx A). EMMA 1. The manager s optmal effort s characterzed by: wb e [ G( e ) G e ]. * * * ( ) c emma 1 presents the ncentve constrant that the optmal contract has to satsfy to (IC) motvate effort choce e. Obvously, hgher effort on dmenson can be ncentvzed by hgher bonus wb,.e., ether by ncreasng the bonus opportunty b or by ncreasng the weght w on performance dmenson. More nterestngly, emma 1 shows how effort depends on targets. The manager chooses effort so that ts margnal benefts equal margnal costs. If performance ends up n the ncentve zone, whch happens wth probablty G( e) G e margnal benefts of effort are ncreasng n the ncentve slope n Fgure 1, wb ( ). The ncentve constrant (IC) combnes the margnal benefts of effort n the ncentve zone and the fact that the margnal benefts are zero outsde of the ncentve zone. EMMA 2. For gven w, b, and c, f optmal effort e can be mplemented wth a hgh target range, the e, then the same effort can also be mplemented wth a low target range e. emma 2 hghlghts that the frm can equvalently use two types of contracts one wth a low target range (and hgh expected bonus) and one wth a hgh target range (and a low expected bonus). Ther equvalence follows from the symmetry of the dstrbuton functon as llustrated n Fgure 2. If both target ranges have the same wdth of the ncentve zone ( ), then the ncentve slope and the probablty of performance endng up n the ncentve zone 9

12 ( G( e) G( e) G( e) G( e)) wll also be the same. The (IC) then mples that both ranges mplement the same effort. EMMA 3. The relatve ncentve weght on performance dmenson and performance targets n the hgh (low) target range are complements (substtutes): () w 0, / w 0 and () w 0, / w 0. emma 3 shows that the hgh and low target ranges have dfferent mplcatons for the choce of optmal weghts w, even though they mplement the same effort. Frst, consder the low target range (, ). Shftng the whole range to the rght ncreases effort because t ncreases the ncentve slope and the probablty of performance endng up n the ncentve zone (gven that the dstrbuton functon G s steepest around zero). At the same tme, the (IC) shows that effort s ncreasng n the ncentve weght w. Thus, ncreasng the ncentve weght and ncreasng the low target range are substtute nstruments n motvatng effort; the frm can ncrease one and lower the other and the equlbrum effort stays the same. Second, consder the hgh target range (, ). Shftng the hgh target range even further to the rght reduces effort because t decreases the ncentve slope and the probablty of performance endng up n the ncentve zone. Therefore, n ths case, both ncentve nstruments are complements shftng the hgh target range to the rght has to be accompaned by a hgher ncentve weght to keep the equlbrum effort unchanged. Fnally, note that the choce of low versus hgh target ranges has mplcatons for the amount of fxed salary the frm has to offer n the optmal contract. Gven that the partcpaton constrant always bnds, the choce of low target range (easy-to-acheve targets) mples hgher expected bonuses and therefore a lower fxed salary. Ths dfference s mportant n settngs 10

13 where adjustments to salary are costly (e.g., frms may be concerned about salary rases because they are dffcult to reverse). 3 In such settngs, favorable labor market opportuntes and hgh reservaton utlty wll go together wth easy-to-acheve targets on some or all performance measures. Combnng ths nsght wth emma 3 yelds the followng proposton. PROPOSITION 1. When salary adjustments are costly, ncreasng the manager s reservaton utlty, u, ncreases the proporton of performance measures for whch t holds that the ncentve weght and the correspondng target dffculty are substtutes. For a suffcently hgh (low) u, the ncentve weght and target dffculty are substtutes (complements) for all performance measures. 2.3 EMPIRICA IMPICATIONS The key takeaway from our model s that performance targets facltate both ncentve provson and retenton of managers. In the former role, targets nfluence how much effort managers exert and how they allocate t across dfferent tasks. Ths role calls for targets that are nether too hard nor too easy and target dffculty that s balanced across tasks. In the latter role, targets assure that total expected compensaton s on par wth other labor market opportuntes. The retenton role s partcularly mportant when labor market opportuntes fluctuate and salary adjustments are costly (Bewley [1999]). Our model mples that frms can motvate the same overall effort as well as the same allocaton of effort across dfferent tasks by usng ether relatvely dffcult targets or easy targets. Nevertheless, as labor markets get stronger and managers reservaton utlty ncreases, frms are more lkely to opt for easy targets. Ths facltates retenton because easer targets 3 For example, there s an extensve labor economcs lterature on downward salary rgdty (e.g., Campbell and Kamlan [1997], Fehr and Goette [2005], all [2005]). 11

14 ncrease expected ncentve compensaton even f salares reman largely unchanged. Our model also shows that ncentve weght and target dffculty are substtutes when targets are easy n that makng easy targets even more achevable has to be accompaned by hgher relatve ncentve weght to avod a reducton n effort. The emprcally testable mplcaton s that when frms are greatly concerned about retenton of ther managers, the lkelhood of achevng a target and the correspondng relatve ncentve weght are postvely assocated. Conversely, our model mples that when labor market opportuntes get weaker and retenton concerns are less mportant, the lkelhood of achevng a target and the relatve ncentve weghts are negatvely assocated. Ths s because decreases n reservaton utlty allow frms to swtch from easy to dffcult targets,.e., to decrease expected ncentve compensaton wthout changng overall effort or ts allocaton across dfferent tasks. Moreover, ncreasng a dffcult target, or equvalently makng the lkelhood of achevng t even lower, has an effortreducng effect that needs to be balanced by hgher ncentve weghts. In the remander of the paper we test our hypothess that retenton concerns moderate the assocaton between target dffculty and relatve ncentve weghts. In partcular, we expect both ncentve choces to be complements when retenton concerns are weak, but to be substtutes when retenton concerns are strong. 3 DATA 3.1 SURVEY DATA COECTION We use data from two surveys of selected members of the AICPA launched n March 2011 and March The surveys targeted AICPA members workng n ndustry n one of the followng postons: CEO, CFO, COO, controller, VP fnance, presdent, managng drector, or manager. Respondents partcpated anonymously and were assured confdental treatment of 12

15 nformaton collected about ther compensaton, performance targets, and other ndvdual and company characterstcs. Casas-Arce, Indjejkan, and Matějka [2013] use aggregated data from the 2011 survey and descrbe the survey admnstraton procedures n more detal. 4 In total, 3,353 respondents partcpated n both surveys, 999 n 2011 and 2,354 n We exclude nonproft enttes and those wth less than $10 mllon n sales. In addton, we requre non-mssng data on the dffculty of performance targets, relatve ncentve weghts, and a number of entty characterstcs used as control varables. Fnally, we exclude enttes where we fnd no evdence of objectve fnancal or nonfnancal targets,.e., where annual bonuses are determned n an entrely subjectve manner. These extensve selecton requrements reduce the fnal sample sze to 1,217 enttes. 3.2 MEASURES In ths secton, we defne measures of all constructs used n the emprcal analyss. A detaled descrpton of relevant survey tems s n Appendx B. A summary of all constructs and ther defnton s n Table Insert Table Relatve ncentve weghts. We collect nformaton on pror years (.e., 2010 and 2012) annual base salary (SAARY) and current target bonus (BONUS). Target bonus s defned as the annual bonus expected f current-year performance (n 2011 and 2013) meets targets on all performance measures. We measure relatve ncentve weghts by askng respondents about the percentage of BONUS contngent on: (a) fnancal performance targets, (b) hgher-level fnancal 4 Admnstraton of the 2013 survey followed largely the same procedures as n owever, one dfference was that the 2013 survey collected data on respondents geographcal locaton and offered partcpants a feedback report on compensaton desgn ncludng a tool to benchmark CFO compensaton by metropoltan areas. The tool was a new feature that generated a great nterest n the survey and consderably ncreased the number of respondents n 2013 relatve to

16 targets n case of BU-level enttes, (c) nonfnancal performance targets, (d) performance evaluated subjectvely, and (e) other factors. Respondents can descrbe ther nonfnancal targets n detal or classfy them nto sx predefned categores: operatons, customers & strategy, accountng & nformaton systems, fnancng, transactons & nvestor relatons, teamwork, and sustanablty. We manually reclassfy open responses nto one of the sx categores. 5 We use a seventh category ( Unclassfed objectve nonfnancal targets ) when respondents provde no addtonal nformaton about ther nonfnancal targets. Weghts (a) (e), ncludng the breakdown of (b) nto more detaled categores, add up to 100%. In our emprcal analyss, we use WEIGT to denote any of the (a) (e) weghts, although n the man estmaton sample WEIGT refers to the percentage of target bonus contngent on fnancal performance targets. Target dffculty. We measure target dffculty by askng: ow lkely s t that you wll meet [2011 or 2013] bonus targets? 6 PROB s the percentage (0 100%) respondents report as the estmated lkelhood of achevng ther earnngs target, other fnancal targets, and nonfnancal targets (for each of the seven categores of nonfnancal targets as long as ther relatve ncentve weght s greater than zero). In our man estmaton sample PROB refers to the lkelhood of achevng fnancal performance targets, whch we calculate as the average of the lkelhood of achevng earnngs targets and the lkelhood of achevng other fnancal targets. Although we cannot drectly valdate PROB n ths study, there s panel-data evdence that a smlar measure of ex-ante achevablty of fnancal targets s hghly correlated wth ex- 5 The followng are examples of performance measures ncluded n the sx categores: operatons qualty, process mprovement metrcs; customers & strategy customer satsfacton, market share; accountng & nformaton systems ERP mplementaton, absence of audt ssues; fnancng, transactons & nvestor relatons capex plannng, M&A related actvtes; teamwork employee turnover, leadershp; sustanablty energy use, emssons. 6 To address the ssue of multple target levels, the survey queston adds the followng explanaton: Bonus target refers to the performance level that earns you the full targeted bonus (as opposed to some mnmum performance level below whch no bonuses are pad or some maxmum performance level at whch bonuses may be capped). 14

17 post success n meetng those targets. Specfcally, Mahlendorf, Matějka, and Schäffer [2015] collect data on target dffculty n four consecutve annual surveys by askng: ow lkely s that your [entty] wll meet the [current year] budgeted proft/loss? They fnd that responses to ths queston strongly predct the actual success/falure n meetng the current-year budgeted earnngs measured by the next-year s survey. Retenton concerns. We measure whether companes are concerned about retenton of ther executves as the extent to whch respondents agree wth the followng statement: Retenton of executves s the key objectve of our [2011 or 2013] bonus plan. RETAIN collects responses on a fve-tem fully-anchored kert scale; hgher values ndcate greater retenton concerns after reverse codng. To valdate RETAIN as a measure of outsde labor market opportuntes, we collect external data on local labor market characterstcs from the followng two publc sources. Frst, we obtan data on average compensaton of Busness and fnancal operatons occupatons by metropoltan areas from the Bureau of abor Statstcs. 7 Second, we obtan cost-of-lvng data by metropoltan areas from the Census Bureau. 8 Our 2013 survey collects data on respondents zp codes and/or locaton n top 20 U.S. metropoltan areas, whch allows us to match SAARY and RETAIN data to both external proxes for labor market opportuntes. The premse of our model s that salares adjust to outsde labor market opportuntes mperfectly and thus, when the local labor market s strong, retenton s an mportant objectve of bonus plans. Consstent wth our model, we fnd that SAARY s sgnfcantly correlated wth both external proxes for labor market opportuntes (r=.114, p<.001 and r=.155, p<.001) but at the same tme does not fully 7 See the Natonal Compensaton Survey avalable from 8 Cost of vng Index--Selected Urban Areas s a part of the 2012 Statstcal Abstract and can be downloaded from the Census Bureau s webste: 15

18 adjust for dfferences n local labor markets. 9 In partcular, we fnd that above average scores on RETAIN, ndcatng concerns about retenton, are assocated wth sgnfcantly hgher average compensaton n the same metropoltan area (p=.023) as well as wth a sgnfcantly hgher costof-lvng ndex (p=.010). Thus, although RETAIN s a nosy measure, t does reflect concerns about retenton due to alternatve labor market opportuntes. Control varables. PUBIC s an ndcator varable for corporate-level respondents n publcly lsted companes, PUBIC_BU represents busness unts of publc companes, PRIVATE_BU represents busness unts of prvate companes. ROS measures proftablty n terms of return on sales or last year s earnngs dvded by sales. FAI s an ndcator for falure to meet last year s earnngs target. SIZE s the log of the number of employees. GROWT s the response to a fve-pont fully-anchored kert scale askng respondents to characterze the longterm prospects of ther entty n terms of expected annual sales growth; t ranges from one ( Negatve growth) to fve ( More than 20% growth). CAPITA s the response to a fve-pont fully-anchored kert scale ndcatng agreement wth the statement that Our [entty] has adequate (access to) captal for the near term; t ranges from one ( Strongly agree ) to fve ( Strongly dsagree ). NOISE s the response to a fve-tem fully-anchored kert scale about the extent to whch fnancal performance measures reflect management s overall performance. After reverse codng, hgher values ndcate that fnancal performance measures poorly reflect manageral performance. Fnally, we use 18 ndcator varables to control for ndustry effects. 9 For the purposes of ths valdaton analyss we use all avalable observatons from the 2013 survey but no observatons from the 2011 survey, whch dd not yet collect data on locaton of respondents. The resultng valdaton sample sze ranges between 1,212 and 1,395 dependng on the assocaton among the four varables (SAARY, RETAIN, and both external proxes). 16

19 3.3 DESCRIPTIVE STATISTICS Table 2 presents descrptve statstcs for our man estmaton sample. Of the total of 1,217 observatons, 877 (72%) are from the 2013 survey and the remander are from Most of our respondents (70%) are from prvate corporate-level enttes; the remander are from publc companes (15%), busness unts of publc companes (9%), or busness unts of prvate companes (6%). CFOs comprse 68% of the sample, CEOs an addtonal 7%, and most of the remanng 25% are fnancal executves drectly reportng to a CFO. --- Insert Table A large majorty of our sample s proftable, and the nter-quartle range of ROS s 2 13%. Most enttes (61%) also met last year s earnngs target, whle earnngs were below target for 39% of the sample. The medan entty has sales of $100 mllon and 300 employees; the means are much hgher, reflectng skewness n the sze measures. The nterquartle range for SIZE (unlogged) s 113 1,000 employees. The average and medan of GROWT s around the md-pont of the scale, ndcatng average annual growth of 6 12%. A large majorty of the sample has adequate access to captal for the near term as reflected n the low mean and medan values of CAPITA. The average and medan of NOISE s around two, suggestng that most respondents beleve that fnancal performance measures reflect manageral performance to a hgh extent. Fnally, RETAIN has mean and medan around the md-pont of the scale and the largest varance of all constructs measured by kert scales, ndcatng that our sample enttes vary greatly n the extent to whch retenton concerns are mportant when desgnng annual bonus plans. 17

20 Table 2 also provdes descrptve data on executve compensaton. On average, respondents earn $192,718 n salary and $92,837 as a bonus f performance meets all targets. 10 Earnngs and other fnancal performance targets account, on average, for about 65% of the target bonus, although there s consderable varaton as reflected n the nterquartle range of %. The average estmated lkelhood of achevng these fnancal performance targets s 69% and also vares wdely as reflected n the nterquartle range of 50 90%. Table 3 descrbes other performance targets ncluded n annual bonus plans. The frst two columns of Panel A tabulate the dstrbuton of the number of performance targets used. Our sample selecton crtera requre at least one objectve target, whch could be ether fnancal or nonfnancal. Of the 1,217 sample enttes, 675 (55%) have one objectve target, 26% have two targets, 9% have three targets, and the remanng 10% use four or more targets. --- Insert Table Panel A of Table 3 further shows that the average lkelhood of achevng performance targets (PROB_a) s around 72% n enttes wth one to three performance targets and slghtly hgher at 76% n enttes wth four or more performance targets. For the results n columns four and fve, we rank the lkelhood of achevement for all targets and select the lowest (PROB_l) and hghest values (PROB_h). We fnd that target achevablty ranges from a low of 67% to a hgh of 79% n enttes usng two targets. In enttes wth three (four) targets, the range s 61 84% (65% 86%). Thus, although ncreasng the number of performance targets does not necessarly reduce average target dffculty, t does greatly ncrease the varance n performance 10 Casas-Arce, Indjejkan, and Matějka [2013] report that annual bonus plans are by far the most mportant ncentve nstruments among the respondents n smlar surveys and mult-year bonus plans or equty plans are not common. As a robustness check, we report n Secton IV that excludng observatons wth non-zero long-term ncentve compensatons yelds qualtatvely smlar results. As a lmtaton of our study, we acknowledge that we do not have nformaton about other potentally mportant compensaton components such as retrement plans, benefts, or perks. 18

21 target dffculty. In other words, performance targets n annual bonus plans vary n terms of ther dffculty easy targets n some areas typcally go together wth dffcult targets n other areas. Fnally, the last four columns n Panel A of Table 3 compare enttes wth dfferent number of performance targets n terms of ther characterstcs. We fnd that annual bonus plans nclude a greater number of performance targets when companes are larger, more proftable, and when executve compensaton s greater. Panel B of Table 3 compares relatve ncentve weghts and target dffculty n dfferent areas. As dscussed earler, on average, 65% of target bonuses s contngent on meetng fnancal performance targets. Panel B further shows that 14% s contngent on nonfnancal targets, 16% s determned subjectvely, 3% relates to hgher-level targets n busness unts, and 2% s determned n some other way (e.g., guaranteed bonuses). The 14% ncentve weght on nonfnancal targets s further dsaggregated nto the seven more specfc categores. The two most mportant categores are operatons targets (4%) and customer & strategy targets (3%). The last two columns of Panel B compare the dffculty of fnancal and nonfnancal performance targets. The average lkelhood of achevng fnancal performance targets s 69% as compared to 75% for nonfnancal targets related to operatons, 73% for customer & strategy targets, 77% for accountng and nformaton systems targets, 79% for fnancng, transactons & nvestor relatons targets, 79% for teamwork targets, 78% for sustanablty targets, and 68% for unclassfed nonfnancal targets. Although ths comparson suggests that fnancal targets are on average more dffcult to acheve than nonfnancal targets, t does not hold the sample constant because dfferent enttes use dfferent targets. 11 To test for a dfference n target dffculty, we 11 For example, achevablty of sustanablty targets (78%) appears hgher than the sample average for fnancal targets (69%). owever, the small sample of companes usng some sustanablty targets happens to have fnancal targets that are even more achevable (83%) than sustanablty targets. 19

22 calculate DPROB as the dfference between achevablty of a nonfnancal target and achevablty of fnancal targets n the same entty. The last column of Panel B shows that, except for customer & strategy and sustanablty targets, all other types of nonfnancal targets are sgnfcantly less dffcult to acheve than fnancal performance targets. 4 Emprcal Results 4.1 TESTING FOR COMPEMENTARITY Our theory predcts a relaton between two endogenous choces, the relatve ncentve weght (WEIGT) and achevablty of performance targets (PROB). Consstent wth pror lterature on testng of complementartes n organzatonal desgn choces (Aral, Brynjolfsson, and Wu [2012], Indjejkan and Matějka [2012], Grabner and Moers [2013]), we estmate the followng seemngly unrelated regressons (SUR) model (Zellner [1962]): PROB ROS FAI SIZE GROWT CAPITA NOISE WEIGT ROS FAI SIZE GROWT CAPITA NOISE (1) We also nclude controls for the type of entty as well as year and ndustry effects. Estmaton of the SUR model yelds cross-equaton correlaton of the error terms 1 and 2 whch reflects complementarty between the dependent varables or ther covarance condtonal on a set of company characterstcs (Arora and Gambardella [1990], Arora [1996]). To take nto account that the correlaton may vary dependng on RETAIN, as predcted by our hypotheses, we separately estmate the SUR model n subsamples wth low and hgh RETAIN values. An alternatve approach s to assume that relatve ncentve weghts change less frequently than the annually re-calbrated target dffculty, so that WEIGT s to some extent pre-determned for the choce of PROB. Ths alternatve approach does not requre splttng the 20

23 sample based on RETAIN values and allows for a drect estmaton of the moderatng effect of RETAIN on the relaton between WEIGT and PROB: PROB ROS FAI SIZE GROWT CAPITA NOISE RETAIN 8WEIGT 9 RETAIN WEIGT, (2) where we agan nclude controls for the type of entty as well as year and ndustry effects. We also take nto account that the dstrbuton of the dependent varable has a probablty mass at both 0% and 100% and estmate (2) as a Tobt model wth two corner values (Wooldrdge [2002]). For ease of presentaton, the followng secton frst presents the Tobt estmates of model (2) and subsequently the estmates of the SUR model n (1) to corroborate that the results do not hnge on the assumpton that ncentve weghts are predetermned. 4.2 YPOTESES TESTS Column (I) of Table 4 presents the Tobt estmates of model (2) usng our man estmaton sample whch only ncludes fnancal performance targets. Ths s motvated by Proposton 3 predctng that the dfference between hgh and low targets s greater for publc than for non-publc performance measures. Another advantage of the sample s that t ncludes only one observaton per entty and thus avods ssues arsng because ncentve weghts and targets from the same entty are not ndependent. Nevertheless, we also use an alternatve estmaton sample that ncludes all performance targets wth a non-zero ncentve weght. Column (II) of Table 4 presents the results based on ths alternatve sample and reports standard errors clustered by entty to account for the fact that enttes can have multple performance targets. --- Insert Table

24 Table 4 shows no sgnfcant year effect,.e., the average lkelhood of achevng performance targets n 2011 s about the same as n There s also no strong varaton n target achevablty across dfferent types of enttes except that corporate-level respondents from prvate companes have weakly easer targets than all other respondents. In Column (II), we fnd that fnancal performance targets are on average more dffcult to acheve than nonfnancal performance targets (p<.001) durng the sample perod. Gven that all other results n Column (II) are smlar to those n Column (I), we further dscuss only the latter. Consstent wth pror lterature (Indjejkan and Nanda [2002], Indjejkan and Matějka [2006]), we fnd that past performance s an mportant determnant of target dffculty. Specfcally, the lkelhood of achevng a target (PROB) s postvely assocated wth last year s proftablty as measured by ROS (p=.014) and negatvely assocated wth falure to meet last year s earnngs target (p<.001). As n Indjejkan, Matějka, Merchant, and Van der Stede [2014], we also fnd that targets are easer to acheve n enttes that are larger (p=.004), grow faster (p=.001), and are suffcently captalzed (p=.100). Addtonally, we fnd that fnancal targets are easer to acheve when they are perceved as less nosy or more reflectve of manageral effort (p=.012). The focus of ths study s how the assocaton between PROB and WEIGT s moderated by retenton concerns. Gven the dffculty of nterpretng nteracton effects n non-lnear models (A and Norton [2003]), we do not dscuss the actual estmates n Column (I) of Table 4 but rather use them to calculate the predcted values and margnal effects presented n Table 5. Panel A of Table 5 shows the predcted values of target achevablty (PROB) for dfferent values of WEIGT and RETAIN. As predcted, when retenton concerns are low, ncreasng ncentve weght on fnancal performance targets from 50% to 100% of target bonus s assocated wth a 22

25 decrease n ther achevablty from an estmated lkelhood of success of 71% to 64%. Conversely, when retenton concerns are hgh, the same ncrease n ncentve weght s assocated wth an ncrease n the lkelhood of success from 71% to 84%. --- Insert Table Panel B of Table 5 tests whether the assocaton between PROB and WEIGT s sgnfcantly dfferent from zero for gven values of retenton concerns. Consstent wth the results n Panel A of Table 5, when RETAIN equals one, there s a negatve assocaton between WEIGT and PROB (p=.022). Conversely, when RETAIN equals three or more, the assocaton s sgnfcantly postve. Fnally, Panel C of Table 5 examnes the assocaton between PROB and retenton concerns. We fnd that the assocaton s sgnfcantly postve for sample enttes wth medan or hgher ncentve weght on fnancal performance targets (70% or more). As dscussed earler, a more general approach to test for complementarty between ncentve weghts and target achevablty s to estmate the SUR model n (1). Table 6 presents the results of ths estmaton for subsamples wth RETAIN lower (greater) than the md-pont of the scale. Frst, we dscuss the results pertanng to target achevablty and how they compare to the full-sample fndngs n Column (I) of Table 4. We fnd several effects that are consstently sgnfcant regardless of the sample choce the lkelhood of achevng a target s ncreasng n past performance (return on sales and success n meetng earnngs target) and decreasng n the nosness of fnancal performance targets. Other effects from the full-sample analyss, pertanng to lstng status, sze, and growth, seem to be drven prmarly by enttes where concerns about retenton of executves are low. --- Insert Table

26 Second, we dscuss the results pertanng to the determnants of ncentve weghts. We fnd that the relatve ncentve weght on fnancal performance targets s lower n busness unts as compared to corporate-level enttes because they commonly put some weght on hgher-level fnancal results whch are not ncluded n WEIGT. We also fnd, at least n the low retenton concerns sample, that the weght on fnancal performance targets s lower when they are noser, whch s consstent wth much of the pror lterature (Banker and Datar [1989], Ittner, arcker, and Rajan [1997]). Most mportantly, after controllng for the above effects as well as all other year and ndustry effects, we fnd that the condtonal correlaton between PROB and WEIGT s negatve n the low-value sample (r=-.091; p=.058) and postve n the hgh-value sample (r=.176; p<.001). Ths s consstent wth the results n Tables 4 and 5 and our theory that retenton concerns nduce a postve relaton between ncentve weghts and the lkelhood of achevng a target. 4.3 ROBUSTNESS TESTS The man estmaton sample n Tables 4 6 maxmzes the power of our tests by poolng dfferent respondents, dfferent types of enttes, and dfferent types of ncentve plans. Ths secton assesses the robustness of our man fndngs by re-estmatng our results n smaller subsamples of enttes wth smlar characterstcs. Frst, we re-estmate Column (I) of Table 4 n subsamples restrcted to: () prvate enttes (n=922), () corporate-level enttes (n=1,037), () respondents who are ether CFOs or fnancal executves reportng drectly to CFOs (n=1,062), and (v) the ntersecton of () () ncludng only corporate fnancal executves from prvate companes (n=754). In all four subsamples, we fnd results (untabulated) smlar to those n Table 4. 24

27 Second, we splt the man estmaton sample from Table 4 nto two subsamples of about the same sze based on the magntude of the target bonus. Specfcally, we consder subsamples wth target bonuses at or above (below) 30% of annual salary as well as subsamples wth target bonuses at or above (below) $50,000. Agan, n all four subsamples, we fnd results (untabulated) smlar to those n Table Insert Table Fnally, we exclude observatons where respondents are elgble for long-term ncentve compensaton. Column (I) of Table 7 excludes observatons wth an equty grant or long-term cash bonus equal to or greater than 15% of annual salary (the lowest quartle n the subsample of observatons wth non-zero long-term ncentve compensaton). Column (II) excludes observatons wth an equty grant or long-term cash bonus of $25,000 or more (the lowest quartle). Fnally, Column (III) only retans observatons wth no long-term ncentve compensaton. In all three columns of Table 7, we fnd that the extent to whch the assocaton between PROB and WEIGT s moderated by retenton concerns s smlar to, or even stronger than, the results n Table 4. 5 Dscusson and Conclusons Pror theoretcal and emprcal work examnes how frms balance tradtonal fnancal measures of performance wth forward-lookng nonfnancal measures to prevent managers from myopcally focusng on short-term results. It s well-understood that the choce of relatve ncentve weghts determnes how managers prortze among varous short-term and long-term objectves. Our study extends ths lterature by pontng out that balancng relatve ncentve weghts alone s not suffcent to motvate a desred allocaton of manageral effort. We provde 25

28 theory and emprcal evdence that frms need to jontly balance relatve ncentve weghts and relatve target dffculty. Our man fndngs suggest that ncentve weghts and target dffculty can act ether as complements or substtutes n motvatng effort, dependng on the mportance of retenton objectves n compensaton desgn. Specfcally, when managers have weak outsde employment opportuntes and retenton objectves are less mportant, frms can economze on ncentve payouts by settng performance targets to be relatvely dffcult to acheve. As a consequence, target dffculty and ncentve weghts are complementary choces n ncentves desgn ncreasng the dffculty of a target that s already dffcult-to-acheve has an effort-reducng effect, whch can be offset by ncreasng the relatve ncentve weght on that dmenson. Conversely, when frms are greatly concerned about manageral retenton, they set performance targets to be relatvely easy to acheve. As a consequence, target dffculty and ncentve weghts act as substtutes ncreasng the dffculty of a relatvely easy-to-acheve target has an effortncreasng effect, whch can be offset by decreasng the relatve ncentve weght. Thus, our study s one of the frst to suggest that relatve ncentve weghts and target dffculty are complementary compensaton desgn choces that are made smultaneously to nfluence manageral allocaton of effort. Ths nsght mproves our understandng of what consttutes a balanced performance measurement system. For example, t explans why managers may focus on short-term fnancal results despte ncreases n ncentve weghts on nonfnancal performance measures. If greater ncentve weghts on nonfnancal measures go together wth targets are too easy (or too dffcult) to acheve, then manageral focus on short-term fnancal results may reman unchanged or even ncrease. 26