BANKING REGULATION AND PROMPT CORRECTIVE ACTION

Size: px
Start display at page:

Download "BANKING REGULATION AND PROMPT CORRECTIVE ACTION"

Transcription

1 BANKING REGULATION AND PROMPT CORRECTIVE ACTION XAVIER FREIXAS BRUNO M. PARIGI CESIFO WORKING PAPER NO CATEGORY 6: MONETARY POLICY AND INTERNATIONAL FINANCE NOVEMBER 2007 PRESENTED AT CESIFO AREA CONFERENCE ON APPLIED MICROECONOMICS, MARCH 2007 An electronc verson of the paper may be downloaded from the SSRN webste: from the RePEc webste: from the CESfo webste: Twww.CESfo-group.org/wpT

2 CESfo Workng Paper No BANKING REGULATION AND PROMPT CORRECTIVE ACTION Abstract We explore the ratonale for regulatory rules that prohbt banks from developng some of ther natural actvtes when ther captal level s low, as eptomzed by the US Prompt Correctve Acton (PCA). Ths paper s bult on two nsghts. Frst, n a moral hazard settng, captal requrement regulaton may force banks to hold a large fracton of safe assets whch, n turn, may lower ther ncentves to montor rsky assets. Second, agency problems may be more severe n certan asset classes than n others. Taken together, these two deas explan why, surprsngly, captal regulaton, whch may cope wth rsk and adverse selecton, s unable to address ssues related to moral hazard. Hence, nstead of forcng banks to hold a large fracton of safe assets, prohbtng some types of nvestment and allowng ample scope of nvestment on others may be the only way to preserve ncentves and guarantee fundng. In partcular, provdng ncentves to montor nvestments n the most opaque asset classes may prove to be excessvely costly n terms of the requred captal and thus neffcent. We show that the optmal captal regulaton conssts of a rule that a) allows well captalzed banks to freely nvest any amount n any rsky asset, b) prohbts banks wth ntermedate levels of captal to nvest n the most opaque rsky assets, and c) prohbts undercaptalzed banks to nvest n any rsky asset. JEL Code: E58, G21. Keywords: bankng, prudental regulaton, moral hazard. Xaver Frexas Department of Economcs and Busness Unversty Pompeu Fabra Ramon Tras Fargas Barcelona Span xaver.frexas@econ.upf.es Bruno M. Parg Department of Economcs Unversty of Padova Va del Santo Padova Italy brunomara.parg@unpd.t October 19, 2007

3 1. Introducton The am of ths paper s to understand the logc behnd the US bankng regulaton called Prompt Correctve Acton (PCA). PCA was ntroduced n 1991 by the Federal Depost Insurance Corporaton Improvement Act (FDICIA) n response to the bankng crses of the 1980s to ntegrate captal regulaton wth the man goal to preclude supervsory forbearance (Calem and Rob 1999). The defnton of banks permtted range of actvtes s tradtonally part of bank regulaton. What s orgnal about PCA s that t places mandatory restrctons on bank s actvtes dependng on captal ratos. 1 Banks are classfed n 5 categores dependng on (varous measures of) captal ratos: for example, well captalzed, wth captal rato (total rsk-based captal) 10%; Adequately captalzed 8%; Undercaptalzed < 8%; Sgnfcantly Undercaptalzed < 6%; Crtcally Undercaptalzed 2% of tangble equty. Well captalzed and adequately captalzed banks face no restrctons; banks n the three bottom categores face restrctons whch become more and more severe the lower ther captal ratos. Examples of the restrctons to banks actons are: lmts to dvdends payments and compensaton to senor managers; ncreased montorng; restrctons to asset growth; restrctons to nterafflate transactons; requred authorzaton for acqustons and new busness lnes; requred authorzaton to rase addtonal captal; lmts to credt for hghly leveraged transactons; and n the most extreme cases, recevershp. A key aspect of PCA s that t specfes a mx of dscretonary and mandatory provsons for nsttutons n each category rather than relyng only on regulatory dscreton (Benston and Kaufman 1997). In a context where the scope of bankng actvtes has been expandng, wth the repeal of the Depresson-era bankng legslatons both n the US and n some European countres, banks engage n a wder range of actvtes, and bankng operatons growng n complexty due to fundamental 1 Here we ust sketch the man features of PCA. For a detaled descrpton of ts functonng we refer to e.g. Jones and Kng (1995) and Benston and Kaufman (1997).

4 changes n the fnancal ndustry, the ssue of the benefts of a PCA-type of legslaton n countres outsde the US s tmely and relevant, from the perspectve both of prudental regulaton and of the effcency of the bankng ndustry. Introducng regulaton smlar to PCA s complex, as t requres an mportant amendment both to the bankruptcy code and to the law delegatng powers to the regulator. Wth the exstng law ts mplementaton s mpossble n Europe and n the maorty of countres, and t s not part of Basle s Core Prncples for Effectve Bankng Supervson. Yet, the benefts of PCA seem to be mpressve, as ndvdual bank crses are replaced by low cost open-bank resoluton. Thus, understandng the cost-beneft analyss of PCA and assessng whether ths pece of regulaton should be exported to other countres has been a key motvaton of our research. Snce there s no model of the mpact of PCA, the obectve of ths paper s to develop a model that allows us to dentfy and assess the effects of PCA. Although ntutvely the benefts of PCA are obvous, ts modellng may be challengng. Indeed, t may seem reasonable, prma face, to restrct a bank s rsky actvtes as ts captal s depleted. But to acheve that goal the standard captal regulaton wth approprate rsk weghts should suffce. So, the ssue s more nvolved and requres a careful dstncton between rsk and asymmetrc nformaton. The novelty of our analyss stems from the observaton that the complexty of many bank s nvestments per se, ndependently from rsk, s a source of agency problems that cannot be addressed solely by means of quanttatve captal regulaton; nstead a combnaton of qualtatve and quanttatve restrctons succeeds n provdng effcent regulaton. Thus, our approach goes beyond the vew that ustfes captal as a buffer aganst losses and hence falure (Dewatrpont and Trole 1994). It also departs from the vew that captal lowers rsktakng (Rochet 1992) and algns the ncentves of bank owners wth those of depostors and other 2

5 credtors. These vews consttute the core of what we see as the tradtonal approach, even f there mght be dssentng perspectves. 2 Although from a completely dfferent standpont, our paper shares wth Calem and Rob (1999) the result of establshng the lmtatons of captal regulaton. Calem and Rob fnd that the amount of rsk a bank takes depends on ts level of captal, wth the most severely undercaptalzed banks takng on maxmal rsk. As captal ncreases banks take less rsk, and as captal rses further banks take more rsk. Calem and Rob (1999) argue that ths U-shaped relatonshp between captal poston and rsk-takng s a serous drawback to the usefulness of captal regulaton, and that nstead t provdes a ratonale for the PCA provson of FDICIA. A recent strand of theoretcal and emprcal lterature on the role of captal n banks makes two ponts that are qute relevant for our analyss: frst, market forces exert a promnent nfluence on bank leverage decsons; second, ths lterature challenges the assumpton that banks holds as lttle captal as possble. In partcular two studes have noted that captal ratos are strategc varables n bank competton. Km et al. (2005) usng a sample of Norwegan banks show that banks can use captal ratos to dfferentate ther servces and soften competton. Allen et al. (2005) lnk captal regulaton to the competton banks face n the credt market. When banks compete for proects because there s an excess supply of funds relatve to nvestment opportuntes, market dscplne may be so strong to mpose a level of captal hgher than that mposed by the regulator. Flannery and Rangan (2004) document that book captal ratos at the 100 largest U.S. Bank Holdng Companes (BHC) have rased substantally n the perod between 1986 and The average bank has always exceeded the mnmum requred captal rato, and the percentage of constraned BHC dropped to the pont that captal restrctons became effectvely non-bndng for the 100 largest US BHC after They fnd support to the hypothess that large banks captal growth 2 Other studes argue that captal requrements may have the unntended effect of ncreasng rsk-takng behavor because of the loss of franchse value (Helmann, Murdock, Stgltz 2000), and the compoundng of moral hazard n effort and rsk choce (Besanko and Kanatas 1996). Gorton and Wnton (2003) queston both the very noton that moral hazard nduces banks to take on excessve rsk, and the resultng ratonale for captal regulaton. 3

6 has been a delberate response to market changes makng bank counterpartes more senstve to the default rsk of banks. As a result banks ncreased ther captal ratos to lower ther fundng costs. The lterature on PCA s manly emprcal. Snce the ntroducton of PCA there have been several attempts to assess ts functonng. The consensus s that t has worked well: n partcular PCA has had a sgnfcant mpact both n terms of rasng captal ratos and reducng rsk for banks (e.g. Benston and Kaufmann 1997, Aggarwal and Jaques 2001, Elzalde and Repullo 2006). Two theoretcal papers on PCA are partcularly relevant for our work. Both focus on the optmal closure polcy of banks ht by shocks but not on the benefts of restrctng bankng actvtes dependng on ther captal level. In Shm (2004) the banker can dvert profts and affect rsk and return. In a dynamc game between the depost nsurance regulator and the banker t s optmal to base the regulaton on the level of captal and to use a stochastc termnaton threat to nduce the banker to exert effort and to report ncome truthfully. In Kocherlakota and Shm (2005) loans repayment are enforced only through rsky collateral. The optmal contract among frms, depostors, and taxpayers has bank termnaton or forbearance dependng on the ex ante probablty that taxpayers money s nvolved. 3 Pelzzon and Schaefer (2005) construct a model of the nteracton of the captal requrement (Pllar 1) and supervson (Pllar 2) under the New Basel Accord. They fnd that f captal requrements can be enforced only through audt and f n ts absence the bank faces no constrant on ts portfolo, then regulatory nterventons n the form of forced recaptalzaton or closure, possble under Pllar 2, have a role. In ths vew Pllar 2 s smlar to the concept of PCA n the US. All these papers enhance our understandng of optmal captal regulaton of banks, but they do not ustfy the exstence of qualtatve restrctons to bank actons whch s the key feature of PCA. The obect of our research s precsely to construct a model of bankng regulaton that 3 Modelng optmal bank captal regulaton n a dynamc context s related to the study of dynamc optmal corporate captal structure. Bas et al. (2006) consder a model of corporate fnance where the manager can dvert ncome, and show that the nfnte repetton of the game between fnancers and manager, where the frm s downszed when t runs out of cash, provdes approprate ncentves to the manager. 4

7 combnes two types of restrctons on bank nvestments. The frst one corresponds to forcng the bank to hold a mnmum fracton of safe assets (whch s very smlar to captal requrements). The second one mposes restrctons to the types of rsky assets the bank s allowed to nvest n. Our paper s bult on two nsghts. Frst, n a moral hazard settng, forcng banks to hold a large fracton of safe assets may lower ther ncentves to exert effort to montor rsky assets;.e. t s necessary to guarantee the banks enough profts to recover montorng costs. Hence nstead of forcng the bank to hold a large fracton of safe assets, prohbtng certan types of nvestment and allowng ample scope of nvestment on others may be the only way to preserve ncentves. Second, t s well known that bank assets are generally opaque precsely because banks specalze n lendng to nformaton-senstve customers; however, opacty, and hence agency problems, may be more severe n certan asset classes than n others. Provdng ncentves to montor nvestments n the most opaque asset classes may thus be more costly n the sense that these nvestments can pay out less cash flow and requre more captal. Prohbtng some actvtes could thus allow the bank to have better access to fundng t would have been deprved of because of moral hazard. Our man fndng s that a regulator amng to maxmze the expected value produced by the bankng ndustry should restrct the composton of a bank portfolo accordng to the followng captal rato rule: the regulator should a) allow well captalzed banks to nvest any amount n any rsky asset, b) prohbt banks wth ntermedate levels of captal to nvest n the most opaque rsky assets, and c) prohbt undercaptalzed banks to nvest n rsky assets at all. Ths rule captures n a stylzed fashon one of the key features of the PCA regulaton adopted n the US, namely the noton that restrctons to bank assets becomes more strngent the less captalzed banks are. Notce that these restrctons could not have been replcated wth standard rsk-adusted captal regulaton, except f, by concdence, the rskyness of loans and the moral hazard possbltes are perfectly algned. Fnally we use our basc framework to analyze the adustment of the scale of bank operatons to address regulatory concerns. We show that for a gven level of captal the regulator 5

8 can explot a trade-off between the scope of bank operatons (the set of allowed nvestments) and the scale of bank assets. The rest of the paper s organzed as follows. In secton 2 we set up the basc model of nvestment under moral hazard wth fxed bank sze. In secton 3 we analyze the functonng of the unregulated bankng ndustry. In secton 4 we ntroduce PCA and determne the optmal regulaton. In secton 5 we extend the man result to the varable bank sze, and n secton 6 we conclude. 2. Model set up We consder a statc model of bank nvestments wth a rsk-neutral bank owner-manager. Bank asset sze s fxed and normalzed to 1. In Secton 5 we consder the general case wth varable bank sze. Assets are funded by bank captal, K < 1, and by unnsured labltes n the form of a loan, 1 K from a rsk-neutral perfectly compettve market wth opportunty cost of funds equal to 1+ rf, where rf 0 ndcates the rskless net return. As we wll llustrate below, by focusng on unnsured labltes we allow market dscplne to work most effectvely. We denote by D the break-even repayment promsed to the lender on a 1 K loan. For modelng purposes we wll consder a newly-created bank that operates wth an exogenous level of captal. The economc ntuton we wll produce wll allow us to analyze the case of an ongong bank wth a standng portfolo of assets and labltes where changes n the level of captal can be thought of as the result of the prevous perod s random cash flows. The bank can nvest n rsky assets ndexed by = 1,..., n, and n a rskless asset. The rskless asset returns1+. Unobservable effort e > 0 may be devoted to montor nvestments n any rsky rf asset. Montorng effort may be devoted to more than one rsky asset, but as we wll show later, f the bank montors t wll montor only one rsky asset. Only the bank has the sklls to montor rsky nvestments, whch ustfes fnancal ntermedaton. 6

9 We consder a moral hazard problem smlar to Holmström and Trole (1997). Wth montorng effort e the probablty of success of nvestment n asset class s p, as opposed to p Δ > 0 absent montorng effort, wth Δ > 0. The return X per unt of nvestment n asset class s X > 0 n case of success, and 0 n case of falure for all asset classes. We make no assumpton about the ont dstrbuton of asset returns. The key feature of ths set up s that some asset classes ental hgher agency problems so that the cash flows that can be pad to outsders are lower. Snce, for reasons that wll be clear later, we do not want that the market can condton fundng on the class of rsky assets the bank chooses, we assume that the returns X are observable but not verfable by the market. Banks can also nvest n the rsk-free asset that requres no montorng. Unversal rsk neutralty allows us to abstract from loan portfolo dversfcaton to concentrate on the basc problem of moral hazard n asset choces. We make a number of assumptons about parameters values. Assumpton 1 (postve expected value): only when montorng takes place the expected return of the nvestments n a rsky asset net of montorng cost exceeds the return from the rsk-free asset;.e. ( ) p X e > 1 + r > p Δ X,. (2.1) f The next two assumptons capture the noton of a rsk-return fronter of the rsky asset classes. Assumpton 2 (assets rankng by expected value): rsky assets wth hgher ndex have a hgher expected value wth and wthout montorng;.e. a) p X e p X e,..., p X e ( Δ ) ( Δ ) ( Δ ) b) p X p X,..., p X n n n n n (2.2) Furthermore we assume: 7

10 Assumpton 3 (assets rankng by rsk): asset classes wth hgher expected value have a lower probablty of success, wth and wthout montorng;.e. a) p <,..., < p < p, n 2 1 bp ) Δ <,..., < p Δ < p Δ. n n (2.3) It s mportant to specfy the nformaton and contractng structure of the fnancng and nvestment game. Frst, the composton of bank portfolo (.e. both the asset class and the proporton α of rsky assets) s observable but not verfable, hence not contractble. Thus a regulatory authorty s needed to set and enforce restrctons on both. Notce that smply assumng that the regulator has superor nformaton wth respect to the market (Peek et al. 1999, Berger et al. 2000) would not restore effcency n ths context as the market lacks the power to grant and revoke lcences and mpose penaltes. Second, montorng effort s unobservable to ether the market or the regulator. Fnally, the market observes the equlbrum asset choce and nfers bank s effort decson, and prces debt accordngly. The tmng of the model s as follows: at t=0 the level of bank captal s exogenously determned and made publc; at t=1 the regulator determnes both the maxmum fracton, and the class of rsky assets allowed for a certan level of captal; at t=2 the market sets promsed repayments, and provdes funds; at t=3 the bank decdes both the class of rsky assets t nvests n, and the montorng effort; at t=4 returns are realzed, and repayment made. 3. Unregulated bankng To begn wth, we nvestgate under whch condtons a bank can operate wthout any regulatory restrcton. In our model, ths wll be possble provded the bank holds suffcent captal so that t has ncentves to montor ts nvestments n rsky assets. As we wll, only n ths case the market 8

11 provdes funds to the bank. For the sake of exposton t s convenent to assume that the bank chooses to nvest n, and montor, only one asset - later n ths secton we wll prove that ths s ndeed the optmal bank s choce. In the absence of regulaton bank s nvestment depends only upon the level of captal. Recall that the market observes the equlbrum asset choce and nfers the bank s effort decson, and prces debt accordngly. Thus for each rsky asset class the break-even condton for the perfectly compettve credt market s ( 1 K)( 1 r ) pd ( 1 p )( 1 r )( 1 α ) + = + + (3.1) f f where D s the repayment promsed to the lender n case of success when the fracton of rsky nvestment n asset class s α and the rest s nvested n the rsk-free asset. Observe that from (3.1) D ( 1 K)( 1+ r ) ( 1 p )( 1+ r )( 1 α ) f f = (3.2) p D and, that debt s rsk-senstve, as > 0. α For the moment let us hold fxed the rsky asset class to nvest n. Usng (3.2) the bank s ( ) obectve functon wth montorng α ( 1 α)( 1 ) f ( 1 )(( 1 α) ( 1 )) p X + + r D e becomes f p αx + + r K e whch s ncreasng nα snce, by assumpton 1, p X > 1+ r. f Hence, absent regulaton the bank wll never nvest n the safe asset,.e. the bank would chooseα = 1 for all. Let us now return to the ssue of how many rsky assets the bank wll montor, f t montors, and establsh the followng result. Lemma 1. The bank wll devote effort to montor only one rsky asset, the one wth the hghest expected value. 9

12 Proof. See the appendx. The ntuton s straghtforward. Dsregardng montorng costs, gven rsk neutralty the obectve functon of the bank s convex, and a corner soluton s optmal: the bank nvests only n the asset wth the hghest expected value. Furthermore, montorng costs ncrease f the bank nvests n more assets. Next, we turn to the exploraton of the banks ncentves to montor ther rsky nvestments. Notce that, regardless of the level of captal, unless the bank has ncentves to montor the rsky nvestments, t wll not be funded. Indeed wthout montorng the sum of the expected returns of the bank and of the market s less than the opportunty cost of the funds by assumpton 1;.e. ( p )( X D ) ( p ) D 1 r,. Δ + Δ < + (3.3) f Absent regulaton the bank s ncentve to montor an nvestment n asset class s ( ) ( )( ), p X D e p Δ X D (3.4) e or, equvalently, X D. Havng establshed that absent regulaton the bank never nvests n Δ the safe asset, and snce for Lemma 1 the bank montors only one rsk asset, we can now derve the montorng ncentve constrant as a functon of bank captal. Usng the market clearng condton (3.2) forα = 1, equaton (3.4) becomes K K ( px ( 1 rf )) pe Δ + 1+ r f (3.5) where K denotes the mnmum level of captal that a bank must own to satsfy the ncentve to montor asset class. Equaton (3.5) thus mposes a mnmum level of captal as a necessary condton for outsde fundng n asset. Notce that Lemma 1 mples that, a fortor, the bank could 10

13 not satsfy the montorng ncentve constrant combnng any two rsky assets. 4 Equaton (3.5) can be expressed as e p X K + r ( 1 )( 1 ) f Δ (3.6) e whch has the usual nterpretaton that the expected cash flow payable to outsders p X, Δ should not be smaller than the opportunty cost of outsde funds (Trole 2005). From (3.6) snce, e K<1 t follows that p X > 0 Δ for all. We now turn to the queston whether unregulated market fnance may arse. For the market not to collapse, a necessary condton s that n equlbrum there s no shrkng. Lemma 1 tells us that, f there s no shrkng, then nvestment and montorng wll occur n asset n. Consequently we have to determne whether the bank has any ncentve to devate from montorng asset n, and shrk n the rsky asset that gves the hghest expected payoff when the promsed repayment s D n. From part b) of assumptons 2 and 3 t follows that the best alternatve to montor asset n s to shrk n asset n. Therefore necessary condton for unregulated market fnance s that equaton (3.4) s satsfed for asset n,.e. Recallng that from (3.2) pndn ( 1 K)( 1 rf ) ( ) ( )( ). p X D e p Δ X D (3.7) n n n n n n n D = + for α = 1, and observng that n < 0, then (3.7) K s volated for hgh e and low K. Recallng furthermore that K n s the value of K such that equaton (3.7) s satsfed wth equalty, then, f a bank has a level of captal K< K n the market collapses and we cannot have unregulated market fnance. 4 Notce that f the bank has enough captal to montor more than one rsky asset and f after a gven sze returns n each rsky asset go to zero then the bank wll choose a portfolo composed of several rsky assets startng wth the ones wth the hghest present value, hence generalzng Lemma 1. Snce the qualtatve results of the model would not change, n what follows we wll not formalze ths more general model specfcaton. Focusng on a bank that nvests and montors only one asset s thus a ustfable abstracton n the nterest of smplcty. 11

14 4. Regulaton wth moral hazard Havng dentfed the necessary condton for unregulated market fnance we now nvestgate how the regulator can mprove welfare f the market collapses. Recall that we have assumed that portfolo composton s not contractble. Hence the authorty, e.g. by a regulator, s called upon to set and enforce portfolo restrctons. Indeed one dmenson of bankng regulaton s the power to nspect banks and to grant and revoke lcences on the bass of ths nformaton (see e.g. Bhattacharya et al. 2002), a power that the market does not have. In what follows we successvely consder two regulatory tools: captal regulaton and restrctons on the portfolo of rsky assets,.e. the prohbton of nvestments n certan assets to ncrease the expected value of the bankng ndustry. Our obectve here s to examne whether these two nstruments could be consdered as substtutes. The basc argument for consderng these two regulatory measures as possble substtutes s that when we mpose captal regulaton we force the bank to restructure ts portfolo so as to nvest n less rsky proects, whch s precsely what we obtan f we smply prohbt the proects wth hgher rsks. As we wll see, nevertheless, the analyss of moral hazard wll lead us to dentfy the dfferences between these two regulatory nstruments. Although another mportant dmenson of modern bankng regulaton s depost nsurance here we allow only for unnsured labltes. Our results would not change f we were to consder nsured labltes. If labltes are nsured by a farly-prced depost nsurance scheme ther cost s dentcal to that mposed by a rsk-neutral perfectly compettve lendng market. Under a flat depost nsurance scheme nstead, rents on deposts would be maxmzed by choosng the rskest asset, as shown n Lemma 1 where the nterest rate charged to the bank by the market does not depend on the chosen proect. The analyss of captal requrements s here ustfed by the results obtaned n the prevous secton. As noted there, a mnmum captal s requred, so t s natural to set these lmts as captal requrements: at least a captal K n s requred n order to nvest n asset n, a captal K n-1 n order to nvest n assets n-1, and so on. If so, for a portfolo of assets represented by an nx1 vector λ whose

15 components λ, 0 λ 1, are the proportons of nvestment n rsky assets, wth λ = 1, captal n regulaton mposes that n λ K K. For the same convexty reasons that make Lemma 1 hold, under a captal constrant the optmal portfolo wll be obtaned at a corner soluton. Ths mples that t wll combne, at most, two rsky assets. We wll focus on the case of a suffcently hgh effort cost e, so that effort duplcaton wll never be optmal. Ths wll allow us to restrct our analyss to the comparson of portfolos composed of one rsky asset and the safe asset. We wll show that n some range of values captal regulaton wll not succeed n holdng back non-montored assets. In partcular we establsh the followng result: Proposton 1. Captal regulaton does not prevent a bank from nvestng n asset n wthout montorng t rather than nvestng and montorng asset n-1. Proof. See the appendx. Consequently, captal requrement regulaton may fal to prevent the choce of the asset wth the hghest rsk and substtute t by the next best asset. Stll, ths needs not be a problem f captal regulaton provdes the rght ncentves to nvest a fracton α of the portfolo n the montored asset n and the rest n the safe asset. Gven α, for each asset class the bank s ncentve to montor an nvestment n the rsky asset class s ( α ( 1 α)( 1 ) ) ( ) α ( 1 α)( 1 ) ( ) p X + + r D e p Δ X + + r D (4.1) f f whch becomes e αx + ( 1 α)( 1 + rf ) + D. Δ (4.2) 13

16 Snce for Lemma 1 the bank wll montor only one rsky asset we can now derve the captal constrant when the bank may face restrctons on the fractonα of a rsky asset. Usng the break even condton (3.2), equaton (4.2) becomes αx ( 1 α)( 1 rf ) Δ e ( 1 K)( 1+ r ) ( 1 p )( 1+ r )( 1 α ) f f p (4.3) or K pe Δ ( px ( 1 rf )) α + 1+ r f. (4.4) The RHS of (4.4) ndcates the mnmum level of captal, for each valueα 0, that a bank must own n order to have the ncentve to montor an nvestment n asset class. Part b) of assumptons 2 and 3 guarantees that f (4.4) s satsfed the bank has no ncentve to shrk n an asset wth an ndex <. To focus on the nterestng case, where t s not possble to fnance a proect exclusvely through external debt, we make the followng assumpton. Assumpton 4 (postve captal): for every asset, the expected cash flow that can be pad to e outsders p X Δ e 1 + rf > p X, Δ s smaller than the opportunty cost of funds, ( 1 rf ) for all. + ;.e. Ths leads us to the followng result. Proposton 2. For any rsky assets =1, n-1 f a bank has a level of captal such that K< K n (.e. unregulated market fnance s mpossble) then ether the parameters are such that equaton (4.4) s satsfed for α = 1, that s there are no restrctons on the fracton of assets that can be devoted to 14

17 rsky nvestments, or there s no α 0 that can satsfy t. In the latter case, the only way to guarantee that the market funds the bank s for the regulator to setα = 0, that s to prohbt any nvestment n asset class. The proof s obvous gven assumpton 1 that guarantees that the RHS of (4.4) s a decreasng functon of α. The ntuton for Proposton 2 s that by forcng the bank to nvest a large fracton n the safe asset the regulator lowers the bank s expected proft and thus ts ncentve to montor the rsky asset. Snce the lower the level of captal the hgher s the promsed debt repayment, then there are parameter constellatons such that t s mpossble to provde ncentves to montor the nvestment n rsky asset gven the amount of captal. In such cases, captal regulaton s powerless and prohbton of any nvestment n that asset class s the only way to have the bank funded. 5 It s well known (Trole 2005) that n ths type of models there are two sources of agency problems: the lkelhood rato Δ and the effort level e. They yeld a maxmum level of expected p e cash flow from nvestment n rsky asset that can be pad to outsders equal to p X Δ. Our paper makes the pont that agency problems may be more severe n certan asset classes than n other so that t may be more costly to provde ncentves to montor nvestments n those asset classes. More nnovatve nvestments, for example n dervatves, brdge loans for M&A, propretary equty tradng, hedge fund fnancng, may be more opaque, and therefore leave more scope for manageral dscreton, than more tradtonal credt operatons, thus requrng more costly ncentves. To reflect ths dea n a straghtforward way, we make the followng assumpton that lnks the expected value from nvestng n a rsky asset to the cash flow that can be pad to outsders once we account for the cost of manageral ncentves. 5 Proposton 2 s related to the credt ratonng results of Aghon and Bolton (1997) and Pketty (1997) n growth models wth moral hazard where ndvduals have heterogeneous wealth endowments. 15

18 Assumpton 5 (negatve correlaton between expected values and expected pledgeable cash flow): asset classes wth hgher expected value have lower expected pledgeable cash flow;.e. e e e p1 X1 > p2 X2 >,..., > p n X n. Δ1 Δ2 Δn (4.5) Thus asset class 1 leaves more expected cash flow payable to outsders than asset class 2, and so on. Fgure 1 llustrates the decreasng relatonshp between expected pay-offs and expected pledgeable cash-flows that s mpled by the combnaton of assumptons 2 and 5. Expected value p n X n -e p 1 X 1 -e p n (X n -e/δ n ) p 1 (X 1 -e/δ 1 ) Expected pledgeable cash flow Fgure 1: Expected values and expected pledgeable cash flows: an example. Assumpton 5 deserves some comments. Frst, ts motvaton s to focus on a smplfed case where a maor tenson exsts between net present value maxmzaton and moral hazard. Alternatve assumptons, whle leadng to the same qualtatve results regardng the benefts of regulatory restrctons to complement captal ratos, would make the analyss more cumbersome and would ntroduce addtonal complextes makng the ntuton of our result less clear. Ths tenson between net present value and moral hazard s requred n order to pont out why prohbtng some actvty could be effcent. Second, more generally we stress that the value to outsders of opaque banks 16

19 assets s lnked to the cost of provdng proper ncentves to the bankers, and not necessarly to the ther net present value. Fnally, notce that the rankng s a characterstc of the assets n the whole economy and not of the asset portfolo of a partcular bank. Before ntroducng our man result on optmal bank regulaton we have to establsh the bank optmal asset choce assumng the bank always montors. Ths wll be the one wth the hghest expected value among those that satsfy the montorng constrant. Lemma 2. Assume there s a subset of asset classes {1,,} n whch montorng takes place,.e. equaton (4.4) s satsfed for α = 1. Then, the bank prefers to any proect k such that k<. Proof. See the appendx. Recall that K n (3.5) defnes the montorng threshold for nvestment n asset class and that the negatve correlaton assumpton mples an orderng of the montorng threshold such that K 1 <,,<K <,,< K n and assumpton 4 on mnmum captal mples K 1 >0. We are now n a poston to establsh our man result about optmal bank captal regulaton. Proposton 3. The optmal captal regulaton s characterzed as follows. 1) For banks wth a level of captal K such that K Kn t s optmal to set no restrctons ether on the type of rsky nvestment that the bank s allowed to undertake or on the percentage of nvestment n rsky asset classes, that s t s optmal to set α = 1. 2) For banks wth a level of captal K such that K + 1 > K K for = 1,,n-1 t s optmal to prohbt nvestments n all rsky asset classes wth ndex > and to allow the bank to nvest all( α = 1) n rsky asset classes wth ndex (see fgure 2). 17

20 3) For banks wth a level of captal K such that 0 < K < K1 t s optmal to prohbt nvestments n all rsky asset classes and to allow nvestment n the rsk-free asset only, that s t s optmal to setα = 0. Proof. See the appendx. Allowed asset classes Prohbted asset classes 1 +1 n Fgure 2. Optmal regulaton for banks wth ntermedate captal, K +1 >K K, =1,,n-1 The frst part of Proposton 3 states that f a bank has a suffcently hgh level of captal such that the ncentve to montor s preserved even for the nvestments n the most opaque asset class, then regulaton should not restrct ts choces as the market wll fund t anyway. The second part of Proposton 3 says that for banks wth an ntermedate level of captal the only way to guarantee that the bank has ncentves to montor, and thus t s funded by the market, s to prohbt nvestments n the most opaque asset classes even f those nvestments have the hghest expected value. The thrd part of Proposton 3 posts that for banks wth low level of captal the only way to guarantee that the market funds the bank s to prohbt nvestments n rsky assets altogether. Several comments are n order. Frst, ths result captures n a stylzed way one of the man messages of the PCA regulaton, namely that the lower the bank captal rato the fewer are the types of nvestments that the bank s allowed to undertake. Notce that these are both qualtatve and quanttatve restrctons on bank s actons that acheve results (bank fundng) that could not have 18

21 been acheved wth tradtonal captal regulaton alone as shown n Proposton 2. 6 Second, snce the prohbton of certan nvestments allows a reducton of the level of captal to satsfy the montorng constrant, then ths rule effectvely economzes on captal for a gven bank sze or, alternatvely, t allows ncreasng bank sze gven captal. In the followng secton we wll tackle these ssues. Thrd, as mentoned, the role of the negatve correlaton assumpton (assumpton 5) n Proposton 3 s merely to smplfy matters and provde a clear-cut analyss of the case n pont, where a maor tenson exsts between net present value maxmzaton and moral hazard. If we completely reverse the assumpton, and assume a postve correlaton, then such a tenson ceases to exst and captal regulaton s suffcent to cope wth both, provded rsk weghts are convenently chosen. So n a postve correlaton case the very essence of the problem we are focusng on dsappears, and there s no ratonale for a PCA polcy. The general case can only be understood through the ntuton bult on our model. As we wll have locally ncreasng or decreasng relatonshps between expected net present values and expected pledgeable cash flows, ths wll mply that, as captal decreases, for some proects captal requrement wll be suffcent to solve the moral hazard ssues, but for others a prohbton wll be necessary to allow the bank to successfully tap the market for funds. As noted, one of the ratonales of the PCA regulaton was to mandate some nterventons for undercaptalzed banks rather than relyng on regulatory dscreton only. Although n ths paper we do not address the ssue of the costs and benefts of havng rules vs regulatory dscreton, the rule we have derved n Proposton 3 can be nterpreted as the optmal contract between the regulator and the bank. The bank would fnd t optmal to subscrbe to that contract because havng ts hands ted,.e. beng n the mpossblty to nvest n some moral hazard-senstve proects would allow t to have access to fnance. In ths model, absent unforeseen contngences that mght make dscreton preferable wth respect to rgd rules, commtment to that contract would domnate an ad 6 The result that qualtatve restrctons on the set of allowed nvestments may be optmal s smlar to the prohbton of certan dffcult-to-observe tasks n the mult-task prncpal-agent model of Holmström and Mlgrom (1991). 19

22 hoc method of bank crss resoluton. Indeed dscreton mght lead to forbearance, that f antcpated by the market would result n less fundng for bank nvestment, or otherwse may shft the cost of crss resoluton to lender of last resort facltes. It s mportant to nterpret our results n the context of the lterature on captal regulaton. Frst, notce that n ths model we do not exclude a pror tradtonal captal regulaton. The fact that the optmal value of α s 1 s the result of the need to satsfy an ncentve constrant whch could not be done wth quanttatve restrctons on captal alone. Second, observe that n ths model the tradtonal role of captal regulaton mantanng stablty and solvng depostors collectve acton problems s not operatonal because lablty holders subect fnancal ntermedares to perfect market dscplne as loans are farly prced. However, lablty holders are not capable to enforcng contngent contracts as to the asset choces. Hence, PCA regulaton wth qualtatve asset prohbtons s needed to ntegrate quanttatve captal regulaton when the opacty of bank assets s an ssue. 5. Varable bank sze Up to now we have consdered a fxed captal and fxed sze framework, so that captal regulaton would mply that banks had to nvest a fracton of ther assets n the rskless asset. In fact, the bank could comply wth captal regulaton by contractng the scale of ther operatons. But scale would be observable and contractble and therefore the bank mght be subect to market dscplne. Consequently, consderng the possblty of a varable bank sze s qute relevant for our analyss, as t allows examnng the possble trade-offs between scale and scope of banks. For ths reason we now turn to the case of varable asset sze. The bank has to decde the scale of ts overall actvtes as well as the composton of the portfolo of rsky assets. Assume that asset sze I s such that I 0, I, I beng the maxmum capacty. Ths ntermedate assumpton between fxed and completely varable asset sze captures the dea that after a certan scale returns 20

23 are sharply decreasng. Asset sze I s funded by captal K and by farly prced loans, I-K. Producton has constant returns to scale: wth success the return s IX for all, wth falure 0. Effort s assumed proportonal to asset sze so that ei s the effort to montor any rsky asset of sze I. Probablty of success and falure wth and wthout montorng are as n the fxed-sze case. Snce bank sze s determned together wth funds request and thus, as n the prevous sectons, t s gven at the stage of asset choce, then Lemma 1 apples,.e. the bank wll montor only one rsky asset, f t montors at all. The tmng and the remanng assumptons are as n the fxed-sze case. The break-even constrant for the rsk-neutral compettve lender becomes and the bank obectve functon s Usng (4.6) expresson (4.7) becomes ( )( 1 ) ( 1 )( 1 )( 1 α ) I K + r = pd + p + r I (4.6) f f ( α ( α)( ) ) p XI r I D ei. (4.7) f ( α ( 1 α)( 1 f )) ( 1 f )( ) I px + + r ei + r I K (4.8) whch s ncreasng n α snce p X > 1+ r. Thus agan gven the amount borrowed I-K the bank f wll not nvest n the safe asset unless forced to do so. The montorng ncentve constrant becomes 7 ( px ( 1 rf )) pe α + Δ 1 K I = I 1+ rf m (4.9) where the multpler m s m 1+ rf pe α + Δ ( px ( 1 rf )). (4.10) 7 The dervaton of the expresson (4.9) follows the same logc of the equvalent constrant n secton 4. For a very smlar expresson of the borrowng capacty see Trole (2005) p

24 Notce that once bank sze s determned, banker s decson follows the same logc of the m fxed-asset sze. For all asset classes, > 0, because of assumpton 1. Therefore, gven asset α sze and asset class, ether the montorng constrant (4.9) s satsfed for α = 1 or there s no value α > 0 that can satsfy t, a result smlar to Proposton 2. Thus consderng the value of (4.10) whenα = 1, the nvestment multpler becomes: m ( 1+ rf ) > 1 e ( 1+ rf ) p X Δ (4.11) e because of the mantaned assumpton 4 that 1 + rf > p X, Δ for all. Under the negatve correlaton assumpton (assumpton 5) t follows that m 1 >,,> m n whch mples that the multpler can be ncreased by prohbtng nvestments n the most opaque asset classes. Defne the varable I Km, as the maxmum sze of asset gven the level of captal K, compatble wth montorng ncentves and thus market fundng. Absent regulaton, unless the bank has enough captal such that I n I, then n order to get funded t wll lower ts sze to the pont that the montorng constrant s satsfed. Thus for the banks wth captal such that In < I a regulaton prohbtng nvestment n the most opaque assets allows to ncrease sze. Ths leads us to the followng result. Proposton 4: 1) If the level of captal s such that I n I then placng restrctons on bank asset choce would not ncrease fundng; 2) If nstead the level of captal s such that I n < I a regulaton prohbtng nvestment n the most opaque asset classes can ncrease the multpler and thus fundng. 22

25 The proof follows n a straghtforward way from the assumpton that I 0, I, and the defnton of I. In case 1, the bank s suffcently captalzed so that even the nvestment n the most opaque asset n satsfes the montorng constrant for the relevant range of nvestment opportuntes; no restrcton on asset choces would mprove welfare. The zero margnal returns after reachng the maxmum scale nduces the bank to choose a sze for whch t has ncentves to montor. In case 2, despte the market provdng some fundng, sze s lmted by the scarcty of captal and by the opacty of bank assets, so that, absent regulaton, only partal fundng to explot nvestment opportuntes can be obtaned. Case 2 shows that one can satsfy the montorng constrant (4.9) ether by ncreasng the multpler (.e. prohbtng nvestment n certan asset classes) or by lowerng bank sze, or both. Thus the regulator faces a trade-off between allowng nvestments n many asset classes (low multpler) and allowng banks to pursue large levels of overall nvestment. For an llustraton see fgure 3. I Maxmum sze compatble wth market fundng I n-3 I n-2 I n-1 I n No restrcton Asset n prohbted Assets n, n-1 prohbted Assets n, n-1, n-2 prohbted Restrcton level Fgure 3: Restrctons and sze for banks wth scarce captal; In < I 23

26 The man mplcaton of case 2 s that snce the welfare functon s the net aggregate expected present value of bankng nvestment, the regulator has to consder both the expected return and the sze of the nvestment. Sze depends on the moral hazard dmenson va the multpler m. Thus regulaton affectng the multpler m effectvely determnes the sze of the overall bank nvestments. Under our assumpton of negatve correlaton the hgher the ndex of the asset class the lower the maxmum sze of the nvestment for a gven captal compatble wth montorng ncentves. Thus as we move from asset 1 to n, we go from a combnaton of hgh expected returnlow sze to a combnaton of low expected return-hgh sze. The optmal choce depends on the characterstcs of the rsky assets and n partcular on the relatonshp between expected value and expected pledgeable cash flow. The man dfference wth respect to the fxed-sze result of Proposton 3 s that banks wth lttle captal can stll nvest n opaque assets albet at a small scale. Furthermore, the noton that the ncentve constrant can be satsfed also by allowng the bank to nvest n opaque assets thus effectvely lowerng the overall bank sze can be nterpreted as downszng a bank to force t to satsfy a certan captal requrement. Fnally, the ncentve constrant (4.9) can also be seen as a way to mnmze the amount of captal needed to satsfy the montorng constrant to nvest n rsky assets of gven sze. Hence our framework can be appled to study the ssue of recaptalzaton of undercaptalzed banks wth a gven portfolo of loans. 6. Concluson We have developed a smple framework to study nvestment choces under moral hazard that can be appled to a varety of corporate fnance decsons. What makes t partcularly sutable for the analyss of bank captal regulaton s the regulator s advantage, stemmng from ts supervsory and lcensng role, n gatherng nformaton about bank portfolos and enforcng portfolo restrctons. Our model shows that the logc behnd PCA regulaton s well rooted n the mcroeconomc analyss of banks ncentves. However, our paper has not attempted to provde any analyss for one of the other ratonales behnd the adopton of PCA n the US, namely the desre to avod 24

27 forbearance by tghtenng the regulator s hands and requrng some mandatory actons as a functon of captal ratos. In other countres, n partcular n the European Monetary Unon, bank captal regulaton at the natonal level often follows both the tradtonal quanttatve captal regulaton based on rsk-weghted captal ratos, and a mx of moral suason and ad hoc resoluton of bank crses. A polcy mplcaton of our paper s that a pece of regulaton smlar to PCA should also be adopted outsde the US, especally n countres where a dscretonary approach to bank crss resoluton may lead to regulatory capture by the ndustry. Ths s partcularly true n countres wth weak nsttutonal envronments where, as Bart. et al. (2006) argue, gvng strong dscretonary powers to bank supervsors may actually make matters worse. 25

28 Appendx Proof of Lemma 1. Usng a convexty argument, we frst show that the bank chooses one rsky asset, and then we prove that the selected asset s the one wth the hghest net present value. Recall that at t=2 the market sets a repayment D as a functon of the captal and the equlbrum behavor of the banker. Let λ be a nx1 vector whose components λ, 0 λ 1, are the proportons of nvestment n rsky assets, wth n λ = 1. Denote wth λ * the equlbrum vector of proportons chosen by the bank. We ntroduce the followng defnton: proect s sad to belong to the set A f ts realzed return s X ; proect s sad to belong to the set A f ts realzed return s 0, where A s the complement set of A. Let us denote wth Z ( A) the set of all subsets of A (ncludng the empty set). The expected value of bank profts gross of montorng cost can be expressed as Φ (6.1) S Z S ( λ) p( S) λ X D;0. where p ( S ) ndcates the probablty that the proects n set S are successful. At t=3 the bank wll choose λ to maxmze where 1( λ 0) n ( λ) e 1( λ 0) Φ > (6.2) > s a vector whose -th component takes value 1 when λ > 0, and 0 otherwse. Notce that D s a functon of the equlbrum vector λ * and not of λ. We show now that Φ ( λ ) s convex, that s, that for every vector So t must be the case that 1 λ and 2 λ t must be true that ( αλ 1 ( α) λ 2 ) α ( λ 1 ) ( α) ( λ 2 ) α [ ] Φ + 1 Φ + 1 Φ 0,1. (6.3) 26

29 S Z 1 2 p( S) ( αλ + ( 1 α ) λ ) X D;0 S α λ α λ ( ) ( ) 1 2 p S max X D;0 + 1 max X D;0. S Z S S (6.4) 1 2 ( α λ ) + X D then the LHS of (6.4) s equal to 0, and (6.3) S ( α λ ) X > D then S Two cases are possble: f αλ ( 1 ) s satsfed. If αλ ( 1 ) S Z S Z 1 2 p( S) ( αλ + ( 1 α ) λ ) X D;0 = S 1 2 p( S) ( αλ + ( 1 α ) λ ) X D = S p S α λ X + α λ X D ( ) ( 1 ) 1 2 S Z S S ( ) ( ) 1 2 p S αmax λx D;0 + 1 α max λ X D;0. S Z S S Ths shows that Φ ( λ ) s convex. (6.5) It s standard to show that the maxmzaton of the convex functon Φ ( λ ) over the hyper- n plane λ = 1 yelds a corner soluton. From ( αλ ( 1 α) λ ) α ( λ ) ( 1 α) ( λ ) Φ + Φ + Φ { ( ) ( )} ( ) ( ) ( ) { } { ( ) ( )} α max Φ λ, Φ λ + 1 α max Φ λ, Φ λ max Φ λ, Φ λ (6.6) by quasconvexty. Recall that we denote wth λ * the vector that maxmzes (6.2). Assume that * ( ) λ 0,0,...,1,...0,0 δk (6.7) where δk s the canoncal base where the k-th element s 1, so that * n λ = 1 = αδ, and let { { }} J = = 1, 2,..., n, α > 0 follows that. Because the δ k are n the feasble set, then by quasconvexty t 27

30 * ( λ ) k J ( δk) Φ max Φ. (6.8) * Snce λ s optmal then * ( λ ) k J ( δk) Φ max Φ. (6.9) * So that Φ ( λ ) = Φ ( δ ) max. k J k Snce wth δ k the ntroducton of effort s cost benefts a lower number of rsky asset classes * montored wth respect to λ, the optmal choce condtonal on montorng s to nvest n only one rsky asset. We now show that ths wll be the n-th asset. Ths s the case snce D s ndependent of k. Notce frst that Φ ( δ ) = p ( X D) for any D such that p D ( r )( K) n n n * = 1+ f 1 where * s the asset chosen by the bank. For any such that Φ ( δ ) = 0 asset n s obvously preferred. For such that ( δ ) 0 Φ >, combnng assumpton 1 and 3 we have pnxn px and pnd pd. Consequently ( δ ) ( δ ), 1,2,..., Φ n Φ = n, wth equalty only for =n. Proof of Proposton 1. Consder the bank s choce when t s confronted wth a captal requrement n λk K < Kn for K lmε 0 = K ε. We show that the bank prefers to nvest n n asset n wthout montorng than to nvest and montor asset n-1. In order to do that, denote by D k the repayment due when asset k s chosen, so that p D ( 1 r )( 1 K) = +. Then, because D n > D n-1 k k f t follows that ( p )( X D ) ( p )( X D ) ( p )( X D ) p ( X D ) e. n n n n n n n Δ > Δ Next, at the lmt K=K n, n n n n 1 n n n n. Δ = But assumpton 2 ontly wth p D = ( 1+ r )( 1 K) mples ( ) ( ) n n n n 1 n 1 n 1. k k f p X D e> p X D e Thus, by transtvty ( )( ) ( ) p Δ X D > p X D e and the bank prefers to nvest n asset n wthout n n n n 1 n 1 n 1 n 1 28

31 montorng to montorng asset n-1. By contnuty, the nequalty wll hold true n a neghbourhood of K n, ( K n -ν, K n ) for a suffcently small ν. Proof of Lemma 2. Recall that by assumpton 2 we have that for k<, p X pkxk, and by assumpton 3 p k > p. Hence where p D ( 1 r )( 1 K) f ( ) ( ) p X D e> p X D e (6.10) k k = +, and the result follows. Proof of Proposton 3. Proposton 2 allows us to set α = 1 and focus on the permtted rsky nvestments. Recall that the negatve correlaton assumpton (assumpton 5) mples an orderng of the montorng captal threshold such that K 1 <,,< K <,,< K n and that assumpton 4 on mnmum captal mples that K 1 >0. To prove part 1. For a level of captal K K n equaton (3.7) on market dscplne s satsfed. Because of the negatve correlaton assumpton K > K, =1, n-1. Hence no shrkng wll occur. Thus bank s choce s among n montored nvestments. Lemma 2 states that asset class n s chosen. To prove part 2. Because of the negatve correlaton assumpton equaton (3.7) s not satsfed for asset classes +1,,n whle t s satsfed for asset classes 1,,. Part b) of assumptons 2 and 3 guarantee that f (3.7) s satsfed the bank has no ncentve to shrk n assets wth an ndex. Thus the bank wll shrk for all asset classes +1 to n and wll montor nvestments n asset classes 1,,. Usng Lemma 2 we know that s the bank s preferred choce among montored assets. Recall that from assumpton 1 all non-montored nvestments n rsky assets have negatve expected value. Thus the best acton for the regulator s to prohbt all assets +1,,n. 29

Banking regulation and prompt corrective action *

Banking regulation and prompt corrective action * Bankng regulaton and prompt correctve acton * Xaver Frexas Department of Economcs and Busness, and CEPR, UK Unverstat Pompeu Fabra, Barcelona, Span xaver.frexas@econ.upf.es Bruno M. Parg Department of

More information

Elements of Economic Analysis II Lecture VI: Industry Supply

Elements of Economic Analysis II Lecture VI: Industry Supply Elements of Economc Analyss II Lecture VI: Industry Supply Ka Hao Yang 10/12/2017 In the prevous lecture, we analyzed the frm s supply decson usng a set of smple graphcal analyses. In fact, the dscusson

More information

Money, Banking, and Financial Markets (Econ 353) Midterm Examination I June 27, Name Univ. Id #

Money, Banking, and Financial Markets (Econ 353) Midterm Examination I June 27, Name Univ. Id # Money, Bankng, and Fnancal Markets (Econ 353) Mdterm Examnaton I June 27, 2005 Name Unv. Id # Note: Each multple-choce queston s worth 4 ponts. Problems 20, 21, and 22 carry 10, 8, and 10 ponts, respectvely.

More information

Price and Quantity Competition Revisited. Abstract

Price and Quantity Competition Revisited. Abstract rce and uantty Competton Revsted X. Henry Wang Unversty of Mssour - Columba Abstract By enlargng the parameter space orgnally consdered by Sngh and Vves (984 to allow for a wder range of cost asymmetry,

More information

Quiz on Deterministic part of course October 22, 2002

Quiz on Deterministic part of course October 22, 2002 Engneerng ystems Analyss for Desgn Quz on Determnstc part of course October 22, 2002 Ths s a closed book exercse. You may use calculators Grade Tables There are 90 ponts possble for the regular test, or

More information

Problem Set 6 Finance 1,

Problem Set 6 Finance 1, Carnege Mellon Unversty Graduate School of Industral Admnstraton Chrs Telmer Wnter 2006 Problem Set 6 Fnance, 47-720. (representatve agent constructon) Consder the followng two-perod, two-agent economy.

More information

Chapter 15: Debt and Taxes

Chapter 15: Debt and Taxes Chapter 15: Debt and Taxes-1 Chapter 15: Debt and Taxes I. Basc Ideas 1. Corporate Taxes => nterest expense s tax deductble => as debt ncreases, corporate taxes fall => ncentve to fund the frm wth debt

More information

A MODEL OF COMPETITION AMONG TELECOMMUNICATION SERVICE PROVIDERS BASED ON REPEATED GAME

A MODEL OF COMPETITION AMONG TELECOMMUNICATION SERVICE PROVIDERS BASED ON REPEATED GAME A MODEL OF COMPETITION AMONG TELECOMMUNICATION SERVICE PROVIDERS BASED ON REPEATED GAME Vesna Radonć Đogatovć, Valentna Radočć Unversty of Belgrade Faculty of Transport and Traffc Engneerng Belgrade, Serba

More information

Chapter 10 Making Choices: The Method, MARR, and Multiple Attributes

Chapter 10 Making Choices: The Method, MARR, and Multiple Attributes Chapter 0 Makng Choces: The Method, MARR, and Multple Attrbutes INEN 303 Sergy Butenko Industral & Systems Engneerng Texas A&M Unversty Comparng Mutually Exclusve Alternatves by Dfferent Evaluaton Methods

More information

- contrast so-called first-best outcome of Lindahl equilibrium with case of private provision through voluntary contributions of households

- contrast so-called first-best outcome of Lindahl equilibrium with case of private provision through voluntary contributions of households Prvate Provson - contrast so-called frst-best outcome of Lndahl equlbrum wth case of prvate provson through voluntary contrbutons of households - need to make an assumpton about how each household expects

More information

Chapter 5 Bonds, Bond Prices and the Determination of Interest Rates

Chapter 5 Bonds, Bond Prices and the Determination of Interest Rates Chapter 5 Bonds, Bond Prces and the Determnaton of Interest Rates Problems and Solutons 1. Consder a U.S. Treasury Bll wth 270 days to maturty. If the annual yeld s 3.8 percent, what s the prce? $100 P

More information

2) In the medium-run/long-run, a decrease in the budget deficit will produce:

2) In the medium-run/long-run, a decrease in the budget deficit will produce: 4.02 Quz 2 Solutons Fall 2004 Multple-Choce Questons ) Consder the wage-settng and prce-settng equatons we studed n class. Suppose the markup, µ, equals 0.25, and F(u,z) = -u. What s the natural rate of

More information

Principles of Finance

Principles of Finance Prncples of Fnance Grzegorz Trojanowsk Lecture 6: Captal Asset Prcng Model Prncples of Fnance - Lecture 6 1 Lecture 6 materal Requred readng: Elton et al., Chapters 13, 14, and 15 Supplementary readng:

More information

Finance 402: Problem Set 1 Solutions

Finance 402: Problem Set 1 Solutions Fnance 402: Problem Set 1 Solutons Note: Where approprate, the fnal answer for each problem s gven n bold talcs for those not nterested n the dscusson of the soluton. 1. The annual coupon rate s 6%. A

More information

Wages as Anti-Corruption Strategy: A Note

Wages as Anti-Corruption Strategy: A Note DISCUSSION PAPER November 200 No. 46 Wages as Ant-Corrupton Strategy: A Note by dek SAO Faculty of Economcs, Kyushu-Sangyo Unversty Wages as ant-corrupton strategy: A Note dek Sato Kyushu-Sangyo Unversty

More information

Consumption Based Asset Pricing

Consumption Based Asset Pricing Consumpton Based Asset Prcng Mchael Bar Aprl 25, 208 Contents Introducton 2 Model 2. Prcng rsk-free asset............................... 3 2.2 Prcng rsky assets................................ 4 2.3 Bubbles......................................

More information

Prospect Theory and Asset Prices

Prospect Theory and Asset Prices Fnance 400 A. Penat - G. Pennacch Prospect Theory and Asset Prces These notes consder the asset prcng mplcatons of nvestor behavor that ncorporates Prospect Theory. It summarzes an artcle by N. Barbers,

More information

Raising Food Prices and Welfare Change: A Simple Calibration. Xiaohua Yu

Raising Food Prices and Welfare Change: A Simple Calibration. Xiaohua Yu Rasng Food Prces and Welfare Change: A Smple Calbraton Xaohua Yu Professor of Agrcultural Economcs Courant Research Centre Poverty, Equty and Growth Unversty of Göttngen CRC-PEG, Wlhelm-weber-Str. 2 3773

More information

THE ECONOMICS OF TAXATION

THE ECONOMICS OF TAXATION THE ECONOMICS OF TAXATION Statc Ramsey Tax School of Economcs, Xamen Unversty Fall 2015 Overvew of Optmal Taxaton Combne lessons on ncdence and effcency costs to analyze optmal desgn of commodty taxes.

More information

Highlights of the Macroprudential Report for June 2018

Highlights of the Macroprudential Report for June 2018 Hghlghts of the Macroprudental Report for June 2018 October 2018 FINANCIAL STABILITY DEPARTMENT Preface Bank of Jamaca frequently conducts assessments of the reslence and strength of the fnancal system.

More information

Teaching Note on Factor Model with a View --- A tutorial. This version: May 15, Prepared by Zhi Da *

Teaching Note on Factor Model with a View --- A tutorial. This version: May 15, Prepared by Zhi Da * Copyrght by Zh Da and Rav Jagannathan Teachng Note on For Model th a Ve --- A tutoral Ths verson: May 5, 2005 Prepared by Zh Da * Ths tutoral demonstrates ho to ncorporate economc ves n optmal asset allocaton

More information

ECE 586GT: Problem Set 2: Problems and Solutions Uniqueness of Nash equilibria, zero sum games, evolutionary dynamics

ECE 586GT: Problem Set 2: Problems and Solutions Uniqueness of Nash equilibria, zero sum games, evolutionary dynamics Unversty of Illnos Fall 08 ECE 586GT: Problem Set : Problems and Solutons Unqueness of Nash equlbra, zero sum games, evolutonary dynamcs Due: Tuesday, Sept. 5, at begnnng of class Readng: Course notes,

More information

Taxation and Externalities. - Much recent discussion of policy towards externalities, e.g., global warming debate/kyoto

Taxation and Externalities. - Much recent discussion of policy towards externalities, e.g., global warming debate/kyoto Taxaton and Externaltes - Much recent dscusson of polcy towards externaltes, e.g., global warmng debate/kyoto - Increasng share of tax revenue from envronmental taxaton 6 percent n OECD - Envronmental

More information

Appendix - Normally Distributed Admissible Choices are Optimal

Appendix - Normally Distributed Admissible Choices are Optimal Appendx - Normally Dstrbuted Admssble Choces are Optmal James N. Bodurtha, Jr. McDonough School of Busness Georgetown Unversty and Q Shen Stafford Partners Aprl 994 latest revson September 00 Abstract

More information

Final Exam. 7. (10 points) Please state whether each of the following statements is true or false. No explanation needed.

Final Exam. 7. (10 points) Please state whether each of the following statements is true or false. No explanation needed. Fnal Exam Fall 4 Econ 8-67 Closed Book. Formula Sheet Provded. Calculators OK. Tme Allowed: hours Please wrte your answers on the page below each queston. (5 ponts) Assume that the rsk-free nterest rate

More information

UNIVERSITY OF NOTTINGHAM

UNIVERSITY OF NOTTINGHAM UNIVERSITY OF NOTTINGHAM SCHOOL OF ECONOMICS DISCUSSION PAPER 99/28 Welfare Analyss n a Cournot Game wth a Publc Good by Indraneel Dasgupta School of Economcs, Unversty of Nottngham, Nottngham NG7 2RD,

More information

c slope = -(1+i)/(1+π 2 ) MRS (between consumption in consecutive time periods) price ratio (across consecutive time periods)

c slope = -(1+i)/(1+π 2 ) MRS (between consumption in consecutive time periods) price ratio (across consecutive time periods) CONSUMPTION-SAVINGS FRAMEWORK (CONTINUED) SEPTEMBER 24, 2013 The Graphcs of the Consumpton-Savngs Model CONSUMER OPTIMIZATION Consumer s decson problem: maxmze lfetme utlty subject to lfetme budget constrant

More information

A Theory of Predation Based on Agency Problems in Financial Contracting

A Theory of Predation Based on Agency Problems in Financial Contracting A Theory of Predaton Based on Agency Problems n Fnancal Contractng Patrck Bolton, Davd S. Scharfsten The Amercan Economc evew, Volume 80, Issue Mar., 990, 93-06. Presented by Tatana Levna The Borrower-Lender

More information

University of Toronto November 9, 2006 ECO 209Y MACROECONOMIC THEORY. Term Test #1 L0101 L0201 L0401 L5101 MW MW 1-2 MW 2-3 W 6-8

University of Toronto November 9, 2006 ECO 209Y MACROECONOMIC THEORY. Term Test #1 L0101 L0201 L0401 L5101 MW MW 1-2 MW 2-3 W 6-8 Department of Economcs Prof. Gustavo Indart Unversty of Toronto November 9, 2006 SOLUTION ECO 209Y MACROECONOMIC THEORY Term Test #1 A LAST NAME FIRST NAME STUDENT NUMBER Crcle your secton of the course:

More information

University of Toronto November 9, 2006 ECO 209Y MACROECONOMIC THEORY. Term Test #1 L0101 L0201 L0401 L5101 MW MW 1-2 MW 2-3 W 6-8

University of Toronto November 9, 2006 ECO 209Y MACROECONOMIC THEORY. Term Test #1 L0101 L0201 L0401 L5101 MW MW 1-2 MW 2-3 W 6-8 Department of Economcs Prof. Gustavo Indart Unversty of Toronto November 9, 2006 SOLUTION ECO 209Y MACROECONOMIC THEORY Term Test #1 C LAST NAME FIRST NAME STUDENT NUMBER Crcle your secton of the course:

More information

Macroeconomic equilibrium in the short run: the Money market

Macroeconomic equilibrium in the short run: the Money market Macroeconomc equlbrum n the short run: the Money market 2013 1. The bg pcture Overvew Prevous lecture How can we explan short run fluctuatons n GDP? Key assumpton: stcky prces Equlbrum of the goods market

More information

Clearing Notice SIX x-clear Ltd

Clearing Notice SIX x-clear Ltd Clearng Notce SIX x-clear Ltd 1.0 Overvew Changes to margn and default fund model arrangements SIX x-clear ( x-clear ) s closely montorng the CCP envronment n Europe as well as the needs of ts Members.

More information

OPERATIONS RESEARCH. Game Theory

OPERATIONS RESEARCH. Game Theory OPERATIONS RESEARCH Chapter 2 Game Theory Prof. Bbhas C. Gr Department of Mathematcs Jadavpur Unversty Kolkata, Inda Emal: bcgr.umath@gmal.com 1.0 Introducton Game theory was developed for decson makng

More information

REFINITIV INDICES PRIVATE EQUITY BUYOUT INDEX METHODOLOGY

REFINITIV INDICES PRIVATE EQUITY BUYOUT INDEX METHODOLOGY REFINITIV INDICES PRIVATE EQUITY BUYOUT INDEX METHODOLOGY 1 Table of Contents INTRODUCTION 3 TR Prvate Equty Buyout Index 3 INDEX COMPOSITION 3 Sector Portfolos 4 Sector Weghtng 5 Index Rebalance 5 Index

More information

Ch Rival Pure private goods (most retail goods) Non-Rival Impure public goods (internet service)

Ch Rival Pure private goods (most retail goods) Non-Rival Impure public goods (internet service) h 7 1 Publc Goods o Rval goods: a good s rval f ts consumpton by one person precludes ts consumpton by another o Excludable goods: a good s excludable f you can reasonably prevent a person from consumng

More information

Supplement to Holmström & Tirole: Market equilibrium. The model outlined in Holmström and Tirole (1997) illustrates the role of capital,

Supplement to Holmström & Tirole: Market equilibrium. The model outlined in Holmström and Tirole (1997) illustrates the role of capital, 1 Jon Vsle; Septemer 2014 and out ECON 4335 Economcs of Bankng Supplement to olmström & Trole: Market equlrum The model outlned n olmström and Trole (1997) llustrates the role of captal, oth among entrepreneurs,

More information

Survey of Math: Chapter 22: Consumer Finance Borrowing Page 1

Survey of Math: Chapter 22: Consumer Finance Borrowing Page 1 Survey of Math: Chapter 22: Consumer Fnance Borrowng Page 1 APR and EAR Borrowng s savng looked at from a dfferent perspectve. The dea of smple nterest and compound nterest stll apply. A new term s the

More information

Uniform Output Subsidies in Economic Unions versus Profit-shifting Export Subsidies

Uniform Output Subsidies in Economic Unions versus Profit-shifting Export Subsidies nform Output Subsdes n Economc nons versus Proft-shftng Export Subsdes Bernardo Moreno nversty of Málaga and José L. Torres nversty of Málaga Abstract Ths paper focuses on the effect of output subsdes

More information

Least Cost Strategies for Complying with New NOx Emissions Limits

Least Cost Strategies for Complying with New NOx Emissions Limits Least Cost Strateges for Complyng wth New NOx Emssons Lmts Internatonal Assocaton for Energy Economcs New England Chapter Presented by Assef A. Zoban Tabors Caramans & Assocates Cambrdge, MA 02138 January

More information

Equilibrium in Prediction Markets with Buyers and Sellers

Equilibrium in Prediction Markets with Buyers and Sellers Equlbrum n Predcton Markets wth Buyers and Sellers Shpra Agrawal Nmrod Megddo Benamn Armbruster Abstract Predcton markets wth buyers and sellers of contracts on multple outcomes are shown to have unque

More information

FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS. Richard M. Levich. New York University Stern School of Business. Revised, February 1999

FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS. Richard M. Levich. New York University Stern School of Business. Revised, February 1999 FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS by Rchard M. Levch New York Unversty Stern School of Busness Revsed, February 1999 1 SETTING UP THE PROBLEM The bond s beng sold to Swss nvestors for a prce

More information

Economics 1410 Fall Section 7 Notes 1. Define the tax in a flexible way using T (z), where z is the income reported by the agent.

Economics 1410 Fall Section 7 Notes 1. Define the tax in a flexible way using T (z), where z is the income reported by the agent. Economcs 1410 Fall 2017 Harvard Unversty Yaan Al-Karableh Secton 7 Notes 1 I. The ncome taxaton problem Defne the tax n a flexble way usng T (), where s the ncome reported by the agent. Retenton functon:

More information

15-451/651: Design & Analysis of Algorithms January 22, 2019 Lecture #3: Amortized Analysis last changed: January 18, 2019

15-451/651: Design & Analysis of Algorithms January 22, 2019 Lecture #3: Amortized Analysis last changed: January 18, 2019 5-45/65: Desgn & Analyss of Algorthms January, 09 Lecture #3: Amortzed Analyss last changed: January 8, 09 Introducton In ths lecture we dscuss a useful form of analyss, called amortzed analyss, for problems

More information

Optimal Service-Based Procurement with Heterogeneous Suppliers

Optimal Service-Based Procurement with Heterogeneous Suppliers Optmal Servce-Based Procurement wth Heterogeneous Supplers Ehsan Elah 1 Saf Benjaafar 2 Karen L. Donohue 3 1 College of Management, Unversty of Massachusetts, Boston, MA 02125 2 Industral & Systems Engneerng,

More information

Applications of Myerson s Lemma

Applications of Myerson s Lemma Applcatons of Myerson s Lemma Professor Greenwald 28-2-7 We apply Myerson s lemma to solve the sngle-good aucton, and the generalzaton n whch there are k dentcal copes of the good. Our objectve s welfare

More information

Problem Set #4 Solutions

Problem Set #4 Solutions 4.0 Sprng 00 Page Problem Set #4 Solutons Problem : a) The extensve form of the game s as follows: (,) Inc. (-,-) Entrant (0,0) Inc (5,0) Usng backwards nducton, the ncumbent wll always set hgh prces,

More information

Macroeconomic Theory and Policy

Macroeconomic Theory and Policy ECO 209 Macroeconomc Theory and Polcy Lecture 7: The Open Economy wth Fxed Exchange Rates Gustavo Indart Slde 1 Open Economy under Fxed Exchange Rates Let s consder an open economy wth no captal moblty

More information

Risk and Return: The Security Markets Line

Risk and Return: The Security Markets Line FIN 614 Rsk and Return 3: Markets Professor Robert B.H. Hauswald Kogod School of Busness, AU 1/25/2011 Rsk and Return: Markets Robert B.H. Hauswald 1 Rsk and Return: The Securty Markets Lne From securtes

More information

Solution of periodic review inventory model with general constrains

Solution of periodic review inventory model with general constrains Soluton of perodc revew nventory model wth general constrans Soluton of perodc revew nventory model wth general constrans Prof Dr J Benkő SZIU Gödöllő Summary Reasons for presence of nventory (stock of

More information

Domestic Savings and International Capital Flows

Domestic Savings and International Capital Flows Domestc Savngs and Internatonal Captal Flows Martn Feldsten and Charles Horoka The Economc Journal, June 1980 Presented by Mchael Mbate and Chrstoph Schnke Introducton The 2 Vews of Internatonal Captal

More information

Fall 2016 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out

Fall 2016 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out Economcs 435 Menze D. Cnn Fall 6 Socal Scences 748 Unversty of Wsconsn-Madson. Standard IS-LM Transactons and ortfolo Crowdng Out Transactons crowdng out of nvestment s te reducton n nvestment attrbutable

More information

Mutual Funds and Management Styles. Active Portfolio Management

Mutual Funds and Management Styles. Active Portfolio Management utual Funds and anagement Styles ctve Portfolo anagement ctve Portfolo anagement What s actve portfolo management? How can we measure the contrbuton of actve portfolo management? We start out wth the CP

More information

CS 286r: Matching and Market Design Lecture 2 Combinatorial Markets, Walrasian Equilibrium, Tâtonnement

CS 286r: Matching and Market Design Lecture 2 Combinatorial Markets, Walrasian Equilibrium, Tâtonnement CS 286r: Matchng and Market Desgn Lecture 2 Combnatoral Markets, Walrasan Equlbrum, Tâtonnement Matchng and Money Recall: Last tme we descrbed the Hungaran Method for computng a maxmumweght bpartte matchng.

More information

Online Appendix for Merger Review for Markets with Buyer Power

Online Appendix for Merger Review for Markets with Buyer Power Onlne Appendx for Merger Revew for Markets wth Buyer Power Smon Loertscher Lesle M. Marx July 23, 2018 Introducton In ths appendx we extend the framework of Loertscher and Marx (forthcomng) to allow two

More information

Spring 2018 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out

Spring 2018 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out Economcs 44 Menze D. Cnn Sprng 8 Socal Scences 748 Unversty of Wsconsn-Madson. Standard IS-LM Transactons and Portfolo Crowdng Out Transactons crowdng out of nvestment s te reducton n nvestment attrbutable

More information

Lecture Note 2 Time Value of Money

Lecture Note 2 Time Value of Money Seg250 Management Prncples for Engneerng Managers Lecture ote 2 Tme Value of Money Department of Systems Engneerng and Engneerng Management The Chnese Unversty of Hong Kong Interest: The Cost of Money

More information

Political Economy of International Policy Coordination for Market Regulation

Political Economy of International Policy Coordination for Market Regulation Poltcal Economy of Internatonal Polcy Coordnaton for Market Regulaton August, 2009 Young-Han Km* and S. Km Abstracts: Wth the recent advent of the global fnancal crss ntated by the collapse of the US mortgage

More information

ECO 209Y MACROECONOMIC THEORY AND POLICY LECTURE 11: THE IS-LM MODEL AND EXOGENOUS/ENDOGENOUS MONEY

ECO 209Y MACROECONOMIC THEORY AND POLICY LECTURE 11: THE IS-LM MODEL AND EXOGENOUS/ENDOGENOUS MONEY ECO 209Y MCROECONOMIC THEORY ND POLICY LECTURE 11: THE IS-LM MODEL ND EXOGENOUS/ENDOGENOUS MONEY Gustavo Indart Slde 1 KEYNESIN MONETRY THEORY EXOGENOUS MONEY SUPPLY Gustavo Indart Slde 2 Keynes treated

More information

Assessment of Liquidity Risk Management in Islamic Banking Industry (Case of Indonesia)

Assessment of Liquidity Risk Management in Islamic Banking Industry (Case of Indonesia) Assessment of Lqudty Rsk Management n Islamc Bankng Industry (Case of Indonesa) Paper Presented n The 1 st UK Conference on Islamc Bankng and Fnance Dssertatons London School of Economcs, July 6 th, 2008

More information

Lecture 7. We now use Brouwer s fixed point theorem to prove Nash s theorem.

Lecture 7. We now use Brouwer s fixed point theorem to prove Nash s theorem. Topcs on the Border of Economcs and Computaton December 11, 2005 Lecturer: Noam Nsan Lecture 7 Scrbe: Yoram Bachrach 1 Nash s Theorem We begn by provng Nash s Theorem about the exstance of a mxed strategy

More information

Jeffrey Ely. October 7, This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License.

Jeffrey Ely. October 7, This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. October 7, 2012 Ths work s lcensed under the Creatve Commons Attrbuton-NonCommercal-ShareAlke 3.0 Lcense. Recap We saw last tme that any standard of socal welfare s problematc n a precse sense. If we want

More information

Spring 2010 Social Sciences 7418 University of Wisconsin-Madison. The Financial and Economic Crisis Interpreted in a CC-LM Model

Spring 2010 Social Sciences 7418 University of Wisconsin-Madison. The Financial and Economic Crisis Interpreted in a CC-LM Model Publc Affars 854 Menze D. Chnn Sprng 2010 Socal Scences 7418 Unversty of Wsconsn-Madson The Fnancal and Economc Crss Interpreted n a CC-LM Model 1. Background: Typcal Fnancal Crss Source: Mshkn 2. Theory:

More information

ECON 4921: Lecture 12. Jon Fiva, 2009

ECON 4921: Lecture 12. Jon Fiva, 2009 ECON 4921: Lecture 12 Jon Fva, 2009 Roadmap 1. Introducton 2. Insttutons and Economc Performance 3. The Frm 4. Organzed Interest and Ownershp 5. Complementarty of Insttutons 6. Insttutons and Commtment

More information

Liquidity Management in Banking: What is the Role of Leverage?

Liquidity Management in Banking: What is the Role of Leverage? Lqudty Management n Bankng: What s the Role of Leverage? Fabana Gomez y Quynh - Anh Vo z September 2016 Abstract Ths paper examnes potental mpacts of banks leverage on ther ncentves to manage ther lqudty.

More information

General Examination in Microeconomic Theory. Fall You have FOUR hours. 2. Answer all questions

General Examination in Microeconomic Theory. Fall You have FOUR hours. 2. Answer all questions HARVARD UNIVERSITY DEPARTMENT OF ECONOMICS General Examnaton n Mcroeconomc Theory Fall 2010 1. You have FOUR hours. 2. Answer all questons PLEASE USE A SEPARATE BLUE BOOK FOR EACH QUESTION AND WRITE THE

More information

Dynamic Analysis of Knowledge Sharing of Agents with. Heterogeneous Knowledge

Dynamic Analysis of Knowledge Sharing of Agents with. Heterogeneous Knowledge Dynamc Analyss of Sharng of Agents wth Heterogeneous Kazuyo Sato Akra Namatame Dept. of Computer Scence Natonal Defense Academy Yokosuka 39-8686 JAPAN E-mal {g40045 nama} @nda.ac.jp Abstract In ths paper

More information

Jenee Stephens, Dave Seerattan, DeLisle Worrell Caribbean Center for Money and Finance 41 st Annual Monetary Studies Conference November 10 13, 2009

Jenee Stephens, Dave Seerattan, DeLisle Worrell Caribbean Center for Money and Finance 41 st Annual Monetary Studies Conference November 10 13, 2009 Jenee Stephens, ave Seerattan, esle Worrell Carbbean Center for Money and nance 41 st Annual Monetary Studes Conference November 10 13, 2009 1 OUTINE! Introducton! Revew of lterature! The Model! Prelmnary

More information

Investment Management Active Portfolio Management

Investment Management Active Portfolio Management Investment Management Actve Portfolo Management Road Map The Effcent Markets Hypothess (EMH) and beatng the market Actve portfolo management Market tmng Securty selecton Securty selecton: Treynor&Black

More information

IND E 250 Final Exam Solutions June 8, Section A. Multiple choice and simple computation. [5 points each] (Version A)

IND E 250 Final Exam Solutions June 8, Section A. Multiple choice and simple computation. [5 points each] (Version A) IND E 20 Fnal Exam Solutons June 8, 2006 Secton A. Multple choce and smple computaton. [ ponts each] (Verson A) (-) Four ndependent projects, each wth rsk free cash flows, have the followng B/C ratos:

More information

Problems to be discussed at the 5 th seminar Suggested solutions

Problems to be discussed at the 5 th seminar Suggested solutions ECON4260 Behavoral Economcs Problems to be dscussed at the 5 th semnar Suggested solutons Problem 1 a) Consder an ultmatum game n whch the proposer gets, ntally, 100 NOK. Assume that both the proposer

More information

Two Period Models. 1. Static Models. Econ602. Spring Lutz Hendricks

Two Period Models. 1. Static Models. Econ602. Spring Lutz Hendricks Two Perod Models Econ602. Sprng 2005. Lutz Hendrcks The man ponts of ths secton are: Tools: settng up and solvng a general equlbrum model; Kuhn-Tucker condtons; solvng multperod problems Economc nsghts:

More information

LECTURE 3. Chapter # 5: Understanding Interest Rates: Determinants and Movements

LECTURE 3. Chapter # 5: Understanding Interest Rates: Determinants and Movements LECTURE 3 Hamza Al alk Econ 3215: oney and ankng Wnter 2007 Chapter # 5: Understandng Interest Rates: Determnants and ovements The Loanable Funds Approach suggests that nterest rate levels are determned

More information

5. Market Structure and International Trade. Consider the role of economies of scale and market structure in generating intra-industry trade.

5. Market Structure and International Trade. Consider the role of economies of scale and market structure in generating intra-industry trade. Rose-Hulman Insttute of Technology GL458, Internatonal Trade & Globalzaton / K. Chrst 5. Market Structure and Internatonal Trade Learnng Objectves 5. Market Structure and Internatonal Trade Consder the

More information

/ Computational Genomics. Normalization

/ Computational Genomics. Normalization 0-80 /02-70 Computatonal Genomcs Normalzaton Gene Expresson Analyss Model Computatonal nformaton fuson Bologcal regulatory networks Pattern Recognton Data Analyss clusterng, classfcaton normalzaton, mss.

More information

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 9

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 9 Elton, Gruber, Brown, and Goetzmann Modern Portfolo Theory and Investment Analyss, 7th Edton Solutons to Text Problems: Chapter 9 Chapter 9: Problem In the table below, gven that the rskless rate equals

More information

Random Variables. b 2.

Random Variables. b 2. Random Varables Generally the object of an nvestgators nterest s not necessarly the acton n the sample space but rather some functon of t. Techncally a real valued functon or mappng whose doman s the sample

More information

references Chapters on game theory in Mas-Colell, Whinston and Green

references Chapters on game theory in Mas-Colell, Whinston and Green Syllabus. Prelmnares. Role of game theory n economcs. Normal and extensve form of a game. Game-tree. Informaton partton. Perfect recall. Perfect and mperfect nformaton. Strategy.. Statc games of complete

More information

Privatization and government preference in an international Cournot triopoly

Privatization and government preference in an international Cournot triopoly Fernanda A Ferrera Flávo Ferrera Prvatzaton and government preference n an nternatonal Cournot tropoly FERNANDA A FERREIRA and FLÁVIO FERREIRA Appled Management Research Unt (UNIAG School of Hosptalty

More information

MgtOp 215 Chapter 13 Dr. Ahn

MgtOp 215 Chapter 13 Dr. Ahn MgtOp 5 Chapter 3 Dr Ahn Consder two random varables X and Y wth,,, In order to study the relatonshp between the two random varables, we need a numercal measure that descrbes the relatonshp The covarance

More information

In the 1990s, Japanese economy has experienced a surge in the unemployment rate,

In the 1990s, Japanese economy has experienced a surge in the unemployment rate, Productvty Growth and the female labor supply n Japan Yoko Furukawa * Tomohko Inu Abstract: In the 990s, Japanese economy has experenced a surge n the unemployment rate, and ths s due partly to the recent

More information

iii) pay F P 0,T = S 0 e δt when stock has dividend yield δ.

iii) pay F P 0,T = S 0 e δt when stock has dividend yield δ. Fnal s Wed May 7, 12:50-2:50 You are allowed 15 sheets of notes and a calculator The fnal s cumulatve, so you should know everythng on the frst 4 revews Ths materal not on those revews 184) Suppose S t

More information

Tests for Two Correlations

Tests for Two Correlations PASS Sample Sze Software Chapter 805 Tests for Two Correlatons Introducton The correlaton coeffcent (or correlaton), ρ, s a popular parameter for descrbng the strength of the assocaton between two varables.

More information

ASSET OWNERSHIP AND IMPLICIT CONTRACTS*

ASSET OWNERSHIP AND IMPLICIT CONTRACTS* - 1 - ASSET OWNERSHIP AND IMPLICIT CONTRACTS* Iver Bragelen December 1998 Department of Fnance and Management Scence Norwegan School of Economcs and Busness Admnstraton N-5035 Bergen-Sandvken, Norway.

More information

Tradable Emissions Permits in the Presence of Trade Distortions

Tradable Emissions Permits in the Presence of Trade Distortions 85 Tradable Emssons Permts n the Presence of Trade Dstortons Shnya Kawahara Abstract Ths paper nvestgates how trade lberalzaton affects domestc emssons tradng scheme n a poltcal economy framework. Developng

More information

Introduction to game theory

Introduction to game theory Introducton to game theory Lectures n game theory ECON5210, Sprng 2009, Part 1 17.12.2008 G.B. Ashem, ECON5210-1 1 Overvew over lectures 1. Introducton to game theory 2. Modelng nteractve knowledge; equlbrum

More information

Credit Default Swaps in General Equilibrium: Spillovers, Credit Spreads, and Endogenous Default

Credit Default Swaps in General Equilibrium: Spillovers, Credit Spreads, and Endogenous Default Credt Default Swaps n General Equlbrum: Spllovers, Credt Spreads, and Endogenous Default R. Matthew Darst Ehraz Refayet June 2, 2016 Keywords: credt dervatves, spllovers, nvestment, default rsk. JEL Classfcaton:

More information

ECO 209Y MACROECONOMIC THEORY AND POLICY LECTURE 8: THE OPEN ECONOMY WITH FIXED EXCHANGE RATES

ECO 209Y MACROECONOMIC THEORY AND POLICY LECTURE 8: THE OPEN ECONOMY WITH FIXED EXCHANGE RATES ECO 209 MACROECONOMIC THEOR AND POLIC LECTURE 8: THE OPEN ECONOM WITH FIXED EXCHANGE RATES Gustavo Indart Slde 1 OPEN ECONOM UNDER FIXED EXCHANGE RATES Let s consder an open economy wth no captal moblty

More information

A Utilitarian Approach of the Rawls s Difference Principle

A Utilitarian Approach of the Rawls s Difference Principle 1 A Utltaran Approach of the Rawls s Dfference Prncple Hyeok Yong Kwon a,1, Hang Keun Ryu b,2 a Department of Poltcal Scence, Korea Unversty, Seoul, Korea, 136-701 b Department of Economcs, Chung Ang Unversty,

More information

THE VOLATILITY OF EQUITY MUTUAL FUND RETURNS

THE VOLATILITY OF EQUITY MUTUAL FUND RETURNS North Amercan Journal of Fnance and Bankng Research Vol. 4. No. 4. 010. THE VOLATILITY OF EQUITY MUTUAL FUND RETURNS Central Connectcut State Unversty, USA. E-mal: BelloZ@mal.ccsu.edu ABSTRACT I nvestgated

More information

3/3/2014. CDS M Phil Econometrics. Vijayamohanan Pillai N. Truncated standard normal distribution for a = 0.5, 0, and 0.5. CDS Mphil Econometrics

3/3/2014. CDS M Phil Econometrics. Vijayamohanan Pillai N. Truncated standard normal distribution for a = 0.5, 0, and 0.5. CDS Mphil Econometrics Lmted Dependent Varable Models: Tobt an Plla N 1 CDS Mphl Econometrcs Introducton Lmted Dependent Varable Models: Truncaton and Censorng Maddala, G. 1983. Lmted Dependent and Qualtatve Varables n Econometrcs.

More information

Intensive vs Extensive Margin Tradeo s in a Simple Monetary Search Model

Intensive vs Extensive Margin Tradeo s in a Simple Monetary Search Model Intensve vs Extensve Margn Tradeo s n a Smple Monetary Search Model Sébasten Lotz y Unversty of Pars 2 Andre Shevchenko z Mchgan State Unversty Aprl 2006 hrstopher Waller x Unversty of Notre Dame Abstract

More information

Interregional Trade, Industrial Location and. Import Infrastructure*

Interregional Trade, Industrial Location and. Import Infrastructure* Interregonal Trade, Industral Locaton and Import Infrastructure* Toru Kkuch (Kobe Unversty) and Kazumch Iwasa (Kyoto Unversty)** Abstract The purpose of ths study s to llustrate, wth a smple two-regon,

More information

Scribe: Chris Berlind Date: Feb 1, 2010

Scribe: Chris Berlind Date: Feb 1, 2010 CS/CNS/EE 253: Advanced Topcs n Machne Learnng Topc: Dealng wth Partal Feedback #2 Lecturer: Danel Golovn Scrbe: Chrs Berlnd Date: Feb 1, 2010 8.1 Revew In the prevous lecture we began lookng at algorthms

More information

4: SPOT MARKET MODELS

4: SPOT MARKET MODELS 4: SPOT MARKET MODELS INCREASING COMPETITION IN THE BRITISH ELECTRICITY SPOT MARKET Rchard Green (1996) - Journal of Industral Economcs, Vol. XLIV, No. 2 PEKKA SULAMAA The obect of the paper Dfferent polcy

More information

MULTIPLE CURVE CONSTRUCTION

MULTIPLE CURVE CONSTRUCTION MULTIPLE CURVE CONSTRUCTION RICHARD WHITE 1. Introducton In the post-credt-crunch world, swaps are generally collateralzed under a ISDA Master Agreement Andersen and Pterbarg p266, wth collateral rates

More information

Borrowing Constraint and the Effect of Option Introduction

Borrowing Constraint and the Effect of Option Introduction Insttut des Hautes Etudes Commercales de Carthage From the electedworks of Khaled Bennour 00 Borrowng Constrant and the Effect of Opton Introducton Khaled Amra, uffolk Unversty Khaled Bennour, Insttut

More information

Evaluating Performance

Evaluating Performance 5 Chapter Evaluatng Performance In Ths Chapter Dollar-Weghted Rate of Return Tme-Weghted Rate of Return Income Rate of Return Prncpal Rate of Return Daly Returns MPT Statstcs 5- Measurng Rates of Return

More information

CHAPTER 9 FUNCTIONAL FORMS OF REGRESSION MODELS

CHAPTER 9 FUNCTIONAL FORMS OF REGRESSION MODELS CHAPTER 9 FUNCTIONAL FORMS OF REGRESSION MODELS QUESTIONS 9.1. (a) In a log-log model the dependent and all explanatory varables are n the logarthmc form. (b) In the log-ln model the dependent varable

More information

GOODS AND FINANCIAL MARKETS: IS-LM MODEL SHORT RUN IN A CLOSED ECONOMIC SYSTEM

GOODS AND FINANCIAL MARKETS: IS-LM MODEL SHORT RUN IN A CLOSED ECONOMIC SYSTEM GOODS ND FINNCIL MRKETS: IS-LM MODEL SHORT RUN IN CLOSED ECONOMIC SSTEM THE GOOD MRKETS ND IS CURVE The Good markets assumpton: The producton s equal to the demand for goods Z; The demand s the sum of

More information

INTRODUCTION TO MACROECONOMICS FOR THE SHORT RUN (CHAPTER 1) WHY STUDY BUSINESS CYCLES? The intellectual challenge: Why is economic growth irregular?

INTRODUCTION TO MACROECONOMICS FOR THE SHORT RUN (CHAPTER 1) WHY STUDY BUSINESS CYCLES? The intellectual challenge: Why is economic growth irregular? INTRODUCTION TO MACROECONOMICS FOR THE SHORT RUN (CHATER 1) WHY STUDY BUSINESS CYCLES? The ntellectual challenge: Why s economc groth rregular? The socal challenge: Recessons and depressons cause elfare

More information