Group lending, local information and peer selection 1


 Randall Ward
 1 years ago
 Views:
Transcription
1 Journal of Develoment Economics Ž. Vol Grou lending, local information and eer selection 1 Maitreesh Ghatak ) Deartment of Economics, niõersity of Chicago, Chicago, IL 60637, SA Abstract This aer analyzes how grou lending rograms use joint liability to utilize local information that borrowers have about each other s rojects through selfselection of grou members in the grou formation stage. These schemes are shown to lead to ositive assortative matching in grou formation. Faced with the same contract, this makes the effective cost of borrowing lower to safer borrowers: because they have safer artners, conditional on success their exected dues to the lender are lower than that of riskier borrowers. The resulting imrovement in the ool of borrowers is shown to increase reayment rates and welfare. q 1999 Elsevier Science B.V. All rights reserved. JEL classification: D8; L14; 01; 017 Keywords: Grou lending; Local information; Peer selection 1. Introduction Recent research on rural credit markets in develoing countries has focused on imerfect information and transaction costs in the lending rocess as the key to understand the reorted henomena of high interest rates, market segmentation and credit rationing. This has, led to a greater areciation of the fundamental disadvantages faced by formal lending institutions Že.g., the commercial banking ) 1 This aer is based on the first chater of my PhD thesis entitled Essays on the Economics of Contracts submitted to Harvard niversity Ž June, that was circulated earlier as the working aer Grou Lending and the Peer Selection Effect Ž November, See Hoff and Stiglitz Ž for a review of the recent theoretical and emirical literature r99r$  see front matter q 1999 Elsevier Science B.V. All rights reserved. Ž. PII: S
2 8 ( ) M. GhatakrJournal of DeÕeloment Economics sector and government lending agencies. in this market owing to the costliness of screening loan alicants, monitoring borrowers, and writing and enforcing contracts due to imerfections in the judicial system, backward infrastructure Že.g., transort and communication., and low levels of literacy Ž Besley, It has also rekindled interest in the role of alternative institutional arrangements, such as groulending rograms, credit cooeratives, and rotating saving and credit associations, to overcome these roblems. In this aer we focus on groulending rograms under which borrowers who cannot offer any collateral are asked to form small grous. Grou members are held jointly liable for the debts of each other. 3 Formally seaking, what joint liability does is to make any single borrower s terms of reayment conditional on the reayment erformance of other borrowers in a resecified and selfselected grou of borrowers. The remarkably successful exerience of some recent groulending rograms in terms of loan recovery rates, such as those in Bangladesh, Bolivia, Malawi, Thailand and Zimbabwe, has aroused a lot of interest in relicating them in other countries Ž Hui and Feder, A careful examination of the existing evidence on the relative erformance of these rograms comared to standard lending rograms across different countries yields a mixed icture ŽMorduch, 1998; Hui and Feder, Still, grou lending rograms where loans were made to homogenous selfselected grous of individuals belonging to the same village and with similar economic standing have tended to be more successful than others Ž Hui and Feder, We rovide a theory based on two contractual features of grou lending rograms to exlain why they can otentially achieve high reayment rates desite the fact that borrowers are not required to ut in any collateral: the existence of joint liability and the selection of grou members by borrowers themselves. As mentioned above, screening otential loan alicants is a costly activity for the lender. At the same time, borrowers from the same locality are exected to have some information about each other s rojects. Therefore, one way of looking at contracts based on selfformed grous is that they are a means of deliberately inducing borrowers to select their grou members in a way that exloits this local information. We use a simle adverse selection model to analyze this issue. In our model the borrowers know each others tyes, namely the robability of success of their 3 See Ghatak and Guinnane Ž for a discussion of how joint liability works in ractice. Credit cooeratives, which differ from grou lending rograms in that they borrow from outside sources as well as raise deosits from its own members, too often have some degree of joint liability. For examle, in German credit cooeratives, which first aeared in the middle of the last century and soon became very successful and influenced cooerative design everywhere else, all members of the cooerative were liable in whole or in art for any loan from an outside source on which a cooerative member defaulted. See Guinnane Ž
3 ( ) M. GhatakrJournal of DeÕeloment Economics rojects, but the outside bank does not. At the same time, collateral cannot be used because of the overty of the borrowers. This means loans have to be offered to all borrowers at the same nominal interest rate. Then, as in the lemons model of Akerlof Ž 1970., the resence of enough risky borrowers can ush the initial equilibrium interest rate high enough to drive the safe borrowers away from the market. We show that the joint liability asect of grou lending rograms induces borrowers of the same tye grou together in equilibrium. Given ositive assortative matching in grou formation, the effectiõe borrowing costs facing risky and safe borrowers are no longer the same. Conditional on success, a risky borrower faces a higher exected borrowing cost than a safe borrower because her artners are more likely to have failed. But this is recisely what a fullinformation credit contract would like to do borrowers with riskier rojects, because they succeed less often should ay more when they succeed. Facing a more favorable effective rate of interest, safer borrowers are shown to be attracted back into the market. This reduces the equilibrium interest rate, leads to an imrovement of the ool of borrowers, and increases the average reayment rate. Also, by attracting in safer and roductive rojects, which were not initially in the borrower ool as a result of the lemons roblem, joint liability imroves welfare from the oint of view of aggregate social surlus. Interestingly, even though riskier borrowers are burdened with higher exected jointliability ayments because they have riskier artners, the overall decrease in the interest rate ermitted by the entry of safe borrowers maybe significant enough to imrove the welfare of all tyes of borrowers in the ool. Hence we show that by exloiting an intangible resource, namely local information, that is embodied in secific social networks the institution of joint liability based grou lending can alleviate credit market failures. Hence, it serves the objectives of both efficiency and equity by heling the oor escae from the tra of overty by financing smallscale roductive rojects. 4 We examine one ossible mechanism through which grou lending can imrove efficiency based on the selfselection of borrower grous and the effect on the ool of borrowers. The existing research on the toic, until very recently, has exlored other mechanisms focusing mainly on the effect of joint liability on the 5 behaõior of individual borrowers. Early work by Stiglitz Ž and Varian Ž exlore how joint liability may induce borrowers in a grou to monitor each other, thereby alleviating moral hazard roblems. Besley and Coate Ž address the question how jointliability contracts affect the willingness to reay. They show how they may induce borrowers to ut eer ressure on delinquent 4 For an analysis of how an economy may get stuck in a overty tra due to credit market imerfections see Banerjee and Newman Ž See Ghatak and Guinnane Ž for a more detailed discussion.
4 30 ( ) M. GhatakrJournal of DeÕeloment Economics grou members, which may lead to an imrovement in reayment rates. However, none of these aers with the excetion of Varian Ž examine a crucial feature of these schemes, namely that grou members selfselect each other. Varian Ž rooses a model where the bank directly screens loan alicants and joint liability takes the following form: if the member who is interviewed turns out to be a bad risk all grou members are denied loans. This induces safe borrowers to undertake the task of screening out bad risks on behalf of the bank. In contrast, we show that joint liability lending can imrove efficiency even if there is no direct screening so that risky borrowers too can form a grou and aly for a loan. Because borrowers are shown to end u with artners of the same tye, for the same joint liability contract offered to all borrowers, safer borrowers face lower exected borrowing costs conditional on success. Aart from the current aer, a number of recent aers have studied various roles grou lending can lay in alleviating adverse selection roblems in rural credit markets. Among them, Van Tassel Ž has analyzed grou lending in a similar informational environment and has obtained some similar results on its effect on the formation of grous and reayment rates. However, our aers differ in terms of the model in several resects. For examle, we allow for a general distribution of borrower tyes and arbitrary grou sizes, while Van Tassel allows for variable loan sizes. Armendariz de Aghion and Gollier Ž is another aer that looks at a similar environment and shows that joint liability can imrove the ool of borrowers if borrowers have erfect knowledge of their artners. However, their aer does not formalize the grou formation game. Also, it does not exlore the otimal degree of joint liability Ž by assuming full joint liability. or the welfare imlications of grou lending. On the other hand, their aer, and more recently that of Laffont and N Guessan Ž 1999., address a question we do not consider at all namely, whether grou lending can imrove efficiency in environments with adverse selection where borrowers do not necessarily have better information about each other.. The economic environment We take a simle version of the standard model of a credit market with adverse selection. 6 Everyone lives for one eriod. Borrowers are risk neutral and are endowed with a risky investment roject that needs one unit of caital and one unit of labor. There is no moral hazard and agents suly labor to the roject inelastically. But they have no initial wealth and need to borrow the required amount of caital to launch their roject. 6 Ž. See Stiglitz and Weiss 1981.
5 ( ) M. GhatakrJournal of DeÕeloment Economics A borrower is characterized by the robability of success of her roject, gw, 1x where )0. The return of a roject of a borrower of tye is a random variable y which takes two values, RŽ.)0 if successful, and 0 if it fails for all gw, 1 x. The outcome of a roject is binary random variable, xgs, F4 where S denotes success and F denotes failure. The outcomes of the rojects are assumed to be indeendently distributed for the same tyes as well as across different tyes. 7 Borrowers of all tyes have an exogenously given reservation ayoff u which can be thought of as the market wage rate. We assume that the tye of a borrower is rivate information so that lenders cannot distinguish between different tyes of borrowers. However, borrowers know each other s tyes. This informational environment is fundamental to our model and it may be helful to think of lenders as institutions external to the village Ž e.g., citybased. whereas borrowers are all residents of the same village. The outcome of a roject, i.e., whether it has succeeded or failed, is costlessly observable by the bank and is verifiable as well. But the return of a roject, i.e., how much it yields if successful, is not observed by the bank. Hence, lenders can use only outcomecontingent contracts such as debt contracts and not returncontingent contracts, such as equity. 8 Borrowers have no wealth they can offer as collateral and moreover nonmonetary unishments are ruled out by a limitedliability constraint. We assume that enforcement costs are negligible once the bank receives the verifiable signal that a borrower s roject has been successful, the borrower cannot default. 9 We are going to focus on two tyes of credit contracts in this environment: indiõidualliability contracts and jointliability contracts. The former is a standard debt contract between a borrower and the bank with a fixed reayment r in the nonbankrutcy state Ž here x s S., and maximum recovery of debt in the bankrutcy state Ž xsf. which haens to be 0 in our model. The latter involves asking the borrowers to form grous of a certain size, and stiulating an individual liability comonent r, and a joint liability comonent, c. As in standard debt contracts, if the roject of a borrower fails then owing to the limitedliability constraint, she ays nothing to the bank. But if a borrower s roject is successful, then aart from reaying her own debt to the bank, r, she has to ay an additional 7 Elsewhere Ž Ghatak, we study the imlications of relaxing this assumtion. 8 In Ghatak and Guinnane Ž 1999., we show how this could be derived from an underlying costly state verification model Ž Townsend, The roblem of enforcement is undoubtedly of great ractical imortancein lending to the oor Ž because of limited sanctions against strategic default., and existing research Že.g., Besley and Coate, has shown how grou lending may alleviate this roblem. We make this assumtion to focus on the effect of joint liability on the selection of borrowers which is admittedly only one of several ossible channels through which grou lending can imrove reayment rates, but one which has been largely neglected in the literature so far.
6 3 ( ) M. GhatakrJournal of DeÕeloment Economics jointliability ayment, c, er member of her grou whose rojects have failed. Thus, unlike standard debt contracts, reayment is not fixed in nonbankrutcy states: it is contingent on the roject outcomes of a resecified set of other borrowers. 10 We model the lending side of the credit market as one where there is a single risk neutral bank that chooses the terms of the loans in order to maximize exected aggregate surlus subject to a zero rofit constraint and the relevant informational constraints. As a social welfare function, exected aggregate surlus can be interreted as the ex ante exected utility of the borrower before she knows her tye. 11 The bank can be thought of as a ublic lending institution or a nongovernmental organization Ž NGO. which is most often the case for observed grou lending schemes. We assume that the bank faces a erfectly elastic suly of funds from deositors at the safe rate of interest, r. We model grou lending as the following sequential game: first, the bank offers a contract secifying the interest rate, r, and the amount of joint liability, c, to the borrowers; second, borrowers who wish to accet the contract select their artners; finally, rojects are carried out and outcomecontingent transfers as secified in the contract are met. Borrowers who choose not to borrow enjoy their reservation ayoff of u. 3. Equilibrium in the grou formation game In this section we study the grou formation game under grou lending. For simlicity of exosition we consider grous of size in the aer. In Aendix A, we show how all our results generalize to grous of any size ng. We require the equilibrium in the grou formation game to satisfy the otimal sorting roerty Ž Becker, 1993.: borrowers not in the same grou should not be able to form a grou without making at least one of them worse off. 1 Our main 10 While there are some similarities between standard debt contracts with a cosigner and jointliability contracts used in groulending, there are two imortant differences: in the latter case the artner who can be viewed as a cosigner does not have to be an individual who is known to the bank andror owns some assets, and all members of the grou can be borrowers as well as cosignors on each other s loans at the same time. 11 Changes in social welfare can be measured by changes in aggregate surlus for any social welfare function when references are quasilinear so long as the lanner can make lum sum transfers. Although borrowers are riskneutral in our context and hence their references are quasilinear, since there is rivate information, lum sum transfers across borrower tyes are not feasible. Hence, aggregate exected surlus is no longer a valid welfare measure for any social welfare function. 1 The size of a grou that qualifies for a loan under a grou lending rogram is fixed by institutional design. In game theoretic terms, an assignment satisfying the otimal sorting roerty is in the core given this restriction on the size of ossible coalitions.
7 ( ) M. GhatakrJournal of DeÕeloment Economics result is that for any given jointliability credit contract Ž r,c. offered by the bank in the first stage, borrowers will choose artners of the same tye in the second stage. Consider a borrower with robability of success. The exected ayoff of this borrower under a given jointliability contract Ž r,c. when her artner has robability of success X is: E X Ž r,c. s X RŽ. yr qž 1y X. RŽ. yryc., Ž. Ž. srž. yrqcž 1y X. 4. We establish the following imortant roerty of joint liability: Lemma 1: A borrower of any tye refers a safer artner, but the safer the borrower herself, the more she Õalues a safer artner. Proof: The difference in the exected ayoff of a borrower of tye from having a artner who has robability of success X instead of Y is E X r,c ye Y r,c sc X y Y, Ž., Ž. Ž.. Ž 1. Suose X ) Y. In choosing between two otential artners with different robabilities of success X and Y, any borrower will be willing to ay a strictly ositive amount to have the borrower whose robability of success is X. But the maximum amount a borrower of tye is willing to ay to have a artner of tye X Y X over a artner of tye, cž y Y., is increasing in her own robability of success. B The intuition is as follows: conditional on her own roject being successful, the maximum amount a borrower of any tye would be willing to ay to have a artner who is safer than her existing artner is the amount of joint liability times the difference in the resective robabilities of not defaulting. 13 But this exected gain from having a safer artner is realized only when the borrower herself is successful, and hence is higher the safer her tye. Let us assume that the oulation of borrowers is balanced with resect to grou size, i.e., there are NŽ. borrowers of each tye, where NŽ. is a ositive integer. This ensures that any borrower can always find another borrower 13 Since we assume borrowers have no wealth that can be used as collateral, when we talk about side ayments among borrowers, we mean that these transfers take forms that are not feasible with the bank. For examle, borrowers within a social network can make transfers to each other in ways that are not ossible with an outsider Ž namely, the bank., such as roviding free labor services, or writing contracts based on the outut Ž as oosed to outcome. of their rojects.
8 34 ( ) M. GhatakrJournal of DeÕeloment Economics of the same tye to form a grou. In this case, we rove the following result regarding the equilibrium in the grou formation stage: Proosition 1: If the oulation of borrowers is balanced with resect to grou size, the unique assignment satisfying the otimal sorting roerty under groulending schemes based on joint liability is one where all borrowers in a giõen grou haõe the same robability of success. Proof: Start with the assignment where all grous are erfectly homogeneous. Consider the ossibility that a risky borrower might try to induce a safe borrower to be her artner by offering a side ayment. By Lemma 1, the exected gain to a borrower of tye X from leaving a artner of the same tye and having a artner X of tye where , namely, c X Ž y X., is less than the exected loss to a borrower of tye from leaving a artner of the same tye and having a artner X of tye,namely, cž y X.. Hence, a mutually rofitable transfer from a borrower of a riskier tye to a borrower of a safer tye to induce the latter to form a grou with the former does not exist and the initial assignment satisfies the otimal sorting roerty. Conversely, start with an assignment where all grous are not erfectly homogeneous and suose it satisfies the otimal sorting roerty. Within the set of all mixed grous, consider the subset of grous which have one borrower of the highest tye, namely, 1. Since the oulation of borrowers is balanced with resect to grou size, for every borrower of tye 1 in a mixed grou with a artner of tye 1, there will be another borrower of tye 1 in a mixed grou with a artner of tye X 1. By Lemma 1, if the two borrowers of tye 1 leave their existing artners and match together, their existing artners will not find it rofitable to induce them to remain by offering side ayments. Reeating this argument within the set of all remaining mixed grous iteratively, we comlete the roof that only erfectly homogeneous grous satisfy the otimal sorting roerty. B Intuitively, because a borrower with a high robability of success lace the highest value on having a artner with a high robability of success, they bid the most for these borrowers. As a result, borrowers of the same robability of success are matched together, just as artners of similar quality of are matched together in Becker s marriage model or to take a more recent examle, workers of the same skill are matched together in firms when they have Kremer s ORing roduction function. 14 The underlying force driving the ositive assortative matching result is also similar in these models: the tyes of agents are comlementary in the ayoff functions See Becker Ž 1993., Cha. 4, and Kremer Ž For examle, in our model ŽE E X Ž r,c.. ržee X. sc)0.,
9 ( ) M. GhatakrJournal of DeÕeloment Economics Notice that our roof uses only the fact that borrowers have different robabilities of success and does not deend on whether safe and risky borrowers have the same or different exected roject returns Ži.e., we make no assumtions about RŽ... In Aendix A we show that it also does not deend on whether borrowers have some wealth or not. However, if the oulation distribution of borrowers is not balanced with resect to grou size that requires some modifications to this result. In Aendix A we analyze this case. 4. Credit market equilibrium with adverse selection Let us assume now that there is a continuum of borrowers with robability of success gw,1x where ) 0 following the continuously differentiable density function of the robability of success gž.. The corresonding distribution function is denoted by GŽ.'H gž s. d s for gw,1 x. The size of the total oulation of borrowers in the village is normalized to unity. Following Stiglitz and Weiss Ž we assume that rojects have the same mean and differ only in terms of riskiness Žin the sense of secondorder stochastic dominance.: 16 RŽ. sr for all g,1 Assumtion 1 We assume that the rojects of borrowers are socially roductive in terms of exected returns given the oortunity costs of labor and caital: R)rqu. Assumtion 4.1. Lending with indiõidual liability We model lending with individual liability as the following sequential game: the bank moves first and announces an interest rate, r. Borrowers who wish to borrow at the interest rate r do so, rojects are carried out and outcomecontingent transfers as secified in the contract are met. Borrowers who choose not to borrow enjoy their reservation ayoff of u. As a benchmark, consider the case where the bank has full information about a borrower s tye. It can then offer loan contracts under which a borrower whose robability of success is ays the fullinformation interest rate r s rr when her roject succeeds, and nothing otherwise Ž by limited liability.. Since safe borrowers reay their loan more often they are charged a lower interest rate than risky tyes. Given this contract, the bank earns zero exected rofit er loan, all 16 Ž. Elsewhere Ghatak, 1999 we study the imlications of relaxing this assumtion on the distribution of roject returns.
10 36 ( ) M. GhatakrJournal of DeÕeloment Economics tyes of borrowers borrow in the second stage and hence aggregate exected surlus is maximized. If the bank cannot identify a borrower s tye then charging searate interest rates to different tyes of borrowers would not work. A risky borrower would have an incentive to retend to be a safe borrower and ay a lower interest rate, but the bank would not be able to break even if all tyes of borrowers borrow at that rate. It, therefore, has to offer the same interest rate to all borrowers given the absence of collateral or any other screening instrument in our environment. The exected ayoff to borrower of tye when the interest rate is r is E Ž r. sryr, g w,1 x. Let denote the robability of success of the marginal borrower, i.e., one who is indifferent between borrowing and not. nder lending with individual liability, at the interest rate r the marginal borrower has a robability of success given by: Ryu s ˆ. Ž. r It follows that d Ryu sy 0. Ž 3. dr r Intuitively, borrowers who strictly refer to borrow at the interest rate r must have Ryr)u or, . ˆ That is, they are riskier than the marginal borrower. This is a consequence of the fact under a debt contract borrowers of all tyes ay nothing if the roject fails and ay the same nominal interest rate r when their roject is successful. As a result, riskier borrowers face a lower exected interest rate and so an increase in r always reduces. ˆ Let denote the average robability of success in the ool of borrowers who choose to borrow at the interest rate r. In this case: H sg Ž s. d s s GŽ. Ž 4. Since all borrowers who strictly refer to borrow at the interest rate r are riskier than the marginal borrower, ). ˆ Ž 5. Moreover, differentiating Eq. Ž. 4 with resect to r and using Eqs. Ž. 3 and Ž. 5 we get: d g ˆ Ž. d s 1y 0 dr GŽ. dr ž /
11 ( ) M. GhatakrJournal of DeÕeloment Economics i.e., an increase in the interest rate reduces the aõerage robability of success in the ool of borrowers. The bank s objective is to choose an interest rate that maximizes exected aggregate surlus subject to the constraint that its exected rofit er loan is zero. Since the bank s rofits are negative for r0, we will restrict our attention to nonnegative values of r. If it offers an interest rate r in the first stage, it anticiates an average robability of reayment of er loan given the exected ool of borrowers in the second eriod. The equilibrium of the lending game with individual liability contracts is an interest rate r which is the outcome of the bank s otimization roblem: max rg0 H Ž Ryrs. g Ž s. d s s.t. ryrs0. Let VŽ r.'h Ž Ryrs. gž s. d ssž Ryr. GŽ. and Ž r.'ryr. Substitut ing rsr from the zero rofit condition into the bank s objective function we get VŽ r.' Ž Ryr. GŽ ˆ.. As a result, the bank s otimization roblem can be reformulated as one where it chooses the minimum ossible value of r Žwhich ensures the maximum ossible level of and hence VŽ r.. subject to the zero rofit condition: r sminrg0: Ž r. s04 Therefore, by definition Ž r. s0. Ž 6. Let and denote the robability of success of the marginal borrower and the average robability of success of the borrower ool at rsr. Let m denote the unconditional mean of the robability of success in the borrower oulation: H 1 m' sg Ž s. d s. Now we are ready to rove: Proosition : An equilibrium interest rate r exists and is unique under lending with indiõidual liability for all arameter Õalues satisfying Assumtions 1 and. If in addition r) Ž R y u. m, then indiõidual liability achieões a lower leõel of exected reayment rate and aggregate surlus comared to full information. HoweÕer, for rfž Ryu. m indiõidual liability achieões the same exected reayment rate and aggregate surlus as under full information.
12 38 ( ) M. GhatakrJournal of DeÕeloment Economics X Proof: If the bank charges the interest rate r sž Ryu. r then only borrowers with the lowest robability of success will be willing to borrow. Now lim Ž r. sr X lim yr X r r X r r X H sg Ž s. d s sr lim ˆ GŽ. yr Alying L Hoital s rule we have lim ŽŽH sgž s. d s. ržgž... ˆ ˆ s. Hence, X X lim X Ž r. r r sr yrsryuyr)0 by Assumtion. Also, for r)r, no one borrows so that VŽ r. s0 and the zero rofit condition is satisfied trivially. On the other hand, lim Ž r. syr 0. Since Ž r. is continuous in r Ž r 0 which follows from the fact that gž. and are continuous functions. there exists at least one value of r gž0, r X. and corresondingly gž,1. such that Ž r. s 0. By the continuity of Ž r., the set of values r satisfying Ž r. s0 is closed and bounded and so r s minr G 0: Ž r. s 04 exists and is unique. Since all borrowers of tye  borrow at this interest rate and so VŽr.)0. Hence, an equilibrium exists and is unique. Since Ž. 00, and by definition r is the lowest value of rgw0,r X x satisfying Ž r. s0, it must be the case the exected rofit of the bank should be ositively sloed with resect to r at r s r. That is, using Eqs. Ž. and Ž. 4, and the zerorofit condition Žwhich yields s rrr.: X Ž r. s qr d dr rsr Ž. Ž. g Ryuyr s 1y )0 Ž 7. GŽ. r where X Ž r.'d Ž r. rdr. We are ruling out the degenerate case where Ž r. is tangent to the horizontal axis at rsr, i.e., the ossibility that X Žr. s0. If condition Ž. 7 is not satisfied, the bank can cut the interest rate which will attract in more safe borrowers Ž thereby raising aggregate exected surlus. and make ositive rofits, which is inconsistent with equilibrium. Together, the conditions Ž. 6 and Ž. 7 comletely characterize the equilibrium under lending with individual liability. Notice that if Ž r.)0 for rsryu, then s1. ˆ In that case, in equilibrium, r will go down such that Ž r. s0 and will continue to remain at 1. In this case, the equilibrium under individual lending will achieve the firstbest. On the other hand if Ž Ryu. sž Ryu. myr0 then 1 and m and the exected reayment rate and aggregate surlus will be less than their firstbest levels. B
Screening by the Company You Keep: Joint Liability Lending and the Peer Selection Maitreesh Ghatak presented by Chi Wan
Screening by the Company You Keep: Joint Liability Lending and the Peer Selection Maitreesh Ghatak presented by Chi Wan 1. Introduction The paper looks at an economic environment where borrowers have some
More informationTHE WELFARE IMPLICATIONS OF COSTLY MONITORING IN THE CREDIT MARKET: A NOTE
The Economic Journal, 110 (Aril ), 576±580.. Published by Blackwell Publishers, 108 Cowley Road, Oxford OX4 1JF, UK and 50 Main Street, Malden, MA 02148, USA. THE WELFARE IMPLICATIONS OF COSTLY MONITORING
More informationWhat is Adverse Selection. Economics of Information and Contracts Adverse Selection. Lemons Problem. Lemons Problem
What is Adverse Selection Economics of Information and Contracts Adverse Selection Levent Koçkesen Koç University In markets with erfect information all rofitable trades (those in which the value to the
More informationI will make some additional remarks to my lecture on Monday. I think the main
Jon Vislie; august 04 Hand out EON 4335 Economics of Banking Sulement to the the lecture on the Diamond Dybvig model I will make some additional remarks to my lecture on onday. I think the main results
More informationOn Software Piracy when Piracy is Costly
Deartment of Economics Working aer No. 0309 htt://nt.fas.nus.edu.sg/ecs/ub/w/w0309.df n Software iracy when iracy is Costly Sougata oddar August 003 Abstract: The ervasiveness of the illegal coying of
More informationRisk and Return. Sample chapter. e r t u i o p a s d f CHAPTER CONTENTS LEARNING OBJECTIVES. Chapter 7
Chater 7 Risk and Return LEARNING OBJECTIVES After studying this chater you should be able to: e r t u i o a s d f understand how return and risk are defined and measured understand the concet of risk
More informationPenalty Interest Rates, Universal Default, and the Common Pool Problem of Credit Card Debt
Penalty Interest Rates, Universal Default, and the Common Pool Problem of Credit Card Debt Lawrence M. Ausubel and Amanda E. Dawsey * February 2009 Preliminary and Incomlete Introduction It is now reasonably
More informationAsymmetric Information, Transaction Cost, and. Externalities in Competitive Insurance Markets *
Asymmetric Information, Transaction Cost, and Externalities in Cometitive Insurance Markets * Jerry W. iu Deartment of Finance, University of Notre Dame, Notre Dame, IN 465565646 wliu@nd.edu Mark J. Browne
More informationA Simple Model of Pricing, Markups and Market. Power Under Demand Fluctuations
A Simle Model of Pricing, Markus and Market Power Under Demand Fluctuations Stanley S. Reynolds Deartment of Economics; University of Arizona; Tucson, AZ 85721 Bart J. Wilson Economic Science Laboratory;
More information6.4 The Basic Scheme when the Agent is Risk Averse
100 OPTIMAL COMPENSATION SCHEMES such that Further, effort is chosen so that ˆβ = ˆα = 0 e = δ The level of utility in equilibrium is strictly larger than the outside otion (which was normalized to zero
More informationPiracy and Network Externality An Analysis for the Monopolized Software Industry
Piracy and Network Externality An Analysis for the Monoolized Software Industry Ming Chung Chang Deartment of Economics and Graduate Institute of Industrial Economics mcchang@mgt.ncu.edu.tw Chiu Fen Lin
More informationSeparating Trading and Banking: Consequences for Financial Stability
Searating Trading and Banking: Consequences for Financial Stability Hendrik Hakenes University of Bonn, Max Planck Institute Bonn, and CEPR Isabel Schnabel Johannes Gutenberg University Mainz, Max Planck
More informationCompensating Fund Managers for RiskAdjusted Performance
Comensating Fund Managers for RiskAdjusted Performance Thomas S. Coleman Æquilibrium Investments, Ltd. Laurence B. Siegel The Ford Foundation Journal of Alternative Investments Winter 1999 In contrast
More informationJoint Production and Financing Decisions: Modeling and Analysis
Joint Production and Financing Decisions: Modeling and Analysis Xiaodong Xu John R. Birge Deartment of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208,
More informationLarge firms and heterogeneity: the structure of trade and industry under oligopoly
Large firms and heterogeneity: the structure of trade and industry under oligooly Eddy Bekkers University of Linz Joseh Francois University of Linz & CEPR (London) ABSTRACT: We develo a model of trade
More informationThe risk of using the Q heterogeneity estimator for software engineering experiments
Dieste, O., Fernández, E., GarcíaMartínez, R., Juristo, N. 11. The risk of using the Q heterogeneity estimator for software engineering exeriments. The risk of using the Q heterogeneity estimator for
More informationManaging specific risk in property portfolios
Managing secific risk in roerty ortfolios Andrew Baum, PhD University of Reading, UK Peter Struemell OPC, London, UK Contact author: Andrew Baum Deartment of Real Estate and Planning University of Reading
More informationInterbank Market and Central Bank Policy
Federal Reserve Bank of New York Staff Reorts Interbank Market and Central Bank Policy JungHyun Ahn Vincent Bignon Régis Breton Antoine Martin Staff Reort No. 763 January 206 This aer resents reliminary
More informationAn Introduction to Risk Parity Hossein Kazemi
An Introduction to Risk Parity Hossein Kazemi In the aftermath of the financial crisis, investors and asset allocators have started the usual ritual of rethinking the way they aroached asset allocation
More informationX How to Schedule a Cascade in an Arbitrary Graph
X How to Schedule a Cascade in an Arbitrary Grah Flavio Chierichetti, Cornell University Jon Kleinberg, Cornell University Alessandro Panconesi, Saienza University When individuals in a social network
More informationThe impact of metadata implementation on webpage visibility in search engine results (Part II) q
Information Processing and Management 41 (2005) 691 715 www.elsevier.com/locate/inforoman The imact of metadata imlementation on webage visibility in search engine results (Part II) q Jin Zhang *, Alexandra
More informationAn important observation in supply chain management, known as the bullwhip effect,
Quantifying the Bullwhi Effect in a Simle Suly Chain: The Imact of Forecasting, Lead Times, and Information Frank Chen Zvi Drezner Jennifer K. Ryan David SimchiLevi Decision Sciences Deartment, National
More informationApplications of Regret Theory to Asset Pricing
Alications of Regret Theory to Asset Pricing Anna Dodonova * Henry B. Tiie College of Business, University of Iowa Iowa City, Iowa 522421000 Tel.: +13193379958 Email address: annadodonova@uiowa.edu
More informationSynopsys RURAL ELECTRICATION PLANNING SOFTWARE (LAPER) Rainer Fronius Marc Gratton Electricité de France Research and Development FRANCE
RURAL ELECTRICATION PLANNING SOFTWARE (LAPER) Rainer Fronius Marc Gratton Electricité de France Research and Develoment FRANCE Synosys There is no doubt left about the benefit of electrication and subsequently
More informationRisk in Revenue Management and Dynamic Pricing
OPERATIONS RESEARCH Vol. 56, No. 2, March Aril 2008,. 326 343 issn 0030364X eissn 15265463 08 5602 0326 informs doi 10.1287/ore.1070.0438 2008 INFORMS Risk in Revenue Management and Dynamic Pricing Yuri
More informationCFRI 3,4. Zhengwei Wang PBC School of Finance, Tsinghua University, Beijing, China and SEBA, Beijing Normal University, Beijing, China
The current issue and full text archive of this journal is available at www.emeraldinsight.com/20441398.htm CFRI 3,4 322 constraints and cororate caital structure: a model Wuxiang Zhu School of Economics
More informationUnraveling versus Unraveling: A Memo on Competitive Equilibriums and Trade in Insurance Markets
Unraveling versus Unraveling: A Memo on Competitive Equilibriums and Trade in Insurance Markets Nathaniel Hendren January, 2014 Abstract Both Akerlof (1970) and Rothschild and Stiglitz (1976) show that
More information6.042/18.062J Mathematics for Computer Science December 12, 2006 Tom Leighton and Ronitt Rubinfeld. Random Walks
6.042/8.062J Mathematics for Comuter Science December 2, 2006 Tom Leighton and Ronitt Rubinfeld Lecture Notes Random Walks Gambler s Ruin Today we re going to talk about onedimensional random walks. In
More informationPresales, Leverage Decisions and Risk Shifting
Presales, Leverage Decisions and Risk Shifting Su Han Chan Professor Carey Business School Johns Hokins University, USA schan@jhu.edu Fang Fang AssociateProfessor School of Public Economics and Administration
More informationCapital, Systemic Risk, Insurance Prices and Regulation
Caital, Systemic Risk, Insurance Prices and Regulation Ajay Subramanian J. Mack Robinson College of Business Georgia State University asubramanian@gsu.edu Jinjing Wang J. Mack Robinson College of Business
More informationProject Finance as a Risk Management Tool in International Syndicated Lending
Discussion Paer No. 183 Project Finance as a Risk Management Tool in International Syndicated ending Christa ainz* Stefanie Kleimeier** December 2006 *Christa ainz, Deartment of Economics, University of
More informationF inding the optimal, or valuemaximizing, capital
Estimating RiskAdjusted Costs of Financial Distress by Heitor Almeida, University of Illinois at UrbanaChamaign, and Thomas Philion, New York University 1 F inding the otimal, or valuemaximizing, caital
More informationCashintheMarket Pricing and Optimal Bank Bailout Policy 1
CashintheMaret Pricing and Otimal Ban Bailout Policy 1 Viral V. Acharya 2 London Business School and CEPR Tanju Yorulmazer 3 Ban of England J.E.L. Classification: G21, G28, G38, E58, D62. Keywords:
More informationMultiperiod Portfolio Optimization with General Transaction Costs
Multieriod Portfolio Otimization with General Transaction Costs Victor DeMiguel Deartment of Management Science and Oerations, London Business School, London NW1 4SA, UK, avmiguel@london.edu Xiaoling Mei
More informationMonitoring Frequency of Change By Li Qin
Monitoring Frequency of Change By Li Qin Abstract Control charts are widely used in rocess monitoring roblems. This aer gives a brief review of control charts for monitoring a roortion and some initial
More informationSt.George  ACCI SMALL BUSINESS SURVEY August 2007
Release Date: 21 August 2007 St.George  ACCI SMALL BUSINESS SURVEY August 2007 Identifying National Trends and Conditions for the Sector Working in Partnershi for the future of Australian Business St.George
More informationPoint Location. Preprocess a planar, polygonal subdivision for point location queries. p = (18, 11)
Point Location Prerocess a lanar, olygonal subdivision for oint location ueries. = (18, 11) Inut is a subdivision S of comlexity n, say, number of edges. uild a data structure on S so that for a uery oint
More informationPrice Discrimination in the Digital Economy*
Price Discrimination in the Digital Economy Drew Fudenberg (Harvard University) J. Miguel VillasBoas (University of California, Berkeley) May 2012 ABSTRACT With the develoments in information technology
More informationDEPARTMENT OF ECONOMICS DISCUSSION PAPER SERIES
ISSN 14710498 DEPARTMENT OF ECONOMICS DISCUSSION PAPER SERIES MARGINAL COST PRICING VERSUS INSURANCE Simon Cowan Number 102 May 2002 Manor Road Building, Oxford OX1 3UQ Marginal cost ricing versus insurance
More informationOn Multicast Capacity and Delay in Cognitive Radio Mobile Adhoc Networks
On Multicast Caacity and Delay in Cognitive Radio Mobile Adhoc Networks Jinbei Zhang, Yixuan Li, Zhuotao Liu, Fan Wu, Feng Yang, Xinbing Wang Det of Electronic Engineering Det of Comuter Science and Engineering
More informationA Modified Measure of Covert Network Performance
A Modified Measure of Covert Network Performance LYNNE L DOTY Marist College Deartment of Mathematics Poughkeesie, NY UNITED STATES lynnedoty@maristedu Abstract: In a covert network the need for secrecy
More informationPOISSON PROCESSES. Chapter 2. 2.1 Introduction. 2.1.1 Arrival processes
Chater 2 POISSON PROCESSES 2.1 Introduction A Poisson rocess is a simle and widely used stochastic rocess for modeling the times at which arrivals enter a system. It is in many ways the continuoustime
More informationc 2009 Je rey A. Miron 3. Examples: Linear Demand Curves and Monopoly
Lecture 0: Monooly. c 009 Je rey A. Miron Outline. Introduction. Maximizing Pro ts. Examles: Linear Demand Curves and Monooly. The Ine ciency of Monooly. The Deadweight Loss of Monooly. Price Discrimination.
More informationThe fast Fourier transform method for the valuation of European style options inthemoney (ITM), atthemoney (ATM) and outofthemoney (OTM)
Comutational and Alied Mathematics Journal 15; 1(1: 16 Published online January, 15 (htt://www.aascit.org/ournal/cam he fast Fourier transform method for the valuation of Euroean style otions inthemoney
More informationTworesource stochastic capacity planning employing a Bayesian methodology
Journal of the Oerational Research Society (23) 54, 1198 128 r 23 Oerational Research Society Ltd. All rights reserved. 165682/3 $25. www.algravejournals.com/jors Tworesource stochastic caacity lanning
More informationEconomics 431 Fall 2003 2nd midterm Answer Key
Economics 431 Fall 2003 2nd midterm Answer Key 1) (20 oints) Big C cable comany has a local monooly in cable TV (good 1) and fast Internet (good 2). Assume that the marginal cost of roducing either good
More informationJena Research Papers in Business and Economics
Jena Research Paers in Business and Economics A newsvendor model with service and loss constraints Werner Jammernegg und Peter Kischka 21/2008 Jenaer Schriften zur Wirtschaftswissenschaft Working and Discussion
More informationThe Economics of Credence Goods: On the Role of Liability, Verifiability, Reputation and Competition
WORKING PAPERS IN ECONOMICS No 348 he Economics of Credence Goods: On the Role of Liability, Verifiability, Reutation and Cometition Uwe Delleck Rudolf Kerschbamer Matthias Sutter February 29 Institutionen
More informationA joint initiative of LudwigMaximilians University s Center for Economic Studies and the Ifo Institute for Economic Research
A joint initiative of LudwigMaximilians University s Center for Economic Studies and the Ifo Institute for Economic Research Area Conference on Alied Microeconomics  2 March 20 CESifo Conference Centre,
More informationWASHINGTON UNIVERSITY IN ST. LOUIS Olin Business School CONTAGION OF A CRISIS, CORPORATE GOVERNANCE, AND CREDIT RATING
WASHINGTON UNIVERSITY IN ST. LOUIS Olin Business School Dissertation Examination Committee: Armando R. Gomes, CoChair David K. Levine, CoChair Ohad Kadan Todd T. Milbourn John H. Nachbar Anjan V. Thakor
More informationLargeScale IP Traceback in HighSpeed Internet: Practical Techniques and Theoretical Foundation
LargeScale IP Traceback in HighSeed Internet: Practical Techniques and Theoretical Foundation Jun Li Minho Sung Jun (Jim) Xu College of Comuting Georgia Institute of Technology {junli,mhsung,jx}@cc.gatech.edu
More informationEffect Sizes Based on Means
CHAPTER 4 Effect Sizes Based on Means Introduction Raw (unstardized) mean difference D Stardized mean difference, d g Resonse ratios INTRODUCTION When the studies reort means stard deviations, the referred
More informationReDispatch Approach for Congestion Relief in Deregulated Power Systems
ReDisatch Aroach for Congestion Relief in Deregulated ower Systems Ch. Naga Raja Kumari #1, M. Anitha 2 #1, 2 Assistant rofessor, Det. of Electrical Engineering RVR & JC College of Engineering, Guntur522019,
More informationLocal Connectivity Tests to Identify Wormholes in Wireless Networks
Local Connectivity Tests to Identify Wormholes in Wireless Networks Xiaomeng Ban Comuter Science Stony Brook University xban@cs.sunysb.edu Rik Sarkar Comuter Science Freie Universität Berlin sarkar@inf.fuberlin.de
More informationThe Economics of the Cloud: Price Competition and Congestion
Submitted to Oerations Research manuscrit The Economics of the Cloud: Price Cometition and Congestion Jonatha Anselmi Basque Center for Alied Mathematics, jonatha.anselmi@gmail.com Danilo Ardagna Di. di
More informationCorporate Compliance Policy
Cororate Comliance Policy English Edition FOREWORD Dear Emloyees, The global nature of Bayer s oerations means that our activities are subject to a wide variety of statutory regulations and standards
More informationWorking paper No: 23/2011 May 2011 LSE Health. Sotiris Vandoros, Katherine Grace Carman. Demand and Pricing of Preventative Health Care
Working aer o: 3/0 May 0 LSE Health Sotiris Vandoros, Katherine Grace Carman Demand and Pricing of Preventative Health Care Demand and Pricing of Preventative Healthcare Sotiris Vandoros, Katherine Grace
More informationDynamics of Open Source Movements
Dynamics of Oen Source Movements Susan Athey y and Glenn Ellison z January 2006 Abstract This aer considers a dynamic model of the evolution of oen source software rojects, focusing on the evolution of
More informationEvaluating a WebBased Information System for Managing Master of Science Summer Projects
Evaluating a WebBased Information System for Managing Master of Science Summer Projects Till Rebenich University of Southamton tr08r@ecs.soton.ac.uk Andrew M. Gravell University of Southamton amg@ecs.soton.ac.uk
More informationSQUARE GRID POINTS COVERAGED BY CONNECTED SOURCES WITH COVERAGE RADIUS OF ONE ON A TWODIMENSIONAL GRID
International Journal of Comuter Science & Information Technology (IJCSIT) Vol 6, No 4, August 014 SQUARE GRID POINTS COVERAGED BY CONNECTED SOURCES WITH COVERAGE RADIUS OF ONE ON A TWODIMENSIONAL GRID
More informationVariations on the Gambler s Ruin Problem
Variations on the Gambler s Ruin Problem Mat Willmott December 6, 2002 Abstract. This aer covers the history and solution to the Gambler s Ruin Problem, and then exlores the odds for each layer to win
More informationChapter 1 Introduction
Chapter 1 Introduction 1.1 Aim of the study Development economists and policy makers generally identify access to credit as one of the main determinants of economic activity and alleviation of poverty
More informationOntheJob Search, Work Effort and Hyperbolic Discounting
OntheJob Search, Work Effort and Hyerbolic Discounting Thomas van Huizen March 2010  Preliminary draft  ABSTRACT This aer assesses theoretically and examines emirically the effects of time references
More informationBUBBLES AND CRASHES. By Dilip Abreu and Markus K. Brunnermeier 1
Econometrica, Vol. 71, No. 1 (January, 23), 173 24 BUBBLES AND CRASHES By Dili Abreu and Markus K. Brunnermeier 1 We resent a model in which an asset bubble can ersist desite the resence of rational arbitrageurs.
More informationEuropean Journal of Operational Research
Euroean Journal of Oerational Research 15 (011) 730 739 Contents lists available at ScienceDirect Euroean Journal of Oerational Research journal homeage: www.elsevier.com/locate/ejor Interfaces with Other
More informationAn inventory control system for spare parts at a refinery: An empirical comparison of different reorder point methods
An inventory control system for sare arts at a refinery: An emirical comarison of different reorder oint methods Eric Porras a*, Rommert Dekker b a Instituto Tecnológico y de Estudios Sueriores de Monterrey,
More informationSage HRMS I Planning Guide. The HR Software Buyer s Guide and Checklist
I Planning Guide The HR Software Buyer s Guide and Checklist Table of Contents Introduction... 1 Recent Trends in HR Technology... 1 Return on Emloyee Investment Paerless HR Workflows Business Intelligence
More informationThe Online Freezetag Problem
The Online Freezetag Problem Mikael Hammar, Bengt J. Nilsson, and Mia Persson Atus Technologies AB, IDEON, SE3 70 Lund, Sweden mikael.hammar@atus.com School of Technology and Society, Malmö University,
More informationTOWARDS REALTIME METADATA FOR SENSORBASED NETWORKS AND GEOGRAPHIC DATABASES
TOWARDS REALTIME METADATA FOR SENSORBASED NETWORKS AND GEOGRAPHIC DATABASES C. Gutiérrez, S. Servigne, R. Laurini LIRIS, INSA Lyon, Bât. Blaise Pascal, 20 av. Albert Einstein 69621 Villeurbanne, France
More informationNBER WORKING PAPER SERIES HOW MUCH OF CHINESE EXPORTS IS REALLY MADE IN CHINA? ASSESSING DOMESTIC VALUEADDED WHEN PROCESSING TRADE IS PERVASIVE
NBER WORKING PAPER SERIES HOW MUCH OF CHINESE EXPORTS IS REALLY MADE IN CHINA? ASSESSING DOMESTIC VALUEADDED WHEN PROCESSING TRADE IS PERVASIVE Robert Kooman Zhi Wang ShangJin Wei Working Paer 14109
More informationConcurrent Program Synthesis Based on Supervisory Control
010 American Control Conference Marriott Waterfront, Baltimore, MD, USA June 30July 0, 010 ThB07.5 Concurrent Program Synthesis Based on Suervisory Control Marian V. Iordache and Panos J. Antsaklis Abstract
More informationStat 134 Fall 2011: Gambler s ruin
Stat 134 Fall 2011: Gambler s ruin Michael Lugo Setember 12, 2011 In class today I talked about the roblem of gambler s ruin but there wasn t enough time to do it roerly. I fear I may have confused some
More informationChapter Three. Topics To Be Covered
Chater Three Alying the SulyandDemand Model Toics To Be Covered How the shaes of demand and suly curves matter? Sensitivity of quantity demanded to rice. Sensitivity of quantity sulied to rice. Long run
More informationTHE RELATIONSHIP BETWEEN EMPLOYEE PERFORMANCE AND THEIR EFFICIENCY EVALUATION SYSTEM IN THE YOTH AND SPORT OFFICES IN NORTH WEST OF IRAN
THE RELATIONSHIP BETWEEN EMPLOYEE PERFORMANCE AND THEIR EFFICIENCY EVALUATION SYSTEM IN THE YOTH AND SPORT OFFICES IN NORTH WEST OF IRAN *Akbar Abdolhosenzadeh 1, Laya Mokhtari 2, Amineh Sahranavard Gargari
More informationComparing Dissimilarity Measures for Symbolic Data Analysis
Comaring Dissimilarity Measures for Symbolic Data Analysis Donato MALERBA, Floriana ESPOSITO, Vincenzo GIOVIALE and Valentina TAMMA Diartimento di Informatica, University of Bari Via Orabona 4 76 Bari,
More informationAn actuarial approach to pricing Mortgage Insurance considering simultaneously mortgage default and prepayment
An actuarial aroach to ricing Mortgage Insurance considering simultaneously mortgage default and reayment Jesús Alan Elizondo Flores Comisión Nacional Bancaria y de Valores aelizondo@cnbv.gob.mx Valeria
More informationThe Economics of the Cloud: Price Competition and Congestion
Submitted to Oerations Research manuscrit (Please, rovide the manuscrit number!) Authors are encouraged to submit new aers to INFORMS journals by means of a style file temlate, which includes the journal
More informationIEEM 101: Inventory control
IEEM 101: Inventory control Outline of this series of lectures: 1. Definition of inventory. Examles of where inventory can imrove things in a system 3. Deterministic Inventory Models 3.1. Continuous review:
More informationENFORCING SAFETY PROPERTIES IN WEB APPLICATIONS USING PETRI NETS
ENFORCING SAFETY PROPERTIES IN WEB APPLICATIONS USING PETRI NETS Liviu Grigore Comuter Science Deartment University of Illinois at Chicago Chicago, IL, 60607 lgrigore@cs.uic.edu Ugo Buy Comuter Science
More information401K Plan. Effective January 1, 2014
401K Plan Effective January 1, 2014 Summary Plan Descrition Particiation...2 Contributions...2 Disabled Particiants...4 Definition of Comensation...4 Legal Limits on Contributions...4 Enrollment...5 Investment
More informationIEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 29, NO. 4, APRIL 2011 757. LoadBalancing Spectrum Decision for Cognitive Radio Networks
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 29, NO. 4, APRIL 20 757 LoadBalancing Sectrum Decision for Cognitive Radio Networks LiChun Wang, Fellow, IEEE, ChungWei Wang, Student Member, IEEE,
More informationRisky Loans and the Emergence of Rotating Savings and Credit Associations
Risky Loans and the Emergence of Rotating Savings and Credit Associations Stefan Klonner, Cornell University November 2006 Abstract: This aer rovides an exlanation for the revalence of rotating savings
More informationDAYAHEAD ELECTRICITY PRICE FORECASTING BASED ON TIME SERIES MODELS: A COMPARISON
DAYAHEAD ELECTRICITY PRICE FORECASTING BASED ON TIME SERIES MODELS: A COMPARISON Rosario Esínola, Javier Contreras, Francisco J. Nogales and Antonio J. Conejo E.T.S. de Ingenieros Industriales, Universidad
More informationStochastic Derivation of an Integral Equation for Probability Generating Functions
Journal of Informatics and Mathematical Sciences Volume 5 (2013), Number 3,. 157 163 RGN Publications htt://www.rgnublications.com Stochastic Derivation of an Integral Equation for Probability Generating
More information1 Gambler s Ruin Problem
Coyright c 2009 by Karl Sigman 1 Gambler s Ruin Problem Let N 2 be an integer and let 1 i N 1. Consider a gambler who starts with an initial fortune of $i and then on each successive gamble either wins
More informationCRITICAL AVIATION INFRASTRUCTURES VULNERABILITY ASSESSMENT TO TERRORIST THREATS
Review of the Air Force Academy No (23) 203 CRITICAL AVIATION INFRASTRUCTURES VULNERABILITY ASSESSMENT TO TERRORIST THREATS Cătălin CIOACĂ Henri Coandă Air Force Academy, Braşov, Romania Abstract: The
More informationComputational Finance The Martingale Measure and Pricing of Derivatives
1 The Martingale Measure 1 Comutational Finance The Martingale Measure and Pricing of Derivatives 1 The Martingale Measure The Martingale measure or the Risk Neutral robabilities are a fundamental concet
More informationPricing the Internet. Outline. The Size of the Internet (Cont.) The Size of the Internet
Pricing the Internet Costas Courcoubetis thens University of Economics and Business and ICSFORTH Outline The growth of the internet The role of ricing Some ricing roosals Pricing in a cometitive framework
More informationA MOST PROBABLE POINTBASED METHOD FOR RELIABILITY ANALYSIS, SENSITIVITY ANALYSIS AND DESIGN OPTIMIZATION
9 th ASCE Secialty Conference on Probabilistic Mechanics and Structural Reliability PMC2004 Abstract A MOST PROBABLE POINTBASED METHOD FOR RELIABILITY ANALYSIS, SENSITIVITY ANALYSIS AND DESIGN OPTIMIZATION
More informationService Network Design with Asset Management: Formulations and Comparative Analyzes
Service Network Design with Asset Management: Formulations and Comarative Analyzes Jardar Andersen Teodor Gabriel Crainic Marielle Christiansen October 2007 CIRRELT200740 Service Network Design with
More informationAutomatic Search for Correlated Alarms
Automatic Search for Correlated Alarms KlausDieter Tuchs, Peter Tondl, Markus Radimirsch, Klaus Jobmann Institut für Allgemeine Nachrichtentechnik, Universität Hannover Aelstraße 9a, 0167 Hanover, Germany
More informationBeyond the F Test: Effect Size Confidence Intervals and Tests of Close Fit in the Analysis of Variance and Contrast Analysis
Psychological Methods 004, Vol. 9, No., 164 18 Coyright 004 by the American Psychological Association 108989X/04/$1.00 DOI: 10.1037/108989X.9..164 Beyond the F Test: Effect Size Confidence Intervals
More informationConsumer Price Index Dynamics in a Small Open Economy: A Structural Time Series Model for Luxembourg
Aka and Pieretii, International Journal of Alied Economics, 5(, March 2008, 3 Consumer Price Index Dynamics in a Small Oen Economy: A Structural Time Series Model for Luxembourg Bédia F. Aka * and P.
More informationOVERVIEW OF THE CAAMPL EARLY WARNING SYSTEM IN ROMANIAN BANKING
Annals of the University of Petroşani, Economics, 11(2), 2011, 7180 71 OVERVIEW OF THE CAAMPL EARLY WARNING SYSTEM IN ROMANIAN BANKING IMOLA DRIGĂ, CODRUŢA DURA, ILIE RĂSCOLEAN * ABSTRACT: The uniform
More informationUniversiteitUtrecht. Department. of Mathematics. Optimal a priori error bounds for the. RayleighRitz method
UniversiteitUtrecht * Deartment of Mathematics Otimal a riori error bounds for the RayleighRitz method by Gerard L.G. Sleijen, Jaser van den Eshof, and Paul Smit Prerint nr. 1160 Setember, 2000 OPTIMAL
More informationNew Approaches to Idea Generation and Consumer Input in the Product Development
New roaches to Idea Generation and Consumer Inut in the Product Develoment Process y Olivier Toubia Ingénieur, Ecole Centrale Paris, 000 M.S. Oerations Research, Massachusetts Institute of Technology,
More informationTimeCost TradeOffs in ResourceConstraint Project Scheduling Problems with Overlapping Modes
TimeCost TradeOffs in ResourceConstraint Proect Scheduling Problems with Overlaing Modes François Berthaut Robert Pellerin Nathalie Perrier Adnène Hai February 2011 CIRRELT201110 Bureaux de Montréal
More informationService Network Design with Asset Management: Formulations and Comparative Analyzes
Service Network Design with Asset Management: Formulations and Comarative Analyzes Jardar Andersen Teodor Gabriel Crainic Marielle Christiansen October 2007 CIRRELT200740 Service Network Design with
More informationThe MagnusDerek Game
The MagnusDerek Game Z. Nedev S. Muthukrishnan Abstract We introduce a new combinatorial game between two layers: Magnus and Derek. Initially, a token is laced at osition 0 on a round table with n ositions.
More informationThe Behavioral Economics of Insurance
DEPARTMENT OF ECONOMICS The Behavioral Economics of Insurance Ali alnowaihi, University of Leicester, UK Sanjit Dhami, University of Leicester, UK Working Paer No. 0/2 Udated Aril 200 The Behavioral Economics
More information