Government intervention in credit allocation: a collective decision making model. Ruth Ben-Yashar and Miriam Krausz* Bar-Ilan University, Israel
|
|
- Godfrey Harrison
- 8 years ago
- Views:
Transcription
1 Govermet itervetio i credit allocatio: a collective decisio makig model Ruth Be-Yashar ad Miriam Krausz* Bar-Ila Uiversity, Israel Abstract The urose of this study is to address the imortat issue of govermet itervetio i credit markets through govermet loa rograms. This toic has sigificace for the ecoomic develomet of certai weaker sectors i society ultimately affectig overall ecoomic ad social coditios. We aly a collective decisio makig model to a bak's credit decisio rocess to show the effect of govermet loa rograms o credit allocatio. This allows us to aalyze the effect of the decisio makig structure of a bak (the collective decisio rule, e.g., cetralized ad decetralized, as a crucial factor i determiig the effectiveess of govermet itervetio. Key words: govermet loa rograms, collective decisio makig. JEL classificatio: G, G8, D7 *Corresodig author, kerausm@mail.biu.ac.il
2 Govermet itervetio i credit allocatio: a collective decisio makig model. Itroductio I this research we focus o the govermet's efforts to icrease the amout of credit available to certai tyes of borrowers such as miorities, wome ad develoig regios or idustries. We aly a collective decisio makig model to a bak's credit decisio rocess to show the effect of govermet itervetio o credit allocatio. The combiatio of these two strads of research allows us to aalyze the decisio makig structure of a bak as a crucial factor i determiig the effectiveess of govermet itervetio. Fiacial itermediaries have a imortat role i the ecoomy of trasferrig fuds from ivestors to roductive eterrises. But, due to asymmetry i iformatio, baks are ot always able to erform their task fully ad heomea such as credit ratioig (Stiglitz ad Weiss, 98 are observed. Govermets itervee i the credit market i order to rovide loas i cases where rivate markets will ot. They may be actig i resose to geeral credit ratioig i the market or to difficulties faced by certai sectors such as small busiesses. Govermet loa rograms have macro-ecoomic imlicatios (Esiosa-Vega, Smith ad Yi, as well as affectig certai targeted sectors. Ideed weak sectors such as miorities, studets ad small busiesses costatly face credit ratioig imlyig that o itermediary will suly them with credit eve whe they are willig to ay high iterest rates. Cosequetly, may govermets have loa rograms (e.g SBA loa rogram, Faie Mae, Sally Mae ad Freddie Mac i the U.S., studet's loa rogram i Caada ad SBS loa guaratees i the U.K. desiged to icrease the suly of loas to these targeted sectors. Such loa rograms effectively costitute govermet itervetio i the credit market. The two most commo methods of itervetio are loa guaratees ad loa subsidies ivolvig either existig itermediaries or secial ledig istitutios. However, oce these tools are i lace, baks are ot obliged to use them. The usual loa screeig
3 methods ad credit scorig techiques are alied to loa requests ad the bak decides whether or ot to grat the loas. If a govermet i a free ecoomy does ot wish to imose credit o itermediaries, ad leaves the bak to make its ow decisio withi the framework of a credit rogram, the govermet caot be esured that the suly of credit will match its exectatios eve whe govermets establish secial itermediaries for credit rograms. By aalyzig the bak's credit decisio rocess we wish to rovide a exlaatio as to why govermets sometimes oly artially succeed i icreasig the suly of credit ad how govermets should act i order to icrease ledig to target oulatios. I the field of bakig a large body of literature deals with credit scorig methods (Mester, 997, Altma ad Sauders, 997 ad Alle, Delog ad Sauders, 4, while a much smaller amout of research has bee devoted to the desig of the decisio makig rocess i baks. Most otably Stei ( discusses the effect of cetralized vs. decetralized decisio makig o the share of small busiess ledig. His focus is o the effect of the bak's decisio makig desig o the ability of soft iformatio, cocerig small busiess loas, to comete with loa requests made by large firms. Stei (5 discusses the desig of cut-off methods for credit decisios whe a credit score is rovided ad Adersso (4 carries out a exerimetal study that determies the role of a decisio maker's exeriece i the decisio to led. I this aer the bak's credit decisio whether to accet or reect a secific loa request is aalyzed withi the framework of a collective decisio makig model, which focuses o the aggregatio of the decisios of a grou of exerts, i.e, the (collective decisio rule. The subect of otimal grou decisio-makig i a committee of fixed size that is subect to huma fallibility has attracted a great deal of attetio i the ast coule of decades or so. Nitza ad Paroush (98, 985, Grofma et al. (983 ad Shaely ad Grofma(984 are the first works which lay the theoretical foudatios of the biary choice model. Be-Yashar ad Nitza (997 defied the otimal decisio rule i a more geeral framework, which allows asymmetric choice. Other studies aalyzed the otimal decisio rule uder costraits (Be-Yashar, Kraus ad Khuller, ; Be-Yashar ad Kraus,, the otimal decisio rule i olychotomous choice (Be-Yashar ad Paroush, ad other asects of collective decisio makig. The results obtaied by several studies are
4 alicable to a variety of ecoomic fields such as labor ecoomics (e.g., Nitza ad Paroush 98, Maagemet (e.g., Be-Yashar ad Nitza, 998 ad Ivestmet ad Reliability Theory (e.g., Sah ad Stiglitz 988 ad Sah 99, 99. The collective decisio makig model assumes a team of decisio makers whose task is to arove or reect a roect so as to maximize the exected utility of the orgaizatio. The decisios of the team members are aggregated by a cetral laer uder a collective decisio rule, to rovide a fial decisio whether to accet or reect the roect. Withi our alicatio of the decisio makig model, each team member has exertise i determiig whether or ot a loa should be grated. The grou of team members ca also be iterreted as a grou of criteria used i a credit decisio model. Both loa guaratees ad subsidies ca directly affect the secific decisio but ot ecessarily the decisio rocess. This deeds o whether the bak always adots the otimal decisio rule or abides to a fixed decisio rule that may ot ecessarily be otimal. I the former case the decisio rocess will chage whe govermets itervee ad this must be take ito cosideratio by the govermet. I the latter case the decisio rocess does ot chage whe the govermet itervees. The distictio betwee the case where the rocess is affected ad the case where it is ot, is imortat because differet istitutioal frameworks are used by govermets for their loa rograms. I some coutries govermet loa rograms are oerated through rivate ledig istitutios that rovide fiacial services to the geeral oulatio icludig loas. I other coutries secial ledig istitutios are established to deal oly with govermet loas. Differet istitutios may differ i their willigess or ability to adust their decisio rocess. However, i both cases the ledig istitutio emloys screeig methods ad credit decisio makig rocedures i order to exted credit to high quality borrowers that are most likely to reay the loa. We therefore aalyze govermet loa rograms both whe the decisio ad the decisio rocess are affected as well as whe oly the secific decisio is affected. We cosider govermet itervetio whe baks follow the otimal decisio rule/structure ad whe baks kee to a rigid decisio structure which may ot ecessarily be otimal. 3
5 . The model We assume that there are decisio makers i a bak whose task is to arove or reect a loa alicatio so as to maximize the bak's exected rofit. There are two kids of loa requests, good ( or bad (-. A good loa rovides the bak with a rofit while a bad loa creates a loss. We deote by x i decisio maker i s decisio, where x i = (accet or x i =- (reect, ad a decisio rofile x={x,,x }. Let us deote by + x the umber of decisio makers who decide i favor of accetig the loa. The idividual's decisio regardig the tye of loa is based o his iformatio such as ast exeriece i ledig to the alicat, the loa alicat's leverage ad other attributes of the borrower ad the loa alicatio. Decisio maker i s decisioal skill is rereseted by i (the robability that idividual i accets a good loa ad reects a bad oe. We assume that the decisioal skill is /< i < ad decisioal skills are statistically ideedet across decisio makers. A collective decisio is reached by the bak maager who alies a decisive decisio rule that is a fuctio f that assigs (aroval or - (reectio to ay x i Ω={,-}, f: Ω {,- }. Each loa of size L at a iterest rate r fiaces a roect with a retur which is kow to the alicat but ot to the bak. The bak faces a cost r of fiacig the loa, such that r > r. All alicats require the same loa size such that size of the loa is set by the alicat. Prices are set cometitively i the loa market. Facig asymmetric iformatio, the bak sigs a stadard debt cotract with the borrower i order to miimize moitorig costs. The state of a loa ca be good with a riori robability > α >, ad bad with a riori robability α. The state is determied as a fuctio of the radom retur o the roect beig fiaced, R, which is draw from a kow distributio of returs i the oulatio of borrowers, rereseted by the desity ( h such that the state is (good if R > Lr ad - otherwise. The distributio of returs i the oulatio of borrowers is kow to the bak maager while a idividual decisio maker gais iformatio oly about the articular loa she is facig. The decisio makers may be iterreted as comoets of a comuterized credit decisio model. 4
6 The govermet ca itervee i two ways. It ca give a loa guaratee which is activated i the case of bakrutcy (whe R < Lr such that the bak is comesated by a roortio g of missig icome, Lr R. The govermet ca also subsidize the loa by reducig the bak's cost of fuds, r, which is activated whether or ot there is bakrutcy. Whe there is govermet itervetio, the state is good if r gr r gr R > L. Note that Lr > L. Therefore, the rior robability that the g g loa is good icreases with g ad/or with the reductio i r. The rofit associated with the aroval ( (reect (- of a good ( loa is deoted by B(, (B(-,, where B(,>B(-,. Similarly, the rofits associated with aroval ad reectio of a bad (- loa are deoted by B(,- ad B(-,-, resectively, where B(-,->B(,-. B(=B(,-B(-, is the ositive et rofit from a good loa ad B(-=B(-,--B(,- is the ositive et rofit from a bad loa. Without loss of geerality, we assume that reectio of a roect (good or bad is associated with zero rofit. That is, B(-,= ad B(-,-=. Hece, B(=B(, ad B(- = -B(,-. Note that, B ad r gr L g ( = ( R + g( Lr R Lr h( R dr ( Lr r gr L g ( R + g( Lr R Lr h( R dr + L( r r h( R B( = dr. ( Lr The et rofits are also affected by the loa guaratee ad by the subsidy as described later o i the aer. The exected rofit is give by α[b(,t(f:+b(-,(-t(f:]+(-α[b(-,-t(f:-+b(,-(-t(f:-] where T(f: ad T(f:- are resectively the robabilities of reachig a correct collective decisio whe the state is (good ad - (bad, give the decisio rule f. The above exected rofit ca be reduced to the followig form E=αB(T(f:+ (-αb(-t(f:-- (-αb(-. (3 5
7 The otimal rule (Be-Yashar ad Nitza, 997 fˆ is a qualified weighted maority rule ad give by: where f ˆ = sig[ w i x i + λ + δ ]. (4 sig{ M} = i= M >, wi = M l i i α B(, λ = l, δ = l. α B( The otimal rule is defied by the otimal weight w i that is assiged to idividual i s decisio ad by some bias comoets determiig the extet of the otimal bias toward oe of the alteratives: λ ad δ. λ reflects the asymmetry i the riors of the two states, δ reflect the asymmetry of the rofits associated with the two states. Notice that λ+δ rereset the combied bias due to a riori robabilities ad the rofits, which are a fuctio of g ad r so that govermet itervetio affects the bias too. i We assume that idividuals have homogeeous skills, that is = = i. I this case the otimal rule is a qualified maority rule. That is [ w + λ ] fˆ = sig x i + δ, where w = wi = w = l. Note that the qualified maority rule ca be rereseted by k (Be Yashar ad Nitza 997, where more tha k decisio makers are required to decide i favor of the loa i order to accet a loa. More recisely, f k = x + > k otherwise We ca oit to several iterestig rules. k = is the simle maority rule, that is if the umber of decisio makers is odd the miimum umber of decisio Uder the assumtio that >, the weight is o-egative. i 6
8 + makers i favor of the loa must be i order to arove the loa. Two extreme decisio makig systems ca be idetified, hierarchy ad olyarchy. I a olyarchy (decetralized, the accetace of the loa by oe decisio maker imlies that the loa is aroved (i.e., k <. I a hierarchy (cetralized the bak aroves a loa oly if it is acceted by all decisio makers ( k <. The otimal k, kˆ, is give by: + kˆ δ λ =. (5 l I the symmetric case where B(=B(- ad α =, the bias elemets vaish ad the otimal aggregatio rule is the simle maority rule, k ˆ =. If δ + λ >, the bias is i favor of accetig the loa request ad therefore k ˆ <, i.e., less tha half of the decisio makers are required to decide i favor of the loa i order for a accet decisio. I the extreme case, whe the bias is very large, oly oe decisio maker is required to make a ositive decisio. This is a olyarchy. The oosite is true whe δ + λ <. It is ossible that the bak will ot ecessarily use the otimal decisio rule. This is because there may be costraits o the bak that determie the weights ad/or the bias. I this case we assume that the decisio rule is a qualified maority rule rereseted by the miimum umber of decisio makers, q, required to decide i favor of a loa i order for the loa to be aroved ( q = mi ( k, k +. For examle, if is a odd umber the q = +, where q is the simle maority rule. We aalyze both cases where the otimal rule is used ad where it is ot. 7
9 3. Results As show above, govermet itervetio is reflected i g ad r such that whe there is govermet itervetio, the state is good if r R > L gr g. That is α > ad < r. The et rofits from good ad bad loas are also affected by govermet itervetio such that B( icreases with g ad decreases with r while B(- decreases with g ad icreases with r. 3 B ( B( <, r That is B ( B( >, r < ad >. All the followig results are reseted for the case of a govermet guaratee where g is icreased but hold also for the case of a subsidy where r is decreased. Our first set of results assumes that the decisio rule is fixed ad is rereseted by q. Note that i this case, sice the decisio rule remais uchaged, the robabilities of accetig good roects, T ( q :, ad of reectig bad roects, T ( q :, do ot chage as a result of govermet itervetio. We assig the robability of arovig a loa uder the decisio rule q by Pr ob ( accet : q. Result : The robability of aroval icreases with the magitude of govermet rob itervetio, that is i the case of a guaratee: Proof: ( q : + ( α ( T ( : Pr ob( accet : q = α T q, ( accet : q >. 3 Usig Liebitz rule for differetiatig a itegral, i this case Lr R>. Also, ad sice L ( < Lr B ( r gr, R > g r gr L g = B ( Lr = r gr L g ( ( Lr R h( R dr + < Lr. The same method leads us to the results for ( ( Lr R h( R dr + > (Note that r gr. (Note that i this case R < L( r. g 8
10 :, = q where T ( q = (. = q ad ( T ( q : = ( rob ( accet : q = T ( q : ( T ( q : = q = ( T ( q : ( T ( : = q where ( = ( Sice (a >. { }. If (b >, >. 4 (c = a, =. 5 a a q >, the from (a ad (b rob ( accet : q >. If q <, the from (c we kow that = q rob with (a Q.E.D. = = q+ ( accet : q. Sice -q+>/, this last term is ositive from (b, ad >. Result is a straightforward result that imlies that give a fixed decisio makig structure i the bak, the robability of accetig loas icreases with govermet itervetio. This is achieved simly by the fact that the share of good roects has, from the bak's oit of view, icreased due to govermet itervetio. 4 ( ( > > > >. >. (Note that uder the model's assumtios >/ ad hece 5 a ( [ ( ( ] a a a a = ad a ( [ ( ( ] a a a a = a a =.. Hece, a a 9
11 The imlicatio is that some loas that would have bee reected before the guaratee was itroduced will ow be aroved ad the govermet succeeds i icreasig the umber of loas allocated. Furthermore, the larger the guaratee, the greater the icrease i ledig. Also, the bak will always wish to articiate i the loa rogram because the guaratee icreases the bak's utility from ledig. This ca be see by derivig E=αB(T(f:+ (-αb(-t(f:-- (-αb(- (equatio (3 with resect to g: E = T ( f B( ( ( B B : + α ( T ( f : B( + ( α > We have determied that the govermet ca use the guaratee as a tool to icrease ledig. We ow show that the structure of decisio makig i the bak has crucial imortace i determiig the magitude of the effect of govermet itervetio o the robability of loa accetace. Result : The effect of govermet itervetio o the robability of accetig a loa icreases as a symmetric fuctio of the decisio rule, as the simle maority rule is aroached from either side. I other words, it is determied as a symmetric fuctio of q that eaks at the simle maority rule. That is: ad rob rob ( accet : q rob( accet : q + i rob( accet : q i q ( accet : q + i q i > q < where i is a iteger. = q Proof: From (c above, if q < the = = q = q+ ( accet : q rob( accet : q + rob =. q q, therefore: Secifically this is true whe q is q + i + = q i. + q = q i, the by substitutig q = +,
12 Hece, Recall that, ( accet : q i rob( accet q + i rob : = q q rob ( accet : q = = q ad from (b above, Furthermore, the term o the RHS of this iequality decreases with i. Q.E.D.. = q > = q + i. Result imlies that structure of decisio makig i the bak affects the success of the govermet i imlemetig a loa rogram. The govermet ca exect the highest degree of success whe the bak uses the simle maority rule to arove a loa request. Thus if the govermet decides to establish a secial ledig istitutio that grats loas withi the govermet's loa rogram, these istitutios should embrace the olicy of the simle maority rule. Also, the govermet ca achieve the same level of success whether the bak imlemets a oliarchy rule whereby oly oe decisio maker is required to arove a loa or a hierrachy rule, whereby all decisio makers must arove a loa. However, i both these cases the govermet achieves the lowest level of success. Furthermore, there is symmetry i the level of success that ca be achieved whe movig away from the simle maority rule towards hierarchy ad oliarchy. The imlicatio of this result is that as a bak is either more cetralized i its decisio makig rocess or more decetralized its decisio makig rocess, the level of success of a loa rogram is reduced. The worst case from the govermet's oit of view is to face either extreme cetralizatio or extreme decetralizatio. Whe the govermet decides to imlemet its loa rogram through the commercial bakig system, the govermet will robably ot be able to imose a decisio makig rocess o the ledig istitutio. At the same time, a utility maximizig istitutio is likely to adot the decisio rule that maximizes its utility. However, the otimal decisio rule is a fuctio of the a riori robabilities ad the exected returs, both of which are affected by the guaratee. Hece whe a guaratee is itroduced the otimal rule chages. I other words, govermet itervetio affects the way i which bak make their decisios cocerig loa aroval. I the followig set of results we show how the otimal rule is affected by
13 govermet itervetio ad we aalyze the level of success of such itervetio uder the otimal rule. From equatio (5 above it follows that the otimal decisio rule, kˆ is egatively related toδ + λ. Sice B( icreases with g ad B(- decreases with g, ( ( = l B α δ icreases with g. Also, because α icreases with g, λ = l B α icreases with g. That is if g icreases the the otimal structure of the bak becomes more leiet toward aroval of the roect, i.e., a smaller roortio of decisio makers is ecessary for collectively choosig to arove the roect. That is kˆ = l <. Note that this derivative is ot a fuctio of the decisio rule. We deote by qˆ the miimum umber of decisio makers required to arove the loa so that the loa is acceted uder the otimal decisio rule. Result 3: Whe the bak chooses the otimal decisio rule: (a The robability of accetig a roect icreases with g. (b Give a decisio rule qˆ, the effect of g o the robability of aroval is greater whe qˆ is a otimal decisio rule that chages otimally with g, rather tha whe it is a fixed rule. Proof: (a Pr ob( accet : qˆ = α T ( qˆ : + ( α ( T ( qˆ : ( accet : qˆ ( qˆ : ( T ( qˆ : rob T = T ( qˆ : ( T ( qˆ : + α + ( α Note that the sum of the first two terms o the RHS is ositive (from Result. Also, ( qˆ : T ( qˆ : T > sice qˆ = (, lˆ < qˆ, = lˆ where lˆ is the ew otimal rule (i.e., the miimum umber of decisio makers required to be i favor of a loa uder the ew otimal rule, i order for the loa
14 to be acceted. As we have show the rule is more leiet i accetig loas as a result of the icrease i g therefore lˆ < qˆ. ( ( T qˆ : Also, ( T ( qˆ : Hece, rob (b Note that >, sice qˆ = (, lˆ < qˆ. = lˆ ( accet : qˆ rob >. ( accet : qˆ is comosed of two elemets: ( T ( qˆ : ( T ( qˆ :, which is the effect of g o the robability of accetace whe the rule is fixed, qˆ, ad ( ( qˆ : ( T ( qˆ : T α + ( α, which is the effect of g o the robability that arises from chagig the otimal rule. Thus, give a decisio rule qˆ, the effect of g o the robability of aroval is greater whe qˆ is a otimal decisio rule rather tha whe qˆ is alied as a fixed decisio rule. Q.E.D. Result 3 imlies that it is i the iterest of the govermet that the ledig istitutio adusts its decisio makig rocess to the otimal rule rather tha remaiig with the same rule which erforms as a fixed rule, because the the govermet ca achieve a greater icrease i ledig. Thus, whe facig a ledig istitutio with ay tye of decisio makig rocess, the govermet will always achieve more whe the istitutio adusts its decisio makig rocess as a result of the govermet loa rogram istead of remaiig with its rule fixed. It is also imortat to ote that the utility of the bak icreases whe it articiates i the govermet loa rogram uder the otimal decisio rule. This ca be see by the fact metioed above that the bak's utility icreases uder a fixed rule. Sice otimizig the decisio rule always imroves utility it must be that baks that otimize their decisio rule certaily icrease utility i the resece of 3
15 govermet itervetio. Furthermore, the utility icreases more whe the bak otimizes the decisio tha whe a fixed rule is used. 4. Coclusio I this aer we have show that the structure of decisio makig i baks is a crucial factor i determiig the effect of govermet loa rograms o the amout of ledig. This has imortat olicy imlicatios for govermets that wish to icrease ledig to certai sectors. I essece our results oit to the coclusio that govermets ca achieve better results from their rograms whe facig baks that have either cetralized or decetralized decisio makig systems. I fact, the closer the decisio makig rocess is to the simle maority rule, the greater the effect of the govermet rogram. Furthermore, the govermet ca achieve suerior results whe ledig istitutios are versatile i their decisio makig rocess, choosig the otimal decisio rule i accordace with the level of govermet itervetio. I our aalysis the govermet always succeeds i icreasig ledig ad baks always fid it worthwhile to articiate i the govermet rogram. There may however be cases where baks will ot be willig to exted loas through a govermet rogram, or alteratively exted far fewer loas tha the govermet iteded. I our model this ca be exlaied by adverse selectio that affects the a riori robabilities. A larger umber of bad loas will eter the market, kowig that there is a icrease i the robability of loa aroval. This will chage the distributio of oulatio of borrowers faced by the bak ad accordigly will affect the rior robabilities of facig good ad bad loas. 4
16 Literature Alle, L., DeLog G. Sauders A., 4 "Issues i the Credit Risk Modelig of Retail Markets" Joural of Bakig ad Fiace, 8( Altma ad A. Sauders, 997, "Credit Risk Measuremet: Develomets over the Last Twety Years", Joural of Bakig ad fiace (- 7-4 Adersso P., 4, "Does exeriece matter i ledig? A rocess-tracig study o exerieced loa officers' ad ovices decisio behavior", Joural of Ecoomic Psychology, 5, Be-Yashar, R. ad Kraus, S.,, Otimal collective dichotomous choice uder quota costraits, Ecoomic Theory 9, Be-Yashar, R., Kraus, S., ad Khuller, S.,, Otimal collective dichotomous choice uder artial order costraits, Mathematical Social Scieces 4, Be-Yashar, R. C. ad Nitza, S., 997, The otimal decisio rule for fixed-size committees i dichotomous choice situatios: The geeral result, Iteratioal Ecoomic Review 38, Be-Yashar, R. ad Nitza, S., 998, Quality ad structure of orgaizatioal decisio makig, Joural of Ecoomic Behavior ad Orgaizatio 36, Be-Yashar, R. ad Paroush, J.,, Otimal decisio rules for fixed-size committees i olychotomous choice situatios, Social Choice ad Welfare 8, Esiosa-Vega M. A., Bruce D. Smith, Chog K. Yi,, "Moetary olicy ad govermet credit rograms", Joural of Fiacial Itermediatio, Grofma, B., Owe, G., Feld, S.L., 983, "Thirtee theorems i search of the truth". Theory ad Decisio 5, Mester L. J., 997, "What's the oit of credit scorig?", Busiess Review, Setember/October, 3-6. Miro J. A., 986, "Fiacial aics, the seasoality of the omial iterest rate, ad the foudig of the Fed", America Ecoomic Review 76(
17 Nitza, S., Paroush, J., 98. "Ivestmet i huma caital ad social self rotectio uder ucertaity". Iteratioal Ecoomic Review, Nitza, S. ad Paroush, J., 98, Otimal decisio rules i ucertai dichotomous choice situatio, Iteratioal Ecoomic Review 3, Nitza, S. ad Paroush, J., 985, Collective Decisio Makig: A Ecoomic Outlook. Cambridge: Cambridge Uiv. Press. Sah, R. K.,99, A exlicit closed-form formula for rofitmaximizig k-out-of- systems subect to two kids of failures, Microelectroics ad Reliability 3, 3 3. Sah, R. K., 99, Fallibility i huma orgaizatios ad olitical systems, The Joural of Ecoomic Persectives 5, Sah, R. K. ad Stiglitz, J. E., 988, Qualitative roerties of rofitmakig k-out-of- systems subect to two kids of failures, IEEE Trasactios o Reliability 37, Shaley, L. ad Grofma, B., 984, Otimizig grou udgmetal accuracy i the resece of iterdeedecies, Public Choice 43, Stei R. M., 5, "The relatioshi betwee default redictio ad ledig rofits: Itegratig ROC aalysis ad loa ricig, bak rus", Joural of Bakig ad Fiace 9, Stei, J. C.,, "Iformatio Productio ad Caital Allocatio: Decetralized versus Hierarchical Firms", Joural of Fiace 57( Stiglitz ad Weiss, 98, Credit Ratioig i Markets with Imerfect Iformatio America Ecoomic Review
The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection
The aalysis of the Courot oligopoly model cosiderig the subjective motive i the strategy selectio Shigehito Furuyama Teruhisa Nakai Departmet of Systems Maagemet Egieerig Faculty of Egieerig Kasai Uiversity
More informationFrance caters to innovative companies and offers the best research tax credit in Europe
1/5 The Frech Govermet has three objectives : > improve Frace s fiscal competitiveess > cosolidate R&D activities > make Frace a attractive coutry for iovatio Tax icetives have become a key elemet of public
More informationCHAPTER 3 THE TIME VALUE OF MONEY
CHAPTER 3 THE TIME VALUE OF MONEY OVERVIEW A dollar i the had today is worth more tha a dollar to be received i the future because, if you had it ow, you could ivest that dollar ad ear iterest. Of all
More informationwhere: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return
EVALUATING ALTERNATIVE CAPITAL INVESTMENT PROGRAMS By Ke D. Duft, Extesio Ecoomist I the March 98 issue of this publicatio we reviewed the procedure by which a capital ivestmet project was assessed. The
More information3 Energy. 3.3. Non-Flow Energy Equation (NFEE) Internal Energy. MECH 225 Engineering Science 2
MECH 5 Egieerig Sciece 3 Eergy 3.3. No-Flow Eergy Equatio (NFEE) You may have oticed that the term system kees croig u. It is ecessary, therefore, that before we start ay aalysis we defie the system that
More informationPROCEEDINGS OF THE YEREVAN STATE UNIVERSITY AN ALTERNATIVE MODEL FOR BONUS-MALUS SYSTEM
PROCEEDINGS OF THE YEREVAN STATE UNIVERSITY Physical ad Mathematical Scieces 2015, 1, p. 15 19 M a t h e m a t i c s AN ALTERNATIVE MODEL FOR BONUS-MALUS SYSTEM A. G. GULYAN Chair of Actuarial Mathematics
More informationINVESTMENT PERFORMANCE COUNCIL (IPC) Guidance Statement on Calculation Methodology
Adoptio Date: 4 March 2004 Effective Date: 1 Jue 2004 Retroactive Applicatio: No Public Commet Period: Aug Nov 2002 INVESTMENT PERFORMANCE COUNCIL (IPC) Preface Guidace Statemet o Calculatio Methodology
More informationTaking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling
Taig DCOP to the Real World: Efficiet Complete Solutios for Distributed Multi-Evet Schedulig Rajiv T. Maheswara, Milid Tambe, Emma Bowrig, Joatha P. Pearce, ad Pradeep araatham Uiversity of Souther Califoria
More informationInstitute of Actuaries of India Subject CT1 Financial Mathematics
Istitute of Actuaries of Idia Subject CT1 Fiacial Mathematics For 2014 Examiatios Subject CT1 Fiacial Mathematics Core Techical Aim The aim of the Fiacial Mathematics subject is to provide a groudig i
More informationVladimir N. Burkov, Dmitri A. Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT
Keywords: project maagemet, resource allocatio, etwork plaig Vladimir N Burkov, Dmitri A Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT The paper deals with the problems of resource allocatio betwee
More informationI. Chi-squared Distributions
1 M 358K Supplemet to Chapter 23: CHI-SQUARED DISTRIBUTIONS, T-DISTRIBUTIONS, AND DEGREES OF FREEDOM To uderstad t-distributios, we first eed to look at aother family of distributios, the chi-squared distributios.
More informationSubject CT5 Contingencies Core Technical Syllabus
Subject CT5 Cotigecies Core Techical Syllabus for the 2015 exams 1 Jue 2014 Aim The aim of the Cotigecies subject is to provide a groudig i the mathematical techiques which ca be used to model ad value
More informationPostprint. http://www.diva-portal.org
htt://www.diva-ortal.org Postrit This is the acceted versio of a aer ublished i Joural of Public Ecoomics. This aer has bee eer-reviewed but does ot iclude the fial ublisher roof-correctios or joural agiatio.
More informationOption Pricing: A Simplified Approach
Otio Pricig: A Simlified Aroach Joh C. Cox Massachusetts Istitute of Techology ad Staford Uiversity Stehe A. Ross Yale Uiversity Mark Rubistei Uiversity of Califoria, Berkeley March 1979 revised July 1979
More informationCOMPARISON OF THE EFFICIENCY OF S-CONTROL CHART AND EWMA-S 2 CONTROL CHART FOR THE CHANGES IN A PROCESS
COMPARISON OF THE EFFICIENCY OF S-CONTROL CHART AND EWMA-S CONTROL CHART FOR THE CHANGES IN A PROCESS Supraee Lisawadi Departmet of Mathematics ad Statistics, Faculty of Sciece ad Techoology, Thammasat
More informationInvesting in Stocks WHAT ARE THE DIFFERENT CLASSIFICATIONS OF STOCKS? WHY INVEST IN STOCKS? CAN YOU LOSE MONEY?
Ivestig i Stocks Ivestig i Stocks Busiesses sell shares of stock to ivestors as a way to raise moey to fiace expasio, pay off debt ad provide operatig capital. Ecoomic coditios: Employmet, iflatio, ivetory
More informationChapter 6: Variance, the law of large numbers and the Monte-Carlo method
Chapter 6: Variace, the law of large umbers ad the Mote-Carlo method Expected value, variace, ad Chebyshev iequality. If X is a radom variable recall that the expected value of X, E[X] is the average value
More informationTIAA-CREF Wealth Management. Personalized, objective financial advice for every stage of life
TIAA-CREF Wealth Maagemet Persoalized, objective fiacial advice for every stage of life A persoalized team approach for a trusted lifelog relatioship No matter who you are, you ca t be a expert i all aspects
More informationModified Line Search Method for Global Optimization
Modified Lie Search Method for Global Optimizatio Cria Grosa ad Ajith Abraham Ceter of Excellece for Quatifiable Quality of Service Norwegia Uiversity of Sciece ad Techology Trodheim, Norway {cria, ajith}@q2s.tu.o
More informationOutput Analysis (2, Chapters 10 &11 Law)
B. Maddah ENMG 6 Simulatio 05/0/07 Output Aalysis (, Chapters 10 &11 Law) Comparig alterative system cofiguratio Sice the output of a simulatio is radom, the comparig differet systems via simulatio should
More information.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth
Questio 1: What is a ordiary auity? Let s look at a ordiary auity that is certai ad simple. By this, we mea a auity over a fixed term whose paymet period matches the iterest coversio period. Additioally,
More informationDepartment of Computer Science, University of Otago
Departmet of Computer Sciece, Uiversity of Otago Techical Report OUCS-2006-09 Permutatios Cotaiig May Patters Authors: M.H. Albert Departmet of Computer Sciece, Uiversity of Otago Micah Colema, Rya Fly
More informationHow to use what you OWN to reduce what you OWE
How to use what you OWN to reduce what you OWE Maulife Oe A Overview Most Caadias maage their fiaces by doig two thigs: 1. Depositig their icome ad other short-term assets ito chequig ad savigs accouts.
More informationChapter 7 Methods of Finding Estimators
Chapter 7 for BST 695: Special Topics i Statistical Theory. Kui Zhag, 011 Chapter 7 Methods of Fidig Estimators Sectio 7.1 Itroductio Defiitio 7.1.1 A poit estimator is ay fuctio W( X) W( X1, X,, X ) of
More information5.4 Amortization. Question 1: How do you find the present value of an annuity? Question 2: How is a loan amortized?
5.4 Amortizatio Questio 1: How do you fid the preset value of a auity? Questio 2: How is a loa amortized? Questio 3: How do you make a amortizatio table? Oe of the most commo fiacial istrumets a perso
More informationSupply Chain Network Design with Preferential Tariff under Economic Partnership Agreement
roceedigs of the 2014 Iteratioal oferece o Idustrial Egieerig ad Oeratios Maageet Bali, Idoesia, Jauary 7 9, 2014 Suly hai Network Desig with referetial ariff uder Ecooic artershi greeet eichi Fuaki Yokohaa
More informationPre-Suit Collection Strategies
Pre-Suit Collectio Strategies Writte by Charles PT Phoeix How to Decide Whether to Pursue Collectio Calculatig the Value of Collectio As with ay busiess litigatio, all factors associated with the process
More informationStatistical inference: example 1. Inferential Statistics
Statistical iferece: example 1 Iferetial Statistics POPULATION SAMPLE A clothig store chai regularly buys from a supplier large quatities of a certai piece of clothig. Each item ca be classified either
More informationRF Engineering Continuing Education Introduction to Traffic Planning
RF Egieerig otiuig Educatio Itroductio to Traffic Plaig Queuig Systems Figure. shows a schematic reresetatio of a queuig system. This reresetatio is a mathematical abstractio suitable for may differet
More informationBanks, Taxes, and Nonbank Competition *
Commets Welcome Baks, Taxes, ad Nobak Competitio * by George Peacchi Departmet of Fiace Uiversity of Illiois 4041 BIF, Box 25 505 E. Gregory Drive Champaig, IL 61820 Phoe: (217) 244-0952 Email: gpeacc@illiois.edu
More informationA Mixed-Integer Optimization Model for Compressor Selection in Natural Gas Pipeline Network System Operations
Joural of virometal Iformatics 3 () 33-4 (2004) 04JI00025 726-235/684-8799 2004 ISIS www.iseis.org/jei A Mixed-Iteger Otimizatio Model for Comressor Selectio i Natural as Pielie Network System Oeratios
More informationVolatility of rates of return on the example of wheat futures. Sławomir Juszczyk. Rafał Balina
Overcomig the Crisis: Ecoomic ad Fiacial Developmets i Asia ad Europe Edited by Štefa Bojec, Josef C. Brada, ad Masaaki Kuboiwa http://www.hippocampus.si/isbn/978-961-6832-32-8/cotets.pdf Volatility of
More informationAmendments to employer debt Regulations
March 2008 Pesios Legal Alert Amedmets to employer debt Regulatios The Govermet has at last issued Regulatios which will amed the law as to employer debts uder s75 Pesios Act 1995. The amedig Regulatios
More informationDiscrete Mathematics and Probability Theory Spring 2014 Anant Sahai Note 13
EECS 70 Discrete Mathematics ad Probability Theory Sprig 2014 Aat Sahai Note 13 Itroductio At this poit, we have see eough examples that it is worth just takig stock of our model of probability ad may
More informationThe following example will help us understand The Sampling Distribution of the Mean. C1 C2 C3 C4 C5 50 miles 84 miles 38 miles 120 miles 48 miles
The followig eample will help us uderstad The Samplig Distributio of the Mea Review: The populatio is the etire collectio of all idividuals or objects of iterest The sample is the portio of the populatio
More informationUnit 8: Inference for Proportions. Chapters 8 & 9 in IPS
Uit 8: Iferece for Proortios Chaters 8 & 9 i IPS Lecture Outlie Iferece for a Proortio (oe samle) Iferece for Two Proortios (two samles) Cotigecy Tables ad the χ test Iferece for Proortios IPS, Chater
More informationbstract The aer ivestigates the imact of fiacial itegratio o asset retur, risk diversificatio ad breadth of fiacial markets. We aalyse a three-coutry macroecoomic model i which (i) the umber of fiacial
More informationEkkehart Schlicht: Economic Surplus and Derived Demand
Ekkehart Schlicht: Ecoomic Surplus ad Derived Demad Muich Discussio Paper No. 2006-17 Departmet of Ecoomics Uiversity of Muich Volkswirtschaftliche Fakultät Ludwig-Maximilias-Uiversität Müche Olie at http://epub.ub.ui-mueche.de/940/
More informationDetermining the sample size
Determiig the sample size Oe of the most commo questios ay statisticia gets asked is How large a sample size do I eed? Researchers are ofte surprised to fid out that the aswer depeds o a umber of factors
More informationA probabilistic proof of a binomial identity
A probabilistic proof of a biomial idetity Joatho Peterso Abstract We give a elemetary probabilistic proof of a biomial idetity. The proof is obtaied by computig the probability of a certai evet i two
More informationPreserving Your Financial Legacy with Life Insurance Premium Financing.
Preservig Your Fiacial Legacy with Life Isurace Premium Fiacig. Prepared by: Keeth M. Fujita, Natioal Director, The Private Bak Specialty Fiace Group Life Isurace Premium Fiace. James Mosrie, Seior Wealth
More informationSoving Recurrence Relations
Sovig Recurrece Relatios Part 1. Homogeeous liear 2d degree relatios with costat coefficiets. Cosider the recurrece relatio ( ) T () + at ( 1) + bt ( 2) = 0 This is called a homogeeous liear 2d degree
More informationBENEFIT-COST ANALYSIS Financial and Economic Appraisal using Spreadsheets
BENEIT-CST ANALYSIS iacial ad Ecoomic Appraisal usig Spreadsheets Ch. 2: Ivestmet Appraisal - Priciples Harry Campbell & Richard Brow School of Ecoomics The Uiversity of Queeslad Review of basic cocepts
More informationCS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations
CS3A Hadout 3 Witer 00 February, 00 Solvig Recurrece Relatios Itroductio A wide variety of recurrece problems occur i models. Some of these recurrece relatios ca be solved usig iteratio or some other ad
More informationODBC. Getting Started With Sage Timberline Office ODBC
ODBC Gettig Started With Sage Timberlie Office ODBC NOTICE This documet ad the Sage Timberlie Office software may be used oly i accordace with the accompayig Sage Timberlie Office Ed User Licese Agreemet.
More informationGrow your business with savings and debt management solutions
Grow your busiess with savigs ad debt maagemet solutios A few great reasos to provide bak ad trust products to your cliets You have the expertise to help your cliets get the best rates ad most competitive
More informationA markovian study of no claim discount system of Insurance Regulatory and Development Authority and its application
Thailad Statisticia July 214; 12(2): 223-236 htt://statassoc.or.th Cotributed aer A markovia study of o claim discout system of Isurace Regulatory ad Develomet Authority ad its alicatio Dili C. Nath* [a]
More informationData Analysis and Statistical Behaviors of Stock Market Fluctuations
44 JOURNAL OF COMPUTERS, VOL. 3, NO. 0, OCTOBER 2008 Data Aalysis ad Statistical Behaviors of Stock Market Fluctuatios Ju Wag Departmet of Mathematics, Beijig Jiaotog Uiversity, Beijig 00044, Chia Email:
More informationHow to read A Mutual Fund shareholder report
Ivestor BulletI How to read A Mutual Fud shareholder report The SEC s Office of Ivestor Educatio ad Advocacy is issuig this Ivestor Bulleti to educate idividual ivestors about mutual fud shareholder reports.
More informationTradigms of Astundithi and Toyota
Tradig the radomess - Desigig a optimal tradig strategy uder a drifted radom walk price model Yuao Wu Math 20 Project Paper Professor Zachary Hamaker Abstract: I this paper the author iteds to explore
More informationSupply Chain Management
Supply Chai Maagemet LOA Uiversity October 9, 205 Distributio D Distributio Authorized to Departmet of Defese ad U.S. DoD Cotractors Oly Aim High Fly - Fight - Wi Who am I? Dr. William A Cuigham PhD Ecoomics
More information5: Introduction to Estimation
5: Itroductio to Estimatio Cotets Acroyms ad symbols... 1 Statistical iferece... Estimatig µ with cofidece... 3 Samplig distributio of the mea... 3 Cofidece Iterval for μ whe σ is kow before had... 4 Sample
More informationHypothesis testing. Null and alternative hypotheses
Hypothesis testig Aother importat use of samplig distributios is to test hypotheses about populatio parameters, e.g. mea, proportio, regressio coefficiets, etc. For example, it is possible to stipulate
More informationSavings and Retirement Benefits
60 Baltimore Couty Public Schools offers you several ways to begi savig moey through payroll deductios. Defied Beefit Pesio Pla Tax Sheltered Auities ad Custodial Accouts Defied Beefit Pesio Pla Did you
More informationMAGNT Research Report (ISSN. 1444-8939) Vol.3 (2). PP: 189-198
MAGNT Research Reort (ISSN. 14448939) Vol.3 (2). PP: 189198 Exlaiig the Model of the Imact of Demograhic Variables with kowledge ad Collaborative Accordig to the Moderatig Role of Orgaizatioal Culture
More informationCenter, Spread, and Shape in Inference: Claims, Caveats, and Insights
Ceter, Spread, ad Shape i Iferece: Claims, Caveats, ad Isights Dr. Nacy Pfeig (Uiversity of Pittsburgh) AMATYC November 2008 Prelimiary Activities 1. I would like to produce a iterval estimate for the
More informationBENCHMARK NEW PRODUCT DEVELOPMENT PROCESSES USING DEA-BASED MODULARIZED APPROACH
BENCHMARK NEW PRODUCT DEVELOPMENT PROCESSES USING DEA-BASED MODULARIZED APPROACH Tzu-A Chiag, Migchi Uiversity o Techology, tachiag@mail.mit.edu.tw Amy J.C. Traey, Natioal Taiei Uiversity o Techology,
More informationProperties of MLE: consistency, asymptotic normality. Fisher information.
Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout
More informationFI A CIAL MATHEMATICS
CHAPTER 7 FI A CIAL MATHEMATICS Page Cotets 7.1 Compoud Value 117 7.2 Compoud Value of a Auity 118 7.3 Sikig Fuds 119 7.4 Preset Value 122 7.5 Preset Value of a Auity 122 7.6 Term Loas ad Amortizatio 123
More informationDesigning Incentives for Online Question and Answer Forums
Desigig Icetives for Olie Questio ad Aswer Forums Shaili Jai School of Egieerig ad Applied Scieces Harvard Uiversity Cambridge, MA 0238 USA shailij@eecs.harvard.edu Yilig Che School of Egieerig ad Applied
More informationIntroducing Your New Wells Fargo Trust and Investment Statement. Your Account Information Simply Stated.
Itroducig Your New Wells Fargo Trust ad Ivestmet Statemet. Your Accout Iformatio Simply Stated. We are pleased to itroduce your ew easy-to-read statemet. It provides a overview of your accout ad a complete
More informationEstimating Probability Distributions by Observing Betting Practices
5th Iteratioal Symposium o Imprecise Probability: Theories ad Applicatios, Prague, Czech Republic, 007 Estimatig Probability Distributios by Observig Bettig Practices Dr C Lych Natioal Uiversity of Irelad,
More informationLecture 2: Karger s Min Cut Algorithm
priceto uiv. F 3 cos 5: Advaced Algorithm Desig Lecture : Karger s Mi Cut Algorithm Lecturer: Sajeev Arora Scribe:Sajeev Today s topic is simple but gorgeous: Karger s mi cut algorithm ad its extesio.
More informationBond Valuation I. What is a bond? Cash Flows of A Typical Bond. Bond Valuation. Coupon Rate and Current Yield. Cash Flows of A Typical Bond
What is a bod? Bod Valuatio I Bod is a I.O.U. Bod is a borrowig agreemet Bod issuers borrow moey from bod holders Bod is a fixed-icome security that typically pays periodic coupo paymets, ad a pricipal
More informationAsymptotic Growth of Functions
CMPS Itroductio to Aalysis of Algorithms Fall 3 Asymptotic Growth of Fuctios We itroduce several types of asymptotic otatio which are used to compare the performace ad efficiecy of algorithms As we ll
More informationINVESTMENT PERFORMANCE COUNCIL (IPC)
INVESTMENT PEFOMANCE COUNCIL (IPC) INVITATION TO COMMENT: Global Ivestmet Performace Stadards (GIPS ) Guidace Statemet o Calculatio Methodology The Associatio for Ivestmet Maagemet ad esearch (AIM) seeks
More informationRISK TRANSFER FOR DESIGN-BUILD TEAMS
WILLIS CONSTRUCTION PRACTICE I-BEAM Jauary 2010 www.willis.com RISK TRANSFER FOR DESIGN-BUILD TEAMS Desig-builD work is icreasig each quarter. cosequetly, we are fieldig more iquiries from cliets regardig
More informationCase Study. Normal and t Distributions. Density Plot. Normal Distributions
Case Study Normal ad t Distributios Bret Halo ad Bret Larget Departmet of Statistics Uiversity of Wiscosi Madiso October 11 13, 2011 Case Study Body temperature varies withi idividuals over time (it ca
More informationHow To Find FINANCING For Your Business
How To Fid FINANCING For Your Busiess Oe of the most difficult tasks faced by the maagemet team of small busiesses today is fidig adequate fiacig for curret operatios i order to support ew ad ogoig cotracts.
More informationPerformance Attribution in Private Equity
Performace Attributio i Private Equity Austi M. Log, III MPA, CPA, JD Parter Aligmet Capital Group 4500 Steier Rach Blvd., Ste. 806 Austi, TX 78732 Phoe 512.506.8299 Fax 512.996.0970 E-mail alog@aligmetcapital.com
More informationChapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions
Chapter 5 Uit Aual Amout ad Gradiet Fuctios IET 350 Egieerig Ecoomics Learig Objectives Chapter 5 Upo completio of this chapter you should uderstad: Calculatig future values from aual amouts. Calculatig
More informationInfinite Sequences and Series
CHAPTER 4 Ifiite Sequeces ad Series 4.1. Sequeces A sequece is a ifiite ordered list of umbers, for example the sequece of odd positive itegers: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29...
More informationAnnuities Under Random Rates of Interest II By Abraham Zaks. Technion I.I.T. Haifa ISRAEL and Haifa University Haifa ISRAEL.
Auities Uder Radom Rates of Iterest II By Abraham Zas Techio I.I.T. Haifa ISRAEL ad Haifa Uiversity Haifa ISRAEL Departmet of Mathematics, Techio - Israel Istitute of Techology, 3000, Haifa, Israel I memory
More informationNon-life insurance mathematics. Nils F. Haavardsson, University of Oslo and DNB Skadeforsikring
No-life isurace mathematics Nils F. Haavardsso, Uiversity of Oslo ad DNB Skadeforsikrig Mai issues so far Why does isurace work? How is risk premium defied ad why is it importat? How ca claim frequecy
More informationRegression with a Binary Dependent Variable (SW Ch. 11)
Regressio with a Biary Deedet Variable (SW Ch. 11) So far the deedet variable (Y) has bee cotiuous: district-wide average test score traffic fatality rate But we might wat to uderstad the effect of X o
More informationCHAPTER 7: Central Limit Theorem: CLT for Averages (Means)
CHAPTER 7: Cetral Limit Theorem: CLT for Averages (Meas) X = the umber obtaied whe rollig oe six sided die oce. If we roll a six sided die oce, the mea of the probability distributio is X P(X = x) Simulatio:
More informationDAME - Microsoft Excel add-in for solving multicriteria decision problems with scenarios Radomir Perzina 1, Jaroslav Ramik 2
Itroductio DAME - Microsoft Excel add-i for solvig multicriteria decisio problems with scearios Radomir Perzia, Jaroslav Ramik 2 Abstract. The mai goal of every ecoomic aget is to make a good decisio,
More information1. C. The formula for the confidence interval for a population mean is: x t, which was
s 1. C. The formula for the cofidece iterval for a populatio mea is: x t, which was based o the sample Mea. So, x is guarateed to be i the iterval you form.. D. Use the rule : p-value
More informationSection 11.3: The Integral Test
Sectio.3: The Itegral Test Most of the series we have looked at have either diverged or have coverged ad we have bee able to fid what they coverge to. I geeral however, the problem is much more difficult
More informationConfidence Intervals. CI for a population mean (σ is known and n > 30 or the variable is normally distributed in the.
Cofidece Itervals A cofidece iterval is a iterval whose purpose is to estimate a parameter (a umber that could, i theory, be calculated from the populatio, if measuremets were available for the whole populatio).
More informationFM4 CREDIT AND BORROWING
FM4 CREDIT AND BORROWING Whe you purchase big ticket items such as cars, boats, televisios ad the like, retailers ad fiacial istitutios have various terms ad coditios that are implemeted for the cosumer
More informationTime Value of Money. First some technical stuff. HP10B II users
Time Value of Moey Basis for the course Power of compoud iterest $3,600 each year ito a 401(k) pla yields $2,390,000 i 40 years First some techical stuff You will use your fiacial calculator i every sigle
More informationMTO-MTS Production Systems in Supply Chains
NSF GRANT #0092854 NSF PROGRAM NAME: MES/OR MTO-MTS Productio Systems i Supply Chais Philip M. Kamisky Uiversity of Califoria, Berkeley Our Kaya Uiversity of Califoria, Berkeley Abstract: Icreasig cost
More informationWHAT IS YOUR PRIORITY?
MOVE AHEAD The uderlyig priciples of soud ivestmet should ot alter from decade to decade, but the applicatio of these priciples must be adapted to sigificat chages i the fiacial mechaisms ad climate. BENJAMIN
More informationIncremental calculation of weighted mean and variance
Icremetal calculatio of weighted mea ad variace Toy Fich faf@cam.ac.uk dot@dotat.at Uiversity of Cambridge Computig Service February 009 Abstract I these otes I eplai how to derive formulae for umerically
More information*The most important feature of MRP as compared with ordinary inventory control analysis is its time phasing feature.
Itegrated Productio ad Ivetory Cotrol System MRP ad MRP II Framework of Maufacturig System Ivetory cotrol, productio schedulig, capacity plaig ad fiacial ad busiess decisios i a productio system are iterrelated.
More informationLEASE-PURCHASE DECISION
Public Procuremet Practice STANDARD The decisio to lease or purchase should be cosidered o a case-by case evaluatio of comparative costs ad other factors. 1 Procuremet should coduct a cost/ beefit aalysis
More informationTO: Users of the ACTEX Review Seminar on DVD for SOA Exam FM/CAS Exam 2
TO: Users of the ACTEX Review Semiar o DVD for SOA Exam FM/CAS Exam FROM: Richard L. (Dick) Lodo, FSA Dear Studets, Thak you for purchasig the DVD recordig of the ACTEX Review Semiar for SOA Exam FM (CAS
More informationOne-sample test of proportions
Oe-sample test of proportios The Settig: Idividuals i some populatio ca be classified ito oe of two categories. You wat to make iferece about the proportio i each category, so you draw a sample. Examples:
More informationIn nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008
I ite Sequeces Dr. Philippe B. Laval Keesaw State Uiversity October 9, 2008 Abstract This had out is a itroductio to i ite sequeces. mai de itios ad presets some elemetary results. It gives the I ite Sequeces
More informationTHE HEIGHT OF q-binary SEARCH TREES
THE HEIGHT OF q-binary SEARCH TREES MICHAEL DRMOTA AND HELMUT PRODINGER Abstract. q biary search trees are obtaied from words, equipped with the geometric distributio istead of permutatios. The average
More informationRisk contributions of trading and non-trading hours: Evidence from commodity futures markets
Risk cotributios of tradig ad o-tradig hours: Evidece from commodity futures markets Qigfu Liu Istitute for Fiacial Studies Fuda Uiversity, Shaghai, Chia Yubi A 1 Odette School of Busiess Uiversity of
More informationPSYCHOLOGICAL STATISTICS
UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION B Sc. Cousellig Psychology (0 Adm.) IV SEMESTER COMPLEMENTARY COURSE PSYCHOLOGICAL STATISTICS QUESTION BANK. Iferetial statistics is the brach of statistics
More informationMainStay Funds IRA/SEP/Roth IRA Distribution Form
MaiStay Fuds IRA/SEP/Roth IRA Distributio Form Do ot use for IRA Trasfers or SIMPLE IRA INSTRUCTIONS Before completig this form, please refer to the applicable Custodial Agreemet ad Disclosure Statemet
More informationStatement of cash flows
6 Statemet of cash flows this chapter covers... I this chapter we study the statemet of cash flows, which liks profit from the statemet of profit or loss ad other comprehesive icome with chages i assets
More informationQuaderni di Dipartimento. A note on the Exclusion Principle. Paolo Bertoletti (University of Pavia) # 179 (12-05)
Quaderi di Diartimeto A ote o te xclusio Pricile Paolo Bertoletti Uiersity of Paia # 79-05 Diartimeto di ecoomia olitica e metodi quatitatii Uiersità degli studi di Paia Via Sa Felice 5 I-700 Paia Dicembre
More informationAnalyzing Longitudinal Data from Complex Surveys Using SUDAAN
Aalyzig Logitudial Data from Complex Surveys Usig SUDAAN Darryl Creel Statistics ad Epidemiology, RTI Iteratioal, 312 Trotter Farm Drive, Rockville, MD, 20850 Abstract SUDAAN: Software for the Statistical
More informationOn the L p -conjecture for locally compact groups
Arch. Math. 89 (2007), 237 242 c 2007 Birkhäuser Verlag Basel/Switzerlad 0003/889X/030237-6, ublished olie 2007-08-0 DOI 0.007/s0003-007-993-x Archiv der Mathematik O the L -cojecture for locally comact
More informationCHAPTER 3 DIGITAL CODING OF SIGNALS
CHAPTER 3 DIGITAL CODING OF SIGNALS Computers are ofte used to automate the recordig of measuremets. The trasducers ad sigal coditioig circuits produce a voltage sigal that is proportioal to a quatity
More informationECE606: Solid State Devices Lecture 16 p-n diode AC Response
ECE66: Solid State Devices Lecture 16 - diode C esose Gerhard Klimeck gekco@urdue.edu Klimeck ECE66 Fall 1 otes adoted from lam Toic Ma Equilibrium DC Small sigal Large Sigal Circuits Diode Schottky Diode
More information