# QUANTITATIVE METHODS CLASSES WEEK SEVEN

Save this PDF as:

Size: px
Start display at page:

## Transcription

1 QUANTITATIVE METHODS CLASSES WEEK SEVEN Th rgrssion modls studid in prvious classs assum that th rspons variabl is quantitativ. Oftn, howvr, w wish to study social procsss that lad to two diffrnt outcoms. In ths instancs, thn, th rspons variabl is catgorical. For xampl, whn w study unmploymnt, marriag or votr s choic. In th cas of unmploymnt, for xampl, our rspondnts will ithr b mployd or unmployd. Dnot th rspons on Y by 1 if unmployd and 0 if mployd (it is also common to us th trm failur and succss). Th sum of th scors in th sampl is thn th numbr of succsss (i.., unmployd rspondnts). Th man of this rspons variabl (th 0s and 1s scors) quals th proportion of succsss (i.., th proportion of unmployd rspondnts). Obviously, thn, th proportion of mployd rspondnts quals 1-that man. Transforming th catgorical rspons variabl (0,1) to proportion allows us to think in trns of rgrssion analysis, sinc th ordinary rgrssion modls th man of th rspons variabl. Lt π dnot th probability of succss, and it is possibl to writ th following linar quation: π=a+b() This is th linar probability modl, and it implis that th probability of succss is a linar function of. Unfortunatly, this modl is oftn poor. First, it implis probabilitis blow 0 and abov 1, whras probabilitis must fall btwn 0 and 1. Scond, th rspons variabl is not normally distributd, and thus it violats som of th assumptions w mak whn applying OLS rgrssion. Thus, w nd to furthr transform our rspons variabl. In othr words, w nd to dscrib th rlationship btwn π and with a curvilinar rathr than a linar function. This can b achivd by th following quation: π log = α + β 1 π Th ratio π/(1- π) quals th odds. Thus, for xampl, whn th proportion of unmployd individuals (succss) in our sampl quals 0.20 th odds quals 0.25 (0.2/0.8=0.25), which mans that a succss is four tims lss likly as failur. This quation uss th natural log of th odds, and is calld th logistic transformation, or logit for short. Thus, as π incrass from 0 to 1, th odds incrass from 0 to +, and th logit incrass from to +. Tabl 1: Rangs of Probability, Odds and Log Odds Lowst Lvl Mid point Highst Lvl Probability π Odds π /1- π Log Odds log (π /1- π) or logit (π) 0 + 1

2 Logistic Rgrssion Th modl: logit (π) =a+b is calld th logistic rgrssion modl. In logistic rgrssion th paramtrs of th modl ar stimatd using th maximumliklihood mthod. That is, th cofficints that mak th obsrvd rsults most likly ar slctd. For ach possibl valu a paramtr might hav, SPSS computs th probability that th obsrvd valu would hav occurrd if it wr th tru valu of th paramtr. Thn, for th stimat, it picks th paramtr for which th probability of th actual obsrvation is gratst. Th quation for logistic rgrssion may b givn in ithr th additiv or multiplicativ forms. Additiv form: log (π/1-π) = a + ß Multiplicativ form: π/1-π = xp (a) *xp ( ß ) π is th proportion with th charactristic (th probability), a is a constant, ß 1,ß 2... ar cofficints and 1, 2... ar prdictor variabls. log π/1-π is known as th log-odds and π/1- π as th odds. Exponntial (ß), ar th odds multiplirs and intrst is in valus that diffr from 1. Running Logistic Rgrssion in SPSS Hr w modl th probability of bing unmployd rathr than bing mployd (EMP86). First, w hav to mak sur that EMP86 is codd 1 and 0. It is important to cod th succss as 1. As w ar intrstd in prdicting unmploymnt, th unmployd should b codd 1 and th mployd codd 0 (w simply crat a nw variabl UNEMP: 0=mployd and 1=unmployd). W ar going to us two prdictors: Class and Ag. As Class is a catgorical variabl, w nd to rcod class to a thr-catgory variabl (CLASS1: 10,20=1 (prof); 31,41,42,43,50=2 (intr); and, 32,60,71,72=3 (working)), and thn to crat dummy variabls for Prof, Intr and working. logistic rgrssion variabls=unmp /mthod = ntr prof intr. 2

4 2. Th Cofficints. B S.E. Wald Df Sig. Exp(B) AGE PROF INTER Constant a Variabl(s) ntrd on stp 1: AGE, PROF, INTER. Th Bs rfr to th log-odds of bing unmployd. W can insrt ths into th logistic rgrssion quation as was don in multipl rgrssion. Additiv form: logit( π ) = α + β + β... + β n n = (.027)( AGE) + ( 1.145)( PROF) + (.722)( INTER) This tlls us that incrasing ag dcrass th log odds of unmploymnt (controlling for class). Bing in th profssional/managrial class or bing in th intrmdiat class also rducs th log-odds of bing unmployd rlativ to thos in th working class. Th Wald statistic (B/SE). Most softwar rports its squar (B/SE) 2. Th significanc of th Wald statistic is rportd in th column markd Sig. This shows that th thr prdictor variabls ar significant. If th cofficint is vry larg th Wald statistic can bcom unrliabl so you should rfr to th chang in th log liklihood instad (s blow). Howvr, log-odds is not a vry straightforward concpt. It is probably asir to us th multiplicativ form of th quation using xp(b), s last column of th SPSS output. Ths ar th Odds Multiplirs. Multiplicativ form π = (1 π) α β β n n (AGE) 1.145(PROF) 0.722(INTER) = = (AGE) 0.318(PROF) 0.486(INTER) Rmmbr intrst is in cofficints that diffr from 1. Valus gratr than 1 indicat that th variabl in qustion incrass th odds of th dpndnt vnt occurring and valus lss than 1 (i.. btwn 0 and 1) indicat a dcras in th odds. Effctivly th odds for th bas catgory ar st to 1. Using th odds multiplirs w can mak th mor undrstandabl claims that, whn othr factors in th modl ar hld constant: ach addd yar of ag lads to about 3% rduction in th odds of bing unmployd. 4

5 bing in th profssional class, compard to bing in th working class, lads to about 68% rduction in th odds of bing unmployd bing in th intrmdiat class, compard to bing in th working class, lads to about 51% rduction in th odds of bing unmployd. 2. Estimating Probabilitis Th original logistic rgrssion quation can b transformd to show th stimatd probability of succss by: (α + β ) π = (α + β β β β ) β ) 3 3 so for any individual th probability of bing unmployd can b calculatd. Exampl: What is th stimatd probability of bing unmployd for a prson agd 30 in th profssional class? ( (0.27)(30) + ( 1.145)(1) ).137 π = = = =.12 ( (0.27)(30) + ( 1.145)(1) Answr: a 30 yar old profssional has an stimatd probability of bing unmployd of.12. 5

### Question 3: How do you find the relative extrema of a function?

ustion 3: How do you find th rlativ trma of a function? Th stratgy for tracking th sign of th drivativ is usful for mor than dtrmining whr a function is incrasing or dcrasing. It is also usful for locating

### by John Donald, Lecturer, School of Accounting, Economics and Finance, Deakin University, Australia

Studnt Nots Cost Volum Profit Analysis by John Donald, Lcturr, School of Accounting, Economics and Financ, Dakin Univrsity, Australia As mntiond in th last st of Studnt Nots, th ability to catgoris costs

### Econ 371: Answer Key for Problem Set 1 (Chapter 12-13)

con 37: Answr Ky for Problm St (Chaptr 2-3) Instructor: Kanda Naknoi Sptmbr 4, 2005. (2 points) Is it possibl for a country to hav a currnt account dficit at th sam tim and has a surplus in its balanc

### Non-Homogeneous Systems, Euler s Method, and Exponential Matrix

Non-Homognous Systms, Eulr s Mthod, and Exponntial Matrix W carry on nonhomognous first-ordr linar systm of diffrntial quations. W will show how Eulr s mthod gnralizs to systms, giving us a numrical approach

### Parallel and Distributed Programming. Performance Metrics

Paralll and Distributd Programming Prformanc! wo main goals to b achivd with th dsign of aralll alications ar:! Prformanc: th caacity to rduc th tim to solv th roblm whn th comuting rsourcs incras;! Scalability:

### The Matrix Exponential

Th Matrix Exponntial (with xrciss) 92.222 - Linar Algbra II - Spring 2006 by D. Klain prliminary vrsion Corrctions and commnts ar wlcom! Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial

### Adverse Selection and Moral Hazard in a Model With 2 States of the World

Advrs Slction and Moral Hazard in a Modl With 2 Stats of th World A modl of a risky situation with two discrt stats of th world has th advantag that it can b natly rprsntd using indiffrnc curv diagrams,

### Mathematics. Mathematics 3. hsn.uk.net. Higher HSN23000

hsn uknt Highr Mathmatics UNIT Mathmatics HSN000 This documnt was producd spcially for th HSNuknt wbsit, and w rquir that any copis or drivativ works attribut th work to Highr Still Nots For mor dtails

### Foreign Exchange Markets and Exchange Rates

Microconomics Topic 1: Explain why xchang rats indicat th pric of intrnational currncis and how xchang rats ar dtrmind by supply and dmand for currncis in intrnational markts. Rfrnc: Grgory Mankiw s Principls

### The example is taken from Sect. 1.2 of Vol. 1 of the CPN book.

Rsourc Allocation Abstract This is a small toy xampl which is wll-suitd as a first introduction to Cnts. Th CN modl is dscribd in grat dtail, xplaining th basic concpts of C-nts. Hnc, it can b rad by popl

### Traffic Flow Analysis (2)

Traffic Flow Analysis () Statistical Proprtis. Flow rat distributions. Hadway distributions. Spd distributions by Dr. Gang-Ln Chang, Profssor Dirctor of Traffic safty and Oprations Lab. Univrsity of Maryland,

### Lecture 3: Diffusion: Fick s first law

Lctur 3: Diffusion: Fick s first law Today s topics What is diffusion? What drivs diffusion to occur? Undrstand why diffusion can surprisingly occur against th concntration gradint? Larn how to dduc th

### 5 2 index. e e. Prime numbers. Prime factors and factor trees. Powers. worked example 10. base. power

Prim numbrs W giv spcial nams to numbrs dpnding on how many factors thy hav. A prim numbr has xactly two factors: itslf and 1. A composit numbr has mor than two factors. 1 is a spcial numbr nithr prim

### Deer: Predation or Starvation

: Prdation or Starvation National Scinc Contnt Standards: Lif Scinc: s and cosystms Rgulation and Bhavior Scinc in Prsonal and Social Prspctiv s, rsourcs and nvironmnts Unifying Concpts and Procsss Systms,

### AP Calculus AB 2008 Scoring Guidelines

AP Calculus AB 8 Scoring Guidlins Th Collg Board: Conncting Studnts to Collg Succss Th Collg Board is a not-for-profit mmbrship association whos mission is to connct studnts to collg succss and opportunity.

### New Basis Functions. Section 8. Complex Fourier Series

Nw Basis Functions Sction 8 Complx Fourir Sris Th complx Fourir sris is prsntd first with priod 2, thn with gnral priod. Th connction with th ral-valud Fourir sris is xplaind and formula ar givn for convrting

### Principles of Humidity Dalton s law

Principls of Humidity Dalton s law Air is a mixtur of diffrnt gass. Th main gas componnts ar: Gas componnt volum [%] wight [%] Nitrogn N 2 78,03 75,47 Oxygn O 2 20,99 23,20 Argon Ar 0,93 1,28 Carbon dioxid

### CALCULATING MARGINAL PROBABILITIES IN PROC PROBIT Guy Pascale, Memorial Health Alliance

CALCULATING MARGINAL PROBABILITIES IN PROC PROBIT Guy Pascal, Mmorial Halth Allianc Introduction Th PROBIT procdur within th SAS systm provids a simpl mthod for stimating discrt choic variabls (i.. dichotomous

### the so-called KOBOS system. 1 with the exception of a very small group of the most active stocks which also trade continuously through

Liquidity and Information-Basd Trading on th Ordr Drivn Capital Markt: Th Cas of th Pragu tock Exchang Libor 1ÀPH³HN Cntr for Economic Rsarch and Graduat Education, Charls Univrsity and Th Economic Institut

### EFFECT OF GEOMETRICAL PARAMETERS ON HEAT TRANSFER PERFORMACE OF RECTANGULAR CIRCUMFERENTIAL FINS

25 Vol. 3 () January-March, pp.37-5/tripathi EFFECT OF GEOMETRICAL PARAMETERS ON HEAT TRANSFER PERFORMACE OF RECTANGULAR CIRCUMFERENTIAL FINS *Shilpa Tripathi Dpartmnt of Chmical Enginring, Indor Institut

### HSBC Bank International Expat Explorer Survey 08

HSBC Bank Intrnational Expat Explorr Survy 08 Rport On: Expat Existnc Th Survy Th Expat Explorr survy qustiond 2,155 xpatriats across four continnts about th opportunitis and challngs thy fac. Th survy

### A Theoretical Model of Public Response to the Homeland Security Advisory System

A Thortical Modl of Public Rspons to th Homland Scurity Advisory Systm Amy (Wnxuan) Ding Dpartmnt of Information and Dcision Scincs Univrsity of Illinois Chicago, IL 60607 wxding@uicdu Using a diffrntial

### C H A P T E R 1 Writing Reports with SAS

C H A P T E R 1 Writing Rports with SAS Prsnting information in a way that s undrstood by th audinc is fundamntally important to anyon s job. Onc you collct your data and undrstand its structur, you nd

### The Normal Distribution: A derivation from basic principles

Th Normal Distribution: A drivation from basic principls Introduction Dan Tagu Th North Carolina School of Scinc and Mathmatics Studnts in lmntary calculus, statistics, and finit mathmatics classs oftn

### Intermediate Macroeconomic Theory / Macroeconomic Analysis (ECON 3560/5040) Final Exam (Answers)

Intrmdiat Macroconomic Thory / Macroconomic Analysis (ECON 3560/5040) Final Exam (Answrs) Part A (5 points) Stat whthr you think ach of th following qustions is tru (T), fals (F), or uncrtain (U) and brifly

### 5.4 Exponential Functions: Differentiation and Integration TOOTLIFTST:

.4 Eponntial Functions: Diffrntiation an Intgration TOOTLIFTST: Eponntial functions ar of th form f ( ) Ab. W will, in this sction, look at a spcific typ of ponntial function whr th bas, b, is.78.... This

### Statistical Machine Translation

Statistical Machin Translation Sophi Arnoult, Gidon Mailltt d Buy Wnnigr and Andra Schuch Dcmbr 7, 2010 1 Introduction All th IBM modls, and Statistical Machin Translation (SMT) in gnral, modl th problm

### SPECIAL VOWEL SOUNDS

SPECIAL VOWEL SOUNDS Plas consult th appropriat supplmnt for th corrsponding computr softwar lsson. Rfr to th 42 Sounds Postr for ach of th Spcial Vowl Sounds. TEACHER INFORMATION: Spcial Vowl Sounds (SVS)

### SUBATOMIC PARTICLES AND ANTIPARTICLES AS DIFFERENT STATES OF THE SAME MICROCOSM OBJECT. Eduard N. Klenov* Rostov-on-Don. Russia

SUBATOMIC PARTICLES AND ANTIPARTICLES AS DIFFERENT STATES OF THE SAME MICROCOSM OBJECT Eduard N. Klnov* Rostov-on-Don. Russia Th distribution law for th valus of pairs of th consrvd additiv quantum numbrs

### Abstract. Introduction. Statistical Approach for Analyzing Cell Phone Handoff Behavior. Volume 3, Issue 1, 2009

Volum 3, Issu 1, 29 Statistical Approach for Analyzing Cll Phon Handoff Bhavior Shalini Saxna, Florida Atlantic Univrsity, Boca Raton, FL, shalinisaxna1@gmail.com Sad A. Rajput, Farquhar Collg of Arts

### Free ACA SOLUTION (IRS 1094&1095 Reporting)

Fr ACA SOLUTION (IRS 1094&1095 Rporting) Th Insuranc Exchang (301) 279-1062 ACA Srvics Transmit IRS Form 1094 -C for mployrs Print & mail IRS Form 1095-C to mploys HR Assist 360 will gnrat th 1095 s for

### Keywords Cloud Computing, Service level agreement, cloud provider, business level policies, performance objectives.

Volum 3, Issu 6, Jun 2013 ISSN: 2277 128X Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring Rsarch Papr Availabl onlin at: wwwijarcsscom Dynamic Ranking and Slction of Cloud

### 7 Timetable test 1 The Combing Chart

7 Timtabl tst 1 Th Combing Chart 7.1 Introduction 7.2 Tachr tams two workd xampls 7.3 Th Principl of Compatibility 7.4 Choosing tachr tams workd xampl 7.5 Ruls for drawing a Combing Chart 7.6 Th Combing

### Category 7: Employee Commuting

7 Catgory 7: Employ Commuting Catgory dscription This catgory includs missions from th transportation of mploys 4 btwn thir homs and thir worksits. Emissions from mploy commuting may aris from: Automobil

### Lecture 20: Emitter Follower and Differential Amplifiers

Whits, EE 3 Lctur 0 Pag of 8 Lctur 0: Emittr Followr and Diffrntial Amplifirs Th nxt two amplifir circuits w will discuss ar ry important to lctrical nginring in gnral, and to th NorCal 40A spcifically.

### Logo Design/Development 1-on-1

Logo Dsign/Dvlopmnt 1-on-1 If your company is looking to mak an imprssion and grow in th marktplac, you ll nd a logo. Fortunatly, a good graphic dsignr can crat on for you. Whil th pric tags for thos famous

### Use a high-level conceptual data model (ER Model). Identify objects of interest (entities) and relationships between these objects

Chaptr 3: Entity Rlationship Modl Databas Dsign Procss Us a high-lvl concptual data modl (ER Modl). Idntify objcts of intrst (ntitis) and rlationships btwn ths objcts Idntify constraints (conditions) End

### CPS 220 Theory of Computation REGULAR LANGUAGES. Regular expressions

CPS 22 Thory of Computation REGULAR LANGUAGES Rgular xprssions Lik mathmatical xprssion (5+3) * 4. Rgular xprssion ar built using rgular oprations. (By th way, rgular xprssions show up in various languags:

### Financial Mathematics

Financial Mathatics A ractical Guid for Actuaris and othr Businss rofssionals B Chris Ruckan, FSA & Jo Francis, FSA, CFA ublishd b B rofssional Education Solutions to practic qustions Chaptr 7 Solution

### Time to Event Tutorial. Outline. How Not to Understand Time to Event

Holford & Lavill http://www.pag-mting.org/dfault.asp?abstract=8 Rvision Errors corrctd slid 8 Tim to Evnt Tutorial Nick Holford Dpt Pharmacology & Clinical Pharmacology Univrsity of Auckland, Nw Zaland

### An Adaptive Clustering MAP Algorithm to Filter Speckle in Multilook SAR Images

An Adaptiv Clustring MAP Algorithm to Filtr Spckl in Multilook SAR Imags FÁTIMA N. S. MEDEIROS 1,3 NELSON D. A. MASCARENHAS LUCIANO DA F. COSTA 1 1 Cybrntic Vision Group IFSC -Univrsity of São Paulo Caia

### FACULTY SALARIES FALL 2004. NKU CUPA Data Compared To Published National Data

FACULTY SALARIES FALL 2004 NKU CUPA Data Compard To Publishd National Data May 2005 Fall 2004 NKU Faculty Salaris Compard To Fall 2004 Publishd CUPA Data In th fall 2004 Northrn Kntucky Univrsity was among

### ESTIMATING VEHICLE ROADSIDE ENCROACHMENT FREQUENCY USING ACCIDENT PREDICTION MODELS

ESTMATNG VEHCLE ROADSDE ENCROACHMENT FREQUENCY USNG ACCDENT PREDCTON MODELS ShawPin Miaou Cntr for Transportation Analysis, Enrgy Division Oak Ridg National Laboratory P.O.Box 28,MS 6366, Building 55A

### (Analytic Formula for the European Normal Black Scholes Formula)

(Analytic Formula for th Europan Normal Black Schols Formula) by Kazuhiro Iwasawa Dcmbr 2, 2001 In this short summary papr, a brif summary of Black Schols typ formula for Normal modl will b givn. Usually

### METHODS FOR HANDLING TIED EVENTS IN THE COX PROPORTIONAL HAZARD MODEL

STUDIA OECONOMICA POSNANIENSIA 204, vol. 2, no. 2 (263 Jadwiga Borucka Warsaw School of Economics, Institut of Statistics and Dmography, Evnt History and Multilvl Analysis Unit jadwiga.borucka@gmail.com

### June 2012. Enprise Rent. Enprise 1.1.6. Author: Document Version: Product: Product Version: SAP Version: 8.81.100 8.8

Jun 22 Enpris Rnt Author: Documnt Vrsion: Product: Product Vrsion: SAP Vrsion: Enpris Enpris Rnt 88 88 Enpris Rnt 22 Enpris Solutions All rights rsrvd No parts of this work may b rproducd in any form or

### Estimating Aboveground Tree Biomass on Forest Land in the Pacific Northwest: A Comparison of Approaches

Unitd Stats Dpartmnt of Agricultur Forst Srvic Pacific Southwst Rsarch Station Rsarch Papr PNW-RP-584 Novmbr 2009 Estimating Abovground Tr Biomass on Forst Land in th Pacific Northwst: A Comparison of

### Principal Component Analysis & Factor Analysis. Purpose. Principal Component Analysis. Principal Component Analysis. Principal Component Analysis

Principal Componnt Analysis & Factor Analysis Psych 818 DShon Purpos Both ar usd to rduc th dimnsionality of corrlatd masurmnts Can b usd in a purly xploratory fashion to invstigat dimnsionality Or, can

### Long run: Law of one price Purchasing Power Parity. Short run: Market for foreign exchange Factors affecting the market for foreign exchange

Lctur 6: Th Forign xchang Markt xchang Rats in th long run CON 34 Mony and Banking Profssor Yamin Ahmad xchang Rats in th Short Run Intrst Parity Big Concpts Long run: Law of on pric Purchasing Powr Parity

### Section 5-5 Inverse of a Square Matrix

- Invrs of a Squar Matrix 9 (D) Rank th playrs from strongst to wakst. Explain th rasoning hind your ranking. 68. Dominan Rlation. Eah mmr of a hss tam plays on math with vry othr playr. Th rsults ar givn

### Installation Saving Space-efficient Panel Enhanced Physical Durability Enhanced Performance Warranty The IRR Comparison

Contnts Tchnology Nwly Dvlopd Cllo Tchnology Cllo Tchnology : Improvd Absorption of Light Doubl-sidd Cll Structur Cllo Tchnology : Lss Powr Gnration Loss Extrmly Low LID Clls 3 3 4 4 4 Advantag Installation

### HOMEWORK FOR UNIT 5-1: FORCE AND MOTION

Nam Dat Partnrs HOMEWORK FOR UNIT 51: FORCE AND MOTION 1. You ar givn tn idntial springs. Dsrib how you would dvlop a sal of for (i., a mans of produing rpatabl fors of a varity of sizs) using ths springs.

### GOAL SETTING AND PERSONAL MISSION STATEMENT

Prsonal Dvlopmnt Track Sction 4 GOAL SETTING AND PERSONAL MISSION STATEMENT Ky Points 1 Dfining a Vision 2 Writing a Prsonal Mission Statmnt 3 Writing SMART Goals to Support a Vision and Mission If you

### Noble gas configuration. Atoms of other elements seek to attain a noble gas electron configuration. Electron configuration of ions

Valnc lctron configuration dtrmins th charactristics of lmnts in a group Nobl gas configuration Th nobl gass (last column in th priodic tabl) ar charactrizd by compltly filld s and p orbitals this is a

### ME 612 Metal Forming and Theory of Plasticity. 6. Strain

Mtal Forming and Thory of Plasticity -mail: azsnalp@gyt.du.tr Makin Mühndisliği Bölümü Gbz Yüksk Tknoloji Enstitüsü 6.1. Uniaxial Strain Figur 6.1 Dfinition of th uniaxial strain (a) Tnsil and (b) Comprssiv.

### Performance Evaluation

Prformanc Evaluation ( ) Contnts lists availabl at ScincDirct Prformanc Evaluation journal hompag: www.lsvir.com/locat/pva Modling Bay-lik rputation systms: Analysis, charactrization and insuranc mchanism

### Over-investment of free cash flow

Rv Acc Stud (2006) 11:159 189 DOI 10.1007/s11142-006-9012-1 Ovr-invstmnt of fr cash flow Scott Richardson Publishd onlin: 23 Jun 2006 Ó Springr Scinc+Businss Mdia, LLC 2006 Abstract This papr xamins th

### MONEY ILLUSION IN THE STOCK MARKET: THE MODIGLIANI-COHN HYPOTHESIS*

MONEY ILLUSION IN THE STOCK MARKET: THE MODIGLIANI-COHN HYPOTHESIS* RANDOLPH B. COHEN CHRISTOPHER POLK TUOMO VUOLTEENAHO Modigliani and Cohn hypothsiz that th stock markt suffrs from mony illusion, discounting

### Entity-Relationship Model

Entity-Rlationship Modl Kuang-hua Chn Dpartmnt of Library and Information Scinc National Taiwan Univrsity A Company Databas Kps track of a company s mploys, dpartmnts and projcts Aftr th rquirmnts collction

### Analyzing the Economic Efficiency of ebaylike Online Reputation Reporting Mechanisms

A rsarch and ducation initiativ at th MIT Sloan School of Managmnt Analyzing th Economic Efficincy of Baylik Onlin Rputation Rporting Mchanisms Papr Chrysanthos Dllarocas July For mor information, plas

### Incomplete 2-Port Vector Network Analyzer Calibration Methods

Incomplt -Port Vctor Ntwork nalyzr Calibration Mthods. Hnz, N. Tmpon, G. Monastrios, H. ilva 4 RF Mtrology Laboratory Instituto Nacional d Tcnología Industrial (INTI) Bunos irs, rgntina ahnz@inti.gov.ar

### Rural and Remote Broadband Access: Issues and Solutions in Australia

Rural and Rmot Broadband Accss: Issus and Solutions in Australia Dr Tony Warrn Group Managr Rgulatory Stratgy Tlstra Corp Pag 1 Tlstra in confidnc Ovrviw Australia s gographical siz and population dnsity

### Closed-form solutions for Guaranteed Minimum Accumulation Benefits

Closd-form solutions for Guarantd Minimum Accumulation Bnfits Mikhail Krayzlr, Rudi Zagst and Brnhard Brunnr Abstract Guarantd Minimum Accumulation Bnfit GMAB is on of th variabl annuity products, i..

### The Australian Rules Football Fixed Odds and Line Betting Markets: Econometric Tests for Efficiency and Simulated Betting Systems

Th Australian Ruls Football Fixd Odds and Lin Btting Markts: Economtric Tsts for Efficincy and Simulatd Btting Systms by Adi Schnytzr and Guy Winbrg a Papr to b prsntd at: Th 4 th Binnial Equin Industry

### B-285141. April 21, 2000. The Honorable Charles B. Rangel Ranking Minority Member Committee on Ways and Means House of Representatives

Unit Stats Gnral Accounting Offic Washington, DC 20548 Halth, Eucation, an Human Srvics Division B-285141 April 21, 2000 Th Honorabl Charls B. Rangl Ranking Minority Mmbr Committ on Ways an Mans Hous of

### Gold versus stock investment: An econometric analysis

Intrnational Journal of Dvlopmnt and Sustainability Onlin ISSN: 268-8662 www.isdsnt.com/ijds Volum Numbr, Jun 202, Pag -7 ISDS Articl ID: IJDS20300 Gold vrsus stock invstmnt: An conomtric analysis Martin

### Basis risk. When speaking about forward or futures contracts, basis risk is the market

Basis risk Whn spaking about forward or futurs contracts, basis risk is th markt risk mismatch btwn a position in th spot asst and th corrsponding futurs contract. Mor broadly spaking, basis risk (also

### Cloud and Big Data Summer School, Stockholm, Aug., 2015 Jeffrey D. Ullman

Cloud and Big Data Summr Scool, Stockolm, Aug., 2015 Jffry D. Ullman Givn a st of points, wit a notion of distanc btwn points, group t points into som numbr of clustrs, so tat mmbrs of a clustr ar clos

### The international Internet site of the geoviticulture MCC system Le site Internet international du système CCM géoviticole

Th intrnational Intrnt sit of th goviticultur MCC systm L sit Intrnt intrnational du systèm CCM géoviticol Flávio BELLO FIALHO 1 and Jorg TONIETTO 1 1 Rsarchr, Embrapa Uva Vinho, Caixa Postal 130, 95700-000

### The fitness value of information

Oikos 119: 219230, 2010 doi: 10.1111/j.1600-0706.2009.17781.x, # 2009 Th Authors. Journal compilation # 2009 Oikos Subjct Editor: Knnth Schmidt. Accptd 1 Sptmbr 2009 Th fitnss valu of information Matina

### econstor Make Your Publication Visible

constor Mak Your Publication Visibl A Srvic of Wirtschaft Cntr zbwlibniz-informationszntrum Economics Rich, Robrt; Tracy, Josph Working Papr Th rlationship btwn xpctd inflation, disagrmnt, and uncrtainty:

### http://www.wwnorton.com/chemistry/tutorials/ch14.htm Repulsive Force

ctivation nrgis http://www.wwnorton.com/chmistry/tutorials/ch14.htm (back to collision thory...) Potntial and Kintic nrgy during a collision + + ngativly chargd lctron cloud Rpulsiv Forc ngativly chargd

### IMES DISCUSSION PAPER SERIES

IMES DISCUSSIN PAPER SERIES Th Choic of Invoic Currncy in Intrnational Trad: Implications for th Intrnationalization of th Yn Hiroyuki I, Akira TANI, and Toyoichirou SHIRTA Discussion Papr No. 003-E-13

### Real-Time Evaluation of Email Campaign Performance

Singapor Managmnt Univrsity Institutional Knowldg at Singapor Managmnt Univrsity Rsarch Collction L Kong Chian School Of Businss L Kong Chian School of Businss 10-2008 Ral-Tim Evaluation of Email Campaign

### Upper Bounding the Price of Anarchy in Atomic Splittable Selfish Routing

Uppr Bounding th Pric of Anarchy in Atomic Splittabl Slfish Routing Kamyar Khodamoradi 1, Mhrdad Mahdavi, and Mohammad Ghodsi 3 1 Sharif Univrsity of Tchnology, Thran, Iran, khodamoradi@c.sharif.du Sharif

### Criminal Offenses - On campus

14 Campus Saf and Scuri Survy Instituti: Main Campus (164933001) Scrning Qustis Plas answr ths qustis carfully. Th answrs you provid will dtrmin which scrns you will b askd to complt for this data collcti.

### The Constrained Ski-Rental Problem and its Application to Online Cloud Cost Optimization

3 Procdings IEEE INFOCOM Th Constraind Ski-Rntal Problm and its Application to Onlin Cloud Cost Optimization Ali Khanafr, Murali Kodialam, and Krishna P. N. Puttaswam Coordinatd Scinc Laborator, Univrsit

### Production Costing (Chapter 8 of W&W)

Production Costing (Chaptr 8 of W&W).0 Introduction Production costs rfr to th oprational costs associatd with producing lctric nrgy. Th most significant componnt of production costs ar th ful costs ncssary

### Architecture of the proposed standard

Architctur of th proposd standard Introduction Th goal of th nw standardisation projct is th dvlopmnt of a standard dscribing building srvics (.g.hvac) product catalogus basd on th xprincs mad with th

### [ ] These are the motor parameters that are needed: Motor voltage constant. J total (lb-in-sec^2)

MEASURING MOOR PARAMEERS Fil: Motor paramtrs hs ar th motor paramtrs that ar ndd: Motor voltag constant (volts-sc/rad Motor torqu constant (lb-in/amp Motor rsistanc R a (ohms Motor inductanc L a (Hnris

### Government Spending or Tax Cuts for Education in Taylor County, Texas

Govrnmnt Spnding or Tax Cuts for Education in Taylor County, Txas Ian Shphrd Abiln Christian Univrsity D Ann Shphrd Abiln Christian Univrsity On Fbruary 17, 2009, Prsidnt Barack Obama signd into law th

### Section 3: Logistic Regression

Scton 3: Logstc Rgrsson As our motvaton for logstc rgrsson, w wll consdr th Challngr dsastr, th sx of turtls, collg math placmnt, crdt card scorng, and markt sgmntaton. Th Challngr Dsastr On January 28,

### Electronic Commerce. and. Competitive First-Degree Price Discrimination

Elctronic Commrc and Comptitiv First-Dgr Pric Discrimination David Ulph* and Nir Vulkan ** Fbruary 000 * ESRC Cntr for Economic arning and Social Evolution (ESE), Dpartmnt of Economics, Univrsity Collg

### Relationship between Cost of Equity Capital And Voluntary Corporate Disclosures

Rlationship btwn Cost of Equity Capital And Voluntary Corporat Disclosurs Elna Ptrova Eli Lilly & Co, Sofia, Bulgaria E-mail: ptrova.lnaa@gmail.com Gorgios Gorgakopoulos (Corrsponding author) Amstrdam

### Analysis of Trade Before and After the WTO: A Case Study of India

Global Journal of Financ and Managmnt. ISSN 0975-6477 Volum 6, Numbr 8 (2014), pp. 801-808 Rsarch India Publications http://www.ripublication.com Analysis of Trad Bfor and Aftr th WTO: A Cas Study of India

### Modeling Motorcycle Accident on Rural Highway

Modling Motorcycl Accidnt on Rural Highway A.K.Sharma, V.S. Landg, and N.V.Dshpand Abstract Motorcyclists ar th most crash-pron road-usr group in many Asian countris including India. Statistics of accidnt

### A Note on Approximating. the Normal Distribution Function

Applid Mathmatical Scincs, Vol, 00, no 9, 45-49 A Not on Approimating th Normal Distribution Function K M Aludaat and M T Alodat Dpartmnt of Statistics Yarmouk Univrsity, Jordan Aludaatkm@hotmailcom and

### Theoretical approach to algorithm for metrological comparison of two photothermal methods for measuring of the properties of materials

Rvista Invstigación Cintífica, ol. 4, No. 3, Nuva época, sptimbr dicimbr 8, IN 187 8196 Thortical approach to algorithm for mtrological comparison of two photothrmal mthods for masuring of th proprtis

### Remember you can apply online. It s quick and easy. Go to www.gov.uk/advancedlearningloans. Title. Forename(s) Surname. Sex. Male Date of birth D

24+ Advancd Larning Loan Application form Rmmbr you can apply onlin. It s quick and asy. Go to www.gov.uk/advancdlarningloans About this form Complt this form if: you r studying an ligibl cours at an approvd

### Dehumidifiers: A Major Consumer of Residential Electricity

Dhumidifirs: A Major Consumr of Rsidntial Elctricity Laurn Mattison and Dav Korn, Th Cadmus Group, Inc. ABSTRACT An stimatd 19% of U.S. homs hav dhumidifirs, and thy can account for a substantial portion

### Expert-Mediated Search

Exprt-Mdiatd Sarch Mnal Chhabra Rnsslar Polytchnic Inst. Dpt. of Computr Scinc Troy, NY, USA chhabm@cs.rpi.du Sanmay Das Rnsslar Polytchnic Inst. Dpt. of Computr Scinc Troy, NY, USA sanmay@cs.rpi.du David

### Category 1: Purchased Goods and Services

1 Catgory 1: Purchasd Goods and Srvics Catgory dscription T his catgory includs all upstram (i.., cradl-to-gat) missions from th production of products purchasd or acquird by th rporting company in th

### SPREAD OPTION VALUATION AND THE FAST FOURIER TRANSFORM

RESEARCH PAPERS IN MANAGEMENT STUDIES SPREAD OPTION VALUATION AND THE FAST FOURIER TRANSFORM M.A.H. Dmpstr & S.S.G. Hong WP 26/2000 Th Judg Institut of Managmnt Trumpington Strt Cambridg CB2 1AG Ths paprs

### Sharp bounds for Sándor mean in terms of arithmetic, geometric and harmonic means

Qian t al. Journal of Inqualitis and Applications (015) 015:1 DOI 10.1186/s1660-015-0741-1 R E S E A R C H Opn Accss Sharp bounds for Sándor man in trms of arithmtic, gomtric and harmonic mans Wi-Mao Qian

### ESCI 341 Atmospheric Thermodynamics Lesson 14 Humidity Dr. DeCaria

PARIAL PRESSURE ESCI 341 Atmoshric hrmoynamics Lsson 14 Humiity Dr. DCaria In a mixtur of gass, ach gas scis contributs to th total rssur. ο h rssur xrt by a singl gas scis is known as th artial rssur

### A copy of the Consultation Paper is in the Members Library and further details are available at www.scotland~qov.umpublications/2012/12/5980

To: CORPORATE SERVICES COMMITTEE NORTH LANARKSHIRE COUNCIL REPORT Subjct: CONSULTATION: CIVIL LAW OF DAMAGES - ISSUES IN PERSONAL INJURY From: HEAD OF LEGAL SERVICES Dat: 30 JANUARY 2013 Rf: AL LE CSN

### The price of liquidity in constant leverage strategies. Marcos Escobar, Andreas Kiechle, Luis Seco and Rudi Zagst

RACSAM Rv. R. Acad. Cin. Sri A. Mat. VO. 103 2, 2009, pp. 373 385 Matmática Aplicada / Applid Mathmatics Th pric of liquidity in constant lvrag stratgis Marcos Escobar, Andras Kichl, uis Sco and Rudi Zagst

### Lecture notes: 160B revised 9/28/06 Lecture 1: Exchange Rates and the Foreign Exchange Market FT chapter 13

Lctur nots: 160B rvisd 9/28/06 Lctur 1: xchang Rats and th Forign xchang Markt FT chaptr 13 Topics: xchang Rats Forign xchang markt Asst approach to xchang rats Intrst Rat Parity Conditions 1) Dfinitions