Chapter 4 - Consumer. Household Demand and Supply. Solving the max-utility problem. Working out consumer responses. The response function

Size: px
Start display at page:

Download "Chapter 4 - Consumer. Household Demand and Supply. Solving the max-utility problem. Working out consumer responses. The response function"

Transcription

1 Almost essetial Cosumer: Optimisatio Chapter 4 - Cosumer Osa 2: Household ad supply Cosumer: Welfare Useful, but optioal Firm: Optimisatio Household Demad ad Supply MICROECONOMICS Priciples ad Aalysis Frak Cowell 2 Workig out cosumer resposes The aalysis of cosumer optimisatio gives us some powerful tools: The primal problem of the cosumer is what we are really iterested i. Related dual problem ca help us uderstad it. The aalogy with the firm helps solve the dual. The work we have doe ca map out the cosumer's resposes to chages i s to chages i icome what we kow about the primal 3 Lik to full discussio Solvig the max-utility problem The primal problem ad its solutio max U(x) + µ[ y Σ p i x i ] i= U (x * ) = µp U 2 (x * ) = µp U (x * ) = µp Σ p i x i* = y i= Solve this set of equatios: * = D (p, y) * = D 2 (p, y) x * = D (p, y) Σ p i D i (p, y) = y i= The Lagragea for the max U problem The + first-order coditios, assumig all goods purchased. Gives a set of fuctios, oe for each good. Fuctios of s ad icomes. A restrictio o the equatios. Follows from the budget costrait 4 The respose fuctio hthe respose fuctio for the primal problem is for good i: x i* = D i (p,y) hthe system of equatios must have a addig-up property: Σ p i D i (p, y) = y i= heach equatio i the system must be homogeeous of degree 0 i s ad icome. For ay t > 0: x i * = D i (p, y )= D i (tp, ty) Should be treated as just oe of a set of equatios. Reaso? This follows immediately from the budget costrait: left-had side is total expediture. Reaso? Agai follows immediately from the budget costrait. To make more progress we eed to exploit the relatioship How you would use this i practice... Cosumer surveys give data o expediture for each household over a umber of categories ad perhaps icome, hours worked etc as well. Market data are available o s. Give some assumptios about the structure of prefereces we ca estimate household fuctios for commodities. From this we ca recover iformatio about utility fuctios. betwee primal ad dual approaches agai Cosumer s resposes Effect of a chage i icome Lik to budget costrait What s s the effect of a budget chage o? Depeds o the type of budget costrait. Fixed icome? Icome edogeously determied? Ad o the type of budget chage. Icome aloe? Price i primal type problem? Price i dual type problem? So let s s tackle the questio i stages. Begi with a type (exogeous icome) budget costrait. 7 * Take the basic equilibrium Suppose icome rises The effect of the icome icrease. Demad for each good does ot if it is ormal But could the opposite happe? 8

2 A iferior good A glimpse ahead... * Take same origial s, but differet prefereces Agai suppose icome rises The effect of the icome icrease. Demad for good rises, but Demad for iferior good 2 s a little Ca you thik of ay goods like this? We ca use the idea of a icome effect i may applicatios. Basic to a uderstadig of the effects of s o the cosumer. Because a cut makes a perso better off, as would a icome icrease... How might it deped o the categorisatio 9 of goods? 0 Effect of a chage i Ad ow let s look at it i maths icome effect * substitutio effect Agai take the basic equilibrium Allow of good to The effect of the. The jourey from to * broke ito two parts We wat to take both primal ad dual aspects of the problem......ad work out the relatioship betwee the respose fuctios usig properties of the solutio fuctios. (Yes, it s s time for Shephard s lemma agai...) 2 A fudametal decompositio htake the two methods of writig x i* : H i (p,υ) = D i (p,y) huse cost fuctio to substitute for y: H i (p,υ) = D i (p, C(p,υ)) hdifferetiate with respect to p j : H j i (p,υ) = D j i (p,y) + D y i (p,y)c j (p,υ) hsimplify : H i j (p,υ) = D i j (p,y) + D i y (p,y) H j (p,υ) = D ji (p,y) + D yi (p,y) x * j had so we get: Remember: they are two ways of represetig the same thig Gives us a implicit relatio i s ad utility. Uses fuctio-of-a-fuctio rule agai. Remember y=c(p,u) Usig cost fuctio ad Shephard s Lemma agai From the comp. fuctio The Slutsky equatio D ji (p,y) = H ji (p,υ) x j* D yi (p,y) Gives fudametal breakdow of effects of a chage Icome effect: I'm better off if the of jelly s, so I buy more thigs, icludig icecream Substitutio effect: Whe the of jelly s ad I m kept o the same, I prefer to switch from icecream for dessert D 3 ji (p,y) = H ji (p,υ) x j* D yi (p,y) This is the Slutsky equatio 4 * Slutsky: Poits to watch The Slutsky equatio: ow- Icome effects for some goods may be egative iferior goods. For > 2 the substitutio effect for some pairs of goods could be positive (H ji > 0) et substitutes Apples ad baaas? while that for others could be egative (H( ji < 0) back to the maths 5 Lik to firm s iput hset j = i to get the effect of the of icecream o the for icecream D ii (p,y) = H ii (p,υ) x i* D yi (p,y) how- substitutio effect must be egative hicome effect of icrease is o-positive for ormal goods hso, if the for i does ot decrease whe y rises, the it must decrease whe p i rises. Follows from the results o the firm Price icrease meas less disposable icome 6

3 Price : ormal good Price : iferior good iitial p D (p,y) curve Compesatig (Hicksia) curve H (p,υ) : substitutio effect total effect: ormal good icome effect: ormal good For ormal good icome effect must be positive or zero iitial p curve curve Compesatig : substitutio effect total effect: iferior good icome effect: iferior good Note relative slopes of these curves i iferior-good case. For iferior good icome effect must be egative ** 7 ** 8 Features of fuctios Almost essetial Firm: Optimisatio Cosumptio: Basics Homogeeous of degree zero Satisfy the addig-up costrait Symmetric substitutio effects Negative ow- substitutio effects Icome effects could be positive or egative: i fact they are early always a pai. Cosumer: Welfare MICROECONOMICS Priciples ad Aalysis Frak Cowell 9 20 Usig cosumer theory The problem Cosumer aalysis is ot just a matter of cosumers' reactios to s We pick up the effect of s o icomes o attaiable utility - cosumer's welfare This is useful i the desig of ecoomic policy, for example The tax structure? We ca use a umber of tools that have become stadard i applied microecoomics idices? 2 υ υ' * How do we quatify this gap? Take the cosumer's equilibrium ad allow a to... Obviously the perso is better off....but how much better off? 22 some distace fuctio Approaches to valuig utility chage Three thigs that are ot much use:. υ' υ 2. υ' / υ 3. d(υ', υ) Utility differeces Utility ratios A more productive idea: depeds o the uits of the U fuctio depeds o the origi of the U fuctio depeds o the cardialisatio of the U fuctio. Use icome ot utility as a measurig rod 2. To do the trasformatio we use the V fuctio 3. We ca do this i (at least) two ways Story umber Suppose p is the origial vector ad p' is vector after good becomes cheaper. This causes utility to rise from υ to υ'. υ = V(p, y) υ' ' = V(p', y) Express this rise i moey terms? What hypothetical chage i icome would brig the perso back to the startig poit? (ad is this the right questio to ask...?) Gives us a stadard defiitio. 24

4 I this versio of the story we get the Compesatig υ = V(p, y) the origial at s p ad icome y The compesatig variatio υ The i of good The origial is the referece poit. CV measured i terms of good 2 CV υ = V(p', y CV) the origial restored at ew s p' The amout CV is just sufficiet to udo the effect of goig from p to p. 25 * Origial s ew 26 CV assessmet The CV gives us a clear ad iterpretable measure of welfare chage. It values the chage i terms of moey (or goods). But the approach is based o oe specific referece poit. The assumptio that the right thig to do is to use the origial. There are alterative assumptios we might reasoably make. For istace... Here s story umber 2 Agai suppose: p is the origial vector p' ' is the vector after good becomes cheaper. This agai causes utility to rise from υ to υ'. But ow, ask ourselves a differet questio: Suppose the had ever happeed What hypothetical chage i icome would have bee eeded to brig the perso to the ew? I this versio of the story we get the Equivalet υ' = V(p', y) the at ew s p' ad icome y The equivalet variatio EV υ' Price is as before. The ew is ow the referece poit EV measured i terms of good 2 the ew υ' = V(p, y + EV) reached at origial s p The amout EV is just sufficiet to mimic the effect of goig from p to p. 29 * Origial s ew 30 CV ad EV... Both defiitios have used the idirect utility fuctio. But this may ot be the most ituitive approach So look for aother stadard tool.. As we have see there is a close relatioship betwee the fuctios V ad C. So we ca reiterpret CV ad EV usig C. The result will be a welfare measure the chage i cost of hittig a welfare. Welfare chage as (cost) Compesatig as (cost): CV(p p') = C(p, υ) C(p', υ) Equivalet as (cost): EV(p p') = C(p, υ') C(p', υ') ( ) chage i cost of hittig utility υ. If positive we have a welfare icrease. ( ) chage i cost of hittig utility υ'. If positive we have a welfare icrease remember: cost decreases mea welfare icreases. Prices before Usig the above defiitios we also have CV(p' p) = C(p', υ') C(p, υ') = EV(p p') Prices after Referece Lookig at welfare chage i the reverse directio, startig at p' ad movig to p.

5 Prices before Prices after Aother (equivalet) form for CV Use the cost-differece defiitio: CV(p p') = C(p, υ) C(p', υ) Assume that the of good chages from p to p ' while other s remai uchaged. The we ca rewrite the above as: CV(p p') = C (p, υ) dp Further rewrite as: CV(p p') = H (p, υ) dp p p ' p p ' So CV ca be see as a area uder the curve Referece ( ) chage i cost of hittig υ. If positive we have a welfare icrease. (Just usig the defiitio of a defiite itegral) Hicksia () for good You're right. It's usig Shephard s lemma agai Let s see 33 iitial Compesated ad the value of a p Compesatig (Hicksia) curve H (p,υ) origial : (welfare icrease) value of, relative to origial The CV provides a exact welfare measure. But it s ot the oly approach 34 Compesated ad the value of a (2) p (Hicksia) curve H (p,υ ) As before but use ew utility as a referece poit : (welfare icrease) value of, relative to ew Ordiary ad the value of a p (Marshallia) curve D (p, y) : (welfare icrease) A alterative method of valuig the? Equivalet ew The EV provides aother exact welfare measure. But based o a differet referece poit Cosumer's surplus CS provides a approximate welfare measure. * Other possibilities 35 * 36 Three ways of measurig the beefits of a Welfare measures applied... p D (p, y) CV CS H (p,υ) H (p,υ ) CS EV Summary of the three approaches. Coditios for ormal goods So, for ormal goods: CV CS EV The cocepts we have developed are regularly put to work i practice. Applied to issues such as: Cosumer welfare idices Price idices Cost-Beefit Aalysis Ofte this is doe usig some (acceptable?) approximatios... * For iferior goods: CV >CS >EV 37 Example of cost-of-livig idex 38 Cost-of-livig idices A idex based o CV: All summatios C(p', υ) are from to. I CV = C(p, υ) A approximatio: Σ i p' i x i IL = Σ i p i x i I CV. A idex based o EV: C(p', υ') I EV = C(p, υ') A approximatio: Σ i p' i x' i IP = Σ i p i x' i I EV. = C(p, υ) What's the chage i cost of hittig the base welfare υ? C(p', υ) What's the chage i cost of buyig the base cosumptio budle x? This is the Laspeyres idex the basis for the Retail Price Idex ad other similar idices. What's the chage i cost of hittig the ew welfare υ'? = C(p', υ') What's the chage i cost of buyig the ew cosumptio budle x'? This is the Paasche idex 39 C(p, υ') Summary: key cocepts Compesatig variatio Equivalet variatio CV ad EV are measured i moetary uits. I all cases: CV(p p' p') ) = EV(p' p' p). Cosumer s s surplus The CS is a coveiet approximatio For ormal goods: CV CS EV. For iferior goods: CV > CS > EV. 40

MICROECONOMICS Principles and Analysis Frank Cowell

MICROECONOMICS Principles and Analysis Frank Cowell Prerequisites Almost essential Consumer: Optimisation Useful, but optional Firm: Optimisation HOUSEHOLD DEMAND AND SUPPLY MICROECONOMICS Principles and Analysis Frank Cowell Note: the detail in slides

More information

Overlapping Generations

Overlapping Generations Eco. 53a all 996 C. Sims. troductio Overlappig Geeratios We wat to study how asset markets allow idividuals, motivated by the eed to provide icome for their retiremet years, to fiace capital accumulatio

More information

Binomial Model. Stock Price Dynamics. The Key Idea Riskless Hedge

Binomial Model. Stock Price Dynamics. The Key Idea Riskless Hedge Biomial Model Stock Price Dyamics The value of a optio at maturity depeds o the price of the uderlyig stock at maturity. The value of the optio today depeds o the expected value of the optio at maturity

More information

EC426 Class 5, Question 3: Is there a case for eliminating commodity taxation? Bianca Mulaney November 3, 2016

EC426 Class 5, Question 3: Is there a case for eliminating commodity taxation? Bianca Mulaney November 3, 2016 EC426 Class 5, Questio 3: Is there a case for elimiatig commodity taxatio? Biaca Mulaey November 3, 2016 Aswer: YES Why? Atkiso & Stiglitz: differetial commodity taxatio is ot optimal i the presece of

More information

CHAPTER 2 PRICING OF BONDS

CHAPTER 2 PRICING OF BONDS CHAPTER 2 PRICING OF BONDS CHAPTER SUARY This chapter will focus o the time value of moey ad how to calculate the price of a bod. Whe pricig a bod it is ecessary to estimate the expected cash flows ad

More information

Anomaly Correction by Optimal Trading Frequency

Anomaly Correction by Optimal Trading Frequency Aomaly Correctio by Optimal Tradig Frequecy Yiqiao Yi Columbia Uiversity September 9, 206 Abstract Uder the assumptio that security prices follow radom walk, we look at price versus differet movig averages.

More information

Estimating Proportions with Confidence

Estimating Proportions with Confidence Aoucemets: Discussio today is review for midterm, o credit. You may atted more tha oe discussio sectio. Brig sheets of otes ad calculator to midterm. We will provide Scatro form. Homework: (Due Wed Chapter

More information

Statistics for Economics & Business

Statistics for Economics & Business Statistics for Ecoomics & Busiess Cofidece Iterval Estimatio Learig Objectives I this chapter, you lear: To costruct ad iterpret cofidece iterval estimates for the mea ad the proportio How to determie

More information

A random variable is a variable whose value is a numerical outcome of a random phenomenon.

A random variable is a variable whose value is a numerical outcome of a random phenomenon. The Practice of Statistics, d ed ates, Moore, ad Stares Itroductio We are ofte more iterested i the umber of times a give outcome ca occur tha i the possible outcomes themselves For example, if we toss

More information

When you click on Unit V in your course, you will see a TO DO LIST to assist you in starting your course.

When you click on Unit V in your course, you will see a TO DO LIST to assist you in starting your course. UNIT V STUDY GUIDE Percet Notatio Course Learig Outcomes for Uit V Upo completio of this uit, studets should be able to: 1. Write three kids of otatio for a percet. 2. Covert betwee percet otatio ad decimal

More information

Notes on Expected Revenue from Auctions

Notes on Expected Revenue from Auctions Notes o Epected Reveue from Auctios Professor Bergstrom These otes spell out some of the mathematical details about first ad secod price sealed bid auctios that were discussed i Thursday s lecture You

More information

Problem Set 1a - Oligopoly

Problem Set 1a - Oligopoly Advaced Idustrial Ecoomics Sprig 2014 Joha Steek 6 may 2014 Problem Set 1a - Oligopoly 1 Table of Cotets 2 Price Competitio... 3 2.1 Courot Oligopoly with Homogeous Goods ad Differet Costs... 3 2.2 Bertrad

More information

STRAND: FINANCE. Unit 3 Loans and Mortgages TEXT. Contents. Section. 3.1 Annual Percentage Rate (APR) 3.2 APR for Repayment of Loans

STRAND: FINANCE. Unit 3 Loans and Mortgages TEXT. Contents. Section. 3.1 Annual Percentage Rate (APR) 3.2 APR for Repayment of Loans CMM Subject Support Strad: FINANCE Uit 3 Loas ad Mortgages: Text m e p STRAND: FINANCE Uit 3 Loas ad Mortgages TEXT Cotets Sectio 3.1 Aual Percetage Rate (APR) 3.2 APR for Repaymet of Loas 3.3 Credit Purchases

More information

Basic formula for confidence intervals. Formulas for estimating population variance Normal Uniform Proportion

Basic formula for confidence intervals. Formulas for estimating population variance Normal Uniform Proportion Basic formula for the Chi-square test (Observed - Expected ) Expected Basic formula for cofidece itervals sˆ x ± Z ' Sample size adjustmet for fiite populatio (N * ) (N + - 1) Formulas for estimatig populatio

More information

We learned: $100 cash today is preferred over $100 a year from now

We learned: $100 cash today is preferred over $100 a year from now Recap from Last Week Time Value of Moey We leared: $ cash today is preferred over $ a year from ow there is time value of moey i the form of willigess of baks, busiesses, ad people to pay iterest for its

More information

Subject CT1 Financial Mathematics Core Technical Syllabus

Subject CT1 Financial Mathematics Core Technical Syllabus Subject CT1 Fiacial Mathematics Core Techical Syllabus for the 2018 exams 1 Jue 2017 Subject CT1 Fiacial Mathematics Core Techical Aim The aim of the Fiacial Mathematics subject is to provide a groudig

More information

CD Appendix AC Index Numbers

CD Appendix AC Index Numbers CD Appedix AC Idex Numbers I Chapter 20, we preseted a variety of techiques for aalyzig ad forecastig time series. This appedix is devoted to the simpler task of developig descriptive measuremets of the

More information

First determine the payments under the payment system

First determine the payments under the payment system Corporate Fiace February 5, 2008 Problem Set # -- ANSWERS Klick. You wi a judgmet agaist a defedat worth $20,000,000. Uder state law, the defedat has the right to pay such a judgmet out over a 20 year

More information

Chapter Four Learning Objectives Valuing Monetary Payments Now and in the Future

Chapter Four Learning Objectives Valuing Monetary Payments Now and in the Future Chapter Four Future Value, Preset Value, ad Iterest Rates Chapter 4 Learig Objectives Develop a uderstadig of 1. Time ad the value of paymets 2. Preset value versus future value 3. Nomial versus real iterest

More information

14.30 Introduction to Statistical Methods in Economics Spring 2009

14.30 Introduction to Statistical Methods in Economics Spring 2009 MIT OpeCourseWare http://ocwmitedu 430 Itroductio to Statistical Methods i Ecoomics Sprig 009 For iformatio about citig these materials or our Terms of Use, visit: http://ocwmitedu/terms 430 Itroductio

More information

Chapter 8. Confidence Interval Estimation. Copyright 2015, 2012, 2009 Pearson Education, Inc. Chapter 8, Slide 1

Chapter 8. Confidence Interval Estimation. Copyright 2015, 2012, 2009 Pearson Education, Inc. Chapter 8, Slide 1 Chapter 8 Cofidece Iterval Estimatio Copyright 2015, 2012, 2009 Pearso Educatio, Ic. Chapter 8, Slide 1 Learig Objectives I this chapter, you lear: To costruct ad iterpret cofidece iterval estimates for

More information

Models of Asset Pricing

Models of Asset Pricing APPENDIX 1 TO CHAPTER4 Models of Asset Pricig I this appedix, we first examie why diversificatio, the holdig of may risky assets i a portfolio, reduces the overall risk a ivestor faces. The we will see

More information

Today: Finish Chapter 9 (Sections 9.6 to 9.8 and 9.9 Lesson 3)

Today: Finish Chapter 9 (Sections 9.6 to 9.8 and 9.9 Lesson 3) Today: Fiish Chapter 9 (Sectios 9.6 to 9.8 ad 9.9 Lesso 3) ANNOUNCEMENTS: Quiz #7 begis after class today, eds Moday at 3pm. Quiz #8 will begi ext Friday ad ed at 10am Moday (day of fial). There will be

More information

Subject CT5 Contingencies Core Technical. Syllabus. for the 2011 Examinations. The Faculty of Actuaries and Institute of Actuaries.

Subject CT5 Contingencies Core Technical. Syllabus. for the 2011 Examinations. The Faculty of Actuaries and Institute of Actuaries. Subject CT5 Cotigecies Core Techical Syllabus for the 2011 Examiatios 1 Jue 2010 The Faculty of Actuaries ad Istitute of Actuaries Aim The aim of the Cotigecies subject is to provide a groudig i the mathematical

More information

Models of Asset Pricing

Models of Asset Pricing 4 Appedix 1 to Chapter Models of Asset Pricig I this appedix, we first examie why diversificatio, the holdig of may risky assets i a portfolio, reduces the overall risk a ivestor faces. The we will see

More information

5. Best Unbiased Estimators

5. Best Unbiased Estimators Best Ubiased Estimators http://www.math.uah.edu/stat/poit/ubiased.xhtml 1 of 7 7/16/2009 6:13 AM Virtual Laboratories > 7. Poit Estimatio > 1 2 3 4 5 6 5. Best Ubiased Estimators Basic Theory Cosider agai

More information

Chapter Four 1/15/2018. Learning Objectives. The Meaning of Interest Rates Future Value, Present Value, and Interest Rates Chapter 4, Part 1.

Chapter Four 1/15/2018. Learning Objectives. The Meaning of Interest Rates Future Value, Present Value, and Interest Rates Chapter 4, Part 1. Chapter Four The Meaig of Iterest Rates Future Value, Preset Value, ad Iterest Rates Chapter 4, Part 1 Preview Develop uderstadig of exactly what the phrase iterest rates meas. I this chapter, we see that

More information

Appendix 1 to Chapter 5

Appendix 1 to Chapter 5 Appedix 1 to Chapter 5 Models of Asset Pricig I Chapter 4, we saw that the retur o a asset (such as a bod) measures how much we gai from holdig that asset. Whe we make a decisio to buy a asset, we are

More information

Confidence Intervals. CI for a population mean (σ is known and n > 30 or the variable is normally distributed in the.

Confidence 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 information

1 Savings Plans and Investments

1 Savings Plans and Investments 4C Lesso Usig ad Uderstadig Mathematics 6 1 Savigs las ad Ivestmets 1.1 The Savigs la Formula Lets put a $100 ito a accout at the ed of the moth. At the ed of the moth for 5 more moths, you deposit $100

More information

Models of Asset Pricing

Models of Asset Pricing APPENDIX 1 TO CHAPTER 4 Models of Asset Pricig I this appedix, we first examie why diversificatio, the holdig of may risky assets i a portfolio, reduces the overall risk a ivestor faces. The we will see

More information

EVEN NUMBERED EXERCISES IN CHAPTER 4

EVEN NUMBERED EXERCISES IN CHAPTER 4 Joh Riley 7 July EVEN NUMBERED EXERCISES IN CHAPTER 4 SECTION 4 Exercise 4-: Cost Fuctio of a Cobb-Douglas firm What is the cost fuctio of a firm with a Cobb-Douglas productio fuctio? Rather tha miimie

More information

Pension Annuity. Policy Conditions Document reference: PPAS1(6) This is an important document. Please keep it in a safe place.

Pension Annuity. Policy Conditions Document reference: PPAS1(6) This is an important document. Please keep it in a safe place. Pesio Auity Policy Coditios Documet referece: PPAS1(6) This is a importat documet. Please keep it i a safe place. Pesio Auity Policy Coditios Welcome to LV=, ad thak you for choosig our Pesio Auity. These

More information

The material in this chapter is motivated by Experiment 9.

The material in this chapter is motivated by Experiment 9. Chapter 5 Optimal Auctios The material i this chapter is motivated by Experimet 9. We wish to aalyze the decisio of a seller who sets a reserve price whe auctioig off a item to a group of bidders. We begi

More information

FINM6900 Finance Theory How Is Asymmetric Information Reflected in Asset Prices?

FINM6900 Finance Theory How Is Asymmetric Information Reflected in Asset Prices? FINM6900 Fiace Theory How Is Asymmetric Iformatio Reflected i Asset Prices? February 3, 2012 Referece S. Grossma, O the Efficiecy of Competitive Stock Markets where Traders Have Diverse iformatio, Joural

More information

MATH : EXAM 2 REVIEW. A = P 1 + AP R ) ny

MATH : EXAM 2 REVIEW. A = P 1 + AP R ) ny MATH 1030-008: EXAM 2 REVIEW Origially, I was havig you all memorize the basic compoud iterest formula. I ow wat you to memorize the geeral compoud iterest formula. This formula, whe = 1, is the same as

More information

of Asset Pricing R e = expected return

of Asset Pricing R e = expected return Appedix 1 to Chapter 5 Models of Asset Pricig EXPECTED RETURN I Chapter 4, we saw that the retur o a asset (such as a bod) measures how much we gai from holdig that asset. Whe we make a decisio to buy

More information

Where a business has two competing investment opportunities the one with the higher NPV should be selected.

Where a business has two competing investment opportunities the one with the higher NPV should be selected. Where a busiess has two competig ivestmet opportuities the oe with the higher should be selected. Logically the value of a busiess should be the sum of all of the projects which it has i operatio at the

More information

Standard Deviations for Normal Sampling Distributions are: For proportions For means _

Standard Deviations for Normal Sampling Distributions are: For proportions For means _ Sectio 9.2 Cofidece Itervals for Proportios We will lear to use a sample to say somethig about the world at large. This process (statistical iferece) is based o our uderstadig of samplig models, ad will

More information

ISBN Copyright 2015 The Continental Press, Inc.

ISBN Copyright 2015 The Continental Press, Inc. TABLE OF CONTENTS Itroductio 3 Format of Books 4 Suggestios for Use 7 Aotated Aswer Key ad Extesio Activities 9 Reproducible Tool Set 183 ISBN 978-0-8454-7897-4 Copyright 2015 The Cotietal Press, Ic. Exceptig

More information

0.07. i PV Qa Q Q i n. Chapter 3, Section 2

0.07. i PV Qa Q Q i n. Chapter 3, Section 2 Chapter 3, Sectio 2 1. (S13HW) Calculate the preset value for a auity that pays 500 at the ed of each year for 20 years. You are give that the aual iterest rate is 7%. 20 1 v 1 1.07 PV Qa Q 500 5297.01

More information

1 ECON4415: International Economics Problem Set 4 - Solutions

1 ECON4415: International Economics Problem Set 4 - Solutions ECON445: Iteratioal Ecoomics Problem Set 4 - Solutios. I Moopolistic competitio. Moopolistic competitio is a market form where May rms producig di eret varieties. Each rm has moopoly power over its ow

More information

1 The Power of Compounding

1 The Power of Compounding 1 The Power of Compoudig 1.1 Simple vs Compoud Iterest You deposit $1,000 i a bak that pays 5% iterest each year. At the ed of the year you will have eared $50. The bak seds you a check for $50 dollars.

More information

Online appendices from Counterparty Risk and Credit Value Adjustment a continuing challenge for global financial markets by Jon Gregory

Online appendices from Counterparty Risk and Credit Value Adjustment a continuing challenge for global financial markets by Jon Gregory Olie appedices from Couterparty Risk ad Credit Value Adjustmet a APPENDIX 8A: Formulas for EE, PFE ad EPE for a ormal distributio Cosider a ormal distributio with mea (expected future value) ad stadard

More information

Monetary Economics: Problem Set #5 Solutions

Monetary Economics: Problem Set #5 Solutions Moetary Ecoomics oblem Set #5 Moetary Ecoomics: oblem Set #5 Solutios This problem set is marked out of 1 poits. The weight give to each part is idicated below. Please cotact me asap if you have ay questios.

More information

Maximum Empirical Likelihood Estimation (MELE)

Maximum Empirical Likelihood Estimation (MELE) Maximum Empirical Likelihood Estimatio (MELE Natha Smooha Abstract Estimatio of Stadard Liear Model - Maximum Empirical Likelihood Estimator: Combiatio of the idea of imum likelihood method of momets,

More information

CAPITAL PROJECT SCREENING AND SELECTION

CAPITAL PROJECT SCREENING AND SELECTION CAPITAL PROJECT SCREEIG AD SELECTIO Before studyig the three measures of ivestmet attractiveess, we will review a simple method that is commoly used to scree capital ivestmets. Oe of the primary cocers

More information

of Asset Pricing APPENDIX 1 TO CHAPTER EXPECTED RETURN APPLICATION Expected Return

of Asset Pricing APPENDIX 1 TO CHAPTER EXPECTED RETURN APPLICATION Expected Return APPENDIX 1 TO CHAPTER 5 Models of Asset Pricig I Chapter 4, we saw that the retur o a asset (such as a bod) measures how much we gai from holdig that asset. Whe we make a decisio to buy a asset, we are

More information

Using Math to Understand Our World Project 5 Building Up Savings And Debt

Using Math to Understand Our World Project 5 Building Up Savings And Debt Usig Math to Uderstad Our World Project 5 Buildig Up Savigs Ad Debt Note: You will have to had i aswers to all umbered questios i the Project Descriptio See the What to Had I sheet for additioal materials

More information

FOUNDATION ACTED COURSE (FAC)

FOUNDATION ACTED COURSE (FAC) FOUNDATION ACTED COURSE (FAC) What is the Foudatio ActEd Course (FAC)? FAC is desiged to help studets improve their mathematical skills i preparatio for the Core Techical subjects. It is a referece documet

More information

ii. Interval estimation:

ii. Interval estimation: 1 Types of estimatio: i. Poit estimatio: Example (1) Cosider the sample observatios 17,3,5,1,18,6,16,10 X 8 X i i1 8 17 3 5 118 6 16 10 8 116 8 14.5 14.5 is a poit estimate for usig the estimator X ad

More information

Calculation of the Annual Equivalent Rate (AER)

Calculation of the Annual Equivalent Rate (AER) Appedix to Code of Coduct for the Advertisig of Iterest Bearig Accouts. (31/1/0) Calculatio of the Aual Equivalet Rate (AER) a) The most geeral case of the calculatio is the rate of iterest which, if applied

More information

Institute of Actuaries of India Subject CT5 General Insurance, Life and Health Contingencies

Institute of Actuaries of India Subject CT5 General Insurance, Life and Health Contingencies Istitute of Actuaries of Idia Subject CT5 Geeral Isurace, Life ad Health Cotigecies For 2017 Examiatios Aim The aim of the Cotigecies subject is to provide a groudig i the mathematical techiques which

More information

Financial Analysis. Lecture 4 (4/12/2017)

Financial Analysis. Lecture 4 (4/12/2017) Fiacial Aalysis Lecture 4 (4/12/217) Fiacial Aalysis Evaluates maagemet alteratives based o fiacial profitability; Evaluates the opportuity costs of alteratives; Cash flows of costs ad reveues; The timig

More information

Hopscotch and Explicit difference method for solving Black-Scholes PDE

Hopscotch and Explicit difference method for solving Black-Scholes PDE Mälardale iversity Fiacial Egieerig Program Aalytical Fiace Semiar Report Hopscotch ad Explicit differece method for solvig Blac-Scholes PDE Istructor: Ja Röma Team members: A Gog HaiLog Zhao Hog Cui 0

More information

Chapter 5: Sequences and Series

Chapter 5: Sequences and Series Chapter 5: Sequeces ad Series 1. Sequeces 2. Arithmetic ad Geometric Sequeces 3. Summatio Notatio 4. Arithmetic Series 5. Geometric Series 6. Mortgage Paymets LESSON 1 SEQUENCES I Commo Core Algebra I,

More information

Parametric Density Estimation: Maximum Likelihood Estimation

Parametric Density Estimation: Maximum Likelihood Estimation Parametric Desity stimatio: Maimum Likelihood stimatio C6 Today Itroductio to desity estimatio Maimum Likelihood stimatio Itroducto Bayesia Decisio Theory i previous lectures tells us how to desig a optimal

More information

Chapter Six. Bond Prices 1/15/2018. Chapter 4, Part 2 Bonds, Bond Prices, Interest Rates and Holding Period Return.

Chapter Six. Bond Prices 1/15/2018. Chapter 4, Part 2 Bonds, Bond Prices, Interest Rates and Holding Period Return. Chapter Six Chapter 4, Part Bods, Bod Prices, Iterest Rates ad Holdig Period Retur Bod Prices 1. Zero-coupo or discout bod Promise a sigle paymet o a future date Example: Treasury bill. Coupo bod periodic

More information

1 Random Variables and Key Statistics

1 Random Variables and Key Statistics Review of Statistics 1 Radom Variables ad Key Statistics Radom Variable: A radom variable is a variable that takes o differet umerical values from a sample space determied by chace (probability distributio,

More information

Section 3.3 Exercises Part A Simplify the following. 1. (3m 2 ) 5 2. x 7 x 11

Section 3.3 Exercises Part A Simplify the following. 1. (3m 2 ) 5 2. x 7 x 11 123 Sectio 3.3 Exercises Part A Simplify the followig. 1. (3m 2 ) 5 2. x 7 x 11 3. f 12 4. t 8 t 5 f 5 5. 3-4 6. 3x 7 4x 7. 3z 5 12z 3 8. 17 0 9. (g 8 ) -2 10. 14d 3 21d 7 11. (2m 2 5 g 8 ) 7 12. 5x 2

More information

If your home is bigger than you need

If your home is bigger than you need If your home is bigger tha you eed Avoidig ad copig with the bedroom tax (uder-occupacy charge) www.soha.co.uk THE BEDROOM TAX If you re of workig age, receive Housig Beefit ad have oe or more spare bedrooms,

More information

Your guide to Protection Trusts

Your guide to Protection Trusts Your guide to Protectio Trusts Protectio Makig the most of your Aviva protectio policy Nobodylikestothikaboutwhatwill happewhetheyhavegoe.you realready thikigaheadbyhavigaprotectiopolicy iplace,whichcouldhelptheoesyoulove

More information

APPLICATION OF GEOMETRIC SEQUENCES AND SERIES: COMPOUND INTEREST AND ANNUITIES

APPLICATION OF GEOMETRIC SEQUENCES AND SERIES: COMPOUND INTEREST AND ANNUITIES APPLICATION OF GEOMETRIC SEQUENCES AND SERIES: COMPOUND INTEREST AND ANNUITIES Example: Brado s Problem Brado, who is ow sixtee, would like to be a poker champio some day. At the age of twety-oe, he would

More information

Section Mathematical Induction and Section Strong Induction and Well-Ordering

Section Mathematical Induction and Section Strong Induction and Well-Ordering Sectio 4.1 - Mathematical Iductio ad Sectio 4. - Strog Iductio ad Well-Orderig A very special rule of iferece! Defiitio: A set S is well ordered if every subset has a least elemet. Note: [0, 1] is ot well

More information

III. RESEARCH METHODS. Riau Province becomes the main area in this research on the role of pulp

III. RESEARCH METHODS. Riau Province becomes the main area in this research on the role of pulp III. RESEARCH METHODS 3.1 Research Locatio Riau Provice becomes the mai area i this research o the role of pulp ad paper idustry. The decisio o Riau Provice was supported by several facts: 1. The largest

More information

Introduction to Financial Derivatives

Introduction to Financial Derivatives 550.444 Itroductio to Fiacial Derivatives Determiig Prices for Forwards ad Futures Week of October 1, 01 Where we are Last week: Itroductio to Iterest Rates, Future Value, Preset Value ad FRAs (Chapter

More information

INTERVAL GAMES. and player 2 selects 1, then player 2 would give player 1 a payoff of, 1) = 0.

INTERVAL GAMES. and player 2 selects 1, then player 2 would give player 1 a payoff of, 1) = 0. INTERVAL GAMES ANTHONY MENDES Let I ad I 2 be itervals of real umbers. A iterval game is played i this way: player secretly selects x I ad player 2 secretly ad idepedetly selects y I 2. After x ad y are

More information

r i = a i + b i f b i = Cov[r i, f] The only parameters to be estimated for this model are a i 's, b i 's, σe 2 i

r i = a i + b i f b i = Cov[r i, f] The only parameters to be estimated for this model are a i 's, b i 's, σe 2 i The iformatio required by the mea-variace approach is substatial whe the umber of assets is large; there are mea values, variaces, ad )/2 covariaces - a total of 2 + )/2 parameters. Sigle-factor model:

More information

Statistical techniques

Statistical techniques 4 Statistical techiques this chapter covers... I this chapter we will explai how to calculate key statistical idicators which will help us to aalyse past data ad help us forecast what may happe i the future.

More information

- competitive economy with n consumption goods, and a single form of labor which is only input

- competitive economy with n consumption goods, and a single form of labor which is only input APPLIED WELFARE ECONOMICS AND POLICY ANALYSIS Commodity Taxatio Basic problem i commodity taxatio: if a social welfare fuctio is assumed, whas the choice of commodity tax rates that will maximize social

More information

Sampling Distributions & Estimators

Sampling Distributions & Estimators API-209 TF Sessio 2 Teddy Svoroos September 18, 2015 Samplig Distributios & Estimators I. Estimators The Importace of Samplig Radomly Three Properties of Estimators 1. Ubiased 2. Cosistet 3. Efficiet I

More information

Twitter: @Owe134866 www.mathsfreeresourcelibrary.com Prior Kowledge Check 1) State whether each variable is qualitative or quatitative: a) Car colour Qualitative b) Miles travelled by a cyclist c) Favourite

More information

An Empirical Study of the Behaviour of the Sample Kurtosis in Samples from Symmetric Stable Distributions

An Empirical Study of the Behaviour of the Sample Kurtosis in Samples from Symmetric Stable Distributions A Empirical Study of the Behaviour of the Sample Kurtosis i Samples from Symmetric Stable Distributios J. Marti va Zyl Departmet of Actuarial Sciece ad Mathematical Statistics, Uiversity of the Free State,

More information

Combining imperfect data, and an introduction to data assimilation Ross Bannister, NCEO, September 2010

Combining imperfect data, and an introduction to data assimilation Ross Bannister, NCEO, September 2010 Combiig imperfect data, ad a itroductio to data assimilatio Ross Baister, NCEO, September 00 rbaister@readigacuk The probability desity fuctio (PDF prob that x lies betwee x ad x + dx p (x restrictio o

More information

Solutions to Problem Sheet 1

Solutions to Problem Sheet 1 Solutios to Problem Sheet ) Use Theorem.4 to prove that p log for all real x 3. This is a versio of Theorem.4 with the iteger N replaced by the real x. Hit Give x 3 let N = [x], the largest iteger x. The,

More information

Osborne Books Update. Financial Statements of Limited Companies Tutorial

Osborne Books Update. Financial Statements of Limited Companies Tutorial Osbore Books Update Fiacial Statemets of Limited Compaies Tutorial Website update otes September 2018 2 f i a c i a l s t a t e m e t s o f l i m i t e d c o m p a i e s I N T R O D U C T I O N The followig

More information

10. The two-period economy with sticky prices

10. The two-period economy with sticky prices 0. The two-period ecoomy with sticky prices Idex: 0. The two-period ecoomy with sticky prices... 9. Itroductio... 9. Basic model... 9.. Mai assumptios... 9.. Equilibrium...4 9.3 The well fuctioig versus

More information

living well in retirement Adjusting Your Annuity Income Your Payment Flexibilities

living well in retirement Adjusting Your Annuity Income Your Payment Flexibilities livig well i retiremet Adjustig Your Auity Icome Your Paymet Flexibilities what s iside 2 TIAA Traditioal auity Icome 4 TIAA ad CREF Variable Auity Icome 7 Choices for Adjustig Your Auity Icome 7 Auity

More information

CHAPTER 8: CONFIDENCE INTERVAL ESTIMATES for Means and Proportions

CHAPTER 8: CONFIDENCE INTERVAL ESTIMATES for Means and Proportions CHAPTER 8: CONFIDENCE INTERVAL ESTIMATES for Meas ad Proportios Itroductio: We wat to kow the value of a parameter for a populatio. We do t kow the value of this parameter for the etire populatio because

More information

setting up the business in sage

setting up the business in sage 3 settig up the busiess i sage Chapter itroductio Settig up a computer accoutig program for a busiess or other orgaisatio will take some time, but as log as the correct data is etered i the correct format

More information

A Technical Description of the STARS Efficiency Rating System Calculation

A Technical Description of the STARS Efficiency Rating System Calculation A Techical Descriptio of the STARS Efficiecy Ratig System Calculatio The followig is a techical descriptio of the efficiecy ratig calculatio process used by the Office of Superitedet of Public Istructio

More information

Chapter 2 Demand and Supply Analysis

Chapter 2 Demand and Supply Analysis Chapter 2 Demad ad Supply Aalysis Outlie 1. Competitive Markets Defiitio Assumptios of the model 2. The Market Demad Curve 3. The Market Supply Curve 4. Competitive Market Equilibrium 5. Elasticity 2 Mothly

More information

Math 312, Intro. to Real Analysis: Homework #4 Solutions

Math 312, Intro. to Real Analysis: Homework #4 Solutions Math 3, Itro. to Real Aalysis: Homework #4 Solutios Stephe G. Simpso Moday, March, 009 The assigmet cosists of Exercises 0.6, 0.8, 0.0,.,.3,.6,.0,.,. i the Ross textbook. Each problem couts 0 poits. 0.6.

More information

The Time Value of Money in Financial Management

The Time Value of Money in Financial Management The Time Value of Moey i Fiacial Maagemet Muteau Irea Ovidius Uiversity of Costata irea.muteau@yahoo.com Bacula Mariaa Traia Theoretical High School, Costata baculamariaa@yahoo.com Abstract The Time Value

More information

Class Sessions 2, 3, and 4: The Time Value of Money

Class Sessions 2, 3, and 4: The Time Value of Money Class Sessios 2, 3, ad 4: The Time Value of Moey Associated Readig: Text Chapter 3 ad your calculator s maual. Summary Moey is a promise by a Bak to pay to the Bearer o demad a sum of well, moey! Oe risk

More information

Sampling Distributions and Estimation

Sampling Distributions and Estimation Cotets 40 Samplig Distributios ad Estimatio 40.1 Samplig Distributios 40. Iterval Estimatio for the Variace 13 Learig outcomes You will lear about the distributios which are created whe a populatio is

More information

1. Suppose X is a variable that follows the normal distribution with known standard deviation σ = 0.3 but unknown mean µ.

1. Suppose X is a variable that follows the normal distribution with known standard deviation σ = 0.3 but unknown mean µ. Chapter 9 Exercises Suppose X is a variable that follows the ormal distributio with kow stadard deviatio σ = 03 but ukow mea µ (a) Costruct a 95% cofidece iterval for µ if a radom sample of = 6 observatios

More information

. (The calculated sample mean is symbolized by x.)

. (The calculated sample mean is symbolized by x.) Stat 40, sectio 5.4 The Cetral Limit Theorem otes by Tim Pilachowski If you have t doe it yet, go to the Stat 40 page ad dowload the hadout 5.4 supplemet Cetral Limit Theorem. The homework (both practice

More information

KEY INFORMATION DOCUMENT CFD s Generic

KEY INFORMATION DOCUMENT CFD s Generic KEY INFORMATION DOCUMENT CFD s Geeric KEY INFORMATION DOCUMENT - CFDs Geeric Purpose This documet provides you with key iformatio about this ivestmet product. It is ot marketig material ad it does ot costitute

More information

DESCRIPTION OF MATHEMATICAL MODELS USED IN RATING ACTIVITIES

DESCRIPTION OF MATHEMATICAL MODELS USED IN RATING ACTIVITIES July 2014, Frakfurt am Mai. DESCRIPTION OF MATHEMATICAL MODELS USED IN RATING ACTIVITIES This documet outlies priciples ad key assumptios uderlyig the ratig models ad methodologies of Ratig-Agetur Expert

More information

10.The Zero Lower Bound in a two period economy

10.The Zero Lower Bound in a two period economy .The Zero Lower Boud i a two period ecoomy Idex:. The Zero Lower Boud i a two period ecoomy.... Itroductio.... A two period closed ecoomy with moey.....osumptio.....the IS curve...3..3the Fisher equatio...3..4the

More information

Online appendices from The xva Challenge by Jon Gregory. APPENDIX 10A: Exposure and swaption analogy.

Online appendices from The xva Challenge by Jon Gregory. APPENDIX 10A: Exposure and swaption analogy. APPENDIX 10A: Exposure ad swaptio aalogy. Sorese ad Bollier (1994), effectively calculate the CVA of a swap positio ad show this ca be writte as: CVA swap = LGD V swaptio (t; t i, T) PD(t i 1, t i ). i=1

More information

Topic-7. Large Sample Estimation

Topic-7. Large Sample Estimation Topic-7 Large Sample Estimatio TYPES OF INFERENCE Ò Estimatio: É Estimatig or predictig the value of the parameter É What is (are) the most likely values of m or p? Ò Hypothesis Testig: É Decidig about

More information

1 Estimating sensitivities

1 Estimating sensitivities Copyright c 27 by Karl Sigma 1 Estimatig sesitivities Whe estimatig the Greeks, such as the, the geeral problem ivolves a radom variable Y = Y (α) (such as a discouted payoff) that depeds o a parameter

More information

FOR TEACHERS ONLY. The University of the State of New York REGENTS HIGH SCHOOL EXAMINATION PHYSICAL SETTING/PHYSICS

FOR TEACHERS ONLY. The University of the State of New York REGENTS HIGH SCHOOL EXAMINATION PHYSICAL SETTING/PHYSICS PS P FOR TEACHERS ONLY The Uiersity of the State of New York REGENTS HIGH SCHOOL EXAMINATION PHYSICAL SETTING/PHYSICS Wedesday, Jue, 005 :5 to 4:5 p.m., oly SCORING KEY AND RATING GUIDE Directios to the

More information

CHAPTER 8: CONFIDENCE INTERVAL ESTIMATES for Means and Proportions

CHAPTER 8: CONFIDENCE INTERVAL ESTIMATES for Means and Proportions CHAPTER 8: CONFIDENCE INTERVAL ESTIMATES for Meas ad Proportios Itroductio: I this chapter we wat to fid out the value of a parameter for a populatio. We do t kow the value of this parameter for the etire

More information

Annual compounding, revisited

Annual compounding, revisited Sectio 1.: No-aual compouded iterest MATH 105: Cotemporary Mathematics Uiversity of Louisville August 2, 2017 Compoudig geeralized 2 / 15 Aual compoudig, revisited The idea behid aual compoudig is that

More information

Exam 2. Instructor: Cynthia Rudin TA: Dimitrios Bisias. October 25, 2011

Exam 2. Instructor: Cynthia Rudin TA: Dimitrios Bisias. October 25, 2011 15.075 Exam 2 Istructor: Cythia Rudi TA: Dimitrios Bisias October 25, 2011 Gradig is based o demostratio of coceptual uderstadig, so you eed to show all of your work. Problem 1 You are i charge of a study

More information

Lecture 4: Parameter Estimation and Confidence Intervals. GENOME 560 Doug Fowler, GS

Lecture 4: Parameter Estimation and Confidence Intervals. GENOME 560 Doug Fowler, GS Lecture 4: Parameter Estimatio ad Cofidece Itervals GENOME 560 Doug Fowler, GS (dfowler@uw.edu) 1 Review: Probability Distributios Discrete: Biomial distributio Hypergeometric distributio Poisso distributio

More information

18.S096 Problem Set 5 Fall 2013 Volatility Modeling Due Date: 10/29/2013

18.S096 Problem Set 5 Fall 2013 Volatility Modeling Due Date: 10/29/2013 18.S096 Problem Set 5 Fall 2013 Volatility Modelig Due Date: 10/29/2013 1. Sample Estimators of Diffusio Process Volatility ad Drift Let {X t } be the price of a fiacial security that follows a geometric

More information