Two Period Financial Markets

Total Page:16

File Type:pdf, Size:1020Kb

Two Period Financial Markets Foundations of Financial Economics Two period financial markets Paulo Brito [email protected] University of Lisbon April 3, 2020 1 / 63 Topics I Financial assets I Financial market I State prices I Portfolios I Absence of arbitrage opportunities I Complete financial markets I Arbitrage pricing I Equity premium I Equity premium puzzle 2 / 63 Information I Assume again that there is complete information regarding time t = 0, but incomplete information regarding time t = 1. I Until now we have (mostly) assumed that the probability distribution is given by nature. I But next we start assuming that information regarding time t = 1 is provided by the financial market. I A financial market is defined by a collection of contingent claims. I The general idea: under some conditions, we can extract an implicit probability distribution of the states of nature from the structure of the financial market. 3 / 63 Financial assets Prices and payoffs A financial asset or contract or contingent claim: is defined by the price and payoff pair (Sj; Vj) (for asset j): I for an observed price, Sj, paid at time t = 0 I a contingent payoff, Vj, will be received at time t = 1, > Vj = (Vj1;:::; Vjs;:::; VjN) 4 / 63 Financial assets Returns and rates of return I Return Rj and rate of return rj of asset j are related as Rj = 1 + rj; I In the 2-period case: it is the payoff/price ratio 0 1 Vj;1 0 1 B Sj C 1 + rj;1 B ::: C B ::: C V B C B C R = j = B Vj;s C = B 1 + r C j Sj B j;s C Sj B C @ A @ ::: A ::: Vj;N 1 + rj;N Sj 5 / 63 Financial assets Timing, information and flow of funds Two alternative ways of representing (net) income flows: I as a price-payoff sequence 0 1 Vj;1 B C B ::: C B C B Vj;s C @ ::: A −Sj Vj;N 0 1 I as an investment-return sequence 0 1 Rj;1 B C B ::: C B C B Rj;s C @ ::: A −1 Rj;N 0 1 6 / 63 Financial assets Statistics I From the information, at time t = 0, on the probabilities for the states of nature at time t = 1 we can compute: I Expected return for asset j at time t = 1, from the information at time t = 0 XN E[Rj] = πsRj;s = π1Rj;1 + : : : πsRj;s + ::: + πNRj;N s=1 I Variance of the return for asset j at time t = 1, from the information at time t = 0 XN 2 2 2 V[Rj] = πs(Rjs−E[Rj]) = π1 (Rj;1 − E[Rj]) +: : : πN (Rj;N − E[Rj]) s=1 I Observation: an useful relationship V[R] = E[R2] − (E[R])2 7 / 63 Classification of assets Risk classification As regards risk: I risk-less or risk-free asset: V> = (v;:::; v)> I > > risky asset: V = (v1;:::; vN) with at least two different elements, i.e. there are at least two elements, vi and vj such that vi =6 vj for i =6 j 8 / 63 Classification of assets Types of assets Particular types of assets as regards the income flows: I one period bonds with unit facial value: 1 S = ; V> = (1; 1;:::; 1)> 1 + i I deposits: S = 1; V> = (1 + i; 1 + i;:::; 1 + i)> I equity: the payoff are dividends > > Se; Ve = (d1;:::; dN) 9 / 63 Classification of assets Types of assets Derivatives: I forward contract on an underlying asset with offered price p: > − − > Sf; Vf = (v1 p;:::; vN p) I european call option with exercise price p: > f − g f − g > Sc; Vc = (max v1 p; 0 ;:::; max vN p; 0 ) I european put option with exercise price p: > f − g f − g > Sp; Vp = (max p v1; 0 ;:::; max p vN; 0 ) 10 / 63 Financial market Definition:A financial market is a collection of K traded assets. It can be characterized by the structure of prices and payoffs of all K assets : i.e by the pair (S; V): I vector of observed prices, at time t = 0 (we use row vectors for prices) |{z}S = (S1;:::; SK); K×1 I and a matrix of contingent (i.e., uncertain) payoffs, at time t = 1 0 1 V11 ::: VK1 B . C |{z}V = @ . A × N K V1N ::: VKN I The participants observe S and know V, but they do not know which payoff they will get for every asset (i.e, which line of V will be realized) 11 / 63 Financial market The payoff matrix contains the following information: I each column represents the payoff forasset j = 1;:::; K 0 1 V11 ::: Vj1 ::: VK1 B C B . C B . C B C V = B V1s ::: Vjs ::: VKs C B . C @ . A V1N ::: VjN ::: VKN I each row represents the outcomes (in terms of payoffs) for state of nature s = 1;:::; N 0 1 V11 ::: Vj1 ::: VK1 B C B . C B . C B C V = BV1s ::: Vjs ::: VKsC B . C @ . A V1N ::: VjN ::: VKN 12 / 63 Financial market I Equivalently, we can charaterize a financial market by the matrix of returns 0 1 R11 ::: RK1 B . C |{z}R = @ . A × N K R1N ::: RKN Vj;s where Rj;s = = 1 + rj;s Sj I Therefore −1 |{z}R = |{z}V |(diag{z(S)) } × × N K N K K×K where 0 1 S1 ::: 0 ::: 0 B C B . C B . C B C |diag{z(S}) = B 0 ::: Sj ::: 0 C B . C K×K @ . A 0 ::: 0 ::: SK 13 / 63 State prices Implicit state valuation: the modern approach to financial economics characterizes asset markets by the prices of the states of nature implicit in the relationship between present prices S and future payoffs V, i.e. Q := fx : S = xVg I if Q is unique it is a vector |{z}Q = (q1;:::; qN) 1×N satisfying , > > > |{z}S = |{z}Q |{z}V |{z}S = |{z}V |{z}Q 1×K 1×N N×K K×1 K×N N×1 I Definition: Q is a state price vector if is it positive , i.e. qs > 0 for all s 2 f1;:::; Ng 14 / 63 Arbitrage opportunities Definition: if there is at least one qs ≤ 0, s = 1;:::; N then we say there are arbitrage opportunities Definition: we say there are no arbitrage opportunities if qs > 0, for all s = 1;:::; N Intuition: I existence of arbitrage (opportunities) means there are free or negatively valued states of nature I absence of arbitrage means every state of nature is costly and therefore, positively priced. Proposition 1 Given (S; V), there are no arbitrage opportunities if and only if Q is a vector of state prices. 15 / 63 Completeness of a financial market Definition: if Q is unique, then we say markets are complete Definition: if Q is not unique then we say markets are incomplete Intuition: I completeness: there is an unique valuation of the states of nature. I incompleteness: there is not an unique valuation of the states of nature. 16 / 63 Completeness of a financial market Conditions for completeness We can classify completeness of a market by looking at the number of assets, number of states of nature and the independence of payoffs: 1. if K = N and det (V) =6 0 then markets are complete and all assets are independent; 2. if K > N and det (V) =6 0 then markets are complete and there are N independent and K − N redundant assets; 3. if K < N or K ≥ N and det (V) = 0 then markets are incomplete. Proposition 2 Given (S; V), markets are complete if and only if dim(V) = N dim(V) = number of linearly independent columns (i.e., assets) 17 / 63 Characterization of a financial market No arbitrage opportunities and completeness I Consider a financial market (S; V), such that K = N and det (V) =6 0 I We defined state prices from S = QV I As K = N and det (V) =6 0 then V−1 exists and is unique I Therefore, we obtain uniquely −1 |{z}Q = |{z}S |V{z} 1×N 1×K K×N that is 0 1−1 V1;1 ::: V1;K @ A (q1;:::; qN) = (S1;:::; SK) ::::::::: VN;1 ::: VN;K I If Q ≫ 0 we say there are no arbitrage opportunities I And because Q is unique we say markets are complete 18 / 63 Characterization of a financial market No arbitrage opportunities and completeness: alternative 1 Alternatively, because > > > |{z}V |{z}Q = |{z}S K×N N×1 K×1 If det (V) =6 0 then ( )−1 Q> = V> S> that is 0 1 0 1 0 1 q −1 S 1 V1;1 ::: VN;1 1 B . C @ A B . C @ . A = ::::::::: @ . A V ::: V qN 1;K N;K SK 19 / 63 Characterization of a financial market No arbitrage opportunities and completeness: alternative 2 As Rjs = Vjs=Sj equivalently, we can write > |{z}Q |{z}R = |{z}1 1×N N×K 1×K 0 1 R1;1 ::: R1;K ( ) @ A (q1;:::; qN) ::::::::: = 1 1 1 RN;1 ::: RN;K then Q = 1>R−1 20 / 63 Characterization of a financial market No arbitrage opportunities and completeness: alternative 3 Or, alternatively, R>Q> = 1 then > > −1 |{z}Q =| (R{z) } |{z}1 × N×1 N×K K 1 matricially 0 1 0 1 0 1 q −1 1 1 R1;1 ::: R1;K B . C @ A B.C @ . A = ::::::::: @.A R ::: R qN N;1 N;K 1 21 / 63 Characterization of a financial market Market incompleteness I Consider a financial market (S; V), such that K < N, and in the partition > > > |{z}V = ( |{z}V1 |{z}V2 ) × K N (K×K) (N−K×K) assume that det (V1) =6 0 I We defined state prices from V>Q> = S> I But now we have ( ) ( ) > > > Q1 > V1 V2 > = S Q2 where Q1 is (1 × K) and Q2 is (1 × N − K).
Recommended publications
  • Chapter 4 — Complete Markets
    Chapter 4 — Complete Markets The Basic Complete-Market Problem There are N primary assets each with price pi and payoff Xsi is state s. There are also a complete set of S pure state securities each of which pays $1 in its own state s and 0 otherwise. These pure state securities are often called Arrow-Debreu securities. Assuming there is no arbi- trage, the price of the pure state s security must be qs, the state price. In a complete market like this, investors will be indifferent between choosing a portfolio from the S state securities and all N + S securities. A portfolio holding n shares of primary assets and η1 shares of the Arrow-Debreu securities will provide consumption c = Xn + η1 in the states at time 1. A portfolio holding η2 ≡ Xn + η1 of just the Arrow-Debreu securities obviously gives the same consumption. The costs of the two portfolios are q′c and p′n + q′η1. From the definition of c and the no-arbitrage result that p′ = q′X, these are obviously the same. Of course in equilibrium the original primary assets must actually be held. However this can be done by financial intermediaries like mutual funds. They buy all the primary shares finan- cing the purchases by issuing the Arrow-Debreu securities. By issuing h = Xn Arrow-Debreu securities where n is the aggregate supply of the primary assets, the intermediary is exactly hedged, and their role can be ignored. So with no loss of generality, we can therefore assume that individual investors only purchases Arrow-Debreu securities ignoring the primary assets.
    [Show full text]
  • QR43, Introduction to Investments Class Notes, Fall 2004 I. Prices, Portfolios, and Arbitrage
    QR43, Introduction to Investments Class Notes, Fall 2004 I. Prices, Portfolios, and Arbitrage A. Introduction 1. What are investments? You pay now, get repaid later. But can you be sure how much you will be repaid? Time and uncertainty are essential. Real investments, such as machinery, require an input of re- sources today and deliver an output of resources later. Financial investments,suchasstocksandbonds,areclaimstotheoutput produced by real investments. For example: A company issues shares of stock to investors. The proceeds of the share issue are used to build a factory and to hire workers. The factory produces goods, and the sales proceeds give the company revenue or sales. After paying the workers and set- ting aside money to replace the machinery and buildings when they wear out (depreciation), the company is left with earnings.The company keeps some earnings to make new real investments (re- tained earnings), and pays the rest to shareholders in the form of dividends. Later, the company decides to expand production and needs to raisemoremoneytofinance its expansion. Rather than issue new shares, it decides to issue corporate bonds that promise fixed pay- ments to bondholders. The expanded production increases revenue. However, interest payments on the bonds, and the setting aside of 1 money to repay the principal (amortization), are subtracted from revenue. Thus earnings may increase or decrease depending on the success of the company’s expansion. Financial investments are also known as capital assets or finan- cial assets. The markets in which capital assets are traded are known as capital markets or financial markets. Capital assets are commonly divided into three broad categories: Fixed-income securities promise to make fixed payments in the • future.
    [Show full text]
  • Money and Prices Under Uncertainty1
    Money and prices under uncertainty1 Tomoyuki Nakajima2 Herakles Polemarchakis3 Review of Economic Studies, 72, 223-246 (2005) 4 1We had very helpful conversations with Jayasri Dutta, Ronel Elul, John Geanakoplos, Demetre Tsomokos and Michael Woodford; the editor and referees made valuable comments and suggestions. The work of Polemarchakis would not have been possible without earlier joint work with Gaetano Bloise and Jacques Dr`eze. 2Department of Economics, Brown University; tomoyuki [email protected] 3Department of Economics, Brown University; herakles [email protected] 4Earlier versions appeared as \Money and prices under uncertainty," Working Paper No. 01- 32, Department of Economics, Brown University, September, 2001 and \Monetary equilibria with monopolistic competition and sticky prices," Working Paper No. 02-25, Department of Economics, Brown University, 2002 Abstract We study whether monetary economies display nominal indeterminacy: equivalently, whether monetary policy determines the path of prices under uncertainty. In a simple, stochastic, cash-in-advance economy, we find that indeterminacy arises and is characterized by the initial price level and a probability measure associated with state-contingent nom- inal bonds: equivalently, monetary policy determines an average, but not the distribution of inflation across realizations of uncertainty. The result does not derive from the stability of the deterministic steady state and is not affected essentially by price stickiness. Nom- inal indeterminacy may affect real allocations in cases we identify. Our characterization applies to stochastic monetary models in general, and it permits a unified treatment of the determinants of paths of inflation. Key words: monetary policy; uncertainty; indeterminacy; fiscal policy; price rigidities. JEL classification numbers: D50; D52; E31; E40; E50.
    [Show full text]
  • Intermediation Markups and Monetary Policy Passthrough ∗
    Intermediation Markups and Monetary Policy Passthrough ∗ Semyon Malamudyand Andreas Schrimpfz This version: December 12, 2016 Abstract We introduce intermediation frictions into the classical monetary model with fully flexible prices. Trade in financial assets happens through intermediaries who bargain over a full set of state-contingent claims with their customers. Monetary policy is redistributive and affects intermediaries' ability to extract rents; this opens up a new channel for transmission of monetary shocks into rates in the wider economy, which may be labelled the markup channel of monetary policy. Passthrough efficiency depends crucially on the anticipated sensitivity of future monetary policy to future stock market returns (the \Central Bank Put"). The strength of this put determines the room for maneuver of monetary policy: when it is strong, monetary policy is destabilizing and may lead to market tantrums where deteriorating risk premia, illiquidity and markups mutually reinforce each other; when the put is too strong, passthrough becomes fully inefficient and a surprise easing even begets a rise in real rates. Keywords: Monetary Policy, Stock Returns, Intermediation, Market Frictions JEL Classification Numbers: G12, E52, E40, E44 ∗We thank Viral Acharya, Markus Brunnermeier, Egemen Eren, Itay Goldstein, Piero Gottardi, Michel Habib, Enisse Kharroubi, Arvind Krishnamurthy, Giovanni Lombardo, Matteo Maggiori, Jean-Charles Rochet, Hyun Song Shin, and Michael Weber, as well as seminar participants at the BIS and the University of Zurich for helpful comments. Semyon Malamud acknowledges the financial support of the Swiss National Science Foundation and the Swiss Finance Institute. Parts of this paper were written when Malamud visited BIS as a research fellow.
    [Show full text]
  • Lecture 02: One Period Model
    Fin 501: Asset Pricing Lecture 02: One Period Model Prof. Markus K. Brunnermeier 10:37 Lecture 02 One Period Model Slide 2-1 Fin 501: Asset Pricing Overview 1. Securities Structure • Arrow-Debreu securities structure • Redundant securities • Market completeness • Completing markets with options 2. Pricing (no arbitrage, state prices, SDF, EMM …) 10:37 Lecture 02 One Period Model Slide 2-2 Fin 501: Asset Pricing The Economy s=1 • State space (Evolution of states) s=2 Two dates: t=0,1 0 S states of the world at time t=1 … • Preferences s=S U(c0, c1, …,cS) (slope of indifference curve) • Security structure Arrow-Debreu economy General security structure 10:37 Lecture 02 One Period Model Slide 2-3 Fin 501: Asset Pricing Security Structure • Security j is represented by a payoff vector • Security structure is represented by payoff matrix • NB. Most other books use the transpose of X as payoff matrix. 10:37 Lecture 02 One Period Model Slide 2-4 Fin 501: Asset Pricing Arrow-Debreu Security Structure in R2 One A-D asset e1 = (1,0) c2 This payoff cannot be replicated! Payoff Space <X> c1 Markets are incomplete ) 10:37 Lecture 02 One Period Model Slide 2-5 Fin 501: Asset Pricing Arrow-Debreu Security Structure in R2 Add second A-D asset e2 = (0,1) to e1 = (1,0) c2 c1 10:37 Lecture 02 One Period Model Slide 2-6 Fin 501: Asset Pricing Arrow-Debreu Security Structure in R2 Add second A-D asset e2 = (0,1) to e1 = (1,0) c2 Payoff space <X> c1 Any payoff can be replicated with two A-D securities 10:37 Lecture 02 One Period Model Slide 2-7 Fin 501: Asset
    [Show full text]
  • Finance: a Quantitative Introduction Chapter 7 - Part 2 Option Pricing Foundations
    The setting Complete Markets Arbitrage free markets Risk neutral valuation Finance: A Quantitative Introduction Chapter 7 - part 2 Option Pricing Foundations Nico van der Wijst 1 Finance: A Quantitative Introduction c Cambridge University Press The setting Complete Markets Arbitrage free markets Risk neutral valuation 1 The setting 2 Complete Markets 3 Arbitrage free markets 4 Risk neutral valuation 2 Finance: A Quantitative Introduction c Cambridge University Press The setting Complete Markets Arbitrage free markets Risk neutral valuation Recall general valuation formula for investments: t X Exp [Cash flowst ] Value = t (1 + discount ratet ) Uncertainty can be accounted for in 3 different ways: 1 Adjust discount rate to risk adjusted discount rate 2 Adjust cash flows to certainty equivalent cash flows 3 Adjust probabilities (expectations operator) from normal to risk neutral or equivalent martingale probabilities 3 Finance: A Quantitative Introduction c Cambridge University Press The setting Complete Markets Arbitrage free markets Risk neutral valuation Introduce pricing principles in state preference theory old, tested modelling framework excellent framework to show completeness and arbitrage more general than binomial option pricing Also introduce some more general concepts equivalent martingale measure state prices, pricing kernel, few more Gives you easy entry to literature (+ pinch of matrix algebra, just for fun, can easily be omitted) 4 Finance: A Quantitative Introduction c Cambridge University Press The setting Time and states Complete
    [Show full text]
  • State Prices and Implementation of the Recovery Theorem
    J. Risk Financial Manag. 2015, 8, 2-16; doi:10.3390/jrfm8010002 OPEN ACCESS Journal of Risk and Financial Management ISSN 1911-8074 www.mdpi.com/journal/jrfm Article State Prices and Implementation of the Recovery Theorem Alex Backwell Department of Actuarial Science and the African Collaboration for Quantitative Finance and Risk Research, University of Cape Town, Rondebosch, Cape Town 7700, South Africa; E-Mail: [email protected]; Tel.: +27-21-650-2474 Academic Editor: Michael McAleer Received: 29 October 2014 / Accepted: 5 January 2015 / Published: 19 January 2015 Abstract: It is generally held that derivative prices do not contain useful predictive information, that is, information relating to the distribution of future financial variables under the real-world measure. This is because the market’s implicit forecast of the future becomes entangled with market risk preferences during derivative price formation. A result derived by Ross [1], however, recovers the real-world distribution of an equity index, requiring only current prices and mild restrictions on risk preferences. In addition to being of great interest to the theorist, the potential practical value of the result is considerable. This paper addresses implementation of the Ross Recovery Theorem. The theorem is formalised, extended, proved and discussed. Obstacles to application are identified and a workable implementation methodology is developed. Keywords: Recovery Theorem; Ross recovery; real-world measure; predictive information; state prices; state-price matrix 1. Introduction Financial derivatives are forward-looking in nature, and therefore one may ask whether inferences about the future can be made from liquid derivative prices. In particular, one may aim to make deductions about the real-world, or natural, probability measure.
    [Show full text]
  • Asset Prices and Banking Distress: a Macroeconomic Approach by Goetz Von Peter
    BIS Working Papers No 167 Asset prices and banking distress: a macroeconomic approach by Goetz von Peter Monetary and Economic Department December 2004 BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements, and from time to time by other economists, and are published by the Bank. The views expressed in them are those of their authors and not necessarily the views of the BIS. Copies of publications are available from: Bank for International Settlements Press & Communications CH-4002 Basel, Switzerland E-mail: [email protected] Fax: +41 61 280 9100 and +41 61 280 8100 This publication is available on the BIS website (www.bis.org). © Bank for International Settlements 2004. All rights reserved. Brief excerpts may be reproduced or translated provided the source is cited. ISSN 1020-0959 (print) ISSN 1682-7678 (online) Abstract∗ This paper links banking with asset prices in a monetary macroeconomic model. The main innovation is to consider how falling asset prices affect the banking system through wide-spread borrower default, while deriving explicit solutions and balance sheet effects even far from the steady state. We find that the effect of falling asset prices is indirect, non-linear, and involves feedback from the banking system in the form of a credit contraction. When borrowers repay, the effect ‘passes through’ the bank balance sheet; once borrowers default, asset prices drive bank capital, and constrained credit in turn drives asset prices. This interaction can explain capital crunches, financial instability, and banking crises, either as fundamental or as self-fulfilling outcomes.
    [Show full text]
  • Xinfu Chen Mathematical Finance II
    Xinfu Chen Mathematical Finance II Department of mathematics, University of Pittsburgh Pittsburgh, PA 15260, USA ii MATHEMATICAL FINANCE II Course Outline This course is an introduction to modern mathematical ¯nance. Topics include 1. single period portfolio optimization based on the mean-variance analysis, capital asset pricing model, factor models and arbitrage pricing theory. 2. pricing and hedging derivative securities based on a fundamental state model, the well-received Cox-Ross-Rubinstein's binary lattice model, and the celebrated Black-Scholes continuum model; 3. discrete-time and continuous-time optimal portfolio growth theory, in particular the universal log- optimal pricing formula; 4. necessary mathematical tools for ¯nance, such as theories of measure, probability, statistics, and stochastic process. Prerequisites Calculus, Knowledge on Excel Spreadsheet, or Matlab, or Mathematica, or Maple. Textbooks David G. Luenberger, Investment Science, Oxford University Press, 1998. Xinfu Chen, Lecture Notes, available online www.math.pitt.edu/~xfc. Recommended References Steven Roman, Introduction to the Mathematics of Finance, Springer, 2004. John C. Hull, Options, Futures and Other Derivatives, Fourth Edition, Prentice-Hall, 2000. Martin Baxter and Andrew Rennie, Financial Calculus, Cambridge University Press, 1996. P. Wilmott, S. Howison & J. Dewynne, The Mathematics of Financial Derviatives, CUP, 1999. Stanley R. Pliska, Inroduction to Mathematical Finance, Blackwell, 1999. Grading Scheme Homework 40 % Take Home Midterms 40% Final 40% iii iv MATHEMATICAL FINANCE II Contents MATHEMATICAL FINANCE II iii 1 Mean-Variance Portfolio Theory 1 1.1 Assets and Portfolios . 1 1.2 The Markowitz Portfolio Theory . 9 1.3 Capital Asset Pricing Model . 14 1.3.1 Derivation of the Market Portfolio .
    [Show full text]
  • Do the Unemployed Pay Lower Prices? a Reassessment of the Value Of
    DO THE UNEMPLOYED PAY LOWER PRICES? A REASSESSMENT OF THE VALUE OF UNEMPLOYMENT INSURANCE Downloaded from https://academic.oup.com/jeea/article/18/5/2135/5607409 by Banco de España. Biblioteca user on 16 December 2020 Rodolfo G. Campos Iliana Reggio Banco de Espana˜ Goethe University Frankfurt Abstract It is well known that transitions from employment to unemployment reduce consumption expenditure, but is this fall mainly driven by quantities or by prices? Using panel data on expenditure and quantities from the Spanish consumption survey we find that the unemployed pay prices that are, on average, 1.5% lower, and that this difference in prices accounts for roughly one sixth of the gap in consumption expenditure between the employed and the unemployed. The reduction in prices estimated with panel data is considerably lower than the existing estimates for the United States, which rely on cross- sectional comparisons. Based on our estimates, and using economic theory, we reassess the value of providing unemployment insurance and show how the social value of providing unemployment insurance can be decomposed into a consumption-smoothing component and a component that depends on prices. (JEL: D12, J64, H11) 1. Introduction Economic theory indicates that the consumption-smoothing benefits of unemployment insurance can be inferred from the gap in consumption between the employed and the unemployed. The measurement of this gap has received considerable attention and has been estimated, for example, by Cochrane (1991), Gruber (1997), Browning and Crossley (2001), and Stephens (2001). Because of data limitations, the consumption gap is usually estimated using consumption expenditure (price times quantity) rather than consumption (quantity).
    [Show full text]
  • Monthly Unemployment Rate – NSA
    The National, State & Local Economies September 29, 2017 Tatiana Bailey, Ph.D. Director, UCCS Economic Forum Please do not reproduce, forward or post this presentation without permission. Platinum Level Sponsors: Gold Level Sponsors: Silver Level Sponsors: Sustaining Level Sponsors: ADD STAFF, Inc. Independent Bank Aventa Credit Union Integrity Bank and Trust CAMA South IREM Southern Colorado Chapter 53 Channelvation Legacy Bank Children’s Hospital Colorado Olive Real Estate Group, Inc. City of Fountain The Patterson Group Classic Companies Peoples Bank The Colomina Life Company Pikes Peak Small Business Development Center Colorado Springs Convention & Visitors Bureau Pikes Peak Workforce Center Downtown Partnership of Colorado Springs Red Leg Brewing Company dpiX, LLC RTA Architects The Eastern Colorado Bank Salzman Real Estate Services, Ltd. Financial Planning Association of Southern Colorado TMR Direct FirstBank UCHealth Memorial Hospital GH Phipps Construction Companies University of Colorado Executive Programs HUB International Insurance Services U.S. Bank Housing & Building Association of Colorado Springs Overview • A Few National Indicators – Big Picture • The Colorado State Economy • Our Local Economy Real Growth in GDP vs. Year Ago 5 4 3 Q2: 2.2% 2 1 0 -1 Percentage Jan-02 Jan-13 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-14 Jan-15 Jan-16 Jan-17 -2 Jan-01 -3 Forecasts 2017 2018 -4 Longest expansion in 150 years GDP 2.2% 2.3% -5 Time Period (Quarterly at Annualized Rate) Source: U.S. Bureau of Economic Analysis; GDP forecasts by CO Office of State Planning & Budgeting in “real” terms.
    [Show full text]
  • The Case for Price Stability
    Working Paper Series This paper can be downloaded without charge from: http://www.richmondfed.org/publications/ The Case for Price Stability Marvin Goodfriend Robert G. King¤ Federal Reserve Bank of Richmond Working Paper No. 01-02 April 2001 JEL Nos. E3, E5, E6 Keywords: in‡ation persistence, markup constancy, neutral monetary policy, new neoclassical synthesis, optimal monetary and …scal policy, price level stability, real business cycles, sticky wages and prices Abstract Reasoning within the New Neoclassical Synthesis (NNS) we previously recom- mended that price stability should be the primary objective of monetary policy. We called this a neutral policy because it keeps output at its potential, de…ned as the out- come of an imperfectly competitive real business cycle model with a constant markup of price over marginal cost. We explore the foundations of neutral policy more fully in this paper. Using the principles of public …nance, we derive conditions under which markup constancy is optimal monetary policy. Price stability as the primary policy objective has been criticized on a number of grounds which we evaluate in this paper. We show that observed in‡ation persistence in U.S. time series is consistent with the absence of structural in‡ation stickiness as is the case in the benchmark NNS economy. We consider reasons why monetary policy might depart from markup constancy and price stability, but we argue that optimal departures are likely to be minor. Finally, we argue that the presence of nominal wage stickiness in labor markets does not undermine the case for neutral policy and price stability. ¤Goodfriend is Senior Vice President and Policy Advisor at the Federal Reserve Bank of Richmond.
    [Show full text]