Utility Maximisation Problem
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The Soft Budget Constraint
Acta Oeconomica, Vol. 64 (S1) pp. 25–79 (2014) DOI: 10.1556/AOecon.64.2014.S1.2 THE SOFT BUDGET CONSTRAINT An Introductory Study to Volume IV of the Life’s Work Series* János KORNAI** The author’s ideas on the soft budget constraint (SBC) were first expressed in 1976. Much progress has been made in understanding the problem over the ensuing four decades. The study takes issue with those who confine the concept to the process of bailing out loss-making socialist firms. It shows how the syndrome can appear in various organizations and forms in many spheres of the economy and points to the various means available for financial rescue. Single bailouts do not as such gener- ate the SBC syndrome. It develops where the SBC becomes built into expectations. Special heed is paid to features generated by the syndrome in rescuer and rescuee organizations. The study reports on the spread of the syndrome in various periods of the socialist and the capitalist system, in various sectors. The author expresses his views on normative questions and on therapies against the harmful effects. He deals first with actual practice, then places the theory of the SBC in the sphere of ideas and models, showing how it relates to other theoretical trends, including institutional and behav- ioural economics and theories of moral hazard and inconsistency in time. He shows how far the in- tellectual apparatus of the SBC has spread in theoretical literature and where it has reached in the process of “canonization” by the economics profession. Finally, he reviews the main research tasks ahead. -
Lecture 4 " Theory of Choice and Individual Demand
Lecture 4 - Theory of Choice and Individual Demand David Autor 14.03 Fall 2004 Agenda 1. Utility maximization 2. Indirect Utility function 3. Application: Gift giving –Waldfogel paper 4. Expenditure function 5. Relationship between Expenditure function and Indirect utility function 6. Demand functions 7. Application: Food stamps –Whitmore paper 8. Income and substitution e¤ects 9. Normal and inferior goods 10. Compensated and uncompensated demand (Hicksian, Marshallian) 11. Application: Gi¤en goods –Jensen and Miller paper Roadmap: 1 Axioms of consumer preference Primal Dual Max U(x,y) Min pxx+ pyy s.t. pxx+ pyy < I s.t. U(x,y) > U Indirect Utility function Expenditure function E*= E(p , p , U) U*= V(px, py, I) x y Marshallian demand Hicksian demand X = d (p , p , I) = x x y X = hx(px, py, U) = (by Roy’s identity) (by Shepard’s lemma) ¶V / ¶p ¶ E - x - ¶V / ¶I Slutsky equation ¶p x 1 Theory of consumer choice 1.1 Utility maximization subject to budget constraint Ingredients: Utility function (preferences) Budget constraint Price vector Consumer’sproblem Maximize utility subjet to budget constraint Characteristics of solution: Budget exhaustion (non-satiation) For most solutions: psychic tradeo¤ = monetary payo¤ Psychic tradeo¤ is MRS Monetary tradeo¤ is the price ratio 2 From a visual point of view utility maximization corresponds to the following point: (Note that the slope of the budget set is equal to px ) py Graph 35 y IC3 IC2 IC1 B C A D x What’swrong with some of these points? We can see that A P B, A I D, C P A. -
2. Budget Constraint.Pdf
Engineering Economic Analysis 2019 SPRING Prof. D. J. LEE, SNU Chap. 2 BUDGET CONSTRAINT Consumption Choice Sets . A consumption choice set, X, is the collection of all consumption choices available to the consumer. n X = R+ . A consumption bundle, x, containing x1 units of commodity 1, x2 units of commodity 2 and so on up to xn units of commodity n is denoted by the vector xx =(1 ,..., xn ) ∈ X n . Commodity price vector pp =(1 ,..., pn ) ∈R+ 1 Budget Constraints . Q: When is a bundle (x1, … , xn) affordable at prices p1, … , pn? • A: When p1x1 + … + pnxn ≤ m where m is the consumer’s (disposable) income. The consumer’s budget set is the set of all affordable bundles; B(p1, … , pn, m) = { (x1, … , xn) | x1 ≥ 0, … , xn ≥ 0 and p1x1 + … + pnxn ≤ m } . The budget constraint is the upper boundary of the budget set. p1x1 + … + pnxn = m 2 Budget Set and Constraint for Two Commodities x2 Budget constraint is m /p2 p1x1 + p2x2 = m. m /p1 x1 3 Budget Set and Constraint for Two Commodities x2 Budget constraint is m /p2 p1x1 + p2x2 = m. the collection of all affordable bundles. Budget p1x1 + p2x2 ≤ m. Set m /p1 x1 4 Budget Constraint for Three Commodities • If n = 3 x2 p1x1 + p2x2 + p3x3 = m m /p2 m /p3 x3 m /p1 x1 5 Budget Set for Three Commodities x 2 { (x1,x2,x3) | x1 ≥ 0, x2 ≥ 0, x3 ≥ 0 and m /p2 p1x1 + p2x2 + p3x3 ≤ m} m /p3 x3 m /p1 x1 6 Opportunity cost in Budget Constraints x2 p1x1 + p2x2 = m Slope is -p1/p2 a2 Opp. -
3 Lecture 3: Choices from Budget Sets
3 Lecture 3: Choices from Budget Sets Up to now, we have been rather demanding about the data that we need in order to test our models. We have made two important assumptions: that we observe choices from all possible choice sets, and that we observe choice correspondences (i.e. we see all the options that a decision maker would be ‘happy with’). In many cases, we may not be so lucky with our data. Unfortunately, without these two properties, conditions and are no longer necessary or sufficient to guarantee a utility representation. Consider the following example of an incomplete data set. Example 1 Let = and say we observe the following (incomplete) choice correspondence { } ( )= { } { } ( )= { } { } ( )= { } { } This choice correspondence satisfies properties and trivially. is satisfied because we do not observe any choices from sets that are subsets of each other. is satisfied because we never see two objects chosen from the same set. However, there is no way that we can rationalize these choices with a complete preference relation. The first observation implies that ,thesecond  that and the third that 3. Thus, any binary relation that would rationalize these choices   would be intransitive. In fact, in order for theorem 1 to hold, we don’t have to observe choices from all subsets of , but we do have to need at least all subsets of that contain two and three elements (you should go back and look at the proof of theorem 1 and check that you agree with this statement). What about if we drop the assumption that we observe a choice correspondence, and instead observe a choice function? For example, we could ask the following question: Question 1 Let :2 ∅ be a choice function. -
EC9D3 Advanced Microeconomics, Part I: Lecture 2
EC9D3 Advanced Microeconomics, Part I: Lecture 2 Francesco Squintani August, 2020 Budget Set Up to now we focused on how to represent the consumer's preferences. We shall now consider the sour note of the constraint that is imposed on such preferences. Definition (Budget Set) The consumer's budget set is: B(p; m) = fx j (p x) ≤ m; x 2 X g Francesco Squintani EC9D3 Advanced Microeconomics, Part I August, 2020 2 / 49 Budget Set (2) 6 x1 2 L = 2 X = R+ c c c c c c c c c c c c B(p; m) c c c c c c c - x2 Francesco Squintani EC9D3 Advanced Microeconomics, Part I August, 2020 3 / 49 Income and Prices The two exogenous variables that characterize the consumer's budget set are: the level of income m the vector of prices p = (p1;:::; pL). Often the budget set is characterized by a level of income represented by the value of the consumer's endowment x0 (labour supply): m = (p x0) Francesco Squintani EC9D3 Advanced Microeconomics, Part I August, 2020 4 / 49 Utility Maximization The basic consumer's problem (with rational, continuous and monotonic preferences): max u(x) fxg s:t: x 2 B(p; m) Result If p > 0 and u(·) is continuous, then the utility maximization problem has a solution. Proof: If p > 0 (i.e. pl > 0, 8l = 1;:::; L) the budget set is compact (closed, bounded) hence by Weierstrass theorem the maximization of a continuous function on a compact set has a solution. Francesco Squintani EC9D3 Advanced Microeconomics, Part I August, 2020 5 / 49 First Order Condition Result If u(·) is continuously differentiable, the solution x∗ = x(p; m) to the consumer's problem is characterized by the following necessary conditions. -
A Macroeconomic Model with Financially Constrained Producers and Intermediaries ∗
A Macroeconomic Model with Financially Constrained Producers and Intermediaries ∗ Vadim Elenev Tim Landvoigt Stijn Van Nieuwerburgh NYU Stern UT Austin NYU Stern, NBER, and CEPR October 24, 2016 Abstract We propose a model that can simultaneously capture the sharp and persistent drop in macro-economic aggregates and the sharp change in credit spreads observed in the U.S. during the Great Recession. We use the model to evaluate the quantitative effects of macro-prudential policy. The model features borrower-entrepreneurs who produce output financed with long-term debt issued by financial intermediaries and their own equity. Intermediaries fund these loans combining deposits and their own equity. Savers provide funding to banks and to the government. Both entrepreneurs and intermediaries make optimal default decisions. The government issues debt to finance budget deficits and to pay for bank bailouts. Intermediaries are subject to a regulatory capital constraint. Financial recessions, triggered by low aggregate and dispersed idiosyncratic productivity shocks result in financial crises with elevated loan defaults and occasional intermediary insolvencies. Output, balance sheet, and price reactions are substantially more severe and persistent than in non-financial recession. Policies that limit intermediary leverage redistribute wealth from producers to intermediaries and savers. The benefits of lower intermediary leverage for financial and macro-economic stability are offset by the costs from more constrained firms who produce less output. JEL: G12, -
Soft Budget Constraint Theories from Centralization to the Market1
Economics of Transition Volume 9 (1) 2001, 1–27 Soft budget constraint theories From centralization to the market1 Eric Maskin* and Chenggang Xu** *Institute for Advanced Study, Princeton and Department of Economics, Princeton University. Institute for Advanced Study, Einstein Drive, Princeton, NJ 08540, USA. Tel: + 1 609-734- 8309; E-mail: [email protected] **Department of Economics and CEP, London School of Economics, London WC2A 2AE, UK. Tel: +44 (0)207 955 7526; E-mail: [email protected] Abstract This paper surveys the theoretical literature on the effect of soft budget constraints on economies in transition from centralization to capitalism; it also reviews our understanding of soft budget constraints in general. It focuses on the conception of the soft budget constraint syndrome as a commitment problem. We show that the two features of soft budget constraints in centralized economies – ex post renegotiation of firms’ financial plans and a close administrative relationship between firms and the centre – are intrinsically related. We examine a series of theories (based on the commitment-problem approach) that explain shortage, lack of innovation in centralized economies, devolution, and banking reform in transition economies. Moreover, we argue that soft budget constraints also have an influence on major issues in economics, such as the determination of the boundaries and capital structure of a firm. Finally, we show that soft budget constraints theory sheds light on financial crises and economic growth. JEL classification: D2, D8, G2, G3, H7, L2, O3, P2, P3. Keywords: soft budget constraint, renegotiation, theory of the firm, banking and finance, transition, centralized economy. -
Econ 337901 Financial Economics
ECON 337901 FINANCIAL ECONOMICS Peter Ireland Boston College Spring 2021 These lecture notes by Peter Ireland are licensed under a Creative Commons Attribution-NonCommerical-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License. http://creativecommons.org/licenses/by-nc-sa/4.0/. 1 Mathematical and Economic Foundations A Mathematical Preliminaries 1 Unconstrained Optimization 2 Constrained Optimization B Consumer Optimization 1 Graphical Analysis 2 Algebraic Analysis 3 The Time Dimension 4 The Risk Dimension C General Equilibrium 1 Optimal Allocations 2 Equilibrium Allocations Mathematical Preliminaries Unconstrained Optimization max F (x) x Constrained Optimization max F (x) subject to c ≥ G(x) x Unconstrained Optimization To find the value of x that solves max F (x) x you can: 1. Try out every possible value of x. 2. Use calculus. Since search could take forever, let's use calculus instead. Unconstrained Optimization Theorem If x ∗ solves max F (x); x then x ∗ is a critical point of F , that is, F 0(x ∗) = 0: Unconstrained Optimization F (x) maximized at x ∗ = 5 Unconstrained Optimization F 0(x) > 0 when x < 5. F (x) can be increased by increasing x. Unconstrained Optimization F 0(x) < 0 when x > 5. F (x) can be increased by decreasing x. Unconstrained Optimization F 0(x) = 0 when x = 5. F (x) is maximized. Unconstrained Optimization Theorem If x ∗ solves max F (x); x then x ∗ is a critical point of F , that is, F 0(x ∗) = 0: Note that the same first-order necessary condition F 0(x ∗) = 0 also characterizes a value of x ∗ that minimizes F (x). -
Lecture 4 - Utility Maximization
Lecture 4 - Utility Maximization David Autor, MIT and NBER 1 1 Roadmap: Theory of consumer choice This figure shows you each of the building blocks of consumer theory that we’ll explore in the next few lectures. This entire apparatus stands entirely on the five axioms of consumer theory that we laid out in Lecture Note 3. It is an amazing edifice, when you think about it. 2 Utility maximization subject to budget constraint Ingredients • Utility function (preferences) • Budget constraint • Price vector Consumer’s problem • Maximize utility subject to budget constraint. 2 • Characteristics of solution: – Budget exhaustion (non-satiation) – For most solutions: psychic trade-off = market trade-off – Psychic trade-off is MRS – Market trade-off is the price ratio • From a visual point of view utility maximization corresponds to point A in the diagram below – The slope of the budget set is equal to − px py – The slope of each indifference curve is given by the MRS at that point • We can see that A P B, A I D, C P A. Why might we expect someone to choose A? 3 2.1 Interior and corner solutions There are two types of solution to this problem, interior solutions and corner solutions • The figure below depicts an interior solution • The next figure depicts a corner solution. In this specific example the shape of the indifference curves means that the consumer is indifferent to the consumption of good y. Utility increases only with consumption of x. Thus, the consumer purchases x exclusively. 4 • In the following figure, the consumer’s preference for y is sufficiently strong relative to x that the the psychic trade-off is always lower than the monetary trade-off. -
Theoretical Tools of Public Finance
Theoretical Tools of Public Finance 131 Undergraduate Public Economics Emmanuel Saez UC Berkeley 1 THEORETICAL AND EMPIRICAL TOOLS Theoretical tools: The set of tools designed to understand the mechanics behind economic decision making. Empirical tools: The set of tools designed to analyze data and answer questions raised by theoretical analysis. 2 CONSTRAINED UTILITY MAXIMIZATION Economists model individuals' choices using the concepts of utility function maximization subject to budget constraint. Utility function: A mathematical function representing an individual's set of preferences, which translates her well-being from different consumption bundles into units that can be compared in order to determine choice. Constrained utility maximization: The process of maximiz- ing the well-being (utility) of an individual, subject to her re- sources (budget constraint). 3 UTILITY MAPPING OF PREFERENCES Indifference function: A utility function is some mathemat- ical representation: U = u(X1;X2;X3; :::) where X1;X2;X3; and so on are the goods consumed by the individual and u(:; :; :::) is some mathematical function that describes how the consumption of those goods translates to utility p Example with two goods: u(X1;X2) = X1 · X2 with X1 num- ber of movies, X2 number of music songs Individual utility increases with the level of consumption of each good 4 PREFERENCES AND INDIFFERENCE CURVES Indifference curve: A graphical representation of all bundles of goods that make an individual equally well off. Because these bundles have equal utility, an individual is indifferent as to which bundle he consumes Mathematically, indifference curve giving utility level U¯ is given by the set of bundles (X1;X2) such that u(X1;X2) = U¯ Indifference curves have two essential properties, both of which follow naturally from the more-is-better assumption: 1. -
Senior Secondary Course ECONOMICS (318)
Senior Secondary Course ECONOMICS (318) 2 Course Coordinator Dr. Manish Chugh fo|k/kue~ loZ/kua iz/kkue~ NATIONAL INSTITUTE OF OPEN SCHOOLING (An Autonomous Institution under MHRD, Govt. of India) A-24-25, Institutional Area, Sector-62, NOIDA-201309 (U.P.) Website: www.nios.ac.in, Toll Free No. 18001809393 Printed on 60 GSM Paper with NIOS Watermark. © National Institute of Open Schooling May, 2015 (,000 Copies) Published by the Secretary, National Institute of Open Schooling, A-24-25, Institutional Area, Sector-62, Noida and printed at M/s #1PGQHHUGV Printers, 5/3, Kirti Nagar, Industrial Area, New Delhi. ADVISORY COMMITTEE Prof. C.B. Sharma Dr. Kuldeep Agarwal Dr. Rachna Bhatia Chairman Director (Academic) Assistant Director (Academic) NIOS, NOIDA (UP) NIOS, NOIDA (UP) NIOS, NOIDA (UP) CURRICULUM COMMITTEE Dr. O.P. Agarwal Sh. J. Khuntia Dr. Padma Suresh (Former Director of the Eco. Deptt.) Associate Professor (Economics) Associate Professor (Economics) NREC College, Meerut University School of Open Learning Sri Venkateshwara College Khurja (UP) Delhi University, Delhi Delhi University, Delhi Prof. Renu Jatana Sh. H.K. Gupta Sh. A.S. Garg Associate Professor, MLSU, Rtd.PGT, From NCT Rtd.Vice Principal, From NCT Udaipur (Rajasthan) New Delhi. New Delhi. Sh. Ramesh Chandra Dr.Manish Chugh Retd. Reader (Economics) Academic Officer (Economics), NCERT, Delhi. NIOS, NOIDA LESSON WRITERS Sh. J. Khuntia Dr. Anupama Rajput Ms.Sapna Chugh Associate Professor (Eco.), Associate Professor, PGT (Economics) School of Open Learning, Janki Devi Memorial College S.V. Public School, Jaipur Univ. of Delhi Univ. of Delhi Dr. Bhawna Rajput Sh. A.S. Garg Dr. -
Mathematical Economics
Mathematical Economics Dr Wioletta Nowak, room 205 C [email protected] http://prawo.uni.wroc.pl/user/12141/students-resources Syllabus Mathematical Theory of Demand Utility Maximization Problem Expenditure Minimization Problem Mathematical Theory of Production Profit Maximization Problem Cost Minimization Problem General Equilibrium Theory Neoclassical Growth Models Models of Endogenous Growth Theory Dynamic Optimization Syllabus Mathematical Theory of Demand • Budget Constraint • Consumer Preferences • Utility Function • Utility Maximization Problem • Optimal Choice • Properties of Demand Function • Indirect Utility Function and its Properties • Roy’s Identity Syllabus Mathematical Theory of Demand • Expenditure Minimization Problem • Expenditure Function and its Properties • Shephard's Lemma • Properties of Hicksian Demand Function • The Compensated Law of Demand • Relationship between Utility Maximization and Expenditure Minimization Problem Syllabus Mathematical Theory of Production • Production Functions and Their Properties • Perfectly Competitive Firms • Profit Function and Profit Maximization Problem • Properties of Input Demand and Output Supply Syllabus Mathematical Theory of Production • Cost Minimization Problem • Definition and Properties of Conditional Factor Demand and Cost Function • Profit Maximization with Cost Function • Long and Short Run Equilibrium • Total Costs, Average Costs, Marginal Costs, Long-run Costs, Short-run Costs, Cost Curves, Long-run and Short-run Cost Curves Syllabus Mathematical Theory of Production Monopoly Oligopoly • Cournot Equilibrium • Quantity Leadership – Slackelberg Model Syllabus General Equilibrium Theory • Exchange • Market Equilibrium Syllabus Neoclassical Growth Model • The Solow Growth Model • Introduction to Dynamic Optimization • The Ramsey-Cass-Koopmans Growth Model Models of Endogenous Growth Theory Convergence to the Balance Growth Path Recommended Reading • Chiang A.C., Wainwright K., Fundamental Methods of Mathematical Economics, McGraw-Hill/Irwin, Boston, Mass., (4th edition) 2005.