Cobb-Douglas Production Function

Similar documents
19 : Theory of Production

Note on growth and growth accounting

The Aggregate Production Function Revised: January 9, 2008

Productioin OVERVIEW. WSG5 7/7/03 4:35 PM Page 63. Copyright 2003 by Academic Press. All rights of reproduction in any form reserved.

Monopoly and Monopsony Labor Market Behavior

The Cobb-Douglas Production Function

Sample Midterm Solutions

8. Average product reaches a maximum when labor equals A) 100 B) 200 C) 300 D) 400

Multi-variable Calculus and Optimization

1 Calculus of Several Variables

5.1 Radical Notation and Rational Exponents

Constrained optimization.

Real Roots of Univariate Polynomials with Real Coefficients

c 2008 Je rey A. Miron We have described the constraints that a consumer faces, i.e., discussed the budget constraint.

This unit will lay the groundwork for later units where the students will extend this knowledge to quadratic and exponential functions.

Section 3-7. Marginal Analysis in Business and Economics. Marginal Cost, Revenue, and Profit. 202 Chapter 3 The Derivative

MA Macroeconomics 10. Growth Accounting

0.8 Rational Expressions and Equations

Q = ak L + bk L. 2. The properties of a short-run cubic production function ( Q = AL + BL )

Lecture Notes on Elasticity of Substitution

Microeconomics Sept. 16, 2010 NOTES ON CALCULUS AND UTILITY FUNCTIONS

1 Error in Euler s Method

Chapter 4 Online Appendix: The Mathematics of Utility Functions

John Kennan University of Wisconsin-Madison October, 1998

Linear and quadratic Taylor polynomials for functions of several variables.

Increasing for all. Convex for all. ( ) Increasing for all (remember that the log function is only defined for ). ( ) Concave for all.

Keynesian Macroeconomic Theory

Long-Run Average Cost. Econ 410: Micro Theory. Long-Run Average Cost. Long-Run Average Cost. Economies of Scale & Scope Minimizing Cost Mathematically

Partial Fractions. Combining fractions over a common denominator is a familiar operation from algebra:

3.1. RATIONAL EXPRESSIONS

Walrasian Demand. u(x) where B(p, w) = {x R n + : p x w}.

Algebra. Exponents. Absolute Value. Simplify each of the following as much as possible. 2x y x + y y. xxx 3. x x x xx x. 1. Evaluate 5 and 123

3.2. Solving quadratic equations. Introduction. Prerequisites. Learning Outcomes. Learning Style

y = a + bx Chapter 10: Horngren 13e The Dependent Variable: The cost that is being predicted The Independent Variable: The cost driver

IT Productivity and Aggregation using Income Accounting

Concepts in Investments Risks and Returns (Relevant to PBE Paper II Management Accounting and Finance)

DERIVATIVES AS MATRICES; CHAIN RULE

1 National Income and Product Accounts

SECTION 10-2 Mathematical Induction

General Framework for an Iterative Solution of Ax b. Jacobi s Method

Microeconomic Theory: Basic Math Concepts

mod 10 = mod 10 = 49 mod 10 = 9.

Maximizing volume given a surface area constraint

Lecture Notes on MONEY, BANKING, AND FINANCIAL MARKETS. Peter N. Ireland Department of Economics Boston College.

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS

CORRELATED TO THE SOUTH CAROLINA COLLEGE AND CAREER-READY FOUNDATIONS IN ALGEBRA

TRADE AND INVESTMENT IN THE NATIONAL ACCOUNTS This text accompanies the material covered in class.

Mechanics 1: Conservation of Energy and Momentum

Vieta s Formulas and the Identity Theorem

Session 9 Case 3: Utilizing Available Software Statistical Analysis

Basic Proof Techniques

5 Numerical Differentiation

DIVISIBILITY AND GREATEST COMMON DIVISORS

AK 4 SLUTSKY COMPENSATION

Name: Date: 3. Variables that a model tries to explain are called: A. endogenous. B. exogenous. C. market clearing. D. fixed.

A Statistical Analysis of the Prices of. Personalised Number Plates in Britain

db, dbm, dbw db 10 log (x) where x is unitless! For example, amplifier gain is a unitless value!

Profit Maximization. PowerPoint Slides prepared by: Andreea CHIRITESCU Eastern Illinois University

An Introduction to Calculus. Jackie Nicholas

Preparation course MSc Business&Econonomics: Economic Growth

Common sense, and the model that we have used, suggest that an increase in p means a decrease in demand, but this is not the only possibility.

Schooling, Political Participation, and the Economy. (Online Supplementary Appendix: Not for Publication)

Continuous Compounding and Discounting

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m

This is a square root. The number under the radical is 9. (An asterisk * means multiply.)

Econometrics Simple Linear Regression

CHAPTER 7 Economic Growth I

Technology, Production, and Costs

Student Outcomes. Lesson Notes. Classwork. Discussion (10 minutes)

Computational Geometry Lab: FEM BASIS FUNCTIONS FOR A TETRAHEDRON

Chapter 31 out of 37 from Discrete Mathematics for Neophytes: Number Theory, Probability, Algorithms, and Other Stuff by J. M.

Example: Boats and Manatees

Basic numerical skills: EQUATIONS AND HOW TO SOLVE THEM. x + 5 = = (2-2) = = 5. x = 7-5. x + 0 = 20.

Definition and Properties of the Production Function: Lecture

Overview of Violations of the Basic Assumptions in the Classical Normal Linear Regression Model

Product Mix as a Framing Exercise: The Role of Cost Allocation. Anil Arya The Ohio State University. Jonathan Glover Carnegie Mellon University

Overview. Essential Questions. Precalculus, Quarter 4, Unit 4.5 Build Arithmetic and Geometric Sequences and Series

Employment and Pricing of Inputs

More Quadratic Equations

REVIEW OF ANALYTIC GEOMETRY

Chapter 7 - Roots, Radicals, and Complex Numbers

Microeconomics Topic 3: Understand how various factors shift supply or demand and understand the consequences for equilibrium price and quantity.

Lecture 2. Marginal Functions, Average Functions, Elasticity, the Marginal Principle, and Constrained Optimization

INTRODUCTION THE LABOR MARKET LABOR SUPPLY INCOME VS. LEISURE THE SUPPLY OF LABOR

Linear Equations. Find the domain and the range of the following set. {(4,5), (7,8), (-1,3), (3,3), (2,-3)}

SOCIAL AND NONMARKET BENEFITS FROM EDUCATION IN AN ADVANCED ECONOMY

Technology and Economic Growth

Deriving Demand Functions - Examples 1

Section 1.5 Linear Models

This means there are two equilibrium solutions 0 and K. dx = rx(1 x). x(1 x) dt = r

Macroeconomics Lecture 1: The Solow Growth Model

DIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents

PART A: For each worker, determine that worker's marginal product of labor.

INTRODUCTION AGGREGATE DEMAND MACRO EQUILIBRIUM MACRO EQUILIBRIUM THE DESIRED ADJUSTMENT THE DESIRED ADJUSTMENT

Simplifying Square-Root Radicals Containing Perfect Square Factors

NIKE Case Study Solutions

Representation of functions as power series

Elasticity. I. What is Elasticity?

CHAPTER 4 Consumer Choice

Transcription:

Cobb-Douglas Production Function Bao Hong, Tan November 20, 2008 1 Introduction In economics, the Cobb-Douglas functional form of production functions is widely used to represent the relationship of an output to inputs. It was proposed by Knut Wicksell (1851-1926), and tested against statistical evidence by Charles Cobb and Paul Douglas in 1928. In 1928 Charles Cobb and Paul Douglas published a study in which they modeled the growth of the American economy during the period 1899-1922. They considered a simplified view of the economy in which production output is determined by the amount of labor involved and the amount of capital invested. While there are many other factors affecting economic performance, their model proved to be remarkably accurate. Figure 1: A two-input Cobb-Douglas production function The function they used to model production was of the form: where: P (L, K) = bl α K β P = total production (the monetary value of all goods produced in a year) L = labor input (the total number of person-hours worked in a year) K = capital input (the monetary worth of all machinery, equipment, and buildings) b = total factor productivity α and β are the output elasticities of labor and capital, respectively. These values are constants determined by available technology. 1

Output elasticity measures the responsiveness of output to a change in levels of either labor or capital used in production, ceteris paribus. For example if α = 0.15, a 1% increase in labor would lead to approximately a 0.15% increase in output. Further, if: α + β = 1, the production function has constant returns to scale. That is, if L and K are each increased by 20%, then P increases by 20%. Returns to scale refers to a technical property of production that examines changes in output subsequent to a proportional change in all inputs (where all inputs increase by a constant factor). If output increases by that same proportional change then there are constant returns to scale (CRTS), sometimes referred to simply as returns to scale. If output increases by less than that proportional change, there are decreasing returns to scale (DRS). If output increases by more than that proportion, there are increasing returns to scale (IRS) However, if α + β < 1, returns to scale are decreasing, and if α + β > 1, returns to scale are increasing. Assuming perfect competition, α and β can be shown to be labor and capital s share of output. 2

2 Discovery This section will discuss the discovery of the production formula and how partial derivatives are used in the Cobb-Douglas model. 2.1 Assumptions Made If the production function is denoted by P = P (L, K), then the partial derivative P is the L rate at which production changes with respect to the amount of labor. Economists call it the marginal production with respect to labor or the marginal productivity of labor. Likewise, the partial derivative P is the rate of change of production with respect to capital and is called the K marginal productivity of capital. In these terms, the assumptions made by Cobb and Douglas can be stated as follows: 1. If either labor or capital vanishes, then so will production. 2. The marginal productivity of labor is proportional to the amount of production per unit of labor. 3. The marginal productivity of capital is proportional to the amount of production per unit of capital. 2.2 Solving Because the production per unit of labor is P, assumption 2 says that L P L = αp L for some constant α. If we keep K constant(k = K 0 ), then this partial differential equation becomes an ordinary differential equation: dp dl = αp L This separable differential equation can be solved by re-arranging the terms and integrating both sides: 1 1 P dp = α L dl ln(p ) = α ln(cl) ln(p ) = ln(cl α ) 3

And finally, P (L, K 0 ) = C 1 (K 0 )L α (1) where C 1 (K 0 ) is the constant of integration and we write it as a function of K 0 since it could depend on the value of K 0. Similarly, assumption 3 says that P K = β P K Keeping L constant(l = L 0 ), this differential equation can be solved to get: And finally, combining equations (1) and (2): where b is a constant that is independent of both L and K. Assumption 1 shows that α > 0 and β > 0. P (L 0, K) = C 2 (L 0 )K β (2) P (L, K) = bl α K β (3) Notice from equation (3) that if labor and capital are both increased by a factor m, then P (ml, mk) = b(ml) α (mk) β = m α+β bl α K β = m α+β P (L, K) If α + β = 1, then P (ml, mk) = mp (L, K), which means that production is also increased by a factor of m, as discussed earlier in Section 1. 4

3 Usage This section will demonstrate the usage of the production formula using real world data. 3.1 An Example Year 1899 1900 1901 1902 1903 1904 1905... 1917 1918 1919 1920 P 100 101 112 122 124 122 143... 227 223 218 231 L 100 105 110 117 122 121 125... 198 201 196 194 K 100 107 114 122 131 138 149... 335 366 387 407 Table 1: Economic data of the American economy during the period 1899-1920 not shown for the sake of brevity [1]. Portions Using the economic data published by the government, Cobb and Douglas took the year 1899 as a baseline, and P, L, and K for 1899 were each assigned the value 100. The values for other years were expressed as percentages of the 1899 figures. The result is Table 1. Next, Cobb and Douglas used the method of least squares to fit the data of Table 1 to the function: P (L, K) = 1.01(L 0.75 )(K 0.25 ) (4) For example, if the values for the years 1904 and 1920 were plugged in: P (121, 138) = 1.01(121 0.75 )(138 0.25 ) 126.3 P (194, 407) = 1.01(194 0.75 )(407 0.25 ) 235.8 which are quite close to the actual values, 122 and 231 respectively. The production function P (L, K) = bl α K β has subsequently been used in many settings, ranging from individual firms to global economic questions. It has become known as the Cobb-Douglas production function. Its domain is {(L, K) : L 0, K 0} because L and K represent labor and capital and are therefore never negative. 3.2 Difficulties Even though the equation (4) derived earlier works for the period 1899-1922, there are currently various concerns over its accuracy in different industries and time periods. Cobb and Douglas were influenced by statistical evidence that appeared to show that labor and capital shares of total output were constant over time in developed countries; they explained this 5

by statistical fitting least-squares regression of their production function. However, there is now doubt over whether constancy over time exists. Neither Cobb nor Douglas provided any theoretical reason why the coefficients α and β should be constant over time or be the same between sectors of the economy. Remember that the nature of the machinery and other capital goods (the K) differs between time-periods and according to what is being produced. So do the skills of labor (the L). The Cobb-Douglas production function was not developed on the basis of any knowledge of engineering, technology, or management of the production process. It was instead developed because it had attractive mathematical characteristics, such as diminishing marginal returns to either factor of production. Crucially, there are no microfoundations for it. In the modern era, economists have insisted that the micro-logic of any larger-scale process should be explained. The C-D production function fails this test. For example, consider the example of two sectors which have the exactly same Cobb-Douglas technologies: if, for sector 1, P 1 = b(l α 1 )(K β 1 ) and, for sector 2, P 2 = b(l α 2 )(K β 2 ), that, in general, does not imply that P 1 + P 2 = b(l 1 + L 2 ) α (K 1 + K 2 ) β This holds only if L 1 L 2 = K 1 K 2 and α + β = 1, i.e. for constant returns to scale technology. It is thus a mathematical mistake to assume that just because the Cobb-Douglas function applies at the micro-level, it also applies at the macro-level. Similarly, there is no reason that a macro Cobb-Douglas applies at the disaggregated level. 6

This entire article was adapted from the following resources: References [1] James Stewart, Calculus: Early Transcendentals. Thomson Brooks/Cole, 6th Edition, 2008, Pages 857 and 887 [2] Wikipedia, Cobb-Douglas. http://en.wikipedia.org/wiki/cobb douglas 7