Explaining Total Factor Productivity. Ulrich Kohli University of Geneva December 2015

Similar documents
On Measuring Pro-Poor Growth. 1. On Various Ways of Measuring Pro-Poor Growth: A Short Review of the Literature

The general Solow model

Problem Set 5. Graduate Macro II, Spring 2017 The University of Notre Dame Professor Sims

( ) (, ) F K L = F, Y K N N N N. 8. Economic growth 8.1. Production function: Capital as production factor

Macroeconomics I, UPF Professor Antonio Ciccone SOLUTIONS PROBLEM SET 1

Final Exam Advanced Macroeconomics I

Problem Set #1 - Answers

Decomposing Value Added Growth Over Sectors into Explanatory Factors

Problem Set #3: AK models

The Brock-Mirman Stochastic Growth Model

Vehicle Arrival Models : Headway

Intermediate Macro In-Class Problems

The Simple Linear Regression Model: Reporting the Results and Choosing the Functional Form

Lecture 3: Solow Model II Handout

Inventory Analysis and Management. Multi-Period Stochastic Models: Optimality of (s, S) Policy for K-Convex Objective Functions

Final Exam. Tuesday, December hours

Biol. 356 Lab 8. Mortality, Recruitment, and Migration Rates

T. J. HOLMES AND T. J. KEHOE INTERNATIONAL TRADE AND PAYMENTS THEORY FALL 2011 EXAMINATION

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux

Chapter 7: Solving Trig Equations

Decompositions of Productivity Growth into Sectoral Effects

72 Calculus and Structures

EXERCISES FOR SECTION 1.5

5.1 - Logarithms and Their Properties

Seminar 4: Hotelling 2

E β t log (C t ) + M t M t 1. = Y t + B t 1 P t. B t 0 (3) v t = P tc t M t Question 1. Find the FOC s for an optimum in the agent s problem.

A First Course on Kinetics and Reaction Engineering. Class 19 on Unit 18

Suggested Solutions to Assignment 4 (REQUIRED) Submisson Deadline and Location: March 27 in Class

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

KINEMATICS IN ONE DIMENSION

Unit Root Time Series. Univariate random walk

A Dynamic Model of Economic Fluctuations

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities:

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3

Bias in Conditional and Unconditional Fixed Effects Logit Estimation: a Correction * Tom Coupé

ACE 562 Fall Lecture 5: The Simple Linear Regression Model: Sampling Properties of the Least Squares Estimators. by Professor Scott H.

Macroeconomic Theory Ph.D. Qualifying Examination Fall 2005 ANSWER EACH PART IN A SEPARATE BLUE BOOK. PART ONE: ANSWER IN BOOK 1 WEIGHT 1/3

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

Math 333 Problem Set #2 Solution 14 February 2003

Time series Decomposition method

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

Solutions to Odd Number Exercises in Chapter 6

4.1 - Logarithms and Their Properties

Solutions Problem Set 3 Macro II (14.452)

WEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x

Lecture Notes 3: Quantitative Analysis in DSGE Models: New Keynesian Model

= ( ) ) or a system of differential equations with continuous parametrization (T = R

Let us start with a two dimensional case. We consider a vector ( x,

SOLUTIONS TO ECE 3084

1 Review of Zero-Sum Games

13.3 Term structure models

Introduction D P. r = constant discount rate, g = Gordon Model (1962): constant dividend growth rate.

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum

Final Spring 2007

Lecture Notes 5: Investment

1 Answers to Final Exam, ECN 200E, Spring

ACE 562 Fall Lecture 8: The Simple Linear Regression Model: R 2, Reporting the Results and Prediction. by Professor Scott H.

Financial Econometrics Jeffrey R. Russell Midterm Winter 2009 SOLUTIONS

Sterilization D Values

Module 2 F c i k c s la l w a s o s f dif di fusi s o i n

Linear Response Theory: The connection between QFT and experiments

Errata (1 st Edition)

Matlab and Python programming: how to get started

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Chapter 2. First Order Scalar Equations

Econ107 Applied Econometrics Topic 7: Multicollinearity (Studenmund, Chapter 8)

( ) a system of differential equations with continuous parametrization ( T = R + These look like, respectively:

HOMEWORK # 2: MATH 211, SPRING Note: This is the last solution set where I will describe the MATLAB I used to make my pictures.

Solutions to Exercises in Chapter 12

Essential Microeconomics : OPTIMAL CONTROL 1. Consider the following class of optimization problems

Notes 8B Day 1 Doubling Time

20. Applications of the Genetic-Drift Model

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality

Maintenance Models. Prof. Robert C. Leachman IEOR 130, Methods of Manufacturing Improvement Spring, 2011

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 17

Online Appendix to Solution Methods for Models with Rare Disasters

Some Basic Information about M-S-D Systems

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4.

Linear Time-invariant systems, Convolution, and Cross-correlation

Lecture Notes 2. The Hilbert Space Approach to Time Series

STA 114: Statistics. Notes 2. Statistical Models and the Likelihood Function

1 Consumption and Risky Assets

Problem 1 / 25 Problem 2 / 20 Problem 3 / 10 Problem 4 / 15 Problem 5 / 30 TOTAL / 100

MONOPOLISTIC COMPETITION IN A DSGE MODEL: PART II OCTOBER 4, 2011 BUILDING THE EQUILIBRIUM. p = 1. Dixit-Stiglitz Model

Introduction to AC Power, RMS RMS. ECE 2210 AC Power p1. Use RMS in power calculations. AC Power P =? DC Power P =. V I = R =. I 2 R. V p.

ACE 562 Fall Lecture 4: Simple Linear Regression Model: Specification and Estimation. by Professor Scott H. Irwin

Introduction to choice over time

18 Biological models with discrete time

Phys1112: DC and RC circuits

Appendix 14.1 The optimal control problem and its solution using

The Real Exchange Rate, Real Interest Rates, and the Risk Premium. Charles Engel University of Wisconsin

Cash Flow Valuation Mode Lin Discrete Time

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles

Cooperative Ph.D. Program in School of Economic Sciences and Finance QUALIFYING EXAMINATION IN MACROECONOMICS. August 8, :45 a.m. to 1:00 p.m.

A Note on Raising the Mandatory Retirement Age and. Its Effect on Long-run Income and Pay As You Go (PAYG) Pensions

15. Vector Valued Functions

More Digital Logic. t p output. Low-to-high and high-to-low transitions could have different t p. V in (t)

Chapter 2. Models, Censoring, and Likelihood for Failure-Time Data

Solutions from Chapter 9.1 and 9.2

Transcription:

Explaining Toal Facor Produciviy Ulrich Kohli Universiy of Geneva December 2015

Needed: A Theory of Toal Facor Produciviy Edward C. Presco (1998) 2

1. Inroducion Toal Facor Produciviy (TFP) has become he choice measure of produciviy TFP is ofen referred o as he Solow residual, and i is generally jus ha, namely a residual TFP is raher opaque as o he naure of he phenomena ha i perains o measure I is difficul o reconcile TFP wih various models of facor augmening echnological change Is echnological change neural or is i biased? If i is neural, is i neural in he sense of Hicks, Harrod, or Solow? 3

1. Inroducion, coninued Do increases in produciviy, as capured by TFP, necessarily imply increases in real wages? Wha abou he real reurn on capial, mus i necessarily increase oo? The purpose of his paper is o sor ou some of hese quesions and o show how TFP can be decomposed ino he conribuion of labor and he conribuion of capial As an illusraion, some esimaes for he Unied Saes are repored 4

2. Index Number Approach Toal facor produciviy can be defined as he par of oupu growh ha canno be explained by inpu growh Noaion: y, p quaniy and price of oupu x K,, w K, quaniy and price of capial services x L,, w L, quaniy and price of labor services 5

2. Index Number Approach, coninued A sae-of-he ar measure of TFP is given by he following index: (1) 1, 1, 1,!!! = X Y T where (2) 1 1,!! " y y Y (3)!! " # $ $ % & + + + ' ( ( ( ( ( 1,, 1,, 1,, 1,, 1, ln ) ( 2 1 )ln ( 2 1 exp L L L L K K K K x x s s x x s s X (4) j j j y p x w s,,,!, }, { L K j! 6

2. Index Number Approach, coninued Using he daa of Kohli (2010) for he Unied Saes, one finds ha TFP has averaged abou 1.09% per year over he period 1970 2001 While his is useful informaion, i ells us nohing abou he naure of echnological change, and wheher i benefied capial or labor, or boh 7

3. Producion funcion approach TFP can also be defined wih reference o a producion funcion This acually leads o for four inerpreaions of TFP 8

3. Producion funcion approach, coninued 9

3. Producion funcion approach, coninued Le µ! "ln y " be he insananeous rae of echnological change; we hen have: (8)! f (")! = µ y Following Diewer and Morrison (1986), we define he following index of TFP: (10) T,!1 " f (x K,!1, x L,!1,) f (x K,!1, x L,!1,!1) f (x K,, x L,,) f (x K,, x L,,!1) (inerpreaion 1) 10

3. Producion funcion approach, coninued Assume ha he producion funcion has he Translog form: (11) ln y " T = # + " +! 0 KT K (ln x ln x K, K, $ ln x + (1 $ " )ln x L, ) K 1 +! TT 2 2 L, + 1! 2 KK (ln x K, $ ln x L, ) 2 + The inverse inpu demand funcions: $ ln f (%) $ ln x (12) s = = " +! (ln x # ln x ) + K, K KK K, L,! KT K, $ ln f (%) $ ln x (13) s = = (1 # " ) #! (ln x # ln x ) #! L, L, K KK K, L, KT 11

3. Producion funcion approach, coninued 12

3. Producion funcion approach, coninued 13

3. Producion funcion approach, coninued TFP can hus be inerpreed in four differen ways: (1) i is he change in oupu made possible by he passage of ime, holding inpu quaniies consan (2) i is he average of he insananeous raes of echnological change of imes -1 and (3) i is he average rae of echnological change beween imes -1 and (4) i is he par of oupu growh ha canno be explained by inpu growh In he Translog case, all four inerpreaions are equivalen 14

3. Producion funcion approach, coninued Esimaes of he Translog producion funcion from Kohli (2010) are repored in Table 1, column 1 TFP compued according o (15) or equivalenly (16), (17), or (20) averaged 1.02% over he period 1970-2001 15

16

4. Impac of TFP on facor renal prices Wih he index number approach, one does no need economeric esimaes of he parameers of he producion funcion o measure TFP; ha makes i very aracive On he oher hand, his approach ells us nohing abou he naure of echnological change, or abou is impac on income shares or on he wo facor renal prices The economeric approach is more revealing in his respec The sign of φ KT is essenial in deermining he impac of he passage of ime on facor shares 17

4. Impac of TFP on facor renal prices, coninued If φ KT > 0, as i urns ou in he U.S. case, one can say ha echnological is pro-capial and ani-labor biased, in he sense ha i increases he share of capial over ime and reduces he share of labor Capial is hus favored a he expense of labor Wha abou facor renal prices, hough? Clearly, if echnological change leads o an increase in oupu, for given facor endowmens, and o an increase in he share of capial, i mus increase he real reurn o capial Bu wha abou labor? 18

4. Impac of TFP on facor renal prices, coninued 19

4. Impac of TFP on facor renal prices, coninued 20

4. Impac of TFP on facor renal prices, coninued As long as he echnology is progressing, he firs erm on he righ hand side is posiive If φ KT is posiive, echnological change is ani-labor biased I migh even be ha φ KT /s L, > µ, in which case echnological change would be ulra ani-labor biased: echnological change would hen lead o an acual fall in he wage rae even hough echnological progress would unambiguously increase average labor produciviy 21

4. Impac of TFP on facor renal prices, coninued As i urns ou for he U.S. case, φ KT /s L, < µ ; echnological case is hus ani-labor biased, bu no ulra ani-labor biased Noneheless, he rae of increase in real wages is less han he rae of growh of TFP and of average labor produciviy Over he enire sample period, real wages increased by abou 46%, wih 27% explained by echnological change, he res being explained by capial deepening Alhough he economeric approach yields much richer resuls han he index number approach, he fac remains ha i sill does no each us much abou he naure of he echnological change process, or as o why echnological change is ani-labor biased 22

5. Disembodied facor augmening echnological change 23

5. Disembodied facor augmening echnological change, coninued 24

5. Disembodied facor augmening echnological change, coninued 25

5. Disembodied facor augmening echnological change, coninued 26

5. Disembodied facor augmening echnological change, coninued 27

5. Disembodied facor augmening echnological change, coninued Esimaes of (31), based on Kohli (2010), are shown in Table 1 Technological change in he Unied Saes comes close o being Harrod neural TFP, compued on he basis of (36) or equivalenly (37), (38), or (41) averaged 1.02% per year beween 1970 and 2001 28

29

6. The decomposiion of TFP beween labor and capial 30

6. The decomposiion of TFP beween labor and capial, coninued 31

32

7. Facor augmening echnological change and TP flexibiliy 33

7. Facor augmening echnological change and TP flexibiliy, coninued 34

7. Facor augmening echnological change and TP flexibiliy, coninued 35

7. Facor augmening echnological change and TP flexibiliy, coninued 36

7. Facor augmening echnological change and TP flexibiliy, coninued 37

7. Facor augmening echnological change and TP flexibiliy, coninued 38

7. Facor augmening echnological change and TP flexibiliy, coninued 39

40

41

8. A parsimonious and ye flexible model 42

8. A parsimonious and ye flexible model, coninued 43

8. A parsimonious and ye flexible model, coninued 44

45

46

9. The impac of echnological change on facor renal prices reexamined, coninued We can now explain why echnological change is ani-labor biased in he case of he Unied Saes As shown by (22), echnological progress mus increase he real reurn of a leas one facor, bu no necessarily of boh Take he exreme case of Harrod-neural echnological progress, which is a reasonable approximaion for he Unied Saes; in ha case, echnological progress leads o an increase in he endowmen of labor measured in efficiency unis Oupu necessarily increases, and so does oupu per uni of labor (average labor produciviy) The reurn o capial mus increase as well since in he woinpu case, he wo inpus are necessarily Hicksian complemens for each oher 47

9. The impac of echnological change on facor renal prices reexamined, coninued The reurn o labor per efficiency uni mus necessarily decrease because of diminishing marginal reurns; by how much depends on he size of he elasiciy of complemenariy If capial and labor are srong Hicksian complemens, he reurn o labor per efficiency uni will fall by a large amoun, so ha he reurn o labor per observed uni may decline, even hough each uni of labor has become more efficien! 48

9. The impac of echnological change on facor renal prices reexamined, coninued 49

9. The impac of echnological change on facor renal prices reexamined, coninued 50

9. The impac of echnological change on facor renal prices reexamined, coninued 51

9. The impac of echnological change on facor renal prices reexamined, coninued Looking a he resuls for he Unied Saes, i is clear ha echnological progress leads o an increase in he reurn o capial since all hree righ-hand-side erms in (80) are posiive For labor he firs wo erms of (82) are posiive, alhough hey are close o zero given ha echnological change urns ou o be almos Harrod-neural and ha λ is numerically small; he hird erm is posiive as long as ψ KL < 1/s K, which indeed urns ou o be he case So we can conclude ha echnological progress also increases he reurn o labor in he U.S. case; noe, however, ha because he share of labor declines, he increase in real wages is less ha he increase in average labor produciviy, or of TFP for ha maer 52

9. The impac of echnological change on facor renal prices reexamined, coninued Technological change in he Unied Saes is ani-labor biased because i is mosly labor augmening, and because he Hicksian elasiciy of complemenariy beween capial and labor is greaer han one; hese wo findings ogeher explain why echnological change has a negaive impac on he share of labor This could no have been inferred from he mere finding ha φ KT is posiive: echnological change would also be ani-labor biased if i were Solow neural and if he elasiciy of complemenariy were less han one 53

10. Generalizaion o an arbirary number of inpus 54

10. Generalizaion o an arbirary number of inpus, coninued 55

10. Generalizaion o an arbirary number of inpus, coninued 56

11. Conclusions In his paper we aemped o explain TFP in erms of disembodied, facor augmening echnological change This led us o come up wih five differen inerpreaions of TFP: (1) i is he par of oupu growh ha canno be explained by inpu growh (2) i is he change in oupu made possible by he passage of ime, holding inpu quaniies consan (3) i is he average of he insananeous raes of echnological change of imes -1 and (4) i is he average rae of echnological change beween imes -1 and (5) i is a moving geomeric mean of he raes of facor efficiency augmenaion In he Translog case, all five inerpreaions are equivalen 57

11. Conclusions, coninued We have shown ha in he case of a TP-flexible Translog producion funcion TFP can always be inerpreed as he oucome of disembodied, facor augmening echnological change Indeed, we have proposed a convenien way o derive he facor-augmening raes of echnological change from he esimaes of such a Translog producion funcion We have found ha echnological change is almos Harrodneural in he case of he Unied Saes, so ha TFP is overwhelmingly explained by labor 58

11. Conclusions, coninued Furhermore, echnological change is ani-labor biased, in he sense ha i ends o decrease he income share of labor; his is due o he relaively large Hicksian elasiciy of complemenariy beween capial and labor Noneheless, echnological change has a posiive effec on he reurn of boh capial and labor, alhough he benefi o labor is less han wha TFP or average labor produciviy would sugges 59

Thank you for your aenion! 60

Growh facors 1970-2001 Quaniy of capial services: XK 2.25706 Quaniy of labor services: XL 1.70513 Price of oupu: P 3.76623 Quaniy of oupu: Y 2.52563 Price of labor services: WL 5.50201 Toal facor produciviy: T 1.37071 Capial componen of TFP: T K 1.01850 Labor componen of TFP: T L 1.34581 Capial efficiency: ΓK 1.06789 Labor efficiency: ΓL 1.50832 Labor share: SL 0.98628 Oupu per uni of labor: A Y/X! 1.48119 Real wage rae: M W! /P 1.46088 Relaive capial inensiy: X X! /X! 1.32369 Relaive efficiency facor: Γ Γ! /Γ! 0.70800 Capial inensiy in efficiency erms: K X Γ 0.93718 Approximae mean levels: Share of capial: sk 0.28 Inverse price elasiciy: εlk 0.49 * * * Decomposiion of produciviy growh 1970-2001: Average labor produciviy A = T K T L X s K = 1.48119 Capial produciviy effec (4.67%) T! = 1.01850 Labor produciviy effec (75.60%) T! = 1.34581 Capial deepening effec (19.73%) X!! 1.32369 0.28 1.08060 Marginal labor produciviy M = X ε LK Γ ε LK Γ L = 1.46088 Capial deepening effec (36.43%) X!!" 1.32369 0.49 1.14809 Relaive efficiency effec (-44.86%) Γ!!" 0.70800 0.49 0.84362 Facor augmenaion effec (108.43%) Γ L = 1.50832