Decomposing Value Added Growth Over Sectors into Explanatory Factors

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

Decompositions of Productivity Growth into Sectoral Effects

The general Solow model

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

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

The Brock-Mirman Stochastic Growth Model

GMM - Generalized Method of Moments

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

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

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

Problem Set #3: AK models

Final Exam. Tuesday, December hours

Unemployment and Mismatch in the UK

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

Reserves measures have an economic component eg. what could be extracted at current prices?

Exponential Smoothing

Problem Set on Differential Equations

Macroeconomics I, UPF Professor Antonio Ciccone SOLUTIONS PROBLEM SET 1

Solutions Problem Set 3 Macro II (14.452)

Intermediate Macro In-Class Problems

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation

Problem Set #1 - Answers

A Specification Test for Linear Dynamic Stochastic General Equilibrium Models

Economics 8105 Macroeconomic Theory Recitation 6

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

1. Consider a pure-exchange economy with stochastic endowments. The state of the economy

ANSWERS TO EVEN NUMBERED EXERCISES IN CHAPTER 6 SECTION 6.1: LIFE CYCLE CONSUMPTION AND WEALTH T 1. . Let ct. ) is a strictly concave function of c

Math 333 Problem Set #2 Solution 14 February 2003

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.

Solutions to Odd Number Exercises in Chapter 6

Lecture 20: Riccati Equations and Least Squares Feedback Control

The Brock-Mirman Stochastic Growth Model

Seminar 4: Hotelling 2

Math 10B: Mock Mid II. April 13, 2016

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

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

Some Basic Information about M-S-D Systems

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

OBJECTIVES OF TIME SERIES ANALYSIS

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

COMPETITIVE GROWTH MODEL

(a) Set up the least squares estimation procedure for this problem, which will consist in minimizing the sum of squared residuals. 2 t.

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 Dynamic Model of Economic Fluctuations

Why is Chinese Provincial Output Diverging? Joakim Westerlund, University of Gothenburg David Edgerton, Lund University Sonja Opper, Lund University

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

Distribution of Estimates

The Aggregate Implications of Innovative Investment in the Garcia-Macia, Hsieh, and Klenow Model (preliminary and incomplete)

An introduction to the theory of SDDP algorithm

) were both constant and we brought them from under the integral.

Estimation Uncertainty

State-Space Models. Initialization, Estimation and Smoothing of the Kalman Filter

Final Exam Advanced Macroeconomics I

Final Spring 2007

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

Chapter 11. Heteroskedasticity The Nature of Heteroskedasticity. In Chapter 3 we introduced the linear model (11.1.1)

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

Robust estimation based on the first- and third-moment restrictions of the power transformation model

Economic Growth & Development: Part 4 Vertical Innovation Models. By Kiminori Matsuyama. Updated on , 11:01:54 AM

The Returns to Scale Effect in Labour Productivity Growth

1 Answers to Final Exam, ECN 200E, Spring

5.1 - Logarithms and Their Properties

Summer Term Albert-Ludwigs-Universität Freiburg Empirische Forschung und Okonometrie. Time Series Analysis

Online Appendix to Solution Methods for Models with Rare Disasters

15.023J / J / ESD.128J Global Climate Change: Economics, Science, and Policy Spring 2008

Estimation of Investment in Residential and Nonresidential Structures v2.0

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux

Estimation of R&D Depreciation Rates: A Suggested Methodology and Preliminary Application

PENALIZED LEAST SQUARES AND PENALIZED LIKELIHOOD

Introduction to choice over time

Lecture 5. Time series: ECM. Bernardina Algieri Department Economics, Statistics and Finance

SHADOW PRICE APPROACH TO PRODUCTIVITY MEASUREMENT

Math 334 Fall 2011 Homework 11 Solutions

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

Announcements: Warm-up Exercise:

The Multiple Regression Model: Hypothesis Tests and the Use of Nonsample Information

Modal identification of structures from roving input data by means of maximum likelihood estimation of the state space model

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Errata (1 st Edition)

Lecture 19. RBC and Sunspot Equilibria

Vectorautoregressive Model and Cointegration Analysis. Time Series Analysis Dr. Sevtap Kestel 1

Lecture Notes 5: Investment

Regression with Time Series Data

Unit Root Time Series. Univariate random walk

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

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

AJAE Appendix for: Induced Innovation In U.S. Agriculture: Time-series, Direct Econometric, and Nonparametric Tests. Yucan Liu. C.

Time series Decomposition method

Distribution of Least Squares

Appendix 14.1 The optimal control problem and its solution using

Cosumnes River College Principles of Macroeconomics Problem Set 1 Due January 30, 2017

20. Applications of the Genetic-Drift Model

5.2. The Natural Logarithm. Solution

Vehicle Arrival Models : Headway

STATE-SPACE MODELLING. A mass balance across the tank gives:

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

72 Calculus and Structures

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

Solutions to Assignment 1

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

Transcription:

Business School Decomposing Value Added Growh Over Secors ino Explanaory Facors W. Erwin Diewer (UBC and UNSW Ausralia) and Kevin J. Fox (UNSW Ausralia) EMG Workshop UNSW 2 December 2016

Summary Decompose nominal value added growh over muliple secors ino explanaory facors. For a single secor, explanaory facors are efficiency changes, changes in oupu prices, changes in primary inpus, changes in inpu prices, echnical progress, and reurns o scale.

Summary Need secor s bes pracice echnology for he wo periods under consideraion. Could use economeric or nonparameric (DEA) echniques We use Free Disposal Hull approach no convexiy assumpions Our approach has he advanage ha i does no involve economeric esimaion, and involves only observable daa. Simple enough o be implemened by saisical agencies If efficien in boh periods, can use he index number echniques of Diewer-Morrison (1986)/Kohli (1990). Address he problem of aggregaing over secors.

Cos Consrained Value Added Funcion for a Secor A secor produces M ne oupus, y [y 1,...,y M ], using N primary inpus x [x 1,...,x N ] 0 N. If y m > 0, hen he secor produces he mh ne oupu during period while if y m < 0, hen he secor uses he mh ne oupu as an inermediae inpu. Sricly posiive vecor of ne oupu prices p [p 1,...,p M ] >> 0 M and sricly posiive vecor of inpu prices w [w 1,...,w N ] >> 0 N Period producion possibiliies se for he secor S

Cos Consrained Value Added Funcion for a Secor S saisfies he following regulariy condiions: (i) S is a closed se; (ii) for every x 0 N, (0 M,x) S ; (iii) if (y,x) S and y * y, hen (y *,x) S (free disposabiliy of ne oupus); (iv) if (y,x) S and x * x, hen (y,x * ) S (free disposabiliy of primary inpus); (v) if x 0 N and (y,x) S, hen y b(x) where he upper bounding vecor b can depend on x (bounded primary inpus implies bounded from above ne oupus).

Cos Consrained Value Added Funcion for a Secor Period cos consrained value added funcion: R (p,w,x) max y,z {p y : (y,z) S ; w z w x} R (p,w,x) is well defined even if here are increasing reurns o scale in producion; i.e., he consrain w z w x leads o a finie value for R (p,w,x). If (y *,z * ) solves his consrained maximizaion problem, hen secoral value added p y is maximized subjec o he consrains ha (y,z) is a feasible producion vecor and primary inpu expendiure w z is equal o or less han observed primary inpu expendiure w x.

Cos Consrained Value Added Funcion for a Secor Observed value added, p y, may no equal he opimal value added. Value added efficiency of he secor during period : e p y /R (p,w,x ) 1 The cos consrained valued added funcion has some ineresing properies. If S is a cone, so ha producion is subjec o consan reurns o scale, can show ha R (p,w,x) w x/c (w,p) where c (w,p) is he uni cos funcion for producing a uni of value added.

Decomposing Value Added Growh for a Secor ino Explanaory Facors Change in value added efficiency ε e /e 1 = [p y /R (p,w,x )]/[p 1 y 1 /R 1 (p 1,w 1,x 1 )] If ε > 1, hen value added efficiency has improved going from period 1 o whereas i has fallen if ε < 1.

Decomposing Value Added Growh for a Secor ino Explanaory Facors Follow mehod of Konüs (1939) and Allen (1949) o define various families of indexes ha vary only one of he four ses of variables,, p, w and x, beween he wo periods under consideraion and hold consan he oher ses of variables. Family of oupu price indexes: α(p 1,p,w,x,s) R s (p,w,x)/r s (p 1,w,x). Two alernaives: α L α(p 1,p,w 1,x 1, 1) R 1 (p,w 1,x 1 )/R 1 (p 1,w 1,x 1 ) ; α P α(p 1,p,w,x,) R (p,w,x )/R (p 1,w,x ). Preferred overall measure of oupu price growh: α [α L α P ] 1/2

Decomposing Value Added Growh for a Secor ino Explanaory Facors Family of inpu quaniy indexes: β(x 1,x,w) w x /w x 1. β L w 1 x /w 1 x 1 ; β P w x /w x 1. Preferred overall measure of inpu quaniy growh: β [β L β P ] 1/2.

Decomposing Value Added Growh for a Secor ino Explanaory Facors Family of inpu mix indexes: γ(w 1,w,p,x,s) R s (p,w,x)/r s (p,w 1,x) More accurae o say ha γ(w 1,w,p,x,s) represens he hypoheical proporional change in cos consrained value added for he period s reference echnology due o he effecs of a change in he inpu price vecor from w 1 o w when facing he reference ne oupu prices p and he reference vecor of inpus x. γ LPP γ(w 1,w,p 1,x,) R (p 1,w,x )/R (p 1,w 1,x ); γ PLL γ(w 1,w,p,x 1, 1) R 1 (p,w,x 1 )/R 1 (p,w 1,x 1 ). γ [γ LPP γ PLL ] 1/2.

Decomposing Value Added Growh for a Secor ino Explanaory Facors Family of echnical progress indexes: τ( 1,,p,w,x) R (p,w,x)/r 1 (p,w,x) τ L τ( 1,,p 1,w 1,x ) R (p 1,w 1,x )/R 1 (p 1,w 1,x ). τ P τ( 1,,p,w,x 1 ) R (p,w,x 1 )/R 1 (p,w,x 1 ). Recall, if he reference echnologies in periods and 1 are cones, R (p,w,x) = w x/c (w,p) and R 1 (p,w,x) = w x/c 1 (w,p). Thus in he case where he reference echnology is subjec o CRS, hese mixed indexes of echnical progress are independen of x and hen rue Laspeyres and Paasche ype indexes.

Decomposing Value Added Growh for a Secor ino Explanaory Facors Family of (global) reurns o scale measures: δ(x 1,x,p,w,s) [R s (p,w,x )/R s (p,w,x 1 )]/[w x /w x 1 ]. δ L δ(x 1,x,p 1,w 1, 1) R 1 (p 1,w 1,x )/R 1 (p 1,w 1,x 1 )]/[w 1 x /w 1 x 1 ]; δ P δ(x 1,x,p,w,) [R (p,w,x )/R (p,w,x 1 )]/[w x /w x 1 ]. δ [δ L δ P ] 1/2

Decomposing Value Added Growh for a Secor ino Explanaory Facors Six explanaory growh facors: 1. Change in cos consrained value added efficiency: ε e /e 1 2. Change in oupu prices: α(p 1,p,w,x,s) 3. Change in inpu quaniies: β(x 1,x,w) 4. Change in inpu prices: γ(w 1,w,p,x,s) 5. Changes due o echnical progress: τ( 1,,p,w,x) 6. Reurns o scale measure: δ(x 1,x,p,w,s)

Decomposing Value Added Growh for a Secor ino Explanaory Facors Exac decomposiions of observed value added: p y /p 1 y 1 = ε α P β L γ LPP δ L τ L ; p y /p 1 y 1 = ε α L β P γ PLL δ P τ P. Take he geomeric mean of boh sides of he above equaions o ge our preferred decomposiion: p y /p 1 y 1 = ε α β γ δ τ. Can re-organise o ge: TFPG {[p y /p 1 y 1 ]/α }/β = ε γ δ τ

A Nonparameric Approximaion o he Cos Consrained Value Added Funcion Assume ha he producion uni s period producion possibiliies se S is he conical free disposal hull of he period acual producion vecor and pas producion vecors. LP problem: R (p,w,x) max λ {p (Σ s=1 y s λ s ) ; w (Σ s=1 x s λ s ) w x ; λ 1 0,..., λ 0} = max s {p y s w x/w x s : s = 1,2,...,} = w x max s {p y s /w x s : s = 1,2,...,} = w x/min s {w x s /p y s : s = 1,2,...,} = w x/c (w,p) where c (w,p) is he period nonparameric uni cos funcion

Naional Value Added Growh Decomposiions: The Secoral Weighed Average Approach Secoral value added decomposiion, for each secor k: v k /v k, 1 = α k β k γ k δ k ε k τ k Period share of naional value added for secor k: s k v k /v Can use period -1 or period shares o aggregae: v /v 1 = Σ k=1 K s k, 1 α k β k γ k δ k ε k τ k v /v 1 = [Σ k=1 K s k (α k β k γ k δ k ε k τ k ) 1 ] 1

Naional Value Added Growh Decomposiions: The Secoral Weighed Average Approach Nice! Bu hese exac decomposiions don lead o simple decomposiions ino naional explanaory facors. Define (logarihms of) weighed naional explanaory facors: ln α Σ K k=1 (1/2)(s k + s k, 1 )ln α k ; ln β Σ K k=1 (1/2)(s k + s k, 1 )ln β k ; ln γ Σ K k=1 (1/2)(s k + s k, 1 )ln γ k ; ln δ Σ K k=1 (1/2)(s k + s k, 1 )ln δ k ; ln ε Σ K k=1 (1/2)(s k + s k, 1 )ln ε k ; ln τ Σ K k=1 (1/2)(s k + s k, 1 )ln τ k.

Naional Value Added Growh Decomposiions: The Secoral Weighed Average Approach Use some approximaions (drawing on Schlömilch s inequaliy) o wrie: ln v /v 1 Σ k=1 K (1/2)(s k + s k, 1 )ln(v k /v k, 1 ) = Σ k=1 K (1/2)(s k + s k, 1 )ln(α k β k γ k δ k ε k τ k ) = ln α + ln β + ln γ + ln δ + ln ε + ln τ Naional Toal Facor Produciviy Growh: TFPG [v /v 1 ]/α β γ δ ε τ

Naional Value Added Growh Decomposiions: The Secoral Weighed Average Approach Assume ha he echnology of each secor can be represened by a ranslog value added funcion wih he resricions on echnical progress ha are described in Diewer and Morrison (1986) and Kohli (1990). These papers also assumed consan reurns o scale and compeiive profi maximizing behavior. Under hese assumpions: v k /v k, 1 = α k β k τ k where α k urns ou o be he period Törnqvis value added oupu price index for secor k and β k is he period Törnqvis primary inpu quaniy index for secor k. v /v 1 α β τ ; Can be implemened using index numbers; i.e. no necessary o have esimaes for secoral bes pracice funcions.

Naional Value Added Growh Decomposiions: The Secoral Weighed Average Approach This is a boom up approach; sar a he secor level and aggregae up o he naional level. No clear ha he correc definiion of naional TFPG [v /v 1 ]/α β is correc. Now look a a op down approach.

Naional Value Added Growh Decomposiions: The Naional Cos Consrained Value Added Funcion Approach Secor k share of naional bes pracice value added in period : σ k R k (p k,w k,x k )/R (p,w,x ) Naional efficiency Level: e v /R (p,w,x ) = Σ K k=1 σ k e k Naional efficiency change: ε e /e 1 = [Σ K k=1 σ k e k ]/[Σ K k=1 σ k, 1 e k, 1 ]

Naional Value Added Growh Decomposiions: The Naional Cos Consrained Value Added Funcion Approach Using a similar approach for oher componens, and similar definiions as for he explanaory componens as before, we ge he following exac decomposiion of naional value added growh: v /v 1 = α β γ δ ε τ Can derive approximaions o all six naional explanaory facors, so ha we ge: v /v 1 = α β γ δ ε τ α β γ δ ε τ Which is he same decomposiion ha we had for he boom up approach.

TFP Growh for he U.S. Corporae Nonfinancial Secor, 1960-2014 Use he (BEA, BLS, Fed Reserve) Inegraed Macroeconomic Accouns o consruc a daa se for wo major secors of he U.S. economy in Diewer and Fox (2016) : Alernaive User Coss, Raes of Reurn and TFP Growh Raes for he US Nonfinancial Corporae and Noncorporae Business Secors: 1960-2014 Secor 1: US Corporae Nonfinancial Secor Secor 2: US Noncorporae Nonfinancial Secor

TFP Growh for he U.S. Corporae Nonfinancial Secor, 1960-2014 There was a subsanial decline in value added efficiency over he years 2006-2009 TFP has grown a a slower han average rae since 2006. The level of TFP also fell in he 1974, 1979, 1982, 1989 and 2001 recessions when efficiency growh dipped below one. On he whole, TFP growh in he U.S. Corporae Nonfinancial Secor has been saisfacory.

TFP Growh for he U.S. Noncorporae Nonfinancial Secor, 1960-2014 The loss of value added efficiency in Secor 2 was massive over he 20 years 1974-1993. This loss of efficiency dragged down he level of Secor 2 TFP over hese years. TFP growh resumed in 1994 and was excellen unil 2006 when TFP growh again salled wih he excepion of wo good years of growh in 2011 and 2012. Illusraes he adverse influence of recessions when oupu falls bu inpus canno be adjused opimally due o he fixiy of many capial sock (and labour) componens of aggregae inpu. Under hese circumsances, producion akes place in he inerior of he producion possibiliies se and for Secor 2, he resuling wase of resources was subsanial.

Summary Derived decomposiions of nominal value added growh (and TFP growh) for a single secor ino explanaory facors. We also used wo alernaive approaches o relaing he secoral decomposiions o a naional growh decomposiion: a weighed average secoral approach and a naional value added funcion approach. A main advanage of our new approach is ha our new nonparameric measure of echnical progress never indicaes echnical regress. During recessions, value added efficiency drops below uniy and depresses TFP growh.

Summary For our U.S. daa se, TFP growh is well explained as he produc of value added efficiency growh imes he rae of echnical progress. For he U.S. Noncorporae Nonfinancial Secor, we found ha he cos of recessions was paricularly high. Implemenaion of he decomposiions can provide key insighs ino he drivers of economic growh a a deailed secoral level. Hence, we believe ha hey will provide new insighs ino he sources of economic growh. Our decomposiions may also indicae daa mismeasuremen problems ha can hen be addressed by saisical agencies.