International Outsourcing and the Demand for Skills Kurt Kratena WP8 EUKLEMS Consortium Meeting Brussels, 15 - 17 March, 2007

International Outsourcingand the Demand for Skills

Kurt KratenaWP8

EUKLEMS Consortium MeetingBrussels, 15 - 17 March, 2007

Motivation

• Stylized facts: • Increase in the wage gap between skilled and unskilled

workers (U.S and UK) or employment shifts (increasing unemployment of unskilled) with stable wage structures (continental EU countries)

• Increased use of inputs, e.g.:

• skilled labour

• imported materials

• Decreased use of inputs:

• Unskilled workers (in particular older workers)

Outsourcing & demand for skills

• Methodological questions (Feenstra, Hanson, 2001):

(i) single (relative) labour demand functions: Berman, Bound and Griliches, 1994; Feenstra, Hanson (1999), Amiti, Wei (2004).

(ii) system of labour demand equations derived from a flexible cost function:Morrison-Paul, Siegel, 2001; Eckholm, Hakkala 2006; Hijzen, Görg and Hine (2005)

advantage of (ii): theoretical consistency (elasticities), econometric results based on efficient estimation technique


• Methodological questions

(i) outsourcing as a “quasi fixed” factor like factor biased technical change: most studies(ii) outsourcing as a variable factor = imported intermediates: Falk, Koebel 2002; Tombazos, 1999. Measures of outsourcing:(iii) imports of intermediates from the same industry = narrow measure(iv) total imported intermediates (in EUKLEMS without energy!) = broad measureadvantage of (ii) over (i) : directly quantifying the role of prices for outsourcing (= substitution).


• Methodological approach

• Cost and factor demand functions with different skills of labour and outsourcing as imported intermediates (without energy): (i) own and cross price elasticities(ii) impact of outsourcing on costs (~ productivity)

• EU countries: Austria, Finland, Germany, Italy Sweden (geography criterion)

• Pooling across countries (not industries)


• Data issues Basic data of EUKLEMS: capital stock gross outputinputs of intermediates (values & volumes)inputs of labour (skilled/unskilled, compensation & hours)

Additional data from other sources (Eurostat or national): inputs of imported intermediates (values & volumes):(i) full use matrices for imports(ii) import price indicesInterpolation of import matrices ?


• Data issues

Additional data from other sources by countries

Italy: Statistics Italy, WIFO √Austria: Statistics Austria, WIFO √Germany: ?Finland: EUKLEMS consortium partner (?)Sweden: Eckholm, Hakkala 2006 (EUKLEMS consortium partner ?), WIFO √

Outsourcing: Methodology

• General Translog cost function with i variable factors:i = L (unskilled), H (skilled), MM (imported intermediates), MD (domestic intermediates) and capital stock (xK), gross output (Y) and deterministic trend (t), Berndt, Hesse (1986):

Y

xtppt

xYxYppY

x

pppppp

ttxppYVC

KtK

initi

KKYKi

niK

Ki

niniji

ijnii

ii

tttKYi

niiY

log/log

log2

1log

2

1loglog)/log(log

)/log()/log()/log(2

1

2

1log1)/log(loglog

22

,

2

20


• General Translog cost function: homogeneity and constant returns to scale imposedDeriving factor demand (Shephard’s Lemma):

tY

xpppppp

VC

HptH

KKHDMHMDLHLDHHHH

H log)/log()/log()/log(

tY

xpppppp

VC

LptL

KKLDMMLDHHLDLLLL

L log)/log()/log()/log(

tY

xpppppp

VC

MptM

KKMDMMLDHHMDMMMM

MM log)/log()/log()/log(


• General Translog cost function: homogeneity and constant returns to scale imposedDeriving shadow price of capital (Berndt, Hesse 1986):

System estimation (SUR) of: cost function, factor demand and shadow cost equation.

Own price elasticity:

Cross price elasticity:

tppppppY

x

VC

x

x

VC

x

VCtKDMKMDHKHDLKL

KYKY

K

KK

)/log()/log()/log(log1log

log

i

iiii

i

iii s

ss

p

x

2

log

log

i

ijji

j

iij s

ss

p

x

log

log


Impact on costs: Definition of cost equation with input coefficients wi =xi/Y :

dynamic cost equation:

with

Decomposition into: (i) substitution effects

(ii) price effects

DDMMHHLL pwpwpwpwVC

i

ii

i

i

i

ii

i

i

VC

pw

p

dp

VC

pw

w

dw

VC

dVC

ii

i sVC

pw

i

ii

i

i

VC

pw

w

dw

i

ii

i

i

VC

pw

p

dp

First empirical results (Austria)

• Import matrices for Austria: 1995 , 2000, 2001 • Interpolation of import matrices for 1988 – 2004

(similar to Eckholm, Hakkala 2006):

import destination, not constant as in Eckholm, Hakkala (2006)

• Import prices based on unit value indices at 3 digit NACE with outlier detection (relative variance of 3 digits within 2 digits industry)

ii

ijij M

M

MM


Stylized facts for Austria 1988 – 2004

1. Input coefficient of imported intermediates1988 2004

Other Mining & Quarrying 0,016 0,031Food, beverages and tobacco 0,058 0,102Textiles, leather and footwear 0,184 0,304Wood and of wood and cork 0,077 0,061

Pulp, paper, printing and publishing 0,142 0,191Coke, refined petroleum, nuclear 0,020 0,013Chemicals and pharmaceuticals 0,092 0,262

Other non-metallic mineral 0,055 0,104Basic metals and fabricated metal 0,140 0,192

Machinery nec 0,186 0,222Electrical and optical equipment 0,226 0,358

Transport equipment 0,322 0,469


Stylized facts for Austria 1988 – 2004

2. Input coefficient of unskilled labour

1988 2004

Other Mining & Quarrying 0,048 0,022Food, beverages and tobacco 0,084 0,044Textiles, leather and footwear 0,147 0,040Wood and of wood and cork 0,076 0,023

Pulp, paper, printing and publishing 0,084 0,028Coke, refined petroleum, nuclear 0,058 0,011Chemicals and pharmaceuticals 0,081 0,029

Other non-metallic mineral 0,085 0,039Basic metals and fabricated metal 0,154 0,047

Machinery nec 0,071 0,027Electrical and optical equipment 0,086 0,031

Transport equipment 0,052 0,015


• Own price elasticities of factor demand

L,L

H,H

MM

Other Mining & Quarrying -0,40 -0,26 -0,81Food, beverages and tobacco -0,09 -0,18 -0,83Textiles, leather and footwear -0,12 -0,46 -0,67Wood and of wood and cork -0,05 -1,57 -2,47

Pulp, paper, printing and publishing -0,13 -0,24 -0,70Coke, refined petroleum, nuclear -0,15 -0,30 -1,65Chemicals and pharmaceuticals -0,05 -0,25 -0,72

Other non-metallic mineral -0,41 -0,34 -1,47Basic metals and fabricated metal -0,22 -0,15 -0,98

Machinery nec -0,07 -0,27 -0,40Electrical and optical equipment -0,12 -0,06 -0,42

Transport equipment -4,16 -1,07 -0,55


• Cross price elasticities of labour

LM

LH

LD

HM

HL

HD

Other Mining & Quarrying 0,16 -0,56 0,79 0,13 -0,02 0,15Food, beverages and tobacco 0,18 -0,45 0,36 0,10 -0,23 0,32Textiles, leather and footwear 0,24 0,58 -0,71 0,12 0,24 0,10Wood and of wood and cork -0,25 2,16 -1,85 0,43 0,53 0,62

Pulp, paper, printing and publishing -0,03 0,34 -0,18 0,32 0,11 -0,18Coke, refined petroleum, nuclear -0,15 0,65 -0,34 0,32 0,16 -0,18Chemicals and pharmaceuticals 0,35 -0,86 0,56 0,28 -0,24 0,20

Other non-metallic mineral -0,05 -0,27 0,73 0,06 -0,05 0,33Basic metals and fabricated metal 0,00 -0,02 0,24 0,11 0,04 0,00

Machinery nec 0,48 0,02 -0,42 0,12 0,01 0,13Electrical and optical equipment -0,76 2,32 -1,44 -0,02 0,36 -0,28

Transport equipment 3,90 -2,25 2,51 0,82 -0,28 0,53


• Unskilled labour and imported intermediates are substitutes in 7 out of 12 manufacturing industries (especially: transport equipment, machinery, textiles)

• Skilled labour and imported intermediates are substitutes in almost all manufacturing industries (especially transport equipment, wood, pulp and paper/printing)

which skill aggregation is appropriate ? (aggegating medium skill category to high or low ?)

• Both categories of labour are complements in 5 out of 12 industries

• Domestic intermediates are rather a substitute for high skilled labour than for low skilled labour (domestic outsourcing)

Documents

International Outsourcing and the Demand for Skills Kurt Kratena WP8 EUKLEMS Consortium Meeting Brussels, 15 - 17 March, 2007