Inequality, Unemployment and the Chimera of Labour Market Reform A - - PowerPoint PPT Presentation

Inequality, Unemployment and the Chimera of Labour Market Reform

A Presentation to the

Treasury

Wellington, New Zealand September 29, 2005

by James K. Galbraith

The University of Texas Inequality Project

http://utip.gov.utexas.edu

Based on an article, “Inequality, Unemployment and the Policy of Europe, 1984-2000 co-authored with Enrique Garcilazo published in Banca Nazionale del Lavoro Quarterly Review

• No. 228, March 2004

The Standard View

• Employment is determined in a labour

market.

• Labour markets are primarily national.
• National institutions matter.
• Flexibility reduces unemployment.
• The United States has more jobs than

Europe, but only at the expense of more inequality.

• But… is this actually true?

“Data! Data! Data! I can’t make bricks without clay.”

Sherlock Holmes The Adventure of the Copper Beeches

In this case, we need a data set that permits to assess whether variations in unemployment are primarily due to local, national or international factors.

European Regional Panel Data Set

• Pay across Sectors by European Region
• From Eurostat’s REGIO
• Annual 1984-2000, up to 159 Regions
• Enables us to compute measures of

inequality within and between regions.

• Permits construction of a panel with which

we can isolate regional, national and continental effects

A Simple Theory of European Unemployment at the Regional Level

• Demand Factors:

– GDP Growth (-) (Investment & Construction) – Relative Wealth (-) (Demand for Services; Reflects EU Integration)

• Supply Factors:

– Youth Population Share (+) (Transition to work) – Inequalities of Pay (+) (Rehn-Meidner; Harris-Todaro)

Plus: Country and Time Fixed Effects, Capturing Country-specific Institutions and Common International Factors, respectively.

We use Theil’s T statistic, measured across sectors, and sometimes across provinces or regions as well, to show the evolution of economic inequality. The components of the statistic provide a measure of the contribution of each “province-sector cell” to inequality. This measure takes account both of the relative income of the cell and its size in relation to the whole employed population. The method permits us to map changes in the flow of incomes across regions and across sectors very accurately through time, without relying on sample surveys.

General Technique for Computing Inequality Measures

T p R R p R T T n r r

j j j m j j j m j j j j i i g i

j

= + = ⎧ ⎨ ⎪ ⎪ ⎩ ⎪ ⎪

= = ∈

∑ ∑ ∑

1 1

1 log log

p n n

j j

=

A brief review of the Theil Statistic:

n ~ employment; ~ average income; j ~ subscript denoting group

The The “ “Between Between-

• Groups Component

Groups Component” ”

Rj

j

= μ

μ

μ

Im p

• v

e ris h e d F a r B e lo w A v e ra ge B e lo w A v e ra g e L

• w

lo w N e utra l L

• w

N e u tra l N e u tra l H ig h N e u tra l A b

• v

e A v e ra g e P ro s p e ro u s W e a lth y

Contribution of European Provinces to Inequality Across the European continent, late 1990s.

Contribution of European Provinces to Inequality Across the European continent, late 1990s.

Total Male Female < 25 Yrs > 25 Yrs Beta Pvalue Beta Pvalue Beta Pvalue Beta Pvalue Beta Pvalue Theil 4.969 0.039 3.221 0.126 6.805 0.039 11.967 0.032 4.081 0.042 PopUn24 57.019 0.000 50.581 0.000 76.462 0.000 112.319 0.000 38.037 0.000 RelWage

• 7.085

0.000

• 4.951

0.000

• 9.907

0.000

• 6.371

0.004

• 7.434

0.000 G-GDP

• 4.485

0.025

• 5.670

0.001

• 2.347

0.393

• 6.299

0.175

• 4.687

0.005 R^2 0.6140 0.5869 0.6535 0.6172 0.5831 N 1465 1465 1465 1465 1465 Beta Pvalue Beta Pvalue Beta Pvalue Beta Pvalue Theil

4.027 0.180 4.808 0.039 5.393 0.087 4.969 0.039

PopUn24

50.205 0.000 48.640 0.000 54.227 0.000 57.019 0.000

RelWage

• 2.816

0.000

• 6.809

0.000

• 2.210

0.002

• 7.085

0.000

G-GDP

• 11.830

0.000

• 8.561

0.000

• 9.494

0.001

• 4.485

0.025

Regional

X X X X

Country

X X

Time

X X

R^2

0.1644 0.5702 0.2057 0.6140

Table 2. Coefficient Estimates: Linear Model - (1984-2000).

Table 3. Analysis of Variance Explained Under Different Specifications.

Regression analysis of European unemployment

(Two-way fixed effects panel)

All Workers

• 11 - -5
• 4
• 3 - 3

4 - 5

Emigration? Centralized wage bargains? Country Fixed Effects Show the Differences Between Countries Not Explained by the Explanatory Variables.

These May Interpreted as “Labour Market Institutions”

Few major differences separate the large countries

Table A7. Ratio of Austrian to German Average Wages, by Major Sectors

1995 1996 1997 1998 1999 2000 Mining and quarrying 1.04 1.01 1.01 1.06 1.09 0.98 Manufacturing 0.88 0.88 0.88 0.89 0.92 0.86 Electricity, gas and water supply 1.22 1.19 1.21 1.26 1.22 1.14 Construction 1.04 1.03 1.06 1.11 1.27 1.20 Transport, storage and communication 1.03 1.00 1.03 1.07 1.18 1.14 Financial intermediation 1.06 1.07 1.08 1.09 1.23 1.18 Real estate, renting and business activities 0.99 0.96 0.94 0.90 1.09 0.95 Public administration and defence; compulsory social security 1.16 1.15 1.13 1.10 1.12 1.12

The Inflexibility Advantage: Austria’s centralized wage bargains permit them to discount labour in traded goods, and import full employment from Germany. (Ditto Ireland and the UK).

Table A8. Ratio of Irish to British Average Wages, by Major Sectors

1995 1996 1997 1998 Mining and quarrying 0.71 1.05 0.86 0.87 Manufacturing 0.81 0.84 0.75 0.71 Electricity, gas and water supply 0.74 0.65 0.70 0.63 Construction 1.32 1.27 1.17 1.11 Wholesale and retail trade,* 1.35 1.39 1.32 1.29 Hotels and restaurants 1.15 1.05 0.97 0.90 Transport, storage and communication 0.79 0.87 0.76 0.70 Financial intermediation 1.51 1.49 1.20 1.11 Real estate, renting and business activities 1.19 1.13 1.07 1.02 Public administration and defence,** 1.08 1.17 1.11 1.18 Education 1.27 1.30 1.17 1.10 Health and social work 1.52 1.48 1.39 1.22 Other community, social, personal service activities 0.97 0.90 0.66 0.57

* repair of motor vehicles, motorcycles and personal and household goods **compulsory social security

Ireland has a similar relationship to the UK, not quite so effectively done…

Total Male Female <25 Yrs >25 Yrs BE 1.540

• 0.353

5.164

• 2.436

2.298 DE 3.315 4.115 2.965

• 7.587

3.926 GR

• 5.200
• 5.123
• 3.640

1.450

• 6.821

ES 5.036 3.704 8.960 9.707 2.859 IE

• 9.695
• 6.479
• 14.570
• 24.117
• 7.472

IT 0.528

• 0.235

3.460 9.279

• 1.692

NL

• 3.694
• 3.162
• 4.031
• 12.998
• 2.790

AT

• 6.030
• 4.896
• 7.053
• 17.094
• 5.118

PT

• 10.786
• 8.246
• 13.855
• 16.812
• 10.432

FI 0.904 3.257

• 1.974

3.300 0.423 SE

• 1.059

1.882

• 4.414
• 3.699
• 0.948

UK

• 4.095
• 0.281
• 9.089
• 12.636
• 3.496

European Effects

• 8
• 6
• 4
• 2

2 4 6 8

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Years Unemployment Total Male Female <25 Yrs >25 Yrs

Single European Act Maastricht Treaty Birth of the Euro Growth and Stability pact

Time Fixed Effects Show the Common Movements of Unemployment Across All Regions: This is the Macroeconomic Dimension!

The U.S. Case

In the U.S. Case, it is necessary to distinguish between income inequality, which rose sharply in the 1990s, and inequalities of pay which did not.

Income inequality in the United States, 1969-2000 Three Measures

.02 .025 .03 .035 .04 .045 Inequality per capita personal income btw-county 34 36 38 40 42 44 Gini coefficient 1970 1980 1990 2000 year... EHII 2.2 D&S Inequality per capita personal income btw-county

Pay Inequality in the U.S.

• We have measured inequalities of pay (weekly earnings)

in the manufacturing sector on a monthly basis going back to January, 1947, for sectors that are continuously measured since that time. The result gives us a time series of pay inequalities in a key part of the American industrial economy. It ignores income from capital and pay in the high-tech sector, which are almost entirely responsible for rising income inequality in the U.S. in the late 1990s. It is reasonably similar to the patterns in service pay, which encompass more workers but are harder to measure.

JFK LBJ NIXON FORD CARTER REAGAN BUSH CLINTON

Wage Inequality and Some Historical Events

TRUMAN EISENHOWER

Korean War Recession Vietnam War Recession Recession Recession Recession

Wage Inequality and Unemployment

Open Unemployment Rate

Did the U.S. reach full employment by increasing pay gaps? No, it did not.

The U.S and Europe

• Is the U.S really more unequal than

Europe?

• First, let’s compare U.S. income inequality

to that in each European country.

• Then, let’s compare U.S. pay inequality to

that in Europe-as-a-whole.

EHII -- Estimated Household Income Inequality for OECD Countries Gini coefficient SWE DNK FIN NOR AUS ISL NZL CAN JPN IRL PRT GBR LUX DEU NLD FRA AUT BEL ITA USA ESP GRC 25 30 35 40 45

1963 1963 1963 1963 1963 1963 1963 1963 1963 1977 1968 1963 1963 1963 1963 1967 1963 1963 1963 1963 1963 1963 1999 1999 1998 1994 1999 1994 1998 1999 1997 1998 1996 1999 1996 1992 1999 1998 1999 1999 1998 1999 1989 1999

Low High

0.01 0.02 0.03 0.04 0.05 Theil Value 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 Within Country Between Countries

Inequality in Europe

Manufacturing Earnings

The average value for the U.S. on this scale is about 0.029, or roughly the height of the blue bar. Overall European manufacturing pay inequality –including differences between countries – was higher than in the US through the early 1990s at least. Now, is pay inequality in Europe really lower than in the U.S.? Not when you count the between-country component!

US Average

100 200 300 400 500

63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95

Australia New Zealand

Australia and New Zealand

30 32 34 36 38 40 42 44

Gini Coefficient

1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999

Australia New Zealand

Estimated Income Inequality

Australia, New Zealand,---

30 32 34 36 38 40 42 44

Gini Coefficient

1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999

Australia New Zealand United States

Estimated Income Inequality

Australia, New Zealand, US

Conclusions

• Labour markets are not national; unemployment depends on regional,

national and international conditions.

• Demand conditions matter.
• Equality of pay helps. Despite deeply rooted belief, there is no evidence

that pay flexibility reduces unemployment.

• Institutional differences between large countries have been overrated.
• Small countries with centralized wage bargains have been able to

prosper and enjoy low unemployment by importing traded goods employment from their larger neighbours. (New Zealand, take note.)

• The view of the U.S. as a flexible, high inequality labour market, as

compared to Europe, is an optical illusion. It is based on the “national view” of labour market phenomena. This view is plainly obsolete in today’s integrated European economy, and it is probably obsolete in the world economy as a whole.

• The urgently needed reform is not in labour markets … but in the

economics of labour markets.

For more information: The University of Texas Inequality Project

http://utip.gov.utexas.edu

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