The Political Economy of Structural Change and Progressive Income Distribution

LAC-EU ECONOMIC FORUM 2013Globalization, International Trade and the Welfare State at

Crossroads:Converging Views in European and Latam countries?

Santiago, ECLAC, January 2013

Luis BértolaUniversidad de la República, Uruguay

ECLAC consultant

Content

1. Productivity, structural heterogeneity and income distribution.

2. Productivity distribution among world citizens (structural heterogeneity).

3. Functional distribution and productivity: what is left behind the cycles?

4. Different dimensions of inequality5. The Robin Hood paradox revisitedFinal remarks: The distinctive case of the political

economy of natural resource-intensive economies

1. Productivity, structural heterogeneity and income distribution: main arguments

• High income inequality in Latin America is deeply rooted in its heterogeneous productive structure.

• Other institutional features, as the weak State and unequal distribution of economic, social and political power, add to inequality in factoral distribution.

• The role of natural resources in capital building, concentration of property and generation of rents is crucial to understand the heterogeneous productive structure and the patterns of income distribution.

• The role of natural resources is also crucial to understand the extreme volatility of the Latin American economy and the challenges imposed to policy-making and sustainable growth.

• The scarce diversification of the productive structure, adds to power relations, in limiting income growth and the expansion of the public sector and the welfare state.

• Structural differences with Europe are clearly noticeable.

2. Productivity distribution among world citizens (global structural heterogeneity)

A classical topic at ECLAC since Anibal PintoIntegrating cross-section and convergence-

divergence approaches.- 32 countries- 7 groups(AL, Asia, Scandinavia, Eurolatin, Settlers,

Europe Core, USA, (and also All Europe).- 9 productive sectors: GDP at current dollars,

employment, labour productivity.- Years: 1991, 1996, 2001, 2006.

Basic dataTable 1.Pop share, GDP share, average and relative productivity by sector, 1991

Sector % Population % GDP ProductivityRelative

productivityAGRICULTURE, HUNTING, FORESTRY AND FISHING 1 0.091 0.027 10163 0.3

MINING AND QUARRYING 2 0.005 0.014 91420 2.6

MANUFACTURING 3 0.186 0.205 38177 1.1ELECTRICITY GAS AND, WATER SUPPLY 4 0.008 0.027 116217 3.4

CONSTRUCTION 5 0.069 0.061 30605 0.9WHOLESALE AND RETAIL TRADE - RESTAURANTS AND HOTELS 6 0.208 0.153 25469 0.7TRANSPORT, STORAGE AND COMMUNICATIONS 7 0.056 0.073 44877 1.3FINANCE, INSURANCE, REAL ESTATE AND BUSINESS SERVICES 8 0.094 0.189 69498 2.0COMMUNITY, SOCIAL AND PERSONAL SERVICES 9 0.283 0.250 30524 0.9

“Global” inequality in productivity, 1991-2006

• A slight increase in inequality during these 15 years.

Table 2. "Global" inequality in productivity, 1991-1996GE(0) GE(1) Gini

1991 0.4026 0.2721 0.3881996 0.3842 0.2798 0.3982001 0.4508 0.3207 0.4212006 0.4404 0.3197 0.417

Inequality by sectors

• Inequality within sectors is a proxy for inequality between countries, given that each observation corresponds to one particular country and that each country has only one obervation per sector.

• Inequality increases both within and between sectors (countries), but is higher within sectors (between countries). Inequality, at a global level, is mainly within sectors (i.e., international, between countries).

• However, the dynamic force is between-sector inequality, which also poses the problem of specialization.

Table 3: Within- and between-sector inequalityGE(0) BY SECTORS 1991 1996 2001 2006within sectors 0.299 0.282 0.321 0.305between sectors 0.104 0.102 0.129 0.136total 0.403 0.384 0.451 0.440

within sectors % 0.742 0.734 0.713 0.692between sectors % 0.258 0.266 0.287 0.308

Which sectors are more heterogeneous?Table 4. Global Ginis by sector

1991 1996 2001 2006 Average % Changes

AGRICULTURE, HUNTING, FORESTRY AND FISHING 1 0.564 0.545 0.585 0.580 0.568 0.017

MINING AND QUARRYING 2 0.385 0.414 0.449 0.420 0.417 0.035ELECTRICITY GAS AND, WATER SUPPLY 4 0.359 0.344 0.361 0.305 0.342 -0.054

WHOLESALE AND RETAIL TRADE - RESTAURANTS AND HOTELS 6 0.282 0.323 0.358 0.333 0.324 0.051MANUFACTURING 3 0.287 0.294 0.334 0.326 0.310 0.040CONSTRUCTION 5 0.307 0.266 0.310 0.297 0.295 -0.011

COMMUNITY, SOCIAL AND PERSONAL SERVICES 9 0.285 0.300 0.263 0.254 0.276 -0.031

TRANSPORT, STORAGE AND COMMUNICATIONS 7 0.255 0.265 0.289 0.282 0.273 0.027FINANCE, INSURANCE, REAL ESTATE AND BUSINESS SERVICES 8 0.209 0.249 0.255 0.241 0.239 0.032

Inequality by country groups

• Inequality is slightly higher between groups than within, a feature that is reinforced during these years.

Table 5: Inequality between- and within groupsGE(0) BY GROUPSwithin groups 0.175 0.158 0.193 0.182between groups 0.228 0.227 0.258 0.259total 0.403 0.384 0.451 0.440

within groups % 0.435 0.410 0.429 0.413between groups % 0.565 0.590 0.571 0.587

Which groups are more heterogeneous?

• Latin America is the more heterogeneous group…• … and the more volatile one!!!!!!!! (even in comparison to Europe, with

more countries 13-10, and higher pop. share, 30-26%).

Table 6. Structural heterogeneity by groupsGroup/Gini 1991 1996 2001 20061. AMLAT (Ar, Br, Ch, Col, CR, Ecu, Mex, Pe, Uy, Ven) 0.455 0.406 0.478 0.4482. CORE EUROPE (Alem, Fr, UK, Bel, Holanda, Suiza) 0.168 0.191 0.158 0.1803. ASIA (Korea, Japón) 0.318 0.314 0.332 0.2814. SCAN (Din, Fin, Nor, Suecia) 0.198 0.220 0.234 0.2595. LATPER (Esp., It., Port) 0.229 0.218 0.217 0.2096. SETTLERS (Aust, Can, NZ) 0.269 0.278 0.286 0.2867.USA 0.211 0.211 0.221 0.2338. ALL EUROPE (2, 4 and 5) 0.188 0.208 0.188 0.203Group/ precentual changes 1991-96 1996-2001 2011-061. AMLAT (Ar, Br, Ch, Col, CR, Ecu, Mex, Pe, Uy, Ven) -4.8 7.1 -3.02. CORE EUROPE (Alem, Fr, UK, Bel, Holanda, Suiza) 2.3 -3.3 2.23. ASIA (Korea, Japón) -0.4 1.8 -5.14. SCAN (Din, Fin, Nor, Suecia) 2.2 1.4 2.55. LATPER (Esp., It., Port) -1.1 -0.1 -0.86. SETTLERS (Aust, Can, NZ) 0.9 0.8 0.07.USA 0.0 1.0 1.28. ALL EUROPE (2, 4 and 5) 2.0 -2.0 1.5

Latin America:Inequality by sectors

Table 7. Lat America , basic data 1991 1996 2001 2006

sector Popn. shareIncome share Popn. share Income share Popn. share

Income share Popn. share

Income share

AGRICULTURE, HUNTING, FORESTRY AND FISHING0.20 0.07 0.18 0.07 0.17 0.05 0.17 0.05MINING AND QUARRYING 0.01 0.05 0.01 0.04 0.01 0.05 0.01 0.09MANUFACTURING 0.17 0.20 0.16 0.20 0.15 0.19 0.14 0.18ELECTRICITY GAS AND, WATER SUPPLY 0.01 0.02 0.01 0.02 0.01 0.02 0.00 0.03CONSTRUCTION 0.06 0.05 0.06 0.06 0.06 0.06 0.07 0.06WHOLESALE AND RETAIL TRADE - RESTAURANTS AND HOTELS0.19 0.16 0.21 0.15 0.24 0.15 0.24 0.15TRANSPORT, STORAGE AND COMMUNICATIONS0.05 0.07 0.05 0.07 0.05 0.10 0.06 0.09FINANCE, INSURANCE, REAL ESTATE AND BUSINESS SERVICES0.06 0.20 0.06 0.14 0.06 0.15 0.07 0.13COMMUNITY, SOCIAL AND PERSONAL SERVICES0.25 0.18 0.26 0.24 0.25 0.22 0.25 0.21

Table 8. Gini by sectors 1991 1996 2001 2006AGRICULTURE, HUNTING, FORESTRY AND FISHING0.343 0.222 0.294 0.255MINING AND QUARRYING 0.436 0.465 0.517 0.449MANUFACTURING 0.289 0.182 0.272 0.186ELECTRICITY GAS AND, WATER SUPPLY 0.217 0.137 0.140 0.214CONSTRUCTION 0.245 0.134 0.274 0.169WHOLESALE AND RETAIL TRADE - RESTAURANTS AND HOTELS0.307 0.251 0.334 0.242TRANSPORT, STORAGE AND COMMUNICATIONS0.382 0.259 0.357 0.309FINANCE, INSURANCE, REAL ESTATE AND BUSINESS SERVICES0.277 0.525 0.619 0.582COMMUNITY, SOCIAL AND PERSONAL SERVICES0.193 0.244 0.189 0.176

• The dominating and increasing inequality-source is between-sector inequality (i.e., within countries).

Table 9: Latin America: inequality between- and within-sectors, 1991-2006G(0) bySectors 1991 1996 2001 2006within sectors 0.158 0.141 0.306 0.145between sectors 0.212 0.147 0.224 0.220total 0.370 0.287 0.529 0.365

within sectors % 0.428 0.490 0.577 0.397between sectors % 0.572 0.510 0.423 0.603

• Inequality in productivity within Latin America is not mainly arising from differences between countries, but within them.

• This confirms Latin America as the one with hihest heterogeneity and volatility.

Table 10. Latin America: inequality between- and within countries, 1991-2006G(0) by countries 1991 1996 2001 2006within countries 0.271 0.234 0.232 0.279between countries 0.100 0.053 0.171 0.086total 0.370 0.287 0.403 0.365within countries 0.731 0.814 0.575 0.764between countries 0.269 0.186 0.425 0.236

Structural heterogeneity by country(Gini-coefficient for productivity)

1991 1996 2001 2006 PromedioCRI 0.277 0.244 0.224 0.205 0.238ARG 0.279 0.276 0.291 0.308 0.289URY 0.311 0.310 0.335 0.302 0.314BRA 0.353 0.290 0.338 0.355 0.334PER 0.393 0.288 0.266 0.464 0.353COL 0.371 0.334 0.352 0.378 0.359ECU 0.394 0.374 0.322 0.417 0.377CHL 0.405 0.372 0.396 0.452 0.406MEX 0.467 0.478 0.402 0.404 0.438VEN 0.408 0.478 0.399 0.475 0.440

Structural heterogeneity and income distribution are highly correlated: Norway,

Venezuela are outliers

ARG

AUTDEU

BEL

BRA

CHE

CHL

COL

CRIDEN

ECU

ESP

FINFRA

GRCIRL

ITA

JPN

KOR

MEX

NLD

NORPER

SLV

SWE

URY

USA

VEN

y = 0,5811x + 0,0799R² = 0,4361

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0,45

0,50

0,55

0,20 0,25 0,30 0,35 0,40 0,45 0,50 0,55 0,60 0,65

Prod

ucti

ve G

ini c

oeffi

cien

t (2

000

-200

8)

Income Gini coefficient (2000-2010)

Source: Astorga, R. (ECLAC)

3. Functional distribution and productivity: what is left after the cycles?

0

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Total wealth per capita

Capital per capita by kind: seven regions, 2005 (dollars)

Intangible

Producido

Natural

América Latina

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25%

1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

% o

f GD

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Rents of natural resources as a share of per capita GDP, 1970-2010 Argentina

Brazil

Chile

Colombia

Latin America & Caribbean (all income levels)Mexico

Minerals

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1908

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Uruguay: share of landowner´s rents in agrarian and total GDP, 1908-1966

% agrarian GDP % total GDP

Agriculture

0

50

100

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350

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450

500

1902

1906

1910

1914

1918

1922

1926

1930

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1966

1970

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1982

1986

1990

1994

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2010

Uruguay: Precio real de la tierra (defactado por IPC) y estimación de la renta (1913=100)

Precio de la tierra corregido por productividad Precio de la tierra

Uruguay: real land prices (deflated by CPI) and productivity adjusted real land price, 1913=100

- LABOUR SHARES ARE LOW IN LATIN AMERICA AND TENDED TO DECREASE IN 1990-2009- AS LABOUR PRODUCTIVITY INCREASES, LABOUR SHARES ARE REDUCED (ECLAC, 2012, BOX V.2)

LABOUR SHARES (AT CONSTANT FACTOR COSTS), 1990-2009

The dynamics of the functional distribution of income

• The role of the rents of natural resources• Control of natural resources• Distribution of rents• Sustainability vs. volatility• The political economy of structural change

and relative price movements

4: Different dimensions of inequality: the Human Development Equality Index

Year Southern Cone Core Australia-New ZealandLatin Europe Scandinavia Japan1900 0,559 0,4031910 0,606 0,3961920 0,576 0,653 0,490 0,5281930 0,641 0,711 0,548 0,5621940 0,682 0,726 0,567 0,6701950 0,344 0,755 0,689 0,587 0,767 0,6521960 0,369 0,768 0,785 0,661 0,830 0,7391970 0,361 0,789 0,803 0,727 0,867 0,7241980 0,408 0,794 0,836 0,752 0,890 0,8081990 0,428 0,768 0,798 0,794 0,887 0,7972000 0,419 0,777 0,773

5. Per capita GDP and Public Expenditure, 2001-2007.

• The 1rst Robin Hood Paradox: those countries that need more public expenditure are those that collect less taxes in relation to GDP and thus have a less than proportional per capita public expenditure.

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0 5000 10000 15000 20000 25000 30000 35000

%

Gasto/PIB

PIB per capita 2001-2007 (dólares PPP de 1990)

Gasto público y PIB per capita, 32 países, 2001-2007

The Second Robin Hood Paradox: the lower the per capita income, the lower the impact of social expenditure on the reduction of inequality

Source: Lindert, P.

• The Third Robin Hood Paradox: social expedniture not always help reducing inequality.

Final remarks:The distinctive political economy of natural

resource-intensive economies• Unless capital investment and human capital investment creates

conditions for innovation and a drastic and persistent change in the productive structure, sustained per capita GDP convergence will not take place and the welfare state will not be sustainable.

• Inequality will not signifcantly decrease, as a consequence of persistent structural heterogeneity, and because of the persistence of forces recreating inequality.

• The great problem is that this process cannot take place without the simultaneous creation of a welfare state.

• The key is an integrated approach to industrial policy, innovation, structural change and social policy.

• The risk is the combination of cycles of optimism with redistribution without structural change.