Sectorial shifts and Inequality A way to relate macroeconomic events to inequality changes Carlos Villalobos Barría (University of Goettingen) Chair of

Sectorial shifts and InequalityA way to relate macroeconomic

events to inequality changes

Carlos Villalobos Barría (University of Goettingen)

Chair of Development Economics -- University of Goettingen

Migration, Development, and Demographic Change Problems, Consequences, Solutions”

June 25 – 28, 2013, University of Antwerp, Belgium

Arnoldshain S 2013 Antwerp, Belgien – Villalobos Barría – Sectorial Shifts and Inequality


Outline

• Motivation• Research question• The decomposition methodology• Results• Conclusions



MotivationThis is a methodological paper based on the non-conclusive evidence about the

relationship between macroeconomic variables/shocks and income inequality changes (Cornia, 2012).

The opening up of the Latin American economies during the early 90s and liberalization reforms (Lopez-Calva and Lustig, 2010)

The Hurricane Mitch in 1998 – Increasing remittances (aprox. 20% of GDP in 2005)– Important aid and capital flows

Steadily appreciation of the RER after 1994A declining tradable sector until 2005 (mainly agricultural activities)



Motivation

Prof. Alan Winters:Conclusion from 1999• Trade Liberalization generally stimulates growth (through it poverty

alleviation) - Not clear in Honduras• It creates losers - it applies to the Honduran case

Honduras, a place where, until now, there is no…• Macro stability• High rates of savings and investments• A committed, credible, capable government



Motivation

But at least in education• The private sector is responsible to allocate resources

– Highly segmented educational system / schools producing agricultural workers

– Low quality education / lack of coverage (specially in rural areas)– Strong evidence of labour immobility

• Strong bias towards the non tradable sector (skill biased)– Not necessarily formal education but unobservable characteristics



Motivation


MitchHurricane

Commodity boom

Inequality peacK


Motivation

Mitch Hurricane (1998)Highest inequality (GINI)

4550

5560

6570

75

Gin

i Ind

ex -

Po

vert

y H

ead

cou

nt R

atio

1990 1995 2000 2005 2010Year

Poverty Head Count Ratio Gini rural areas pcGini country level pc

Source: Honduran household surveys and UNdata.

Poverty and Inequality Trends in Honduras


2 $ PPP per dayperr capita


Motivation

• After 1999 (facts):– Increasing rates of growth with increasing poverty (explosion of

remittances, aid, etc)– Strong disequalization of the per capita income distribution– Mainly a rural phenomena– Upsurge (decay) of the non-tradable sector (tradable)– Strong evidence of labour immobility

• After 2005 (facts):– Increasing rates of growth with declining poverty– Recovery of the tradable sector earnings (particularly at the

bottom of the distribution– Declining inequality (mostly in rural areas)– Commodity boom



MotivationEvidence of Labour Immobility (worker‘s heterogeneity - Low Migration)

-15

-10

-50

5pe

rce

nt

0 20 40 60 80 100

Tradable sector 1991-1999

-20

-15

-10

-50

50 20 40 60 80 100


-20

020

4060

0 20 40 60 80 100


-10

-50

510

perc

ent

0 20 40 60 80 100percentile

Non-tradable sector 1991-1999-1

0-5

05

1015

0 20 40 60 80 100percentile

Non-tradable sector 1999-2005

-40

-20

020

40

0 20 40 60 80 100percentile

Non-tradable sector 2005-2007

Note different y-axis scales.

Source: Authors' calculations based on EPHPM I and EPHPM II

90% ci Median spline Growth rate in mean



Reserach Question• How relevant are macro-economic shifts in explaining the Honduran

income inequality (poverty) developments over the last two decades?

• What is the story behind the fact that Honduras is an outlier in Latin America when considering the inequality trends over the last two decades?– Migration towards the modern sector

• Increasing earnings in the traditional sector

– Declining returns to skills (educational upgrade)– Social policies CCTP

• In this paper, we propose a lower bound methodology to investigate how sectorial shifts affects the income distribution contributing to explain the almost unchanged poverty figures over the last 15 years.



The Decomposition Methodology• Set up as in Devillanova et al. (2010)

– Workers‘ heterogeneity and Capital-skill complementarity (Imperfect mobility of labour)

• Focus in rural areas – 50 % of the total population live in rural areas– 80% of the poor households live in rural areas

• Strong evidence against the tradable sector (backward)– Overvaluation of the RER– Fluctuation in commodity prices are relevant– Natural catastrophes are common affecting principally the rural infrastructure

and production. (Mitch Hurricane in 1998 but many other tropical storms are frequent)



The Decomposition Methodology


0.5

11.

5D

ens

ity

5 10 15 20Log-earnings

Rural log-earnings in Chile 2006

0.2

.4.6

0 2 4 6 8 10Log-earnings

Rural log-earnings in Hunduras 2005

Note: based on full-time employed rural workers.Source: Authors' calculations based on CASEN 2006 and EPHPM 2005.

Tradable sector Non-tradable sector

The backward (tradable) sector

mainly agricuture


The Decomposition Methodology0

.1.2

.3.4

-4 -2 0 2 4

0.1

.2.3

.4

-4 -2 0 2 4

0.1

.2.3

.4

-4 -2 0 2 4

0.1

.2.3

.4

-4 -2 0 2 4

Note: Each distribution consists of 3000 obs. randomly drawn from a normal distribution.

tradable non-tradable

Macroeconomic shift

THE RURAL SECTOR (50 % of the total population - 80% of all poor households)

1999 2005



The Decomposition Methodology• Oaxaca-Blinder type of decomposition of a distribtional change • The symbol (´) makes reference to t2

ΔD = D(t2)− D(t1)

ΔD = D(WS‘, BS‘) − D(WS, BS)

ΔD = [D(WS‘, BS‘) − D(WS‘, BS)] + [D(WS‘, BS) − D(WS, BS)]

We can simulate D(WS‘ , BS)

We decompose the distributional change in a between sectors gap effect and in a within sector effect which is caused by changes in productive endowments, their returns and employment changes across sectors (weights) . Note that there is no path dependence

arising in this methodology.



The Decomposition Methodology• 1991-1999; 1999-2005; 2005-2007


-10

12

Log-

ear

nin

gs g

ap

grow

th

0 20 40 60 80 100Percentiles

delta gap 1999-1991 delta gap 2005-1999

delta gap 2007-2005

Source: Authors' calculations based on EPHPM I and EPHPM II.

0.43

0.14

-0.14


The Decomposition Methodology• 1999-2005 (Period of high GDP Growth without poverty reduction)

0.1

.2.3

.4de

nsiti

es

0 2 4 6 8 10 12

sectorial distributions in rural areas in t

0.43

0.1

.2.3

.4

0 2 4 6 8 10 12

sectorial distributions in rural areas in t'

0.1

.2.3

dens

itie

s

0 2 4 6 8 10 12log - wages

rural wage distribution in t

0.0

5.1

.15

.2.2

5

0 2 4 6 8 10 12log - wages

rural wage distribution in t'

Source: Own elaboration based on randomly simulated data (parameters of Honduras 2005).

tradable sector non-tradable sector



Results• Honduras 1999-2005 (Growth + Unchanged Poverty)

– At least 40% of the Honduran (GINI) disequalization between 1999 and 2005 can be attributed to the decline of the tradable sector.

– Documented elements• Appreciated RER• Mitch Hurricane • Weak commodity prices



Results• Honduras 2005-2007 (Growth with poverty reduction)

– At least 33 % of the Honduran (GINI) equalization between 2005 and 2007 can be attributed to the upsurge of the tradable sector.

– Documented factors• Commodity Boom



ConclusionsThis analysis likely represents a lower bound of the impact of macroeconomic

conditions on inequality changes.• Bias against the tradable sector, increases the return to skills, disequalizing the

labour income distribution

There is an measurable (lower bound) impact of macroeconomic shifts (traduced into the decay or upsurge of the tradable sector) on inequality changes.

Trade reforms as well as changes in the real exchange rate and revenues shocks affecting the tradable sector should be carefully considered when analyzing poverty and inequality dynamics.

The losers in Honduras were no t randomly selected. The were mostly the poor

In the long-run, avoid agricultural workers education. Promote inter-sectorial mobility of workers (as Prof. Winters recommended) by providing as in the developed world general education. Generate basic and open skills (Language and Mathematics)



Thank you!


Documents

Sectorial shifts and Inequality A way to relate macroeconomic events to inequality changes Carlos Villalobos Barría (University of Goettingen) Chair of