Drivers of income inequality change in CEE countries, 2004-2010

Drivers of income inequality change in CEE countries, 20042010 Mรกrton Medgyesi, Tรกrki Social Research Institute

Work in progress

May, 2014

1.Introduction • Transition led to significant increases in inequality and poverty (Milanovic 1999, World Bank 2000, Heyns 2005).

• At the time of accession to the EU CEE countries are heterogeneous in terms of overall income inequality.

• The period after 2004 has been characterized by considerable macroeconomic volatility: huge changes in employment levels.

• This analysis investigates how changes in the distribution of employment among individuals and households have changed and how this contributed to changes in the income distribution during the 20042010 period.

2.Literature and research questions Impact of employment changes on the income distribution: • Declining employment increases inequality of labour earnings between those working and not working (Jenkins et al. 2011).

• Composition of the employed population can also change, which might have opposite effect.

• To assess the effect of changing employment on household income, one has to consider how employment and earnings of individuals are combined in households.

2.Literature and research questions (2) • Burniaux et al. (2006): after 1993-94, income inequality declined in countries where unemployment decreased: an increase in inequality among wage-earners being offset by more people being in work.

• Why increasing employment during the growth period preceding the crisis did not lead to a decline in poverty rates? (eg. Cantillon 2011, Corluy and Vandenbroucke 2012).

• OECD (2011): during 1985-2005, the increase in women’s employment had an equalising effect, but the rise in gross earnings disparities led to increasing inequality of hhd earnings.

Fig. Change in employment rate in EU countries (20-64 age group) 10

5

0

-5

-10

-15 HU PL RO SK BG CZ SI LT LV EE MT IT GR BE ES LU FR PT DE IE AT FI UK CY NL DK SE

CEE countries Source: Eurostat database

2004-2007

2007-2010

3.Data and measurement • Based on the microdata from user databases of the EUSILC 2005, 2008 and 2011.

• Data cover 10 CEE countries (CZ, SK, PL, HU, Sl, EE, LT, LV, BG and RO), data for BG and RO is not available in EU-SILC 2005.

• Income: disposable income is gross market income plus social transfers minus direct taxes and social contributions.

Equivalised with OECD II scale. The income reference year is the calendar year prior to the year of study.

• Employment: – Employment status at time of the interview – Number of months in employment during the year

• The analysis focuses on households with working age hhd head (18-65)

Table: Measurement of individual non-employment in EU-SILC

BG CZ EE HU LT LV PL RO SI SK

% of those not in employment at interview 2004 2007 2010 34.2 37.3 36.2 34.7 35.7 33.3 29.6 35.0 36.3 43.0 44.2 36.4 31.6 39.2 33.7 31.6 41.0 49.1 40.7 39.0 39.5 37.8 40.9 37.5 42.3 37.8 35.2 38.9

% of those employed zero months during the year 2004 2007 2010 29.7 35.1 31.2 31.5 32.5 30.0 23.8 31.6 29.7 37.4 39.8 33.2 28.0 36.6 29.2 25.7 37.6 43.7 35.6 41.2 38.1 38.7 39.1 34.7 37.0 35.2 33.3 37.1

4.Inequality among households in the distribution of work and the distribution of income • Gregg and Wadsworth (2008) have proposed to compare the actual workless household rate to the rate that would prevail, if non-employment was randomly and equally distributed in the population.

I= Σkskwk ̶ Σkskpk

Where household size k=1….K, sk stands for population share, wk is actual workless household rate, p is the individual non-employment rate

Table: Worklessness at the household level and work inequality Workless household rate 2004 actual counter factual BG CZ EE HU LT LV PL RO SI SK

14.8 15.1 14.8 16.6 14.2 23.5

9.5 10.1 9.1 11.0 9.1 14.4

16.2 13.8

11.9 8.4

2007 actual counter factual 12.9 6.5 14.7 9.4 10.4 7.5 20.0 12.6 13.4 7.6 10.6 6.8 18.5 9.6 17.2 10.4 15.2 9.8 12.6 6.9

2010 actual counter factual 14.4 8.9 13.7 10.1 14.8 11.3 20.4 13.9 19.6 12.8 18.3 13.4 17.6 12.6 15.1 10.7 12.6 9.3 13.2 8.9

Work inequality (absolute) (actual -counterfactual) 2004

5.3 4.9 5.6 5.6 5.1 9.1 4.4 5.4

2007

2010

6.4 5.4 2.9 7.4 5.9 3.7 8.9 6.7 5.5 5.7

5.5 3.5 3.5 6.6 6.8 4.9 4.9 4.4 3.4 4.4

Table: Inequality of disposable income (households with working age head) 2004 BG CZ EE HU LT LV PL RO SI SK

0.264 0.338 0.284 0.365 0.356 0.364 0.233 0.263

Gini index 2007 0.356 0.249 0.299 0.258 0.333 0.366 0.325 0.363 0.230 0.235

2010 0.349 0.256 0.321 0.275 0.331 0.356 0.316 0.337 0.228 0.248

Variance of logs 2004 2007 2010 0.495 0.486 0.234 0.218 0.227 0.448 0.381 0.449 0.264 0.225 0.253 0.539 0.424 0.508 0.508 0.512 0.557 0.542 0.387 0.366 0.540 0.506 0.196 0.198 0.183 0.250 0.234 0.268

5.Studying the link between distribution of work and income: methodology (1) Starting point:

Yi=ΣβkXk+εi Y=log household disposable income X= Work intensity of hhd: workless, 0<WI<0.5, 0.5<WI<1, WI=1 Age of hhd head: 18-35, 36-49, 50-64 Education level of hhd head: below up. 2ndary, upper 2ndary, tertiary Household composition: 6 categories • the proportionate contribution (sk) of the composite variable Ck=bkXk to overall inequality (Fields 2003, Cowell and Fiorio 2011): sk= bk σXk,Y/σ2Y where bk is the estimated regression coefficient for variable k, Xk is the value of the k-th explanatory variable, and σ is covariance.

5.Studying the link between distribution of work and income: methodology (2) If incomes in period a and b are Ya=β0a + ΣkβkaXka + εa Yb=β0b + ΣkβkbXkb + εb Where y=log(income), Xkt are exogeneous variables end εt is the residual.

Yun (2006) defines the auxiliary equation, by replacing coefficients of earnings equation of time period a with those of time period b: Y*= β0a + ΣkβkbXka + εa If inequality is measured by the varlog (σ2y), inequality change can be decomposed as: σ2ya ̶ σ2yb= (σ2ya ̶ σ2y*) + (σ2y* ̶ σ2yb)= =Σk(skya σ2ya ̶ sky* σ2y*) + Σk(sky* σ2y* ̶ skyb σ2yb) +(σ2εa - σ2εb)

(coefficients effect) (characteristi cs effect) (residual effect)

Proportional contribution of differences in household work intensity to overall inequality of income (households with working age head) 30% 25% 20% 15%

10% 5% 0%

RO

PL

HU

SI

SK 2004

2007

CZ 2010

LT

BG

LV

EE

CZ

Absolute contributions to inequality change, 2004-2007

SK

PL

Char

Coeff

Sum

Char

Coeff

Sum

Char

Coeff

Sum

Age

0.000

0.001

0.001

-0.001

0.001

0.000

-0.001

-0.001

-0.001

Education

0.001

-0.004

-0.003

0.001

0.005

0.005

0.000

-0.006

-0.006

Work intens.

-0.003

-0.007

-0.010

-0.001

-0.001

-0.002

-0.005

-0.019

-0.024

HHd structure

0.000

-0.001

-0.001

-0.001

0.005

0.004

-0.002

-0.010

-0.012

-0.003

-0.003

-0.023

-0.023

-0.111

-0.111

-0.013

-0.016

-0.013

-0.016

-0.147

-0.155

Residual Sum

-0.002

-0.003

EE

-0.008

LT

LV

Char

Coeff

Sum

Char

Coeff

Sum

Char

Coeff

Sum

-0.001 0.003

0.002 -0.015

0.002 -0.012

0.000 -0.001

0.000 -0.019

-0.001 -0.020

0.000 0.008

0.003 -0.007

0.002 0.000

Work intens.

-0.024 intensity HHd structure -0.004

-0.006

-0.029

-0.015

-0.019

-0.034

-0.021

0.014

-0.007

0.004

0.000

-0.006

0.006

0.000

-0.001

0.004

0.004

Residual

-0.028

-0.028

-0.060

-0.060

0.004

0.004

-0.042

-0.067

-0.092

-0.115

0.018

0.003

Age Education

Sum

-0.026

-0.023

SI

HU

Char

Coeff

Sum

Char

Coeff

Sum

0.000 0.011

-0.002 -0.009

-0.001 0.002

0.001 -0.001

-0.002 -0.008

-0.001 -0.009

Work intens.

-0.002 intensity HHd structure 0.000

0.001

-0.002

0.004

0.007

0.010

-0.001

0.000

0.001

0.000

0.002

Residual

0.004

0.004

-0.042

-0.042

-0.007

0.002

-0.044

-0.040

Age Education

Sum

0.009

0.005

-0.014

Absolute contributions to inequality change, 2007-2010

Age Education Work int.

HHd str.

Residual Sum

Age Education Work int.

HHd str.

Residual Sum

Age Education Work int.

HHd str.

Residual Sum

Age Education Work int.

HHd str.

Residual Sum

Char 0.000 0.003 0.009 0.002 0.014 Char 0.000 0.001 -0.002 0.000 0.000 -0.002 Char 0.000 0.002 0.018 -0.002 0.019 Char 0.001 0.000 -0.003 -0.002 -0.004

BG Coeff -0.004 0.042 -0.025 0.007 -0.044 -0.023 CZ Coeff -0.001 0.007 0.003 -0.001 0.003 0.011 EE Coeff -0.001 0.006 0.006 -0.010 0.049 0.049 SI Coeff 0.000 -0.003 -0.002 0.002 -0.009 -0.012

Sum -0.003 0.045 -0.015 0.008 -0.044 -0.009

Char 0.000 0.016 -0.002 -0.002

Sum -0.002 0.008 0.001 -0.001 0.003 0.010

Char 0.000 0.001 0.002 0.000 0.000 0.003

Sum -0.001 0.008 0.024 -0.012 0.049 0.068

Char 0.000 0.020 0.025 0.008

Sum 0.001 -0.003 -0.004 0.000 -0.009 -0.015

0.012

0.052

RO Coeff 0.002 -0.010 -0.018 -0.003 -0.017 -0.047 SK Coeff 0.000 -0.004 0.012 0.003 0.020 0.031 LT Coeff 0.004 -0.020 -0.003 -0.020 0.070 0.031

Sum 0.002 0.006 -0.020 -0.005 -0.017 -0.034

Char 0.001 0.001 0.002 0.002

Sum 0.000 -0.003 0.014 0.003 0.020 0.034

Char -0.001 0.005 0.001 -0.001 0.000 0.004

Sum 0.004 0.000 0.022 -0.012 0.070 0.084

Char 0.000 0.010 0.059 0.004

0.005

0.072

HU Coeff -0.003 0.016 0.000 -0.002 0.012 0.022 PL Coeff 0.000 -0.009 0.006 0.001 -0.024 -0.026 LV Coeff -0.002 0.011 -0.059 -0.008 0.032 -0.027

Sum -0.002 0.017 0.002 0.000 0.012 0.028 Sum 0.000 -0.004 0.007 0.000 -0.024 -0.022 Sum -0.002 0.020 0.000 -0.004 0.032 0.045

Conclusions â&#x20AC;˘ Inequality in the household distribution of work was increasing in Hungary and to a lesser extent in Slovenia in the first period, while in the case of Estonia and Latvia we saw a decline in inequality. During the 2007-2010 period inequality increased in Latvia, while in Lithuania and Estonia the increase has been only marginal. â&#x20AC;˘ In CEE countries work intensity and also education of the household head are more important in shaping income distribution compared to age or household structure. The contribution of work intensity to total inequality is highest in the Baltic states and Bulgaria (19-20% of the level of inequality), while it is just 6% of overall inequality in Romania and just over 10% in Poland. â&#x20AC;˘ Decomposing changes in income inequality showed that in all Baltic states change in the distribution of work among households (work intensity) contributed to change in income inequality during both periods.