Karsten Staehr. Minimum Wages and the Wage Distribution in Estonia

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Open seminar, Eesti Pank

20 September 2016

Minimum Wages and the Wage Distribution

in Estonia �

KARSTEN STAEHR

Tallinn University of Technology, Eesti Pank

All opinions personal!

Simona Ferraro, Jaanika Meriküll & Karsten Staehr (2016): “Minimum wages and

the wage distribution in Estonia”, Working Papers of Eesti Pank, no. 6/2016

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Menu

1. Introduction

2. Results from literature

3. Methodology

4. Data and summary statistics

5. Estimation results

6. Final comments

NB: Positive / descriptive analysis!

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1. Introduction

“The new normal” � distributional concerns

� Piketty (2014)

� ECB and monetary policy (Mersch, 2014)

� IMF and fiscal policy (Dabla-Norris et al., 2015)

� Changes to person income taxation in EE and LV

Minimum wages

� Politically contested topic in USA, UK

� … and recently Germany

� IMF (2016): “Cross-country report on minimum wages”, IMF Country Report, no.

16/151 (http://www.imf.org/external/pubs/ft/scr/2016/cr16151.pdf)

� Latvia, Lithuania, Poland and Romania

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Questions

a) How do minimum wages affect employment?

b) How do changes in minimum wages affect wage distribution?

b1) How do minimum wages affect wages for wage-earners directly affected by

changes?

b2) How do minimum wages affect wages for wage-earners not directly affected,

i.e. above changed minimum wage?

~ Spill-over or ripple effect

�

Effect on average wage depends on spill-over effects ⇒⇒⇒⇒ macroeconomic

implications

This paper

� Address b2) in isolation!

� How do changes in the minimum wage affect wages at different percentiles of the

wage distribution at or above the changed minimum wage?

Use (modified version of) standard methodology � Lee (1999)

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Contribution

� Estonia � post-communist (until now only detailed studies for Ukraine, Russia)

� EU country from CEE

� Market-oriented, flat tax, low social transfers, little collective bargaining, rather

wide wage and income distributions

� Consider pre-crisis, crisis, post-crisis periods separately ☺☺☺☺

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2. Results from literature

Methodological complication

� In given period � “everybody” typically face same minimum wage (“same

treatment”)

� Changes from period to period ⇒⇒⇒⇒ weak identification

Methods

� Early studies � plots of wage distributions before and after

� From mid-1990s � semi-parametric methods

� Lee (1999) � smart identification strategy & econometrics

� Various other methods

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Results

USA

� Spill-over effects of minimum wage up to 25th

percentile

� Gradual decline of the real value of the federal minimum wage ⇒⇒⇒⇒ lower tail

inequality ↑ (DiNardo et al. 1996, Lee 1999, Autor et al. 2016)

UK

� Generally small or no spill-over effects (Stewart 2012, Dickens & Manning 2004b)

Continental Europe

� Few studies (no minimum wage in many countries)

Post-communist / emerging markets

� Mexico (Bosch & Manacorda 2010), Vietnam (Hansen et al. forthcoming) �

substantial spill-over effects

� Ukraine � large spill-over effects, largest for women (Ganguli & Terrell 2006,

JCE)

� Russia � large spill-over effects, largest for women (Lukiyanova 2011, NSE)

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3. Methodology

Identification problem � lack of variation in minimum wage across wage earners

� Cross-sectional dimension

� Time dimension

Lee (1999)

Consider various “labour markets” / “cells” �

� Lee’s labour market / cell � state, year

� Our labour market / cell � region, year, sector

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Wage distribution differs across cells �

Effect of minimum wage on wage distribution depends on size of the minimum wage

relative to the wages in the particular cell:

� If minimum wage high relative to wage distribution in cell ⇒⇒⇒⇒ binding or effective

for many �� large effect on wage distribution

� If minimum wage low relative to wage distribution in cell ⇒⇒⇒⇒ binding or effective

for only few �� little effect on wage distribution

Measure of “bindingness” or effectiveness of minimum wage in cell

=

Minimum wage – median wage in cell (< 0)

=

“Effective minimum wage” in cell

Median wage in cell � measure of wage distribution in cell

Identifying assumption � the median wage (and above) in cells not affected by the

minimum wage

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Estimations

Find effect of the “effective minimum wage” on various percentiles of the wage

distribution

Our empirical model

ijtijttijttijtpijt wwwwww ε++−β+−β=− controls)()( 250

250

150

� i = region, j = sector, t = year

� pijtw = p-percentile of log wage in region i, sector j and year t

� 50ijtw = median log wage

� tw = log minimum wage in year t

NB: Run regression for any percentile p

� #observations = #regions × # sectors × #years

[Intuition � increase of wt]


Controls � year dummies, regional dummies, GDP growth and unemployment rate

� Hopefully remove effects of other factors

� Quadratic terms allow for non-linear relationship � compute marginal effect at

averages of explanatory variables


4. Data and summary statistics

Statutory minimum wage

� In principle set in tri-partite negotiations � in practice government has final say

0

100

200

300

400

02 04 06 08 10 12 140

100

200

300

400

Figure 0: Pre-tax minimum wage for full-time wage-earner, EUR per month


Estonian Labour Force Survey (LFS)

� 2001-2014

� No panel

� Only full-time wage earners (e.g. self-employed excluded)

� 6000-7000 observations per year � in total 91,447 observations

� Wage net-of-tax

� Other information used

� 5 regions (including counties), 11 sectors for creating cells

� Gender, age for sample splits

� Each cell (region, sector, year) � at least 20 wage-earners


NB1: All wages net of tax

NB2: LFS wage data ≠ Eesti Statistika wage data


5. Estimation results

� For whole sample

� For various subgroups

� Males vs. females

� Age 45 or less vs. age above 45

� Boom 2001-2007, crisis 2008-2010, recovery 2011-2014

Percentiles p = 5, 10, 15, 20, 25, 30, 40 (and for checking: 60, 70, 80, 90)

Empirical notation:

� minw – p50 = log minimum wage – median log wage = effective minimum wage

� p5 – p50 = log wage at 5th

percentile – median log wage

� p10 – p50 = log wage at 10th

percentile – median log wage

� …


Marginal

effects

evaluated at

means of

explanatory

variables


Marginal effect = percentage change in wage (at given percentile of wage

distribution) when minimum wage increases by 1 percent


NB: Percentage change at different log wage levels!

� Next slide � marginal effects in euros!


Wages = net-of-tax wages


Calculate effect on average wage

� Marginal effects at different percentiles

� Average wage at different percentiles

� Number of persons in interval around each percentile �

Minimum wage ↑ € 1 ⇒⇒⇒⇒ average wage ↑ € 0.11


NB: Wage distributions very different for men and women, for young and grown-ups


Effect of minimum wage seems to be smaller during crisis than before and after


6. Final comments

Standard exercise using standard methodology!

� But augmented with sectoral dimension for identification

Results

� Fairly large spill-over effects, at least to 20th

percentile

� Stronger spill-over effects for women than for men and for older than young

(reflecting different wage distributions)

� Weaker spill-over effects during crisis than during boom and recovery

In euros

� Substantial spill-over effects even beyond 20th

percentile

� Minimum wage ↑ € 1 ⇒⇒⇒⇒ average wage ↑ € 0.11 ☺☺☺☺ / ��


Why large spill-over effects in Estonia?

� Minimum wage main collective wage setting mechanism

� Great awareness � negotiations, press, in time for wage adjustments in beginning

of year

� Indexation of fees and prices � kindergarten, child support, traffic fines

Overall conclusion � minimum wage seems to lift wages in lower tail of wage

distribution ⇒⇒⇒⇒ potential to affect wage distribution


Extra slide

Karsten Staehr. Minimum Wages and the Wage Distribution in Estonia

Economy & Finance

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