Effects of the German Minimum Wage on Earnings and Working Time Using Establishment Data

Abstract

This study examines the short-term effects of the introduction of a statutory minimum wage in Germany on hourly wages, monthly wages and paid working hours. We exploit a novel panel dataset by linking the Structure of Earnings Survey (SES) 2014 and the Earnings Survey (ES) 2015 and apply a difference-in-differences approach at the establishment level. The results indicate an effect of the introduction of the statutory minimum wage on the average hourly wages of employees in minimum wage establishments of up to 5.9 %. Due to negative effects on average working time of approximately minus 3.1 %, the effects on monthly gross earnings are smaller but still amount to up to 2.7 % on average. The results further suggest that the minimum wage effects on earnings were greater among low-wage employees than on average, in eastern Germany than in western Germany, and among part-time employees and marginal employees than among full-time employees.

Full text

Clemens Ohlert*
Effects of the German Minimum Wage on
Earnings and Working Time Using
Establishment Data
https://doi.org/10.1515/jbnst-2024-0025
Received February 2, 2024; accepted June 6, 2024
Abstract: This study examines the short-term effects of the introduction of a
statutory minimum wage in Germany on hourly wages, monthly wages and
paid working hours. We exploit a novel panel dataset by linking the Structure
of Earnings Survey (SES) 2014 and the Earnings Survey (ES) 2015 and apply a
difference-in-differences approach at the establishment level. The results indicate an
effect of the introduction of the statutory minimum wage on the average hourly
wages of employees in minimum wage establishments of up to 5.9 %. Due to negative
effects on average working time of approximately minus 3.1 %, the effects on monthly
gross earnings are smaller but still amount to up to 2.7 % on average. The results
further suggest that the minimum wage effects on earnings were greater among
low-wage employees than on average, in eastern Germany than in western Germany,
and among part-time employees and marginal employees than among full-time
employees.
Keywords: minimum wage; evaluation; hourly wages; earnings; working time
JEL Classification: J08; J30; J31
1 Introduction
The introduction of a general minimum wage in 2015 was a major change to the
institutional framework of the labour market in Germany. It had a considerably
larger impact on a range of outcomes than subsequent incremental adjustments
Article Note: This article is part of the special issue “Minimum Wages: Experiences of European
Countries”published in the Journal of Economics and Statistics. Access to further articles of this special
issue can be obtained at www.degruyter.com/jbnst.
*Corresponding author: Clemens Ohlert, Federal Institute for Occupational Safety and Health (BAuA),
Berlin, Germany, E-mail: ohlert.clemens@baua.bund.de
Journal of Economics and Statistics 2025; 245(1–2): 185–213
Open Access. © 2024 the author(s), published by De Gruyter. This work is licensed under the
Creative Commons Attribution 4.0 International License.

of the minimum wage (Bruttel 2019; Caliendo, Schröder, and Wittbrodt 2019;
Mindestlohnkommission 2020). In view of the strong increase in the minimum
wage to 12 euros per hour in October 2022, the introduction of the minimum wage
provides an important reference for how the minimum wage operates in the German
labour market.
1
The effects on hourly wages, monthly wages and working time have
been a major focus of interest in previous evaluation studies since these dimensions
basically determine whether the reform helps increase the incomes of low-wage
earners and hence their welfare.
There has been a lively debate about the size and relation of minimum wage
effects on hourly wages, monthly wages and working hours based on different data
sources and methodological approaches applied in the literature. Previous
researchunanimouslyfoundasignificant positive impact of the minimum wage
introduction on hourly wages, but there have been mixed results regarding the
impact on monthly wages and working hours based on different data and
approaches (see Section 2). In particular, the findings differed between studies
based on household survey data on the one hand and administrative data and
establishment survey data on the other.
This paper extends previous research by examining the short-term effects of the
minimum wage introduction based on novel linked employer–employee panel data
for the years 2014 and 2015. To this end, the Structure of Earnings Survey (SES) 2014
and the Earnings Survey (ES) 2015 were linked to form an establishment panel,
which also contains observations of a random sample of employees in the surveyed
establishments. The SES/ES is one of few large datasets in Germany that allows the
calculation of individual hourly wages (Dütsch, Himmelreicher, and Ohlert 2019).
The applied methodology uses a difference-in-differences approach that
compares changes in earnings and working time among employees in establish-
ments that were affected by the minimum wage to changes among employees in
establishments that were not affected. Affected establishments were defined as
those that had at least one employee with an hourly wage below 8.50 euros in the
year 2014. Heterogenous effects are considered by putting a focus on low-wage
employees and by differentiating between East and West Germany and by type of
employment (full-time, part-time, marginal employees). As a robustness check, a
weighted control group approach is applied.
1The introduction of the minimum wage affected approximately four million employees in
Germany. The adjustment of the minimum wage to 8.84 euros in 2017 affected approximately 3.3
million employees and the adjustment to 9.19 euros in 2019 affected approximately 2.5 million
employees (Mindestlohnkommission 2020). The adjustment of the minimum wage to 12 euros in
October 2022 affected approximately 5.8 million employees (Mindestlohnkommission 2023).
186 C. Ohlert

The results indicate an effect of the introduction of the statutory minimum
wage on the average hourly wages of employees in minimum wage establishments
of up to 5.9 %. Due to negative effects on average working time of approximately
minus 3.1 %, the effects on monthly gross earnings are smaller but still amount to up
to 2.7 % on average. The results further suggest that the minimum wage effects on
earnings were greater among low-wage employees than on average, in eastern
Germany than in western Germany, and among part-time employees and marginal
employees than among full-time employees.
The remainder of the paper is structured as follows. Section 2 provides an overview
of previous evidence. Section 3 introduces the data and describes the sample. Section 4
explicates the econometric approach. Section 5.1 presents descriptive results on the
distribution and changes in earnings and working time. Section 5.2 examines the effects
of the minimum wage. Section 6 provides a robustness check, and Section 7 concludes.
2 Previous Evidence
The literature consistently reports positive effects of the introduction of the
minimum wage on hourly wages, which differ only somewhat in size. Several studies
used household survey data and reported effects between 4 and 9 % based on the
German socioeconomic panel (GSOEP) (Bachmann et al. 2020; Burauel et al. 2020b;
Caliendo et al. 2023) and between 5 and 9 % based on the PASS
2
(Hafner and Lochner
2022). Since working hours are not measured in the Integrated Employment
Biographies (IEB) except from 2010 to 2014, two studies used approximated hourly
wages based on imputed working hours. They reported minimum wage effects on
hourly wages of 6 % (Dustmann et al. 2022) and 4 % (Ahlfeldt, Roth, and Seidel 2018).
Several studies have pointed to stronger effects on hourly wages in the lower part of
the wage distribution (e.g. Ahlfeldt, Roth, and Seidel 2018; Bachmann et al. 2022).
Descriptive evidence based on the Structure of Earnings Survey showed an
immediate substantial shift of employment with hourly wages below the minimum
wage to the value of the minimum wage and closely above after the introduction of
the minimum wage. Changes in the same range of hourly wages were much smaller
according to the GSOEP (e.g. Mindestlohnkommission 2020: 52). Additionally,
measured noncompliance with the minimum wage is substantially larger based on
the GSOEP than based on the SES/ES (Mindestlohnkommission 2018: 62ff.).
3
Estimates
2The PASS (‘Labour Market and Social Security’panel study) is an annual survey of households in
Germany with a focus on low-income households.
3An analysis and discussion of these differences can be found in Bachmann et al. (2020) and Dütsch,
Himmelreicher, and Ohlert (2019); see (Fry and Ritchie 2012) for the UK.
Effects of the German Minimum Wage 187

of minimum wage effects on hourly wages can thus be expected to be larger in the
SES/ES than in the GSOEP. Using the structure of earnings surveys in 2014 and 2018
and regional variation in the minimum wage bite, Biewen, Fitzenberg, and Rümmele
(2022) find significant minimum wage effects on hourly wages along the wage
distribution and spillover effects up to 20 % above the minimum wage. Bossler,
Liang, and Schank (2024) report similar findings along the wage distribution and, on
average, attribute an increase in hourly wages of 5.3 % to the minimum wage
introduction.
The results regarding the impact of the minimum wage on monthly wages were
more mixed. Studies based on the German Socio-Economic Panel (GSOEP) found
that there were no increases in monthly wages for affected workers in 2015, and the
effect of 6.6 % in 2016 was only statistically significant at the 0.1-level (Bachmann
et al. 2020; Burauel et al. 2020a, 2020b). They also showed that the findings on monthly
wages resulted from minimum wage-induced reductions in contractual working
time. However, other studies did find significant positive minimum wage effects on
monthly wages of 3.8–4.3 % using the IAB Establishment Panel (Bossler and Gerner
2020; Bossler et al. 2022) and of 4.4 % in 2015 and 2016 using the Integrated
Employment Biographies (IEB) (Bossler and Schank 2023). According to (Bossler and
Schank 2023: 14), the effects are largest at the 20th percentile of the distribution of
monthly earnings and reach up to the 50th percentile. The authors explain that the
effect is small at the 10th percentile because it is located at the upper earnings limit of
marginal employment (employees with maximum earnings of 450 euros per month,
which are exempt from taxes and social security contributions). For the period from
2014 to 2018, Bossler, Liang, and Schank (2024) find an average effect on monthly
wages of approximately 5 % using the SES.
The evidence on minimum wage effects on working time has previously relied
strongly on household survey data from the GSOEP (Bachmann et al. 2020; Burauel
et al. 2020a) and the PASS (Hafner and Lochner 2022; Pusch, Seifert, and Santoro 2020)
and was complemented by findings based on the IAB Establishment Panel (Bossler
and Gerner 2020), all indicating a reduction in working time due to the introduction
of the minimum wage. The results of Burauel et al. (2020a) indicated a significant
negative effect on contracted working time of approximately minus 5 % in the
one-year period but no significant effect on working time in the two-year period.
Interestingly, negative effects were found only regarding contractual working time
but not regarding actual working time. However, recent evidence based on SESs from
2014 to 2018 by Biewen, Fitzenberg, and Rümmele (2022) and (Bossler, Liang, and
Schank 2024) does not confirm significant minimum wage effects on working time on
average. Bossler, Liang, and Schank (2024), however, noted a reduction in the
working hours of minijobbers.
188 C. Ohlert

Burauel et al. (2020a, 2020b) also examined heterogeneous short-term effects of
the minimum wage by type of employment. They find that the minimum wage had
the greatest positive impact on the hourly wages of marginal workers (15.5 % points),
while the effect on full-time workers amounted to 7.8 % points, and no significant
effect on part-time workers was found. Despite the positive effects on the hourly
wages of full-time and marginal workers, no significant impact on monthly earnings
was found. Regarding working time, they reported a significant and robust reduc-
tion in contractual working hours among employees who are subject to social se-
curity contributions but not among marginally employed workers.
3 Data and Sample Description
This study constructs a panel dataset by linking the structure of earnings survey (SES)
of 2014 and the earnings survey (ES) of 2015 at the establishment level.
4
Based
on these data, I examine the short-term impact of the introduction of a general
minimum wage in Germany. The SES is a large mandatory survey among estab-
lishments that the Federal Statistical Office conducts every four years (Statistisches
Bundesamt 2016, 2017). It collects information on the characteristics of the estab-
lishment and a random sample of employees within each covered establishment.
5
The focus of the survey is earnings and hours of work. The ES 2015 is a special survey,
which is mostly identical to the SES 2014 regarding its content and procedure but
has a smaller sample size, and establishments’participation is nonmandatory. It
was initiated with the specific aim of obtaining information on the impact of the
minimum wage in the years following the introduction of the minimum wage.
6
Both
the SES and the ES cover establishments of all sizes and the entire spectrum
of industries, except employment in private households and extraterritorial
organizations.
Sampling of the SES and ES was carried out in two stages. In the first stage, a
sample stratified by industry, region, and establishment size is drawn at the estab-
lishment level from the Firm Register (URS) of the Federal Statistical Office. The
realized establishment sample from the SES 2014 was used as the sampling base for
the ES 2015 (Statistisches Bundesamt 2017: 15 ff.), which allows us to link the same
establishments in both years based on an establishment identifier. In the second
4Source: RDC of the Federal Statistical Office and Statistical Offices of the Federal States, DOI: 10.
21242/62111.2014.00.00.1.1.1 and 10.21242/62112.2015.00.00.1.1.0.
5Employees can be in a main job or a side job. Therefore, strictly speaking, the data represents
employment relationships held by employees.
6The ES has been conducted for the years 2015–2017 and 2019.
Effects of the German Minimum Wage 189

stage, a simple random selection of employees is independently drawn within
establishments in each year. While all employees are covered in small firms, the
share of covered employees decreases with firm size.
7
The minimum wage in Germany is subject to several exemptions for specific
groups. It does not apply to self-employed persons, to persons under 18 years old
without a vocational degree, individuals in vocational training, individuals in
particular internships, long-term unemployed individuals in the first six months
after taking up employment or, until 2017, employees in particular industries
with sectoral minimum wages (Mindestlohnkommission 2020: 20). Consequently,
individuals younger than 18 and individuals in vocational training were excluded
from the sample. Other exemptions could not be clearly delimited in the SES/ES data
because they would require detailed information on industries and employment
trajectories, which was not available. Hence, the same sample delineation as
in previous minimum wage examinations based on the SES or ES was applied
(Bachmann et al. 2020; Dütsch and Himmelreicher 2020; Dütsch, Himmelreicher, and
Ohlert 2019; Mindestlohnkommission 2020). Retaining exempted employees
(with wages below the minimum wage) in the sample may lead to an overestimation
of the relevance of the minimum wage and to an underestimation of the size of
minimum wage effects among eligible employees.
The SES/ES data have crucial advantages but also several limitations. They
provide very reliable information on monthly earnings because firms usually
transfer this information directly based on their accounting data. The SES/ES data
also provide a relatively large sample of employees and establishments, which al-
lows for the differentiation of analyses by subgroup. The main limitation of these
data is that they usually do not have a panel structure but rather consist of repeated
cross-sections with distinct samples. The years 2014 and 2015 are an exception to this,
which is explained in detail below.
Because the SES/ES is an establishment survey, a presumed tendency of
employers not to disclose hourly wages below the effective minimum wage may be
relevant for the quality of the data (Garnero, Kampelmann, and Rycx 2015). The SES/
ES does not measure unpaid working time and is therefore not designed or ex-
pected to measure noncompliance with the minimum wage. According to quali-
tative research and information from custom agencies actual evasions of the
minimum wage law are mainly related to unpaid and undocumented working time
7Establishments with 1–9 employees: every employee; 10–49 employees: every second employee;
50–99 employees: every third employee; 100–249 employees: every sixth employee; 250–499
employees: every 10th employee; 500–999 employees: every 20th employee; 1,000 and more
employees: every 40th employee.
190 C. Ohlert

(Mindestlohnkommission 2020: 69).
8
Nevertheless, it is of interest that software
tools for wage accounting usually indicate when wages and working hours result in
an hourly wage that is below the minimum wage (Dütsch, Himmelreicher, and
Ohlert 2019: 273). While such tools obviously help employers comply with the
minimum wage regarding hourly wages resulting from documented and paid
working time, it is unknown how accurate working time documentation is and
whether there is unpaid working time. Furthermore, the supposed tendency not to
disclose wages below the effective minimum wage may find its way into survey
responsesbothintheSESandtheESatspecific instances, such as the reporting
of working time for the survey when working time has not been properly docu-
mented or the required random sampling of employees within larger establish-
ments for the survey, the implementation of which is left to the establishments.
The ES 2015 has been subject to one additional concern because, unlike the SES
survey, participation in the ES was not mandatory. While the same sampling pool of
establishments was contacted for the ES 2015 as for the SES 2014, the participation
rate was much lower (12.8 %), which caused the concern that participation in the
survey might have been systematically avoided by establishments that were
not compliant with the minimum wage after its introduction. Previous empirical
evidence does not support this assumption. Most notably, the ascertained rates of
employees below the effective minimum wage vary only slightly between the
nonmandatory surveys of the years 2015–2017 and the mandatory Structural Earn-
ings survey of the year 2018. Furthermore, the Federal Statistical Office analysed
the survey response for the ES 2015 based on the full sample of the SES 2014 and the
subsample that participated in the ES 2015. They found that the probability of taking
part in the survey declined with establishments’wage level (Frentzen and Günther
2017), which is confirmed by a relatively low mean hourly wage in the ES 2015
(Bachmann et al. 2022: 43). As a consequence, and in line with the aim of the survey to
facilitate minimum wage research, the ES is better suited to examining low-wage
employment than high-wage employment. Frentzen and Günther (2017) also found
that the response rate was marginally lower for establishments that were affected
by the minimum wage in 2014 than for establishments that were not affected. This is
not necessarily a problem for the analysis of wage effects since it makes the treat-
ment group (of affected establishments) smaller but does not necessarily distort
wage changes within the treatment group. However, if there was systematic
nonparticipation of establishments that were affected by the minimum wage law
and did not react to it (noncompliance), it would lead to an overestimation of wage
8It is also not measured in contractual working time in the GSOEP. While it is potentially measured
by actual working time in the GSOEP, it is unknown if and how the respective actual working hours
are remunerated.
Effects of the German Minimum Wage 191

effects. In the most comprehensive examination of potential measurement errors to
date, Bachmann et al. (2020) concluded that both the SES/ES and the GSOEP are
presumably affected by measurement errors that are likely to differ due to different
issues in household/employee surveys and establishments surveys. Ultimately,
which data come closer to portraying the true distribution of low hourly wages in
Germany could not be clarified.
For our analysis, the SES 2014 and the ES 2015 were linked at the establishment
level based on an identification number. Linkage is technically not possible for
establishments in public service and establishments that exclusively employ
marginal employees. Apart from these exceptions, all establishments that
participated in the ES 2015 also participated in the SES 2014 and can be followed
over time in the data. Information on wages and working time refers to a random
sample of employees within each establishment. Importantly, the panel structure
of the data is given only at the establishment level but not at the level of individual
employees. This means that the composition of observed employees within
establishments in the treatment and control groups can change over time. Wage
changes therefore can reflect wage increases (or reductions) of workers who
stayed at a firm, or entries of employees with specific wage levels, or exits of
employees with specificwagelevels.
Due to the much smaller sample size of the ES 2015, linking both datasets
greatly reduced the number of cases from the SES 2014, resulting in 73,395
employees in 6,594 establishments (see Table 1).
9
Afirm is categorized in the
treatment group if it had at least one employee earning less than 8.50 euros per
hour in 2014 and in the control group otherwise. Approximately 40.5 % and 2,672
establishments in the sample, respectively, are affected by the minimum wage
(see also Mindestlohnkommission 2020: 131; Ohlert 2021). Accordingly, the sample
comprises the same 6,594 establishments in the ES 2015, but the number of em-
ployees deviates somewhat from the data for the previous year due to job changes.
Table1comparestheunweightedwagedistributionsofthefullsampleandthe
panelsampleoftheSES2014.Thisshowsthattherearenodeviationsinthelower
part of the wage distribution and only small deviations in the upper part, which
suggests that the sample of the ES 2015 is not substantially biased regarding the
distribution of wages. Additionally, the share of employees below 8.50 is the same
in both samples.
9The sample of the total SES 2014 comprises 60.000 establishments (Dütsch, Himmelreicher, and
Ohlert 2019).
192 C. Ohlert

4 Econometric Approach
To answer the question of how the introduction of a minimum wage influences the
earnings and working time of employees, this study applies a difference-in-
differences (DID) approach, in which the factually unobserved situation without a
minimum wage is represented by a control group. The central assumption of this
approach is that the outcomes in the defined treatment and control groups would
develop similarly in the absence of the minimum wage (common trend assumption
or CTA). Because there are few exceptions to the minimum wage in Germany, there is
no obvious control group of employees who are not covered by the minimum wage.
Moreover, the available data in this study do not allow us to follow individual
employees but rather to follow establishments over time. Hence, to identify the
effects of the introduction of the minimum wage, I divide establishments into those
affected by the minimum wage and those not affected to compare the changes in
earnings and working time of employees in the two groups of establishments.
Establishments’affectedness by the minimum wage is measured based on whether at
least one employee with an hourly wage below 8.50 euros per hour was observed in
an establishment in 2014.
Since effects of the minimum wage are likely for workers with wages up to and
closely above the minimum wage but are increasingly unlikely in higher wage
regions (Cengiz et al. 2019), a focus is placed on the group of low-wage employees.
Table :Summary statistics on the distribution of hourly wages.
 
Cross-section Establishment
panel sample
Establishment
panel sample
Mean . . .
Percentiles
P. . .
P . . .
P . . .
P . . .
P . . .
P . . .
P . . .
Share of employees below .€. . .
Number of observations , , ,
Source: SES ,ES, unweighted data, own calculations. Notes: Observations are employees within
establishments. The mean and percentile values are in euros per hour.
Effects of the German Minimum Wage 193

Hence, employees with hourly wages above 10 euros are dropped from the sample in
an alternative specification. Further heterogeneity of minimum wage effects is
considered by conducting separate estimations for East and West Germany and by
interacting treatment effects by type of employment.
The outcomes of interest are hourly wages, monthly earnings and paid working
time of employee iin firm jand year t(see equation (1)). Monthly earnings are
defined as gross monthly earnings excluding overtime pay, and working time is
defined as paid hours of work per month excluding paid overtime.
10
Hourly wages
are calculated by dividing monthly earnings by paid working time per month. The
logarithm of all three dependent variables is taken for the multivariate analyses.
yijt =treatedj*year 2015t*δ+year 2015t*τ+θj+xijt *β+εijt (1)
The treatment effect on the treated is estimated by δ,whichisthecoefficient for an
interaction of a dummy variable indicating establishments affectedbythemini-
mum wage with the year 2015. It shows to what extent the minimum wage changed
the average wages and working time of employees in establishments that had at
least one employee paid less than 8.50 euros per hour in 2014. Furthermore,
Iincludefixed establishment effects (θj)in the models and thus estimate minimum
wage effects based on changes within establishments between 2014 and 2015. The
inclusion of establishment fixed effects controls for time-constant differences
across establishments and thus also between establishments affected by the min-
imum wage and those not affected. As only changes within establishments are
accounted for, changes in the number of observed employees within establish-
ments over time have no influence on the estimated effect.
Furthermore, control variables that can vary over time are included in the
specification. Changes in the composition of employees within establishments could
be a driver of changes in earnings and working time, and there is some concern that
changes in the composition of employees might deviate between the two groups of
establishments, irrespective of the minimum wage introduction, for two reasons:
a) there are substantial differences in the employment structure of minimum wage
establishments and other establishments (see Table A2), b) it is not known from the
data to what extent the same sample of employees was observed within establish-
ments before and after the introduction of the minimum wage (see Section 3). The
characteristics of employees within establishments were hence controlled for in the
regressions regarding employees’highest educational degree, age and age squared
and the type of employment with the categories full-time, part-time and marginal
10 Including overtime in paid working hours and earnings would not change hourly wages strongly.
Overtime pay is slightly higher due to overtime surcharges. Unpaid overtime is not included in the
data.
194 C. Ohlert

employment as well as dummy variables for fixed-term employment and
gender. Furthermore, large-scale changes in establishment size are unlikely to be
due to the minimum wage but could influence average wages and working time in
establishments. Therefore, three categories of establishment size were controlled for
(1–10 employees, 11–100 employees, 101 or more employees). It is assumed that the
common trend assumption holds conditional on these characteristics.
It is common practice to test the CTA based on the trends of both groups prior
to the respective policy intervention. This is not possible based on the available
data in this study, as the panel dataset at the establishment level can only be
compiled for the years 2014 and 2015. Pretrends presented by Bossler and Gerner
(2020) imply that the common trend assumption is not problematic for the anal-
ysis of working time effects. According to this study, which is based on the IAB
Establishment Panel, the development of standard working hours did not differ
significantly between minimum wage establishments and other establishments in
the year before the introduction of the minimum wage (ibid.: 14). The same study
shows that wage trends from 2013 to 2014 were slightly lower (approximately
2.1 %) in establishments affected by the minimum wage than in unaffected
establishments (ibid.: 11). It can therefore be assumed that the DID model
described above tends to overestimate the minimum wage effect on earnings to a
small extent. The effects on hourly wages and monthly earnings are therefore
interpreted as an upper bound.
A robustness check of the results was conducted based on the notion that similar
pretreatment means in the outcome variables in the treatment and control groups
are indicative of a good comparison group (Lechner 2010: 191). To this end, I applied a
synthetic (weighted) control group approach (entropy balancing) that balances the
pretreatment means and distributions of the respective outcome variables and a set
of covariates (Hainmueller 2012; Hainmueller and Xu 2013). The approach is similar
to matching on pretreatment outcomes, which is only possible with panel data and
requires weaker assumptions than the parallel trend assumption in DID. For this
purpose, the data are fully aggregated at the establishment level, which allows us to
apply the obtained balancing weights to establishments in both observed years to
retain a fixed treatment and control group. The approach has been applied
frequently in minimum wage evaluation at the establishment level (e.g. Bossler and
Gerner 2020).
The results on the effects of the minimum wage on earnings and working hours
could in principle also be influenced by employment effects of the minimum wage.
However, the employment effects of the introduction of the minimum wage were
relatively small overall according to previous findings (Caliendo, Schröder, and
Wittbrodt 2019). The presumably minimum wage-related additional conversions
from marginal employment to employment subject to social security contributions
Effects of the German Minimum Wage 195

comprised approximately 100 thousand employment relationships in 2015 (vom
Berge and Weber 2017: 4). For the analyses presented, these findings suggest a low
quantitative relevance of selection into employment.
5 Results
5.1 Descriptive Results
Between 2014 and 2015, hourly wages increased by 11.6 % in establishments
affected by the minimum wage and by 3.7 % in other establishments, on average
(Table 2). The difference in this change between the treatment and control groups
therefore amounts to approximately 8 % points. While the growth of hourly wages
was clearly greater at the bottom of the distribution of affected establishments
than among other establishments, it was also fairly high in the upper half of the
wage distribution, where an impact of the minimum wage is rather unlikely
(Figure 1). In establishments that were not affected by the minimum wage, there
was almost no growth in hourly wages at the 5th and 10th percentiles and slightly
greater wage growth at higher percentiles, which resembles the usual pattern of
wage growth observed in the years prior to the minimum wage introduction
(Burauel et al. 2018: 34).
Table :Means and changes in outcome variables by treatment status.
Employees in establishments
affected by the minimum wage
Employees in other
establishments
  Change   Change
Hourly wages
Mean ...%...%
Monthly wages
Mean ,.,..%,.,..%
Working time
Mean ...%..–,%
Number of observations , , , ,
Source: SES ,ES, unweighte d data, own calculations. Notes: Establishments affected by the minimum wage are
those that had at least one employee paid less than . euros per hour in . The results from a regression without
any control variables show that the changes from  to  in the control group are significantly different from zero
for hourly wages and monthly wages but not for working time. Changes from  to  in the treatment group are
significantly different from the changes in the treatment group for hourly wages and monthly wages but not for working
time.
196 C. Ohlert

On average, monthly wages increased by 12 % in establishments affected by the
minimum wage and by 3.5 % in other establishments (Table 2). Monthly wage growth
was thus approximately as high as the mean hourly wage growth. The difference
between the treatment and control groups regarding monthly wage growth amounts
to approximately 8.5 % points. A comparison of the changes across the distribution of
monthly wages shows that the increase in monthly wages was greatest at the 25th
percentile, where the monthly wage increased from approximately 600 euros to
approximately 870 euros (without figures). These descriptive findings suggest that
the growth of monthly wages was greater for part-time workers who are liable
to social security than for marginal workers and full-time workers with higher
earnings (see also Himmelreicher 2020). For marginal workers, the growth of
monthly wages is limited by definition due to the upper limit of earnings of 450 euros
in this employment form.
On average, working time increased by approximately 1 % in establishments
affected by the minimum wage and remained unchanged in other establishments
(Table 2). Hence, the difference between the treatment and control groups regarding
changes in working time amounts to approximately 1 % point. In the treatment
group, working time also increased most at the 25th percentile of the working time
distribution, from approximately 17 h per week to approximately 20 h per week.
Figure 1: Changes in hourly wages by treatment status along the wage distribution. Source: SES 2014,
ES 2015, unweighted data, own calculations. Notes: The y-axis shows changes in percentages. The x-axis
shows percentiles of the distribution of hourly wages. The establishments affected by the minimum
wage are those that had at least one employee paid less than 8.50 euros per hour in 2014.
Effects of the German Minimum Wage 197

5.2 Results from Difference-in-Differences Analysis
5.2.1 Main Results
The results from difference-in-differences regressions with control variables show
that the introduction of the minimum wage raised the mean hourly wages of em-
ployees in minimum wage establishments by up to 5.9 % (Table 3). The effect on the
average wage of low-wage employees in minimum wage establishments is consid-
erably greater, amounting to up to 13.7 %.
11
Although the overall minimum wage
effect of approximately 6 % is similar in size to the estimated effects in previous
studies, the result implies that the measured impact on affected low-wage workers is
more than twice as large based on the SES/ES data. Studies based on the GSOEP
conducted comparisons of workers who earned less than the minimum wage in 2014
to workers with earnings just above the minimum wage (Bachmann et al. 2020;
Burauel et al. 2018; Caliendo et al. 2023). They found a positive effect of the minimum
wage introduction on hourly wages amounting to approximately 6 %.
Table :Minimum wage effects on hourly wages, monthly wages and working time.
All employees Low-wage employees
Panel A: hourly wages
Year  .a
−.b
Treatment  .a.a
Panel B: monthly wages
Year  .a
−.
Treatment  .a.a
Panel C: working time
Year  −.a
−.
Treatment  −.a
−.a
Observations , ,
Establishment FE Yes Yes
Control variables Yes Yes
Source: SES ,ES, unweighted data, own calculations. Notes: OLS estimation including fixed establishment
effects. The outcome variables are presented in logarithmic form. Treatment refers to a dummy variable indicating
establishments that had at least one employee paid less than . euros per hour in . The included control variables
are employees’highest educational degree, age, age squared, type of employment in the full-time, part-time and
marginal employment categories, a dummy for fixed-term employment and a dummy for female gender. Confidence
level: ap<.,bp<.,cp<..
11 Afixed low-wage threshold of hourly wages lower than 10.05 euros has been applied to include
employees with a round value of 10 euros per hour. The low-wage thresholds reported by the Federal
Statistical Office are close to 10 euros in 2014 and 2015.
198 C. Ohlert

In contrast to the same studies, I find significant positive effects of the minimum
wage introduction on the monthly wages of employees in minimum wage estab-
lishments. It amounts to up to 2.7 %, on average, and to up to 7.9 % for low-wage
employees in minimum wage establishments. These findings are therefore in line
with (Bossler and Schank 2023), who found positive effects of approximately 4.4 % on
monthly wages.
Ifind negative effects of the minimum wage on working time of
approximately −3.1 % in total and approximately −5.7 % for low-wage employees.
Other studies found similar effects on working time of approximately −5%
(Bachmann et al. 2020; Bonin et al. 2018; Bossler and Gerner 2020; Caliendo et al.
2023). I find that the relative reductions in working time are smaller than the
relative increases in hourly wages. The results thus confirm that in the short term,
working time adjustments have diminished increases in monthly earnings
compared to increases in hourly wages. However, working time reductions did not
entirely offset the positive impact of the introduction of the minimum wage on
monthly earnings.
There are distinct differences in the bite of the minimum wage between East
Germany and West Germany. Approximately 21 % of employees in East Germany and
approximately 9 % of employees in West Germany had an hourly wage below 8.50
euros in 2014 (Mindestlohnkommission 2020: 56). Accordingly, a larger impact of the
minimum wage could be expected in East Germany.
Separate estimations for East and West Germany show that the effects of the
minimum wage on wages and working time were indeed clearly greater in East
Germany (see Table 4). Relative to employees in establishments without minimum
wage workers, average hourly wages increased by approximately 4.0 % more in
minimum wage establishments in West Germany and by approximately 10.2 % more
in East Germany. Furthermore, the minimum wage introduction raised the mean
wage of low-wage employees in minimum wage establishments by approximately
11.2 % in West Germany and by approximately 16.0 % in East Germany.
The measured additional increase in average monthly wages in minimum wage
establishments in West Germany amounts to 1.4 % but is statistically insignificant. In
East Germany, average monthly wages increased by approximately 5.8 % due to the
minimum wage. The measured impact on the monthly wages of low-wage employees
is again larger than on average for all employees in minimum wage establishments.
It amounts to approximately 6.0 % in West Germany and approximately 9.9 % in East
Germany. Since earnings are lower, on average, in East Germany than in West
Germany, the observed minimum wage effects cause some convergence of the wage
level between regions.
The impact of the minimum wage introduction on working time is also some-
what stronger in East Germany than in West Germany. In West Germany, working
Effects of the German Minimum Wage 199

time decreased, on average, by approximately 2.6 % more among employees in
minimum wage establishments than among those in other establishments. In East
Germany, the respective estimate is −4.3 %. Working time reductions were
slightly stronger among low-wage workers than on average in minimum wage
establishments. There was a decrease in working time of approximately 5.1 % among
low-wage employees in West German minimum wage establishments and of
approximately 6.1 % in East German minimum wage establishments. Since
contractual working time is, on average, greater in East Germany than in West
Germany, the observed minimum wage effects contribute to some convergence in
working time between the regions.
5.2.2 Heterogeneity Results by Type of Employment
The effects of the minimum wage on the average hourly wages of different groups of
workers are usually greater for groups with a higher bite of the minimum wage,
i.e. groups with a greater share of affected workers. Additionally, workers may
experience differential minimum wage effects by type of employment if there are
differences by group a) in the distance to the minimum wage for affected workers,
Table :Minimum wage effects in East Germany and West Germany.
All employees Low-wage employees
West Germany East Germany West Germany East Germany
Panel A: hourly wages
Year  .a.a
−.a.
Treatment  .a.a.a.a
Panel B: monthly wages
Year  .b.b
−. −.
Treatment  . .a.b.a
Panel C: working time
Year  −.b
−. −. −.
Treatment  −.a
−.a
−.b
−.a
Observations , , , ,
Establishment FE Yes Yes Yes Yes
Control variables Yes Yes Yes Yes
Source: SES ,ES, unweighted data, own calculations. Notes: OLS estimation including fixed establishment
effects. The outcome variables are presented in logarithmic form. Treatment refers to a dummy variable indicating
establishments that had at least one employee paid less than . euros per hour in . The included control variables
are employees’highest educational degree, age, age squared, type of employment in the full-time, part-time and
marginal employment categories, a dummy for fixed-term employment and a dummy for female gender. Confidence
level: ap<.,bp<.,cp<..
200 C. Ohlert

b) regarding differential spillover effects on hourly wages above the minimum
wage, or c) concerning remaining employees below the minimum wage due to
noncompliance or exceptions from the minimum wage.
Table 5 shows that the bite of the minimum wage was greater for part-time
workers and substantially greater for marginally employed workers than for full-
time employees. Approximately 43 % of employees in marginal employment
received an hourly wage below 8.50 euros in 2014. Additionally, the average wages of
employees who were affected by the minimum wage were lower for marginal
employees than for part-time or full-time employees. Hence, the impact of the
minimum wage introduction can be expected to be the largest among employees in
marginal employment.
Reductions in working time are particularly likely to occur among marginal
employees since their monthly gross earnings had to be below the administered
threshold of 450 euros, despite rising hourly wage rates. According to surveys on
working time preferences, part-time workers in Germany wish to increase their
working hours, while full-time employees wish to reduce their working hours
(Harnisch, Müller, and Neumann 2018). Therefore, the effects of the minimum wage
on working time are likely to differ between part-time and full-time workers.
Figure 2 provides a descriptive overview of changes in the respective outcome
variables in establishments that were affected by the introduction of the mini-
mum wage compared to other establishments. In establishments affected by the
minimum wage, the growth in hourly wages was greater for marginal employ-
ment and somewhat greater for full-time employment than for part-time
employment(Figure2).Thewagegrowthofhourlywageswasclearlylowerfor
all three types of employment in establishments not affected by the minimum
Table :Distribution of hourly wages by type of employment in .
Full-time Part-time Marginal
employment
Year   
Mean . . .
Percentiles
P. . .
P . . .
P . . .
P . . .
Share of employees below .€. . .
Number of observations , , ,
Source: SES , unweighted data, own calculations.
Effects of the German Minimum Wage 201

wage. Monthly wages increased to a similar extent among full-time employees and
part-time employees in establishments affected by the minimum wage. However,
in part-time employment, monthly wages also increased in establishments not
affected by the minimum wage. In comparison, increases in monthly wages were
smaller among marginally employed workers and were present only in estab-
lishments affected by the minimum wage. As noted in Section 3, individual
transitions between different types of employment cannot be tracked in the SES/
ES data. Therefore, minimum wage-induced transitions from marginal employ-
ment to part-time employment, which occur by definition when the threshold of
monthly earnings of 450 euros is exceeded, are not captured in the changes re-
ported here. Previous studies showed that the total number of transitions between
marginal employment and regular employment increased from 52 to 104 thousand
between January 2015 and January 2014, which was significantly greater than that
in previous years (Mindestlohnkommission 2020: 91 ff.). According to the data of
the IAB Labour Market Survey, 85 % of the transitions from marginal employment
to employment subject to social security contributions in 2015 were conversions
withinthesamecompany(vomBergeetal.2016). In addition, there was a decline
in the share of marginally employed versus employees subject to social insurance
contributions in the workforce of establishments, which was particularly pro-
nounced in establishments of small and medium-sized enterprises (Bonin et al.
2018; Pestel et al. 2020).
Figure 2: Changes in outcome variables by treatment status and type of employment. Source: SES 2014,
ES 2015, unweighted data, own calculations. Notes: Establishments affected by the minimum wage are
those that had at least one employee paid less than 8.50 euros per hour in 2014.
202 C. Ohlert

Working hours decreased slightly in full-time employment and more so in
establishments affected by the minimum wage. Working hours increased in part-
time employment, but the increase was lower in establishments affected by the
minimum wage than in unaffected establishments (Figure 2). The number of working
hours decreased most clearly among those with marginal employment in estab-
lishments affected by the minimum wage, by approximately 11 %. This finding
reflects that the minimum wage together with the statutory upper earnings limit of
450 euros per month for marginal employment implies a de facto upper limit in
working time.
Difference-in-differences estimates of the minimum wage effects on hourly
wages by type of employment show that there is a similar positive impact of the
minimum wage on full-time and part-time employees, amounting to approxi-
mately 4.8 %, on average (see Table 6, Panel A).
12
Compared to the reference group
of full-time employees, the effect on the hourly wages of marginal employees is on
average approximately 6.3 % points greater. The effects of the minimum wage are
larger for each employment group when only low-wage employees are consid-
ered in the analysis. The positive effect on the hourly wages of low-wage
employees amounts to approximately 10.8 % for full-time employees, which is
2.4 % points greater among part-time employees and approximately 6.3 % points
greater among marginal employees. These results clearly show greater effects of
the minimum wage than reported in previous studies based on the GSOEP for all
three types of employment. Similar to the GSOEP studies, the effects on hourly
wages are greater among marginally employed workers than among regular
workers.
The growth of the monthly wages of full-time employees was on average
approximately 1.4 % greater for in minimum wage establishments than in other
establishments. The difference among part-time workers was not statistically
significantly different from that among full-time employees, and it was approxi-
mately 5.3 % points greater among marginal employees. The respective measured
impact of the minimum wage on monthly wages was greater among low-wage
employees. Compared to low-wage full-time workers, it was 7.3 % points greater
among low-wage part-time employees and 3.6 % points greater among marginal
employees.
On average, reductions in working time amounted to −3 % among full-time
employees in minimum wage establishments compared to full-time employees in
12 The effect for full-time employees is given by the coefficient “Treatment 2015”. The effect for
part-time and marginal employees is given by the sum of the coefficients “Treatment 2015”and the
respective interactions “Part-time ×treatment”and “Full-time ×treatment”.
Effects of the German Minimum Wage 203

other establishments (see Table 6, panel C). The working time reduction due to the
minimum wage is approximately 2.3 % points smaller among part-time employees
in minimum wage establishments. The respective coefficient for marginal em-
ployees is not significantly different from that for full-time employees. The minimum
wage-induced reduction in working time among low-wage employees amounts to
Table :Minimum wage effects by type of employment.
All employees Low-wage
employees
Panel A: hourly wages
Year  .a
−.b
Treatment  .a.a
Full time Reference
Part time −.a
−.a
Marginal employment −.a
−.a
Full time ×treatment  Reference
Part time ×treatment  −. .a
Marginal employment ×treatment  .a.a
Panel B: monthly wages
Year  .a
−.
Treatment  .c.b
Full time Reference
Part time −.a
−.a
Marginal employment −.a
−.a
Full time ×treatment  Reference
Part time ×treatment  . .a
Marginal employment ×treatment  .a.c
Panel C: working time
Year  −.a
−.
Treatment  −.a
−.a
Full time Reference
Part time −.a
−.a
Marginal employment −.a
−.a
Full time ×treatment  Reference
Part time ×treatment  .c.b
Marginal employment ×treatment  −. −.
Observations , ,
Establishment FE X X
Control variables X X
Source: SES ,ES, unweighted data, own calculations. Notes: OLS estimation including fixed establishment
effects. The outcome variables are used in logarithmic form. Treatment refers to a dummy variable indicating
establishments that had at least one employee paid less than . euros per hour in . The included control variables
are employees’highest educational degree, age, age squared, a dummy for fixed-term employment and a dummy for
female gender. Confidence level: ap<.,bp<.,cp<..
204 C. Ohlert

approximately minus 6 % for full-time jobs. It is again of similar size among marginal
employees and it is by 4.9 and thus much smaller among part-time employees.
The relatively small effect on the working time of part-time workers explains the
relatively large positive effect of the minimum wage on the monthly earnings of low-
wage part-time workers.
6 Robustness Check
As a robustness check, a weighted control group approach is applied, which bal-
ances the pretreatment means of the respective outcome variable and a set of
covariates (see Appendix Tables A1–A3). This approach is similar to matching
pretreatment outcomes, but it has the advantages of easier implementation and
greater functional flexibility (Hainmueller 2012; Hainmueller and Xu 2013). For the
robustness check, the data are fully aggregated at the establishment level because
this allows to apply the pretreatment weights for establishments in the control
group also to the posttreatment data, which retains a fixedtreatmentandcontrol
group.
In the main analysis, minimum wage effects were identified by establish-
ments being affected by the minimum wage or not. Control variables at the
employee level were useful for exploiting the available information at the
employee level and thus for increasing the precision of the estimated minimum
wage effects. They are, however, not relevant for the identification of the mini-
mum wage effect, which is estimated based on variation at the establishment level
(Lechner 2010). Hence, the analysis with data aggregated to the establishment
level should yield similar difference-in-differences estimates when establish-
ments are weighted by the number of employee observations in each establish-
ment. The respective results are presented in column two of Table 7 and can be
compared to the main results (from Table 3) in column one of Table 7. Column
three of Table 7 presents the results from balancing pretreatment outcomes prior
to the estimation of the DID model (and weighting by the number of employee
observations in each establishment).
13
The control variables from the main
analysis are also balanced. All variables are aggregated at the establishment level,
resulting in the shares of education groups and employment types, etc., in
establishments.
13 Results from DID-estimation with and without entropy balancing without weighting the aggre-
gated establishment data by employees per establishment are larger in magnitude for all three
outcomes.
Effects of the German Minimum Wage 205

The results regarding hourly wages show that the difference-in-differences
estimates with data aggregated to the establishment level are very similar to the
main results when no balancing of the control group is conducted (see Table 7,
columns 1 and 2). As expected, balancing the control group results in a slightly
lower estimate (by approximately 1 % point) of the measured minimum wage
effect on hourly wages. This finding implies that the minimum wage effect on
hourly wages from the main model could be overestimated to a small extent due to
systematic differences in the composition of the treatment and control group
establishments, which have not been captured by control variables and are
correlated not only with the pretreatment mean hourly wage but also with its
change over time.
Table :Robustness check.
()()()
Main results from Table 
(data on employees in
establishments)
Data aggregated to
establishment level
Data aggregated to
establishment level,
balanced control group
Weighted by employee observations per
establishment
Panel A: hourly
wages
Year  .a.a.a
Treatment  .a.a.a
Panel B: monthly
wages
Year  .a.b.a
Treatment  .a.a.
Panel C: working
time
Year  −.a
−.a
−.a
Treatment  −.a
−.a
−.
Number of
establishments
–, ,
Number of
observations
, ––
Source: SES ,ES, own calculations. Notes: OLS estimation. The outcome variables are presented in logarithmic
form. Balancing of the control group using entropy balancing (see Appendix Tables A–A). The covariates included in
balancing the control group are the share of employees in the establishment by education, type of employment and
gender, a dummy for East/West Germany, three categories of establishment size and a dummy for establishments
covered by a collective bargaining agreement. Confidence level: ap<.,bp<.,cp<..
206 C. Ohlert

The results with respect to working time and monthly wages seem to be less
robust according to the balanced control group approach. Regarding working time,
the negative minimum wage effect is also reduced in the balancing approach by
approximately 1 % point. Because the average effect on working time was too small to
begin with, the remaining estimate is not significantly different from zero. This result
implies that the minimum wage effect on average working time in minimum wage
establishments might be overestimated in the main model.
Regarding monthly wages, the minimum wage effect is relatively strongly
reduced by the balancing approach and is approximately 3 % points smaller. The
remaining estimate is not statistically significant from zero. This result implies that
the minimum wage effect on monthly wages from the main analysis might be
overestimated due to systematic differences between the treatment and control
groups. As presented in Appendix Tables A1–A3, the pretreatment difference in
average monthly earnings between minimum establishments and other establish-
ments is particularly large. Controlling for these differences markedly changes the
DID results.
A similar robustness check with balanced control groups was not feasible for
most of the subgroups because the entropy balancing estimation did not converge.
Consequently, the results for subgroups from the main model must be interpreted
more cautiously. It is nevertheless highly reasonable that minimum wage effects are
larger than average among subgroups that are affected to a high extent by the
minimum wage, as is the case for low-wage employees, employees in East Germany
and marginal employees.
7 Conclusion
This study contributes to understanding the short-term effects of the minimum wage
introduction in Germany on hourly wages, monthly earnings and working time
based on previously unused linked employer–employee panel data, which combines
the SES 2014 and the ES 2015. We find that the effect of the introduction of the
statutory minimum wage on the average hourly wages of employees in minimum
wage establishments is as high as 5.9 %. Due to negative effects on average working
time of approximately minus 3.1 %, the effects on monthly gross earnings are smaller
but still amount to up to 2.7 % on average.
The effects of the minimum wage introduction on monthly wages and
workingtimehavebeenatopicofdebate,withsomestudiesfinding no effects
(in the short-run) and others finding a significantly positive impact. Our results
confirm a significant positive effect on employees’monthly wages in minimum
wage establishments, which is greater among low-wage employees. Similar
Effects of the German Minimum Wage 207

to other studies, the effects on monthly wages are smaller than the effects on
hourly wages because of reductions in working hours. Hence, the finding that the
minimum wage effect on monthly earnings has been reduced but not offset by
reductions in working time is corroborated. The results regarding the average
effects on monthly earnings and working time of employees in minimum wage
establishments could, however, not be confirmed in a robustness check with a
balanced control group, which calls for a cautious interpretation of these
outcomes.
The results further indicate that the minimum wage effects on earnings were
greater than average among low-wage employees in eastern Germany compared to
those in western Germany and for part-time employees. The positive effect of the
introduction of the minimum wage on the hourly wages of low-wage employees
amounts to 13 %, which is substantially greater than that found in previous studies
based on the GSOEP that focused on employees with hourly wages below 8.50 euros
(there is an effect of approximately 6 %). However, these studies cannot be compared
directly because they differ in many aspects.
Our results on heterogeneous minimum wage effects by type of employment
suggest that the hourly pay of low-wage part-time employees and marginal
employees could catch up compared to that of low-wage full-time employees. The
gains in monthly gross earnings were largest among part-time workers and
therefore benefitted women more than men (also see Ohlert 2023). The results
further indicate that part-time employees, particularly marginally employed
workers, benefit from the minimum wage due to the possibility of receiving similar
earnings with fewer hours of work. The possibility of differentiating results by type
of employment based on many observations is an advantage of the applied SES/ES
data.
The overall finding of relatively high minimum wage effects on both hourly
wages and monthly wages corroborates previous evidence that employees actually
receive higher earnings due to the introduction of the minimum wage. Higher gross
earnings are important to low-wage earners, even if they still depend on transfer
payments due to low working hours or household needs (Baumann and Bruttel 2020;
Bruckmeier and Bruttel 2021). Hence, the introduction of the minimum wage in
Germany has improved the opportunities for low-wage earners to achieve an
independent income.
Acknowledgments: I would like to thank Arne Baumann, Mario Bossler, Matthias
Dütsch and Ralf Himmelreicher for very helpful comments and suggestions. The
service of the Research Data Centre of the Statistical Office Berlin-Brandenburg is
gratefully acknowledged.
208 C. Ohlert

Appendix
Table A:Full regression results from main model (complementing Table ).
Hourly wages Monthly wages Working time
All
employees
Low-wage
employees
All
employees
Low-wage
employees
All
employees
Low-wage
employees
Year  .a
−.b.a
−. −.a
−.
Year  ×treatment group .a.a.a.a
−.a
−.a
Employees with no vocational degree Reference Reference Reference
Employees with a vocational degree .a.a.a.a.a.a
College/university degree .a.a.a.b.a.
Unknown vocational degree .a
−. .a
−. .a
−.
Age .a.a.a.a.a.a
Age
−.a
−.a
−.a
−.a
−.a
−.a
Full-time employees Reference Reference Reference
Part-time employees −.a
−.a
−.a
−.a
−.a
−.a
Marginal employees −.a
−.a
−.a
−.a
−.a
−.a
Fixed term contract −.a
−.a
−.a
−.a
−.a
−.b
Female −.a
−.a
−.a
−.a
−.a
−.c
Establishment size: up to  employees Reference Reference Reference
Establishment size: – employees −. . −. . −. −.
Establishment size:  or more employees −. . −. −. −. −.
Constant .a.a.a.a.a.a
Observations , , , , , ,
Source: SES ,ES, own calculations. Notes: Confidence level: ap<.,bp<.,cp<..
Effects of the German Minimum Wage 209

Table A:Pre- and posttreatment balancing statistics of log hourly wages and covariates (means).
Treated Controls
Without
balancing
Balanced
     
Log hourly wage . . . . . .
Establishments in West Germany . . . . . .
Establishment size (categories –). . . . . .
Establishments covered by collective bargaining . –. –. –
Share of employees with no vocational degree in
establishment
. . . . . .
Share of employees with vocational degree in establishment . . . . . .
Share of employees with college/university degree . . . . . .
Share of employees with unknown vocational degree . . . . . .
Share of women in establishment . . . . . .
Share of full-time employees in establishment . . . . . .
Share of part-time employees in establishment . . . . . .
Share of marginal employees in establishment . . . . . .
Notes: For dummy variables, the mean reflects the respective share of establishments in the treatment and the control
group. The collective bargaining status of establishments was not measured in the ES .
Table A:Pre- and posttreatment balancing statistics of log monthly wages and covariates (means).
Treated Controls
Without
balancing
Balanced
     
Log monthly wage . . . . . .
Establishments in West Germany . . . . . .
Establishment size (categories –). . . . . .
Establishments covered by collective bargaining . –. –. –
Share of employees with no vocational degree in
establishment
. . . . . .
Share of employees with vocational degree in establishment . . . . . .
Share of employees with college/university degree . . . . . .
Share of employees with unknown vocational degree . . . . . .
Share of women in establishment . . . . . .
Share of full-time employees in establishment . . . . . .
Share of part-time employees in establishment . . . . . .
Share of marginal employees in establishment . . . . . .
Notes: For dummy variables, the mean reflects the respective share of establishments in the treatment and the control
group. The collective bargaining status of establishments was not measured in the ES .
210 C. Ohlert

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Share of employees with vocational degree in establishment . . . . . .
Share of employees with college/university degree . . . . . .
Share of employees with unknown vocational degree . . . . . .
Share of women in establishment . . . . . .
Share of full-time employees in establishment . . . . . .
Share of part-time employees in establishment . . . . . .
Share of marginal employees in establishment . . . . . .
Notes: For dummy variables, the mean reflects the respective share of establishments in the treatment and the control
group. The collective bargaining status of establishments was not measured in the ES .
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