Incentivizing last-resort social assistance clients: Evidence from a Finnish policy experiment

Abstract

In 2002, the Finnish government introduced an earnings disregard experiment aimed at improving the incentives of low-income individuals who receive last-resort social assistance. The aim of the experiment was to reduce unemployment by providing social assistance clients better incentives to receive at least temporary or part-time work. This paper evaluates the employment effects of the experiment as an event study using coarsened exact matching (CEM) and difference-in-differences. On average, the results show no employment effects, but there is some evidence of positive employment effects on women.

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Vol.:(0123456789)
International Tax and Public Finance (2023) 30:1–19
https://doi.org/10.1007/s10797-022-09739-9
1 3
Incentivizing last‑resort social assistance clients: Evidence
fromaFinnish policy experiment
HeikkiPalviainen1
Accepted: 11 March 2022 / Published online: 28 May 2022
© The Author(s) 2022
Abstract
In 2002, the Finnish government introduced an earnings disregard experiment aimed
at improving the incentives of low-income individuals who receive last-resort social
assistance. The aim of the experiment was to reduce unemployment by providing
social assistance clients better incentives to receive at least temporary or part-time
work. This paper evaluates the employment effects of the experiment as an event
study using coarsened exact matching (CEM) and difference-in-differences. On
average, the results show no employment effects, but there is some evidence of posi-
tive employment effects on women.
Keywords Difference-in-differences· Making work pay· Earnings disregard·
Welfare
JEL Classification C93· H53· I38· J68
1 Introduction
Making work pay policies have been introduced to improve financial incentives to
accept work and alleviate poverty. These aims are vital within social transfer sys-
tems that impose high marginal taxes on low-income individuals. While in-work
benefits are often implemented through tax credits, earnings disregards function
within a social transfer system. They imply that benefits are withdrawn less than in a
one-for-one ratio when a recipient starts to earn income.
In 2002, a three-year experiment—nowadays a permanent policy—was intro-
duced in Finland allowing for a monthly earned income disregard up to €100 for
social assistance recipients. In 2005, the maximum amount was increased to €150.
Before the reform, social assistance was reduced one-for-one when a recipient
started to earn income. The reform is effectively equivalent to reduced tax rates,
* Heikki Palviainen
heikki.palviainen@tuni.fi
1 Tampere University, Tampere, Finland
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H.Palviainen
1 3
consequently leading to an increase in the effective wage rate. Standard economics
theory would predict a higher labour supply for low-income individuals as a result
of the reform.
The purpose of this paper is to evaluate the Finnish earnings disregard experi-
ment using a quasi-experimental design. This evaluation is based on high-quality
individual-level register data that cover the years 1995–2007. While many of the
in-work benefit programs are targeted at specific demographic groups such as work-
ing families or single mothers, the Finnish experiment was targeted at all social
assistance clients without additional eligibility conditions. The earnings disregard
is evaluated as an event study. A difference-in-differences model is combined with
coarsened exact matching and individual fixed effects. The control group is formed
of means-tested labour market subsidy recipients. Labour market subsidy is meant
for unemployed persons who enter the labour market for the first time or who have
not worked long enough so that they are not entitled to earnings-related unemploy-
ment insurance. On average, the results show no employment effects, but there is
some evidence of women’s positive employment response to the earnings disregard.
This study is motivated by several factors. First, the maximum €150 monthly
income increase can be significant for individuals living under the poverty line.
Second, last resort-social assistance recipients are a substantial and policy-relevant
group for their high rate of unemployment and social exclusion. For example in
2002, when the policy was introduced, 8.3% of the population received last resort
social assistance. Last, quasi-experimental labour supply evidence related to making
work pay policies is limited in Nordic countries1.
This paper is organized in the following way. The next section introduces related
literature and contributions. The third section describes the social security system
in Finland and provides details on the experiment. The fourth section describes the
empirical strategy and the data. The fifth section provides the results and discusses
the sensitivity of the estimations, and the last section concludes.
2 Related literature
Internationally in-work benefits are widely used and researched. More than half of
the OECD countries have implemented an in-work benefit (Immervoll & Pearson,
2009). Most of the research has focused on the earned income tax credit (EITC) in
the USA and its close counterpart in the UK. The EITC is a refundable tax credit for
low-income families with qualifying children. Several studies have found the EITC
increased the labour supply at the extensive margin but not at the intensive mar-
gin (Eissa & Liebman, 1996; Eissa & Hoynes, 2004; Hotz & Scholz, 2006). For
1 To our knowledge the effects of in-work benefits or earnings disregards on social assistance clients
have not been studied in a Nordic country before. Edmark etal. (2016) evaluated the Swedish earned
income tax credit, but they conclude that the reform cannot be evaluated using a quasi-experimental
design. Related to the same EITC scheme in Sweden, Laun (2017) utilised a larger EITC for older work-
ers, above the age of 65. There are also some studies on supplementary UI benefits. Kyyrä etal. (2013)
studied a supplementary UI benefit in Denmark, and Kyyrä (2010)) studied a similar scheme in Finland.
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Incentivizing last‑resort social assistance clients: Evidence…
example, Nichols and Rothstein (2015) review the literature on the EITC. Recently,
Kleven (2019) has questioned the consensus related to the effectiveness of the EITC
reform. His estimations imply that the earlier results were driven by confounding
effects of welfare reform and a booming macroeconomy. The British Working Fami-
lies’ Tax Credit (WFTC) was introduced in 1999. In contrast to the EITC, the Brit-
ish tax credit has a minimum 16 hours of work a week condition and no phase-
in region. Francesconi and Van der Klaauw (2007) found a large seven percentage
point increase in single mothers’ employment rate. Blundell etal. (2005) found that
the WFTC and related reforms increased single parents’ employment by around
3.6% points. Since other reforms were introduced at the same time as the WFTC,
several other studies use a structural model. For example, Brewer etal. (2005) found
that the reform increased the labour supply of single mothers by around 5.1 per-
centage points. The EITC and its British counterpart work through the tax system.
Some studies have found substantial behavioural effects on labour supply for welfare
recipients. The Canadian Self-Sufficiency Project was designed to provide evidence
of the effects of a generous financial incentive on long-term welfare recipients. One-
third of the single-parent welfare recipients began to work full-time (at least 30
hours a week), but the temporary program did not have a lasting effect on wages or
receiving welfare (Michalopoulos etal., 2005). Lemieux and Milligan (2008) pro-
vided labour supply evidence from a substantial incentive change in social assis-
tance. In Quebec, social assistance recipients under the age of 30 without children
received benefits 60% lower than the recipients older than 30. Using a regression
discontinuity design, the authors found that the employment rate dropped from three
to five percentage points after the increase in social assistance payments.
Others have studied income disregard policies implemented through the social
transfer system. Knoef and Van Ours (2016) studied an earnings disregard experi-
ment for single mothers in Holland. In the Dutch experiment, single mothers were
allowed to earn €4 per hour up to €120 per month without having it deducted from
their welfare benefits. Using a triple difference-in-differences approach, they found a
positive employment effect for immigrants but a small effect for native single moth-
ers. Matsudaira and Blank (2014) evaluated changes in earnings disregards for US
welfare recipients following a welfare reform in 1996. Although some states intro-
duced large earnings disregards, they found little evidence on increased labour sup-
ply because only few women used the earning disregards. These results imply that
the labour supply effect may be different depending on whether the in-work benefit
is implemented through the tax or social transfer system.
This paper contributes to the earlier literature in two ways. First, since everyone
receiving social assistance was eligible, labour supply responses can be compared
across many demographic groups. The previous literature has typically focused on
narrow demographic groups, such as single mothers or families with dependent chil-
dren. Second, the literature is mainly focused on the USA and the UK with rela-
tively low benefits and high incentives. Finland is representative of a Nordic country
with low incentives and high benefits. Nordic countries tend to have a high rate of
social spending but a higher rate of unemployment linked to a different institutional
setting.
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3 Background
3.1 Social assistance inFinland
According to the constitution of Finland, everyone is entitled to basic income and
care necessary for a dignified life. Social assistance is meant to provide this last-
resort minimum level of income. It is means-tested at the family level and generally
granted on a monthly basis. Social assistance is meant to be temporary and second-
ary in the sense that it comes on top of other primary benefits such as housing allow-
ance and labour market subsidy. However, primary benefits have become increas-
ingly insufficient to cover individuals’ and families’ living expenses causing overlap
with last-resort social assistance.
A deep recession at the beginning of the 1990s increased the number of social
assistance clients. The share of individuals receiving social assistance nearly dou-
bled from 6.3 to 11.9% between 1990 and 1996. Both poverty, at awide range of
measures, and inequality rose after the recession (Riihelä, 2009). After 1996, the
share of individuals receiving social assistance started to decline until the financial
crisis in 2008. However, long-term dependency on social assistance has increased,
andthe average length of social assistance reached six months in 2010 (Kauppinen
et al., 2013,p. 40). In an effort to reduce the number of people receiving social
assistance and long-term unemployment, activation policy emphasizing individual
responsibility has become the guiding policy - the earnings disregard reform being
one example.
3.2 Eligibility forsocial assistance
All individuals living in Finland are entitled to receive social assistance. Eligibility
and entitlement amounts can be described by a simple formula:
where B describes the basic part of social assistance. The basic part is meant to
cover food, clothing, phone, transportation, Internet, basic health and small costs
for hobbies and leisure. In 2021, this minimum level of basic income was €504.06
a month for an individual who lives alone. The basic part is a function of house-
hold composition. H describes necessary housing expenses and covers, for example
acceptable rent, electricity and heating. A describes discretionary expenses that can
be covered with supplementary and preventive social assistance. They are meant to
support social assistance clients’ independent living. Supplementary social assis-
tance covers extraordinary expenses, such as sudden housing costs or expenses
related to parenting. Preventive social assistance can be granted to ease sudden
adverse changes in finances.
Y describes family members’ summed earned income and primary benefits. Y
includes earned income and assets that are easily liquidated and not necessary for
basic living or work. Y also includes primary benefits, such as child benefits, labour
market subsidy and housing allowance. The labour market subsidy and housing
(1)
SA = max[0;(B+A+H)−Y],
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Incentivizing last‑resort social assistance clients: Evidence…
allowance are means-tested. Because multiple benefits are means-tested and extra
benefits can be collected back at a later stage, it is often difficult to know how extra
earnings affect disposable income creating income uncertainty. If the family mem-
bers’ summed income in equation1 is smaller than acceptable expenses, an appli-
cant is entitled to social assistance.
3.3 Set upoftheexperiment
The earnings disregard experiment became effective in April 2002. It started as a
three-year experiment but became a permanent policy in 2014. It allowed for social
assistance clients to keep at least 20% of their earned income up to €100 (€150 as
of 2005) a month without having it deducted from their social assistance payments.
The experiment was household-specific so that one household was entitled to only
one maximum €150 amount disregarded irrespective of the number of earners in a
household. This creates relatively a larger incentive effect for small households. The
aim of the experiment was to decrease unemployment by providing social assistance
clients incentives to take at least temporary or part-time work. Ideally, the goal of
the experiment can be summarized as a three-stage model (Hiilamo etal., 2004, p.
68):
• In the first stage, a social assistance client has no earned income or very little.
• In the second stage, the experiment provides incentives for extra income. The
new income stays at a level at which the social assistance client is entitled to the
disregarded earnings amount but does not lose his or her social assistance.
• In the third stage, the social assistance recipient is attached to the labour market
due to higher incentives and has no need or little need for social assistance.
Figure 1 shows a stylized budget constraint without the earnings disregard and
with the disregard excluding other benefits. The budget constraints are calculated
for an individual who lives alone using the basic social assistance amount (€378.54)
in 2005.2 The social assistance amount depends on household size and individual
conditions, and the budget constraints differ accordingly. The vertical axis shows
disposable income as a function of earned income. The BC line indicates dispos-
able income before the earnings disregard experiment.3 For a social assistance client
with a low earning potential, it is not optimal to accept irregular or temporary work.
The BDA and BEFA lines present the budget constraints after the earnings disregard
experiment is introduced.
The social assistance law allowed municipalities and social workers to decide the
disregard percentage between 20 and 100% they applied to earned income (at most
€150). The lines BDA and BEFA present the budget constraints at these extremes.
When 20% of the earned income is disregarded, the maximum monthly benefit from
2 The budget constraints do not take into account interactions from other social transfers and benefits.
The social assistance is dependent on the household type and housing costs which generally increase the
amount of social assistance.
3 A negligible amount of earnings and gifts was already disregarded before and after the experiment.
This amount was generally €50, but the practice varied across municipalities.
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H.Palviainen
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the experiment is €100, and after earning €478.54, an individual is no longer eligi-
ble for social assistance. This indicates a small incentive effect at a very low income.
On the CD line there may be some individuals who may reduce their labour supply
after the experiment, but this case seems quite trivial. The line BEFA shows the
budget constraint at the other extreme when 100% of the earned income is disre-
garded. Here, it is optimal to work until point E - that is to earn €150. For more than
€150 in earnings, the marginal tax rate is 100%.
At the time of the experiment, there was no uniform policy on how the earnings
disregard policy was implemented across different municipalities. Likely because of
the high volume of social assistance applications and due to cost reasons, in most
municipalities the computing systems were set to automatically disregard the mini-
mum 20%. Still, social workers used discretion in applying the disregard percent-
age.4 Because it is not known how much was disregarded, this is an intention-to-
treat research setting.
Fig. 1 Budget constraints for single persons before and after the earnings disregard experiment. Note: the
lines BCA show the old policy. The lines BDA show the budget constraint when 20% is disregarded. The
lines BEFA show the budget constraint with €150 disregarded
4 Karjalainen etal. (2013,pp. 193–195) interviewed 142 social workers in nine municipalities and asked
how they applied the earnings disregard. Based on the social workers’ interviews in 2012, 47% usually
disregarded 20% of the earned income and 43% disregarded the maximum amount €150. Ten per cent of
the social workers disregarded between these extremes.
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Incentivizing last‑resort social assistance clients: Evidence…
4 Empirical strategy
4.1 Difference‑in‑differences withcoarsened exact matching
The aim of this paper is to causally evaluate the employment effects of the earnings
disregard experiment. Observable differing characteristics between the treatment
and control groups are balanced using coarsened exact matching (Iacus etal., 2012).
CEM coarsens the selected variables into strata and performs exact matching on the
coarsened data. The CEM algorithm allows for decreasing imbalance in any vari-
able without increasing imbalance in any other variables. This monotonic imbalance
property reduces model dependence accounting for interactions and nonlinearities.
An individual fixed effects model is estimated with the following specification:
where
𝛼i
and
𝛾
are individual and year fixed effects, respectively, and i denotes an
individual. The main identifying assumption is the parallel trends assumption, that
is the treatment and control groupswould have had parallel trends in the absence of
treatment. The main outcome variable
Yit
is yearly earnings. This is the most accu-
rate employment measure in the data, and it covers all years between 1995–2007.
The model is also estimated using work months as an outcome. This variable
includes the years 1997–2007 and does not contain entrepreneurs. Yearly earn-
ingsalso contain entrepreneurial income. The treatment variable D is defined solely
on a pretreatment period, that is, in 2001 (-1). This is because the earnings disregard
increased eligibility for social assistance, and there is likely some inflow to social
assistance in the post-treatment period. Period-1 is used as a reference category. The
regressions are estimated with CEM-weights, and the standard errors are clustered
at the individual level.
All variables are measured at the individual level. Although social assistance is
means-tested at the family level, it is granted to the applicant. The earnings disre-
gard was household-specific so that one household was entitled to a maximum €150
earnings disregard. In the means-testing, the social assistance applicant’s earnings
and spouse’s earnings were disregarded up to €150. Because social assistance is
(2)
Y
it =𝛼i+𝛾t+
5
∑
s=−7
s
≠−1
𝛽×1[t=s]×Di+𝜖it
,
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means-tested at the household level and the experiment changed spouses’ incentives,
the results are also estimated without social assistance clients’ spouses who belong
to the control group.
The labour market subsidy recipients form a similar group to social assistance
recipients. The labour market subsidy is a means-tested benefit provided by the gov-
ernment. It is meant for unemployed persons who enter the labour market for the
first time or who have not worked long enough so that they are not entitled to an
earnings related unemployment insurance. The labour market subsidy is paid on
weekdays only, and the paid amount was €33.78 a day in 2021. There is no duration
limit in the labour market subsidy. As a robustness check, the results are also esti-
mated using only home-owning labour market subsidy recipients as a control group.
This group does not receive social assistance for predominately exogenous reasons.
Home-owners are entitled to social assistance, but their earnings are higher on aver-
age, and they have more often a spouse to support their economic well-being.
4.2 Data andsample selection
This evaluation uses rich individual-based panel data collected by Statistics Finland.
The register-based data cover the years from 1995 to 2007, each year containing
more than 500 000 observations with a variety of income as well as socio-demo-
graphic and regional characteristics. The observations form a representative sample
of approximately 10% of the Finnish population. Ages 18–64 are included to reflect
primary working age. All variables are measured on a yearly level. Register-based
data sets from the experiment time do not contain monthly earnings that could be
linked to monthly social assistance. Using yearly measures likely adds some inac-
curacy to the results. Since social assistance is granted monthly, monthly data would
capture the experiment effect more precisely. Monthly data would capture a treat-
ment effect on those social assistance clients who did not receive it in 2001, but they
received it for some month(s) before the experiment in 2002. The benefit of yearly
measures is that the control group is to a larger extent formed of individuals and
families that were not eligible or did not apply for social assistance.
Table 1 shows how many months social assistance and labour market subsidy
were received in 2001. The reported values are for ages 18–64. Social assistance
recipients are more often short-term recipients. Table1 shows that 21.2% of social
assistance clients received it for onlya month, and 13.5% of labour market subsidy
recipients received it for one month. The empirical model does not capture positive
treatment effects on those social assistance clients who received social assistance in
2001 but not afterwards. Of all social assistance clients who received social assis-
tance in 2001, 64.9% received it in 2002, 55.6% in 2003, 47.1% in 2004 and 33.6%
in 2007.5 Twenty-two per cent (21.6%) of social assistance clients did not receive
social assistance on any consecutive year between 2002 and 2007.
5 The frequencies are author’s calculations from the data. The frequencies were calculated for social
assistance clients aged 18–64 in 2001.
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Incentivizing last‑resort social assistance clients: Evidence…
Table 1 Social assistance
and labour market subsidy
dependency in 2001
(1) The reported values are averages expect for the cumulative dis-
tribution function. Standard deviations are shown in parentheses.
(2) Labour market subsidy is granted for weekdays only. Labour
market subsidy months are calculated assuming that there are 21.5
weekdays in a month. Days below 10.75 are rounded upwards to one
month
Variable Social assistance Labour market subsidy
Months received 5.33 (3.95) 6.64 (4.05)
Cumulative month
distribution
1 21.17 13.51
2 35.13 22.02
3 44.99 30.61
4 52.0 37.49
5 58.39 44.23
6 63.73 51.37
7 68.55 56.83
8 73.04 62.13
9 77.51 67.18
10 82.20 71.97
11 88.01 77.16
12 100 100
Observations 17 375 21 238
Table 2 Descriptive statistics on labour market status in 2001
(1) The reported values are averages for earnings, work months and hourly wages (aged 18–64). Standard
deviations are shown in parentheses. (2) Main activity refers to activity in the last week of the year
Variable Social assistance Labour market subsidy
Earnings (€) 4679.0 (7135.1) 3256.8 (4617.5)
Months employed 3.63 (4.44) 3.12 (3.85)
Hourly wage (€) 9.09 (16.5) 8.30 (3.60)
Main activity, %
Employee 30.14 27.22
Unemployed 34.72 51.72
Student 13.09 9.77
Retiree 8.89 0.45
Disability retiree 0.30 0.16
Military or civilian servant 0.64 1.22
Outside the labour force 12.22 9.46
N17 375 21 169
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Table 2 shows descriptive statistics on labour market status and employment
in 2001 (aged 18–64). Social assistance clients have approximately €1400 higher
yearly earnings, and the earnings have considerably more variance. Receiving social
assistance can be very temporary, or it can become a long-term dependency. Short-
term recipients are more often students, they may be between jobs, or for various
reasons they have experienced a sudden but temporary loss of income. Table2 also
shows that hourly wages have more variation for social assistance recipients. The
higher share of short-term recipients and higher variance in earnings implies that
some of the social assistance clients have a reasonably good labour market position.
It is likely that these short-term recipients became employed for reasons unrelated to
the earnings disregard.
Table2 also shows the main activity in the last week of the year. The shares of
activity appear quite similar. For example, the share of employees and individuals
outside the labour force is similar between the social assistance and labour market
subsidy recipients. A distinctive characteristic is a larger share of retirees among the
social assistance recipients. Because retirees form a less relevant group for the stud-
ied scheme, they are dropped from the sample.
Table 3 Descriptive statistics for the selected sample
Treatment Control
Mean(Sd.) Freq. Mean(Sd.) Freq.
Earned income (€) 5592.5 (7486.3) 7137 4072.0 (4940.2) 6795
Months employed 4.35 (4.55) 6734 3.91 (4.07) 6385
Months received 5.24 (3.89) 7134 6.30 (3.99) 6790
Age 33.49 (10.43) 7137 35.81 (11.80) 6795
Female 0.46 (0.50) 3308 0.61 (0.49) 4136
Spouse 0.21 (0.41) 1517 0.39 (0.49) 2647
High education 0.10 (0.30) 689 0.14 (0.35) 962
Middle education 0.51 (0.50) 3618 0.59 (0.49) 3990
Low education 0.40 (0.49) 2820 0.27 (0.44) 1837
Couple without children 0.09 (0.29) 671 0.18 (0.39) 1255
Couple with children 0.28 (0.45) 2003 0.54 (0.50) 3691
Single parent 0.25 (0.43) 1794 0.12 (0.32) 792
Single person 0.28 (0.45) 2014 0.10 (0.31) 707
Tenant 0.70 (0.46) 5 048 0.37 (0.48) 2512
Observations
Treatment: 7137
Control: 6795
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Incentivizing last‑resort social assistance clients: Evidence…
The treatment and control groups are defined so that individuals in the treatment
group have received a positive amount of social assistance, and the control group
does not receive any social assistance in 2001. Table3 shows summary statistics for
the treatment and control groups. In a balanced panel, there are totally 7137 individ-
uals in the treatment group and 6795 individuals in the control group. Both the treat-
ment and control groups have higher earnings than in Table2. The treatment group
has higher earnings because retirees were dropped and the control group because
individuals who receive social assistance are excluded. In 2001, 33% of labour mar-
ket subsidy recipients were also social assistance recipients, which is an indicator
of a weaker social position as they receive multiple benefits. Table 3 also shows
thatthe average time to receive social assistance was 5.2 months and 6.3 months for
labour market subsidy recipients. Social assistance recipients were more often ten-
ants, without a partner, low educated and single parents.
Figure2 shows the employment trends with earnings and work months as out-
comes. The graphs are formed of the panel so that the treatment status is defined on
the pre-treatment period, that is in 2001. Graph 3.2A shows that the treatment and
control groups follow similar employment paths, but the level difference is not con-
stant in the pre-treatment period. This is adjusted by the CEM matching. Graph 2B
shows average work months from the raw data. Statistics Finland changed its work
month classification after 1998. In 1997 and 1998, work months were coded zero for
all work days between 0 and 15, including individuals who did not have any work-
days. After 1998, individuals with no workdays received a NULL value. In graph
The earning disregard experiment
0500010000 15000
Earnings, (€)
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Year
CI95%
Treatment Control
(A)
Average earnings for the treatment and control groups
The earnings disregard experiment
012345678910
Work months
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Year
CI 95%
Treatment Control
(B)
Average work months from the raw data
The earnings disregard experiment
012 3 4 567
Work months
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Year
CI 95%
Treatment Control
(C) Average work months after inputting zeros
Fig. 2 Employment trends for the treatment and control groups
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12
H.Palviainen
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2C, the NULL values are replaced with zeros for all individuals who had zero yearly
earnings. This makes the earnings and work month outcomes more comparable.
4.3 Matched variables andcovariate balance
The following introduces the matched variables. Strictly exogenous variables are
chosen. Household types are omitted because these likely affect the treatment. The
age of children between 0–2 and 3–8 are included. Young children are less likely to
affect the treatment variable, but they may affect the labour supply of their parents.
Age is based on quantiles with coarsened bins (24, 34, 44). Earnings are balanced
on two pre-treatment periods to avoid endogeneity. The coarsened bins are based
on earnings quantiles with coarsened bins in 2000 (0 193 1231 2684 4454 6839
11764). In addition, regional characteristics, education level, sex and students in the
pre-treatment period are balanced. Table4 shows the covariate balance before and
after matching.
Table4 shows that there is a reasonably good covariate balance. The pre-treat-
ment earnings are not fully balanced, but other variables’ covariate balance is zero
or very close to it. In CEM matching, there is a trade-off between external and inter-
nal validity. The more bins, the more precise the results are, but the results may not
be externally valid. After matching, there are 5344 individuals in the control group
and 4508 individuals in the treatment group. The unmatched individuals are 1451
and 2620 respectively. Thus, the results are not fully externally valid.
Figure3 shows the employment trends after matching. Figure3A and B shows
that the pre-trends follow similar paths, andthe confidence intervals overlap in the
pre-treatment period. The employment effects on work months without inputting
zeros (Fig.3B) are not further studied since only positive workdays were counted
after 1998. This intensive margin outcome is not further studied as conditioning on
positive earnings causes some bias to the results.Figure3C showsthe average work
months after inputting zeros if an individual has zero earnings. The pre-trend differ-
ence is not constant over time, and these results should be interpreted with caution.
It may be more challenging to obtain a good covariate balance with work months as
an outcome since the work months is an integer variable withfewer available bins
than in earnings.
5 Results
This section begins by showing the regression results for four outcomes. In Table5,
the first column shows the results for earnings and the second column for logged
earnings. The third and fourth columns show the results for work months and logged
work months, respectively. Work months are estimated for the years 1997–2007 only
due to lacking data. Figure4 plots the treatment effects on yearly earnings and work
months.
Figure4A and Table4 show no statistically significant treatment effects on earn-
ings. The drawn confidence intervals show that the treatment effects would not be
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13
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Incentivizing last‑resort social assistance clients: Evidence…
Table 4 Covariate balance before and after matching
Treatment Control Unmatched diff. Matched diff.
Unmatched mean Matched mean Unmatched mean Matched mean
Earnings
t=2000
5335.65 3280.11 2490.70 3094.19 2845.95 185.92
Earnings
t=1999
4971.68 2784.52 1963.57 2661.98 3008.11 122.54
Student
t=2000
0.18 0.14 0.14 0.16 0.04 -0.02
Age 33.40 33.76 35.81 34.02
−2.41
−0.26
Woman 0.46 0.47 0.61 0.47
−0.15
0.00
Low education 0.40 0.40 0.27 0.40 0.13 0.00
Middle education 0.51 0.54 0.59 0.54
−0.08
0.00
High education 0.10 0.06 0.14 0.06
−0.04
0.00
Children 0-2 0.09 0.03 0.03 0.03 0.06 0.00
Children 3-8 0.16 0.09 0.15 0.09 0.01 0.00
Large cities 0.27 0.22 0.16 0.22 0.11 0.00
Towns and rural areas 0.56 0.63 0.68 0.63
−0.12
0.00
N 7137 4508 6795 5344
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14
H.Palviainen
1 3
sizeable even though the effects were at the upper boundary. Figure4B also shows
that the pre-trend differs statistically significantly from zero in the case of work
months. As discussed above, it may be more difficultto flatten the pre-trends for
work months because work months is an integer variable with less available bins
Fig. 3 Employment trends for the treatment and control groups after matching
Table 5 Estimated treatment effects
(1) Work months are estimated for the years 1997-2007. Full sample is used for the other outcomes.
(2) Standard errors are clustered at the individual level. (3) *Significant at 10%; ** significant at 5%;
***Significant at 1%
(1) (2) (3) (4)
Earnings Logged earnings Work months Logged work
months
𝛽DiD
S.E.
𝛽DiD
S.E.
𝛽DiD
S.E.
𝛽DiD
S.E.
t=2002
−
557.4*** 180.4
−
0.07 0.13
−
0.12 0.09 0.01 0.02
t=2003
−
278.8 233.1 0.02 0.12 0.06 0.12 0.02 0.02
t=2004
−
196.9 279.8 0.09 0.12 0.08 0.13 0.03 0.02
t
=
2005
−
56.3 298.5
−
0.07 0.13 0.08 0.13 0.03 0.02
t=2006
−
294.5 321.7
−
0.09 0.15 0.04 0.13 0.03 0.02
t=2007
−
233.7 367.9 0.00 0.16
−
0.02 0.14 0.00 0.02
N128076 128076 91143 91143
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15
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Incentivizing last‑resort social assistance clients: Evidence…
than in earnings. Thus, the results should be interpreted with caution. Table4 also
reports the results after a logarithmic transformation. This gives less weight to high
earning individuals. The results are very close to zero.
Figure4 shows the results for women and men (4C and 4D). The empirical labour
supply literature often finds that women are more responsive to financial incentives
than men (e.g. Meghir & Phillips, 2010). There are no statistically significant effects
on women, but the effects on men are negative, which may be caused by imprecise
matching. As a sensitivity analysis, Fig.5 shows the results after adding household
types and unemployment in the pre-treatment period-2 to the set of matched vari-
ables. That is, the specification is the same as the main specification introduced in
Sect.4.3 but adds household types and pre-treatment unemployment. The household
types include single persons, single parents and couples with children and without
children. The additional matched variables increase precision to the estimates (bias-
variance trade-off), but the household types are potentially endogenous. Figure5C
shows that there are statistically significant effects on women, but the confidence
intervals are wide. Figure5B also shows that the work month pre-trend is flat with
the additional matched variables. The treatment effects remain non-significant using
work months as an outcome variable. Figure5D shows that treatment effects for
men are no longer negative.
Table 6 shows three types of robustness checks. The first result column (1)
excludes social assistance clients’ spouses who belong to the control group. This is
because social assistance is means-tested at the family level, and the earnings disre-
gard was household-specific. This creates a potential downward bias. Table6 shows
Fig. 4 Estimated treatment effects for the whole sample and women and men
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16
H.Palviainen
1 3
that the results are very similar without the spouses. This is partly explained by
the yearly data. Because the control group did not receive social assistance for one
year, it is to a large extent formed of families and individuals who were not eligible
for social assistance or did not apply for it. Approximately eight per cent (8.2%) of
the control group members had a spouse who received social assistance in 2001.
Fig. 5 Estimated treatment effects after adding household types and pre-treatment unemployment in
period-2. Household types and pre-treatment unemployment are added to the main specification intro-
duced in Sect.3. Household types refer to single persons, single parents, couples without children and
with children. Pre-treatment unemployment in period-2 refers to unemployment in 2000
Table 6 Robustness checks
(1) Standard errors are clustered at the individual level. (2) *Significant at 10%; **significant at 5%;
***significant at 1%
(1) (2) (3)
Spouses excluded Pre-trend controlled Tenants excluded
𝛽DiD
S.E.
𝛽DiD
S.E.
𝛽DiD
S.E.
t
=
2002
−
618.2*** 183.4
−
561.1*** 180.4
−
543.0*** 189.0
t
=
2003
−
345.4 237.6
−
286.3 233.1
−
418.2* 226.0
t=2004
−
250.2 284.5
−
208.2 279.8
−
579.8** 271.2
t=2005
−
85.7 303.0
−
71.3 298.5
−
349.8 287.6
t=2006
−
290.8 325.8
−
313.2 321.7
−
296.9 326.4
t=2007
−
206.6 373.0
−
256.2 367.9
−
428.2 343.5
N122,499 128,076 91,143
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17
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Incentivizing last‑resort social assistance clients: Evidence…
Evenif there was a treatment effect, the effect would be likely smaller for spouses
in the control group. This is because the social assistance was paid to the applicant’s
bank account. Although families may share earnings, the fact that the spouse did not
receive the social assistance could have diminished the perceived incentive effect for
the spouses.
The second model (2) in Table6 controls for differing pre-existing trends between
the treatment and control groups similarly to Kleven etal. (2014). At first, the earn-
ings growth is predicted for post-treatment years from pre-treatment data separately
for the treatment and control groups. Then the trends are subtracted from post-treat-
ment data, and these values are used as outcomes. The results remain very similar.
The third result column (3) excludes tenants from the control group. Home-owners
are less likelyto be eligible for social assistance. One way to measure exogeneity
and inflow to social assistance is the share of social assistance clients’ spouses in the
control group. Only 4.2 % of home owners had a spouse who received social assis-
tance in 2001. The results do not significantly change, but the treatment effects are
more negative, which may be caused by imprecise matching. Figure6 plots the treat-
ment effects with the main specification (6A) and after adding household types and
pre-treatment unemployment in period-2 (6B). Figure6 shows no positive effects
after excluding tenants from the control group.
The results show no statistically significant employment effects on average. There
is some evidence of women’s employment response to the earnings disregard, but
the estimations are potentially endogenous, and the sample size limits the examina-
tions. The results appear robust to the potential inflow from the control group as
shown by the estimations using exogenous home owners as a control group and to
the changed incentives of social assistance recipients’ spouses.
Fig. 6 Estimated treatment effects after excluding tenants from the control group. The right-hand side
figure adds household types and unemployment in period-2 to the main specification. The left-hand side
figure plots the treatment effects with the main specification introduced in section4.3. Household types
refer to single persons, single parents, couples without children and with children. Pre-treatment unem-
ployment in period-2 refers to unemployment in 2000
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18
H.Palviainen
1 3
6 Conclusions
This paper examined the employment effects of the Finnish earnings disregard
experiment between 2002–2007. The results show no significant employment effects
on average, but the results suggest a treatment effect on women. The empirical
approach does not allow for studying the short-term recipients, and monthly data
would provide more subtle results. Although the results suggest no clear positive
effects, the new policy had positive aspects. The earnings disregard unambiguously
improved social assistance clients’ situation with limited fiscal implications. Before
the experiment social assistance was effectively reduced in one-to-one ratio after
a recipient started to earn income. However, from a policy perspective, there are
factors that weakened the effectiveness of the experiment. Applying the earnings
disregard at the individual level instead of the household level would have likely
given a higher incentive effect. Also, the rules for applying the earnings disregard
varied across municipalities. Simple rules should be applied to earnings disregards
so that it is easy to perceive how taking up work affects disposable income. Interac-
tion effects from other means-tested benefits add complexity to the social security
system making it more difficult to perceive how temporary work affects disposable
income .
Acknowledgements The author would like to thank the Editor, Sara LaLumia, and two anonymous refer-
ees, Jukka Pirttilä, Kaisa Kotakorpi, Tomi Kyyrä and Heikki Hiilamo, as well as participants at the IIPF
Tokyo 2017, seminar participants in ZEW Mannheim and Allecon in Jyväskylä for their helpful com-
ments. Funding from the Finnish Centre of Excellence in Tax Systems Research (no. 346250) and Work,
Inequality and Public Policy (no. 252369) funded by the Academy of Finland is gratefully acknowledged.
The results and their interpretation are solely the responsibility of the author.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as
you give appropriate credit to the original author(s) and the source, provide a link to the Creative Com-
mons licence, and indicate if changes were made. The images or other third party material in this article
are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the
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directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen
ses/ by/4. 0/.
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