Essays on Labor Economics : The Role of Government in Labor Supply Choices

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Essays on Labor Economics

The Role of Government in Labor Supply Choices

Niklas Blomqvist

Niklas Blomqvist Essa ys on La bor Economics

Dissertations in Economics 2020:1

Doctoral Thesis in Economics at Stockholm University, Sweden 2020

Department of Economics

ISBN 978-91-7911-142-7

ISSN 1404-3491

Niklas Blomqvist

Niklas holds a B.Sc. and an M.Sc. in Economics from Stockholm University

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Essays on Labor Economics

The Role of Government in Labor Supply Choices

Niklas Blomqvist

Academic dissertation for the Degree of Doctor of Philosophy in Economics at

Stockholm University to be publicly defended on Tuesday 9 June 2020 at 10.00 in sal G, Arrheniuslaboratorierna, Svante Arrhenius väg 20 C.

Abstract

"Right to Work Full-time" Policies and Involuntary Part-time Employment

This paper investigates the effect of right to full-time policies implemented to decrease involuntary part-time work for public care workers employed by Swedish municipalities. Taking advantage of a staggered decision process, these policies are evaluated using a difference-in-differences approach. Results show that involuntary part-time employment is real and significant, with 10% of part-time employed workers choosing full-time when given the opportunity. The effect mainly comes from a decrease in contracts of <75% of full-time and an increase in contracts of 80% of full-time and above. Further results from the full-time policies show that being more flexible in the choice of hours worked is popular among workers, indicated by an increase in tenure and reduced turnover in municipalities that offer more flexibility in the choice of hours worked.

Hours Constraints and Tax Elasticity Estimates - Evidence from Swedish Public Care Workers

There is a concern that tax elasticity estimates may be downward biased in the presence of optimization frictions for workers. So far, there is limited evidence on the nature of these optimization frictions. This paper provides new insight into one part of the optimization frictions black box, namely hours constraints. Using unique and newly collected data, I exploit a staggered implementation of a policy that gave some public care workers the opportunity to choose their preferred hours of work. Taking advantage of this policy, I estimate differences in tax elasticities between constrained and unconstrained public care workers by comparing bunching at a large tax kink in the Swedish tax system. The empirical evidence points to the conclusion that hours constraints do not affect tax elasticity estimates.

Restricting Residence Permits - Short-Run Evidence from a Swedish Reform

In June 2016, the Swedish parliament decided to restrict the granting of permanent residence permits for asylum seekers in Sweden. The new status quo for a refugee is a temporary rather than a permanent residence permit. In a first evaluation of this reform we use a Regression discontinuity analysis in which we follow refugees, aged 25-65, over their first years after arrival. Our main results show that a temporary residence permit increases the probability of working and enrolling in regular education.

Mom and Dad Got Jobs: Natural Resources, Economic Activity, and Infant Health

The impact of local economic shocks, such as the discovery and exploitation of natural resources, on labor markets and health is not well understood. Both positive and negative effects have been documented in the literature. In this paper, we show that the phase before active resource extraction begins directly affects the local economy. This implies that previous estimates – typically based on designs exploiting differences before and after the active phase of extraction begins - may have understated the actual effect of natural resource extraction on outcomes of interest. Using rich data from Sweden combined with differences in the timing and location of mineral exploitation permits, we find a positive impact on female and male employment and earnings and a negative effect on housing prices. Children’s health outcomes are also negatively affected, an effect likely driven by the increase in local economic activity rather than extraction-related externalities.

Keywords: Involuntary Part-time Employment, Labor Supply, Tax Elasticity, Refugees, Immigration, Integration,

Natural Resource Extraction, Family Resources, Health.

Stockholm 2020 http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-180933 ISBN 978-91-7911-142-7 ISBN 978-91-7911-143-4 ISSN 1404-3491 Department of Economics Stockholm University, 106 91 Stockholm

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ESSAYS ON LABOR ECONOMICS

Niklas Blomqvist

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Essays on Labor Economics

The Role of Government in Labor Supply Choices

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ISBN PDF 978-91-7911-143-4 ISSN 1404-3491

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Till den som känner sig träffad

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Acknowledgements

First, I would like to thank my supervisors, Peter Skogman Thoursie, Martin Olsson, and Björn Tyrefors. Peter and Martin have helped me, read and commented on my drafts more times than I would wish upon my worst enemy. Their help and support have been invaluable and for this I am grateful. Working together with Björn on two of my thesis chapters has been great since he has always been able to spot the good things among the bad. It is also obvious how much Björn cares for the welfare of his Ph.D. students and for this he will always have my respect. Not being a supervisor, but a co-author on one of the thesis chapters, Andreas Madestam has been a great help to me as well. I would also like to thank Lisa Laun for a thorough reading of all chapters and many valuable comments.

Second, but first among equals, I have to mention Jonas Cederlöf, whom I have been sharing the experience of university studies with for a decade. It looks crazy when I type it out, a decade together completing both the Bachelor and Master program, before leaving me the last year of the Ph.D. program to finish it off at Uppsala University. But I guess that time flies when you have fun, and having fun is all but a guarantee when spending it with Jonas. I also think that the end result, the thesis at this moment in your hand, would not have been half as good without his help or without all our discussions about economics and econometrics, big and small.

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ated our accidental tradition of visiting Scandinavian cities together. Even though she had, and still have, strange working hours and I have come to suspect that she does not understand what "impeccable sense of humor" means, she made the days at the office more enjoyable.

Kasper Kragh-Sørensen and Fredrik Paues deserve a special shout out for, together with Jonas, making the first year of the Ph.D. pro-gram easier for me. Who would have thought that it could be really fun to sit next to another person and write code together in different statistic software programs? Furthermore, I like to thank Benedetta Lerva who saved me from going insane in Berkeley. Jon Olofsson al-most seamlessly took over when Jonas abandoned Stockholm Uni-versity for Uppsala UniUni-versity, and let me ask stupid econometric questions. Our "Poem of the day" was, of course, one of the daily highlights during the last year of the Ph.D. program. I would also like to thank Roza Khoban and Ulrika Ahrsjö for being great office neigh-bors, Fredrik Runelöf for hoarding all the cups, Anna Linderoth for keeping tabs on him, Louise Lorentzon for making the Ph.D. program a better social experience for everyone, Erik Lindgren for teaching me bouldering, Karin Kinnerud for showing me how to walk really long distances, and Dany Kessel for being a great teacher and colleague.

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Introduction

Governments have a vast and variable impact on employment, wages, and hours of work. First, the government is an employer, with a direct impact on some workers’ wages and hours of work. In Sweden, this is an important way in which the government can affect employment conditions, with one-third of all workers being employed by the public sector. Second, in order for the government to function, it taxes its citizens. These taxes have an indirect impact on workers and their choice of hours worked, which depends on the type and level of the tax. Third, apart from taxes, the government decides on the institutions that in themselves affect choices and possibilities in the labor market for its citizens. This thesis consists of four self-contained chapters that each focus on some of the different ways in which governments can have an impact on employment, wages, and hours of work.

The first chapter of this thesis, "Right to Work Full-time" Policies and Involuntary Part-time Employment, visits the government as an employer. In this chapter, I study the effect of a policy change implemented by Swedish local governments on the mu-nicipality level. The municipalities decided to implement "right to full-time" policies. These policies gave public care workers, employed by the municipalities, the right to choose how many hours they wanted to work, within certain limits. Taking advantage of a staggered decision process, these policies are evaluated using a difference-in-differences approach. The results from the evaluation of the policies show that

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10% of part-time workers choose to work full-time instead, when given the opportunity. The study also showed that the changes in contracted hours mainly stem from workers with contracts of <75% of a full-time contract deciding to increase their contracted hours. Furthermore, af-ter the local governments decided to implement full-time policies for public care workers, turnover in the sector decreased while tenure increased, indicating the policies were popular.

The fact that public care workers did change their contracted hours of work when given the opportunity shows that a significant minority of them did not work their optimal hours. This, in turn, indicates that local governments acting as employers in the public care sectors can act as monopsonist employers to some extent. In Sweden, almost 18% of all workers are employed in the public sector on the municipality level, and out of these, 38% are public care workers. Thus, a significant part of the labor market can be characterized as monopsonistic (in a broad sense).

There has been a concern among politicians on the local govern-ment level that public care work is not attractive enough to meet the long-term demand for public care workers. This chapter shows that such concerns might be correct. Since public care employers can act as monopsonists, it might lead to cheaper employment solutions in the short term and a lack of workers in the long term. This chapter shows that, since turnover decreased and tenure increased because of the right to full-time policies, it is possible for local governments to change policies in such a way to make public work more attractive. As one last point, leading up to the next chapter in the thesis, these re-sults strongly suggest that some workers are constrained in the choice of hours worked.

The second chapter of this thesis, Hours Constraints and Tax Elasticity Estimates - Evidence from Swedish Public Care Workers, focuses on how we measure tax elasticities. Governments need taxes to function. One problem is that taxes, to different

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grees, affect labor supply. For tax policies to help reach the goals of the public, it is important to understand how and by how much taxes affect labor supply. Thus, empirical tax elasticity estimates are paramount to study and understand in order to decide the optimal level of taxes. By extension, it is important to understand if, and by how much, optimization frictions affect empirical tax elasticity mea-sures. There has been a worry that tax elasticities estimated in the empirical literature are biased because of optimization frictions fac-ing workers. So far, there is limited evidence on the nature of these optimization frictions. This chapter provides insight into one part of the optimization friction black box, namely hours constraints.

Using the "right to full-time" policies from the previous chapter, I estimate the difference in tax elasticities between public care workers who are constrained in their choice of hours work compared with those who are unconstrained. Workers who are unconstrained in their choice of hours work should have larger tax elasticity estimates than constrained workers. The reason for this is that constrained workers should not be able to react to taxes by changing their labor supply in the short run, while unconstrained workers can. Thus, if hours constraints create an important bias in tax elasticity estimates, public care workers in "right to full-time" municipalities should have larger tax elasticity estimates than their counterparts in non "right to full-time" municipalities.

That some type of optimization friction affects empirical tax elas-ticity estimates is already known. The question is what these opti-mization frictions consist of. Hours constraints is one candidate, and lack of information or understanding of the tax system is another. It is important to be able to differentiate between these two optimiza-tion fricoptimiza-tions, since they might have different long-run implicaoptimiza-tions. Hours constraints is a short-term constraint that will bias the esti-mated tax elasticity downwards, while workers will still react fully to taxes in the long run. Lack of information or understanding of the

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tax system, on the other hand, may affect how workers react to taxes both in the short- and long run. If workers are uninformed in both the short- and long run they will not react to taxes, which will yield small tax elasticity estimates. However, as long as the lack of information is persistent, the empirical observation that workers do not react to taxes is correct, rather than a result of a bias. Thus, it is important to separate hours constraints and information as optimization frictions, since they might lead to different conclusions about a potential bias in tax elasticity estimates.

Using the bunching approach around a large kink in the Swedish tax system, I show that there is no difference in bunching for con-strained and unconcon-strained public care workers. The null result points to the conclusion that hours constraints do not significantly affect tax elasticity estimates for this group of public care workers. The impor-tance of information, and its persistence, as an optimization friction remains to be studied.

The third and fourth chapters of this thesis go into two spe-cific institutions and policies that may affect employment, wages and hours of work. The third chapter, Restricting Residence Permits - Short-run Evidence from a Swedish Reform, jointly written with Peter Skogman Thoursie and Björn Tyrefors, evaluates one ma-jor component of the Swedish integration policy, stipulating whether temporary or permanent residence permits should be granted to asy-lum seekers. The question of how to integrate refugees has received great attention considering the rise in refugees arriving in the EU in the last decade. Furthermore, with climate change, we can count on this issue to be even more prominent in the future. This chapter an-swers the question of how two different types of residence permits, temporary or permanent, affect integration for refugees. Since it is impossible to grant asylum to a refugee without giving some type of residence permit, the policy choice of granting temporary or perma-nent permits will affect all refugees and how it affects integration is

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5

important to study.

Using a policy change in June 2016, where the Swedish parliament decided to restrict the granting of residence permits for asylum seek-ers in Sweden, this chapter uses a Regression discontinuity design in which we follow the refugees over their first years after arrival. This first study analyzes the effect on refugees 25-65 years old and finds positive effects on education and employment of receiving a temporary instead of permanent residency. One possible explanation for this re-sult is that the Swedish legislation provides work incentives for asylum seekers with temporary residence permits. A major component of the Swedish legislation is that an immigrant with a temporary residence permit can receive a permanent residence permit by working. How-ever, we have yet to conduct a study on younger individuals, since too few have received grades from primary and upper secondary school to do so. Furthermore, in the future, we are going to look into the health effects for individuals receiving temporary instead of perma-nent residency. This remains to be done. Without that information, it is too soon to use this study to give policy recommendations, or draw too stark conclusions about the effect of different types of residence permits. It is also important to note that temporary residency per-mits can have other effects. One example is that it could reduce the number of asylum seekers arriving to a specific country, which could be a preference of the government.

The fourth chapter of this thesis, Mom and Dad Got Jobs: Natural Resources, Economic Activity, and Infant Health, jointly written with Andreas Madestam, Emilia Simeonova, and Björn Tyrefors, study another institutional setting that may be of impor-tance for employment, wages and health outcomes. Here we delve deeper into the mining and fracking literature and the local economic and health impacts of resource extraction. The impact of local eco-nomic shocks, such as the discovery and exploitation of natural re-sources on labor markets and health is not well understood. Both

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positive and negative effects have been documented in the literature. This chapter shows that the phase before active resource extraction begins, affect the local economy. We use rich data from Sweden com-bined with differences in the timing and location of mineral exploita-tion permits in a difference-in-differences setting. The results show a positive impact on employment and earnings and a negative ef-fect on housing prices. Children’s health outcomes are also negatively affected, an effect likely driven by the increase in local economic ac-tivity rather than extraction-related externalities. Previous studies have typically based their research designs on exploiting differences before and after the active phase of resource extraction begins. Our results imply that these previous estimates may have understated the actual effect of natural resource extraction on outcomes of interest. Taken together, the results point to the importance of accounting for all phases related to natural resource extraction to correctly assess the full impact on local economies and health.

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Chapter 1

"Right to Work Full-time"

Policies

and Involuntary Part-time Employment

∗

I thank Jonas Cederlöf, Lisa Laun, Jon Olofsson, Martin Olsson, Peter Skog-man Thoursie, and seminar participants at Stockholm University Department of Economics for valuable comments and feedback. I would also like to thank Emil Johansson who got me interested in this subject, to begin with. All errors are my own.

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1.1 Introduction

Regulation of working hours has long been an important topic both in the political debate and in the economic literature (Boeri and van Ours 2008). From the perspective of workers, it might not be pos-sible to choose the optimal amount of hours worked. If workers are constrained in their choice of hours there exist under- and overemploy-ment, which, just like unemployoveremploy-ment, may have welfare consequences. In the debate about the regulation of working hours, the choice be-tween part-time and full-time employment is important. Part-time work has, at least historically, enabled women to enter the labor force (Blau and Kahn 2013, Sundström 1991). At the same time, a sig-nificant minority of workers work part-time involuntary according to surveys (Boeri and van Ours 2008). There is also a concern that part-time work might lead to women being marginalized in the labor mar-ket. Part-time work might come with a pay penalty (Manning and Petrongolo 2008) and it has been shown that part of the gender wage gap can be explained by employers rewarding those who work long hours (Goldin 2014).

In surveys from 1997, presented by Boeri and van Ours (2008),

31% (35%) of women (men) worked part-time involuntary in Sweden.1

However, the extent of involuntary part-time employment varies be-tween countries. For example, the US only had 8% (7%) of part-time work being involuntary during the same period, while France had 39% (53%) involuntary part-time workers. In light of the evidence of widespread involuntary part-time employment, several Swedish mu-nicipalities started to implement "right to work full-time" policies (henceforth full-time policies) for public care workers. From 2000 to 2013, 99 of Sweden’s 290 municipalities decided to implement a full-time policy. Two primary reasons motivated politicians to implement these policies. First, they wanted to make public work in the

munic-1

In a similar survey from 2002-2003, presented by Lundqvist et al. (2005), 20% of women and men worked part-time involuntary.

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1.1. INTRODUCTION 9

ipality sector more attractive. Second, they wanted to decrease in-voluntary part-time employment, which was seen as one of the main drivers of the gender earnings gap.

The setting, with a staggered decision process, provides a unique opportunity to evaluate the full-time policies extensively. To this end I have collected minutes from the municipal council meetings from when the decisions to implement a full-time policy were made. The policies made it possible for public care workers to choose how many hours they wanted to work and the employer had to comply with

that choice.2 To evaluate the policies I use a difference-in-differences

model to first measure how the policies affected earnings, contracted hours and share of workers on a full-time contract in the public care sector. In order to better understand the full effect of the policies I also look at how the distribution of contracted hours changes. Second, to get an idea of whether hours constraints affect the match quality of the constrained workers I measure how the full-time policies affected tenure and turnover.

Thanks to the minutes, it is possible to get a more detailed under-standing of the full-time policies. Some municipalities offered a free choice of hours, while other municipalities offered a choice between part-time and full-time employment only. Half of the municipalities also implemented the policy for all public workers, not just public care workers. Furthermore, some municipalities implemented the full-time policy immediately and some municipalities implemented the full-time policy a few years after the decision. The effects of these differences are explored in a heterogeneity analysis.

I find that the full-time policies led to an increase in contracted hours of 1.4 percentage points on average for public care workers in the municipalities. The increase in contracted hours came from a de-crease in contracts below 75% of a full-time contract and an inde-crease

2

The choice was typically restricted to be within a certain interval, e.g. within 75-100%, of a full-time contract.

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in contracts of 80% of a full-time contract and above. When looking at the change in the distribution of contracted hours, it seems as if public care workers in practice could change their contracts in incre-ments of five percentage points. Furthermore, the annual earnings for

the public care workers increased by 3,000 SEK,3 while the share of

public care workers on a full-time contract increased by 6 percentage points. The last point constitutes 10% of part-time workers switching to full-time. These results point to the conclusion that a significant minority of public care workers were, in fact, working part-time in-voluntary. There is also evidence of the policies being popular among the workers, as shown by a 5% increase in tenure and 7% fewer public care workers leaving their employment. Surprisingly, a heterogeneity analysis shows that even in municipalities that implemented full-time policies for all public workers, only public care workers were affected in practice.

These results give insights that relate to the literature that ex-amines the prevalence of hours constraints (see e.g. Beffy et al. 2019, Bloemen 2000, Blundell and Brewer 2008, Bryan 2007, Dickens and Lundberg 1993, Johnson 2011, Kahn and Lang 1991, 1995). In gen-eral, these studies find that there are workers that are constrained in their choice of hours worked − with some notable exceptions, see e.g. Ham and Reilly (2002) or Johnson (2011). Furthermore, this pa-per provides an extensive review of Swedish municipalities’ full-time policies which, being interesting in their own right, can be used as the first stage in many potential studies of other economic questions. For example, as have been done in the second chapter of this thesis, these policies can be used to answer the question of how optimiza-tion fricoptimiza-tions, in the form of hours constraints, affect tax elasticity estimates.

The rest of the paper is structured as follows. Section 1.2 goes through the institutional setting. Section 1.3 presents the data and

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1.2. THE RIGHT TO FULL-TIME POLICIES 11

empirical model, while section 1.4 shows the results and robustness tests. Finally, section 1.5 concludes.

1.2 The Right to Full-time Policies

The data on the decisions to implement full-time policies come from

municipal council meeting minutes.4 I sent out requests to all

munic-ipal archives for municmunic-ipal council meeting minutes from the meeting when a decision to implement a full-time policy was made. 91% (265) of Sweden’s municipal archives answered. Out of the 265, 99 had de-cided to implement such a policy during 2000-2013. The first wave of data collection for municipal council meeting minutes started in 2014, making 2013 the last year for which it is possible to know if a full-time policy was decided upon.

The purpose of the policies was to reduce involuntary part-time work among public workers, employed by the municipalities. There were usually two main arguments in favor prior to the decision to implement full-time policies. First, politicians and officials worried about the weak interest of young people in working in the public sector. With a large share of older workers, close to retirement, there was a risk of labor supply shortage and a need of making work in the public sector more attractive. The full-time policies were meant to do just that. Second, part-time is more common for women compared to men. By reducing involuntary part-time politicians saw a way of increasing equality between men and women.

The decisions, and subsequent implementations, of full-time poli-cies differed from municipality to municipality. Since there was a lot of heterogeneity in the full-time rules I divided the decisions into three categories. In the first, workers could choose hours freely

be-4_{These decisions are public documents and must be archived. This whole}

sec-tion is based on a thorough reading of minutes from municipal council meetings from when the decisions of full-time policies were made.

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tween 75-100% of a full-time contract.5 _{In the second, workers could}

choose hours in increments of 5 or 10 percentage points between at least 75-100% of a full-time contract. In the third, workers could only choose between working part-time or full-time. In the third category, it was unclear if there were several different part-time contracts to choose from. Thus, this category could include municipalities that of-fered a range of different contracted hours. As Table 2.5 shows, 49% of the municipalities that decided to implement a full-time policy of-fered freely adjustable contracts. Thus, it was usually not necessary to demand full-time. A 70% part-time worker could demand an 80% part-time contract, for example.

As shown in Table 2.5, 44% of the municipalities implemented the policy almost immediately upon decision, while 56% implemented the policy gradually over a few years. Some municipalities did not have a specific date for implementation. Because of this, and because it is possible that some public employers started to act upon the decisions even before implementation, I have to use the decision date, rather than the implementation date, as the treatment variable in the empirical model. All municipalities included both present workers and future hires in the policy. In general, the biggest issue for the municipalities was the public care sector. Involuntary part-time was seen as more widespread in the care sector, compared to other sectors. This is why all municipalities that decided to implement a policy included the care sector. In half of the cases all sectors were included in the full-time policy. Because of this, the main focus of this paper will be the public care sector.

5_{This is the minimum requirement to be part of the first category. Some}

full-time municipalities had a wider range where the choice was free, for example from 60-100% of a full-time contract. Furthermore, municipalities that implemented a free choice of hours without mentioning a restriction are part of this category. In practice, it is safe to assume that there were some restrictions downward in the choice of contracted hours also in these municipalities.

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1.2. THE RIGHT TO FULL-TIME POLICIES 13 T able 1.1: Descriptive statistics of the de cision to implement ful l-time p olicies F ree choice P artly free ch oi ce P art-time or All of hours of hours F ull-time Share of full-time m unicipalities 0.49 0.15 0.36 1 Share in tro ducing full-time: within 1 y ear 0.59 0.42 0.27 0.44 successiv ely o v er < 5 y ears 0.41 0.58 0.73 0.56 Share in tro ducing full-time to: Care sector 1 1 1 1 Sc ho ol sector 0.48 0.62 0.68 0.57 All sectors 0.38 0.54 0.68 0.51 Notes : Municipalities are coun ted as pro viding F re e choic e of hours if it is at least p ossible to cho ose hours freely within an in terv al of 75-100% of a full-time con tract. Partly fr ee choic e of hours means that w ork ers can cho ose certain in terv als (e.g. in terv als of 5% of full-time). Part-time or F ul l-time means that w ork ers can cho ose b et w een only those. F or Part-time or F ul l-time , it is often unclear if part-time is fixed, or if it is p ossible to cho ose b et w een sev eral differen t part-time con tracts. Th us, this column includes w ork ers that are probably more free in their choice of hours than just cho osing b et w een tw o fixed con tracts. Sc ho ol sector include presc ho ols.

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In general, the public care sector workers are employed as nurses, assistant nurses, caretakers, and personal assistants working in the el-derly care sector or for people with disabilities. Another large group in the public care sector are social workers. On average, 38% of the pub-lic workers employed by the municipalities are care workers. Around the same share of public workers employed by the municipalities work in schools or preschools.

Only a few (13) municipalities specified when workers could choose their hours worked, but those who did stipulated that workers should be able to change to their preferred hours of work at least once a year. Even though the employer had to comply with their employees’ wishes, extra hours did not always have to be situated in the same workplace. The extra hours demanded by part-time employees could be pooled by the municipality, meaning that workers could be sent to other workplaces substituting for workers on sick leave. In some mu-nicipalities this rule applied to all workers, meaning that all employees had some of their hours in a pool. One of the reasons full-time was not offered before the policies were the fear of losing flexibility. Pooling workers was one solution to this problem. Another solution presented by some municipalities was a short-term injection of money in order to give the establishments in the public care sector the possibility to work out scheduling issues.

Figure 1.1 shows the number of municipalities that decided to im-plement a full-time policy during the years 2000-2013. There does not seem to be any macro shocks behind the decisions, rather there was a steady increase in municipalities offering full-time policies. Not even the Great recession seems to have affected the rate of municipalities deciding to implement such a policy.

Figure 1.2 and Table 1.3 show descriptive statistics for public care workers in municipalities one year before a full-time policy was de-cided upon. These statistics are compared to a random sample of public care workers in municipalities that never decided to implement

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Figure 1.1: Timing of the decision to implement full-time policies

0 20 40 60 80 100

Number of municipalities with full-time policy

2000 2002 2004 2006 2008 2010 2012

year

Yearly decisions Cumulative sum

Notes: Yearly number of municipalities that decided to implement a full-time

pol-icy.

a full-time policy, sampled to match the number of workers in each year in the full-time sample. Figure 1.2 shows that the most common contract for public care workers in all municipalities is a full-time contract. There are spikes at part-time contracts offering 50, 75, 80, 85, and 90% of a full-time contract. Figure 1.2 also shows that the distribution of contracted hours does not differ between public care workers in time municipalities and public care workers in non full-time municipalities before the policies take place. Table 1.3 shows that in full-time municipalities, before deciding to implement a full-time policy, public care workers are quite similar to public care workers in municipalities that do not implement full-time policies. Earnings, wages, tenure, age, etc. are all similar. However, as shown in Table 1.2 there are some differences when it comes to which municipalities that decide to implement a full-time policy. Compared to the average

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Figure 1.2: Distribution of contracted hours before the reform 0 .1 .2 .3 .4

Density of workers with specific contracted hours ₅₀ ₆₀ ₇₀ ₇₅ ₈₀ ₈₅ ₉₀ ₁₀₀

contract

One year before non full-time One year before full-time

Notes: Density distribution of contracted hours for public care workers in full-time

municipalities one year before the decision (maroon colored bars) and for a random sample of public care workers in non full-time municipalities (uncolored bars) sampled to match the number of public care workers in full-time municipalities each year. The x-axis is defined as the percent of a full-time contract. All workers with contracts above 100% are pooled in the 100% bar.

Swedish municipality the full-time municipalities are more left-wing. It is more common for medium-sized towns to implement a full-time policy and less common among large cities and municipalities near large cities.

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Table 1.2: Summary statistics for municipalities deciding to implement a

full-time policy Full-time All municipalities municipalities Share with: Left-wing government 0.57 0.42 Right-wing government 0.26 0.40

Share type of municipality:

Large city 0.10 0.16

Medium sized town 0.43 0.38

Smaller town/rural 0.46 0.46

Notes: This table shows descriptive statistics of municipalities that decided

to implement a full-time policy, one year before the decision. The second column shows the average statistics for all municipalities in the sample (in-cluding the full-time municipalities). Large city includes municipalities near large cities. Medium-sized town includes municipalities near medium-sized towns. Smaller town/rural includes smaller urban areas and rural munici-palities.

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Table 1.3: Summary statistics for public care workers

Full-time Control

municipality municipality

Share working full-time 0.38 0.35

(0.49) (0.48)

Mean contracted hours (% of full-time) 77% 76%

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Mean labor earnings (in SEK) 187,352 186,768

(85,449) (85,562)

Mean labor PT earnings (in SEK) 156,633 158,225

(77,075) (76,798)

Full-time equivalent wage (in SEK) 20,966 21,110

(4,239) (4,269)

Mean tenure (in years) 4.1 4.1

(4.1) (4.2)

Mean age 42 42

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Share women 0.89 0.90

(0.31) (0.31)

Share with children 0.38 0.38

(0.48) (0.49)

Highest achieved education:

College degree 0.23 0.24

(0.42) (0.43)

High school degree 0.68 0.67

(0.29) (0.29)

Observations 112,335 112,335

Notes: The values in the first column come from all public care workers in

full-time municipalities the year before a decision was made. The values in the second column come from a random sample of public care workers in non full-time mu-nicipalities, where the sample matches the number of public care workers in each year in full-time municipalities. "Mean labor PT earnings" is the mean earnings for workers on a part-time contract. Both labor earnings variables are expressed in an-nual earnings. Full-time equivalent wage is expressed in monthly wages. Earnings and wages are inflation-adjusted (in 2019, 1 USD∼9.5 SEK). Standard deviation in parenthesis.

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1.3. DATA AND RESEARCH DESIGN 19

1.3 Data and Research Design

1.3.1 Data and Sample

The data in this paper comes from four main sources. The first source is the minutes from the municipality council meetings, described above. From those minutes, I create a variable with information on the year when a full-time policy was decided on. Furthermore, I create dummy-variables for different decision types (if the municipality offered a free choice of hours or only offered a choice between part-time and full-time, if the decision was implemented within a year or successively and if other sectors than the public care sector were affected).

The second source is Statistic Sweden’s registers LISA6 which

in-clude the full population of Swedish residents over the age of fifteen. From LISA I got information on annual labor earnings, age, gen-der, number of children and highest achieved education. LISA report two-digit industry codes, which are used to establish if workers are employed in the care sector, school sector, or another sector. All pub-lic workers employed in industries working with "Human health and social work activities" are defined as care workers. Thus care work in this setting include elderly care, health care, disability care, and

social workers, but not child care workers.7

The third source is Statistic Sweden’s "Wage structure statistics" which report yearly panels of administrative data on all workers em-ployed by a municipality, and include the full population of (munici-pality employed) public care workers. The "Wage structure statistics" thus provide information on if workers are employed by the munici-pality or not. From these registers, I got information on contracted

6

The "Longitudinal integrated database for health insurance and labour mar-ket studies".

7_{This is "The Swedish Standard Industrial Classification", or SNI codes. For}

the years 1996-2006, the two-digit SNI code 85 includes all care workers in the sample, while the years 2007-2013 have the SNI codes 86-88.

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hours (reported in percent of a time contract), and monthly full-time equivalent wage rates. Contracted hours is used to understand if a worker has a full-time contract or not. In this paper, a full-time contract is defined as having contracted hours of at least 90% of a time contract or more, which is in line with the definition of full-time used by Statistic Sweden. Tenure is defined as the number of consecutive years working in the same municipality in the public care sector. If a worker works somewhere else for a year, and then return,

the tenure variable is reset to zero.8

The fourth source comes from the Swedish Association of Local Authorities and Regions (SALAR). This data is openly available and provides information on what type of majority run the municipality councils (left-, right-wing, or bipartisan) as well as information on the type of municipality (large city, medium sized town, or small town/rural).

The main sample is restricted to all public care workers employed by the municipalities 1996-2013. Workers in the municipalities that did not answer if they have a full-time policy are excluded. This means that the sample consists of repeated cross-sections of all public care workers in full-time municipalities and municipalities that never de-cide to implement a full-time policy.

1.3.2 Model and Research Design

To measure the effect of deciding to implement the full-time poli-cies employment in municipalities I use the following difference-in-differences model,

Yimt = α + δSDimtS + δMDimtM + δLDLimt+ µm+ µt+ Ximt+ eimt, (1.1)

8_{From the perspective of the municipality, what is interesting is to retain}

workers in the public care sector, not which specific elderly care center a worker is employed at, which is why I use this definition of tenure.

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where Y_imt is the outcome variable of interest. µ_m are municipality

fixed effects, µt are year fixed effects and Ximt is a vector of control

variables. D_imtS is a dummy variable equal to one if it is 0-3 years

after the decision to implement a full-time policy in a municipality.

Similarly, DM_imt is equal to one if is 4-7 years after a decision, and

D_imtL is equal to one if it is 8 or more years after a decision. Thus,

δS shows the short run effect of the full-time policy, while δM and δL

shows the medium- and the long run effects, respectively.

To test the common trends assumption, I also estimate the fol-lowing event study model,

Yimt = α +

X

k

δkDimtk + µm+ µt+ Ximt+ eimt, (1.2)

where D_imtk are dummy variables that equal one when it is k periods

to (from) the decision to implement a full-time policy in a

munici-pality. Thus, holding time- and municipality trends constant, δ_k show

the average difference in Y_imt each period compared to the reference

period, which is one year before implementation. If δ_k= 0 for all

pe-riods prior to the full-time policy it lends credibility to the common trends assumption.

All regressions are carried out using robust standard errors tered at the municipality level (Moulton, 1990). The number of clus-ters, and treatment units, are more than enough to get the correct standard errors (Bertrand et al. 2004, Conley and Taber 2011). Fur-thermore, all regressions include individuals from never-treated

mu-nicipalities.9

As a robustness test, I also run the control variables as dependent

9

Borusyak and Jaravel (2017) have shown that event study estimations may have a problem identifying a linear trend in the pre-trend path and dynamic treatment effects. The fix for this problem is to include a control group that can pin down the year effects. Thus, the event study regressions in this paper will include the 166 never treated municipalities as well as the 99 treated municipalities.

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Table 1.4: Number and share of municipalities that are included in event

timeP

k

Lead Number of Share of Lag Number of Share of municipalities municipalities municipalities municipalities

-1 99 1 1 86 0.87 -2 99 1 2 73 0.74 -3 99 1 3 67 0.68 -4 99 1 4 58 0.59 -5 97 0.97 5 50 0.51 -6 87 0.88 6 43 0.43 -7 80 0.81 7 36 0.36 -8 76 0.77 8 29 0.29 -9 73 0.74 9 26 0.26 -10 70 0.71 10 23 0.23 -11 63 0.64 11 19 0.19 -12 56 0.57 12 12 0.12 variables, using

Ximt= α + δSDSimt+ δMDMimt+ δLDLimt+ µm+ µt+ eimt, (1.3)

where X_imt is the control variable.10

Table 1.4 shows the number of municipalities included in each event time. Only 30% of municipalities are left to estimate an effect after 8 years, and after 12 years only 12% of the municipalities are

present. This means that the long run effect, δ_L, should be interpreted

with caution in the next section.

There’s been a recent discussion about the use of staggered difference-in-differences models in the presence of dynamic effects

10_{Pei et al. (2017) caution against using control variables on the right-hand side}

of regressions. Adding control variables affect the δ estimate of interest through two channels, the effect of the control on Yimt and the correlation between the

control variable and the independent variable of interest. Thus, the effect on the

δ estimate of interest of including control variables might be attenuated towards

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(see e.g. Goodman-Bacon 2018, Meer and West 2015).11 _{If there}

are dynamic effects, the difference-in-differences estimate will be biased towards zero. One way to overcome this problem is to use an event study model instead. In this paper, I present the main results using both event study- and difference-in-differences estimates. However, the difference-in-differences estimates are divided on short-, medium-, and long run effects, which in practice is a middle way between an event study and a pure difference-in-differences model. This will to some extent alleviate the potential problem of the estimates being biased toward zero.

11_{The main problem arises because a staggered difference-in-differences model}

will be a weighted average of all two-by-two difference-in-differences estimators in the panel data set. What this means is that units that are treated early will act as a control for units that are treated later (Goodman-Bacon 2018). Early treated units acting as controls for later treated units are only a problem if the treatment effect is dynamic. In that case, an early treated unit’s outcome variable will be on a different trend path because of the treatment and the comparison will necessarily become biased.

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Figure 1.3: Density of contracted hours 0 .05 .1 .15 .2

contract One year before non full-time Five years after non full-time

(a) Distribution before/after a non decision

0

.05

.1

.15

.2

contract One year before full-time Five years after full-time

(b) Distribution before/after a decision

Notes: Density distribution of contracted hours for public care workers in full-time

municipalities and for a random sample of public care workers in non full-time nicipalities sampled to match the number of public care workers in full-time mu-nicipalities each year. The x-axis is defined as the percent of a full-time contract. Panel (a) includes a random sample of public care workers from municipalities that never decided to implement a full-time policy. The maroon colored bars show the distribution of contracted hours for the random sample of public care workers drawn to match the yearly number of public care workers in full-time municipal-ities one year before the decision. The uncolored bars show the distribution of contracted hours for the random sample of public care workers drawn to match the yearly number of public care workers in full-time municipalities five years af-ter a decision. Panel (b) shows the distribution of contracted hours for public care workers in actual full-time municipalities one year before (maroon colored bars) and five years after (uncolored bars) a full-time decision, respectively.

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1.4. RESULTS 25

1.4 Results

1.4.1 Raw Distributions of Contracted Hours

Before moving to the regression results it is enlightening to look at the raw distributions of contracted hours. Figure 2.5 shows the distribu-tion of contracted hours (in percent of a full-time contract) for public care workers. Panel (a) shows the distribution for a random sample of public care workers drawn from municipalities that never decided to implement a full-time policy. The maroon colored bars represent a random sample drawn to match the yearly number of public care workers employed in a time municipality one year before a full-time decision. The uncolored bars represent a random sample drawn to match the yearly number of public care workers employed in a full-time municipality five years after a full-full-time decision. By creating these samples from non full-time municipalities it is possible to see that there does not seem to be any major changes in the distribution of contracted hours over time in municipalities that have not decided to implement full-time policies.

Panel (b) shows the distribution of contracted hours for public care workers in full-time municipalities one year before an actual de-cision compared to five years after. The change in distribution comes from increased density for contracts of 80, 85, and 90% of a full-time contract and a decrease in contracts below 80% of full-time. These figures have left out a 100% full-time contract, since that type of con-tract dwarfs the other and thus obscures changes in the distribution. Furthermore, for readability purposes contracts below 50% of full-time have been left out. For the full set of contracts, see Figure 1.8 in Appendix A, which also shows that the major change after a full-time policy has been decided upon seems to be the increase in contracts on exactly 100% of full-time. Figure 1.9 in Appendix A shows that these discrete changes in increments of five percentage points are at work also in municipalities that offer "free choice of hours".

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Panel (a) and (b) of Figure 1.7, in Appendix A, is another way to represent the same change reported here. Panel (a) shows that the dis-tribution of hours for public care workers in full-time municipalities, one year before a decision, is similar to the distribution of hours for public care workers in non full-time municipalities. Panel (b) shows that five years after the decision to implement a full-time policy, this is no longer the case. Five years after the decision, there are more workers on 80, 85, and 90% contracts than in the non full-time mu-nicipalities. At the same time, contracts below 80% of full-time work have decreased. Again, Figure 1.8, in Appendix A shows that there is also an increase in density for contracts on exactly 100% of full-time.

1.4.2 Contracted Hours and Annual Labor Earnings

If the existing contracts were preferred by all public care workers, a full-time policy would not change contracted hours of work for the employees. Thus, to continue to gauge at the effect on the distribution of contracted hours Figure 1.4 shows the outcomes from 100 regres-sions where the probability of being above different sets of contracted hours are the dependent variables and the independent variables are the medium run (4-7 years) difference-in-differences estimates. That is, in the first regression the dependent variable is the probability of having contracted hours above 1% of a full-time contract, which is represented by the first blue dot in the figure. In the last regression the dependent variable is the probability of having contracted hours above 99% of a full-time contract, which is represented by the last blue dot in the figure. The results from this exercise indicate that the change in contracted hours comes from an increase in contracted hours above 75% of a full-time contract. The jump in probability of being above 75% of a full-time contract tells the same story as the raw distribution of contracted hours in Figure 2.5, namely that most of the effect comes from workers on contracted hours of 75% and below increasing their hours.

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1.4. RESULTS 27

Figure 1.4: Change in distribution of contracts

-.02 -.01 0 .01 .02 .03 .04 .05 .06 .07 .08 .09 .1

Change in P(Contracted hours>x)

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Contracted hours (percent of full-time)

Notes: The results come from equation (1.1) in section 1.3.2. The regressions

in-clude municipality and year fixed effects, as well as controls for local government majority, age, gender, child, and educational dummies. The blue, dotted line rep-resents average treatment effects for the medium run (4-7 years) and the dashed, red lines represent the 95% confidence interval. Standard errors clustered on the municipality level. Each dot represents a regression on the dependent variable P(Contracted hoursimt>x), where x is the number represented on the x-axis.

Contracted hours and share of full-time workers are the outcomes directly targeted by the policy. However, contracted hours could in theory change without actual hours changing, which is why it is also important to look at labor earnings. Thus, the rest of this section will look into how the full-time policies affected the mean of contracted hours, share full-time workers and annual labor earnings. Figure 1.5 shows that the pre-trends are stable for all outcomes, indicating that the common trends assumption is plausible. The effects of the policies are clearly dynamic, increasing the first few years after the decision.

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Figure 1.5: Event-study estimates on earnings, contracted hours and full-time work -2000 0 2000 4000 6000 Annual earnings -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7

Event time in years

(a) Annual labor earnings

-1 -.5 0 .5 1 1.5 2 2.5

Contracted hours in percent of full-time

-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7

Event time in years

(b) Contracted hours -.05 -.025 0 .025 .05 .075 .1

Share working full-time

-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7

Event time in years

(c) Share working full-time

Notes: The blue, dotted line represents average treatment effects and the dashed,

red lines represent the 95% confidence interval. The results come from the event study regression (1.2) in section 1.3.2, where event time t-1 is the reference period. The regressions include municipality and year fixed effects, as well as controls for local government majority, age, gender, child, and educational dummies.

years after policy), medium run (4-7 years), and the long run (8+ years). In the short run, the change is not significant, but after 4-7 years annual earnings have increased by 3, 142 SEK on average (or ∼ 2% of mean earnings). Since 38% of the public care workers already had a full-time contract, that is an increase of ∼ 5, 000 SEK for the workers on part-time contracts (or ∼ 3% of mean part-time earnings).

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1.4. RESULTS 29

In the medium run contracted hours are 1.38 percentage points longer and the share of full-time workers has increased by 6%. The last point constitutes ∼ 10% of workers on part-time contracts switching to full-time contracts. The mid-point estimates for the long run effects are somewhat higher, but insignificantly so. Furthermore, they are less precise, because there are fewer observations left to measure a long run effect.

Panel B, C, and D of Table 1.5 show the same outcomes but divided into the three types of policy decisions with respect to how free the public care workers were in their choice of contracted hours (see Table 2.5 in Section 1.2). In the long run, the effects are not significantly different for public care workers in municipalities that offer "free choice of hours" to municipalities that offer either a part-time or a full-part-time contract. The positive effect on annual earnings and share working full-time is more immediate in the "free choice of hours" municipalities, with a significant effect already in the medium run. This can be explained by the fact that municipalities that offer a "free choice of hours" in general also implemented the policy faster than municipalities that offered a choice between part-time and full-time (see Table 2.5 in Section 1.2). In Appendix A, Table 1.9 indeed shows that there is a more immediate effect of the full-time policies in municipalities that implement the decision within a year.

Panel C shows the effect for those municipalities that offered sev-eral contracted hours options, but with increments of 5, or 10 per-centage points, rather than a free distribution. However, since only 15 municipalities offered this type of contract, the results are not very precise. There is a significant, and positive, effect on contracted hours and share working full-time in the long run, but a negative, and insignificant, effect on annual earnings.

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Table 1.5: Main outcomes

(1) (2) (3)

Annual Contracted Share working earnings hours full-time

Panel A: All public care workers

Short-run (0-3 years) 829 0.39 0.02∗∗∗ (515) (0.20) (0.00) Medium run (4-7 years) 3,142∗∗∗ 1.38∗∗∗ 0.06∗∗∗

(865) (0.31) (0.01) Long run (8+ years) 3,632∗∗ 1.44∗∗∗ 0.06∗∗∗

(1,264) (0.37) (0.01) Observations 3,958,528 3,958,528 3,958,528

Panel B: Free choice of hours municipalities

Short-run (0-3 years) 1,464∗ 0.72∗ 0.03∗∗∗ (662) (0.30) (0.01) Medium run (4-7 years) 4,343∗∗∗ 1.81∗∗∗ 0.07∗∗∗

(897) (0.34) (0.01) Long run (8+ years) 4,121∗∗ 1.74∗∗∗ 0.07∗∗∗

(1,328) (0.38) (0.01) Observations 2,817,413 2,817,413 2,817,413

Panel C: Partly Free choice of hours municipalities

Short-run (0-3 years) -425 -0.03 0.01 (827) (0.63) (0.01) Medium run (4-7 years) 263 1.02∗∗ 0.04

(1,387) (0.32) (0.02) Long run (8+ years) -1,152 1.60∗∗∗ 0.04∗

(1,819) (0.44) (0.02) Observations 2,247,692 2,247,692 2,247,692

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1.4. RESULTS 31

Panel D: Part-time or Full-time municipalities

Short-run (0-3 years) -483 -0.03 0.02∗∗ (1,086) (0.30) (0.01) Medium run (4-7 years) 2,000 0.79 0.05∗∗∗

(1,506) (0.61) (0.01) Long run (8+ years) 4,360∗∗ 0.95 0.07∗∗∗

(1,551) (0.61) (0.02) Observations 2,597,562 2,597,562 2,597,562

Notes: The results come from the regression equation (1.1) in section 1.3.2. Panel

B, C, and D only include subsets of public care workers depending on what type of municipality they work for, as defined in Table 2.5. The regressions include munici-pality and year fixed effects, as well as controls for local government majority, age, gender, child, and educational dummies. Annual earnings are inflation-adjusted and expressed in SEK. Contracted hours is defined as the percent of a full-time contract. Full-time is the share of full-time workers. Standard errors clustered at the municipality level in parenthesis.∗ p < 0.05,∗∗ p < 0.01,∗∗∗ p < 0.001

In Appendix A, Table 1.8 shows the same outcome for the subset of public workers employed by those municipalities that claim to im-plement the full-time policy for all workers. Panel A shows the effect for public care workers in those municipalities, Panel B for all other public workers, Panel C for public school (and preschool) workers, and Panel D for public child care workers. Public care workers in these municipalities have comparable effects to the full sample of public care workers. However, there does not seem to be a significant effect on other public workers. Only when focusing on public child care work-ers, a significant positive effect on earnings is visible. However, the effect is not stable, nor explained by an increase in contracted hours and should be interpreted with caution. In all, the full-time policies seem to mainly target public care workers, even in municipalities that implement the policy for all public workers.

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Table 1.6: Tenure and turnover

(1) (2) (3) (4) Tenure Share leaving Share leaving Share leaving

to other to other care employer municipality Short run 0.06 -0.004 -0.004 0.000 (0-3 years) (0.04) (0.003) (0.003) (0.000) Medium run 0.22∗∗ -0.013∗∗ -0.012∗∗ 0.001 (4-7 years) (0.08) (0.004) (0.004) (0.001) Long run 0.40∗∗∗ -0.011∗ -0.008 0.000 (8+ years) (0.11) (0.005) (0.005) (0.001) Mean one year 4.1 0.18 0.13 0.01 before decision

Observations 3,958,528 3,731,406 3,731,406 3,731,406

Notes: The results come from the regression equation (1.1) in section 1.3.2. The

regressions include municipality and year fixed effects, as well as controls for local government majority, age, gender, child, and educational dummies. Tenure is mea-sured in years and defined as consecutive years working in the public care sector for the same municipality. Column (2) shows the share leaving the public care sector in the municipality for any reason. Column (3) shows the share leaving the public care sector in the municipality to work in the private care sector or another level of public care (e.g. county hospitals). Column (4) shows the share leaving the public care sector in a municipality for public care employment in another municipality. Leaving can not be observed in 2013, which is why column (2)-(4) have fewer observations. Standard errors clustered on the municipality level in parenthesis.∗p < 0.05,∗∗ p < 0.01,∗∗∗ p < 0.001

1.4.3 Match Quality

One of the two main goals of the full-time policies was to make public work for the municipality more attractive. One way to measure the success of the policies and to understand if the possibility to choose hours worked more flexibly is popular among workers is to estimate the policies’ effect on tenure and turnover. If the turnover rate

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de-1.4. RESULTS 33

creases and workers stay employed by the municipality longer, it is a sign of the full-time policies having increased the match quality and being popular among the workers. Thus, Table 1.6 shows the effect of the full-time policies on tenure and different measures of the share of public care workers leaving the municipality employment. Column (1) shows the effect on tenure, defined as consecutive years working in the public care sector for the same municipality. Column (2) shows the effect on the share leaving employment in the public care sec-tor in the municipality that decided to implement a full-time policy. Column (3) shows the effect on the share leaving employment in the public care sector in the municipality to work in the private care sec-tor or another level of public care (e.g. county hospitals). Column (4) shows the effect on the share leaving employment in the public care sector in the municipality to work in the public care sector in another municipality. If public care employers use the full-time poli-cies to compete for workers from other municipalities, the last column could have shown such an effect. However, there are few transitions from municipality to municipality and it does not seem to change as a result of the full-time policies.

Table 1.6 shows that tenure increase by 0.22 years 4-7 years after policy decision, or 5% compared to the mean tenure the year before a full-time policy was decided on. The point estimate is almost twice as large, 0.4 years, in the long run. Here, it could perhaps be more illu-minating to look at the long run effects, since it could take some time for reduced turnover to translate to increased tenure. However, there is still the issue of there only being 30% of the full-time municipalities left to measure an effect on 8 years after the reform.

Further results show that the share leaving the public care sector at all in a municipality decreases by 1.3 percentage points, or 7%, 4-7 years after the decision. The effect is of the same magnitude for share leaving to another care employer, but that effect is not stable in the long run.

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Figure 1.6: Event-study estimates on labor demand- and supply proxies -.02 -.01 0 .01 .02

Share older residents

-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7

Event time in years

(a) Share over 65

-.04

-.02

0

.02

.04

Share private care workers

-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7

Event time in years

(b) Share private care workers

-500 -250 0 250 500 Monthly wage -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7

Event time in years

(c) Monthly wage rate

Notes: The blue, dotted line represents average treatment effects and the dashed,

red lines represent the 95% confidence interval. The results come from the event study regression (1.2) in section 1.3.2, where event time t-1 is the reference period. The regressions include municipality and year fixed effects, as well as controls for local government majority, age, gender, child, and educational dummies.

1.4.4 Robustness Checks

Demand and Supply Rather Than Policy?

One worry in the estimation of a policy effect is that there might be something else driving both the implementation of a full-time policy and hours worked. This does not show up in the common trends analysis, but it could potentially be the case that politicians decide

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1.4. RESULTS 35

to implement a policy because of changes in demand for or supply of public care sector workers. To exclude this possibility I use outcome variables that can act as proxies for supply and demand changes.

As a proxy for the demand of public care workers, I use the share of residents over the age of 65. Since public care workers employed by the municipality usually work in the elderly care sector, the share of older residents should affect the demand for public care workers.

Another proxy for both the demand and supply of public care workers is the share of care workers in the private sector. Last, if de-mand or supply factors lie behind the decision to implement full-time policies, this should be visible in the general wage trend of public care workers. If the demand for public care workers increases more in full-time municipalities prior to the policies, wages should go up. Thus, I run the regression specified in equation (1.2) on these outcomes. Fig-ure 1.6 shows the result of this exercise. None of the outcome variables trend differently before the decision to implement full-time policies. Wages do not change, either before or after the policies, the only thing that changes are hours worked, the outcome targeted by the policy. Thus, the common trends tests, both for the main outcome variables and the proxies for demand and supply factors point to the conclusion that it is the policies themselves, and not any underlying factors, that lie behind the effects found in Tables 1.4, 1.5, and 1.6.

The effect of full-time policies on the monthly wage rate could be interesting as an outcome in its own right. However, it is not straight-forward to interpret a wage effect. If full-time work is desirable from the workers’ perspective, but not the employers’, a potential effect of a full-time policy could have been a wage cut to compensate the employers. But since the full-time policies were forced upon the em-ployers, the expectations could also have been a wage hike, if workers negotiate over hours and wage and now with the policy do not need to negotiate for more hours. Panel (c) in Figure 1.6 shows that there is no effect on the wage rate, as a result of the full-time policies.

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Table 1.7: Full-time policies effect on sorting

(1) (2) (3) (4) Share Share with Share with Share with women children high school degree college degree Short-run 0.000 0.001 0.002 -0.001 (0-3 years) (0.001) (0.002) (0.003) (0.002) Medium run 0.003 0.002 0.006 -0.003 (4-7 years) (0.002) (0.004) (0.005) (0.004) Long run 0.009∗∗∗ 0.008 0.011 -0.003 (8+ years) (0.003) (0.005) (0.006) (0.004) Observations 3,963,728 3,963,728 3,958,528 3,958,528

Notes: The results come from the regression equation (1.3) in section 1.3.2. The

regressions include municipality and year fixed effects. Standard errors clustered on the municipality level in parenthesis.

∗

p < 0.05,∗∗ p < 0.01,∗∗∗ p < 0.001

Sorting

If public care workers get the opportunity to work full-time, it might become more attractive to work for the municipality for individuals looking for time work. Similarly, for workers not interested in full-time the municipality might become less attractive as a workplace. Thus, there is a possibility that the effects depend on sorting, rather than those originally employed by the municipality starting to work more. Since the estimations above are measured using repeated cross-sections it is not possible to separate these two potential effects.

Instead, to investigate the sorting mechanism, I run difference-in-differences regressions (see equation (1.3)) on outcome variables that should change if sorting takes place as an effect of the policies. Table 1.7 shows how the share of workers with children, share female work-ers, and share workers with different educational levels are affected by the policies. None of these changes as a result of the policies in the

Essays on Labor Economics : The Role of Government in Labor Supply Choices

Essays on Labor Economics

The Role of Government in Labor Supply Choices

Niklas Blomqvist

Dissertations in Economics 2020:1

Department of Economics

Essays on Labor Economics

The Role of Government in Labor Supply Choices

Niklas Blomqvist

Niklas Blomqvist

Essays on Labor Economics

Acknowledgements

Contents

Introduction

Chapter 1

"Right to Work Full-time"

Policies

and Involuntary Part-time Employment

1.1

Introduction

1.2

The Right to Full-time Policies

1.3

Data and Research Design

1.4

Results