do political parties matter? - evidence from german municipalities · 2019-01-10 · do political...

Do Political Parties Matter? - Evidence from

German Municipalities∗

Nadine Riedel† Martin Simmler‡ Christian Wittrock§

Abstract

This paper tests whether partisanship of local councils affects the level and composi-

tion of public spending by West German municipalities between 1994 and 2006. Our

identification strategy exploits changes in the party with the absolute majority in the

local council in combination with a matching strategy to address potential selection

into treatment. We find evidence for strong partisan effects: In communities with left-

wing councils, spending on ’people-oriented’ public goods, especially recreation goods

and social services, is significantly higher and spending on infrastructure public goods

is significantly lower than in communities with right-wing dominated councils.

.

Keywords: partisan effects, local governments, public spending

JEL Classification: H7, H4, R5

∗We are grateful to participants of the Congress of the German Economic Association in Vienna

and of the Annual Conference of the International Institute of Public Finance in Tokyo for helpful

comments and suggestions. We gratefully acknowledge financial support from the German Research

Foundation (Simmler: SI 2050/1-1 and Riedel: SI 2491/2-1).†Ruhr-University Bochum. E-mail: [email protected].‡University of Oxford Centre for Business Taxation. E-mail: [email protected].§RGS Econ, TU Dortmund and U Bochum. E-mail: [email protected]

1 Introduction

Do political parties matter? A growing body of empirical research suggests that the

answer to this question is ‘yes’, presenting evidence that political partisanship affects

various policy outcomes, including per-capita spending, spending composition and tax

rate choices (see e.g. Besley and Case (2003), Lee et al. (2004), Potrafke (2011a) and

Potrafke (2011b)).1 Existing studies on partisan effects are, however, largely restricted

to the state and federal level. Studies for localities are scarce, despite the fact that the

national and state results may not carry over to the local level, where interjurisdictional

mobility is high and Tiebout sorting into homogenous local units or competition for

mobile tax bases may limit the scope for partisan politics.

There are three recent exceptions. Ferreira and Gyourko (2009) study the link be-

tween partisanship and public spending of US cities, presenting evidence that partisan

effects are largely absent at the US city level. Freier and Odendahl (2015), in turn, pro-

vide evidence that the party composition of the local council and the party affiliation of

the mayor influence jurisdictions’ local business tax rate choices in the German state of

Bavaria. Sole-Olle and Viladecans-Marsal (2013) show that local left-wing governments

in Spain are less likely to convert land from rural to urban uses than their right-wing

counterparts.

We add to this literature by empirically testing for effects of partisanship on overall

spending and the composition of spending in German localities, which are the lowest

government tier in Germany. The analysis relies on detailed data on municipality spend-

ing across different spending categories between 1994 and 2006, including e.g. spending

for child and youth care, culture and infrastructure. The data is linked to information

on the party composition of local councils, which are the local legislative bodies that

decide on local tax and spending policies.

Our empirical strategy is a simple fixed effect regression framework using (ln)

overall spending and the spending shares for different sub-categories as dependent

variables. The main explanatory variable is a dummy if the SPD (CDU), the main left-

wing (right-wing) party in Germany, holds the majority of seats in the local council.

To avoid that our variable of interest captures spending differences between councils

with absolute majorities and coalition majorities, we focus our analysis on jurisdictions

with a change in the party that has the absolute majority in the local council.

1Related to this literature is work that tries to explain why political parties take on extreme

positions, see e.g. Alesina (1988), Besley and Coate (1997) and Glaeser et al. (2005)

1

While the simple fixed effect regression approach absorbs potential time-invariant

unobservable confounders, our estimates might still be biased by potential selection

into treatment. To address this, we combine the fixed effect with an entropy balancing

approach. Since the underlying reasons for a selection into treatment may differ between

jurisdictions with a change in the council majority from SPD to CDU compared to

from CDU to SPD, we construct two subsamples of jurisdictions and exploit that we

observe communities for two consecutive election periods. The first subsample only

includes jurisdictions in which we observe a SPD majority in the local council in the

first election period and either a remaining SPD majority in the consecutive election

period or a change to a CDU majority. In the second subsample, we only include

jurisdictions with a CDU council majority in the first election period, which either

remained unchanged in the second election period or changed to a SPD majority.2

Treatment and control communities are matched within these two subsamples. As

the estimation model includes a rich set of socio-economic municipality controls, our

matching variables focus on jurisdictions’ overall spending, spending composition and

local tax rates (as well as their changes) prior to the second period election. To ensure

covariate-balancing (see, e.g., Hainmueller (2012)), we employ entropy-balancing and

match on the first two moments of the distribution of the matching variables as well

as on the mean of federal state dummies.

The empirical approach hence resembles a difference-in-differences estimator that

compares changes in the level and composition of community spending between lo-

calities that are observationally identical prior to the second period election but then

do and do not experience a change in the council majority in the second election pe-

riod. Note that the model includes a broad set of control variables. Coupled with the

matching strategy, this implies that the empirical identification approach allows for dif-

ferences in underlying spending (composition) trends between treatment and control

jurisdictions that root in observed community characteristics or in unobserved factors

that correlate with localities’ pre-election spending characteristics that are used as

matching variables in the matching strategy.

Our results do point to quantitatively important partisan effects. When the council

majority changes from CDU to SPD (i.e. right-wing to left-wing), we observe a signif-

icant change in the composition of community spending: Spending for publics goods

2To increase the matching quality, our baseline estimates furthermore add communities with a

left-wing (right-wing) majority in the local council in both election periods to the control group in

the first (second) subsample.

2

and services that are targeted towards people (mainly spending for recreational goods

and services and social spending) increases, while spending for infrastructure goods

declines. The level of overall locality spending, in turn, remains unchanged. When the

council majority changes from SPD to CDU, our results, in turn, reject partisan effects

if all years of the electoral period are considered. When we focus on later years in

the election period, symmetric effects emerge in the sense that CDU-dominated local

councils spend more on infrastructure and less on ’people-oriented’ public goods and

services, irrespective of whether council majorities change from SPD to CDU or from

CDU to SPD. The effect size is with 2%-points or 10 to 15% substantial.

In the first post-election years, we in turn observe that both, CDU and SPD, spend

more on people goods and less on infrastructure goods when they gain power and take

over the majority of the local council seats compared to communities where the dom-

inant party in the council remains unchanged. One potential theoretical explanation

for this effect is that opposition parties, in electoral campaigns, have to differentiate

from incumbent policies to sharpen their profile and gain medial visibility. Opposi-

tion parties might find it attractive to promise and, if elected into power, eventually

implement spending policies that put more emphasis on consumptive spending (like

spending for ’people-oriented’ goods and services) than on investment spending (like

infrastructure spending) as the latter goes down better with short-sighted voters. On

top of that, the observed pattern might reflect responses to incumbents’ pre-election

spending choices, which tend to be characterized by increased investment spending

in pre-election years and constant overall spending (see e.g. Kneebone and McKen-

zie (2001), Gonzalez (2002), Brender (2003), Khemani (2004) and Drazen and Eslava

(2010)). Our results are consistent with the notion that parties that gain legislative

power reverse these spending trends (more strongly than incumbents) after the elec-

tion.

Our paper contributes to the prior literature on partisan effects in several ways.

First, we test for partisan effects at the local level, while much of the literature focuses

on state and federal governments and legislative bodies. Existing papers for the local

level, moreover, largely ignore government spending policies and, if they do not, the

spending categories assessed tend to be broad (Ferreira and Gyourko (2009)). We, in

turn, can draw on detailed information on the level and composition of government

spending. While we, similar to Ferreira and Gyourko (2009), do not observe partisan

effects in overall government spending or spending for general public goods, our find-

ings point to partisan effects in detailed spending sub-categories, namely recreational

3

spending and social spending (which dominate the ’people-oriented’ public goods and

service category defined in this paper) and spending for infrastructure, in particular

streets. Secondly, our results stress that tests for partisan effects based on changes

in council majorities are complicated by the fact that opposition parties that come

into power choose spending policies that systematically deviate from spending pat-

terns when majorities remain unchanged (irrespective of whether the change is from

left to right-wing majorities or vice versa). We consider this to be an interesting finding

in its own right. Policy effects of leadership changes have so far received only limited

attention in the empirical literature, with Brender and Drazen (2013) being a notable

exception.3

The remainder of the article is as follows. Section 2 describes the institutional

background and the data. The methodology is outlined in section 3 and section 4

presents the results. Finally, section 5 concludes.

2 Institutional Background and Data

Our empirical analysis assesses the impact of partisanship of local council majori-

ties on overall local spending and the composition of municipal spending using West

German localities as a testing ground.4 In the following, we describe the institutional

background and the data set used for the empirical analysis.

2.1 Institutional Background

According to the German constitution, German municipalities have elected legisla-

tive bodies and governments and have the right to solve any local matters autonomously

(Article 28 of the German constitution). Localities generate income mainly from three

3Brender and Drazen (2013) investigate in a panel of 71 countries whether leadership change affects

an index that aggregates changes in government expenditure over several spending categories. They

find that newly elected leaders in developed countries change expenditure composition in the long run

(i.e. after several years). They attribute the absence of a short run effect to ”legislative, bureaucratic,

or special-interest roadblocks to change” and provide some evidence that suggests it might take time

for newly elected leaders to learn how to steer the budget process in their desired direction. Note that

our testing ground considerably differs from Brender and Drazen (2013) as we study local elections

and determine the impact of changes in local council majorities.4We focus on West Germany as data for public goods and service spending is available for a longer

time span in these localities compared to their East German counterparts.

4

sources. Firstly, a fraction of the personal income tax and the value added tax revenue

administered at the federal and state level are distributed to German municipalities

based on fiscal rules. Second, municipalities receive general and special grants by higher

government tiers. Third, localities have two (major) own revenue instruments at hand:

firstly, they autonomously set the local business tax rate, levied on business income

earned within their borders and secondly, they choose the local property tax.5 The

majority of tax revenues from these two sources remains with the locality, only a minor

fraction is redistributed by fiscal equalization schemes.6 Note that the own tax revenue

instruments generate a significant fraction of local income (on average about 20%).7

German municipalities moreover provide various local public goods and services

(PIGS), e.g. related to the construction and maintenance of roads, sewerage, kinder-

gartens and primary schools. Further, municipalities have to provide social benefits to

the unemployed and social welfare recipients. Additionally, public goods and services

related to culture and sport facilities, tourism, and public transport may be provided.

While some expenditures are mandatory, including administration, social security and

financing liabilities, others are optional, including e.g. spending for theaters, youth

centers, the promotion of science, health care, sport and recreation facilities.

Finally note that legislative processes in the local councils are regulated in the

municipal codes of the community’s hosting state. Municipal codes are similar across

states. Most importantly, in all federal states a simple majority of votes in the local

council is required to enact changes in tax and spending policies.

2.2 Data

As described above, the purpose of our analysis is to test for partisan effects on

local government spending. Our analysis relies on rich data for spending of West Ger-

man localities between 1992 and 2006, which is drawn from municipalities’ accounting

information provided in the Jahresrechnungsstatistik. East Germany is disregarded as

spending information is available from the late 1990ies onwards only. The spending

data allows us to construct spending items for detailed and disaggregated expenditure

categories. Note that, although German municipalities operate in a homogenous en-

5Note that Germany localities set two property taxes (A and B). Property Tax A is applied on

land used for agriculture and forestry. Property Tax B is used for any other build-up property.6Municipalities may also levy other minor local taxes (e.g. a ’dog tax’).7Calculations are based on our sample and the year 2006.

5

vironment, their spending responsibilities are influenced by their size and status. To

increase the comparability of our sample municipalities, we hence focus on small and

mid-size cities with an average number of inhabitants over our sample period between

1,000 and 50,000 and also exclude urban cities (kreisfreie Staedte).

We define different variables to capture the size and structure of municipality spend-

ing, namely (ln) overall real expenditures and (ln) financial expenditures as well as (ln)

voluntary expenditures.8 The voluntary spending measure accounts for the fact that

communities have a number of mandatory spending obligations, which offer no room

for partisan politics. The construction of the voluntary spending measure thus ignores

expenditures that are organized and carried out by higher government tiers, for exam-

ple, at the county level. Second, we exclude spending categories for which the voluntary

dimension tends to be small. See Footnote 9 below for details on the specific spending

categories that enter the voluntary spending variable.

To test for partisan effects on the composition of government, we, in a first step,

account for four relatively broad spending categories. These are (1) spending for gen-

eral public goods, (2) spending for ’people-oriented’ public goods, (3) spending for

culture and (4) spending for infrastructure public goods. Each of the blocs, except of

culture spending, consists of several subcategories. Spending for general public goods

consists of spending for (1.1) public administration, (1.2) public safety, (1.3) commer-

cial enterprises (e.g. own utility or public transport firms) and (1.4) general planning.

Spending for people-oriented public goods consists of spending for (2.1) schools, (2.2)

recreation (as parks and sport facilities) and (2.3) spending for people in need (social

spending). Spending for infrastructure public goods consists of spending for (3.1) roads,

(3.2) public facilities (e.g. sewerage, waste but also public markets) and (3.3) economic

promotion. Testing for partisan effects based on these broad categories offers the ad-

vantage, that estimates are expected to be more precise if the chosen subcategories

are substitutes (what we presume). We will, however, in the following also test for

partisan effects based on individual spending sub-categories. Note, moreover, that in

defining these spending sub-categories, we again define both, comprehensive measures

8Financial expenditures comprise interest payments, debt service as well as taxes and grants trans-

fered to other government tiers.

6

and measures that only comprise voluntary spending within the sub-categories.9 See

Tables (1) and (2) for descriptive statistics. On average municipalities have overall real

expenditures of about 8.96 million Euro and financial expenditures of about 5.89 mil-

lion Euro. The average share of voluntary expenditures to overall real expenditures is

42%. General public spending, spending for ’people-oriented’ goods and infrastructure

spending make up broadly one third of overall spending each. Spending for cultural

goods is, in turn, a small post in communities’ budget.

The sketched spending data is linked to information on the party composition of the

local council obtained from the German Federal Statistical Offices. As will be sketched

in the next section, our empirical identification strategy relies on changes in the party

composition of the local council in the wake of council elections. The timing of council

election varies across German states (as does the term length, which varies between

four and six years). See Table (3) for an overview of election dates and election periods

in each state in our data frame. Note that, on average, we observe three election periods

per state within our data frame.

The party composition of local councils in Germany is shaped by the five main par-

ties, that are also active at the state or federal level, as well as several civil parties that

9Specifically, in all expenditures in the public administration category are defined as voluntary

spending. In term of public safety, spending for policy, public order and the fire department are

classified as voluntary and spending for the environmental office and emergency management as non-

voluntary; For schools, spending on primary and secondary schools as well as spending on schools with

special needs is classified as voluntary, while spending for administration, vocational schools, techni-

cal schools, school transport and other school-related spending is classified as mandatory. In terms of

culture, voluntary spending comprises spending for science and research, museums, collections, the-

aters, concerts, public education and local heritage; non-voluntary spending in that category comprises

spending for administration and churches; In the social spending category, we classify spending for

social welfare centres, nurseries, children and youth work and support for soon-to-be mothers as volun-

tary spending. Non-voluntary in that category comprises spending for administration, social welfare,

support for war victims, support for education, support for young adults and support for families.

In the ’recreation spending’ category, voluntary spending includes spending for sports and own sport

venues, public swimming pools, parks and gardens, other recreation facilities. Non-voluntary spending

in that category comprises spending for administration, hospitals, other health spending. All spending

in the ’general planning’ category (comprising spending for a local building authority and spending for

city planning) is considered to be voluntary. Spending for local streets, county streets, street lightning

and parking facilities is, moreover, considered to be voluntary, while spending for state and country

streets as well as rivers is classified as mandatory. In terms of public facilities, markets and other public

facilities are considered voluntary, while sewerage and waste disposal, slaughterhouses and death care

are mandatory. Moreover, all spending related to public companies is classified as mandatory.

7

Table 1: Descriptive Statistics for Overall Spending and Control Variables

Mean Median Std. Dev.

Overall revenue in million Euro 14.43 6.60 23.02

Real expenditure in million Euro 8.96 3.88 15.03

Financial exp. in million Euro 5.89 2.76 9.24

Overall voluntary public good spending 42.23 42.73 12.91

(as a fraction of overall spending)

Local business tax multiplier 335.80 330.00 33.77

Population in 1000 8.18 3.99 10.96

Share Population under 20 0.23 0.22 0.02

Share Population over 65 0.17 0.17 0.02

Employees in 1000 2.62 1.29 3.49

Unemployment Rate (County) 9.13 8.80 2.37

Debt per capita 942.56 930.39 303.96

Notes: Sample includes all jurisdictions with a SPD or CDU dominated council. Note

that municipalities set a tax multiplier for the local business tax that is reported in the

table. The tax burden is calculated as the product of this multiplier and a base rate

(’Messzahl’) that was 5% for incorporated businesses during our sample period.

Source: Authors’ calculations based on Statistik Lokal and Jahresrechnungsstatistik 1994

to 2006.

focus their activities to the local level. The five main parties are the Christian Demo-

cratic Union and their Bavarian sister party the Christian Social Union in the German

state of Bavaria (in the following, we will refer to both as CDU), the Free Democratic

Party (FDP), the Social Democratic Party (SPD), the Greens (B90/Gruene) and the

party ‘Die Linke’. Following Pappi and Eckstein (1998), these parties can be classified

on a left-wing right-wing scale, where “Die Linke” is on the extreme left and the FDP

on the extreme right. SPD and CDU are the moderate left and right-wing parties. The

Greens are left to the SPD but are, additionally, proponents of environmentally-friendly

policies. Note that this classification scheme cannot be used for the civil parties, whose

programs tend to vary between localities.

To ferret out partisan effects, we will in the following concentrate the analysis on

communities, where the local council is dominated by the large right-wing party, CDU,

or the large left-wing party, SPD, in the observed election periods, or where there is

a switch in the dominating party from SPD to CDU or the other way round. Note

that with ’dominated’, we mean that the considered party holds more than 50% of

the seats in the local council. This design helps us to, firstly, avoid effects related to

8

Table 2: Descriptive Statistics for Spending Composition

Mean expenditure shares for ... ...based on...

in % overall expenditures voluntary expenditures

General public goods 30.73 21.45

Administration 13.82 12.95

Public safety 4.54 4.17

Commercial enterprises 7.75 0.00

General planning 4.62 4.33

’People-oriented’ public goods 33.62 18.12

Schools 10.49 7.50

Recreation 5.47 3.96

Social 17.66 6.67

Culture 1.84 1.23

Infrastructure public goods 33.10 16.96

Traffic 12.53 10.90

Public facilities 18.31 4.44

Economic promotion 2.26 1.62

Notes: Sample includes all jurisdictions with a SPD or CDU dominated council.

Source: Authors’ calculations based on Statistik Lokal and Jahresrechnungsstatistik 1994 to 2006.

Table 3: Elections for the Local Council by State and Year (1993 to 2006)

Year

State 93 94 95 96 97 98 99 00 01 02 03 04 05 06

Schleswig-Holstein X X X

Lower Saxony X X X

North Rhine-Westphalia X X X

Hessia X X X X

Rhineland-Palatine X X X

Baden-Wuerttemberg X X X

Bavaria X X

Saarland X X X

Source: Own data collection.

9

divided governments and political coalitions and, secondly, does not require classifying

local civil parties with varying political positions on the left-right-spectrum. Note,

however, that this also implies that we disregard sample localities, where the local

council is either dominated by a civil party or there is no dominant party at all. In

the end, around 25% of the West German municipalities enter our sample. Around two

thirds of the municipality-year observations is characterized by a local council that is

dominated by the CDU and one third by a local council dominated by the SPD.

We further merged information on socio-economic characteristics of the localities to

our data. These include overall population as well as the age structure of the population,

number of employees, the unemployment rate and debt per capita (the latter two are

available on the county level). Descriptive statistics for the spending variables and the

control variables for communities with an SPD or CDU dominated council respectively

are shown in Table (1). The average municipality has around 8.200 inhabitants and

around 23% (17%) of the population are aged below 20 (above 65).

3 Methodology

Our baseline empirical strategy to assess the impact of partisanship of local coun-

cil majorities on overall spending and spending composition is a simple fixed effect

regression, which reads as follow:

yit = α1Pit + α2Xit + λi + κst + εit. (1)

Our dependent variables are the different measures for the size and structure of local

spending described in the previous section. Our main explanatory variable is Pit, which

is an indicator variable that is one if the ‘SPD’ (CDU) holds the majority (more than

50% of the seat shares) in the local council. The model accounts for municipality fixed

effects λi and state-year fixed effects κst, hence absorbing time constant heterogene-

ity across localities and common shocks to municipality spending in given states over

time. The approach consequently resembles a difference-in-difference strategy, compar-

ing adjustments in the spending of localities with changing majorities in the course of

elections to localities where majorities remained constant. In our sample period, we

observe 59 jurisdictions with a switch in the dominant party in the local council (44

10

from SPD to CDU and 15 from CDU to SPD). While this number of treated observa-

tions is small, the strong sample requirements ensure that the jurisdictions included in

the sample are comparable.

The vector Xit comprises socio-economic control variables for our sample jurisdic-

tions. These include (ln) localities’ population (in 1000), (ln) employed population, age

composition of the jurisdiction as determined by the population shares aged under 20

and above 65 as well as the (ln) unemployment rate and (ln) municipalities debt per

capita (both on the county level). We report robust standard errors that are clustered

at the municipality level.

The Achilles’ heel of the difference-in-differences approach is the common trend

assumption and the assumption that the treatment is exogenous. Thus, treatment and

control group should have behaved similarly in the absence of the treatment and juris-

dictions should not be able to self-select into treatment. In our case, these assumptions

are likely to be violated as the treatment depends on voting behavior in a jurisdiction,

which is influenced by spending policies in the past as well as the jurisdictions’ eco-

nomic environment. Further, municipalities facing different economic environments are

less likely to behave in a similar manner. That this is not only a theoretical concern

can by seen by comparing characteristics of jurisdictions with a SPD dominated coun-

cil and a CDU dominated council (see Columns (1) and (3) in Table (A1) and Table

(A2) in the Appendix). Jurisdictions with SPD majorities tend to be smaller, have

less workers, lower overall expenditures and in particular a lower share of voluntary

spending. To address the potential selection of jurisdictions into the treatment group,

we combine the simple fixed effect framework with a matching strategy.

The most often used matching approach in the literature is propensity score match-

ing (where the propensity score represents the likelihood of being treated). It can be

used to match observations, e.g. to find the closest control unit for every treatment ob-

servation, or to weight observations to create balance between control and treatment

units (see Imbens, 2004, for a review). One particular assumption of the propensity

score approach is that the distribution behind the mean of the matching variables is

the same, as otherwise differences between treatment and control group are not-random

and thus bias the estimated average treatment effect.

One recently proposed approach to overcome the lack of co-variance balancing in

a selection-on-observables framework is entropy-balancing (Hainmueller (2012)). The

main advantage of this method is that covariate balancing is not just assumed but

11

enforced in a constrained, nonlinear estimation approach. The approach obtains weights

for each targeted moment of the balancing/matching variables for treatment and control

group subject to the balancing constraints. The resulting weights can then be used in

a weighted regression.10

Therefore, we apply entropy balancing to balance characteristics of treatment and

control group jurisdictions in the year before the election. Since the underlying reasons

for a change from SPD to CDU majorities in local councils is likely to be different to

a change from CDU to SPD, we construct two subsamples. Each of the two subsample

includes two consecutive election periods of jurisdictions. In the first subsample (Panel

A), we include three types of jurisdictions: (i) jurisdictions which had a CDU majority

in both election periods, (ii) jurisdictions which had a right-wing majority in both

periods and (iii) jurisdictions which had a CDU majority in the first election period

and a SPD majority in the second election period. We do not include jurisdiction in

which the majority changed from right-wing to SPD as this would mean comparing also

divided governments with absolute majorities. We do, however, include jurisdictions

with a right-wing majority in both election periods as this increases the size of the

control group and thus the matching quality. In the second subsample (Panel B), we

include again three types of jurisdictions: (i) jurisdictions with a SPD majority in the

local council in both election periods, (ii) jurisdictions with a left-wing majority in

both election periods and (iii) jurisdictions with a SPD majority in the first election

period and a CDU majority in the second election period.11

We use the same set of matching variables for both subsamples. Specifically, we

include (ln) real expenditures, (ln) financial expenditures and the local business tax

rate as well as the voluntary spending shares for general public goods, people public

goods, culture and infrastructure public goods in the year prior to the second-period

election. In robustness checks, we will, furthermore, change the set of matching variables

to include variables for changes in spending patterns (overall spending and spending

composition) prior to the second-period election. Further, we match on state dummies.

We target for all variables (except for the state dummies) mean and variance of the

10One advantage of entropy balancing compared to coarsened exact matching, another covariate

balancing approach, is that entropy balancing does not disregard treatment and control observations

that cannot be matched exactly.11If we observe three election periods for a particular jurisdiction, the jurisdiction could be in

both subsamples depending on the majority. Note, moreover, that similar results emerge when the

jurisdictions with stable right-wing and left-wing majorities are discarded from the control groups.

12

distribution. The resulting balancing statistics for panel A and panel B are shown in

Table (A1) and Table (A2) in the Appendix.12 The descriptive statistics suggests that

the entropy balancing is highly effective as all variables in the re-weighted sample are

very similarly distributed for treatment and control group. Further, the balancing also

decreases differences in the size of jurisdictions.

4 Results

In this section we report the results of our analysis. We start with a simple fixed ef-

fects model that includes all jurisdiction-years where the local council was dominated by

the SPD or CDU (Panel A and Panel B). The results are presented in row (1) of Table

(4). Specifically, we test for partisan effects on the log of overall real expenditures, fi-

nancial expenditures, voluntary expenditures as well as localities’ spending composition

as captured by voluntary spending shares for general expenditures, ’people-oriented’

expenditures, cultural expenditures and infrastructure spending. The results suggest

that jurisdictions with a SPD majority levy, on average, a higher tax rate on business

profits and spend slightly more on ’people-oriented’ public goods than communities

with a CDU council majority. Both effects are, however, only marginally statistically

significant. Estimates for partisan effects in the other spending dimensions, moreover,

do not point to statistically significant differences in policy choices between CDU and

SPD.

To address potential selection into treatment, we split the sample into the two sub-

samples described above, Panel A and Panel B. Row (2) and (3) show the difference-in-

differences results that compare spending trends for jurisdictions with unchanged CDU

or CDU coalition majority and jurisdictions with a change from CDU to SPD majority.

Row (4) and (5) show the difference-in-differences results that compare spending trends

for jurisdictions with unchanged SPD or SPD coalition majority and jurisdictions with

a change from SPD to CDU majority. In row (2) and (4) we use the unweighted sam-

ples and in row (3) and (5) the entropy balanced samples. When comparing spending

patterns in localities that moved from CDU majorities in the local councils to SPD

majorities with those that kept CDU/right-wing majorities throughout the two consec-

utive election periods, we find that SPD majorities significantly increase the spending

12Tables A3 and A4 show the balancing statistics when the changes in spending patterns before the

second-period election are used as matching variables.

13

share assigned to ’people-oriented’ public goods and services. This is consistent with

the baseline fixed effects result, but is more precisely estimated and the effects turn out

to be quantitatively larger. In the unweighted sample, the point estimate suggests that

the spending share for ’people-oriented’ expenditures increases by around 4 percentage

points when the SPD takes over the council majority, which is quantitatively substan-

tial given that the mean spending share is around 18% for this spending category. In

the entropy-balanced sample, the effect further increases in size to 4.6%. Moreover, the

estimates from the entropy-balanced sample also suggest that a move from a CDU to a

SPD majority is associated with lower spending on infrastructure public goods. Again,

the effect is quantitatively substantial, suggesting that infrastructure spending drops

by 3.6 percentage points. The findings, however, do not point to significant partisan

effects on (ln) overall real government spending, (ln) financial spending, (ln) overall

voluntary spending and jurisdictions’ tax rate choice. Table (A5) in the Appendix fur-

thermore shows that these findings are not driven by the definition of our voluntary

spending measures. Modelling the spending composition of our sample communities by

overall spending shares for each category (instead of voluntary spending shares) yields

similar results.

Note, again, that augmenting the estimation model by time-varying socio-economic

community controls coupled with the entropy matching implies that the estimation

approach allows for differences in underlying spending trends related to changes in

observed locality characteristics (e.g. changes in the unemployment rate, population

or age structure of the locality) as well as differences in spending trends that root in

the composition and size of government spending or tax policies prior to the second-

period election. Table A6 in the Appendix, moreover, shows that these results are

robust to changing the set of matching variables in the entropy-balancing approach

to include variables that capture changes in the public spending level and spending

structures prior to the second-period election (namely, changes from two years prior to

the second-period election to the election year). In this sample, matched communities

hence have similar pre-treatment trends in overall spending and spending composition.

Interestingly, a different result pattern emerges when we study changes from SPD

to CDU majorities. Here, the coefficient estimates for the CDU dummy turn out in-

significant across all defined spending variables if all years of the election period are

considered, cf. row (4) and (5) of Table 4. There are two potential explanations for

this result pattern. Firstly, as the baseline estimates do not identify partisan effects

for overall public good spending but only for the composition of spending, the results

14

Tab

le4:

Est

imat

ion

Res

ult

s-

Ove

rall

Sp

endin

gan

dShar

esfo

rV

olunta

rySp

endin

g

Dep

.V

ar.

(ln

)(l

n)

(ln

)L

oca

lS

har

e

Rea

lF

inan

cial

Vol

unta

ryB

usi

nes

sG

ener

al

Peo

ple

Cu

ltu

reIn

fras

tru

ctu

re

Exp

.E

xp

.E

xp

.T

axR

ate

Exp

.E

xp

.E

xp

.E

xp

.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

SP

Dvs

Un

ion

Majo

rity

inth

eL

oca

lC

ounci

l:N

=15

,614

SP

D0.

016

-0.0

090.

037

2.222

*-0

.692

1.1

32*

-0.0

41

-0.4

11

(0.0

21)

(0.0

34)

(0.0

27)

(1.2

79)

(0.5

54)

(0.6

80)

(0.1

50)

(0.8

40)

Unw

eighte

dP

an

elA

:C

DU

Coa

liti

on

-CD

UC

oali

tion

,C

DU

-CD

Uvs

CD

U-S

PD

,N

=10

,471

SP

D0.

030

0.02

60.

076

4.589

-0.2

224.5

38*

**0.

137

-2.5

78

(0.0

36)

(0.0

65)

(0.0

51)

(3.6

66)

(1.6

55)

(1.5

81)

(0.2

39)

(1.5

96)

Entr

opy-B

ala

nce

dP

an

elA

:C

DU

Coa

liti

on

-CD

UC

oali

tion

,C

DU

-CD

Uvs

CD

U-S

PD

,N

=10,

471

SP

D0.

041

0.04

50.

065

2.127

-0.0

535.0

71*

**0.

167

-3.8

11*

*

(0.0

33)

(0.0

60)

(0.0

52)

(3.1

79)

(1.1

75)

(1.3

71)

(0.1

66)

(1.5

62)

Unw

eighte

dP

an

elB

:S

PD

Coa

liti

on-S

PD

-Coal

itio

n,

SP

D-S

PD

vs.

SP

D-C

DU

,N

=4,

144

CD

U0.

027

0.04

4-0

.010

-2.0

31

-0.1

11

0.1

81

0.116

-0.2

73

(0.0

33)

(0.0

51)

(0.0

39)

(1.6

60)

(0.7

30)

(1.0

59)

(0.2

28)

(1.3

11)

Entr

opy-B

ala

nce

dP

an

elB

:SP

DC

oal

itio

n-S

PD

-Coa

liti

on,

SP

D-S

PD

vs.

SP

D-C

DU

,N

=4,

144

CD

U0.

033

0.03

40.

018

-2.2

86-0

.422

1.0

53

-0.0

60-1

.054

(0.0

34)

(0.0

52)

(0.0

45)

(1.7

20)

(0.7

73)

(1.2

50)

(0.1

58)

(1.0

72)

Con

trol

Var

,M

un

icip

alit

yan

dS

tate

-Yea

rF

EX

XX

XX

XX

X

Notes:

Tab

lesh

ow

sth

ep

oin

tes

tim

ate

sfo

rS

PD

(row

(1)

to(3

))or

CD

Um

ajo

rity

(row

(4)

an

d(5

))in

the

loca

lco

un

cil

usi

ng

diff

eren

td

epen

den

tvari

ab

les.

All

regre

ssio

nin

clu

de

contr

ol

vari

ab

les,

mu

nic

ipality

fixed

effec

tas

wel

las

state

-yea

rfi

xed

effec

ts.

Th

ed

epen

den

tvari

ab

les

are

:(l

n)

real

spen

din

g(c

ol.

(1))

,(l

n)

fin

an

cial

spen

din

g(c

ol.

(2))

,(l

n)

volu

nta

rysp

end

ing

(col.

(3))

,ju

risd

icti

on

s’b

usi

nes

sta

xra

tech

oic

e(c

ol.

(4))

an

dth

evolu

nta

rysp

end

ing

share

sfo

rgen

eral

pu

blic

goods

(col.

(5))

,p

eop

lep

ub

lic

good

s(c

ol.

(6))

,cu

ltu

re(c

ol.

(7))

an

d

infr

ast

ruct

ure

pu

blic

good

s(c

ol.

(8))

.R

ow

(1)

show

sth

eeff

ect

when

ass

um

ing

sym

met

ryfo

rth

ech

an

ge

from

SP

Dto

CD

Uan

db

ack

.In

row

(2)

an

d(3

)w

efo

cus

on

juri

sdic

tion

sw

ith

un

chan

ged

CD

Uor

CD

U-c

oaliti

on

ma

jori

tyin

the

loca

lco

un

cil

or

ach

an

ge

from

CD

Uto

SP

Dm

ajo

rity

.In

row

(4)

an

d(5

)w

efo

cus

on

juri

sdic

tion

sw

ith

eith

eru

nch

an

ged

SP

Dor

SP

D-c

oaliti

on

ma

jori

tyin

the

loca

lco

un

cil

or

ach

an

ge

from

SP

Dto

CD

Um

ajo

rity

.In

row

(2)

an

d(4

)an

unw

eighte

dsa

mp

lean

din

row

(3)

an

d(5

)an

entr

opy-b

ala

nce

dsa

mp

leis

use

d.

Sta

nd

ard

erro

rsin

pare

nth

esis

are

rob

ust

an

dcl

ust

ered

at

the

mu

nic

ipali

tyle

vel

.*,

**,

an

d***

den

ote

sign

ifica

nce

at

the

10,

5,

an

d1%

level

.Source:

Au

thors

’ca

lcu

lati

on

sb

ase

d

on

Sta

tist

ikL

okal

an

dJah

resr

ech

nu

ngss

tati

stik

1994

to2006.

15

might relate to the aggregation of individual spending items to broad spending cate-

gories. We hence re-estimated the baseline models using spending shares for individual

spending items as the dependent variable. Analogously to the baseline analysis, we

restrict our view to spending shares related to our voluntary expenditures, as defined

above, since these are the ones that can plausibly (most strongly) be influenced by par-

tisan politics. Moreover, we focus on individual spending items in the sub-categories of

’people-oriented’ goods expenditures and infrastructure spending as the baseline find-

ings supported partisan effects in these dimensions. Columns (1) to (3) of 5 reestimate

the baseline specifications with the three individual spending items in the ’people-

oriented’ expenditure category: spending for schools, spending for recreation goods

and services and spending for social goods and services (see Footnote 9 and Table 2).

Analogously, Columns (4) and (6) reestimate the baseline model for three particular

spending items related to infrastructure spending, namely spending for streets, public

facilities and economic promotion. The findings largely reject that the difference in the

partisan effects observed in Panels A and B of the baseline analysis masks (potentially

consistent) partisan effects of different sign and size in individual sub-categories.

Another explanation for the result pattern is that partisan effects are partly masked

by changes in local policies that relate to the fact that local council majorities change in

our empirical setting. If leadership changes impact on spending and tax policy choices,

this may confound our empirical estimates. To test for this possibility, we interact

the majority indicator with a continuous variable that measure the year within the

election period (e.g. first year = 0, second year = 1, etc). The approach hence allows

for differences in partisan effects across election years in our setting. If the fact that new

partisan majorities dominate the local council affects spending policies (irrespective of

whether the change is from CDU to SPD or vice versa), this may impact our estimates

for spending in post-election years.

The results are presented in Table (6).13 While both, changes from CDU to SPD

majorities and changes from SPD to CDU majorities are not associated with differences

in the level of real, financial or voluntary spending, the results suggest that both SPD

and CDU, when they newly gain the majority in the local council, adjust the compo-

sition of public spending and allocate more spending to ’people-oriented’ public goods

and services and less towards infrastructure spending relative to councils where the

dominant party remains unchanged in the election. This effect declines over the elec-

13Observations are unweighted in all specifications of 6. Similar results, however, are obtained in

entropy-balanced samples.

16

Table 5: Estimation Results - Shares for Voluntary Spending in Subcategories

Dep. Var. Expenditure Shares

’People-Oriented’ Exp. Infrastructure Exp.

Schools Recreation Social Streets Public Economic

Facilities Promotion

(1) (2) (3) (4) (5) (6)

SPD vs Union Majority in the Local Council: N=15,833

SPD -0.143 0.637* 0.638* -0.244 -0.108 -0.058

(0.366) (0.347) (0.364) (0.687) (0.347) (0.284)

Panel A: CDU Coalition-CDU Coalition, CDU-CDU vs CDU-SPD: N = 10,471

Unweighted Panel A

SPD 2.028** 0.438 2.073** -0.921 -0.936* -0.720***

(0.862) (0.550) (0.916) (1.647) (0.512) (0.238)

Entropy-Balanced Panel A

SPD 2.128** 0.858* 1.664** -1.282 -1.474** -0.873**

(0.864) (0.501) (0.824) (1.484) (0.606) (0.367)

Panel B: SPD Coalition-SPD-Coalition, SPD-SPD vs. SPD-CDU: N = 4,144

Unweighted Panel B

CDU 0.556 -0.097 -0.277 -0.822 0.340 0.209

(0.535) (0.543) (0.595) (0.981) (0.644) (0.388)

Entropy-Balanced Panel B

CDU 1.336* -0.347 0.064 -1.184 0.228 -0.099

(0.756) (0.676) (0.601) (0.783) (0.599) (0.356)

Control Variables X X X X X X

Municipality FE X X X X X X

State-Year FE X X X X X X

Notes: Table shows the point estimates for SPD (row (1) to (3)) or CDU majority (row (4) and (5)) in the local

council using different dependent variables. All regression include control variables, municipality fixed effect as well

as state-year fixed effects. The dependent variables are: (ln) real spending (col. (1)), (ln) financial spending (col. (2)),

(ln) voluntary spending (col. (3)), jurisdictions’ local business tax rate choice (col. (4)) and the voluntary spending

shares for general public goods (col. (5)), people public goods (col. (6)), culture (col. (7)) and infrastructure public

goods (col. (8)). Row (1) shows the effect when assuming symmetry for the change from SPD to CDU and back.

In row (2) and (3) we focus on jurisdictions with unchanged CDU or CDU-coalition majority in the local council

or a change from CDU to SPD majority. In row (4) and (5) we focus on jurisdictions with either unchanged SPD

or SPD-coalition majority in the local council or a change from SPD to CDU majority. In row (2) and (4) an

unweighted sample and in row (3) and (5) an entropy-balanced sample is used. Standard errors in parenthesis are

robust and clustered at the municipality level. *, **, and *** denote significance at the 10, 5, and 1% level. Source:

Authors’ calculations based on Statistik Lokal and Jahresrechnungsstatistik 1994 to 2006.17

toral period. In later years, the results are consistent with symmetric partisan effects in

both samples (Panel A and Panel B): If the SPD gains the council majority, spending

on ’people-oriented’ goods is increased at the expense of spending on infrastructure; if

the CDU gains the council majority, spending on infrastructure is increased relative to

spending on ’people-oriented’ goods. See also the specifications in the last row of Table

6 which compares spending patterns between SPD and CDU dominated local councils

in the last two years of the electoral cycle.14 Quantitatively, the latter estimates suggest

that the SPD dominated councils spend around 2%-points more on ’people-oriented’

public goods and 2% less on infrastructure public goods (significant at the 5% and

10% level). In relative terms this means between 10 and 15% more (less) spending on

people public goods (infrastructure public goods). The driving subcategories (not re-

ported) are recreation (1.7, significant at the 5% level) and social spending (1%-points,

significant at the 5% level) as well as spending for streets (-1.3%-points, p-value: 0.16).

Our results hence suggest that changes in council majorities (irrespective of the

direction of the partisan change) may impact on spending composition. Specifically,

both, CDU and SPD are suggested to spend more on people goods and less on infras-

tructure goods when they gain power and take over the majority of the local council

compared to communities where the dominant party in the council remains unchanged.

One potential theoretical explanation for this effect is that opposition parties, in elec-

toral campaigns, have to differentiate from incumbent policy positions to sharpen their

profile and gain medial visibility. Opposition parties might find it attractive to promise

and, if elected into power, eventually implement spending policies that put more em-

phasis on consumptive spending (like spending for the ’people-oriented’ goods and

services) than on investment spending (like infrastructure spending) as the latter goes

down better with short-sighted voters. On top of that, the observed pattern might

reflect responses to incumbents’ pre-election spending choices, which tend to be char-

acterized by increased investment spending in pre-election years (and constant overall

spending, see e.g. Kneebone and McKenzie (2001), Gonzalez (2002), Brender (2003),

Khemani (2004) and Drazen and Eslava (2010)). Our results are consistent with the

notion that parties that gain legislative power reverse these spending trends (more

strongly than incumbent ones) after the election.

14Note that Table (A7) in the Appendix, moreover, presents results from specifications, where timing

effects across the electoral cycle are modelled in a more flexible non-linear way.

18

Tab

le6:

Est

imat

ion

Res

ult

s-

Tim

ing

ofSp

endin

g

Dep

.V

ar.

(ln

)(l

n)

(ln

)L

oca

lS

har

e

Rea

lF

inan

cial

Vol

unta

ryB

usi

nes

sG

ener

al

Peo

ple

Cult

ure

Infr

astr

uct

ure

Exp

.E

xp

.E

xp

.T

axR

ate

Exp

.E

xp

.E

xp

.E

xp

.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Pan

elA

:C

DU

Coa

liti

on

-CD

UC

oal

itio

n,

CD

U-C

DU

vs

CD

U-S

PD

,N

=10

,098

SP

D0.

020

0.03

00.

022

1.53

6-0

.259

7.0

52*

-0.1

20-6

.273

***

(0.0

47)

(0.0

64)

(0.0

64)

(2.3

15)

(2.1

95)

(3.6

60)

(0.2

01)

(1.8

19)

SP

D*

#Y

ear

0.0

04-0

.001

0.01

91.

074

0.0

13

-0.8

850.0

90

1.3

00*

(0.0

13)

(0.0

20)

(0.0

15)

(1.3

40)

(0.4

51)

(0.9

88)

(0.1

23)

(0.6

96)

Pan

elB

:S

PD

Coa

liti

on

-SP

D-C

oali

tion

,S

PD

-SP

Dvs.

SP

D-C

DU

,N

=4,

144

CD

U0.

013

0.05

8-0

.037

-1.6

720.5

52

2.272

*-0

.620

-2.7

57*

(0.0

37)

(0.0

58)

(0.0

49)

(1.6

01)

(1.0

65)

(1.2

73)

(0.3

85)

(1.5

56)

CD

U*

#Y

ear

0.0

05-0

.005

0.01

0-0

.129

-0.2

39

-0.7

55**

0.2

66*

*0.8

97*

(0.0

09)

(0.0

18)

(0.0

13)

(0.6

87)

(0.2

48)

(0.3

52)

(0.1

16)

(0.5

00)

SP

Dvs

Un

ion

Majo

rity

inth

eL

oca

lC

oun

cil,

only

last

two

year

sin

anel

ecti

onp

erio

d:

N=

6,7

46

SP

D-0

.022

-0.0

36-0

.009

1.83

0-0

.442

2.082

**0.

070

-1.9

63*

(0.0

23)

(0.0

37)

(0.0

31)

(1.4

41)

(0.7

14)

(0.9

48)

(0.1

91)

(1.0

16)

Contr

ol

Var

iab

les,

Mu

nic

ipal

ity

FE

XX

XX

XX

XX

an

dS

tate

-Yea

rF

EX

XX

XX

XX

X

Notes:

Tab

lesh

ow

sth

ep

oin

tes

tim

ate

sfo

rS

PD

ma

jori

tyin

the

loca

lco

un

cil

usi

ng

diff

eren

td

epen

den

tvari

able

s.A

llre

gre

ssio

nin

clu

de

contr

ol

vari

ab

les,

mun

icip

ality

fixed

effec

tas

wel

las

state

-yea

rfi

xed

effec

ts.

Th

ed

epen

den

tvari

ab

les

are

:(l

n)

real

spen

din

g(c

ol.

(1))

,(l

n)

fin

an

cial

spen

din

g(c

ol.

(2))

,(l

n)

volu

nta

rysp

end

ing

(col.

(3))

an

dju

risd

icti

on

s’lo

cal

bu

sin

ess

tax

rate

choic

e(c

ol.

(4))

.F

urt

her

,in

col.

(5)

to(8

)it

isth

evolu

nta

rysp

end

ing

share

of

gen

eral

pu

blic

good

s,p

eop

lep

ub

lic

good

s,cu

ltu

rean

din

frast

ruct

ure

pu

blic

good

s.In

row

(1)

we

focu

son

juri

sdic

tion

sw

ith

un

chan

ged

CD

Uor

CD

U-c

oali

tion

ma

jori

ty

inth

elo

cal

cou

nci

lor

ach

an

ge

from

CD

Uto

SP

Dm

ajo

rity

.In

row

(2)

we

focu

son

juri

sdic

tion

sw

ith

eith

eru

nch

an

ged

SP

Dor

SP

D-c

oaliti

on

ma

jori

tyin

the

loca

l

cou

nci

lor

ach

an

ge

from

SP

Dto

CD

Um

ajo

rity

.In

row

(3)

we

incl

ud

eall

juri

sdic

tion

sw

ith

eith

erS

PD

or

CD

Um

ajo

rity

bu

ton

lyth

ela

sttw

oel

ecti

on

per

iod

yea

rs.

Sta

nd

ard

erro

rsin

pare

nth

esis

are

rob

ust

an

dcl

ust

ered

at

the

mu

nic

ipality

level

.*,

**,

an

d***

den

ote

sign

ifica

nce

at

the

10,

5,

an

d1%

level

.Source:

Au

thors

’ca

lcu

lati

on

sb

ase

don

Sta

tist

ikL

okal

an

dJah

resr

ech

nu

ngss

tati

stik

1994

to2006.

19

5 Conclusion

The aim of this paper was to assess the role of partisanship of West German local

council majorities on overall local public spending and the composition of local pub-

lic spending. We combine a simple fixed effect regression approach with an entropy

balanced matching strategy to empirically identify the effect of interest. Two find-

ings emerge: Firstly, our results point to sizable partisan effects on the composition of

public spending (while aggregate spending levels are suggested to remain unaffected).

Secondly, our findings suggest that the composition of public spending changes sys-

tematically when parties gain the majority of seats in legislative bodies. This, from

our perspective, is an important insight as it affects empirical identification strategies

of partisan effects based on election-induced changes in partisanship (irrespective of

the methodological identification approach - it e.g. emerges in difference-in-differences

strategies as well as in regression discontinuity designs).

20

References

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22

Appendix: Additional Descriptive Statistics and Es-

timation Results

Table A1: Descriptive Statistics for Panel A: Unweighted and Entropy-Balanced

Control Treatment

CDU-Coalition-CDU-Coalition, CDU-CDU CDU-SPD

Unweighted Entropy-Balanced

Mean Variance Mean Variance Mean Variance

(ln) Population in 1000 1.62 1.08 0.92 0.42 0.84 0.41

Share population under 20 0.23 0.00 0.23 0.00 0.23 0.00

Share population over 65 0.17 0.00 0.17 0.00 0.17 0.00

(ln) Employees 7.38 1.09 6.68 0.46 6.65 0.45

Unemployment rate (county) 8.50 3.25 8.68 2.86 9.29 1.93

Debt per capita (county) 6.75 0.11 6.85 0.07 6.86 0.03

Local business tax multiplier 339.91 1362.63 326.82 345.69 326.80 345.03

(ln) Real expenditures 15.91 1.24 15.14 0.47 15.12 0.45

(ln) Financial expenditures 15.03 1.25 14.38 0.50 14.38 0.50

Voluntary expenditure shares for

Share general public good expenditures 12.77 21.03 13.15 11.79 13.15 11.78

Share people public good expenditures 18.09 86.28 23.87 138.96 23.87 138.95

Share culture expenditures 1.30 3.78 0.71 0.42 0.70 0.41

Share firm public good expenditures 17.45 72.29 18.42 131.16 18.42 131.17

Observations 1,121 1,121 15

Notes: Table reports descriptive statistics for jurisdictions with CDU dominated councils that

changed to a SPD dominated council (treatment group) and jurisdictions with CDU or CDU-

Coalition dominated councils with no change in the majority in the local council, before entropy-

balancing (unweighted) and after. The variables refer to the second last period before the next

election. Every jurisdiction is counted only once. The matching variables are local business tax mul-

tiplier, (ln) real and financial spending as well as the voluntary expenditure shares. Source: Authors’

calculations based on Statistik Lokal and Jahresrechnungsstatistik 1994 to 2006.

23

Table A2: Descriptive Statistics for Panel B: Unweighted and Entropy-Balanced

Control Treatment

SPD-Coalition-SPD-Coalition, SPD-SPD SPD-CDU



(ln) Population in 1000 1.53 1.08 1.79 0.91 1.71 0.83



(ln) Employees 7.33 1.11 7.58 0.93 7.47 0.80



Local business tax multiplier 332.90 1063.89 342.79 1028.86 342.77 1029.48

(ln) Real expenditures 15.80 1.20 16.01 0.94 16.01 0.94

(ln) Financial expenditures 14.91 1.19 15.05 1.00 15.05 1.00


General public goods 13.35 14.78 13.40 9.46 13.40 9.46

People public goods 18.67 75.34 17.02 103.34 17.02 103.43

Culture 1.39 4.96 1.12 1.69 1.12 1.69

Infrastructure public goods 16.99 50.21 13.29 34.16 13.29 34.17

Observations 399 399 44

Notes: Table reports descriptive statistics for jurisdictions with SPD dominated councils that changed

to a CDU dominated council (treatment group) and jurisdictions with SPD or SPD-Coalition dom-

inated councils with no change in the majority in the local council, before entropy-balancing (un-

weighted) and after. The variables refer to the last year before the next election. Every jurisdiction

is counted only once. The matching variables are local business tax multiplier, (ln) real and finan-

cial spending as well as the voluntary expenditure shares. Source: Authors’ calculations based on

Statistik Lokal and Jahresrechnungsstatistik 1994 to 2006.

24

Table A3: Descriptive Statistics for Panel A: Unweighted and Entropy-Balanced:

Matching based on Changes in Matching Variables

Control Treatment

CDU-Coalition-CDU-Coalition, CDU-CDU CDU-SPD



(ln) Population in 1000 1.62 1.07 1.21 0.79 0.84 0.41



(ln) Employees 7.39 1.09 6.96 0.85 6.65 0.45



∆ Local business tax multiplier 6.10 119.64 3.00 27.93 3.00 27.86

∆ (ln) Real expenditures 0.02 0.04 0.10 0.04 0.10 0.04

∆ (ln) Financial expenditures 0.02 0.07 0.12 0.04 0.12 0.04


∆ General public goods 0.19 17.10 -2.43 25.47 -2.43 25.47

∆ People public goods 0.27 60.65 0.59 55.17 0.59 55.20

∆ Culture -0.03 3.42 0.00 0.65 0.00 0.65

∆ Infrastructure public goods 0.55 80.69 3.25 89.07 3.25 89.14

Observations 1,118 1,118 15

Notes: Table reports descriptive statistics for jurisdictions with CDU dominated councils that

changed to a SPD dominated council (treatment group) and jurisdictions with CDU or CDU-

Coalition dominated councils with no change in the majority in the local council, before entropy-

balancing (unweighted) and after. The variables refer to the last period before the next election. ∆

measure the two-year change. Every jurisdiction is counted only once. The matching variables are

the two year changes of (ln) real expenditures, (ln) financial expenditures and the local business

tax multiplier as well as the spending share for general, people, culture and infrastructure public

goods in the last year before the election. Source: Authors’ calculations based on Statistik Lokal and

Jahresrechnungsstatistik 1994 to 2006.

25

Table A4: Descriptive Statistics for Panel B: Unweighted and Entropy-Balanced Match-

ing based on Changes in Matching Variables

Control Treatment

SPD-Coalition-SPD-Coalition, SPD-SPD SPD-CDU



(ln) Population in 1000 1.54 1.08 1.71 1.45 1.71 0.83



(ln) Employees 7.33 1.11 7.50 1.48 7.47 0.80



∆ Local business tax multiplier 2.26 43.99 4.21 58.16 4.20 58.07

∆ (ln) Real expenditures 0.02 0.03 0.01 0.03 0.01 0.03

∆ (ln) Financial expenditures 0.04 0.07 0.04 0.08 0.04 0.08


∆ General public goods 0.32 12.71 0.13 8.33 0.13 8.34

∆ People public goods 0.38 36.21 1.79 58.17 1.79 58.20

∆ Culture 0.01 2.77 -0.17 1.17 -0.17 1.17

∆ Infrastructure public goods 0.27 59.66 -1.24 26.61 -1.24 26.61

Observations 399 399 44

Notes: Table reports descriptive statistics for jurisdictions with SPD dominated councils that changed

to a CDU dominated council (treatment group) and jurisdictions with SPD or SPD-Coalition dom-

inated councils with no change in the majority in the local council, before entropy-balancing (un-

weighted) and after. The matching variables are (ln) real expenditures, (ln) financial expenditures

and the local business tax multiplier as well as the spending share for general, people, culture and

infrastructure public goods in the last year before the election. The variables refer to the last year

before the next election. ∆ measure the two-year change. Every jurisdiction is counted only once.

The matching variables are the two year changes of (ln) real expenditures, (ln) financial expenditures

and the local business tax multiplier as well as the spending share for general, people, culture and

infrastructure public goods in the last year before the election. Source: Authors’ calculations based

on Statistik Lokal and Jahresrechnungsstatistik 1994 to 2006.

26

Table A5: Estimation Results - Overall Spending Shares (Mandatory and Voluntary

Spending)

Dep. Var. Share

General People Culture Infrastructure

Expenditure Expenditure Expenditure Expenditure

(1) (2) (3) (4)

SPD vs CDU Majority in the Local Council: N=15,834

SPD -1.215* 1.482* -0.142 -0.192

(0.625) (0.788) (0.174) (0.945)

CDU Coalition-CDU Coalition, CDU-CDU vs CDU-SPD, N = 10,098

Unweighted Panel A

SPD -0.350 3.795** 0.036 -3.792*

(1.467) (1.877) (0.216) (2.132)

Entropy-Balanced Panel A

SPD -0.174 4.093** 0.100 -4.359**

(0.917) (1.694) (0.156) (1.916)

SPD Coalition-SPD-Coalition, SPD-SPD vs. SPD-CDU, N = 4,144

Unweighted Panel B

CDU 1.001 -1.073 0.287 -0.248

(0.980) (1.165) (0.278) (1.352)

Entropy-Balanced Panel B

CDU 1.072 -0.540 0.004 -0.643

(1.055) (1.334) (0.175) (1.213)

Control Variables X X X X

Municipality FE X X X X

State-Year FE X X X X

Notes: Table shows the point estimates for SPD (row (1) to (3)) or CDU majorities (row (4) and (5)) in the local

council using different dependent variables. All regression include control variables, municipality fixed effect as well

as state-year fixed effects. The dependent variables are voluntary expenditures share for general public goods (col.

(1)), people public goods (col. (2)), culture (col. (3)) and infrastructure public goods (col. (4)). Row (1) shows

the effect when assuming symmetry for the change from SPD to CDU and back. In row (2) and (3) we focus on

jurisdictions with unchanged CDU or CDU-coalition majority in the local council or a change from CDU to SPD

majority. In row (4) and (5) we focus on jurisdictions with either unchanged SPD or SPD-coalition majority in the

local council or a change from SPD to CDU majority.In row (2) and (4) an unweighted sample and in row (3) and

(5) an entropy-balanced sample is used. Standard errors in parenthesis are robust and clustered at the municipality

level. *, **, and *** denote significance at the 10, 5, and 1% level. Source: Authors’ calculations based on Statistik

Lokal and Jahresrechnungsstatistik 1994 to 2006. 27

Tab

leA

6:E

stim

atio

nR

esult

s-

Mat

chin

gon

Chan

ges

ofM

atch

ing

Var

iable

s

Dep

.V

ar.

(ln

)(l

n)

(ln

)L

oca

lS

har

e

Rea

lF

inan

cial

Vol

unta

ryB

usi

nes

sG

ener

al

Peo

ple

Cu

ltu

reIn

fras

tru

ctu

re

Exp

.E

xp

.E

xp

.T

axR

ate

Exp

.E

xp

.E

xp

.E

xp

.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Entr

opy-B

ala

nce

dP

an

elA

:C

DU

Coa

liti

on

-CD

UC

oali

tion

,C

DU

-CD

Uvs

CD

U-S

PD

,N

=10,

071

SP

D0.

011

-0.0

020.

063

4.650

1.6

56

4.216

***

0.1

11

-3.7

40**

*

(0.0

31)

(0.0

58)

(0.0

49)

(3.1

71)

(1.2

14)

(1.1

97)

(0.1

65)

(1.3

75)

Entr

opy-B

ala

nce

dP

an

elB

:SP

DC

oal

itio

n-S

PD

-Coa

liti

on,

SP

D-S

PD

vs.

SP

D-C

DU

,N

=4,

128

CD

U0.

005

0.00

8-0

.011

-2.5

80*

0.8

99

-0.1

54

0.1

20

-1.2

12

(0.0

32)

(0.0

50)

(0.0

38)

(1.5

33)

(0.8

89)

(1.0

23)

(0.1

31)

(1.0

03)

Con

trol

Var

,M

un

icip

alit

yan

dS

tate

-Yea

rF

EX

XX

XX

XX

X

Notes:

Tab

lesh

ow

sth

ep

oin

tes

tim

ate

sfo

rS

PD

(row

(1))

or

CD

Um

ajo

rity

(row

(2))

inth

elo

cal

cou

nci

lu

sin

gd

iffer

ent

dep

end

ent

vari

ab

les.

All

regre

ssio

nin

clu

de

contr

ol

vari

ab

les,

mu

nic

ipality

fixed

effec

tas

wel

las

state

-yea

rfi

xed

effec

ts.

Th

ed

epen

den

tvari

ab

les

are

:(l

n)

real

spen

din

g(c

ol.

(1))

,(l

n)

fin

an

cial

spen

din

g(c

ol.

(2))

,(l

n)

volu

nta

rysp

end

ing

(col.

(3))

,

juri

sdic

tion

s’ta

xra

tech

oic

e(c

ol.

(4))

an

dth

evolu

nta

rysp

end

ing

share

sfo

rgen

eral

pu

blic

good

s(c

ol.

(5))

,p

eop

lep

ub

lic

good

s(c

ol.

(6))

,cu

ltu

re(c

ol.

(7))

an

din

frast

ruct

ure

pu

bli

c

good

s(c

ol.

(8))

.In

row

(2)

we

focu

son

juri

sdic

tion

sw

ith

un

chan

ged

CD

Uor

CD

U-c

oaliti

on

ma

jori

tyin

the

loca

lco

un

cil

or

ach

an

ge

from

CD

Uto

SP

Dm

ajo

rity

.In

row

(2)

we

focu

son

juri

sdic

tion

sw

ith

eith

eru

nch

an

ged

SP

Dor

SP

D-c

oali

tion

ma

jori

tyin

the

loca

lco

un

cil

or

ach

an

ge

from

SP

Dto

CD

Um

ajo

rity

.In

all

spec

ifica

tion

we

use

an

entr

opy-b

ala

nce

dsa

mp

le.

Th

em

ain

diff

eren

ceto

ou

rm

ain

resu

ltis

that

matc

hin

gis

don

eu

sin

gch

an

ges

inth

em

atc

hin

gvari

ab

les.

Sta

nd

ard

erro

rsin

pare

nth

esis

are

rob

ust

an

dcl

ust

ered

at

the

mu

nic

ipali

ty

level

.*,

**,

an

d***

den

ote

sign

ifica

nce

at

the

10,

5,

an

d1%

level

.Source:

Au

thors

’ca

lcu

lati

on

sb

ase

don

Sta

tist

ikL

okal

an

dJah

resr

ech

nu

ngss

tati

stik

1994

to2006.

28

Tab

leA

7:E

stim

atio

nR

esult

s-

Tim

ing

ofSp

endin

g(F

lexib

leF

unct

ional

For

ms)

Dep

.V

ar.

(ln

)(l

n)

(ln

)L

oca

lS

har

e

Rea

lF

inan

cial

Vol

unta

ryB

usi

nes

sG

ener

al

Peo

ple

Cu

ltu

reIn

frast

ruct

ure

Exp

.E

xp

.E

xp

.T

axR

ate

Exp

.E

xp

.E

xp

.E

xp

.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Pan

elA

:C

DU

Coa

liti

on

-CD

UC

oal

itio

n,

CD

U-C

DU

vs

CD

U-S

PD

,N

=10

,098

SP

D*

Ele

ctio

nan

d1s

tyea

r0.

032

0.02

50.

035

2.37

4*-0

.606

6.3

03*

*-0

.140

-5.3

92*

**

(0.0

35)

(0.0

52)

(0.0

59)

(1.4

38)

(1.4

65)

(2.8

22)

(0.1

43)

(1.0

98)

SP

D*

2n

dan

d3rd

yea

r0.0

150.

028

0.03

42.

056

0.4

02

2.967

0.1

93

-2.9

34*

(0.0

33)

(0.0

48)

(0.0

44)

(2.4

38)

(2.0

18)

(1.8

74)

(0.1

66)

(1.6

58)

SP

D*>

3rd

year

0.03

40.

014

0.10

1**

4.40

4-0

.177

1.474

0.3

55

0.126

(0.0

33)

(0.0

62)

(0.0

43)

(4.0

18)

(1.1

51)

(1.6

99)

(0.4

57)

(2.0

20)

Pan

elB

:S

PD

Coa

liti

on

-SP

D-C

oali

tion

,S

PD

-SP

Dvs.

SP

D-C

DU

,N

=4,

144

CD

U*

Ele

ctio

nan

d1st

year

-0.0

090.

031

-0.0

57-1

.018

0.1

02

1.3

62

-0.4

90*

-2.1

44

(0.0

32)

(0.0

53)

(0.0

43)

(1.1

21)

(0.8

83)

(0.9

72)

(0.2

54)

(1.3

22)

CD

U*

2nd

and

3rd

yea

r0.0

260.

057

-0.0

07-1

.676

0.6

50

0.9

51

0.004

-1.0

53

(0.0

26)

(0.0

40)

(0.0

35)

(1.1

03)

(0.6

67)

(0.9

43)

(0.3

26)

(1.0

79)

CD

U*>

3rd

year

0.0

130.

012

0.00

6-1

.122

-0.4

73-0

.892

0.379

*0.

933

(0.0

29)

(0.0

50)

(0.0

37)

(2.0

25)

(0.6

48)

(1.0

04)

(0.2

04)

(1.3

95)

Contr

ol

Var

iab

les,

Mu

nic

ipali

tyF

EX

XX

XX

XX

X

an

dS

tate

-Yea

rF

EX

XX

XX

XX

X

Notes:

Tab

lesh

ow

sth

ep

oin

tes

tim

ate

sfo

rS

PD

(row

(1)

to(3

))or

CD

Um

ajo

rity

(row

(4)

an

d(5

))in

the

loca

lco

un

cil

usi

ng

diff

eren

td

epen

den

tvari

ab

les.

All

regre

ssio

n

incl

ud

eco

ntr

ol

vari

ab

les,

mu

nic

ipality

fixed

effec

tas

wel

las

state

-yea

rfi

xed

effec

ts.

Th

ed

epen

den

tvari

ab

les

are

:(l

n)

real

spen

din

g(c

ol.

(1))

,(l

n)

fin

an

cial

spen

din

g

(col.

(2))

,(l

n)

volu

nta

rysp

end

ing

(col.

(3))

,ju

risd

icti

on

s’ta

xra

tech

oic

e(c

ol.

(4))

an

dth

evolu

nta

rysp

end

ing

share

sfo

rgen

eral

pu

blic

good

s(c

ol.

(5))

,p

eop

lep

ub

lic

good

s(c

ol.

(6))

,cu

ltu

re(c

ol.

(7))

an

din

frast

ruct

ure

pu

blic

good

s(c

ol.

(8))

.In

row

(1)

we

focu

son

juri

sdic

tion

sw

ith

un

chan

ged

CD

Uor

CD

U-c

oaliti

on

ma

jori

tyin

the

loca

lco

un

cil

or

ach

an

ge

from

CD

Uto

SP

Dm

ajo

rity

.In

row

(2)

we

focu

son

juri

sdic

tion

sw

ith

eith

eru

nch

an

ged

SP

Dor

SP

D-c

oaliti

on

ma

jori

tyin

the

loca

lco

un

cil

or

ach

an

ge

from

SP

Dto

CD

Um

ajo

rity

.S

tan

dard

erro

rsin

pare

nth

esis

are

rob

ust

an

dcl

ust

ered

at

the

mu

nic

ipality

level

.*,

**,

an

d***

den

ote

sign

ifica

nce

at

the

10,

5,

an

d1%

level

.Source:

Au

thors

’ca

lcu

lati

on

sb

ase

don

Sta

tist

ikL

okal

an

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1994

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29

do political parties matter? - evidence from german municipalities · 2019-01-10 · do political...

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