Government spending and legislative organization:
Quasi-experimental evidence from Germany
Peter Egger
University of Munich and Ifo
Marko Koethenbuerger
University of Vienna and CESifo∗
First version: February 2008
This version: December 2008
Abstract
In this paper we present empirical evidence that council size has a positive effect on
government spending. We use data of 2056 municipalities in the German state of Bavaria
over a time period of 22 years. In particular, we make use of law-induced changes in
the council size, triggered by slight changes in population size (“one more inhabitant”),
to identify a causal relationship between council size and spending. The regressiondiscontinuity design, thereby, circumvents problems of endogeneity of previous studies.
The paper also shows that (i) politically strong mayors do not break the relationship
between the size of government and council size, (ii) municipalities rely on property taxes
(rather than public debt) to finance pork-barrel spending, and (iii) political fragmentation
does not magnify the pro-spending bias inherent to legislature size.
JEL Classification: D7, H7, C2
Keywords: Legislative Organization, Mayor-Council System, Regression-Discontinuity, Fragmentation, Government Spending.
∗
Address: Hohenstaufengasse 9, 1010 Wien, Austria, Phone: [+43] 1 4277 37423, Fax: [+43] 1 4277 9374,
Email: [email protected].
1
1
Introduction
The notion that legislative organization affects government spending is a central feature of the
recent literature on the political economy of fiscal policy.1 Districting of political jurisdictions
is a peculiar force identified in the literature which generates an overspending bias in the
public sector. Legislators internalize the benefit of public projects targeted at their district,
but due to cost sharing underestimate the cost of project provision. The size of government is
hence positively related to the number of legislators; a phenomenon frequently referred to as
pork-barrel spending, the fiscal commons problem, or the “law of 1/n” - see, e.g., Weingast
et al. (1981). In this paper we empirically test the relationship between legislature size and
government spending. Using data from 2056 municipalities in the German state of Bavaria
over the time period 1983-2004 we find that council size has a positive impact on government
spending. Our paper deviates from the political economy literature most importantly in the
empirical strategy used to identify a relationship between council size and spending. Existing
empirical analyses primarily resort to cross-section variation of council size.2 The drawback
of this approach is that it is generically plagued by problems of endogeneity. For instance,
the size of the council may reflect preferences of voters for a fine-grid representation of voters’
preferences in legislature. At the same time these voters may want to see high levels of public
spending. Hence, council size and spending might be positively associated, with no causal
relationship.3 We circumvent the endogeneity problem by applying a regression-discontinuity
design.4 That is, we make use of the fact that municipal council size is formulaically related to
the population size of the municipality in Bavaria. For municipalities whose population size
is slightly below and just above a threshold, the number of legislators differs up to 50%. Since
one more inhabitant will generate the discontinuous change in council size, the assignment
to different council classes is as good as random. The law-induced changes in council size
thus provide a quasi-natural experiment, which enables us to draw causal inference, i.e. to
determine whether council size and government spending are causally linked, with causality
1
See, e.g., Besley and Case (2003), Persson and Tabellini (2003), and Acemoglu (2005) for a review of the
literature.
2
Empirical analyses of the relationship between legislature size and public spending include DelRossi and
Inman (1999), Bradbury and Crain (2001), Baqir (2002), and Schaltegger and Feld (2008).
3
See Acemoglu (2005) for a general discussion of problems of endogeneity in empirical analysis of political
economy.
4
A regression-discontinuity design has only recently been applied in economics and, in particular, in political
economy. See, e.g., Dahlberg et al. (2008), Lee et al. (2004), Lee (2008), and Pettersson-Lidbom (2007, 2008)
for an application of the regression-discontinuity design in political economy analysis.
2
running from council size to spending.
The paper sheds light onto the effectiveness of political institutions to break the relation between council size and fiscal policy. Two political institutions are argued to remedy
the common-pool problem: at-large systems and mayor-council systems. Under the former
institution only a single political district exists and political candidates compete for votes
from the whole population. The at-large system hence removes the overspending bias due to
geographical cost-sharing. Under the latter system a mayor is directly elected. The mayor
will more likely internalize the overall costs of projects and, provided the mayor has a strong
position via-a-vis the council, the mayor can counteract the overspending bias of council
members.5 In fact, Baqir (2002) finds evidence for mayor-council systems to break the relationship between council size and spending in US states; thereby enforcing fiscal discipline.
Municipalities in Bavaria operate under both an at-large system and a mayor-council system.
Our finding shows that the political institutions do not offset the impact of council size on
public spending. Suggestively, although not catering to members of their political district,
council members still cater to their political clientele in the electorate, causing a spending
rise which more than offsets the hypothesized disciplining effect of the mayor-council system.
We further look into the financing implications of politically-motivated spending hikes.
Besides issuing public debt, municipalities have some taxing authority. Tax instruments
available to Bavarian municipalities are property taxes and a tax on business profits. We find
that only property taxes react significantly to council size changes. Intuitively, municipalities
compete for mobile firms with the profit tax and, thus, will generically refrain from increasing
the profit tax burden on mobile firms to finance additional spending.6 As to public debt, it
might be surprising that municipalities do not resort to public debt to finance pork-barrel
spending, given the hypothesized bias toward debt financing in political economy. Munici5
A mayor-council system is implemented, e.g., at the municipal level in some German states and in a
number of US cities (most notably in small and large cities) - see, e.g., Svara (1990) for a review of the
US experience. The idea that a “strong” legislator imposes fiscal discipline is conceptually related to the
discussion of a “strong” finance minister in government and its effect on public debt policy (e.g. von Hagen,
2005, 2006), and to the economic comparison of presidential and parliamentary systems (e.g. Persson and
Tabellini, 2003). A strong finance ministers most likely internalizes the overall costs of pork-barrel spending,
with the consequence of vetoing some of the expenditure proposals of cabinet ministers. In a presidential
system, the president is elected directly into office and has independent authority (as is a mayor in Bavaria).
Differently, in a parliamentary system the prime minister is elected by the parliament and is accountable to
it.
6
The finding is consistent with the view that, by assigning taxes levied on mobile resources to local governments, local politicians will find it more costly to finance additional spending and prefer to shift the tax
burden onto more immobile tax payers - see, e.g., Brennan and Buchanan (1980) and Sinn (2003).
3
palities operate under the Golden Rule of Public Finance which stipulates that public debt
financing is restricted to public investment outlays. We find that consumptive expenditures
primarily react to council size adjustments. For this type of public expenditure public debt
financing is not available. The finding is indicative for the effectiveness of the Golden Rule
regulation in municipal finance. A straightforward question is why municipal governments
resort to consumptive expenditures rather than investment expenditures (or a mix of both).
Presumably, investment expenditures can only be adjusted with a longer time lag after the
adjustment in council size due to, e.g., legal planning requirements and co-financing modalities (and, thus, coordination need) with higher-level governments. Legislators, however, may
prefer a more timely adjustment in expenditures. Consistent with this interpretation, we find
that expenditures react immediately after council size changes.
Finally, we speak to the literature on political fragmentation and fiscal outcomes; see,
e.g., Roubini and Sachs (1989), Alesina and Drazen (1991), and Perotti and Kontopoulos
(2002). This body of literature primarily looks at the political composition of the legislature
(or the executive branch of government) rather than at legislature size per-se as a determinant
of fiscal outcomes. One may conjecture that in our setting the political composition of the
municipal council interacts with the size effect; i.e. that spending rise in municipalities which
are legislated to adjust the council size might be higher the more politically fragmented the
council is. Our findings show that political fragmentation has no bearing on the link between
council size and public expenditures. We can further shed light on the related discussion of
whether party affiliation impacts on the fiscal commons problem. A hypothesis in this context
is that parties may be more effective in limiting the fiscal commons problem than independent
candidates (Grossman and Helpman, 2006). The basic idea is that polities differ in the extent
to which political parties can pre-commit before elections to carry out certain policy actions
if they take power. Commitment problems arise due to a divergence between ex ante and
ex post incentives, which may reflect (among other things) a difference in the objectives
of national parties that seek to capture control of the legislature (and thereby implement
their nation-wide and/or ideological agendas) and the objectives of individual legislators,
whose interests may be more parochial. Parties may thus induce party candidates to stick
to the partly line instead of engaging in pork-barrel spending. Independent candidates do
not face party discipline. They act more like citizen candidates in the spirit of Osborne and
Slivinski (1996) and Besley and Coate (1997), where policies are ex-post chosen in legislative
4
decision-making (featuring pork-barrel spending). To test for it, we make use of the fact
that in Bavarian municipal politics both candidates affiliated with parties and independent
candidates are part of the legislature. In our regression we find that the extent to which
the municipal legislature comprises independent candidates has no influence on the fiscal
commons problem.
Like us, Pettersson-Lidbom (2007) uses a regression-discontinuity approach in testing the
hypothesis of pork-barrel spending. Using data of Swedish and Finish municipal finance,
he finds a negative relationship between council size and government spending. Besides
reporting a qualitatively different results, our data set allows us to speak to a richter set
of questions; most notably, which fiscal instruments municipalities prefer to finance porkbarrel spending, which type of expenditure (current vs. capital expenditure) are primarily
responsive to council size, and whether political institutions as well as fragmentation influence
the relationship between public expenditures and council size.
The paper proceeds by providing a description of municipal finance and politics in Bavaria
in Section 2, followed by the empirical strategy in Section 3, and the empirical results in
Section 4. A summary of the main results and some conclusions are finally presented in
Section 5.
2
Municipal Finance and Politics in Bavaria
Bavaria comprises 2056 municipalities which have considerable degree of fiscal autonomy. On
the revenue side, they can set property taxes and a business tax. Own-source tax revenues
are approximately 50% of total (own-source plus shared, but federally determined) tax revenues. Municipalities can borrow to the extent that the amount of borrowing does not exceed
infrastructure outlays (Golden Rule of Public Finance). Current spending, in contrast, has
to be financed by current receipts. On the expenditure side, municipalities provide important
public services such as sport facilities, kindergarten, old people’s homes, elementary schools
as well as utility and infrastructure services.
Municipalities have the right of self-management. The municipal political system in
Bavaria is a mayor-council system (so called Süddeutsche Ratsverfassung) which in the current form was implemented after World War II by the US military government.7 The system
7
Interestingly, the military government in the British occupation zone in the northern states of former
West-Germany implemented a council-manager system, in which the mayor is elected by the council and
5
features direct elections of the the mayor and council members (mayor-council system) which
take place every 6 years. The mayor has a strong position in municipal politics. The mayor
is the chief executive of the municipality solely responsible for the operation. The mayor
is also a chairman of the council, endowed with voting rights and the prerogative to veto
actions of the council (in particular of subcommittees implemented by the council).8 The
municipal legislature comprises candidates of national parties and candidates which have no
affiliation with national parties. Independent candidates may be politically organized either
on a stand-alone basis or may have joined a voter association. Independent candidates have
a non-negligible role in policy formulation. For instance, in the 2002 election 54% of council
seats in Bavaria went to candidates with no party affiliation, with similar representation in
previous elections.9
An important feature of the political system is that the council size is related to the
population size of the municipalities. Table 1 depicts the mapping between population size
and council size as prescribed by law. There are 13 council sizes where the lower 11 brackets
are formulaically related to the population size of the municipality. Hence, the size of 2063
out of 2065 councils is formulaically determined by the population size. Taken together with
the fine partitioning of population size, the number of law-induced changes in council size
turns out to be relatively high.
insert Table 1 here
Table 2 shows the change in council size between two successive years over the time period
1983-2004. Entries in the main diagonal represent municipalities whose council size stayed
constant between any two years. Off-diagonal entries represent municipalities whose council
size changed, either due to a drop in population size (entries above the main diagonal) or
population growth (entries below the main diagonal). In total, 650 changes were legislated
by law over the sample period.
insert Table 2 here
accountable to it (so called Norddeutsche Ratsverfassung). Recently, these states have gradually transitioned
to a mayor-council system. The expenditure effects of the political reform are analyzed in Egger et al. (2007).
8
See http://www.stmi.bayern.de/service/gesetze/ for more information (in German).
9
The respective figures are 56% in the 1996 election, 56% in the 1990 election, 55% in the 1984 election,
and 56% in the 1978 election.
6
The municipal data we use comes from the Bavarian statistical office and is publicly available.10 It comprises fiscal data on spending and revenues, socio-economic data on population
size, population age structure, and income as well as data on the size and political composition of municipal councils. Data on the number of unemployed at the municipal level is taken
from the Federal Labor Office (Bundesagentur für Arbeit) - also publicly available on-line.11
insert Table 3 here
Table 3 shows total public expenditure and per-capita public expenditure over the sample
period. Expenditures are increasing in council size which per se does not allow to infer
any causal relationship between council size and government spending. Since council size is
formulaically related to population size, Table 3 may display a spurious correlation. The rise
may reflect a higher demand for public spending following a rise in population size, yielding
a higher total amount and per-capita values of public spending. The former response is
straight forward. The latter is consistent with, e.g., “Brecht Law” which stipulates that a
higher concentration of population raises per-capita spending due to, e.g., increased crowding
in the consumption of public services. Disentangling the effect of population size from other
causes of spending growth such as legislative organization is a non-trivial task in empirical
analysis of political economy (see Acemoglu, 2005). In our empirical analysis we address the
concern by employing a regression-discontinuity design as explained in the next section.
3
Empirical Strategy
As mentioned above, the focus in this paper is on the causal impact of council size at on the
extent of expenditures at the municipality level. Two econometric issues are relevant here.
First, expenditure and government size could be co-determined by or correlated with some
excluded variable. This would render the parameter of interest under ordinary least-squares
estimation biased. Second, council size is not continuous. But rather, in Bavaria as in other
German Länder or other foreign countries it is generated by a step-function of population size
at the municipality level as shown in Table 1. Proper inference then should obey endogeneity
of council size along with its discontinuity about population size.
10
11
See http://www.statistik.bayern.de/.
See http://www.pub.arbeitsamt.de.
7
A first step in that direction is the use of a difference-in-difference (DID) estimation
approach. One way of implementing DID estimation is using the available panel data in
levels and include fixed municipality effects along with fixed time effects (see Cameron and
Trivedi, 2005 ).12 An advantage of DID estimation is that it avoids any potential bias from
the omission of relevant time-invariant variables.
Ideally, causal inference relies on a randomized design or experiment, where the number
of legislators is changed randomly across municipalities. Such an experiment is not available
for municipality council size and its impact on municipality expenditures. However, one may
adopt a quasi-experimental design to approximate the actual randomization. For instance,
this can be done by means of regression-discontinuity analysis (RDA). RDA is suitable, if
the probability of receiving a treatment (such as changing council size) is a discontinuous
function of some outcome variable (such as population size), see Angrist and Lavy (1999),
Van der Klaauw (2002), or Cameron and Trivedi (2005). We may think of the nexus between
population size and council size as a sharp design. The latter means that assignment of
municipalities to different council sizes is solely based on continuous population size.13
Let us describe the model in formal accounts for a cross-section of data around discontinuity d as follows:14
ln gov. sizeidt = αt + β ln counc. sizeit + k(ln pop. sizeit ) + ... + µi + εit ,
(1)
where ln gov. sizeit is the logarithm of expenditures of municipality i in year t, ln counc. sizeit
is a step function with steps at d which discontinuously maps the logarithm of population,
P
(ln pop. sizeit ) onto council size. k(·) = Jj = 1[ηj ln pop. sizejit is a semiparametric control
function involving powers of log population size. In our case, we apply J = 3 and use powers
up to an order of three.15
12
The approach is called DID, because an alternative way of implementing it is to use differences rather
than levels of the data (then, the fixed municipality effects cancel out and, with just two periods, the time
effects collapse to the constant in the differenced model). In our case, we would regress changes of expenditures between municipalities whose council size changed from one level to another and compare them to the
expenditures of other municipalities whose council size did not change.
13
There are just a few special treatments of larger cities, namely of Nuremberg and Munich, where council
size is fixed specifically - see Table 1.
14
In our case, we have to distinguish between discontinuities d = 1, ..., 12, where d = 1 is associated with a
council size of 12, d = 2 corresponds to a council size of 14, an so on, and d = 12 corresponds to a council size
of 80 (see Table 1 for the different size classes).
15
One can quite simply test for the appropriate order of the power function. In our case, using higher
powers of log population size does not contribute significantly to the model and it is efficient to use only log
population size up to a power of three.
8
αt , β, ηj , and εit are unknown parameters which have to be estimated similar to the
model parameters of other control variables not mentioned in (1). More specifically, αt is a
time-specific constant, β and ηj are a slope parameters, µi is a municipality fixed effect, and
εit is a remainder error term.
One may then estimate the DID model in (1) for alternative discontinuities d separately
or pool the data across d. The key assumptions for identification and consistent estimation
of β in the pooled model are the following: (i) in the absence of council size differences, municipalities in a small interval around any of the discontinuities generating the step function
about log population size have similar levels of log government expenditure; (ii) after conditioning on population size (and powers thereof) are the levels of government expenditure
similar across the considered discontinuities (i.e., the response is independent of the level of
population size). If (ii) is violated, one should not pool β or the other model parameters
across discontinuities. The latter is easily testable by means of an F-test.
4
Results
Our panel data-set of 2065 municipalities in Bavaria over the period 1983-2004 allows us
to identify the aforementioned causal impact from the 650 discrete (endogenous) changes in
council size on expenditures.
insert Table 4 here
Results for DID models which pool the parameters across size classes are summarized in
the first two columns of Table 4. Reported standard errors are based on Arellano’s (1987)
heteroskedasticity and autocorrelation robust estimator. While Model 1 only includes the
discontinuous variable council size along with the time- and municipality-specific effects,
Model 2 also controls for log population and log income. As can be seen from the council size
parameter of interest, controlling for log population in particular matters for the magnitude
of the estimate β̂. The inclusion of log population alone reduces the positive elasticity of log
government expenditures with respect to log council size by about three quarters. However,
the elasticity β̂ is significant at 5 percent even in Model 2. The between models (using
averaged data for the municipalities across the years) illustrate that including time-invariant
variables is particularly important if log population is not controlled for. Yet, even after
9
including log population in the empirical model, the between estimate of β is about three
times as large in Model 4 as the one in Model 2.
However, it may be insufficient to model k(·) = ln pop. sizeit and the remaining bias in
β̂ in Model 2 could be substantial. Then, one should include higher powers of ln pop. sizeit
in k(·) to obtain an unbiased estimate by means of a difference-in-difference cum regressiondicontinuity design (DID-RDD). Variants of a DID-RDD version of Model 2 are provided in
Table 5.
insert Table 5 here
We estimate three variants of Model 2 which we label Models 2a-2c. Of those, Model
2a includes (ln pop. sizeit )2 and (ln pop. sizeit )3 ) along with ln pop. sizeit ) in the a control
function k(·). Instead, Model 2b relies on a third-order polynomial function of the log number
of eligible voters instead of log population. Model 2c combines the elements of the control
function in Models 2a and 2b.
The results in Table 5 suggest that the remaining bias after including log population
alone is small, because the higher order terms in the control function do not have a large
impact on the estimate of interest, β̂.16 Moreover, whether one uses a population-based or a
number-of-voters-based control function is of minor importance. The point estimates β̂ are
very similar to each other in Table 5, and they are very close to the one of Model 2 in Table
4.
We continue the empirical analysis by shedding light on the sensitivity of the results with
regard to changes in the specification and the econometric model. The findings from this
analysis are summarized in Table 6.
insert Table 6 here
In the first column of the table, we report estimates of a variant of Model 2c as in
Table 5 which additionally includes the municipality-specific unemployment rate. A high
unemployment rate indicates that a municipality faces problems in the process of industry
restructuring. Such a municipality should be expected to have less tax income and, hence, a
lower level of expenditures than other municipalities. Indeed, this is what we find. Notice that
16
Also, the explanatory power changes only to a minor extent as compared to Model 2 when including
higher-order polynomials.
10
the point estimate of interest amounts to β̂ = 0.136 and, hence, is more than twice as high
as in Model 2c. However, this is not brought about by the inclusion of the unemployment
rate as such but by the change in time coverage due to the availability of unemployment
rates (1995-2004 instead of 1983-2004). β̂ = 0.136 also if we exclude the unemployment rate
but focus on the period 1995-2004 with Model 2c. However, notice that the 95% confidence
intervals (i.e., ±1.96σ̂ where σ̂ is the estimated standard error) around β̂ in Model 2 in Table
4, Model 2c in Table 5, and the Augmented Model in Table 6 are overlapping. Hence, the
parameter estimates are not statistically different at a reasonable level.
The remaining models in Table 6 shed light on the parameter stability of β̂ across different
moments of the distribution of log council size. For instance, we find that the point estimate
β̂ is larger in a median regression framework than in a least-squares model (see the second
column in Table 6). When dissecting the sample into municipalities with councils with at
most 14 members, ones with more than 14 but at most 30 members, and ones with more than
30 representatives, we find that the estimated elasticity increases with sample size. While the
estimates β̂ are not statistically different at reasonable significance levels between the two
groups with smaller municipalities, β̂ is significantly larger for changes in council size of large
municipalities with more than 30 council members. However, we should take the latter result
with a grain of salt, since the number of changes we learn from is rather small according to
Table 2.
We next analyze the effect of political fragmentation and party affiliation on the fiscal
commons problem. As to the former, a conjecture might be that municipalities with a more
politically fragmented council experience a more pronounced adjustment in expenditure in
response to a law-induced change in council size. To test for it, we interact the share of
the main parties and voter associations (including independent candidates with no party
affiliation) in the council with council size. The overall finding in Table 7 shows that party
shares do not significantly interact with council size with the exception being the Green Party.
From this we conclude that political fragmentation has no statistically important influence
on the fiscal commons problem.17 The fact that at the municipal level council members are
not always affiliated with a party (either being a member of a voter association or being
an independent candidate) allows us to test for the impact of party affiliation on the fiscal
17
The result is in line with findings in, e.g., Schaltegger and Feld (2008) (for Switzerland) and Perotti and
Kontopoulos (2002) (for OECD countries).
11
commons problem.18 Party affiliation is argued to have an attenuating effect on the legislative
behavior of politicians with the consequence of less pork-barrel spending (e.g., Grossman and
Helpman, 2006). The idea is that parties tend to have a more non-parochial perspective
when devising policy programs. Their local party candidates will adopt the overall policy
stance to the extent that parties can discipline its candidates when deviating from it expost. Independent candidates, in contrast, will act more like citizen candidates which choose
policies in legislative bargaining featuring pork-barrel spending; see Osborne and Slivinski
(1996) and Besley and Coate (1997). As the results in Table 7 show the extent of party
affiliation (for each of the 4 major parties separately - first column - and in aggregate - second
column) and of party independence has no statistically significant influence on fiscal commons
spending. Apparently, in municipal politics the party affiliation seems to be less of a concern
in fiscal decisions. Rather, it appears to be the identity of the municipal candidates which
is of relevance; lending support to the validity of the citizen candidate model of legislative
behavior.
insert Table 7 here
As a final exercise we infer into the financing implications of the spending hikes following
changes in council size. Tax instruments available to Bavarian municipalities are property
taxes and a tax on business profits where the latter is suggestively the focal fiscal instrument
used to compete for firms. Given the set of taxes a presumption might be that municipalities
will refrain from increasing the profit tax burden on mobile firms and, thus, will primarily
resort to property taxes as a means of financing additional spending; e.g., Brennan and
Buchanan (1980) and Sinn (2003).19 Consistent with the view, we find that its is only
property taxes which significantly react to spending hikes following council size adjustments.
Public debt financing appears not to be affected by pork-barrel spending. The result is
possibly unexpected given the tendency in political economy to excessively use public debt
financing; see, e.g., von Hagen (2006). One fiscal institution which may account for the
empirical finding is the Golden Rule of Public Finance under which Bavarian municipalities
operate. It stipulates that public debt can only be incurred for the financing of investment
18
Recall, more than 50% of council seats are won by candidates which are not affiliated with parties over
the sample period.
19
The prediction is of particular relevance at the municipal level where taxes can be avoided at low cost
(relative to cross-national tax avoidance) by relocating activities to neighboring municipalities.
12
expenditures. This type of public outlays, however, does not react significantly to adjustment
in council size - see last column in Table 8. The question arises why current expenditures
are primarily used to satisfy politically-motivated expenditure demand. Presumably, capital expenditures can only be adjusted with some time lag after the adjustment in council
size due to, e.g., legal planning requirements and co-financing modalities (and, thus, coordination need) with higher-level governments. Legislators may however demand more timely
adjustments in expenditures after elections. Consistent with this interpretation, we find that
expenditures react immediately after council size changes.
insert Table 8 here
5
Conclusion
The paper provides evidence for a positive effect of council size on government spending. We
make use of discontinuities in the legal rule which relates population size to the number of
council members, hence generating a quasi-natural experiment which allows to draw causal
inference. Interestingly, we find the positive effect of council size on fiscal spending in a
political environment of single-district jurisdictions (at-large systems) and of a mayor-council
legislature. Both political institutions are inherently exclusive towards the spending effect of
council size. We also find that the degree of political fragmentation of the council and the
party-affiliation of politicians have no bearing on the council size effect. Furthermore, among
the set of available financing options municipalities primarily rely on property taxes (rather
than profits taxes and public debt) to finance council-size related spending hikes.
References
[1] Acemoglu, D. (2005), Constitutions, politics, and economics, Journal of Economic Literature, 43, 1025-1048.
[2] Alesina, A. and A. Drazen (1991), Why are stabalizations delayed, American Economic
Review, 81, 1170-1188.
[3] Angrist, J.D. and V. Lavy (1999), Using Maimonides’ rule to estimate the effect of class
size on scholastic achievement, Quarterly Journal of Economics, 144, 533-576.
[4] Arellano, M. (1987), Computing robust standard errors for within-groups estimators,
Oxford Bulletin of Economics and Statistics, 49, 431-434.
13
[5] Baqir, R. (2002), Districting and government spending, Journal of Political Economy,
110, 1318-1354.
[6] Besley, T. and A. Case (2003), Political institutions and policy choices: Evidence from
the United States, Journal of Economic Literature, 41, 7-73.
[7] Besley, T. and St. Coate (1997), An economic model of representative democracy, Quarterly Journal of Economics, 112, 85-114.
[8] Bradbury, J.C. and W.M. Crain (2001), Legislative organization and government spending: Cross-country evidence, Journal of Public Economics, 82, 309-325.
[9] Brennan, G. and J. Buchanan (1980), The Power to Tax: Analytical Foundations of a
Fiscal Constitution, Cambridge University Press.
[10] Cameron, A.C. and K.R. Trivedi (2005), Microeconometrics: Methods and Applications,
Cambridge University Press, New York.
[11] Dahlberg, M., H. Lundqvist, and E. Mörk (2008), Intergovernmental grants and bureaucratic power, Mimeo, University of Uppsala.
[12] DelRossi, A. and R. Inman (1999), Changing the price of pork: The impact of local
cost sharing on legislators’ demands for distributive public goods, Journal of Public
Economics, 71, 247-273.
[13] Egger, P., M. Koethenbuerger, and M. Smart (2007), Disproportionate influence?
Special-interest politics under proportional and majoritarian electoral systems, Working Paper, University of Munich.
[14] Grossman, G. and E. Helpman (2006), Party discipline and pork-barrel politics, mimeo,
Harvard University.
[15] Lee, D., E. Moretti, and M. Butler (2004), Do voters affect or elect policies? Evidence
from the U.S. House, Quarterly Journal of Economics, 119, 807-860.
[16] Lee, D. (2008), Randomized experiments from non-random selection in U.S. House elections, Journal of Econometrics, 142, 675-697.
[17] Osborne, M. and Al Slivinksi (1996), A model of political competition with citizencandidates, Quartely Journal of Economics, 111, 65-96.
[18] Persson, M. and G. Tabellini (2003), The Economic Effects of Constitutions, MIT Press,
Boston, Massachusetts.
14
[19] Pettersson-Lidbom, P. (2007), Does the size of the legislature affect the size of government? Evidence from two natural experiments, mimeo, University of Stockholm.
[20] Pettersson-Lidbom, P. (2008), Do parties matter for economic outcomes? A regressiondiscontinuity approach, mimeo, University of Stockholm, forthcoming: Journal of the
European Economic Association.
[21] Roubini, N. and J. Sachs (1989), Political and economic determinants of budget deficits
in the industrial economies, European Economic Review, 33, 903-938.
[22] Schaltegger, A. and L. Feld (2008), Do large cabinets favor large government? Evidence
on the fiscal commons problem for Swiss cantons, CREMA Working Paper No. 2008-10,
forthcoming: Journal of Public Economics.
[23] Sinn, H.W. (2003), The New Systems Competition, Basil Blackwell, Oxford.
[24] Svara, J.H. (1990), Official Leadership in the City, Oxford University Press, Oxford.
[25] Van Der Klaauw, W. (2002), Estimating the effect of financial aid offers on college
enrollment: a regression-discontinuity approach, International Economic Review, 43,
1249-1287.
[26] von Hagen, J. (2005), Fiscal rules and fiscal performance in the EU and Japan, CEPR
Discussion Paper No. 5330, London.
[27] von Hagen, J. (2006), Political economy of fiscal instutions, in: B. Weingast and D.
Wittman (eds.), Oxford Handbook of Political Economy, Oxford University Press, Oxford, 464-478.
[28] Weingast, B., K. Shepsle and C. Johnson (1981), The political economy of benefits and
costs: A neoclasical approach to distributive politics, Journal of Political Economy, 96,
132-163.
15
Table 1: Council Size as a discontinuous function
of population size
Population Size (pop)
Council Members
0 < pop <= 1000
8
1000 < pop <= 2000
12
2000 < pop <= 3000
14
3000 < pop <= 5000
16
5000 < pop <= 10000
20
10000 < pop <= 20000
24
20000 < pop <= 30000
30
30000 < pop <= 50000
40
50000 < pop <= 100000
44
100000 < pop <= 200000
50
200000 < pop <= 500000
60
Nueremberg
70
Munich
80
Table 2 - Municipality size class in periods t and t-1 among Bavarian municipalities (1983-2004)
Council size
in period t
8
12
14
16
20
24
30
40
44
50
60
70
80
8
3.634
118
0
0
0
0
0
0
0
0
0
0
0
12
11
12.660
193
0
0
0
0
0
0
0
0
0
0
14
0
11
6.857
153
0
0
0
0
0
0
0
0
0
16
0
0
6
7.688
114
0
0
0
0
0
0
0
0
20
0
0
0
11
5.713
50
0
0
0
0
0
0
0
Council size in period t-1
24
30
40
0
0
0
0
0
0
0
0
0
0
0
0
4
0
0
2.735
3
0
17
489
0
0
2
301
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
44
0
0
0
0
0
0
0
0
198
2
0
0
0
50
0
0
0
0
0
0
0
0
0
88
0
0
0
60
0
0
0
0
0
0
0
0
0
0
20
0
0
70
0
0
0
0
0
0
0
0
0
0
0
20
0
80
0
0
0
0
0
0
0
0
0
0
0
0
20
Total
3.645
12.789
7.056
7.852
5.831
2.788
506
303
199
90
20
20
20
Total
3.752 12.864
7.022
7.808
5.774
2.756
494
302
200
88
20
20
20
41.120
Notes: The figures in the table are observations. Notice that each municipality of the 2056 municipalities is observed repeatedly over time.
Observations in the main diagonal represent municipalities that stay at a given council size between two periods t-1 and t.
Table 3 - Council size and expenditures in 2056
Bavarian municipalities (1983-2004)
Council size
(seats)
8
12
14
16
20
24
30
40
44
50
60
70
80
Average
Total
expenditures
mn. Euro
1,27
2,25
3,76
6,04
11,07
22,60
36,97
77,54
138,81
297,16
559,25
1.334,13
4.189,82
Per-capita
expenditures
Euro
1.507,62
1.515,91
1.502,12
1.532,96
1.585,83
1.634,95
1.545,87
1.970,60
2.264,04
2.545,87
2.185,36
2.729,53
3.404,98
10,99
1545,36
Table 4 - The effect of municipality council size on the level of expenditures
Explanatory variable
Log council sizeit
Log populationit
Log incomeit
Fixed effects OLS models
Model 1
Model 2
0,216 ***
0,059 **
0,024
0,025
0,519 ***
0,030
0,130 ***
0,010
Between OLS models
Model 3
Model 4
2,918 ***
0,171 ***
0,020
0,061
0,840 ***
0,029
0,121 ***
0,015
Observations
43175
43175
Municipalities
2056
2056
2056
2056
R2
0,946
0,947
0,910
0,952
Fixed municipality effects
Yes
Yes
No
No
Fixed time effects
Yes
Yes
No
No
Notes: Standard errors are robust to heteroskedasticity and autocorrelation. ***, **, and *
indicate that coefficients are significantly different from zero according to two-tailed tstatistics.
Table 5 - Difference-in-difference regression-discontinuity-design analysis
Explanatory variable
Log council sizeit
Log populationit
Log incomeit
Using a third-order polynomial about
log population
log voters
pop. & voters
Model 2a
Model 2b
Model 2c
0,045 **
0,059 ***
0,043 *
0,022
0,022
0,022
1,034
0,561 ***
-0,509
1,105
0,029
1,240
0,118 ***
0,128 ***
0,117 ***
0,009
0,009
0,009
Observations
43175
43175
43175
Municipalities
2056
2056
2056
R2
0,948
0,947
0,948
Fixed municipality effects
Yes
Yes
Yes
Fixed time effects
Yes
Yes
Yes
Notes: Model 2a uses a third-order polynomial of log population (instead of
relying on log population only as Model 2 in Table 4). In Model 2b, we use a
third-order polynomial function of the log number of eligible voters instead. In
Model 2c, we use a third-order polynomial of both log population and the log
number of eligible voters. We do not report coefficients of squared and tripled
variables. ***, **, and * indicate that coefficients are significantly different from
zero according to two-tailed t-statistics.
Table 6 - Sensitivity analysis for Model 2c in Table 5
Explanatory variable
Log council sizeit
Log populationit
Log incomeit
Unemployment rateit
Augmented
Model 2
0,136 ***
0,043
-7,610 *
4,078
0,054 ***
0,015
-1,100 ***
0,375
LAD for
Model 2c
0,160 ***
0,020
1,686
1,756
0,097 ***
0,012
-
Council size
≤14
0,047 *
0,029
0,511 ***
0,038
0,091 ***
0,012
-
Council size
>14 and ≤30
0,071 *
0,038
0,554 ***
0,042
0,154 ***
0,014
-
Council size
>30
0,944 ***
0,294
0,301
0,190
0,244 ***
0,065
-
Observations
20559
43175
24737
17754
684
Municipalities
2056
2056
1251
928
34
2
R
0,956
0,700
0,789
0,911
0,988
Fixed municipality effects
Yes
Yes
Yes
Yes
Yes
Fixed time effects
Yes
Yes
Yes
Yes
Yes
Notes: Augmented Model 2 includes the unemployment rate for each municipality and relies on less
observations than the other models, because unemployment figures are not available for the whole time
span considered. LAD is a median (least absolute deviations) regression version of Model 2c. In this case,
the R2 is a pseudo-R2. For subsamples of specific council size, we always use the specification in Model 2.
Notice that the parameter of log council size is identical to its fixed effects counterpart in Table 4, if the lefthand-side of the model is log (expenditure/income) or log (expenditure/population) instead of log
expenditure. ***, **, and * indicate that coefficients are significantly different from zero according to twotailed t-statistics.
Table 7 - Sensitivity analysis for Model 2c continued - The impact of party dominance on the
council size effect on expenditures
Explanatory variable
Log council sizeit
Log council sizeit × Large party fractionit
Log council sizeit × Fraction of CSUit
Log council sizeit × Fraction of SPDit
Log council sizeit × Fraction of FPDit
Log council sizeit × Fraction of Green Partyit
Log council sizeit × Fraction of Free Votersit
Log council sizeit × Fraction of Organised Voter Groupsit
Log populationit
Log incomeit
All parties
separately
0,046 **
0,022
-0,001
0,004
0,001
0,004
-0,020
0,015
-0,159 *
0,086
30,413
37,762
0,003
0,006
0,013
1,247
0,116 ***
0,009
Large 4
parties
0,046 **
0,022
-0,002
0,002
-0,031
1,247
0,116 ***
0,009
Observations
43088
43088
Municipalities
2056
2056
2
R
0,948
0,948
Fixed municipality effects
Yes
Yes
Fixed time effects
Yes
Yes
Notes: The large 4 parties are defined as the fraction of CSU, SPD, FDP, and the Green
Party in total votes at the previous municipality election. The party shares involved in the
interaction terms have generally been demeaned to ensure that the main effect of log council
size measures the average treatment effect. Notice that a third-order polynomial is used for
log population and log number of eligible voters as in Model 2c of Table 5. Hence, the
coefficient of log populationit should be interpreted with care. ***, **, and * indicate that
coefficients are significantly different from zero according to two-tailed t-statistics.
Table 8 - Difference-in-difference regression-discontinuity-design analysis of the effect of municipality council size on
municipality tax rates
Explanatory variable
Log council sizeit
Log populationit
Log incomeit
Using a third-order polynomial about pop. & voters (Model 2c)
Dependent variable is
Debt
Prop. tax A
Prop. tax B
Profit tax
-0,030
3,630 **
3,291 **
-0,898
0,064
1,480
1,436
0,814
18,589 ***
378,865 ***
790,195 ***
311,388 ***
3,569
82,812
80,314
46,083
0,012
-3,953 ***
-4,357 ***
-3,091 ***
0,025
0,583
0,565
0,321
Invest. exp.
0,094
0,068
3,401
3,382
0,190 ***
0,027
Observations
42266
39063
39063
43175
43161
Municipalities
2053
2056
2056
2056
2056
R2
0,799
0,935
0,911
0,856
0,714
Fixed municipality effects
Yes
Yes
Yes
Yes
Yes
Fixed time effects
Yes
Yes
Yes
Yes
Yes
Notes: Model 2a uses a third-order polynomial of log population (instead of relying on log population only as Model 2 in Table
4). In Model 2b, we use a third-order polynomial function of the log number of eligible voters instead. In Model 2c, we use a thirdorder polynomial of both log population and the log number of eligible voters. We do not report coefficients of squared and
tripled variables. ***, **, and * indicate that coefficients are significantly different from zero according to two-tailed t-statistics.