Sources of Revenue and Government Performance:
Theory and Evidence from Colombia
Luis R. Martı́nez*
December 2014
Abstract
Increases in local governments’ revenue have little (if any) impact on public good provision
or development indicators in low-income countries. However, since local governments obtain
most of their revenue from external sources (intra-government transfers, natural resource rents)
it is not clear whether the documented low return is specific to these types of revenue or if it
reflects an intrinsic inability to transform revenue into goods and services. A political agency
model with career concerns predicts that increases in taxation should have a greater impact
on public good provision than increases in external revenue through their opposite effects
on citizens’ willingness or ability to hold the government accountable. I use panel data from
Colombian municipalities for the period 2005-2011 to test the model’s main prediction by
comparing the impact on local public good provision of increases in property tax revenue to
that of increases in oil and coal royalties. I exploit quasi-exogenous variation in the international
prices of oil and coal and in the timing of cadastral updates for this purpose. I find that a $1
increase in tax revenue has an impact on educational enrollment at least twice as large as a $4
increase in oil/coal royalties. Neither type of revenue seems to improve infant mortality, even
though royalties must be spent on education and health.
JEL Classification: H71, H75, P16
*
l.r.martinez@lse.ac.uk. Department of Economics and STICERD, London School of Economics (Houghton Street, WCA2 2AE, London). I would like to thank Gerard Padró i Miquel for his support and advice
throughout this project. I am also grateful to Tim Besley, Miguel Espinosa, Greg Fischer, Lucie Gadenne,
Maitreesh Ghatak, Anders Jensen, Gilat Levy, Munir Squires and to seminar participants at LSE (workin-progress: public, development, STICERD) and EDEPO for comments and suggestions. I thank Mario
Martinez at Instituto Geográfico Agustı́n Codazzi for answering all my questions on cadastral updating and
I also thank Adriana Camacho, Oskar Nupia, Mónica Pachón, Fabio Sánchez, Rafael Santos and Ana Marı́a
Tribı́n for generously sharing data with me. All remaining errors are mine.
1.
Introduction
The number of low-income countries devolving expenditure responsibilities to local go-
vernments has increased in recent years (Gadenne and Singhal, 2014), but it is not clear
that these local governments do a better job at providing basic public goods and services
(Faguet, 2014). Lack of resources could be part of the problem but increases in local governments’ revenue have been shown to have little impact, if any, on public good provision or
development indicators, with increases in corruption often being reported instead.1
However, local governments in developing countries are heavily dependent on revenue
from external sources, like intra-government transfers or natural resource rents, rather than
on internally-raised tax revenue (Gadenne and Singhal, 2014) and it is on these external
sources of revenue that the existing literature has focused for the most part.2 This fact
can change our interpretation of the literature’s findings if we share the widely-held belief
that external revenue undermines government accountability and is relatively ineffective.3 It
could be the case that local governments fail to provide more public goods when they receive
additional revenue because of the particular type of revenue they collect.
But it could also be that these local governments are intrinsically unable (due, for instance, to low technical capacity or weak political institutions) to transform revenue into
goods and services, no matter what the source is. That is, for example, what a recent report on resource-rich municipalities in Colombia concludes (DNP, 2012). More generally,
cross-country evidence suggests that natural resource rents are not always a ‘curse’ for the
1
See Fisman and Gatti (2002); Reinikka and Svensson (2004); Vicente (2010); Caselli and Michaels
(2013); Brollo et al. (2013); Gadenne (2014); Olsson and Valsecchi (2014).
2
These local governments resemble the “rentier states” of the middle east, as characterized by Mahdavy
(1970) and Beblawi (1990), in their high dependence on external rents.
3
A large literature has documented how early European states in need of revenue were forced to implement
policies favoured by tax-payers in return for their contribution (North and Weingast, 1989). Besley and
Persson (2011) provide a theoretical account of how external revenue provides low incentives to improve the
ability to tax, which has a detrimental effect on growth. Ross (2001, 2004) provides evidence in support of a
“rentier effect”, according to which the availability of external revenue leads to a political equilibrium with
low taxation and low accountability. Bauer (1972) argues that one of the reasons for the ineffectiveness of
development assistance is precisely because it allows governments to loosen the fiscal contract with voters.
A similar point has been made in the context of the natural resource curse (See Frankel (2012) or van der
Ploeg (2011) for reviews).
1
countries that receive them (Mehlum et al., 2006b), while theoretical work on this topic
has highlighted how the problem may not lie in external revenue but in the institutional
characteristics of recipients (Robinson et al., 2006, 2014; Mehlum et al., 2006a).
This paper aims to shed light on the relation between the sources of government revenue
and public good provision. First, I develop a political agency model with career concerns
to illustrate how the return on government revenue may depend on the source. The model
formalizes the idea that tax revenue may have an opposite effect to external revenue on voters’
willingness to hold the government accountable or on their ability to do so, as suggested by
Paler (2013). The main prediction of the model is that an increase in tax revenue has a larger
impact on public good provision than an increase in external revenue of the same magnitude.
I test this prediction by comparing the effects of plausibly exogenous increases in property
tax revenue and natural resource royalties (from the extraction of oil and coal) on education
and health provision by Colombian municipal governments between 2005 and 2011.
Colombia is an ideal setting where to study this topic for at least three reasons. First,
municipal governments are responsible for the provision of local public goods and they have
access to several sources of revenue, both internal and external.4 This includes various local
taxes, transfers from the central government and natural resource royalties.
Second, while municipalities can spend property tax revenue at their discretion, revenue
from natural resource royalties can only be spent on projects that contribute to meeting
targets for a set of specific development indicators. I use two of these indicators, the basic
education enrolment rate and the infant mortality rate, as my main outcomes of interest.
Not only are these indicators a good gauge for local public good provision in the areas of
education and health, but due to the constraint mentioned above they are the best place
to look for an effect of additional royalties. The fact that tax revenue can be spent on
other things may bias the comparison in favour of royalties, but this bias works against the
4
Colombia is divided into 32 departments, each of which is itself divided into municipalities, in a somewhat
similar fashion to US states and counties. In total, there are 1100 municipalities in the country plus 20 nonmunicipalized territories in sparsely populated regions.
2
hypothesis I am testing.
Finally, Colombia is also a good setting for this study because high-quality data on the
relevant variables is available at the municipality-year level. The panel structure of the data
allows me to control for permanent differences between municipalities and for departmentspecific time effects affecting the outcomes of interest by including municipality fixed effects
and department-year fixed effects in all estimations.
An important challenge that this type of empirical exercise faces is having access to
plausibly exogenous sources of variation in both tax revenue and external revenue. I exploit
fluctuations in the international prices of oil and coal as a source of variation in the amount
of natural resource royalties received by municipalities where these resources are exploited.
The identifying assumption here is that fluctuations in the international prices of oil and
coal are exogenous to local conditions in producing municipalities in Colombia. Even though
the exclusion restriction is probably violated, as I find evidence consistent with price shocks
having a positive income effect besides the fiscal one of interest, this will likely bias estimates
of the impact of royalties upwards and should also work against the hypothesis being tested.
I exploit the timing of cadastral updates as a source of variation in property tax revenue.
The cadastre is a record of the characteristics of the properties in a municipality, including
their value. This cadastral valuation is the base of the property tax that is collected by the
municipality. Cadastres are updated periodically by the national geography institute (IGAC),
which is run by the central government. Since municipalities have to agree to the update, and
they often partly finance it, the timing of updates could be endogenous. More specifically, I
have to deal with the possibility of joint determination (an unobserved variable affects both
the probability of updating and the outcomes of interest) and of reverse causality (updates
are triggered by good projects in the areas of education or health that require funding).
I argue that the timing of cadastral updates is as good as random, conditional on municipality and department-year fixed effects, by showing that there is no significant correlation
between the timing of cadastral updates and changes in a wide range of observable time-
3
varying municipal characteristics. These include all other sources of revenue, local political
conditions, indicators of civil conflict and central-government policies. I argue that it is unlikely that a change in relevant unobservable characteristics would not be reflected in a change
in one of these observables.
I provide additional evidence supporting that the timing of the updates may be plausibly
exogenous. First, for a more recent period (2012-2013) I match municipalities that updated
during a given year to a ‘wish list’ drafted by IGAC at the start of that year. This exercise
reveals that updating is largely determined by the supply of updates by IGAC, whose objective is to maximize the percentage of properties up-to-date in the country. Second, I show
that during the sample period there was a positive shock to the supply of updates by IGAC,
which resulted in a large and plausibly exogenous increase in the number of municipalities
that updated. This was due to the central government’s demand that IGAC reach 100 % of
cadastres up to date and the availability of an IDB loan that fully funded updates for 15 %
of municipalities.
The results indicate that cadastral updating leads to an increase in property tax revenue
that is only a fraction of the impact of an oil/coal price shock on royalties. But while the
extra tax revenue leads to a small but significant increase in educational enrolment, the extra
royalties have barely any effect. A conservative estimate suggests that a $1 increase in tax
revenue has an effect on educational enrolment at least two times as large on educational
enrolment as a $4 increase in royalties. Extra tax revenue also seems to contribute to a
reduction in infant mortality but the impact is very small and statistically insignificant.
These results are unchanged if I only look at municipalities that receive oil or coal royalties, which alleviates concerns about the variation in the sources of revenue affecting different
sets of municipalities. It also provides further evidence against selection bias as it is very
unlikely that resource-rich municipalities select into updating to raise additional revenue for
education or health. Results are also unchanged if I look at a long time window to account
for a potential lag in the effect of large projects funded with royalties.
4
This paper contributes to a small literature focusing on the effects of different sources of
revenue on government performance. An early example was Zhuravskaya (2000), who showed
that public good provision is better in Russian cities where increases in tax revenue are not
offset by a reduction in transfers from the regional government. A more recent contribution by
Gadenne (2014) finds that the quantity and quality of educational infrastructure in Brazilian
municipalities is positively affected by local tax revenue while additional intra-government
transfers have no effect. The lab experiments in Paler (2013) and Martin (2014) provide
additional evidence on the different effects of internal and external revenue on government
accountability.
The rest of this paper is organized as follows. Section 2 summarizes the theoretical model
and presents the main hypothesis to be tested in the empirical exercise. Section 3 provides
background information on sources of revenue and expenditure responsibilities of municipal
governments in Colombia. I discuss the empirical strategy and the data used in section 4.
Section 5 presents the results and section 6 concludes.
2.
Theory: taxation and accountability
In this section I develop a political agency model with career concerns to show how
taxation may differ from external revenue in the way it shapes the incentives of public
officials. The model formalizes what are perhaps the two most important mechanisms that
previous literature has suggested may drive the heterogeneous impact of internal and external
revenue on government performance. As suggested in Paler (2013), taxation may increase
citizens’ willingness to hold the government accountable but it may also better enable them
to do so.
The model illustrates how these mechanisms operate in a context of imperfect monitoring, where voters can’t perfectly assess the quality of the incumbent based on public good
provision because they only get a noisy signal on the amount of government revenue. This
5
affects the incentives that the incumbent has to put in extra effort, which is unobservable to
voters, in order to appear more competent to them. Formally, the model takes a standard
political agency model with career concerns (Persson and Tabellini, 2000; Brollo et al., 2013)
and adds to it the element of imperfect monitoring, along the lines of Holmström (1999).5
I allow taxation to increase citizens’ ability to hold the government accountable by considering the possibility that the noise in voters’ signal on revenue is decreasing in the share
of taxes in total revenue. I then consider an alternative set-up where voters can improve the
precision of their revenue signal at a cost. Under the assumption that the marginal utility of
public goods is decreasing in private consumption, an increase in taxation increases voters’
willingness to hold the government accountable because it increases their willingness to pay
for more precise revenue information. Both mechanisms suggest that an increase in tax revenue should have a greater impact on public good provision than an increase in external
revenue of the same magnitude.
In what follows I will first present the basic set-up of the model and then look at the two
alternative mechanisms in turn. I close this section by discussing the empirical relevance of
these mechanisms and where the model fits relative to the existing literature. I leave formal
derivations and proofs for a theoretical appendix.
2.1.
Set-up of the model
This is a two-period model in which a citizen/voter obtains utility from private consumption of her disposable income and also from consumption of a public good that is provided
by the politician in power each period (henceforth referred to as the mayor). At the end of
the first period an election between the incumbent and a random opponent takes place. The
incumbent as well as his opponent are drawn from a pool of potential politicians, each endowed with some level of ability θi > 0. The ability of all politicians is unknown to everyone
but there is a common prior that is normally distributed with mean m and precision h.
5
Alesina and Tabellini (2007) analyze the career concerns model with imperfect monitoring with regards
to a very different question.
6
The citizen receives a constant income yt = y each period. She pays a tax on a fraction
of her income, determined by η ∈ (0, 1), with exogenous rate τ ∈ (0, 1). The citizen’s private
consumption is equal to her disposable income: ct = (1 − τ η)yt . Her utility function is
Ut = U (ct , gt ), where gt is the amount of the public good that is supplied that period. U (·)
is increasing in both its arguments.
Government revenue (Rt ) is equal to tax revenue (amounting to τ ηyt ) plus revenue from
an external source (Tt ) such as royalties from the extraction of natural resources or transfers
from another level of government. I assume that operational expenditures eat up a constant
share 1 − µ of revenue, so the amount of revenue available for public good provision is µRt ,
µ ∈ (0, 1).
The amount of public good provided by a mayor with ability level θ is given by the
function
gt = θ + µRt + et
(1)
where Rt = τ ηyt + Tt and et ≥ 0 is the amount of effort put in by the mayor, which is
unobservable to the citizen.6 The cost of effort borne by the mayor is given by the increasing
and strictly convex function γC(e), γ > 0. The mayor also gets a benefit E > 0 from being in
power each period, which includes financial rewards and “ego rents”. Total per-period utility
for the mayor is then E − γC(e).
At the end of the first period the citizen observes the amount of public good provided.
She also receives a noisy signal (R̃t ) on the total amount of revenue (Rt ). Based on this
information and a conjecture on effort she updates her beliefs on the incumbent’s ability.
She then votes for the candidate of her liking.
Before making additional assumptions about the link between the sources of revenue and
the noisy signal that the citizen receives, I summarize the timing of the game (I will drop
the time subscripts for everything that is not changing over time):
6
See Dewatripont et al. (1999) for a discussion of more general versions of this type of model.
7
1. The incumbent (with ability θ unknown to all) gets revenue R = T + τ ηy and picks e1 .
2. A quantity of public goods g1 is provided according to equation 1.
3. The citizen observes g1 and receives the noisy signal R̃. She uses this information to
update her beliefs on the incumbent’s ability.
4. The citizen chooses between the incumbent and a random opponent with the same
prior ability (m).
5. The winner of the election chooses e2 and this determines g2 .
2.2.
Taxes as a source of information on public revenue
I will start by assuming that the share of exogenous revenue in total revenue amplifies
the noise in the citizen’s perception of total revenue:
R
Assumption 1. R̃t = Rt − R
t where t ∼ N [0, 1/h ] and t =
Hence, the precision of R
t is
T +τ ηy
T
T
T +τ ηy
12
t
h . Through this assumption I introduce the idea
that citizens are better informed about changes in tax revenue than about changes in external
revenue.
The functional form of the production function for public goods implies that additional revenue from any source always has a positive direct effect on public good provision
(mechanical revenue effect), but the total effect depends also on the indirect effect through
incumbent effort. Under assumption 1, an increase in revenue affects the incumbent’s effort
choice because it changes the precision of the revenue signal the citizen gets. As tax revenue
increases, the signal becomes more precise and the citizen becomes more attentive to the
amount of public goods provided in her assessment of the incumbent’s quality. This in turn
makes it optimal for the incumbent to increase effort in order to influence the election in his
favour. By the same logic, an increase in exogenous revenue makes the revenue signal noisier
8
and the citizen less responsive, so the incumbent reduces effort.7 The following proposition
formalizes this result.
Proposition 1. Under assumption 1, equilibrium first-period effort of the incumbent is increasing (decreasing) in tax revenue (external revenue). Hence, public good provision in the
first period increases by more (less) than the mechanical revenue effect when there is an
increase in tax revenue (external revenue).
2.3.
Taxes as an incentive for information acquisition on public
revenue
I now substitute Assumption 1 with the following three assumptions:
Assumption 2. R̃t = Rt − t , where t ∼ N [0, 1/h ]
Assumption 3. Ut = U (ct + αgt ) where U (·) is a strictly concave function and α ∈ (0, 1/µ)
Assumption 4. At the start of the game, the citizen can choose how much effort (m1 ≥ 0) to
spend on the improvement of the revenue signal. Effort increases the precision of the revenue
signal according to the linear function h = λm1 , λ > 0, but it has a cost given by the strictly
convex function K(m1 )
Just like before, the citizen is more responsive to public good provision in her assessment
of the incumbent’s quality the better she is informed about revenue. In turn, the incumbent
puts in more effort as the citizen becomes more responsive. Under the new assumptions,
what sets this mechanism in motion is information acquisition by the citizen, which depends
on the marginal utility of public goods. When tax revenue increases, private consumption
mechanically decreases. Although public good provision also increases due to the mechanical
revenue effect, Assumption 3 ensures that the marginal utility of the public good goes up
7
The model can easily be rewritten in terms of incumbent rents rather than effort, as discussed in Alesina
and Tabellini (2007). In that case, additional revenue has an additional effect on rent extraction because
it increases the value of staying in power. This mechanism is at play in the model of the resource curse in
Robinson et al. (2006, 2014).
9
nevertheless, which increases the benefit the citizen gets from additional incumbent effort.
External revenue, on the other hand, has a negative effect on the marginal utility of the
public good due to the positive mechanical revenue effect and the fact that it does not
affect the citizen’s disposable income. Hence, extra taxation provides an incentive for more
information acquisition while the opposite holds true for external revenue. The following
proposition formalizes this result:
Proposition 2. Under Assumptions 2-4, optimal citizen effort and equilibrium first-period
effort of the incumbent are increasing (decreasing) in tax revenue (external revenue). Hence,
public good provision in the first period increases by more (less) than the mechanical revenue
effect when there is an increase in tax revenue (external revenue).
2.4.
Discussion
The theoretical discussion above allows us to better understand the type of environment
in which the source of revenue may matter for government performance. The model shows
that misinformation on local public finance on the part of voters is sufficient and may be
necessary for internal and external revenue to have opposite effects on public good provision.
In a world where revenue is perfectly observed, as in Persson and Tabellini (2000) or Brollo
et al. (2013), incumbent effort is not differentially affected by each source of revenue.
The model also defies the common-sense notion that taxation improves accountability
simply because voters dislike the loss in private consumption that results from taxation.
This asymmetric effect of internal and external revenue on disposable income does not by
itself translate into differential government performance because taxes are a sunk cost at the
time of voting. Voters cannot credibly commit to punish an incumbent who wastes their tax
money if they have reasons to believe that he is of higher ability than his opponent in the
election. The fact that both Martin (2014) and Paler (2013) report that participants in lab
experiments were more willing to punish the government when it was handling tax money
may thus be a consequence of the one-shot nature of the games being played.
10
In the empirical exercise that follows I will test the main prediction of the model (captured
in Propositions 1 and 2), but I will not be able to establish the relative importance of the
two mechanisms discussed. However, I can provide anecdotal evidence on the realisticness of
the underlying assumptions and I can also look to the previous literature to get a sense of
their relevance.
Assumption 1 seems like a reasonable assumption to make given that tax revenue is
coming out of voters’ pockets. This should provide contributors with relatively costless information about changes in tax revenue, while learning about changes in external revenue is
costly. The word ‘changes’ is crucial in this context: voters in resource-rich areas may know
about the abundance of natural resource rents (level), but still they must pay close attention
to fluctuations in prices and output to be well informed about the change in these rents.8
Gadenne (2014) provides a model of moral hazard based on a similar assumption: the amount
of external revenue is only known by the incumbent and this allows him to appropriate a
larger share of revenue when external revenue is high.
Evidence from previous research seems to support the idea that voters are better informed
about changes in tax revenue than about changes in external revenue. For example, Gadenne
(2014) finds that local tax revenue has a larger effect on educational infrastructure than intragovernment transfers only in Brazilian municipalities that don’t have a radio station. This
finding suggests that media presence closes the gap in voters’ awareness about changes in
external revenue relative to changes in tax revenue. A related example is provided by Reinikka
and Svensson (2004), who report that only 13 cents of every $1 from an educational grant
program in Uganda reached the primary schools that were the intended recipient, with the
rest being embezzled by local politicians. The fact that an information campaign started
by the central government in response to this finding led to large increases in the amount
of grants reaching the schools indicates that lack of information about the grants was what
8
Of course, paying one’s own taxes may not be very informative about total tax revenue in a world with
significant heterogeneity in tax liabilities, but this is something the model abstracts from.
11
allowed funds to be diverted (Reinikka and Svensson, 2005).9
However, there is also evidence supporting the idea that taxation increases voters’ willingness to hold the government accountable. Both Paler (2013) and Martin (2014) find
that participants in lab experiments are more willing to engage in costly punishment of a
misbehaving government when the source of revenue is taxation than when it is external.
The experimental setting allows these authors to ensure that information is constant across
treatments, thereby shutting down the mechanism discussed above. Martin (2014) argues
that this finding is consistent with a model of loss-aversion where citizens’ reference point
is given by their pre-tax endowment. In this model taxation drives citizens into the realm
of losses and makes them more willing to engage in costly punishment unless they are compensated through increased public good provision. While punishment is assumed to provide
citizens with an “expressive benefit” in this framework , in the model presented above the
benefit that voters get from not re-electing the incumbent is endogenously determined by the
information available to them. Still, loss aversion may help to explain why taxation increases
the marginal utility of public goods (Assumption 3).
3.
Background
Following decentralization reform in the early 1990s, Colombian departments and muni-
cipalities became responsible for the provision of public services in the areas of education,
health, drinking water and sanitation. The central government provides funding for related expenditures through a system of earmarked and formula-determined transfers called
“Sistema General de Participaciones” (SGP). These transfers account on average for 63 %
of a municipality’s total revenue but they are not fungible with other sources of revenue
9
Several papers provide more general evidence on the importance of information provision for government
accountability: Ferraz and Finan (2008) find that audit reports published before elections allow voters to
punish corrupt politicians. Björkman and Svensson (2009) report that the provision of information to local
communities on the quality of health services leads to improved health outcomes through better monitoring.
Paler (2013) shows that once participants in a lab experiment are provided with information on government
expenditures, they are equally willing to monitor the government no matter what the source of revenue is.
12
and must be kept in separate accounts. Municipalities have more discretion over education
policies than over the ones related to health.10
Taxes are the second most important source of municipal revenue after transfers and
contribute on average with 44 % of current receipts and 13 % of total revenue. The main local
taxes (and their average shares of tax revenue) are the property tax (34 %), the business tax
(17 %) and the petrol surcharge (22 %).11 The property tax is the most important source
of tax revenue for slightly more than one half of municipalities, but its relative importance
decreases with population size.12 Property tax revenue can be spent at the discretion of
the municipal government, except for a fixed share that must be transferred to the relevant
regional environmental agency.13
The property tax is levied on the cadastral value of all real estate in the municipality. The
cadastre or land registry is the official record of the physical and economic characteristics of
all properties in a municipality. The three largest cities (Bogotá, Medellı́n and Cali) as well
as the department of Antioquia have their own cadastral agencies. All others (86 % of municipalities) are under the authority of the National Geography Institute (Instituto Geográfico
Agustı́n Codazzi - IGAC), an agency run by the central government. Through periodic updates of the cadastres under its control, IGAC includes new properties and updates the records
(including the value) of existing ones.
The third most important source of local revenue are royalties from the extraction of
10
Municipalities ‘certified’ by the Ministries of Education or Health directly manage the shares of transfers
assigned to these areas. Otherwise, transfers are managed by the government of the department where the
municipality is located. Any municipality, certified or not, can provide additional funding for the provision
of education and can also invest in infrastructure, quality improvements or school equipment. On the other
hand, municipalities not certified by the Ministry of Health are banned from providing health services, while
certified ones must do so through highly-regulated firms called “Empresas Sociales del Estado” (ESE). All
municipalities are responsible for providing health insurance to the population classified as poor by the
national government’s proxy-means-testing targeting system (SISBEN).
11
Other taxes include those for car registration and the display of billboards and banners. Departments
have authority over the alcohol and cigarettes taxes. They also set their own, albeit smaller, petrol surcharge.
12
Glaeser (2013) reports that local public finances in the US are not very different, with intra-government
transfers and property taxes being the most important sources of revenue for all but the largest cities.
However, Gadenne and Singhal (2014) show that local governments are much more dependant on intragovernment transfers in developing countries than in developed ones.
13
There are 34 such agencies in the country. Some cover a handful of municipalities while others cover
multiple departments. The percentage transferred must be between 15 % and 25 % of property tax revenue.
13
natural resources. Royalties are paid by firms to the central government according to a set
of fixed formulae of the form
royalty = output * world price (USD) * exchange rate (COP/USD) * royalty rate
The vast majority of this revenue is then transfered to producing municipalities and departments, as well as port municipalities, according to predetermined shares. The main source
of royalties is the extraction of oil and coal, which accounts for 93 % of all royalties paid
between 2005 and 2011.14 Oil and coal royalties benefit around 20 % of municipalities (see
Figure 1), for which they represent on average 19 % of total revenue. By law, at least 75 % of
royalties must be spent on education, health, drinking water and sanitation until a specific
set of indicators (listed in Table 1) meet certain target rates.15 The system was reformed
in 2012, with the share of royalties going to producing regions significantly reduced in an
attempt to make the distribution of royalties more equitable.
4.
Empirical Strategy
The main objective of the empirical exercise is to test the hypothesis, summarized in
Propositions 1 and 2, that an increase in tax revenue has a larger effect on public good
provision than an increase in external revenue of the same magnitude. I carry out this
comparison between sources of revenue using data for Colombian municipalities between
2005 and 2011. I compare the effect on local public good provision of increases in property
tax revenue vis-à-vis increases in royalties from the extraction of oil and coal.
As discussed in the previous section, Colombian law stipulates that royalties must be
spent on projects that help to bring indicators in the areas of education and health closer to
14
Royalties are also paid for the extraction of precious metals, gemstones, iron, copper, nickel and salt.
The guidance from the central government in DNP (2007) suggests that in order to reduce infant
mortality municipalities can carry out vaccination campaigns (vaccines are provided at zero cost by the
central government) or set up emergency health posts for common infant diseases. Regarding education,
royalties can be used to finance the provision of education if SGP transfers are shown to be insufficient.
Otherwise, royalties can be spent on education infrastructure, school equipment or transportation. In the
case of water supply and sewage, royalties can be invested in the necessary infrastructure.
15
14
some predetermined target rates. I focus on two of these indicators as the main outcomes of
interest for the empirical exercise: the net enrollment rate in basic education and the infant
mortality rate. Table 1 shows that less than one quarter of the municipalities with positive
oil or coal royalties in 2004 had reached the target goal for these two indicators in 2005,
which makes these variables a good place to look for an effect of royalties.
The availability of yearly observations for each municipality allows me to include municipality and time fixed effects in all regressions. Still, the variation over time in a particular
source of revenue for a given municipality may be correlated with other time-varying municipal characteristics affecting the outcomes of interest, which could lead to biased estimates
of the effects we are interested in measuring. Hence, plausibly exogenous variation in both
sources of revenue must be found in order to claim that the estimates capture causal effects.
I mentioned above that the geographical institute IGAC carries out regular updates
of the cadastres under its supervision. I use the timing of these updates as a source of
variation in property tax revenue. I argue below that these updates are driven for the most
part by the ‘supply’ of such services on the part of IGAC and that they are plausibly
uncorrelated with variation in municipal characteristics, conditional on municipality and time
fixed effects. I provide evidence in support of this claim by showing that the timing of updates
is uncorrelated with a set of relevant and observable economic and political characteristics,
which are also likely to reflect variation in the main unobservables of concern.
I exploit fluctuations in the international prices of oil and coal interacted with a measure
of local resource abundance as a source of variation in royalties. The argument is that
variation in the world prices of commodities affects Colombian municipalities differentially
depending on resource abundance but is plausibly exogenous to local conditions in Colombian
municipalities.
I will next introduce the data employed in the empirical exercise. Afterwards, I will
discuss the identification strategy just outlined and I will provide evidence in support of it.
15
4.1.
Data
The empirical exercise described above requires three main pieces of data. First, I need
data on the different sources of revenue of municipal governments. Second, I require the
indicators that will be the main outcomes of interest. Finally, I must also have information
on the sources of variation of both internal and external revenue. This means having data
on cadastral updates in the case of property taxes, and on the world prices of oil and coal,
as well as on local resource abundance, in the case of royalties.
Data on municipal public finance comes from the yearly balance sheets reported by each
municipality to the Office of the Comptroller General for the purpose of fiscal control. These
balance sheets have disaggregated information on revenue, including taxes (each one separately), transfers and royalties. I express all money values in thousands of 2004 Colombian
Pesos per capita (unless otherwise stated) using the Consumer Price Index and population
estimates from the National Statistical Agency (DANE).
The net enrollment rate in basic education and the infant mortality rate are provided at
the municipality-year level by the Ministry of Education and DANE, respectively.16 These
two indicators are the main outcomes of interest in the empirical exercise. Lack of data before
2005 for either indicator forces me to start the analysis in this year. Although Colombian
law also allows royalties to be spent on projects that increase the percentage of population
with access to drinking water or sanitation, lack of panel data at the municipal level prevents
me from including the corresponding indicators in the analysis. The other potential use of
royalties is in the provision of subsidized health insurance to the poor.17 During the sample
period the central government set out to achieve full coverage in this area and, as Table 1
shows, this policy was very successful: 94 % of the municipalities with oil or coal had reached
the target by 2011 (the percentage is almost identical for the full sample). Thus, it is not
16
Basic education in Colombia includes one year of pre-school, five years of primary and four years of
secondary. The net enrollment rate is calculated by dividing the number of children enrolled with ages
between five and fourteen by the total number of children in this age group.
17
Poor is defined as falling into categories 1 and 2 of the central government’s proxy means testing system,
SISBEN.
16
surprising that increases in either source of revenue don’t seem to have any effect on this
indicator (results are not reported but are available upon request).
Regarding cadastral updating, IGAC has yearly data on the number of properties, the
cadastral value and the year of the last cadastral update for each municipality under its
supervision. The three largest cities in the country (Bogotá, Medellı́n and Cali) as well as
the department of Antioquia have their own cadastral agencies and are excluded from the
analysis. All cadastral information provided by IGAC is disaggregated for each municipality
between the urban and rural areas. I focus on urban cadastral updates since urban areas
contain most of the properties and value. Also, urban updates are more frequent and less
likely to be endogenous, since security concerns related to the internal armed conflict have
often prevented IGAC agents from carrying out rural updates (IGAC, 2012).
As indicators of oil and coal abundance I use the amount of royalties specific to each of
these resources that each municipality received in 2004, according to the National Hydrocarbons Agency (Agencia Nacional de Hidrocarburos - ANH) and the Mining and Energy
Planning Unit (Unidad de Planeacion Minero-Energética - UPME), respectively. I pick this
year because it is the earliest one for which information on resource-specific royalties is publicly available at the municipality level. I then interact the respective measure with the
average yearly price of bituminous coal (from UPME) and the average petroleum spot price
(from the IMF/IFS) to predict variation in royalties over time.
The final panel includes 961 municipalities (out of a total of 1123) between 2005 and 2011.
Table 2 shows summary statistics for the variables discussed above and for some additional
ones employed in the paper.
4.2.
Identification Strategy
The first part of this paper’s identification strategy exploits cadastral updates as a source
of plausibly exogenous variation in property tax revenue. To estimate the reduced-form impact of cadastral updating on the outcomes of interest I use the following flexible specification
17
that allows for time-varying effects in a window around the update year:
yi,j,t = αi + δj,t +
4+
X
βk · D(update(t − k))i,t + i,j,t
(2)
k=−2
where αi is a municipality fixed effect and δj,t is a department-year fixed effect. These account
for all permanent differences between municipalities and for common factors affecting equally
all municipalities from the same department in the same year. D(update(t−k))i,t is a dummy
equal to one if an update took place k years ago. The error term i,j,t is clustered two-way
by municipality and department-year following the methodology in Cameron et al. (2011).
The parameters of interest, βk , flexibly capture the behavior of the dependent variable
both before and after a cadastral update, allowing me to alleviate concerns about potential
pre-trends. These coefficients will provide unbiased estimates of the causal effect of having a
cadastral update k years ago only under the assumption of strict exogeneity of the timing of
the update. They will also be valid instruments for property tax revenue under the additional
exclusion restriction that updating only affects the outcomes of interest through its effect on
tax revenue.
Since cadastral updating is not randomly assigned, joint determination and reverse causality are two major concerns that may compromise the identification strategy. Joint determination occurs if there is variation over time in some unobservable characteristic that not only
makes cadastral updating more likely but also affects the outcomes of interest. For example,
an economic boom may increase parents’ willingness to send their children to school, thereby
improving enrollment rates, while at the same time making local governments more willing
to update the cadastre in an attempt to benefit from the resulting rise in property prices.
Reverse causality has to do with the possibility that improving social indicators affect the
probability of a cadastral update. In the present context, this could happen for instance
if municipalities update in order to raise extra funding when there is a good investment
opportunity in the areas of education or health.
We must better understand the update decision in order to assess the magnitude of the
18
threat that these concerns pose to the identification strategy. Colombian law stipulates that
cadastres should be updated every five years, but this condition is rarely satisfied. Panel A
in Table 2 shows that on average municipalities that updated between 2005 and 2011 did
so 10.3 years after the previous one. Hence, the cadastral updates that we observe are the
equilibrium outcome of the interaction between the supply of updates, provided by IGAC,
and the demand for updates by the municipalities.
The first step of the update process takes place at the start of the calendar year, when
IGAC drafts a list of municipalities that it considers to be suitable for updating.18 Municipalities are included in this list based mostly on the number of years since the previous update,
as IGAC’s institutional objective is to keep the cadastres under its control as updated as
possible. IGAC does not receive any financial reward from cadastral updates. Nevertheless,
other considerations such as the availability of up-to-date cartography and the reports by
the regional offices on the feasibility of potential updates are also taken into account.
The next step involves IGAC contacting the municipal authorities (mainly the mayor’s
office) to seek their approval for the update. Although de jure IGAC has the sole authority
to carry out cadastral updates, de facto it turns out to be almost impossible to do an update
without the support of the local authorities. Additionally, only a small amount of resources is
assigned to IGAC by the central government for cadastral updating, so in most cases IGAC
also asks municipalities to provide at least partial funding for the update.19
The final list of municipalities whose cadastres are updated in a given year is the result
of this bargaining process between IGAC and the municipalities. However, looking at the
preliminary lists drafted by IGAC for the years 2012 and 2013 (after the sample period), I
find that 80 % of the municipalities that effectively updated were in IGAC’s preliminary list,
while 68 % of the municipalities in the list actually updated. This suggests that although
there is room at the margin for selection into and out of updating by municipalities, most
18
Following an update, the revised cadastre comes into effect on January 1st of the following year. Hence
updates must always be carried out within a calendar year.
19
Other sources of funding are the departmental governments and the regional environmental agencies.
19
updates come from the preliminary list drafted by IGAC at the start of the year.
The supply of updates by IGAC may have been particularly important during the sample
period for two extra reasons. First, Alvaro Uribe set for IGAC a target rate of 100 % urban
cadastres up-to-date as part of the official government goals for his first term as president
between 2002 and 2006 (Law 812/2003). Second, IGAC had access to an IDB loan with
which it fully funded urban updates for 145 municipalities (15 % of the sample total) around
the same time (IGAC, 2006). In consequence, there was a significant increase in the number
of municipalities that had a cadastral update in the period 2004-2007, as can be seen in
Figure 3.
Overall, 68 % of municipalities update between 2005 and 2011. These are evenly distributed throughout the country, as shown in Figure 2. Among the non-updaters, 38 % had
updated in 2003 or 2004, which suggests that the ability of municipalities to affect the timing
of cadastral updates is limited. I can’t fully exploit this large number of updates since the
inclusion of all of them in the estimations could introduce significant composition effects, as
I do not observe the same time-window around the update for all update cohorts. In order to
have at least two years of data before an update and at least three years after it I restrict the
main analysis to the update cohorts of 2007, 2008 and 2009.20 The number of municipalities
for which I observe an update drops to 32 % as a result, but I show that the results are very
similar if I include the 2006 cohort (thereby observing updates for 47 % of municipalities),
although this leaves me with only one year of pre-update data.
To further assuage endogeneity concerns, I investigate whether the timing of a cadastral
update is correlated with changes in some important observable economic and political characteristics. For this purpose I estimate equation 2 using these characteristics as dependent
variables.
The first four columns in Table 3 look at sequentially larger aggregates of other sources
20
I drop the years 2005 (and 2006) for the 2008 (2009) cohorts and I code as zero the update dummies for
all other cohorts. Coding updates outside the period 2007-2009 as zeros could potentially bias the estimates
downward, which would work against my hypothesis, but the results are qualitatively similar if I drop these
other update cohorts instead.
20
of revenue different from property taxes. The results suggest that there is no statistically
significant difference in any other source of revenue before or after a cadastral update, which
implies that there is no evidence of revenue offsets leading to or being caused by cadastral
updates.21 These results help to alleviate other concerns as well. Insofar as the business tax
revenue serves as a coarse proxy for municipal GDP (Sánchez and Núñez, 2000), the results in
column 1 indicate that there is no significant change in economic activity around the time of
a cadastral update. Additionally, these results make it less likely that municipalities update
the cadastre to raise revenue for profitable social projects as they show that municipalities
do not raise extra revenue in any other way around this time.
I investigate the possibility of changes in policies by the central government that could
be correlated with the timing of updates in columns 5 and 6 of Table 3. During the Uribe
administration (2002-2010), the president visited a different municipality every week with
some senior members of his staff. During these visits, local residents voiced their problems
and the president agreed to different policies concerning the municipality. One potential
concern is that a cadastral update and other policies affecting educational enrollment or
infant mortality are part of what the president agrees to when he visits a municipality.22
However, the estimates in column 5 show that there is no statistically significant evidence of
any correlation between the timing of updates and Uribe visits. Moreover, column 6 shows
that the number of new families enrolled in the conditional cash transfer program called
“Familias en Acción”, which was expanded dramatically during the Uribe administration
(Nupia, 2011), is also uncorrelated with the timing of updates.
The final two columns explore possible links between changes in violence and the timing
of cadastral updating. This is a source of concern because the presence of illegal armed
actors has often prevented IGAC from carrying out (mostly rural) updates in areas of high
conflict intensity (IGAC, 2012), and because violence could potentially affect the outcomes
of interest. Column 7 shows estimates of equation 2 using the murder rate as dependent
21
22
I do not find any significant effect either if I look at each source of revenue separately.
See Tribı́n (2014) for more information on the political economy of these promises.
21
variable, while in column 8 I use a dummy equal to one if any of the conflict indicators from
the CEDE dataset are positive.23 Again, the results suggest that the timing of cadastral
updates is uncorrelated with variation in violence.
To study the possibility that local political characteristics affect the timing of cadastral
updates I use electoral results from the local elections of 2003 and 2007, as well as the
presidential elections from 2002 and 2006, to construct a series of indicators on political
competition and alignment between branches of the local government, as well as between
levels of government.24 Summary statistics for these variables are provided in Panel E of
Table 2. I then run the following specification at the municipality-term level:
D(update)i,t = αi + δj,t + agei,t + D(age ≤ 3)i,t + Xi,t ξ + i,j,t
(3)
where the dependent variable D(update)i,t is a dummy equal to one if an update took place
in municipality i during local political term t. αi is a municipality fixed effect, δj,t is a
department-term fixed effect and Xi,t is a vector of political characteristics. The variable
agei,t corresponds to the age of the cadastre inherited from the previous administration,
while D(age ≤ 3)i,t is a dummy equal to one when at the start of the administration the
last cadastral update took place less than three years ago. This accounts for the fact that no
municipality updates the cadastre within three years of the previous update. I standardize
all explanatory variables, except dummies, for comparability. The error term i,j,t is clustered
two-way by municipality and department-year (Cameron et al., 2011).
Results are presented in Table 4. The first three columns show that, in the absence of
municipality fixed effects, there is a positive and statistically significant correlation between
the probability of a cadastral update and local political competition, measured by the number
of candidates in mayoral and council elections. There is a similarly positive and significant
23
Results are unaffected if I use an indicator of conflict intensity instead or if I look at presence of different
illegal armed actors separately.
24
All municipalities have simultaneous elections for mayor, city council, governor and departmental assembly every four years. Presidential and congress elections also take place every four years, but with a one
year lead relative to the those of sub-national governments.
22
correlation between the probability of updating and the vote share of the winning candidate
in elections for president and department governor. However, columns 4-7 show that once
I control for fixed differences between municipalities by including municipality fixed effects,
political characteristics have no statistically significant effect on the probability of a cadastral
update, conditional on the number of years since the last cadastral update. A one standard
deviation increase in the age of the inherited cadastre is associated with a 34 percentage point
increase in the probability of updating, which is one order of magnitude greater than the
point estimates for all political characteristics. This provides further evidence that IGAC’s
interest in reducing the age of the cadastres in the country is the main determinant of
cadastral updating. The results are unaffected if I replace the term fixed effect with a more
stringent department-term fixed effect, as can be seen in the last three columns of the table.
The second part of the identification strategy exploits plausibly exogenous variation in
the world prices of oil and coal and the heterogeneous distribution of these resources across
municipalities. This type of difference-in-differences methodology has been widely used in
recent studies on Colombia.25 The identifying assumption in this case is, first, that the world
prices of coal and oil are exogenous to local conditions in Colombian municipalities and,
second, that any effect of being differentially endowed with coal or oil is absorbed by the
municipality fixed effects. I estimate the following equation:
yi,j,t = αi + δj,t +
X
0
X
γm pricert+m · royaltiesri,2004 + i,j,t
(4)
r∈{oil,coal} m=−2
where αi and δj,t are again municipality and department-year fixed effects, respectively.
pricert+m is an index (2004=1) of the price of resource r, m years ago. I include the contemporary price of both resources as well as the values for up to two previous years to account for
the possibility of a lagged impact. The error term i,j,t is clustered two-way by municipality
and department-year (Cameron et al., 2011). As a measure of oil (coal) abundance I use the
amount of oil (coal) royalties received by the municipality in 2004 (royaltiesri,2004 ). Ideally, one
25
See Dube and Vargas (2013); Carreri and Dube (2014); Santos (2014); Idrobo et al. (2014)
23
would want to use some ex-ante geological measure of resource abundance to avoid concerns
about the endogeneity of previous royalties. However, as long as any characteristics specific
to municipalities with positive oil or coal royalties in 2004 are roughly constant during the
following seven years they should be picked up by the municipality fixed effect. Additionally,
the fact that new resource deposits are regularly found makes the case for the exogeneity of
geological indicators less clear. I standardize both the resource price indices and the 2004
royalty indicators to facilitate interpretation.
It is plausible that the world price of oil is not endogenously determined by local conditions in Colombian producing municipalities, as Colombia is a relatively small exporter of
oil. According to the US Energy Information Administration, Colombia is the 18th largest
exporter of oil with less than 1 % of world exports. The exogeneity assumption is slightly
less obvious in the case of coal, since Colombia is ranked sixth and its share of world exports
is approximately 6 %. However, Figure 4 shows that the variation in fuel prices can be accounted for to a large extent by the state of the world economy. Prices were on the rise in
the early years of the sample period, fell as a result of the global financial crisis around 2009
but then recovered in the final years of the sample.
The exclusion restriction in this case is that changes in the price of resources affect the
outcomes of interest in the municipalities where resources are extracted only through their
effect on royalties. This may be an unrealistic assumption to make as resource booms could
potentially affect municipalities where resources are extracted through other channels besides
the fiscal effect of royalties (Dube and Vargas, 2013; Caselli and Michaels, 2013; Asher and
Novosad, 2014).
To get a sense of the relative importance of some of these channels, in Table 5 I present
estimates of equation 4 using as dependent variables indicators for some of the most relevant
ones. In general, the results are somewhat heterogeneous across resources. This may have to
do with differing characteristics of oil and coal extraction in Colombia: oil extraction is more
capital intense, employs less local labour, has fewer linkages to other local industries and is
24
relatively more important for the local economy.
The first four columns look at other sources of revenue. The results in column 1 show that
oil price shocks are accompanied by reductions in property tax revenue. This contradicts the
prediction from the “fly-paper effect” (Hines and Thaler, 1995), but is consistent with “rentier
effect” theories, which suggest that governments respond to external revenue increases with
tax decreases to reduce accountability (Ross, 2001; McGuirk, 2013). Column 2 provides
evidence of a positive impact of coal price increases on the local economy of producing
municipalities, as the coefficients are positive and significant when the dependent variable is
business tax revenue. Additionally, increases in the prices of both resources seem to lead to
increases in “other revenue” (column 4), while only oil price increases are associated with
statistically significant increases in co-financing from the central government (column 3).
The increase in the “other revenue” category is not surprising since this category includes
the fees paid to municipalities that have oil pipes running through them, which includes
producing ones.
The last three columns of Table 5 investigate the possibility that commodity price shocks
lead to increased immigration or to more violence. If anything, the results in column 5 suggest
that the net effect on the municipality’s population is negative and quite small. This could
be the result of higher immigration combined with even higher mortality, but the results
in columns 6 and 7 provide only weak evidence suggesting that increased violence could be
the underlying cause. The estimates indicate that the murder rate falls contemporaneously
with both oil and coal price shocks, with the reduction reverting one year later in the case of
coal. Column 7 shows that coal price shocks seem to lead to a lagged and small increase in
conflict incidence, but there is no evidence of conflict incidence increasing as a result of oil
price shocks. These findings go against those in Dube and Vargas (2013), but this may be
due to the different time period being analyzed: while Dube and Vargas (2013) focus on the
1990s and early 2000s, when the guerrilla and paramilitary groups were on the rise, in the
years I study in this paper the demobilization of paramilitary groups had almost concluded
25
and the guerrillas were on the retreat.
In sum, the results in Table 5 suggest that commodity price shocks may have a positive
impact on the local economy besides the positive fiscal effect. This positive impact, evidenced
by the increase in business tax revenue, is reinforced by the fact that there does not seem
to be any significant change in migration, while the evidence on violence and conflict is
mixed. Acemoglu et al. (2013) provide additional evidence in support of the positive income
effect of oil price shocks and on the positive income elasticity of health expenditures. Under
these assumptions, my estimates using commodity price shocks as a source of variation will
most likely overestimate the effect of royalties on the social indicators of interest, working
against the hypothesis being tested.26 In the next section I further assuage concerns related
to the exclusion restriction by showing that the net fiscal impact is positive, large and almost
exclusively driven by the increase in royalties. I also show that the main results remain very
stable after adding the dependent variables of Table 5 as controls.
5.
Results
Table 6 shows estimates of equation 2. The dependent variable is specified in the header
of each column. Columns 1 and 2 show that, as expected, after a cadastral update both
cadastral values and property tax revenue shoot up dramatically. The point estimates in
column 1 show that the year the update comes into effect cadastral values rise by more than
5 million Colombian pesos (COP) per property, which is more than 50 % of the sample mean.
Similarly, the estimates in column 2 suggest that one year after the update comes into effect
property tax revenue is almost 4,400 COP per person higher, which is approximately 20 % of
the sample mean property tax take of around 21,000 COP per capita. This revenue increase
is followed by an increase in expenditure (mostly investment), as shown in columns 3 and 4.
Column 5 shows estimates of the effect of cadastral updating on the basic education
26
See Miller and Urdinola (2010) for evidence on the procyclicality of the infant mortality rate in Colombia,
based on coffee price shocks.
26
enrolment rate. I find a positive and significant effect that rises over time: contemporaneously
with the update the enrolment rate is 0.7 % higher, but two years later the magnitude of
the increase rises to 2 %. Although this increase corresponds to only 2 % of the sample mean
(88 %), it may still be economically significant as it is likely that these are students with a
high marginal cost of enrolment (under the plausible assumption of convex marginal cost).
Column 7 shows that the magnitude of the estimates drops when the 2006 update cohort
is included, although the coefficients are still statistically significant at conventional levels.
Including this cohort increases the number of municipalities for which an update is observed
from 32 % to 47 %, but for these additional updates it is not possible to estimate any impact
two years before the update, which could lead to a composition effect in the coefficient for
“update (t+2)”.
The results in column 8 show that if I restrict the sample to only include the municipalities with positive oil or coal royalties in 2004 the coefficients not only remain statistically
significant but their magnitude actually increases, relative to column 5. This finding assuages
concerns related to a potential lack of common support between municipalities with cadastral update and those endowed with oil or coal. It also provides evidence against selection
into updating to finance projects in education, as these resource-rich municipalities are less
likely to be strapped for cash.
Finally, column 6 shows estimates of equation 2 using the infant mortality rate as dependent variable. Although the point estimates are consistent with a decrease in the infant
mortality rate following a cadastral update, the magnitude of the estimated effect is quite
low (at the most a 0.4 % reduction after three years) and the coefficients are not statistically
different from zero.
I now turn to the effect of royalties on these same indicators. The first two columns
in Table 7 show estimates of equation 4 using royalties and total revenue, respectively, as
dependent variables. A comparison of the coefficients with those in Table 5 confirm that the
revenue increase resulting from commodity price increases is almost exclusively driven by
27
royalties. For example, a municipality with oil royalties one standard deviation above the
mean in 2004 experiences an increase of 29,400 Colombian pesos per capita in total revenue
when the price of oil is one standard deviation above its mean between 2005 and 2011. 95 %
of this increase (27,800 COP per capita) comes from extra royalties (83 % in the case of
coal). These results also suggest that commodity price shocks (particularly in the case of oil)
have a larger impact on local government revenue than cadastral updating. If we add across
rows in column 2 of Table 6 we can see that on average updating leads to about half as much
revenue (≈ 15,000 COP per capita), spread over four years, as a one standard deviation
increase in the price of oil. In the case of coal, the overall fiscal impact seems to be roughly
of the same magnitude.
The results in columns 3 and 4 then show that the additional revenue is spent almost
exclusively on investment with a one year lag. Although the point estimates seem to suggest
that the revenue elasticity of expenditure is larger in the case of coal, t-tests fail to reject (at
the 5 % level) the null that the lagged effect on expenditure is equal to the contemporaneous
effect on total revenue, as well as the null that the effect on expenditure is equal across
resources.
The results in column 5 of Table 7 do not provide evidence in support of a positive effect
of oil price shocks on the basic education enrolment rate. However, the estimates indicate
that a one standard deviation increase in the price of coal leads to a statistically significant
increase of 0.2 % in this indicator in municipalities with coal royalties one standard deviation
above the 2004 average. Not only is this effect of a smaller magnitude than the one from
additional property tax revenue documented in Table 6, but it also seems to last much less,
as the lagged coefficients are not statistically different from zero. This could be telling us
that the regression is picking up the effect of a temporary increase in income rather than one
from additional public spending, especially if we recall that it was also for coal that I found
a statistically significant effect of price shocks on business tax revenue in Table 5. However,
the coefficients are almost identical after I include controls, including business tax revenue,
28
in column 6.
Moving on to the infant mortality rate, the results in column 7 of Table 6 suggest that this
indicator is not affected by the increase in royalties resulting from commodity price shocks.
If anything, the estimates point towards infant mortality increasing, but the coefficients are
statistically and economically insignificant. Again, the results are very robust to the inclusion
of controls in column 8.
Overall, the results in this section suggest that an increase in the revenue of local governments in Colombia has a positive effect on the provision of education (as measured by the
enrolment rate) when it comes from taxes but not when it comes from oil or coal royalties,
even if the revenue increase is much larger in the latter case than in the former. The results
in Table 8 further illustrate this finding. They also address the posibility that royalties are
invested in projects with more long-term benefits.
Columns 1 and 2 show results based on a modified version of equation 2, in which I add
the dummies for the years following an update into a single post-update dummy and I also
include the interaction between this dummy and one for the 190 resource-rich municipalities
(positive oil or coal royalties in 2004). According to the estimates in column 1, a cadastral
update leads to an increase of about 3,800 COP per capita in the following years. This
increase seems to be a bit smaller in resource-rich municipalities but the difference is not
statistically significant. Column 2 indicates that the extra tax revenue leads to a 1.3 %
increase in educational enrolment, with no significant difference between municipalities with
oil or coal and those without.
The results in the remaining columns are based on a modified version of equation 4,
where I interact the indicator for resource abundance (resource-specific royalties in 2004)
with a full set of year dummies (omitting 2005). The results in columns 3 and 5 highlight
the difference in magnitude between the changes in the two sources of revenue analyzed.
Oil-rich municipalities always received at least as much royalties as in 2005 throughout the
sample period, but they received more than 65,000 COP per capita in extra royalties per
29
year between 2006 and 2008. In the case of coal-rich municipalities, there is some evidence of
a decrease in coal royalties during the early years of the sample, relative again to 2005, but
this is compensated by a royalty increase of 60,000 COP per capita in 2009. In general, the
variation in royalties matches the fluctuation in prices shown in Figure 4 for both resources.
Columns 4 and 6 confirm the very low return of royalties in terms of educational enrolment. Despite the large royalty inflows just discussed, the estimates show that the education
enrolment rate in 2011 is only 0.3 % higher than in 2005 in municipalities one standard deviation above the average in the 2004 oil royalty distribution. This difference is not statistically
significant. Things look only a bit better in the case of coal, where the enrolment rate is 0.6 %
greater in 2011 than in 2005. The specification employed allows us to see that the effect of
the positive shock of 2009 seems to last until the end of the sample period in 2011.
Finally, column 7 shows that the results are unaffected if I include all the explanatory
variables in the same regression. Assuming that the revenue increase from cadastral updating
lasts four years (adding up to approx. 15,000 COP per capita), I conclude that a $1 increase
in property tax revenue has an effect at least twice as large as a $4 increase in royalties.
6.
Conclusion
This paper tries to establish whether the source of revenue matters for government per-
formance. A political agency model with career concerns suggests that this may indeed be
the case: when revenue comes from the citizens’ pockets, they may be both more able or
more willing to monitor the functioning of government.
An empirical exercise based on panel data from Colombian municipalities between 2005
and 2011 provides evidence in support of the main prediction of this model: increases in
tax revenue have a positive effect on educational enrolment, while extra royalties from the
extraction of oil or coal have a much smaller effect, if any.
The findings of this paper have implications for important policy debates regarding de-
30
centralization, the natural resource curse and foreign aid. In particular, they provide quantitative evidence in support of the widely-held belief that external revenue has a very low
impact on public good provision. Future research must try to better understand the mechanism driving the documented difference between sources of revenue. The experimental work
in Paler (2013) and Martin (2014) constitutes early steps in this direction. One particular
topic of interest would be the study of different taxes with the objective of establishing which
characteristics (e.g. salience) are particularly important.
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36
Figure 1: Municipalities receiving oil or coal royalties in 2004
Note: The map shows the location of municipalities that received oil or coal royalties in 2004. Units in grey are excluded
from the sample. This includes municipalities whith their own cadastral agencies (Bogota, Medellin, Cali, Antioquia) and
non-municipalized territories.
37
Figure 2: Municipalities with urban cadastral update (2005-2011)
Note: The map shows the location of municipalities that updated their urban cadastre between 2005 and 2011. Units in grey are
excluded from the sample. This includes municipalities whith their own cadastral agencies (Bogota, Medellin, Cali, Antioquia)
and non-municipalized territories.
38
Figure 3: Urban cadastral updates per persidential term
Note: Colors correspond to presidential terms in Colombia. I assign to each administration its first full calendar year (since
presidential terms always start on August 7th) and the three following ones. Each term is then pushed back by one year to
account for the fact that updated cadastres only come into effect the following year.
Figure 4: Price indices for oil and coal
Note: The international US dollar prices of oil and coal are converted into 2004 Colombian pesos using the official exchange
rate from Banco de la República and the Consumer Price Index calculated by DANE. For both series an index is calculated
with 2004=1.
39
Table 1: Development indicators on which royalties must be spent
(1)
Target
Indicator
Infant mortality rate (h)
Net enrollment rate in basic education ( %)
Poor population with subsidized health insurance ( %)
Population with access to drinking water ( %)
Population with access to sewage ( %)
16,5
100
100
70
70
(2)
(3)
Mean Target met
(2005) ( % in 2005)
24,7
18
91,5
24
75,0
14
67,1
53
43,2
18
(4)
Target met
( % in 2011)
29
31
94
-
Note: Column 1 shows for each indicator the target rate that royalty-recipient municipalities must achieve. Column 2
shows the average of each indicator in 2005 among the 190 municipalities that received oil or coal royalties in 2004.
Columns 3 and 4 show the percentage of these municipalities that had achieved the target rate in 2005 and 2011,
respectively. Data on population with access to drinking water and sewage comes from the 2005 census and is only
available for this year.
40
Table 2: Summary statistics
Variable
Mean
Std. Dev.
Min.
Max.
N
0.885
0
0
2
0.025
0.169
1193.667
21
1
48
83.164
304.507
6419
6419
6419
678
6419
6419
88.824
15.896
0
0
0
0
32.898
0
0
0
0.301
0
0
0
6375.206
2129.607
605.247
1078.371
282.119
1137.991
5678.67
5065.493
4335.940
2098.317
9720.433
7763.297
7763.297
9313.628
6419
6419
6419
6419
6419
6419
6419
6419
6419
6419
6419
6419
6419
6419
18.7
9.237
244.4
64.099
6419
6419
0
0
0
0
159.985
1
459.311
1
6419
6419
6419
6419
1
0.202
0
1
0
0
0.001
0.01
18
1
1
16.538
1
1
0.930
0.997
771
771
771
771
771
771
771
771
0
0
0
1
4050.763
626.276
961
961
961
104.615
86.829
153.118
131.344
7
7
A. cadastral updating
Population (Thousands)
29.473
73.243
Years since last urban update
5.506
4.723
Urban update (Dummy)
0.106
0.307
Years since last urban update at time of next one
10.283
3.514
Cadastral valuation per capita (Millions of 2004 COP)
3.621
4.203
Number of properties
9.044
19.777
B. public finance
Total revenue per capita
546.769
427.232
Current revenue per capita
140.171
120.823
Property tax revenue per capita
20.656
27.214
ICA tax revenue per capita
16.066
47.956
Petrol tax revenue per capita
12.013
15.033
Non-tax revenue per capita
15.092
25.77
Capital revenue per capita
406.598
349.693
Natural resource royalties per capita
53.915
253.352
Transfers per capita
301.779
179.445
Co-financing per capita
24.315
75.56
Total expenditure per capita
585.295
491.999
Current expenditure per capita
84.915
111.734
Operating expenditure per capita
82.183
111.262
Investment per capita
500.38
443.307
C. development indicators
Net enrolment rate in basic education ( %)
88.078
17.199
Infant mortality rate (h)
22.629
8.265
D. central-government policies and conflict
New families with Familias en Accion CCT (per 10,000 inh.)
14.246
25.623
Uribe community council meetings (Dummy)
0.022
0.147
Murder rate (per 100,000 inh.)
33.458
42.154
Internal armed conflict (Dummy)
0.251
0.434
E. political characteristics
Number of candidates in mayoral election
4.296
1.865
Winner’s vote share in mayoral election ( %)
0.527
0.128
Winning in party in mayoral election different from incumbent (Dummy)
0.75
0.433
Number of candidates per seat in council election
4.005
2.197
Herfindahl-Hirschman Index of of council seats per party
0.178
0.116
Share of council seats from mayor’s party( %)
0.345
0.217
Winner’s vote share in presidential elections ( %)
0.438
0.2
Winner’s vote share in governor elections ( %)
0.462
0.218
F. oil and coal abundance
Oil or coal royalties in 2004 (Dummy)
0.198
0.398
Oil royalties per capita in 2004
23.559
170.212
Coal royalties per capita in 2004
2.315
29.835
G. commodity prices
International price of oil (Thousands of 2004 COP per barrel)
128.196
17.04
International price of coal (Thousands of 2004 COP per ton)
111.062
16.613
Note: The sample includes 961 municipalities for the period 2005-2011. Political characteristics in panel E are calculated using results from local
elections in 2003 and 2007 and from presidential elections in 2002 and 2006. All money variables are expressed in thousands of 2004 Colombian
pesos per capita, unless specified otherwise.
41
42
-1.581
[2.496]
2.140
[3.436]
3.785
[4.673]
3.826
[4.525]
7.127
[5.201]
-4.689
[5.370]
2.045
[5.444]
1.199
[6.764]
6.133
[9.435]
12.83
[10.33]
(2)
(1)+
Transfers
7.177
[8.085]
-0.696
[16.03]
9.962
[15.05]
21.36
[18.05]
13.90
[21.79]
(3)
(1)+Capital
Receipts
7.207
[8.041]
-0.903
[16.25]
9.400
[15.32]
22.15
[18.38]
17.31
[23.25]
(4)
(3)+Other
Revenue
-0.00505
[0.0151]
-0.00990
[0.0141]
-0.00777
[0.0123]
0.00250
[0.0141]
-0.00458
[0.0113]
(5)
Uribe visit
(dummy)
-0.213
[2.573]
1.473
[3.366]
-0.922
[2.002]
-0.918
[1.875]
-1.682
[2.030]
(6)
New CCT
recipients
0.855
[2.952]
-1.395
[2.676]
0.129
[2.636]
-1.244
[2.568]
1.134
[3.002]
(7)
Murder
rate
-0.0208
[0.0250]
0.00555
[0.0279]
-0.00169
[0.0288]
-0.00726
[0.0289]
0.0440
[0.0316]
(8)
Civil conflict
(dummy)
Observations
6,419
6,419
6,419
6,419
6,419
6,419
6,419
6,419
Number of municipalities
961
961
961
961
961
961
961
961
Dependent var. mean
44.78
346.55
451.37
466.47
0.02
14.25
33.46
0.25
Dependent variable in the header. All money variables are in thousands of 2004 Colombian pesos per capita. “Other
taxes” includes the business, petrol and vehicule registration taxes. “Capital receipts” includes transfers, royalties and
co-financing from the central government. “Other revenue” includes traffic fines and the profits from firms belonging to
the municipal government, among others. The variables “New CCT recipients” and “Murder rate” are per 1,000 inh. and
100,000 inh., respectively. All regressions include municipality and department-year fixed effects. The omitted category is
“update (t + 1)”. Standard errors clustered two-way by municipality and by department-year in brackets. *** p<0.01, **
p<0.05, * p<0.1
update (t-3)+
update (t-2)
update (t-1)
update (t)
update (t+2)
VARIABLES
(1)
Other
Taxes
Table 3: Economic and political characteristics around the time of a cadastral update
43
0.0292*
[0.0168]
-0.413***
[0.0334]
0.0340***
[0.0125]
0.0107
[0.0132]
0.0233
[0.0265]
0.0631***
[0.0106]
0.00593
[0.0126]
-0.00145
[0.0136]
0.0380**
[0.0166]
-0.415***
[0.0331]
(2)
0.105*
[0.0546]
0.0220*
[0.0117]
0.0257
[0.0169]
-0.423***
[0.0337]
0.349***
[0.0753]
-0.398***
[0.0885]
0.00470
[0.0139]
0.0171
[0.0129]
-0.0262
[0.0328]
-0.00967
[0.0227]
0.0130
[0.0157]
-0.0191
[0.0158]
0.349***
[0.0753]
-0.398***
[0.0882]
0.121
[0.130]
-0.0127
[0.0113]
0.346***
[0.0753]
-0.404***
[0.0893]
0.318***
[0.0751]
-0.442***
[0.0906]
0.00589
[0.0136]
0.0162
[0.0127]
-0.0355
[0.0294]
Dependent variable: Dummy (urban cadastre update)
(3)
(4)
(5)
(6)
(7)
-0.00708
[0.0195]
0.00803
[0.0141]
-0.0122
[0.0137]
0.318***
[0.0751]
-0.440***
[0.0905]
(8)
0.0785
[0.108]
0.0141
[0.0159]
0.318***
[0.0745]
-0.443***
[0.0898]
(9)
Observations
1,546
1,546
1,546
1,546
1,546
1,546
1,546
1,546
1,546
Number of municipalities
773
773
773
773
773
773
773
773
773
Election FE
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
Municipality FE
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Election x Dpt. FE
No
No
No
No
No
No
Yes
Yes
Yes
Dependent variable is a dummy equal to one if the urban cadastre was updated during the term. All explanatory variables are standardized
except for the dummy variables for new party in power and age of cadastre less than 3. Standard errors clustered two-way by municipality and
by department-term in brackets. *** p<0.01, ** p<0.05, * p<0.1
Winner’s vote share (governor)
Winner’s vote share (president)
Mayor’s party in council ( %)
HHI (party shares of council seats)
Candidates per seat (council)
Change of mayor’s party (dummy)
Winner’s vote share (mayor)
Candidates (mayor)
Age of cadastre ≤ 3 (dummy)
Age of cadastre
(1)
Table 4: Probability of cadastral updating and local political characteristics
44
-0.310***
[0.116]
-0.313**
[0.158]
0.0285
[0.0358]
-0.0254
[0.0351]
0.363
[0.407]
-1.126
[0.695]
0.668*
[0.367]
2.104**
[0.859]
(2)
Business
Tax
3.892**
[1.964]
-1.954
[1.977]
-1.246
[0.966]
0.0210
[0.391]
(3)
Co-financing
1.152***
[0.306]
0.587
[0.466]
0.0408
[0.0678]
0.384***
[0.0868]
(4)
Other
Revenue
-0.000157*
[9.18e-05]
-0.000260
[0.000232]
-8.98e-05
[0.000298]
-8.59e-05
[0.000287]
(5)
Log Total
Population
-0.378**
[0.182]
-0.0837
[0.151]
-0.584
[0.387]
0.624***
[0.205]
(6)
Murder
Rate
-0.00220
[0.00459]
-0.00529
[0.00414]
-0.00184
[0.00252]
0.0122***
[0.00259]
(7)
Civil Conflict
(dummy)
Observations
6,419
6,419
6,419
6,419
6,419
6,419
6,419
Number of codmpio
961
961
961
961
961
961
961
Dependent var. mean
20.66
16.07
24.31
15.09
29473
33.46
0.25
Mean 2004 oil royalties (s.d.)
21.41 (159.47)
Mean 2004 coal royalties (s.d.)
1.99 (27.70)
Mean 2005-2011 oil price (s.d.)
1.29 (0.16)
Mean 2005-2011 coal price (s.d.)
1.20 (0.17)
Dependent variable in the header. All money variables in 2004 Colombian pesos per capita. Explanatory variables are interactions between standardized prices (over the years 2005-2011) and standardized resource-specific
royalties in 2004 (over all municipalities). All regressions include municipality and department-year fixed effects.
Standard errors clustered two-way by municipality and by department-year. *** p<0.01, ** p<0.05, * p<0.1
coal
pricecoal
t−1 ∗ royaltiesi,2004
pricecoal
∗ royaltiescoal
t
i,2004
oil
priceoil
t−1 ∗ royaltiesi,2004
oil
priceoil
t ∗ royaltiesi,2004
VARIABLES
(1)
Property
Tax
Table 5: Other effects of commodity price shocks
45
(2)
Property
Tax
(3)
Investment
(4)
Total
Expenditure
(5)
(6)
(7)
Log Basic Log Infant Log Basic
Education Mortality Education
(8)
Log Basic
Education
506.8
0.0248
38.32
38.49
-0.00315
0.00122
-0.00839
-0.00222
[484.0]
[1.108]
[24.48]
[24.51]
[0.00512]
[0.00214]
[0.00567]
[0.0147]
update (t)
5,500***
3.614***
19.38
21.84
0.00703*
-0.000590
0.00394
0.00457
[881.2]
[1.146]
[22.37]
[22.81]
[0.00372]
[0.00176]
[0.00395]
[0.00694]
update (t-1)
4,598***
4.375***
56.75**
59.79**
0.0146***
-0.00193
0.0120**
0.0193**
[789.4]
[1.346]
[27.73]
[28.64]
[0.00484]
[0.00206]
[0.00532]
[0.00966]
update (t-2)
3,747***
4.191**
44.05**
45.88**
0.0219***
-0.00358
0.0157**
0.0281**
[685.5]
[1.906]
[19.90]
[20.62]
[0.00629]
[0.00298]
[0.00623]
[0.0130]
update (t-3)+
2,839***
2.350*
42.59
42.40
0.0209***
-0.00441
0.0137*
0.0266*
[571.4]
[1.259]
[33.09]
[34.11]
[0.00779]
[0.00456]
[0.00791]
[0.0148]
Observations
6,419
6,419
6,419
6,419
6,419
6,419
6,419
1,272
Number of codmpio
961
961
961
961
961
961
961
190
Dependent var. mean
10461
20.66
500.38
585.30
88.08
22.63
88.07
91.55
Sample
full
full
full
full
full
full
full
oil/coal
Update cohorts
2007-2009 2007-2009 2007-2009
2007-2009
2007-2009 2007-2009 2006-2009 2007-2009
Dependent variable in the header. All money variables are in thousands of 2004 Colombian pesos per capita, except property
values in column 1, which is per property. Education enrolment and infant mortality rates are in logs but their mean is reported
in level. All regressions include municipality and department-year fixed effects. The omitted category in all regressions is
“update (t + 1)”. Standard errors clustered two-way by municipality and by department-year in brackets. *** p<0.01, **
p<0.05, * p<0.1
update (t+2)
VARIABLES
(1)
Property
Value
Table 6: Cadastral updating, property tax revenue and public good provision
46
14.84**
[6.407]
4.820
[4.947]
27.77***
[3.681]
8.898**
[4.358]
17.88***
[5.251]
8.738
[7.454]
29.44***
[4.793]
4.207
[3.686]
(2)
Total
Revenue
11.13
[8.266]
28.26***
[9.583]
-19.12
[20.25]
16.03**
[8.061]
(3)
Investment
11.13
[8.351]
29.36***
[9.727]
-19.44
[20.31]
15.63*
[8.041]
(4)
Total
Expenditure
-0.000251
[0.000323]
-0.000627
[0.000485]
0.000692
[0.000721]
0.00247***
[0.000939]
0.00102
[0.00114]
-0.000180
[0.000571]
(5)
Basic
Education
(7)
Infant
Mortality
-0.000435
0.000127
[0.000397] [9.31e-05]
-0.000306 0.000299*
[0.000496] [0.000175]
0.000787
0.000127
[0.000704] [0.000317]
0.00237*** 0.000362
[0.000909] [0.000258]
0.000305
0.000182
[0.00109] [0.000196]
-0.000654
0.000441
[0.000561] [0.000304]
(6)
Basic
Education
0.000109
[0.000106]
0.000375*
[0.000196]
0.000116
[0.000317]
0.000333
[0.000253]
7.60e-05
[0.000188]
0.000374
[0.000304]
(8)
Infant
Mortality
Observations
6,419
6,419
6,419
6,419
6,419
6,419
6,419
6,419
Number of codmpio
961
961
961
961
961
961
961
961
Dependent var. mean
53.92
546.77
500.38
585.30
88.08
88.08
22.63
22.63
Controls
no
no
no
no
no
yes
no
yes
Mean 2004 oil royalties (s.d.)
21.41 (159.47)
Mean 2004 coal royalties (s.d.)
1.99 (27.70)
Mean 2005-2011 oil price (s.d.)
1.29 (0.16)
Mean 2005-2011 coal price (s.d.)
1.20 (0.17)
Dependent variable in the header. All money variables are in thousands of 2004 Colombian pesos per capita. Education enrolment and infant mortality rates are in logs but their mean is reported in level. Explanatory variables are interactions between
standardized prices (over the years 2005-2011) and standardized resource-specific royalties in 2004 (over all municipalities).
All regressions include municipality and department-year fixed effects. Controls in columns 6 and 8 include property tax
revenue, business tax revenue, co-financing, other revenue, log population, murder rate and conflict (dummy). Standard errors
clustered two-way by municipality and by department-year in brackets. *** p<0.01, ** p<0.05, * p<0.1
coal
pricecoal
t−2 ∗ royaltiesi,2004
coal
pricecoal
t−1 ∗ royaltiesi,2004
pricecoal
∗ royaltiescoal
t
i,2004
oil
priceoil
t−2 ∗ royaltiesi,2004
oil
priceoil
t−1 ∗ royaltiesi,2004
oil
priceoil
t ∗ royaltiesi,2004
VARIABLES
(1)
Royalties
Table 7: Commodity price shocks, royalties and public good provision
Table 8: Tax revenue, royalties and educational enrolment
VARIABLES
post-updatei,t
post-updatei,t ∗ D(oil/coal)i,2004
royaltiesoil
i,2004 x2006
royaltiesoil
i,2004 x2007
royaltiesoil
i,2004 x2008
royaltiesoil
i,2004 x2009
royaltiesoil
i,2004 x2010
royaltiesoil
i,2004 x2011
(1)
(2)
Property
Basic
Tax
Education
3.766***
[1.178]
-0.320
[1.657]
(3)
Royalties
(4)
(5)
Basic
Royalties
Education
(6)
Basic
Education
(7)
Basic
Education
0.00155
[0.00150]
-0.000447
[0.00153]
0.00263
[0.00214]
0.00765*
[0.00415]
0.00410
[0.00402]
0.00679**
[0.00327]
0.0142***
[0.00513]
0.00527
[0.0131]
-0.00226
[0.00375]
-0.000342
[0.00490]
0.00258
[0.00464]
0.00246
[0.00496]
0.00393
[0.00525]
0.00348
[0.00548]
0.00140
[0.00144]
-0.000911
[0.00158]
0.00228
[0.00212]
0.00733*
[0.00411]
0.00378
[0.00399]
0.00648**
[0.00320]
0.0136***
[0.00514]
0.00973
[0.0131]
79.03***
[26.69]
67.44***
[24.95]
116.1***
[35.71]
30.02
[29.50]
38.77
[30.42]
56.81*
[33.76]
royaltiescoal
i,2004 x2006
-0.00267
[0.00372]
-0.00100
[0.00504]
0.00201
[0.00477]
0.00240
[0.00513]
0.00388
[0.00542]
0.00343
[0.00567]
-24.22*
[13.96]
-21.08
[18.12]
4.466
[27.98]
60.68***
[9.459]
8.395
[6.316]
-8.528
[18.51]
royaltiescoal
i,2004 x2007
royaltiescoal
i,2004 x2008
royaltiescoal
i,2004 x2009
royaltiescoal
i,2004 x2010
royaltiescoal
i,2004 x2011
Observations
6,419
6,419
6,419
6,419
6,419
6,419
6,419
Number of municipalities
961
961
961
961
961
961
961
Dependent var. mean (level)
20.66
88.08
53.92
88.08
53.92
88.08
88.08
Dependent variable in the header. The variable “Basic Education” is in logs but its mean is reported in level. All
money variables in 2004 Colombian pesos per capita. Resource-specific royalties in 2004 standardized over all
municipalities. All regressions include municipality and department-year fixed effects. Standard errors clustered
by municipality in brackets. *** p<0.01, ** p<0.05, * p<0.1
47
ONLINE APPENDIX
Appendix A
Theoretical Appendix
In this appendix, I solve for the Perfect Bayesian Equilibrium in pure strategies using
backward induction. I first solve the model under Assumption 1 and prove Proposition 1.
I then show how the solution changes under Assumptions 2-4 and provide the proof for
Proposition 2.
Whoever wins the election at the end of the first period will solve the following problem
in the second period:
max E − γC(e2 )
e2 ≥0
Since γC(·) is an increasing function, the second-period mayor will set e?2 = 0 and will
get utility E. Therefore, the amount of public good provided will be g2? (θ2 ) = θ2 + µR,
which is an increasing function of the ability of the mayor in the second period. If the
citizen chooses a candidate with believed ability θ̂, her second period utility will then be
U (c2 , g2? (θ̂)) = U (1 − τ ηy, θ̂ + µR). Since U (·) is increasing in g2 , the incumbent will be
re-elected only if the citizen believes him to have higher ability than the opponent. That is,
if θ̂I ≥ m.
The citizen updates her beliefs on the incumbent’s ability based on the amount of firstperiod public goods (g1 ), her conjecture on the level of effort put in by the incumbent
(ê1 ), and the noisy signal on revenue (R̃). The problem that the citizen faces is that the
discrepancy between the observed amount of public goods and the amount she expected,
which I will label Z1 ≡ g1 − µR̃ − ê1 , is equal to the sum of the incumbent’s ability (θI )
R
and the noise term in the revenue signal (µR
t ). Given that θI and t are independent and
normally distributed random variables the solution to the signal extraction problem is:
θ̂I = E[θI |Z1 ] =
48
mh + Z1 hR
h + hR
(5)
This expression says that the posterior belief on the incumbent’s ability is a weighted average
of the prior m and the discrepancy Z1 , where the respective weights are given by the precision
of the prior and of the noise term, with hR ≡ T T+τµ2ηy h . As the signal gets noisier (hR → 0),
it becomes less informative and the posterior gets closer to the prior. Similarly, as the signal
gets more precise (hR → ∞) it perfectly reveals the incumbent’s ability and full updating
occurs. Equation 5 implies that the re-election condition simplifies to Z1 ≥ m.
From the incumbent’s perspective, his probability of re-election is:
pI (e1 ) = prob(g1 − µR̃ − ê1 ≥ m)
= prob(θ + µR + e1 − µR + µR
t − ê1 ≥ m)
= prob(θ + µR
t ≥ m + ê1 − e1 )
= prob(Z1 ≥ m + ê1 − e1 )
= 1 − ΦZ (m + ê1 − e1 )
where Φ is the cumulative distribution function of the normally distributed Z1 , which has
mean m and precision hZ ≡
h·hR
.
h+hR
The expression above tells us that the incumbent can
increase his probability of re-election by increasing the amount of effort (e1 ) relative to the
voter’s conjecture (ê1 ). Therefore, the problem solved by the incumbent in period 1 is:
max E − γC(e1 ) + (1 − ΦZ (m + ê1 − e1 )) βE
e1 ≥0
Assuming an interior solution, the first-order condition of this problem is:
γC 0 (e?1 ) = φz (m + ê1 − e?1 )βE
where φz is the probability density function of Z1 . Given that in equilibrium ê1 = e?1 the
first-order condition simplifies to:27
27
The equilibrium re-election probability is thus 1 − Φz (m) = 1/2 since m is the mean of the normally
distributed Z1 .
49
βE
γC 0 (e?1 ) = p
2π/hZ
(6)
I will now prove Proposition 1:
Proof. Using the implicit function theorem and noting that C(·) is a strictly convex function,
when we differentiate (6) with respect to τ ηy we obtain:
γ
From φZ =
∂ 2 C ∂e?1
∂φZ ∂hZ
=
βE
? 2 ∂τ ηy
∂hZ ∂τ ηy
∂e1
(7)
p
hZ /2π we can see that ∂φZ /∂hZ > 0. Using the definitions of hZ and hR
we find that
∂hZ
(µh)2 h T
>0
=
∂τ ηy
(h (T + τ ηy) + µ2 hT )2
Since all other terms on both sides of equation 7 are positive,
∂e?1
∂τ ηy
> 0. Hence, the overall
effect of a tax revenue increase on first-period public good provision, based on equation 1, is
given by
∂e?1
∂g1?
=µ+
>µ
∂τ ηy
∂τ ηy
where µ is the mechanical revenue effect.
Using again implicit differentiation on equation (6) but with respect to T we get
γ
∂ 2 C ∂e1
∂φZ ∂hZ
=
βE
2
∂e1 ∂T
∂hZ ∂T
(8)
The argument works the same as in the case of taxes, except that now
∂hZ
−(µh)2 h τ ηy
<0
=
∂T
(h (T + τ ηy) + µ2 hT )2
Since all the other terms on both sides of equation 8 are positive,
∂e?1
∂T
< 0. Therefore,
the overall effect of an increase in exogenous revenue on first-period public good provision is
50
given by
∂g1?
∂e?
∂g1?
=µ+ 1 <µ<
∂T
∂T
∂τ ηy
where again µ is the mechanical revenue effect.
I now analyze the model under Assumptions 2-4. The model is essentially unchanged:
the incumbent’s first-period effort is still determined by (6) with ∂e?1 /∂hZ > 0, except that
now hz =
h·h
.
µ2 h+h
If we substitute the public good production function and the citizen’s budget constraint
into her first-period utility function we can see that the problem the citizen solves is
max U1 = U (c1 + αg1 ) − K(m1 )
m1 ≥0
= U [(1 − τ η)y + α (θI + µ(τ ηy + T ) + e?1 (hZ ))] − K(m1 )
= U [y + (αµ − 1)τ ηy + αµT + αθI + αe?1 (hZ )] − K(m1 )
Assuming an interior solution, the optimal amount of citizen effort is implicitly defined
by the following first-order condition:
U 0 [y + (αµ − 1)τ ηy + αµT + αθI + αe?1 (hZ )]α
∂e?1 ∂hZ
λ = K 0 (m?1 )
∂hZ ∂h
(9)
We can now prove Proposition 2
Proof. Using the implicit function theorem we can differentiate both sides of (9) with respect
to τ ηy to obtain:
∂e?1 ∂hZ ∂m?1
∂m?1
∂e?1 ∂hZ 00
αλ
U (·) (αµ − 1) + α
λ
= K 00 (m?1 )
∂hZ ∂h
∂hZ ∂h ∂τ ηy
∂τ ηy
51
∂m?1
∂e? ∂hZ 00
U (·)(αµ − 1) =
⇒ αλ 1
∂hZ ∂h
∂τ ηy
K 00 (m?1 ) − α2 λ2
∂e?1 ∂hZ
∂hZ ∂h
2
!
U 00 (·)
(10)
Since U (·) is a strictly concave function while K(m1 ) is strictly convex, the LHS in equation 10 is positive and the term in brackets on the right is also positive. Hence, ∂m?1 /∂τ ηy > 0.
This implies, from equation 1, that the overall effect of an increase in tax revenue on public
good provision is given by
∂e? ∂hZ ∂m?1
∂g1?
=µ+ 1
λ
>µ
∂τ ηy
∂hZ ∂h ∂τ ηy
Using implicit differentiation on equation 9 but with respect to exogenous revenue (T )
yields:
∂e? ∂hZ 00
∂m?1
αλ 1
U (·)αµ =
∂hZ ∂h
∂T
K 00 (m?1 ) − α2 λ2
∂e?1 ∂hZ
∂hZ ∂h
2
!
U 00 (·)
(11)
Now the LHS in equation 11 is negative, while the term in brackets on the right remains
positive. Hence, ∂m?1 /∂T < 0. Using again equation 1, we can see that the net effect of an
increase in exogenous revenue on first-period public good provision is
∂e? ∂hZ ∂m?1
∂g1?
∂g1?
=µ+ 1
λ
<µ<
∂T
∂hZ ∂h ∂T
∂τ ηy
52