Antonio Acconcia, Giancarlo Corsetti and Saverio Simonelli. MAFIA AND PUBLIC SPENDING: EVIDENCE ON THE FISCAL MULTIPLIER FROM A QUASI-EXPERIMENT

MAFIA AND PUBLIC SPENDING: EVIDENCE ON
THE FISCAL MULTIPLIER FROM A
QUASI-EXPERIMENT
Antonio Acconcia, Giancarlo Corsetti and Saverio Simonelli
Bank of Estonia
Tallin, August 19 2014
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The main question
I Transmission of fiscal policy: How to recover ‘multiplier
effects’?
I Focus of the debate: Identify innovations to spending or taxation,
distinct from variations that are systematically related to the
business cycle.
I Reverse causation and anticipation effects may spuriously raise,
or lower, estimated multipliers (see e.g. Barro and Redlick 2011
and Ramey 2011).
I But suppose we can identify a truly exogenous shock. Its
transmission can be expected to be different across economic
‘environments’, reflecting policy, strucutal and cyclical factors.
I A single estimate of ‘the’ multiplier cannot provide a good
guidance to policymaker in all circumstances.
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The main question (cont.)
I Determinants of fiscal transmission...
I monetary policy: attitude of central bank towards inflation;
exchange rate regime; constraints on monetary policy (zero
lower bound)
I budget adjustment: current and prospective tax hikes and
spending cuts
I trade and financial openness openness, size of the economy
I cyclical conditions
I state of the financial (banking) system
I wealth distribution within the country; risk sharing across
border
I ...vary both across countries, but also over time (em see e.g.
Christiano et al. 2009, Corsetti et al. 2009, Leeper et al. 2009,
and Woodford 2010 among others).
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The main question (cont.)
I By way of example, the following theoretical example draws on
a 2010 paper on the transmission of spending shock across
exchange rate regimes joint with Keith Kuester and Gernot
Mueller.
I To connect with the rest of the talk, I focus on the effect of a
contraction in spending.
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Model
I Standard new Keynesian small open-economy model
I Imperfectly competitive firms produce country specific varieties
I Pricing in producer currency, prices sticky
I Domestic consumption biased towards home goods
I Government spending falls on home goods
I Complete markets versus incomplete markets/limited
participation (a fraction of households () are without access to
asset market)
I Policies
I Monetary policy: interest rate feedback rule or peg
I Lump-sum taxes respond to spending and debt
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The transmission mechanism in the New Keynesian NK framework
I Well known that in NK model consumption demand is driven by
the long-term rate (real return on a bond of infinite duration).
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I In standard specification with separable preferences, solving the
Euler forward, holding the expectations hypothesis:
ct =
1

Et
1X
s=0
(rt+s t+1+s)
| {z }
zt
; (1)
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ct =
1

Et
1X
s=0
(rt+s t+1+s)
| {z }
zt
; (1)
I The long-term rate in real terms zt synthesizes the whole path of
current and future expected inflation and policy rates: it so
depends on the fiscal and monetary mix at each point in time.
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ct =
1

Et
1X
s=0
(rt+s t+1+s)
| {z }
zt
; (1)
I The long-term rate in real terms zt synthesizes the whole path of
current and future expected inflation and policy rates: it so
depends on the fiscal and monetary mix at each point in time.
I Posit an autoregressive process for G and assume a fiscal
contraction.
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I Under Taylor rule and floating rates, negative inflation and policy
rates throughout the relevant horizon cause a negative response
in long-term real rates, driving a positive consumption response
by agents who participate in the financial markets. Despite 30
percent of population is hand-to-mouth consumers, the output
response is small.
I Taylor coefficient matters quantitatively though = degree of
monetary accommodation (not shown).
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Transmission of spending contraction under floating exchange rates
0 10 20 30
0
−0.5
−1
−1.5
Government spending
limited
no limited
0 10 20 30
0
−0.5
−1
Output
0 10 20 30
0.3
0.2
0.1
0
−0.1
Private consumption
0 10 20 30
0
−0.01
−0.02
−0.03
−0.04
Real interest rate (short)
0 10 20 30
0.4
0.2
0
−0.2
−0.4
Real interest rate (long)
0 10 20 30
0
−0.05
−0.1
Inflation
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What about under a peg? A key analytical characterization
I Under a peg, by PPP lim t ! 1Pt = P, implying
P1t
=0 t = 0.

What about under a peg? A key analytical characterization (cont.)
I To the extent that initial inflation is small, so is the response of
consumption of unconstrained agents.
I The multiplier is magnified by the response of hand-to-mouth
consumer.

Transmission of spending contraction in a monetary union with limited
participation
0 10 20 30
0
−0.5
−1
−1.5
Government spending
limited
no limited
0 10 20 30
0
−0.5
−1
−1.5
Output
0 10 20 30
0.2
0
−0.2
−0.4
−0.6
Private consumption
0 10 20 30
0.06
0.04
0.02
0
−0.02
Real interest rate (short)
0 10 20 30
0
−0.05
−0.1
−0.15
−0.2
Real interest rate (long)
0 10 20 30
0.1
0.05
0
−0.05
−0.1
Inflation
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A resolution to the ’Walters critique’
I As seen above, under a credible peg, long-term real rates must
increase (and consumption fall) with impact inflation.
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I This is so, even if short-term real rates move the other way
around.
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around.
I In its well known critique of common currencies, Sir Walters
claims that a peg is destabilizing, because an increase in inflation
lowers real interest rates.
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around.
I He simply assume that short- and long-rates move together,
which cannot be true in a credible monetary union.
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around.
I By the dynamic of inflation, negative real rates in the short run
are followed by positive rates in the medium run (all in
deviations from steady state).
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around.
I By the dynamic of inflation, negative real rates in the short run
are followed by positive rates in the medium run (all in
deviations from steady state).
I In our experiment, negative and positive rates offset each other as
regards their effects on the long-term real rate on impact.
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Take home for the rest of the talk
I In a standard NK model of a small open economy in a currency
union (a credible fixed exchange rate system), output multiplier
effects are around 1 on impact.
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I With limited participation, the impact multiplier is 1.3.
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I By the way, note that fiscal policy is effective under a float.
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I By the way, note that fiscal policy is effective under a float.
I This ends my example. Now, back to the main question.
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How to recover the multiplier?
How to recover “the multiplier”?
1. Identify innovations to spending or taxation, distinct from
variations that are systematically related to the business cycle.
2. Control for determinants of transmission mechanism.
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This paper
I We address both dimensions of empirical analyses of the
multiplier by relying on a quasi-experiment setting using
sub-national data that enable us to:
1. identify temporary but sizeable variation in public spending
that are exogenous to the cyclical conditions of the
economy;
2. analyze their transmission controlling for monetary and
budget policy.
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This paper
I We address both dimensions of empirical analyses of the
multiplier by relying on a quasi-experiment setting using
sub-national data that enable us to:
1. identify temporary but sizeable variation in public spending
that are exogenous to the cyclical conditions of the
economy;
2. analyze their transmission controlling for monetary and
budget policy.
I Identification Strategy
1. We instrument spending by exploiting an Italian law, which
causes sudden, large spending contractions unrelated to the
cyclical economic conditions of the local economy.
2. We estimate the output multiplier of (large contractions in)
public expenditure at provincial level in Italy, controlling
for both common cyclical movements and common policy
impulses at national level. By the characteristics of Italian
fiscal federalism, the above temporary contractions have
virtually no effect on tax burden.
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Preview of results
I Our point estimates suggest that, unless spending contractions
are compensated by monetary expansions or matched by lower
taxes, their effects on output are larger than the amount of the
cut.
I Our IV estimate of the impact spending multiplier is 1:2,
significantly larger than zero.
I Under the maintained hypothesis that lagged values of spending
are exogenous to current value added, dynamic effects raise our
point estimate to around 1:8.
I However, in our preferred model specification, we cannot reject
the hypothesis that the multiplier is less than, or equal to one at
standard confidence levels.
I Fundamental insights on the transmission mechanism underlying
our results is provided by theoretical models already discussed.
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Related evidence
I Together with the present study a number of works have recently
delved into the analysis of multiplier effects using sub-national
data.
I Large multipliers, 1:5 2, by Nakamura and Steinsson (2010),
Serrato and Wingender (2010), Shoag (2010)
I Evidence, however, not supported by Clemens and Miran (2010)
and Kraay (2011)
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Advantages of using local data
1. Measure the effect of spending controlling for common national
components—whose variations are in some cases predictable
and endogenous to economic cycle.
Time dummies control for
I nation-wide cyclical movements.
I monetary stance with common effects.
2. To the extent that tax changes have a negative impact on output,
the omission of this variable induces a downward bias in the
estimate of the spending multiplier.
I Local setting may be less vulnerable to such criticism, as in
many countries tax rates are to large extent set at national
level.
3. With some luck, quasi-experiment setting.
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The empirical model
yi;t yi;t1
yi;t1
= i + t +

gi;t gi;t1
yi;t1
+
Xi;t + vi;t
Yi;t = i + t +

Gi;t +
Xi;t + vi;t
where for each province i (95 Italian provincesX10 years=950
observations).
I yi is per capita value added
I gi is the per capita infrastructure investment spending
I t is a year fixed effect
I i is a province fixed effect
I Xi;t denotes covariates (discussed below)
The coefficient

is the contemporaneous government spending
multiplier.
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Instrumenting Changes in Public Spending
I Despite advantages of using local information, OLS estimates of
the multiplier subject to standard criticisms, e.g.
1. Spending on infrastructures is planned years before it
actually takes place. A failure to account for anticipation
effects likely to bias results. (Ramey, 2009).
2. The government may systematically allocate funds in
response to local developments, in ways that are not
accounted for by province-fixed effects.
I Need a good instrument for unexpected variations in public
spending exogenous to local economic conditions.
I We rely on a specific law by the Italian government, mandating
compulsory administration of local municipalities on evidence of
mafia infiltration.
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The institutional setting
I Italian penal code (articles 416-bis and 416-ter) recognizes the
specific nature of mafia crimes
I Specific to mafia is the use of intimidation, associative ties
and omerta’ (condition of silence), to acquire direct or
indirect control of otherwise legal economic activities,
especially in the area of provision of public services and
public investment.
I To pursue their goals, Mafia-type associations have specific
interests in influencing the results of electoral competition,
and obtain effective control over public tenders.
I Because of their sheer size of public works under the control of
local administration, these have become one of the most lucrative
businesses for mafia associations, generating profits comparable
to those from extortions and selling drugs (see Relazione, 2000)
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The institutional setting (cont.)
I The Italian Legislator gave the central government the power to
remove elected officials in a city council on evidence of mafia
infiltration, and/or of decisions determined by the mafias (D.L.
31/05/1991 n. 164).
I Upon their removal, the central government appoints three non-elected,
external commissioners, ruling the municipality for a
period of 18 months.
I As of today, the number of dismissed city councils is 199.
I Concentration in the provinces of Naples, Palermo, Reggio
Calabria, and Caserta (2008).
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The institutional setting (cont.)
Napoli 44 Palermo 23 Reggio C. 23 Bari 5
Caserta 22 Catania 9 Catanzaro 7 Lecce 2
Salerno 5 Trapani 5 Vibo V. 5
Avellino 3 Caltanisetta 5 Crotone 3
Benevento 1 Agrigento 4
Messina 2
Ragusa 1
Campania 75 Sicily 49 Calabria 38 Puglia 7
Note: The table reports the number of municipalities put under the adminis-trations
of external commissioners because of relationships between elected
administrators and the mafias. Time period 1991-2008.
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An instrument you can’t refuse
I In our sample (1990-99), we have 109 cases of city councils put
under compulsory administrations. Aggregating them by
province, we obtain 45 observations.
I The external administrators appointed by the central government
have the power to suspend financial flows into local public work.
I Public projects are started again only after investigation and
scrutiny of previous tender procedures and decisions.
I The size of spending contractions is, on average, .5 percent of
value added.
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Mean Difference Test
Log-difference Log-difference Percent of GDP Percent of GDP
Difference -0.220*** -0.228** -0.555** -0.650*
[-3.63] [-3.21] [-2.61] [-2.45]
Control group 0.0584*** 0.0666 0.120** 0.215
[4.70] [1.72] [3.10] [1.32]
N 950 180 950 180
Note: The table shows results of mean difference tests relative to changes in public
infrastructure investment. In the second and fourth columns of results we restrict to
provinces characterized by at least one case of local government dismission during the
period analyzed. Data are annual from 1990 through 1999 at Italian province level. The
t-statistic is reported in brackets: *p 0:05, **p 0:01,***p 0:001
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The size of the spending cuts
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Randomness
I Is the instrument variation systematically related to local
economic activity?
I The procedure leading to a dismissal of a city council because of
mafia infiltration is started by the prefetto on police reports on
the activities of the mafia in the municipality.
I The police evidence is produced in the course of investigations
on crimes often unrelated to the control of local public work.
I Note that city council dismissals are not prompted by
indicators of administrative inefficiency in the procurement
procedures.
I A check looking at growth pattern (relative to average) next.
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Randomness (cont.)
Table: Randomness of council dismissals
0 0 0 or 0
t 1 t 2 1=3 1=6 1=2
t 1 t 2 t 3 1=9 0 8=9
Note: For two and three years before council dismissals
happened, the table reports the proportion of cases with
provincial growth rates always above the national average
(column labeled with 0), always below the national
average (column labeled with 0), without a constant
sign (last column).
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The instruments
I The first instrument (S1), equals the number of municipalities
put under compulsory administration, provided that the official
decree by which a city council is dismissed is formalized in the
first semester of the year.
I The second instrument (S2) equals the number of municipalities
put under compulsory administration in any given year, if the
average number of days spent in such state is less than 180, and
zero otherwise.
I In our baseline model, we instrument Gi;t entering S1
contemporaneously and S2 lagged one period. Thus, the first
stage regression of our baseline specification is
Gi;t = i + t + 1S1i;t + 2S2i;t1 +
Xi;t + ei;t
I The estimates of the coefficients of both instruments are always
negative, as expected, and highly statistically significant.
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Baseline Specification
I The presentation to follows progressively enlarges the set of
instruments and controls.
I All regressions include:
I controls for unemployment (important differences across
regions);
I controls for intensity of police investigations (more below).
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Baseline Specification (cont.)
(1) (2) (3) (4)
G(t)
1.17*
1.21* 1.29* 1.31*
[2.11] [2.30] [2.55] [2.54]
Y(t-1) -0.12 -0.13* -0.12
[-1.92] [-1.97] [-1.92]
Y(t-2) -0.01 -0.00 -0.00
[-0.11] [-0.07] [-0.07]
Council-dismissal(t-2) -0.30
[-1.73]
[-0.49]
time effects YES YES YES YES
provincial fixed effects YES YES YES YES
controls for mafia investigation YES YES YES YES
unemployment rate proxies YES YES YES YES
number of instruments 2 2 2 4
First stage F-test 9.20 9.78 10.48 6.35
(p-value) (0.00) (0.00) (0.00) (0.00)
N 950 950 950 950
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I To address potential problems from serially correlated errors we
include two lags of the left-hand-side variable among the
regressors.
I Only the first lag is significant, but barely so.
I The impact of adding these lags is negligible: there is hardly any
change in the point estimate and the significance of

.
I The inclusion of the lagged dependent variable among the
regressors brings forward dynamic effects of the multiplier.
I Net estimate is 1.14 (the ratio between the estimate of

and 1
minus the coefficient on Y (t 1)).
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(1) (2) (3) (4)
G(t) 1.17*
1.21* 1.29*
1.31*
[2.11] [2.30] [2.55] [2.54]
Y(t-1)
-0.12 -0.13*
-0.12
[-1.92] [-1.97] [-1.92]
Y(t-2)
-0.01 -0.00
-0.00
[-0.11] [-0.07] [-0.07]
[-1.73]
[-0.49]
(p-value) (0.00) (0.00) (0.00) (0.00)
N 950 950 950 950
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I We add as further controls two lags of “Council-dismissal”(at
t 2 and t 3)—recording the total number of municipalities
put under compulsory administration by province year
I The estimated coefficient for

is slightly higher relative to the
specification in the first column,
I However, the two lags of “Council-dismissal” are not statistically
significant .
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(1) (2) (3) (4)
G(t) 1.17* 1.21*
1.29*
1.31*
[2.11] [2.30] [2.55] [2.54]
Y(t-1) -0.12 -0.13* -0.12
[-1.92] [-1.97] [-1.92]
Y(t-2) -0.01 -0.00 -0.00
[-0.11] [-0.07] [-0.07]
Council-dismissal(t-2)
-0.30
[-1.73]
Council-dismissal(t-3)
-0.08
[-0.49]
(p-value) (0.00) (0.00) (0.00) (0.00)
N 950 950 950 950
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I We now use the two lags of ‘council-dismissal’ (at t 2 and
t 3) to enlarge the set of instruments, rather than as controls.
I Since the compulsory administration is designed to last 18
months, it may have effects on three consecutive calendar years.
I Our estimate of the coefficient

is substantially unaffected
relative to column (3).
I In our overidentified models, however, the first-stage F-statistic
for the model with 4 instruments halves in size.
I Note nonetheless that, as for the other regressions with 2
instruments , the Hansen Jstatistic implies a p-value around 0:3,
suggesting that the instruments are uncorrelated with the error
term.
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(1) (2) (3) (4)
G(t) 1.17* 1.21* 1.29*
1.31*
[2.11] [2.30] [2.55] [2.54]
Y(t-1) -0.12 -0.13* -0.12
[-1.92] [-1.97] [-1.92]
Y(t-2) -0.01 -0.00 -0.00
[-0.11] [-0.07] [-0.07]
[-1.73]
[-0.49]
number of instruments 2 2 2
4
(p-value) (0.00) (0.00) (0.00) (0.00)
N 950 950 950 950
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I Add two lags of public investment expenditure to our set of
covariates.
I In both model specifications reported in the table, the coefficient
of the first lag is statistically and economically significant, with a
point estimate which is about one half that of the impact
coefficient.
I Under the assumption that spending is predetermined to current
output, this effect should be added to our IV estimate of the
multiplier.
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(1) (2)
G(t) 1.44** 1.67**
[2.67] [3.13]
Y(t-1) -0.16** -0.17**
[-2.62] [-2.65]
Y(t-2) -0.02 -0.01
[-0.28] [-0.24]
[-0.96]
[-0.44]
G(t-1)
0.74** 0.84***
[2.93] [3.36]
G(t-2) 0.19 0.22
[1.65] [1.82]
time effects YES YES
provincial fixed effects YES YES
controls for mafia investigation YES YES
unemployment rate proxies YES YES
number of instruments
2 4
First stage F-test 9.84 4.93
(instruments validity) (0.00) (0.00)
N 950 950
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I In our preferred specification (with 2 instrument), controlling for
monetary and budget policy:
I the estimate of the net multiplier effect of Gt is 1:24
I adding up this to the coefficients relative to the one-year
lagged spending changes, the point estimate of the overall
multiplier is as high as 1:87.
I Nonetheless, we are not able to reject the null hypothesis

1
I cannot exclude the possibility that the contraction in public
spending is marginally offset by a simultaneous increase in
private demand.
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The influence of individual provinces
I It is plausible that some episodes exerts a stronger influence on
our estimates.
I We address this issue, by analyzing the extent to which our
results are sensitive to the exclusion of any particular province
from the analysis.
I we report results for the most comprehensive specifications of
our model with 2 instruments, excluding one of the following
provinces in turn: Napoli, Caserta, Palermo, Catania, Salerno,
Bari, Reggio Calabria.
I None of these provinces is a crucial driver of our estimates.
I The point estimates of

are in the range 1:26-1:50, while those
of coefficient of the lagged public spending ranges from 0:67 to
0:77 (with the proportion between the two remaining roughly
constant).
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The influence of individual provinces (cont.)
NA CE PA CT SA BA RC
G(t) 1.50** 1.26* 1.40* 1.27* 1.40* 1.43** 1.28**
[2.61] [2.51] [2.53] [2.14] [2.53] [2.70] [2.60]
Y(t-1) -0.16** -0.16** -0.16* -0.16** -0.16* -0.16** -0.13*
[-2.60] [-2.75] [-2.56] [-2.67] [-2.55] [-2.58] [-2.13]
Y(t-2) -0.01 -0.02 -0.02 -0.02 -0.02 -0.01 -0.04
[-0.22] [-0.36] [-0.28] [-0.39] [-0.31] [-0.20] [-0.77]
Council-dismissal(t-2) -0.11 -0.27 -0.16 -0.12 -0.17 -0.17 -0.31
[-0.37] [-1.38] [-0.74] [-0.62] [-0.81] [-0.78] [-1.88]
Council-dismissal(t-3) -0.09 -0.11 -0.05 -0.02 -0.10 -0.06 -0.04
[-0.38] [-0.59] [-0.29] [-0.13] [-0.58] [-0.33] [-0.27]
G(t-1) 0.77** 0.67** 0.73** 0.67* 0.73** 0.74** 0.68**
[2.84] [2.81] [2.92] [2.45] [2.82] [2.95] [2.97]
G(t-2) 0.19 0.16 0.18 0.16 0.18 0.18 0.16
[1.65] [1.45] [1.62] [1.42] [1.65] [1.63] [1.54]
time effects YES YES YES YES YES YES YES
provincial fixed effects YES YES YES YES YES YES YES
controls mafia YES YES YES YES YES YES YES
unemp. proxies YES YES YES YES YES YES YES
number of instruments 2 2 2 2 2 2 2
First stage F-test 10.94 14.21 8.01 8.94 7.91 9.78 7.97
(p-value) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
N 940 940 940 940 940 940 940
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Cross-border effects
I Cross-border effects of public spending, if any, can have a vastly
different nature.
1. Since our provinces are very open economies, part of the
contraction in demand in one municipality may “leak” into
nearby areas. An estimate of the total multiplier effect should
include these spillovers.
2. A positive correlation in the output response across provinces
may also correspond to cases in which the public work
suspended by the commissioners extends across provincial
borders. In this case, including cross-border effects would
overstate the multiplier.
3. In response to a localized spending shock, it is possible that
production factors relocate. The estimate would be biased
upwards.
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Cross-border effects (cont.)
I We carry out an analysis of cross border effects of local spending
in two ways.
I we estimate cross-province effects within each region by
extending the set of regressors.
I we aggregate observations by groups of 2/3 provinces at a
time.
I To extend the regressors
I We consider the variable SGi;t =
Sgi;tSgi;t1
Syi;t1
, where Sgi;t is
the per-capita investment across provinces which are part of
the same region excluding province i itself, and the variable
Syi;t1 is accordingly defined.
I We then enter SGi;t1 interacted with Gi;t1 to allow for the
possibility that the effect of local spending reflects either
complementarity between spending in adjacent areas or
substitutability.
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I The coefficients of the ’spillover’ variable and its lag are not
significantly different from zero.
I Adding the interaction term, the point estimates of the
coefficients of contemporaneous and lagged spending are only
slightly affected. The coefficient of the interaction term is
marginally significant, with a positive sign—lending support to
the hypothesis of complementarity.
I Aggregating either two or three adjacent provinces in a single
unit, the coefficients attached to Gi;t and Gi;t1 increase a bit—
providing further evidence that, if anything, the spillover effects
end up adding to the local effect of spending.
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(1) (2) (3)
G(t)
1.38* 1.35** 1.58**
[2.25] [2.59] [3.07]
Y(t-1) -0.17** -0.16** -0.19**
[-2.75] [-2.71] [-2.95]
Y(t-2) -0.01 -0.01 -0.00
[-0.24] [-0.22] [-0.08]
Council-dismissal(t-2) -0.19 -0.20 -0.15
[-0.97] [-1.03] [-0.91]
Council-dismissal(t-3) -0.07 -0.07 -0.14
[-0.43] [-0.43] [-1.11]
G(t-1) 0.70* 0.68** 0.88**
[2.50] [2.94] [3.29]
G(t-2) 0.17 0.20 0.22
[1.53] [1.83] [1.30]
SG(t)
0.07
[0.38]
SG(t-1)
0.20
[1.06]
G*SG(t-1)
0.22**
[2.67]
First stage F-test 6.93 9.75 14.44
(instruments validity) (0.00) (0.00) (0.00)
N 950 950 410
58 / 74

Exclusion restriction
I Most likely reasons why the exclusion restriction may fail are
linked to circumstances implying a systematic negative
relationship between our instrument and the average level of the
dependent variable at province level. Provinces with lots of
mafia activity may be expected to grow slowly and are likely to
be under mafia investigation. The inclusion of province
fixed-effects, however, takes care of all these issues.
I Nonetheless council dismissals may still be detrimental for
economic activity via channels other than the multiplier of public
spending.
59 / 74

Exclusion restriction (cont.)
I Two relevant channels:
I Impact on economic activity of an increase in the intensity
of police investigation, likely to be associated with council
dismissals.
I Ambiguous effects
I We do control for.
I A general reduction in the productivity of local bureaucracy
because of the regime of compulsory administration.
60 / 74

Do council dismissals per se affect output?
I City councils may be dismissed also for reasons different from
mafia infiltration, and without necessarily implying a freezing of
spending on public work.
I If council dismissals are per se shocks to government, they
should have a negative effect on output even when they do not
imply a contraction in spending.
I Institutional and econometric evidence does not support this
possibility
I In what follows, we include as regressors in the model, the
number of city council dismissals for reasons unrelated to mafia
infiltration (and not associated with spending cuts).
61 / 74

Do council dismissals per se affect output? (cont.)
(1) (2) (3) (4) (5)
G(t) 1.43** 1.46** 1.44** 1.63** 1.46**
[2.63] [2.62] [2.70] [2.61] [2.70]
Y(t-1) -0.16** -0.16** -0.16** -0.17** -0.16**
[-2.62] [-2.61] [-2.63] [-2.63] [-2.64]
Y(t-2) -0.02 -0.01 -0.02 -0.01 -0.01
[-0.29] [-0.27] [-0.29] [-0.20] [-0.25]
G(t-1) 0.74** 0.75** 0.74** 0.82** 0.75**
[2.91] [2.87] [2.95] [2.81] [2.95]
G(t-2) 0.18 0.19 0.19 0.21 0.19
[1.65] [1.63] [1.66] [1.65] [1.66]
Resignation(t) 0.01
[0.17]
Resignation(t-1) -0.00
[-0.06]
Election(t) 0.04
[0.37]
Election(t-1) -0.03
[-0.28]
Budget-No confidence vote(t) 0.04
[0.29]
Budget-No confidence vote(t-1) -0.03
[-0.20]
Others(t) 0.64*
[2.11]
Others(t-1) 0.19
[0.59]
Province council(t) -0.56
[-1.21]
Province council(t-1) 0.16
[0.34]
62 / 74

Further results
Controlling for North-South differences
I One potential issue is that the mafia-related compulsory
administrations are mainly in the South.
I Different structural, institutional and policy features may in
principle affect the transmission of fiscal shocks (beyond what is
captured already by our controls).
I When we exclude observations from the North, the multiplier
remains the same of the basic specification.
63 / 74

Further results (cont.)
South Drop t Drop i OLS
G(t)
1.45**
1.78** 1.54** 0.20**
[2.69] [3.16] [2.84] [3.16]
Y(t-1) -0.29** -0.11 -0.07 -0.12*
[-3.03] [-1.81] [-1.05] [-2.15]
Y(t-2) -0.00 0.06 0.06 -0.03
[-0.03] [0.97] [1.01] [-0.55]
Council-dismissal(t-2) -0.21 -0.09 -0.20 -0.28
[-1.07] [-0.47] [-1.03] [-1.84]
Council-dismissal(t-3) -0.02 0.06 -0.07 -0.14
[-0.14] [0.27] [-0.45] [-0.99]
G(t-1) 0.76** 0.75* 0.71** 0.23***
[2.99] [2.49] [2.90] [3.31]
G(t-2) 0.15 0.12 0.13 0.03
[1.23] [1.03] [1.24] [0.47]
time effects YES NO YES YES
provincial fixed effects YES YES NO YES
First stage F-test 8.91 10.54 10.12
(p-value) (0.00) (0.00) (0.00)
N 340 950 950 950
64 / 74

Antonio Acconcia, Giancarlo Corsetti and Saverio Simonelli. MAFIA AND PUBLIC SPENDING: EVIDENCE ON THE FISCAL MULTIPLIER FROM A QUASI-EXPERIMENT

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