Revenue-Side Vs Spending-Side Fiscal Adjustments Evidence from Italian Municipalities

Revenue-Side Vs Spending-Side Fiscal Adjustments Evidence from Italian Municipalities Luigi Marattin - University of Bologna Tommaso Nannicini Bocconi University Francesco Porcelli SOSE SpA University of Rome- La Sapienza 9 May 2017

SUMMARY 1. MOTIVATION AND OVERVIEW 2. LITERATURE REVIEW 3. SOME THEORETICAL INSIGHTS 4. EMPIRICAL ANALYSIS 4.1. Preliminary analysis 4.2. The data 4.3. The model and main results 5. CONCLUSIONS AND NEXT STEPS

OUR QUESTION We are concerned with the composition of the fiscal adjustment at the local level. When receving a trasfer cut from the central government, does a municipality meet its budget constraint by acting on the revenue side or the expenditure side?

1. Motivation and overview The reaction of local authorities to central governments spending cuts has been only marginally explored so far both by the theoretical and empirical literature This paper aims at closing some of the literature gaps providing a theoretical framework and an empirical analysis showing how local authorities react to a contraction of intergovernmental grants.

We sketch a theoretical framework whose aim is simply to gain some insights on the conditions under which local authorities are more prone to increase local taxes rather than reducing local expenditure to cope with the grants contraction No connection with the empirical model. The empirical analysis relies on new and unique dataset of Italian municipalities over a period of three years from 2010 to 2012.

Italy provides a good case-study for the empirical analysis due to the intense program of intergovernmental grants reduction implemented since 2010 (8,43 billions from 2010 to 2015) Moreover, Italian data are particularly useful because of the presence of a discontinuity in the allocation of the grants reduction: municipalities below 5000 inhabitants have been permanently exempted from the spending cut of 2.5 bln implemented by the central government in 2010 (DL 78/2010).

Our identification strategy allows us to obtain standard difference in discontinuities estimates of the Italian municipalities fiscal adjustment behaviour. By doing so, we provide a good measure of the causal relationship between central and local fiscal decisions. Final results show that Italian municipalities reacted to the contraction of inter-governmental grants mainly by increasing local taxes rather than by reducing local expenditure

Macro Composition (of fiscal adjustment) matters. Alesina et al (2015, JIE): on average, the output costs of expenditurebased fiscal adjustments are close to zero. Inter-governmental Skidmore (1999, Public Choice) on US: imposing tax limitations tends to increase unconstrained revenue sources rather than reduce spending Gong and Zue (2002, JEDC): theoretical framework On Italy: Gennari and Messina (2014, Int.Tax.Pub.Fin): flypaper effect Political economy 2. Related literature Political cycle: Brender (2003, J.PubEco), Brender and Drazen (2005, JME), Drazen and Eslava (2010, J.Dev.Eco).

Y Federal Government (FG) moves G t and τ t+1 Its budget constraint is: G t + Γ t = τ Y t Y t K Local Government (LG) moves g t and τ t+1 Its budget constraint is: g t = Γ t + τ k t K t Households (HS) chooses C t to maximize: U = (C t, G t, g t ) Its budget constraint is: K t+1 = (1 τ t Y )Y t K t C t + 1 τ t K K t Timing First move FG Second move LG Third move HS 3. Theoretical framework

Theoretical framework Optimization process Households choose consumption C t and capital K t+1 (under their resource constraint) in order to maximize the discounted sum of instantaneous utility function U C t = βu Y C t+1 1 τ t+1 Y t+1 + (1 τ K K t+1 ) t+1 the optimum the opportunity cost of accumulating one unit of new capital (LHS) must be equal to the discounted net marginal benefit of future consumption (RHS). In turn, this latter is the sum of the net-of-taxation unit of capital and the net-of-taxation output produced by that unit. K The local government chooses local public spending g t and local tax instrument τ t+1 (under its budget constraint and FOCs) in order to maximize welfare function (=utility function) U C t+1 λ 2,t = U g t+1 K t+1 the trade-off facing the LG: if it increases local tax instrument τ K, the benefit is future marginal utility of local public spending (RHS), but the cost is the foregone future marginal utility of consumption. Y The federal government chooses federal public spending G t and federal tax instrument τ t+1 (under its budget constraint, LG FOC and HS FOC) in order to maximize welfare function (=utility function) λ 5,t U C t+1 Y t+1 K t+1 = U G t+1 at the optimum the marginal cost of increasing federal tax (LHS) must be equal to the marginal benefit of the corresponding increase in public spending or transfer to the local government.

Theoretical framework - Equilibrium The equilibrium is pictured by a vector of endogenous variables: [ K t+1, C t, G t, g t, τ Y t+1, τ K t+1, Γ t ] At the equilibrium: g Γ = τk K > 0 τy when the central government reduces transfers to local government (Γ), the latter reduces local public spending g. Such a reduction is greater the higher the steady-state level of local tax rate (τ K ) and the stock of capital (K). Re-arranging we ge: τ K = gτ Y KΓ τ Y KY τ K Γ = gτy K (KΓ τ Y KY) 2 when the central government reduces transfers to local government, the latter increases the local tax rate (τ K ). Such an increase is greater the higher the steady-state level of local public spending and the steady-state tax rate on income.

4. EMPIRICAL ANALYSIS 4.1. Preliminary Analysis 4.2. The data 4.3. The model and main results

art. 61 c. 11 DL 112/2008 art. 47 c. 8 DL 66/2014 e art. 9 DL 16/2014 art. 1 c. 435 L 190/2014 art. 28 c. 7 DL 201/2011 art 14 c. 2 DL 78/2010 art. 16 c. 6 DL 95/2012 Billion euros I TAGLI DEI COMUNI 4.1. Preliminary analysis Since 2010 the Italian government has been conducting an intense program of spending cuts for municipalities (over 8000 elected local authories) TOTAL 8,6 billions (18% of current expenditure and 33% of 2007 capital expenditure) 13 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Source Ministry of Internal Affairs 2009 => art. 61 c. 11 DL 112/2008 (0,2 billions) 2011 => art 14 c. 2 DL 78/2010 (2,5 billions exemption of municipalities < 5000 inhabitants) 2012 => art. 28 c. 7 DL 201/2011 (1,4 billions) 2013 => art. 16 c. 6 DL 95/2012 (2,6 billions exemption municipalities affected by 2009 and 2012 the earthquake) 2014 => art. 47 c. 8 DL 66/2014 e art. 9 DL 16/2014 (0,7 billions) 2015 => art. 1 c. 435 DL 190/2014 (1,2 billions exemption municipalities affected by 2009 and 2012 the earthquake)

I TAGLI DEI COMUNI Allocation rules of spending cuts S i = β X i + ε i where: i = municipal index; S = per capita spending cuts; X = matrix of financial and environmental variables, β coefficients estimated with OLS Total 2010-2015 spending cuts art. 61 c. 11 DL 112/2008 art 14 c. 2 DL 78/2010 art. 28 c. 7 DL 201/2011 art. 16 c. 6 DL 95/2012 art. 47 c. 8 DL 66/2014 e art. 9 DL 16/2014 art. 1 c. 435 L 190/2014 tax revenues 0.128 0.006-0.025 0.067 0.003 0.001 0.074 current expenditure 0.051 0.001 0.002 0.009 0.030 0.008 0.001 capital expenditure 0.001 0.001-0.001-0.001 0.001 0.001-0.001 Income 0.001-0.001 0.001 0.001 0.001 0.001-0.00 1 real estate value 0.019-0.001 0.006 0.011 0.001 0.001 altitude zone (1=low - 5=high) -0.810 0.054-0.835-0.666 0.435 0.118 0.082 degree of urbanization(1 = low - 3 = high) 2.504-0.241 6.362-0.584-2.262-0.450-0.321 population 0.257 0.010 0.255-0.047 0.039-0.001 0.001 n. of municipalites 6825 6825 6825 6825 6825 6825 6825 R-squared 0.771 0.579 0.449 0.654 0.67 0.682 0.98 14 linear allotment criteria on spending or resources strong impact of population levels different criteria depending on the type of reduction Impact of population

milion euros I TAGLI DEI COMUNI Current expenditure composition 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000-2010 2011 2012 2013 2014 2015 personnel expenditure Consumption Grants to other local gov. Interests other current expenditure Expnediture net of public transport and waste management. Only municipalities of normal regions 15 Source Ministry of Internal Affairs

no. of municipalities Municipalities by population 1800 1600 1400 1200 1000 800 600 400 200 0 above >500 >1000 >2000 >3000 >5000 >10000 >20000 >60000 >100000 >250000 >500000 500000 Special regions 140 222 297 199 188 172 93 65 8 7 1 1 Normal regions 714 897 1,291 807 946 1,018 606 343 48 27 5 5 Normal regions Special regions Source Ministry 16 of Internal Affairs, year 2014

Italian municipalities institutional framework 6700 municipalities (comuni ) [ around 600 > 15,000 inhabitants], ruled by a local government (giunta), headed by an elected mayor (sindaco ). Mayors: elected directly by residents (from1993); Plurality system for municipalities below 15000 inhab. Runoff system for municipalities above 15000 inhab. in power for five years and are subject to a two-term limit; power to nominate/dismiss members of the local government; competencies on environment, local transport, local police, culture and education; Some discretionary powers on how to raise fiscal revenue; supported by a coalition of parties There are two main party coalitions in Italy: centre-left and centre-right.

euro per capita Expenditure composition 3,000 2,500 2,000 1,500 1,000 500 - population brackets Current expenditures Source Ministry of Internal Affairs, year 2014 Capital expenditures

Municipalities provides 10 main public services (billion euros): waste management (7.61) general admin. services (6.39) social services (4.67) complementary education services (3.57) public roads and transport (3.21) land management and planning (2.69) local police (2.64) nursery services (1.44) tax office (0.50) civil registry (0.55)

euros per capita Local Governments' Financing 2,500 2,000 1,500 1,000 500 - population brackets taxes grants current grants capital debt Source Ministry 20 of Internal Affairs, year 2014

Local Governments' Financing Municipalities' revenues come from two main sources: transfers from upper levels of government (mainly from regional governments), from 2010 to abolition of central transfers => horizontal equalization system Taxes: Property Tax (ICI/IMU);Tax on Waste Disposal (TARSU/TARI); Other Taxes (Income tax and electricity surcharge). Fees for: general services (road and traffic, libraries, theatres and culture, burial services, etc.); other services (occupation of public spaces, public billboards, issues of certificates).

4.2. The data The (administrative) dataset contains yearly information at the municipality level about budget items (only normal regions => 6700 local authorities) Source: Italian Ministry of Internal Affairs, ISTAT (National Institute of Statistics); Italian Ministry of Economy and Finance Budget variables: Spending cuts current expenses, capital expenses (investments) (local) tax revenues, fees & tariffs, transfers Domestic stability pact target Merged with dataset containing political information: term limit, electoral outcomes, electoral cycle, turn out Merged with dataset containing a set of control variables: population by age, income, real estate market values Panel structure: from 2010 to 2012

Data snapshot Variable All sample Treatment = 1 (pop > 5000) Treatment = 0 (pop < 5000) Obs Mean Std. Dev. Obs Mean Std. Dev. Obs Mean Std. Dev. After treatment dummy 10418 0.09 0.28 2773 0.33 0.47 7645 0.00 0.00 Treatment dummy 10418 0.27 0.44 2773 1.00 0.00 7645 0.00 0.00 Spending cuts (dl 78/2010) ( per capita) 10336 5.46 12.54 2753 20.27 16.74 7583 0.00 0.00 Spending cuts (total) ( per capita) 10296 18.50 22.59 2743 32.34 29.11 7553 13.48 17.12 Current expenditure ( per capita) 10316 589.46 211.72 2760 527.35 178.60 7556 612.15 218.24 Capital expenditure ( per capita) 10317 279.50 329.96 2762 172.71 208.30 7555 318.54 356.55 Property tax ( per capita) 10262 154.88 91.23 2741 161.98 85.03 7521 152.29 93.26 Local income tax ( per capita) 10274 46.73 22.62 2725 52.12 22.74 7549 44.79 22.26 Fees (net of waste manag.) ( per capita) 10249 61.91 52.52 2750 55.15 44.45 7499 64.39 54.98 Total tax revenues ( per capita) 10092 261.50 120.06 2694 266.61 109.97 7398 259.64 123.49 Domestic stability pact (target) ( per capita) 10418 4.08 27.43 2773 15.09 51.28 7645 0.09 3.41 Population (0-2) % total pop. 10418 2.67 0.64 2773 2.88 0.53 7645 2.60 0.67 Population (3-14) % total pop. 10418 10.89 1.73 2773 11.53 1.49 7645 10.66 1.75 Population (15-65) % total pop. 10418 66.16 2.81 2773 67.04 2.24 7645 65.84 2.92 Population (over 65) % total pop. 10418 21.32 4.52 2773 19.58 3.70 7645 21.95 4.62 Real estate declared income ( per capita) 10371 355 217 2754 397 226 7617 339 211 Declared employment income ( per capita) 10371 6240 1916 2754 6594 1991 7617 6112 1872 Residential estate market values ( per sq meter) 10320 1087 518 2732 1236 673 7588 1034 438 Electoral cycle discrete (0-4) 9868 1.95 1.17 2593 1.95 1.25 7275 1.96 1.14 Term limit dummy 9867 0.19 0.40 2593 0.38 0.49 7274 0.13 0.33 Electoral year dummy 9868 0.11 0.31 2593 0.14 0.35 7275 0.10 0.30 Turnout % 9868 76.17 8.02 2593 76.45 6.18 7275 76.07 8.58 margin of victory % 9513 17.95 15.38 2566 16.23 13.62 6947 18.59 15.94

Euros per capita I TAGLI DEI COMUNI Analysis of the raw data 1000 Source Ministry of Internal Affairs 800 600 400 200 0-200 2010 2011 2012 2013 2014 2015-400 Current expenditure Capital expenditure Property taxes Local income tax Fees Spending cuts 24 Expenditure net of public transport and waste management. Only municipalities of normal regions

4.3. The model and main results Y P = budget outcome = population size, P c = 5000 Y 1 = potential outcome with D = 1 (spending cuts) Y 0 = potential outcome with D = 0 (no spending cuts) After T 0 D = 1 if P P c D = 0 if P < P c Before T 0 D = 0 for all Main estimate of interest: after treatment effect = E[Y 1 Y 0 P = P c ]

Potetial outcome: Y(1) = spending cuts, Y(0) = no spending cuts The empirical strategy Post-treatment period E ( Y(1) P, t >= T0] γ 1 E ( Y(0) P, t >= T0] π γ 0 γ 0 = Conf. Effects post 2010 (no cuts) γ 1 = Conf. Effectcs post 2010 (cuts) π = Effect of spending cuts Pc = 5000 Population size observed not observed

Potetial outcome: Y(1) = spending cuts, Y(0) = no spending cuts The empirical strategy Pre-treatment period E ( Y(1) P, t < T0] γ 1 E ( Y(0) P, t < T0] π γ 0 γ 0 = Conf. Effects pre 2010 (no cuts) γ 1 = Conf. Effects pre 2010 (cuts) π = Effect of spending cuts Pc = 5000 Population size observed not observed

The empirical strategy Estimation methods Assumptions No time variation in the confounding discontinuity: γ 1 = γ 1 No interaction effect between treatment and confounding effects: γ 0 = γ 1 Diff-in-disc estimator identifies: E[Y1 - Y0 P = Pc] π = lim P Pc E Y P, t T o lim P Pc E Y P, t < T o lim P Pc E Y P, t T o lim P Pc E Y P, t < T o = E Y 1 Y 0 P = P c Estimation of the dierence of two discontinuities at Pc with: Local Linear Regression (LLR) Spline polynomial approximation

The empirical strategy LLR For given bandwidth, restrict the sample to cities in the interval P i [P c, P c + ] Y i = δ o + δ 1 P i + D i γ 0 + γ 1 P i + T i α o + α 1 P i + D i β 0 + β 1 P i + ε i Where D i is the treatment, T i = 1 after 2010, P i is the normalized population and standard errors are clustered at the city level β 0 identifies the after treatment effect Robusteness checks => multiple bandwithds

The empirical strategy spline polynomial approximation Flexible functional form to fit the relationship between Y and P on either side of P c in the entire sample p p k k Y i = (δ k P i ) + D i (γ k P i ) k=0 k=0 p p k k + T i (α k P i ) + D i (β k P i ) k=0 k=0 + ε i Where D i is the treatment, T i = 1 after 2010, P i is the normalized population and standard errors are clustered at the city level β 0 identifies the after treatment effect Robusteness checks => multiple p-order polynomials

Diff-in-disc jumps in spending cuts (T 1 T 0 ) 0 100 150 50 Euros per capita (T 1 T 0 ) Regression function fit -4000-2000 0 2000 4000 6000 Sample average within bin 2th order global polynomial

Diff-in-disc jumps in current expenditure (T 1 T 0 ) 200 400 0 Euros per capita (T 1 T 0 ) Regression function fit -600-400 -200-4000 -2000 0 2000 4000 6000 Sample average within bin 2th order global polynomial

Diff-in-disc jumps in total revenues (T 1 T 0 ) -50 0-100 50 100 150 Euros per capita (T 1 T 0 ) Regression function fit -4000-2000 0 2000 4000 6000 Sample average within bin 2th order global polynomial

Total tax revenues (cut at 1000 inhab.) (1) (2) (3) (5) VARIABLES did llr llr lpr_2 After treatment effect 29.76*** 48.26*** 38.06*** 53.07*** Treatment effect -14.69*** -39.39*** -15.55*** -31.67*** T = 1 23.31*** 18.31** 44.66*** 27.09** Domestic Stability Pact (target) 0.116*** 0.116*** % pop. 0-2 36.17*** 36.85*** % pop 3-14 16.55** 17.10*** % pop15-65 21.17*** 21.92*** % pop over 65 23.66*** 24.30*** Real estate declared income 0.210*** 0.209*** Declared employment income 0.00279** 0.00288*** Residential estate market values 0.0668*** 0.0667*** Electoral cycle 26.54*** 26.89*** Electoral cycle sq. -5.911*** -5.962*** Term limit -7.252*** -7.466*** Election year 17.47** 17.67** % turnout 0.368** 0.332* % margin of victory 0.105 0.103 Constant 255.7*** 268.2*** -2,139*** -2,194*** Polynomia no first first second Observations 5,067 5,067 4,752 4,752 R-squared 0.021 0.024 0.437 0.439 standard errors are clustered at the city level, *** p<0.01, ** p<0.05, * p<0.1

Total current expenditure (cut at 1000 inhab.) (1) (2) (3) (5) VARIABLES did llr llr lpr_2 After treatment effect -0.837-35.59-30.69* -18.53 Treatment effect -34.23*** 34.34*** 18.77** 20.12 T = 1-20.87*** -17.46-13.16-35.02** Domestic Stability Pact (target) 0.0685 0.0667 % pop. 0-2 6.281 6.855 % pop 3-14 6.103 6.087 % pop15-65 18.82* 19.29* % pop over 65 21.48* 21.79** Real estate declared income 0.137*** 0.139*** Declared employment income -0.0135*** -0.0134*** Residential estate market values 0.119*** 0.119*** Electoral cycle -3.533-2.485 Electoral cycle sq. 1.903 1.756 Term limit -5.813-5.894 Election year -8.864-8.385 % turnout -1.018** -1.128*** % margin of victory 0.466*** 0.469*** Constant 581.4*** 544.3*** -1,264-1,263 Polynomia no first first second Observations 5,168 5,168 4,843 4,843 R-squared 0.011 0.022 0.287 0.294 standard errors are clustered at the city level, *** p<0.01, ** p<0.05, * p<0.1

Robustness checks - Total tax revenues (1) (2) (3) (4) VARIABLES lpr_2 cut 1000 lpr_3 cut 1000 lpr_3 cut 1500 lpr_3 cut 500 After treatment effect 53.07*** 50.11* 49.94** 28.45 Treatment effect -31.67*** -18.37-23.05** -10.43 T = 1 27.09** 49.05*** 30.59** 31.07 Domestic Stability Pact (target) 0.116*** 0.117*** 0.0343 0.157*** % pop. 0-2 36.85*** 37.43*** 45.52*** 31.75*** % pop 3-14 17.10*** 17.66*** 21.39*** 5.588 % pop15-65 21.92*** 22.29*** 26.75*** 13.52 % pop over 65 24.30*** 24.71*** 29.76*** 14.86 Real estate declared income 0.209*** 0.207*** 0.203*** 0.196*** Declared employment income 0.00288*** 0.00289*** 0.00364*** 0.00118 Residential estate market values 0.0667*** 0.0670*** 0.0596*** 0.0652*** Electoral cycle 26.89*** 26.52*** 28.46*** 22.64** Electoral cycle sq. -5.962*** -5.896*** -6.152*** -5.246*** Term limit -7.466*** -7.543*** -4.253* -8.983** Election year 17.67** 17.07** 19.65*** 17.37 % turnout 0.332* 0.353** 0.353** 0.268 % margin of victory 0.103 0.102 0.162** 0.133 Constant -2,194*** -2,257*** -2,707*** -1,294 Polynomia second third third third Observations 4,752 4,752 7,240 2,306 R-squared 0.439 0.441 0.424 0.409 standard errors are clustered at the city level, *** p<0.01, ** p<0.05, * p<0.1

Robustness checks - Total current expenditure (5) (7) (8) (9) VARIABLES lpr_2 lpr_3 lpr_3 cut 1500 lpr_3 cut 500 After treatment effect -18.53 17.44-32.27-0.916 Treatment effect 20.12-2.378 42.02*** -4.425 T = 1-35.02** -25.11-25.40-45.33 Domestic Stability Pact (target) 0.0667 0.0723 0.0296 0.0895 % pop. 0-2 6.855 7.930 30.38*** -12.39 % pop 3-14 6.087 6.486 21.06** -13.50 % pop15-65 19.29* 19.72* 34.73*** 2.916 % pop over 65 21.79** 22.21** 38.22*** 5.454 Real estate declared income 0.139*** 0.139*** 0.167*** 0.0942*** Declared employment income -0.0134*** -0.0134*** -0.0144*** -0.0128*** Residential estate market values 0.119*** 0.119*** 0.105*** 0.120*** Electoral cycle -2.485-3.068 0.904-2.934 Electoral cycle sq. 1.756 1.869 1.473 1.569 Term limit -5.894-6.121 2.534-8.155 Election year -8.385-8.811-1.595-8.880 % turnout -1.128*** -1.089*** -1.247*** -0.987** % margin of victory 0.469*** 0.474*** 0.333*** 0.622*** Constant -1,263-1,320-2,861*** 430.9 Polynomia second third third third Observations 4,843 4,843 7,375 2,350 R-squared 0.294 0.296 0.302 0.321 standard errors are clustered at the city level, *** p<0.01, ** p<0.05, * p<0.1

Robustness checks - Total spending cuts (1) (2) (3) (5) (7) (8) (9) VARIABLES did cut 1000 llr cut 1000 llr cut 1000 lpr_2 cut 1000 lpr_3 cut 1000 lpr_3 cut 1500 lpr_3 cut 500 After treatment effect 32.19*** 29.16*** 29.27*** 21.87*** 16.94** 20.68*** 6.637 Treatment effect 3.469*** 3.791*** 3.639*** 4.278*** 3.357*** 3.909*** 2.502* T = 1 42.11*** 46.87*** 46.01*** 52.03*** 54.30*** 53.19*** 58.15*** Domestic Stability Pact (target) 0.0644*** 0.0643*** 0.0648*** 0.0642*** 0.0517*** % pop. 0-2 -5.628*** -5.674*** -5.710*** -5.279*** -7.335*** % pop 3-14 -4.537*** -4.609*** -4.648*** -4.477*** -5.943*** % pop15-65 -4.857*** -4.921*** -4.951*** -4.611*** -6.204*** % pop over 65-4.452*** -4.515*** -4.549*** -4.290*** -5.843*** Real estate declared income 0.00769*** 0.00786*** 0.00798*** 0.00844*** 0.00959*** Declared employment income -0.000229-0.000234-0.000242-0.000221-0.000450* Residential estate market values 0.00228*** 0.00226*** 0.00225*** 0.00224*** 0.00167 Electoral cycle -1.742** -1.716** -1.680** -2.000*** -0.713 Electoral cycle sq. 0.423** 0.419** 0.410** 0.504*** 0.211 Term limit -0.132-0.0884-0.0939 0.0707-0.480 Election year -1.376-1.312-1.278-1.426* -0.634 % turnout -0.129*** -0.132*** -0.133*** -0.138*** -0.194*** % margin of victory -0.00973-0.00943-0.00942-0.0145-0.0121 Constant 1.334*** 1.408*** 489.8*** 496.4*** 500.4*** 469.0*** 634.7*** Polynomia no first first second third third third Observations 5,158 5,158 4,836 4,836 4,836 7,371 2,356 R-squared 0.811 0.813 0.841 0.842 0.842 0.839 0.840 standard errors are clustered at the city level, *** p<0.01, ** p<0.05, * p<0.1

Diff-in-disc jumps - Revenues compostion (T 1 T 0 ) Regression function fit Regression function fit 100 150 100 50-50 100 50 0-50 -100 10 20 30 40 0-4000 -2000 0 2000 4000 6000 Sample average within bin 2th order global polynomial 0 Euros per capita (T 1 T 0 ) Euros per capita (T 1 T 0 ) Euros per capita (T 1 T 0 ) Euros per capita (T 1 T 0 ) Total tax revenues Property tax -50 0 50-100 -4000-2000 0 2000 4000 6000 Sample average within bin 2th order global polynomial Local Income tax Regression function fit Fees (no waste manag.) Regression function fit -100-4000 -2000 0 2000 4000 6000 Sample average within bin 2th order global polynomial -4000-2000 0 2000 4000 6000 Sample average within bin 2th order global polynomial

Diff-in-disc jumps - Revenues compostion Property tax Local income tax Fees VARIABLES did cut 1000 lpr_2 cut 1000 did cut 1000 lpr_2 cut 1000 Did cut 1000 lpr_2 cut 1000 After treatment effect 16.39*** 33.97** 4.152** -0.814 12.21*** 22.11** Treatment effect -4.887* -22.33*** 1.252* 2.806* -10.29*** -12.53*** T = 1 16.55*** 21.89** 14.22*** 16.60*** -7.016*** -15.47*** Domestic Stability Pact (target) 0.0339 0.00787 0.0583*** % pop. 0-2 45.69*** -13.18*** 8.798** % pop 3-14 30.63*** -14.17*** 2.824 % pop15-65 35.53*** -13.98*** 3.028 % pop over 65 34.92*** -12.26*** 4.291 Real estate declared income 0.173*** 0.00681** 0.0215*** Declared employment income -0.00255*** 0.00588*** -0.000300 Residential estate market values 0.0398*** 0.00396*** 0.0204*** Electoral cycle 30.13*** -1.113-2.079 Electoral cycle sq. -6.846*** 0.354 0.476 Term limit -3.221-0.0312-4.604*** Election year 19.59*** 0.587-2.258 % turnout 0.791*** 0.0769** -0.516*** % margin of victory 0.0317-0.0514*** 0.157*** Constant 151.1*** -3,569*** 40.53*** 1,369*** 65.42*** -257.2 Polynomia no second no second no second Observations 5,130 4,812 5,121 4,799 5,151 4,826 R-squared 0.015 0.420 0.081 0.392 0.009 0.108 standard errors are clustered at the city level, *** p<0.01, ** p<0.05, * p<0.1

5. CONCLUSIONS AND NEXT STEPS Final results show that Italian municipalities reacted to the contraction of intergovernmental grants mainly by increasing local taxes rather than by reducing local expenditure Main policy implication: Transmission mechanism from central spending cuts to local spending in the presence of local fiscal autonomy Next steps: Validity tests Analysis of heterogeneous effects Discontinuity in 2012 and 2015 spending cuts (earthquakes exemptions)