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7. Regression Discontinuity Designs with a Continuous Treatment. (2019). Dong, Yingying ; Lee, Ying-Ying ; Gou, Michael.
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57. As emphasized by Farhi and Werning (2016), the national multiplier in a liquidity trap is likely to be larger under a flexible exchange rate regime as the initial devaluation associated with the fiscal expansion triggers also an expenditure-switching effect.
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58. Consider two pairs of municipalities in the state of Minas Gerais over the years 2010 and 2011, displayed in Figure B.1.1 The first pair consists of Bela Vista and Centralina. These municipalities experienced a slight drop in population over that period. On the one hand, Bela Vista’s population went from 10, 333 to 10, 004. The small decline was nevertheless sufficient for the city to cross the FPM population cutoff of 10, 188 residents; as such its FPM coefficient was reduced from 0.8 to 0.6. Accordingly, FPM transfers fell from R$2, 328, 037 in 1
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59. Even though 2012 is not technically a census year, we conservatively classify it here as a census year because it significantly carries the manipulative sorting from 2011 as discussed above.
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60. ik λ̃i t (2) where λ̃i t = αtλi t + (1 − αt)λi 97 and αt = ( 0.2 + (t − 1999) ∗ 0.1 if t < 2008 1 if t ≥ 2008 Figure C.2a illustrates the association (elasticity) between (log) actual FPM and lawimplied FPM Transfers. The relationship is evidently strong, with most observations close to the 45 degree line. Figures C.2b and C.2c relate transfers to municipal revenue and expenditures. As expected the relationships are not as close to a perfect fit as with actual transfers, but the correlation is strong. D Identification. Further Evidence In this section, we first provide further evidence on the validity of the identifying assumptions behind the fuzzy-RD empirical design and then we discuss in detail manipulation. 2 We have also re-estimated the specifications dropping these municipalities altogether finding similar results.
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61. ik λi,t . (1) FPMk,t is the amount of resources allocated to state k, based on the fixed (in 1991) state shares and the total pot of FPM funds in year t. λi is the FPM coefficient of municipality i based on its population bracket in year t. The fraction λi,t P ik λi,t is the share of state FPM transfers allocated to municipality i in state k in year t.
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62. In Appendix Table 13, we examine the sensitivity of the main categories of municipal spending, namely public administration, education, health, housing & urbanism, and others, to changes in regional transfers in the neighborhood of the FPM cutoffs. The elasticities are positive and highly significant across all municipal spending categories. This suggests that the increase in municipal expenditure triggered by a "locally" (close to the FPM cutoffs) exogenous increase in transfers is spread across all budget categories.3 D.2 Systematic Manipulation The RDD framework requires that local variation in the assignment to treatment is as-goodas random in the neighborhood of the cutoffs (Lee and Lemieux, 2010). Below, we present four test that are supportive of the identification design. D.2.1 Population Density Test We begin by testing whether the density of municipal population is continuous at the cutoffs.
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63. In the 1990s, some municipalities split into two, but temporarily managed to keep their former FPM coefficient through court rulings. In an effort to correct for such distortions, the federal government (through Complementary Law LC 91/97) mandated that all municipalities should be framed in the correct population brackets by 2008. To prevent immediate disruption to the municipal public finances, the law established a transition period. Hence in the period 1999 − 2007 some municipalities still received FPM transfers which were not fully consistent with their population estimate.
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64. Law LC 91/97 determined that FPM transfers for these municipalities should be calculated using a modified FPM coefficient (λ̃t); a weighted average of their coefficient in 1997 (λ97) and their "correct" coefficient in year t (λt). The weight αt given to the "correct" FPM coefficient (λt) would start at α99 = 0.2 and increase by 0.1 per year until 2008, when (a) Actual FPM (b) Municipal Revenue (c) Municipal Expenditure Figure C.2: Law-Implied FPM Transfers and Actual Outcomes the correction would be complete. This affects 1, 503 municipalities.2 Hence the law-implied FPM Transfer \ FPM k i,t for municipality i in state k and year t is: \ FPM k i,t = FPMk t λ̃i t P
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65. Minas Gerais is the largest state in terms of the number of municipalities (853) and the second largest in terms of population (21 million inhabitants in 2015).
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66. Moreover, earlier work on the political economy of the FPM programme has also distinguished across municipal size (Brollo, et al. 2014). The estimates in Appendix Table 37 Panel A allow the private employment law-implied FPM association to differ for relatively small (centred on FPM cutoffs 1-3) and relatively big municipalities (centred on cutoffs 4-7). First, all estimates, in both the level and the difference specifications are positive. Second, the estimates are larger and more precisely estimated in the sample of small municipalities. This result appears in line with the evidence in Table 12 of larger and more precisely estimate elasticities in the sample of more financially constrained and less developed municipalities.
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67. produced varieties to 6. These values are in line with earlier works (e.g. Nakamura and Steinsson, 2014). 12 Relative to the results reported below, a lower value of ρg would generate a monotonically larger gap between externally-financed and locally-financed multipliers, mostly driven by a larger negative wealth effect in the local taxes scenario. 13 The red line may also be interpreted as the locus of national fiscal multipliers for a small open economy operating in a liquidity trap (i.e. with a fixed nominal interest rate) and under a fixed exchange rate regime.
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68. The sample includes 43,466 yearly observations covering 3,279 Brazilian municipalities over the period 1999-2014. Panel A-C respectively report mean and standard deviations on total earnings, total employment and wage per worker by employee tenure (old or new hires) and by sub-sector (Agriculture, Manufacturing and Services), respectively.

69. The second pair of cities in Minas Gerais, Caetanopolis and Pedralva, experienced a slight increase in population over 2010 − 2011. On the one hand, the population of Pedralva went up by 116 inhabitants, from 11, 351 to 11, 467. This population change was not large enough to move the city to a higher FPM population bracket. As such, the increase in FPM transfers was moderate - from R$2, 328, 037 to R$2, 686, 415, reflecting the overall raise in the total pot of funds at the national level. On the other hand, Caetanopolis population increased by 178 inhabitants from 10, 040 to 10, 218, which was enough, however, to move Caetanopolis to a higher FPM population bracket (λ increased from 0.8 to 1.0). FPM transfers increased by more than 50% from R$1, 746, 027 to R$2, 686, 415, reflecting both the higher FPM coefficient and the increase in the total proceeds of the FPM program at the federal level.
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70. This is in line with the independently developed work of Braga et al. (2017) who find that FPM transfers affect most types of spending, albeit in different magnitudes.
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71. This result is in line with the parallel work of Braga, Guillen and Thompson (2017), who fail to find any effect of government spending on private sector average wages in virtually all specifications.
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72. Total No Movement 1410 1087 2497 Moves to Lower Bracket 93 689 782 Total 1503 1776 3279 Total No Movement 601 976 1577 Moves to Lower Bracket 146 172 318 Total 747 1148 1895 Panel A reports the number of municipalities in the full sample that move to a higher/lower FPM population brackets at least once across the full sample period 1999-2014, and the number of municipalities that stay in the same FPM population bracket. Panel B repeats Panel A only for observation near a cut-off (relative bandwidths 4%).
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15. Regional Transfer Multipliers. (2018). Surico, Paolo ; Papaioannou, Elias ; Corbi, Raphael.
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16. Fiscal Trade‐Offs: The Relationship Between Output and Debt in Policy Interventions. (2018). McManus, Richard.
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17. WHICH FISCAL MULTIPLIERS ARE REGIME‐DEPENDENT? A META‐REGRESSION ANALYSIS. (2018). Rannenberg, Ansgar ; Gechert, Sebastian.
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18. Local manufacturing productivity markers: an empirical study of the Italian counties. (2017). Santoni, Gianluca ; Manzocchi, Stefano ; Quintieri, Beniamino.
    In: The Annals of Regional Science.
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19. Geographic Cross-Sectional Fiscal Multipliers: What Have We Learned?. (2017). Chodorow-Reich, Gabriel.
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20. The Employment Effects of Countercyclical Infrastructure Investments. (2017). Watzinger, Martin ; Buchheim, Lukas.
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21. On theories and estimation techniques of fiscal multipliers. (2017). Gechert, Sebastian.
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22. Intergovernmental Transfers: Are they pro- or counter-cyclical?. (2017). Égert, Balázs ; Blöchliger, Hansjörg ; Blochliger, Hansjorg ; Egert, Balazs.
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23. Law enforcement, municipal budgets and spillover effects: Evidence from a quasi-experiment in Italy. (2017). Galletta, Sergio.
    In: Journal of Urban Economics.
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24. Fiscal policy coordination in currency unions at the effective lower bound. (2017). Müller, Gernot ; Hettig, Thomas ; Muller, Gernot.
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25. Estimating Transfer Multiplier using Spending on Rural Development Programs in India. (2017). Bahal, Girish.
    In: Cambridge Working Papers in Economics.
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26. The Impact of Public Employment : Evidence from Bonn. (2017). Heblich, Stephan ; Becker, Sascha ; Sturm, Daniel M.
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27. The Effect of Local Taxes on Firm Performance: Evidence from Geo-referenced Data. (2016). Santoni, Gianluca ; Di Porto, Edoardo ; Belotti, Federico.
    In: CSEF Working Papers.
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28. The Effect of Local Taxes on Firm Performance: Evidence from Geo-referenced Data. (2016). Santoni, Gianluca ; Di Porto, Edoardo ; Belotti, Federico.
    In: CEIS Research Paper.
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29. Do fiscal rules reduce the political cycle? Evidence from Italian municipalities. (2016). Forni, Lorenzo ; Bonfatti, Andrea.
    In: Marco Fanno Working Papers.
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30. Law enforcement, municipal budgets and spillover effects: Evidence from a quasi-experiment in Italy. (2016). Galletta, Sergio.
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31. Estimating Fiscal Multipliers with Correlated Heterogeneity. (2016). Patnam, Manasa ; Kitsios, Emmanouil.
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32. Law enforcement, municipal budgets and spillover effects: evidence from a quasi-experiment in Italy. (2016). Galletta, Sergio.
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33. The effect of local taxes on firm performance: evidence from geo-referenced data. (2016). Santoni, Gianluca ; Di Porto, Edoardo ; Belotti, Federico.
    In: Working Paper Series.
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34. Boulevard of broken dreams. The end of EU funding (1997: Abruzzi, Italy). (2016). de Blasio, Guido ; Barone, Guglielmo ; David, Francesco.
    In: Regional Science and Urban Economics.
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35. Natural Experiments in Macroeconomics. (2016). Hassan, T A ; Fuchs-Schndeln, N.
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36. Trust and in-group favoritism in a culture of crime. (2016). Meier, Stephan ; Pierce, Lamar ; la Cara, Barbara ; Vaccaro, Antonino.
    In: Journal of Economic Behavior & Organization.
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37. How large is the local fiscal multiplier? Evidence from Chinese counties. (2016). Guo, Qingwang ; Ma, Guangrong ; Liu, Chang.
    In: Journal of Comparative Economics.
    RePEc:eee:jcecon:v:44:y:2016:i:2:p:343-352.

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38. Business cycle synchronisation in EMU: Can fiscal policy bring member-countries closer?. (2016). Filis, George ; Duffy, David ; Degiannakis, Stavros ; Livada, Alexandra.
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39. Politics in the Family Nepotism and the Hiring Decisions of Italian Firms. (2016). Manacorda, Marco ; Gagliarducci, Stefano.
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40. The effect of local taxes on firm performance: evidence from geo referenced data. (2016). Santoni, Gianluca ; Di Porto, Edoardo ; Belotti, Federico.
    In: Working Papers.
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41. Law Enforcement, Municipal Budgets and Spillover Effects: Evidence from a Quasi-Experiment in Italy. (2016). Galletta, Sergio.
    In: CESifo Working Paper Series.
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42. Boulevard of broken dreams. The end of the EU funding (1997: Abruzzi, Italy). (2016). de Blasio, Guido ; Barone, Guglielmo ; David, Francesco.
    In: Temi di discussione (Economic working papers).
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43. Fiscal policy coordination in currency unions (at the zero lower bound). (2015). Müller, Gernot ; Mueller, Gernot ; Muller, Gernot Johannes ; Hettig, Thomas.
    In: VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy.
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44. Austerity and Households Expenditure. (2015). Trezzi, Riccardo ; Surico, Paolo.
    In: 2015 Meeting Papers.
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45. Natural Experiments in Macroeconomics. (2015). Hassan, Tarek ; Fuchs-Schuendeln, Nicola.
    In: NBER Working Papers.
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46. Natural Experiments in Macroeconomics. (2015). Hassan, Tarek ; Fuchs-Schuendeln, Nicola ; Fuchs-Schundeln, Nicola.
    In: CEPR Discussion Papers.
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47. Natural Disasters, Government Spending, and the Fiscal Multiplier. (2015). Fidrmuc, Jan ; Yang, Weonho ; Ghosh, Sugata.
    In: CESifo Working Paper Series.
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48. Natural disasters, growth and institutions: A tale of two earthquakes. (2014). Mocetti, Sauro ; Barone, Guglielmo.
    In: Journal of Urban Economics.
    RePEc:eee:juecon:v:84:y:2014:i:c:p:52-66.

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49. The Precautionary Saving Effect of Government Consumption. (2014). Pavoni, Nicola ; Ercolani, Valerio.
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50. The a/simmetrie annual macroeconometric model of the Italian economy: structure and properties. (2014). Mongeau Ospina, Christian Alexander ; Bagnai, Alberto ; Christian Alexander Mongeau Ospina, .
    In: a/ Working Papers Series.
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