Albert Solé-Ollé

Pilar Sorribas-Navarro

The dynamic adjustment of local government budgets: does Spain behave differently?

Keywords: H70, H72, H77 fiscal adjustment, intergovernmental transfers, local government

Version with "track changes"

The aim of this paper is to analyze whether Spanish municipalities adjust in response to budget shocks and (if so) which elements of the budget they are more likely to adjust. The methodology we use to answer these questions is a vector error-correction model (VECM), estimated with data from a panel of Spanish municipalities during the period 1988-2006. Our results confirm that Spanish municipalities do indeed make adjustments in response to fiscal shocks (i.e., the deficit is stationary in the long run). We compare our results with those obtained for US and Germany to evaluate if the viability of local finance depends on the institutional arrangement and to analyze how it affects the adjustment patterns. We observe that grants have a more important role in the adjustment process in environments where either they have an equalization objective or where there is no clear rule that determines their distribution. This fact can generate a moral hazard problem: governments tend to spend more due to the expected intervention by the central government. Own revenues have a lower adjustment capacity in environments where subcentral governments have limited fiscal autonomy. These results, however, suggest that the viability of the local finance system is feasible with different institutional arrangements.

Introduction

Local governments deliver a range of public services that have a strong impact on a community's quality of life. In most countries, they are responsible for refuse collection and recycling, water delivery and sewerage, street lighting and maintenance, public transportation, capital improvement construction, police, planning and land use regulations, and recreational and cultural facilities and programs. In some places, they are also involved in the provision of education, health and social services. Many scholars and international organizations currently advocate the virtues of the provision of these services by sub-national governments and, in particular, by local governments (see, e.g., the contributions in Brosio et al., 2008). However, there is less agreement as to how these local services should be funded. Traditional advice from 'fiscal federalism' scholars (see, e.g., Oates, 1972) recommends relying primarily on property taxes and user charges, but the U.S. experience with the imposition of property tax limitations has demonstrated the problems associated with this approach (e.g., Downes et al., 1998;Bradbury, 2001). And yet, other major taxes (e.g., income taxes) are often inappropriate given the size of local governments, and so the solution in the end is either the decentralization of minor and inefficient taxes or grant financing.

In these circumstances, such intergovernmental transfers serve to attenuate the inefficiencies of local tax systems and may help smooth spending and tax policy (Sala-i-Martin andSachs, 1992, von Hagen andEichengreen, 1996). However, recent studies also emphasize the perils of grant financing. First, grants can create a moral-hazard problem, with local governments, aware that intergovernmental grants provide insurance against budget shocks, pursuing overly risky policies (Persson and Tabellini, 1997). Second, grants might soften the local budget constraint (e.g., Wildasin, 1997;Rodden, 2000;Inman, 2001), creating incentives to run up excessive deficits that local governments expect to be covered by future grants. Third, grant financing may diffuse accountability (Rodden, 2000) and foster rent-seeking and clientelism (Devarajan et al., 2008), thus eroding the very benefits gained from spending decentralization. With its F o r P e e r R e v i e w 2 virtues and perils, any final evaluation of grant financing has to be country specific, with the system depending on the particular details of the whole local government financing system (see, e.g., Rodden et al., 2003). This being the case, a promising avenue for research involves evaluating the viability of local finance systems in countries with different institutional arrangements. One way of conducting such an evaluation is to analyze whether local government budgets undergo any adjustments following a budget shock, and the role that is played by intergovernmental grants in this process. According to the three perils of grant financing just mentioned, we expect to observe, first, that grants that have an equalization objective will play an important role in the adjustment process and that can reduce the incentive to use fiscal autonomy, on the revenue and the expenditure side, to adjust after a budget shock. Nevertheless, on the revenue side, the extent to which own revenues can contribute to the fiscal adjustment is conditioned by their flexibility and the existence of normative restrictions.

Second, the lack of an objective and clear formula to determine the distribution of grants allows their use to provide fiscal assistance to subcentral governments in order to ensure the adjustment. Thus, discretionary grants can also reduce the incentives to control expenditures, which can generate a moral-hazard problem. This effect should be more pronounced when the central government cannot commit itself to a strict no bail out rule.

This research question has been previously addressed by Buettner and Wildasin (2005) and Buettner (2007) using data for U.S. and German local governments, respectively. Their results suggest that the system is viable in both countries, albeit that grants were found to play a more prominent role in the absorption of revenue shocks in the German case because of the role played by equalization transfers. Buettner (2007) suggests that the high degree of insurance might account for the greater reliance in Germany on the volatile local business tax.

In this paper we perform a similar analysis for the Spanish case. A number of specific institutional characteristics suggest that Spanish municipalities constitute an interesting case study (see Suárez-Pandiello, 1999, for a survey). First, as in the U.S. and Germany, the municipalities are responsible for the provision of services Deleted: with Deleted: In situations where local budgets either do not adjust (so, that the deficit is not reverted over time), adjust very slowly, or require massive fiscal assistance in order to ensure the adjustment, then there is compelling evidence that the local governmental system is not viable unless it receives interventions from the higher tiers of government. Second, since the end of the 1980s, Spanish municipalities have been able to modify the tax rates of all taxes assigned to them, albeit subject to compulsory minimum tax rates (common to all municipalities) and ceilings (which grow with population size), which might serve to constrain their responses. The main local taxes are (in the following order) a property tax, a business tax, and a motor vehicle tax. These tax bases are quite inelastic 1 , which insures against large revenue shocks during downturns but also against automatic increases during times of boom 2 . Third, vertical unconditional transfers represent a third of current revenues and are formula-based, but they have a very low equalizing power (see, e.g., Suárez-Pandiello, 1999;Bosch and Solé-Ollé, 2005). Thus, they are more relevant than in the U.S. case, but they do not share the insurance properties of German transfers. Conditional grants play an important role in the financing of capital projects (a half of all investments being funded by them) and many of them require co-funding by own-revenues. They very rarely include an equalization component, and their allocation is largely discretional (Solé-Ollé and Sorribas-Navarro, 2008). Finally, local debt is subject to certain ceilings, involving both the ratio between debt and current revenues and the short-term financial position.

However, the problems entailed in controlling these indicators effectively are enormous, and mean that successive Spanish governments have had great room to use 1 Unlike its German counterpart, Spain's local business tax (Impuesto sobre Actividades Económicas) is a presumptive tax, with a tax base computed using simple indicators of economic activity (e.g., surface area, electricity usage, number of workers, sectoral classification, see Jofre-Monseny and Solé-Ollé, 2008), which makes it less volatile than the German tax. 2 Other local taxes are a construction tax and a tax on land value improvements, which tend to become important during housing booms, and as such are quite volatile. This would seem to modify our conclusion, therefore, regarding the elasticity of the main taxes.

Deleted: These taxes are considered as being inequitable and, therefore, somewhat unpopular, while preventing the municipalities from making major short-term adjustments.

Deleted: for example Deleted: They are proportional, closedended grants, which are used for funding capital expenditure projects proposed by the local government. Further, they are not subject to explicit equalization grants as their German counterparts are, while they can rely to a great extent on discretionary transfers to fund investment.

The results of our analysis should show us whether these institutional differences among Germany, US and Spain are reflected in different patterns of adjustment to budget shocks, specially focusing on the role of grants The methodology we adopt here closely mirrors that applied by Buettner and Wildasin (2006) and Buettner (2007). To trace the budget adjustment process, we use a vector error-correction model (VECM), estimated with panel data drawn from a set of Spanish municipalities during the period 1988-2006 4 . Our results confirm, first, that Spanish municipalities do adjust in response to fiscal shocks (i.e., the deficit is stationary in the long run). Second, we observe that the adjustment process is conditioned by the design of intergovernmental relationships.

After a revenue shock, grants play a more important role in the adjustment process when they have an equalization and/or insurance component. Adjustments to expenditure shocks are compensated to a larger extend by grants at institutional arrangements where their allocation criteria is not based on a clear and objective rule.

The rest of this paper is organized as follows. In the second section, we briefly present the analytical framework used here. In the third, we describe the data and the 3 Since 2002, with the enactment of the 'Budget Stability Law', the running up of deficits by any tier of government is forbidden (i.e., new debt should be used to fund past debt service). Compliance with this law, however, has been minimal outside very big cities, with regional governments (which are responsible for the overseeing of local debt policies) still applying the older rules. 4 The model is very similar to the vector autoregression (VAR) used by Holtz-Eakin et al. (1989) and Dalhberg andJohansson (1998, 2000), the only difference being that the VEC model includes the deficit (considered as being stationary) in the estimated equations. Other papers that analyze subnational adjustment to fiscal shocks, but adopting different methodologies, include those by Poterba (1994), Rattso (1999) and Darby et al. (2005). No such studies have been undertaken of the Spanish case.

Deleted: in Deleted: to those described in these other countries.

Deleted: first developed by Bohn (1991) and Deleted: to local governments Deleted: find Deleted: that most of the adjustment to a revenue shock is borne by the municipalities themselves -through the cutting of expenditure, with a minor role being played by grant financing. By contrast, adjustments to expenditure shocks are shared on largely similar terms by the municipality -through the raising of taxes-and higher tiers of government -through the raising of grants. many tests performed to ensure the model is correctly specified. In the fourth section, we discuss the results and compare them with those obtained previously for other countries. In the final section, we conclude.

Analytical framework

The analytical framework employed here is similar to that employed in Buettner and Wildasin (2006) and Buettner (2007), who where the first to apply the methods previously used by Bohn (1991) and Hjelm (2001) in describing the dynamic fiscal adjustment of national governments to local government budgets. This procedure models budgetary adjustment to fiscal shocks through a vector error-correction model (VECM). If we distinguish the following four budgetary components: own-source revenues, R it , grants, G it , expenditures, E it , and debt service, DS it , we can express the VECM(p), using matrix notation, as follows:

it t p j j it j it u X X A X + + ∆ = ∆ - = - ∑ 1 1 γφ (1)
where ( )

it it it it it G DS E R X , , , = , ( )' 1 - , 1 , 1 , 1 - = φ and t X φ is the general deficit.
Since the estimation of the VECM provides a large number of parameters, which are difficult to interpret at first sight, we compute the generalized impulse-response functions (GIRFs hereinafter), following Pesaran and Shin (1998) 5 . The GIRFs project the response of each budgetary component in reaction to a shock, which is either to itself or to any other budgetary component. Moreover, the GIRFs consider the historical distribution of the residuals. That is, the GIRFs take into account the correlations 5 Prior to doing this, we use the recursive procedure proposed by Lütkepohl and Reimers (1992) to obtain the coefficients of the VAR(p+1) in levels derived from the VECM(p) and then the moving average (MA) representation of the VAR(p+1).

Deleted: Prior to doing this, we use the recursive procedure proposed by Lütkepohl and Reimers (1992) to obtain the coefficients of the VAR(p+1) in levels derived from the VECM(p) and then the moving average (MA) representation of the VAR(p+1). between the fiscal variables and do not assume that if a shock occurs in one fiscal variable everything else remains constant. Thus, the GIRFs are invariant to the ordering of the variables in the VECM, and thereby overcome the main problem of the traditional IRF 6 . We summarize the information provided by the GIRFs when computing the present value of the fiscal adjustment process.

Analytically the GIRF is defined by the following expression:

( ) [ ] [ ] 1 - t 1 - t 1 - t I E I , E I , , h t k kt h t k X X X h GIRF + + - = = δ ε δ (2)
where h is the number of periods ahead, k δ represents a shock to variable k, and I t-1 is all the information available at the time of the shock. Thus, Equation 2 states that the GIRF for the vector X, h periods ahead, is the difference in the expected value (E) of X t+h , when taking the shock k δ into account. Pesaran and Shin (1998) ( )

k kk k h X e h GIRF δ σ 1 1 - t I , 1 , - Σ Φ = (3)
where h Φ is the MA coefficient matrix at t+h, k e is a m × 1 selection vector, where m is the number of endogenous variables, with unity as its kth element and zero elsewhere 7 .

Data and model specification

Data. We use panel data for a 19-year period (1988-2006), including annual budgetary information for 258 municipalities in Catalonia, a Spanish region 8 . As in 6 By traditional IRF we refer to the IRF as computed by Sims (1987) and Hamilton (1994). The use of the GIRF rather than the IRF constitutes the main methodological difference with respect to Buettner and Wildasin (2006) and Buettner (2007). 7 We computed the bootstrap standard errors of the coefficients of the GIRFs by conducting 100 replications with replacement. The initial dataset contained more cross-sectional observations, but some municipalities have been removed from the sample owing to the lack of information for certain years. Although the sample contains just 256 of the 800 Catalan municipalities, its distribution by size does match that of the complete population of municipalities. We have to restrict our sample to Catalan municipalities due to the inability to have a long time series for the municipalities of other regions. However, note that since the financing system and the expenditure responsibilities of the municipalities are primarily determined by the central government, Catalan municipalities are a representative sample of all the Spanish municipalities (except from those in the Basque Country and Navarre, and to a lesser extent Canary Islands) 9 We have not scaled fiscal variables in terms of income due to the lack of elasticity of the municipal revenues in Spain. This is also the scale factor used by Buettner and Wildasin (2006) and Buettner (2007). the deficit and all the variables when expressed in differences are stationary 12 . The fact that the deficit is stationary is interesting in itself, indicating that the financial arrangements of Spanish municipalities ensure that budget adjustments occur after a shock with deficits eventually being reverted. In the rest of the paper we investigate how these adjustments are made (i.e., which budget components are involved). Notes: (1) Im, Pesaran and Shin (2003) unit root test, where H 0 : I(1). W tbar statistic is reported, which allows for serially correlated errors. Tests for variables in levels include time effects, except for the deficit. p: number of lags of the dependent variable considered in the regression to allow for serial correlation in the errors. All specifications include a constant.

F

F
(2) Pesaran (2007) unit root test, where H 0 : I(1) Z tbar statistic is reported, which allows for serially correlated errors and cross section dependence. Test for variables in levels include a time trend, except for the deficit. f: number of lags of the cross section average of lagged levels and first-differences of the dependent variable considered in the regression to allow for serial and cross sectional correlation.

(3) [ ]: P-value.

In ensuring the proper specification of the VECM, the first aspect to consider is the optimal lag length of the variables included in the model. The empirical literature 10 Im, Pesaran and Shin (2003) test belongs to the so called "first generation" panel unit root test, while Pesaran (2007) belongs to the "second generation". The main difference between them is that the second generation tests allow for cross-sectional dependencies.

11 Different orders of lag length (p=0,1,2) were used in computing the Im, Pesaran and Shin (2003) test to allow for serial correlation in the errors. 12 We also report the unit root statistics of the fiscal variables in levels. These statistics show that stationarity is rejected for own revenues and expenditures for all specifications and tests performed. However, the rejection of stationarity for grants and debt service depends on whether the test controls for cross-sectional correlation. et al, 1989;Dahlberg andJohansson, 1998 and2000). Moreover, Dahlberg and Johansson (2000) report that the estimation techniques that are generally adopted tend to reject too often a true null of no significance of the lags. Given the size of our sample and the empirical evidence, here, in order to specify the lag length of the model, we begin with three lags and test for a possible reduction in the number of lags in all the equations simultaneously. As the results in Table 3 show, a reduction of the lag length is always rejected 13 .

A second aspect of the model specification to consider is whether municipalityfixed effects are actually required. There is some theoretical controversy as regards the need to include them in the equations, since this would mean that we allow each municipality to converge to a different level of deficit, and thus some converge to deficits that are different from zero. Here, nevertheless, we decided to test the need to include them in the estimation. As shown in Table 3, we reject the presence of municipality-fixed effects, which means that all municipalities converge to the same level of deficit 14 . Thus, each of the equations is estimated by OLS without these municipality-fixed effects. Finally, each of the four equations has been estimated equation by equation. Given that the set of regressors is the same in all the equations, this procedure is asymptotically efficient and joint estimation does not improve efficiency (Baltagi, 1995). 13 As a robustness check, we have estimated the model with 4 lags and the GIRF computed are not significantly different from those obtained with 3 lags. 14 This test has been performed after estimating the equations by OLS, since the time dimension of our sample suggests that the Nickell (1981) bias should not be a major problem. Moreover, the performance of the GMM estimator with a relatively small number of municipalities is questionable.

Deleted: We also present some additional results when including yearfixed effects, which should control for those budget shocks that are common to all the municipalities (see section 4 for interpretation).

Empirical results

As we can see in Table 4, the estimated coefficients of the error correction term, i.e., the long-run reaction, show that Catalan municipalities converge toward the intertemporal budget constraint. A higher deficit has a positive impact on revenues and a negative impact on expenditures. On the revenue side, not only do own-source revenues react to an increase in the deficit, but grants do also. Thus, the adjustment is carried out simultaneously by municipalities and by upper tiers of government. (2) *** , ** & * = statistically significant at the 99, 95 and 90% levels.

Table 5 reports the present value of the GIRFs 15 computed from the estimates of the VECM 16 by fixing the discount rate at 3% and considering a ten-year period 17 . The 15 Each column of the table shows the present value response of all fiscal variables to a shock recorded in a given fiscal variable. Each row in the table captures how responsive a given fiscal variable is to shocks to itself and to other fiscal variables. 16 Table A1 in the appendix reports the estimated coefficients used to compute the GIRFs. 17 We report the generalized impulse-response function considering a 10-year period since the GIRFs show that at that point all the adjustment has been realized. After that point, the GIRFs 5 reports the responses of all the components to a shock of each of them (thus allowing the adjustment to be made to the variable that has experienced the shock too), while the bottom panel presents the response to a permanent increase in one of the variables for all the other variables. Notes: (1) Generalized Impulse Response Functions, GIRF (Pesaran and Shin, 1998).

(2) Bootstrap standard errors: 100 replications with replacement.

(3) *** , ** & * = statistically significant at the 99, 95 and 90% levels.

Main results. Several of our results are to be remarked. First, a 1€ positive (negative) shock18 to own-source revenues is followed by a reduction (increase) in future own revenues of 71 cents19 and an increase (decrease) in future expenditures of 26 cents (first column of Table 5). Grants and debt service do not react to an innovation are nearly flat lines. As a robustness check we have also computed the GIRFs considering a 20year period and obtained substantially the same results. We have also computed the present value of the GIRFs with different discount rates and the qualitative results do not change significantly. This can be explained by the fact that the largest share of the adjustment takes place quite quickly during the first few years of the period considered. estimate that an additional euro of own revenues offsets 97 cents in the primary surplus.

In the Spanish case, therefore, grants do not play any role in offsetting own-source revenues losses, while the adjustments that follow a deficit attributable to a revenue shortfall are borne entirely by the municipalities themselves. This is at odds both with the U.S., where grants offset 9 cents of own-source revenue shocks (Buettner and Wildasin, 2006), and with Germany, where equalization grants offset 15 cents of the shock (Buettner, 2007). This might reflect the low equalization power of the main unconditional grant that Spanish municipalities receive as well as the fact that many of the grants are earmarked as capital grants, the sum of which has to be matched by a municipality's resources. These results provide empirical evidence that grants have a more important role in the adjustment process when they have an equalization objective.

Second, the GIRFs also predict that an innovation to grants (third column) will be balanced by the response of the variable that experiences the shock, i.e. grants and expenditures. The response of own-source revenues to an innovation to grants is very low (just 2 cents, explaining 7% of the permanent increase), providing evidence of a very strong flypaper effect, which has been already obtained for Spain using different methodologies (e.g., Solé-Ollé, 2001;Bosch and Solé-Ollé, 2005). This result also differs markedly from that reported for the U.S. -where own revenues offset 14 cents of a grant shock and represented roughly a quarter of the adjustment-, but is more similar to that reported for Germany, where the revenues offset 4 cents of the innovation in grants (9% of the permanent increase). The several constraints on fiscal autonomy operating on local taxes in both countries might explain this result.

Third, when a 1€ innovation affects expenditures, the budget is balanced by a 73 cents reduction in future expenditures and by an increase of 8 and 16 cents in future 13 own-source revenues and grants, respectively. So, while higher tiers of government play no role in absorbing revenue shocks, their role is of paramount importance in the adjustment that follows an expenditure shock. Once again, this result is extreme: ownsource revenues in Spain play a similar role to that reported in Germany (where they offset 6 cents of an expenditure shock, since in both cases fiscal autonomy is restricted), but they have much less influence than in the U.S. (where they offset 16 cents of the shock). In the U.S. and Germany, however, grants play the same role in offsetting expenditure shocks (8 cents, approximately), which is much lower than in the Spanish case. Here again this might be due to the nature of intergovernmental grants in Spain.

There is empirical evidence that capital grants, given their discretionary allocation, are disproportionally allocated to municipalities facing population growth pressures, mainly caused by urban growth, (Solé-Ollé and Sorribas-Navarro, 2008), since these jurisdictions are the ones that can most readily justify the inadequacy of past facilities.

This might have generated a moral-hazard problem, with municipalities having the incentive to undertake excessive expansion since additional capital spending will always be financed (at least in the long run) by higher tiers of government (Solé-Ollé and Viladecans, 2008).

Fourth, we observe that a great share of the fiscal adjustment (70%) is held by the future value of the fiscal variable that experiences the shock. This figure is very similar to those reported in the case of spending for the U.S. and Germany. However, revenues and grants are less volatile in Germany (57% and 55%) and, particularly so, in the U.S. (35% and 47%). The higher volatility of Spanish local own-source revenues could be due to the fact that although the three main local taxes are quite stable (recall that these are the property tax, the business tax and the motor vehicle tax), this might not be the case of other taxes and user charges which are more closely linked to the real Deleted: On the one hand, the main driver of unconditional grants is weighted population, with weights rising steeply with population size. On the other hand, c

Deleted: Thus, in Spain, spending shocks arising from urban growth are partially offset by the higher tiers of government.

F o r P e e r R e v i e w 14 estate cycle (i.e., construction tax, tax on land transactions, building permits, etc.). In the case of grants, this might reflect the impact of capital grants, which are highly volatile, since they are not automatic and their discretional allocation.

Fifth, given this strong reversion effect, it could be interesting to compute the response to a 1€ permanent increase in each fiscal variable 20 . As we can see at the bottom of Table 5, a 1€ permanent increase in own-source revenues is basically followed by a spending decrease of a similar magnitude (recall that the other effectstop panel -were not statistically significant). Spanish grants, thus, provide less insurance than their German counterparts (34% of the permanent increase), but also even less than U.S. grants (13%). A permanent increase of 1€ in spending is followed by an increase in own-source revenues and grants of proportions 1/3 and 2/3. Note again that this suggests that higher tiers of government match local resources in a 2 to 1 proportion in order to finance additional expenditure needs, which we speculate are related to the urban expansion process. This proportion is just 1 to 1 in Germany and 1 to 2 in the U.S.. Intergovernmental grants in Germany and, especially, in Spain seem to be quite biased towards funding additional local expenses (particularly compared to the U.S. case), reaction that can arise a moral hazard problem. Finally, a permanent increase in grants leads to a higher level of spending, a situation that also occurs to a great extent in Germany, though not in the U.S..

Additional results.

In order to clarify the above results, we have performed some additional analyses. To save space, we only discuss the most interesting results and report the coefficients referred to in Table 6. First, we re-estimated the VECM including time effects so as to capture the common innovations in fiscal variables. Hence, in this 20 We compute the response to a permanent increase dividing the GIRF by the permanent component of the innovation. That is, in the case of a shock to own-source revenues, we divide the estimated response of the other fiscal variables by (1-0.709).

Deleted: This might have generated, at least in the Spanish case, a moral-hazard problem, with municipalities having the incentive to undertake excessive expansion since additional capital spending will always be financed (at least in the long run) by higher tiers of government (Solé-Ollé and Viladecans, 2008). Thus, that the viability of local financial systems does not depend on the type of shock (common or idiosyncratic) experienced. Second, we do not observe substantial differences in the adjustment pattern following an idiosyncratic shock. It should only be mentioned that grants are slightly more responsive to an idiosyncratic shock than to shocks that affect all the municipalities. For example, we show in Table 6 how a 1€ positive (negative) idiosyncratic innovation in revenues is followed by a statistically significant reduction (increase) of 5 cents in grants (recall that the response to general shocks was nearly zero), and a 1€ positive (negative) idiosyncratic innovation in expenditures is followed by an increase (decrease) in grants of 21 cents (this was just 16 cents in the case of a general shock). In the case of revenues, this should be interpreted as evidence that the 16 overall amount of grants to municipalities does not respond to the evolution in overall local tax revenues 21 , but that grants do respond (to some extent) to revenue shocks that are specific to a given municipality. In the case of capital grants, this might occur because a municipality dedicates greater efforts in applying for project grants after a revenue shortfall; in the case of current grants, this might be due to the equalization component, which despite its obvious shortcomings, could play some role in insuring against asymmetric shocks 22 . This result might also be due to very ad-hoc interventions by the central government in terms of their providing help to certain municipalities with revenue difficulties.

Third, given the importance of grants in the adjustment process we have estimated the VECM disaggregating grants in current and capital grants 23 . We observe in Table 6 that capital grants are more responsive than current grants. For example, when expenditures experience a 1€ shock, capital grants increase by 12 cents whereas current grants only increase by 4 cents. This difference, in absolute values, is even greater when we scale the response of grants by their quantitative importance. On average, capital grants provide around 1/3 of total resources granted. The importance of the reaction of capital grants is even higher in the case of an idiosyncratic shock (17 vs. 21 If grants tend to offset idiosyncratic shocks rather than general shocks, they should increase/decrease after a common positive/negative revenue shock. Note, for instance, that in Spain, the overall pool of unconditional grants to municipalities is indexed to the growth of central government revenues (see Suarez, 1999), which means that unconditional grants tend to fall during a downturn (when both municipal and central revenues decline). So, without significant ad-hoc interventions to provide more resources to the local sector, it is quite natural to see a decrease in the overall amount of grants during a downturn, exacerbating the procyclical nature of local own-source revenues. 22 The main reason for this different reaction is that equalization grants are allocated according to the relative position of municipalities. This relative position will more likely change when an idiosyncratic shock occurs than when there is a common shock to all municipalities. However, the reaction of this grant (that is the main current grant) is of a minor magnitude. 23 In general, the qualitative results provided by the estimation when adding one new variable are similar, although the precision of the estimates is not as great. Detailed results are available upon request. Fourth, since the adjustment pattern can be conditioned by the institutional environment, we have replicated the analysis considering only the smaller municipalities. In Spain, the institutional environment across municipalities varies with population size 24 . We qualify a municipality as small if it has less than 5 000 inhabitants.

We have fixed this as our threshold in order to obtain a representative sample of municipalities with the same institutional environment. Moreover, around 85% of Spanish municipalities have less than 5 000 inhabitants 25 . The main difference between the two samples is the slightly higher response of grants to shocks affecting small municipalities. Thus, the role of upper tiers of government in the fiscal adjustment process is more important in small municipalities than it is in their larger counterparts.

As Table 6 shows, when own-source revenues experience a 1€ shock in a small municipality, future grants fall 4 cents (7 cents in the case of an idiosyncratic shock). A positive 1€ expenditure shock in a small municipality implies an increase in future grants and own-source revenues of 18 and 4 cents, respectively (23 and 7 cents in the presence of an idiosyncratic shock). The importance of the upper tiers of government in the case of small municipalities could reflect a combination of factors. First, they have lower maximum ceilings on tax rates, which serve to constrain any reaction they might make through using their own-source revenues. Second, capital investment might be more volatile in small municipalities, due to the lumpiness of capital improvement projects. Third, they will almost certainly experience greater difficulties in obtaining credit. 24 We identify the following four institutional environments depending on the size of the municipality's population: i) 5 000 or fewer; ii) more than 5 000 but fewer than 20 000; iii) more than 20 000 but fewer than 50 000; and iv) more than 50 000 inhabitants. 25 In our sample 148 (of the 258) are small municipalities. We did not perform the analysis separately for the other institutional environment as we had few observations for each sample.

Conclusions

In this paper we have traced the dynamic adjustment process of local budgets in Spain. We have found that municipalities do adjust after a budget shock, and manage to balance their budgets after a period of some years. Municipalities respond to revenue shocks by adjusting both revenues and spending, with intergovernmental grants being of limited importance and only then in the case of idiosyncratic shocks. Grants do not seem to insure the entire local sector against revenue shocks, although they can provide some coverage for asymmetric shocks. The level of insurance is similar (but lower) to that provided in the U.S. but is quite at odds with the situation in Germany.

The adjustments made following an expenditure shock are, however, of a quite distinct nature. Here, grants play a more prominent role than own revenues, which contrasts markedly with the situation in Germany (where the two play a largely similar role) and in the U.S., where own-source revenues play the main role. We have shown that this reflects the greater reliance on ear-marked capital grants in Spain, which have great room for discretional allocation. This reliance on grants might have given rise to a moral-hazard problem: additional infrastructure needs generated by population growth are disproportionately funded by higher tiers of government, inducing municipalities to foster urban expansion without considering the full fiscal consequences of these policies (Solé-Ollé and Viladecans, 2007).

Our results provide empirical evidence that the fiscal adjustment pattern is conditioned by the institutional arrangements. We observe that grants have a more important role in the adjustment process when they have an equalization objective (as in Germany) or when there is no clear and objective rule that determines their allocation (as in Spain, capital grants). Own revenues have a lower adjustment capacity when Deleted: Clearly, by not being insured against revenue shortfalls, Spanish municipalities might not face the perverse incentives to abuse overly volatile sources of revenue (i.e., the local business tax) identified by Buettner (2007). Despite their high degree of autonomy, Spanish local governments have managed to keep the deficit under control, so that the system does in fact appear viable.

Deleted: Thus, while Spanish municipalities are perfectly autonomous and quite capable of funding their current spending, they are highly dependent on intergovernmental assistance when it comes to funding their capital spending. It might be argued, however, that most Spanish municipalities are too small to avoid being credit constrained and, as such, they need capital grants to fund their infrastructure projects. If this is indeed the case, the intervention of higher tiers of government is vital to ensure the viability of local government. We show, however, that while it is true that smaller municipalities are more dependent on grants to make adjustments to their budgets, their behavior does not differ that markedly from that of the larger municipalities. Finally, we speculate that t

Universitat de Barcelona & Institut d'Economia de Barcelona (IEB)

The aim of this paper is to analyze whether Spanish municipalities adjust in response to budget shocks and (if so) which elements of the budget they are more likely to adjust. The methodology we use to answer these questions is a vector error-correction model (VECM), estimated with data from a panel of Spanish municipalities during the period 1988-2006. Our results confirm that Spanish municipalities do indeed make adjustments in response to fiscal shocks (i.e., the deficit is stationary in the long run). We compare our results with those obtained for US and Germany to evaluate if the viability of local finance depends on the institutional arrangement and to analyze how it affects the adjustment patterns. We observe that grants have a more important role in the adjustment process in environments where either they have an equalization objective or where there is no clear rule that determines their distribution. This fact can generate a moral hazard problem: governments tend to spend more due to the expected intervention by the central government. Own revenues have a lower adjustment capacity in environments where subcentral governments have limited fiscal autonomy. These results, however, suggest that the viability of the local finance system is feasible with different institutional arrangements.

JEL codes: H70, H72, H77

Introduction

Local governments deliver a range of public services that have a strong impact on a community's quality of life. In most countries, they are responsible for refuse collection and recycling, water delivery and sewerage, street lighting and maintenance, public transportation, capital improvement construction, police, planning and land use regulations, and recreational and cultural facilities and programs. In some places, they are also involved in the provision of education, health and social services. Many scholars and international organizations currently advocate the virtues of the provision of these services by sub-national governments and, in particular, by local governments (see, e.g., the contributions in Brosio et al., 2008). However, there is less agreement as to how these local services should be funded. Traditional advice from 'fiscal federalism' scholars (see, e.g., Oates, 1972) recommends relying primarily on property taxes and user charges, but the U.S. experience with the imposition of property tax limitations has demonstrated the problems associated with this approach (e.g., Downes et al., 1998;Bradbury, 2001). And yet, other major taxes (e.g., income taxes) are often inappropriate given the size of local governments, and so the solution in the end is either the decentralization of minor and inefficient taxes or grant financing.

In these circumstances, such intergovernmental transfers serve to attenuate the inefficiencies of local tax systems and may help smooth spending and tax policy (Sala-i- Martin andSachs, 1992, von Hagen andEichengreen, 1996). However, recent studies also emphasize the perils of grant financing. First, grants can create a moral-hazard problem, with local governments, aware that intergovernmental grants provide insurance against budget shocks, pursuing overly risky policies (Persson and Tabellini, 1997). Second, grants might soften the local budget constraint (e.g., Wildasin, 1997;Rodden, 2000;Inman, 2001), creating incentives to run up excessive deficits that local governments expect to be covered by future grants. Third, grant financing may diffuse accountability (Rodden, 2000) and foster rent-seeking and clientelism (Devarajan et al., 2008), thus eroding the very benefits gained from spending decentralization. With its 2 virtues and perils, any final evaluation of grant financing has to be country specific, with the system depending on the particular details of the whole local government financing system (see, e.g., Rodden et al., 2003). This being the case, a promising avenue for research involves evaluating the viability of local finance systems in countries with different institutional arrangements. One way of conducting such an evaluation is to analyze whether local government budgets undergo any adjustments following a budget shock, and the role that is played by intergovernmental grants in this process. According to the three perils of grant financing just mentioned, we expect to observe, first, that grants that have an equalization objective will play an important role in the adjustment process and that can reduce the incentive to use fiscal autonomy, on the revenue and the expenditure side, to adjust after a budget shock. Nevertheless, on the revenue side, the extent to which own revenues can contribute to the fiscal adjustment is conditioned by their flexibility and the existence of normative restrictions.

Second, the lack of an objective and clear formula to determine the distribution of grants allows their use to provide fiscal assistance to subcentral governments in order to ensure the adjustment. Thus, discretionary grants can also reduce the incentives to control expenditures, which can generate a moral-hazard problem. This effect should be more pronounced when the central government cannot commit itself to a strict no bail out rule.

This research question has been previously addressed by Buettner and Wildasin (2005) and Buettner (2007) using data for U.S. and German local governments, respectively. Their results suggest that the system is viable in both countries, albeit that grants were found to play a more prominent role in the absorption of revenue shocks in the German case because of the role played by equalization transfers. Buettner (2007) suggests that the high degree of insurance might account for the greater reliance in Germany on the volatile local business tax.

In this paper we perform a similar analysis for the Spanish case. A number of specific institutional characteristics suggest that Spanish municipalities constitute an interesting case study (see Suárez-Pandiello, 1999, for a survey). First, as in the U.S.

and Germany, the municipalities are responsible for the provision of services Second, since the end of the 1980s, Spanish municipalities have been able to modify the tax rates of all taxes assigned to them, albeit subject to compulsory minimum tax rates (common to all municipalities) and ceilings (which grow with population size), which might serve to constrain their responses. The main local taxes are (in the following order) a property tax, a business tax, and a motor vehicle tax. These tax bases are quite inelastic 1 , which insures against large revenue shocks during downturns but also against automatic increases during times of boom 2 . Third, vertical unconditional transfers represent a third of current revenues and are formula-based, but they have a very low equalizing power (see, e.g., Suárez-Pandiello, 1999;Bosch and Solé-Ollé, 2005). Thus, they are more relevant than in the U.S. case, but they do not share the insurance properties of German transfers. Conditional grants play an important role in the financing of capital projects (a half of all investments being funded by them) and many of them require co-funding by own-revenues. They very rarely include an equalization component, and their allocation is largely discretional (Solé-Ollé and -Navarro, 2008). Finally, local debt is subject to certain ceilings, involving both the ratio between debt and current revenues and the short-term financial position.

Sorribas

However, the problems entailed in controlling these indicators effectively are enormous, and mean that successive Spanish governments have had great room to use arguably seem to be a less volatile tax system than the one operating in Germany.

Further, they are not subject to explicit equalization grants as their German counterparts are, while they can rely to a great extent on discretionary transfers to fund investment.

The results of our analysis should show us whether these institutional differences among Germany, US and Spain are reflected in different patterns of adjustment to budget shocks, specially focusing on the role of grants The methodology we adopt here closely mirrors that applied by Buettner and Wildasin (2006) and Buettner (2007). To trace the budget adjustment process, we use a vector error-correction model (VECM), estimated with panel data drawn from a set of Spanish municipalities during the period 1988-2006 4 . Our results confirm, first, that Spanish municipalities do adjust in response to fiscal shocks (i.e., the deficit is stationary in the long run). Second, we observe that the adjustment process is conditioned by the design of intergovernmental relationships.

After a revenue shock, grants play a more important role in the adjustment process when they have an equalization and/or insurance component. Adjustments to expenditure shocks are compensated to a larger extend by grants at institutional arrangements where their allocation criteria is not based on a clear and objective rule.

The rest of this paper is organized as follows. In the second section, we briefly present the analytical framework used here. In the third, we describe the data and the 3 Since 2002, with the enactment of the 'Budget Stability Law', the running up of deficits by any tier of government is forbidden (i.e., new debt should be used to fund past debt service).

Compliance with this law, however, has been minimal outside very big cities, with regional governments (which are responsible for the overseeing of local debt policies) still applying the older rules. 4 The model is very similar to the vector autoregression (VAR) used by Holtz-Eakin et al. (1989) and Dalhberg andJohansson (1998, 2000), the only difference being that the VEC model includes the deficit (considered as being stationary) in the estimated equations. Other papers that analyze subnational adjustment to fiscal shocks, but adopting different methodologies, include those by Poterba (1994), Rattso (1999) and Darby et al. (2005). No such studies have been undertaken of the Spanish case. we discuss the results and compare them with those obtained previously for other countries. In the final section, we conclude.

Analytical framework

The analytical framework employed here is similar to that employed in Buettner and Wildasin (2006) and Buettner (2007), who where the first to apply the methods previously used by Bohn (1991) and Hjelm (2001) in describing the dynamic fiscal adjustment of national governments to local government budgets. This procedure models budgetary adjustment to fiscal shocks through a vector error-correction model (VECM). If we distinguish the following four budgetary components: own-source revenues, R it , grants, G it , expenditures, E it , and debt service, DS it , we can express the VECM(p), using matrix notation, as follows:

it t p j j it j it u X X A X + + ∆ = ∆ - = - ∑ 1 1 γφ (1)
where ( )

it it it it it G DS E R X , , , = , ( )' 1 - , 1 , 1 , 1 - = φ and t X φ is the general deficit.
Since the estimation of the VECM provides a large number of parameters, which are difficult to interpret at first sight, we compute the generalized impulse-response functions (GIRFs hereinafter), following Pesaran and Shin (1998) 5 . The GIRFs project the response of each budgetary component in reaction to a shock, which is either to itself or to any other budgetary component. Moreover, the GIRFs consider the historical distribution of the residuals. That is, the GIRFs take into account the correlations 5 Prior to doing this, we use the recursive procedure proposed by Lütkepohl and Reimers (1992) to obtain the coefficients of the VAR(p+1) in levels derived from the VECM(p) and then the moving average (MA) representation of the VAR(p+1). between the fiscal variables and do not assume that if a shock occurs in one fiscal variable everything else remains constant. Thus, the GIRFs are invariant to the ordering of the variables in the VECM, and thereby overcome the main problem of the traditional IRF 6 . We summarize the information provided by the GIRFs when computing the present value of the fiscal adjustment process.

Analytically the GIRF is defined by the following expression:

( ) [ ] [ ] 1 - t 1 - t 1 - t I E I , E I , , h t k kt h t k X X X h GIRF + + - = = δ ε δ (2)
where h is the number of periods ahead, k δ represents a shock to variable k, and I t-1 is all the information available at the time of the shock. Thus, Equation 2 states that the GIRF for the vector X, h periods ahead, is the difference in the expected value (E) of X t+h , when taking the shock k δ into account. Pesaran and Shin (1998) demonstrate that if the innovation, kt ε , has a normal distribution, kt ε ∼ ( ) Σ , 0 , the GIRF of a δ shock to variable k can be expressed as follows:

( )

k kk k h X e h GIRF δ σ 1 1 - t I , 1 , - Σ Φ = (3)
where h Φ is the MA coefficient matrix at t+h, k e is a m × 1 selection vector, where m is the number of endogenous variables, with unity as its kth element and zero elsewhere 7 .

Data and model specification

Data. We use panel data for a 19-year period (1988-2006), including annual budgetary information for 258 municipalities in Catalonia, a Spanish region 8 . As in 6 By traditional IRF we refer to the IRF as computed by Sims (1987) and Hamilton (1994). The use of the GIRF rather than the IRF constitutes the main methodological difference with respect to Buettner and Wildasin (2006) and Buettner (2007). 7 We computed the bootstrap standard errors of the coefficients of the GIRFs by conducting 100 replications with replacement. 7 Buettner and Wildasin (2006), to maintain the parsimony of the model, we aggregate the budgetary data in four fiscal variables: own-source revenues, it R , grants, it G , expenditures, E it , and debt service, DS it . This decomposition on the revenue side allows us to estimate the role of grants in the adjustment process. All the variables have been deflated and are expressed in per capita terms 9 . Table 1 reports the definition of the four fiscal variables used in the analysis as well as their summary statistics. Model specification. Before estimating the model, it is important to check whether the basic hypothesis of the model holds, i.e., whether each of the fiscal variables in first differences as well as the deficit is stationary. We compute the Im, Pesaran and Shin 8 This information has been provided by the Public Audit Office of Catalonia (Sindicatura de Comptes de Catalunya), for the period 1988-2005, and by the Spanish Ministry of Economics and Finance, for the final year, 2006. This sample does not include information about the city of Barcelona. The initial dataset contained more cross-sectional observations, but some municipalities have been removed from the sample owing to the lack of information for certain years. Although the sample contains just 256 of the 800 Catalan municipalities, its distribution by size does match that of the complete population of municipalities. We have to restrict our sample to Catalan municipalities due to the inability to have a long time series for the municipalities of other regions. However, note that since the financing system and the expenditure responsibilities of the municipalities are primarily determined by the central government, Catalan municipalities are a representative sample of all the Spanish municipalities (except from those in the Basque Country and Navarre, and to a lesser extent Canary Islands) 9 We have not scaled fiscal variables in terms of income due to the lack of elasticity of the municipal revenues in Spain. This is also the scale factor used by Buettner and Wildasin (2006) and Buettner (2007). 2 11 . They show that the deficit and all the variables when expressed in differences are stationary 12 . The fact that the deficit is stationary is interesting in itself, indicating that the financial arrangements of Spanish municipalities ensure that budget adjustments occur after a shock with deficits eventually being reverted. In the rest of the paper we investigate how these adjustments are made (i.e., which budget components are involved). Notes: (1) Im, Pesaran and Shin (2003) unit root test, where H 0 : I(1). W tbar statistic is reported, which allows for serially correlated errors. Tests for variables in levels include time effects, except for the deficit. p: number of lags of the dependent variable considered in the regression to allow for serial correlation in the errors. All specifications include a constant. ( 2) Pesaran (2007) unit root test, where H 0 : I(1) Z tbar statistic is reported, which allows for serially correlated errors and cross section dependence. Test for variables in levels include a time trend, except for the deficit. f: number of lags of the cross section average of lagged levels and first-differences of the dependent variable considered in the regression to allow for serial and cross sectional correlation. ( 3) [ ]: P-value.

In ensuring the proper specification of the VECM, the first aspect to consider is the optimal lag length of the variables included in the model. The empirical literature 10 Im, Pesaran and Shin (2003) test belongs to the so called "first generation" panel unit root test, while Pesaran (2007) belongs to the "second generation". The main difference between them is that the second generation tests allow for cross-sectional dependencies.

11 Different orders of lag length (p=0,1,2) were used in computing the Im, Pesaran and Shin (2003) test to allow for serial correlation in the errors. 12 We also report the unit root statistics of the fiscal variables in levels. These statistics show that stationarity is rejected for own revenues and expenditures for all specifications and tests performed. However, the rejection of stationarity for grants and debt service depends on whether the test controls for cross-sectional correlation. et al, 1989;Dahlberg andJohansson, 1998 and2000). Moreover, Dahlberg and Johansson (2000) report that the estimation techniques that are generally adopted tend to reject too often a true null of no significance of the lags. Given the size of our sample and the empirical evidence, here, in order to specify the lag length of the model, we begin with three lags and test for a possible reduction in the number of lags in all the equations simultaneously. As the results in Table 3 show, a reduction of the lag length is always rejected13 .

A second aspect of the model specification to consider is whether municipalityfixed effects are actually required. There is some theoretical controversy as regards the need to include them in the equations, since this would mean that we allow each municipality to converge to a different level of deficit, and thus some converge to deficits that are different from zero. Here, nevertheless, we decided to test the need to include them in the estimation. As shown in Table 3, we reject the presence of municipality-fixed effects, which means that all municipalities converge to the same level of deficit14 . Thus, each of the equations is estimated by OLS without these municipality-fixed effects. Finally, each of the four equations has been estimated equation by equation. Given that the set of regressors is the same in all the equations, this procedure is asymptotically efficient and joint estimation does not improve efficiency (Baltagi, 1995).

Empirical results

As we can see in Table 4, the estimated coefficients of the error correction term, i.e., the long-run reaction, show that Catalan municipalities converge toward the intertemporal budget constraint. A higher deficit has a positive impact on revenues and a negative impact on expenditures. On the revenue side, not only do own-source revenues react to an increase in the deficit, but grants do also. Thus, the adjustment is carried out simultaneously by municipalities and by upper tiers of government. A1 in the appendix reports the estimated coefficients used to compute the GIRFs. 17 We report the generalized impulse-response function considering a 10-year period since the GIRFs show that at that point all the adjustment has been realized. After that point, the GIRFs 5 reports the responses of all the components to a shock of each of them (thus allowing the adjustment to be made to the variable that has experienced the shock too), while the bottom panel presents the response to a permanent increase in one of the variables for all the other variables. Notes: (1) Generalized Impulse Response Functions, GIRF (Pesaran and Shin, 1998).

(2) Bootstrap standard errors: 100 replications with replacement.

(3) *** , ** & * = statistically significant at the 99, 95 and 90% levels.

Main results. Several of our results are to be remarked. First, a 1€ positive (negative) shock 18 to own-source revenues is followed by a reduction (increase) in future own revenues of 71 cents 19 and an increase (decrease) in future expenditures of 26 cents (first column of Table 5). Grants and debt service do not react to an innovation are nearly flat lines. As a robustness check we have also computed the GIRFs considering a 20year period and obtained substantially the same results. We have also computed the present value of the GIRFs with different discount rates and the qualitative results do not change significantly. This can be explained by the fact that the largest share of the adjustment takes place quite quickly during the first few years of the period considered. 18 Note that having computed the GIRFs, we do not then analyze the effect of a shock on one fiscal variable assuming that the other fiscal variables remain constant, but rather we take into account the correlation between the fiscal variables. 19 This means that the level of own-source revenues, after the adjustment process, is 29 cents above the level before the shock occurred. estimate that an additional euro of own revenues offsets 97 cents in the primary surplus.

In the Spanish case, therefore, grants do not play any role in offsetting own-source revenues losses, while the adjustments that follow a deficit attributable to a revenue shortfall are borne entirely by the municipalities themselves. This is at odds both with the U.S., where grants offset 9 cents of own-source revenue shocks (Buettner and Wildasin, 2006), and with Germany, where equalization grants offset 15 cents of the shock (Buettner, 2007). This might reflect the low equalization power of the main unconditional grant that Spanish municipalities receive as well as the fact that many of the grants are earmarked as capital grants, the sum of which has to be matched by a municipality's resources. These results provide empirical evidence that grants have a more important role in the adjustment process when they have an equalization objective.

Second, the GIRFs also predict that an innovation to grants (third column) will be balanced by the response of the variable that experiences the shock, i.e. grants and expenditures. The response of own-source revenues to an innovation to grants is very low (just 2 cents, explaining 7% of the permanent increase), providing evidence of a very strong flypaper effect, which has been already obtained for Spain using different methodologies (e.g., Solé-Ollé, 2001;Bosch and Solé-Ollé, 2005). This result also differs markedly from that reported for the U.S. -where own revenues offset 14 cents of a grant shock and represented roughly a quarter of the adjustment-, but is more similar to that reported for Germany, where the revenues offset 4 cents of the innovation in grants (9% of the permanent increase). The several constraints on fiscal autonomy operating on local taxes in both countries might explain this result.

Third, when a 1€ innovation affects expenditures, the budget is balanced by a 73 cents reduction in future expenditures and by an increase of 8 and 16 cents in future 13 own-source revenues and grants, respectively. So, while higher tiers of government play no role in absorbing revenue shocks, their role is of paramount importance in the adjustment that follows an expenditure shock. Once again, this result is extreme: ownsource revenues in Spain play a similar role to that reported in Germany (where they offset 6 cents of an expenditure shock, since in both cases fiscal autonomy is restricted), but they have much less influence than in the U.S. (where they offset 16 cents of the shock). In the U.S. and Germany, however, grants play the same role in offsetting expenditure shocks (8 cents, approximately), which is much lower than in the Spanish case. Here again this might be due to the nature of intergovernmental grants in Spain.

There is empirical evidence that capital grants, given their discretionary allocation, are disproportionally allocated to municipalities facing population growth pressures, mainly caused by urban growth, (Solé-Ollé and Sorribas-Navarro, 2008), since these jurisdictions are the ones that can most readily justify the inadequacy of past facilities.

This might have generated a moral-hazard problem, with municipalities having the incentive to undertake excessive expansion since additional capital spending will always be financed (at least in the long run) by higher tiers of government (Solé-Ollé and Viladecans, 2008).

Fourth, we observe that a great share of the fiscal adjustment (70%) is held by the future value of the fiscal variable that experiences the shock. This figure is very similar to those reported in the case of spending for the U.S. and Germany. However, revenues and grants are less volatile in Germany (57% and 55%) and, particularly so, in the U.S. (35% and 47%). The higher volatility of Spanish local own-source revenues could be due to the fact that although the three main local taxes are quite stable (recall that these are the property tax, the business tax and the motor vehicle tax), this might not be the case of other taxes and user charges which are more closely linked to the real 14 estate cycle (i.e., construction tax, tax on land transactions, building permits, etc.). In the case of grants, this might reflect the impact of capital grants, which are highly volatile, since they are not automatic and their discretional allocation.

Fifth, given this strong reversion effect, it could be interesting to compute the response to a 1€ permanent increase in each fiscal variable 20 . As we can see at the bottom of Table 5, a 1€ permanent increase in own-source revenues is basically followed by a spending decrease of a similar magnitude (recall that the other effectstop panel -were not statistically significant). Spanish grants, thus, provide less insurance than their German counterparts (34% of the permanent increase), but also even less than U.S. grants (13%). A permanent increase of 1€ in spending is followed by an increase in own-source revenues and grants of proportions 1/3 and 2/3. Note again that this suggests that higher tiers of government match local resources in a 2 to 1 proportion in order to finance additional expenditure needs, which we speculate are related to the urban expansion process. This proportion is just 1 to 1 in Germany and 1 to 2 in the U.S.. Intergovernmental grants in Germany and, especially, in Spain seem to be quite biased towards funding additional local expenses (particularly compared to the U.S. case), reaction that can arise a moral hazard problem. Finally, a permanent increase in grants leads to a higher level of spending, a situation that also occurs to a great extent in Germany, though not in the U.S..

Additional results.

In order to clarify the above results, we have performed some additional analyses. To save space, we only discuss the most interesting results and report the coefficients referred to in Table 6. First, we re-estimated the VECM including time effects so as to capture the common innovations in fiscal variables. Hence, in this 20 We compute the response to a permanent increase dividing the GIRF by the permanent component of the innovation. That is, in the case of a shock to own-source revenues, we divide the estimated response of the other fiscal variables by (1-0.709). Thus, that the viability of local financial systems does not depend on the type of shock (common or idiosyncratic) experienced. Second, we do not observe substantial differences in the adjustment pattern following an idiosyncratic shock. It should only be mentioned that grants are slightly more responsive to an idiosyncratic shock than to shocks that affect all the municipalities. For example, we show in Table 6 how a 1€ positive (negative) idiosyncratic innovation in revenues is followed by a statistically significant reduction (increase) of 5 cents in grants (recall that the response to general shocks was nearly zero), and a 1€ positive (negative) idiosyncratic innovation in expenditures is followed by an increase (decrease) in grants of 21 cents (this was just 16 cents in the case of a general shock). In the case of revenues, this should be interpreted as evidence that the overall amount of grants to municipalities does not respond to the evolution in overall local tax revenues 21 , but that grants do respond (to some extent) to revenue shocks that are specific to a given municipality. In the case of capital grants, this might occur because a municipality dedicates greater efforts in applying for project grants after a revenue shortfall; in the case of current grants, this might be due to the equalization component, which despite its obvious shortcomings, could play some role in insuring against asymmetric shocks 22 . This result might also be due to very ad-hoc interventions by the central government in terms of their providing help to certain municipalities with revenue difficulties.

Third, given the importance of grants in the adjustment process we have estimated the VECM disaggregating grants in current and capital grants 23 . We observe in Table 6 that capital grants are more responsive than current grants. For example, when expenditures experience a 1€ shock, capital grants increase by 12 cents whereas current grants only increase by 4 cents. This difference, in absolute values, is even greater when we scale the response of grants by their quantitative importance. On average, capital grants provide around 1/3 of total resources granted. The importance of the reaction of capital grants is even higher in the case of an idiosyncratic shock (17 vs. 21 If grants tend to offset idiosyncratic shocks rather than general shocks, they should increase/decrease after a common positive/negative revenue shock. Note, for instance, that in Spain, the overall pool of unconditional grants to municipalities is indexed to the growth of central government revenues (see Suarez, 1999), which means that unconditional grants tend to fall during a downturn (when both municipal and central revenues decline). So, without significant ad-hoc interventions to provide more resources to the local sector, it is quite natural to see a decrease in the overall amount of grants during a downturn, exacerbating the procyclical nature of local own-source revenues. 22 The main reason for this different reaction is that equalization grants are allocated according to the relative position of municipalities. This relative position will more likely change when an idiosyncratic shock occurs than when there is a common shock to all municipalities. However, the reaction of this grant (that is the main current grant) is of a minor magnitude. 23 In general, the qualitative results provided by the estimation when adding one new variable are similar, although the precision of the estimates is not as great. Detailed results are available upon request. Fourth, since the adjustment pattern can be conditioned by the institutional environment, we have replicated the analysis considering only the smaller municipalities. In Spain, the institutional environment across municipalities varies with population size 24 . We qualify a municipality as small if it has less than 5 000 inhabitants.

We have fixed this as our threshold in order to obtain a representative sample of municipalities with the same institutional environment. Moreover, around 85% of Spanish municipalities have less than 5 000 inhabitants 25 . The main difference between the two samples is the slightly higher response of grants to shocks affecting small municipalities. Thus, the role of upper tiers of government in the fiscal adjustment process is more important in small municipalities than it is in their larger counterparts.

As Table 6 shows, when own-source revenues experience a 1€ shock in a small municipality, future grants fall 4 cents (7 cents in the case of an idiosyncratic shock). A positive 1€ expenditure shock in a small municipality implies an increase in future grants and own-source revenues of 18 and 4 cents, respectively (23 and 7 cents in the presence of an idiosyncratic shock). The importance of the upper tiers of government in the case of small municipalities could reflect a combination of factors. First, they have lower maximum ceilings on tax rates, which serve to constrain any reaction they might make through using their own-source revenues. Second, capital investment might be more volatile in small municipalities, due to the lumpiness of capital improvement projects. Third, they will almost certainly experience greater difficulties in obtaining credit. 24 We identify the following four institutional environments depending on the size of the municipality's population: i) 5 000 or fewer; ii) more than 5 000 but fewer than 20 000; iii) more than 20 000 but fewer than 50 000; and iv) more than 50 000 inhabitants. 25 In our sample 148 (of the 258) are small municipalities. We did not perform the analysis separately for the other institutional environment as we had few observations for each sample.

Conclusions

In this paper we have traced the dynamic adjustment process of local budgets in Spain. We have found that municipalities do adjust after a budget shock, and manage to balance their budgets after a period of some years. Municipalities respond to revenue shocks by adjusting both revenues and spending, with intergovernmental grants being of limited importance and only then in the case of idiosyncratic shocks. Grants do not seem to insure the entire local sector against revenue shocks, although they can provide some coverage for asymmetric shocks. The level of insurance is similar (but lower) to that provided in the U.S. but is quite at odds with the situation in Germany.

The adjustments made following an expenditure shock are, however, of a quite distinct nature. Here, grants play a more prominent role than own revenues, which contrasts markedly with the situation in Germany (where the two play a largely similar role) and in the U.S., where own-source revenues play the main role. We have shown that this reflects the greater reliance on ear-marked capital grants in Spain, which have great room for discretional allocation. This reliance on grants might have given rise to a moral-hazard problem: additional infrastructure needs generated by population growth are disproportionately funded by higher tiers of government, inducing municipalities to foster urban expansion without considering the full fiscal consequences of these policies (Solé-Ollé and Viladecans, 2007).

Our results provide empirical evidence that the fiscal adjustment pattern is conditioned by the institutional arrangements. We observe that grants have a more important role in the adjustment process when they have an equalization objective (as in Germany) or when there is no clear and objective rule that determines their allocation (as in Spain, capital grants). Own revenues have a lower adjustment capacity when

  local governments (as cited at the beginning of this paper), but they have limited responsibilities in the fields of education, health and social services.

  an adjustment 3 . So, in short, Spanish local governments have similar responsibilities and tax possibilities to those enjoyed by the U.S. cities and what would arguably seem to be a less volatile tax system than the one operating in Germany.

  . If we sum up the reaction of own revenues and expenditures, we

  parameters estimated only describe the adjustment of budget components to idiosyncratic shocks. The estimated coefficients of the error correction term and the present values of the GIRFs show that Catalan municipalities converge toward the intertemporal budget constraint, also when they experience an idiosyncratic shock, with estimates of the error correction parameter that are very similar to those obtained earlier.

  . This result suggests that capital grants are the ones that generate the moral hazard problem.

  constrained fiscal autonomy on them (as in Spain and Germany).

  local governments (as cited at the beginning of this paper), but they have limited responsibilities in the fields of education, health and social services.

  to ensure the model is correctly specified. In the fourth section,

  and thePesaran (2007) unit root statistics 10 , which are fairly quite standard in the panel data literature and they allows for heterogeneous constants and slopes across cross-sections andPesaran (2007) controls for cross-sectional correlation. Results for the variables both in differences and in levels are presented in Table

  the dynamic relationship between local government revenues and expenditures mainly takes place in a period of between two to four years (Holtz-Eakin

  . If we sum up the reaction of own revenues and expenditures, we

  parameters estimated only describe the adjustment of budget components to idiosyncratic shocks. The estimated coefficients of the error correction term and the present values of the GIRFs show that Catalan municipalities converge toward the intertemporal budget constraint, also when they experience an idiosyncratic shock, with estimates of the error correction parameter that are very similar to those obtained earlier.

  . This result suggests that capital grants are the ones that generate the moral hazard problem.

  constrained fiscal autonomy on them (as in Spain and Germany).

  Buettner and Wildasin (2006), to maintain the parsimony of the model, we aggregate the budgetary data in four fiscal variables: own-source revenues, it R , grants, it G , expenditures, E it , and debt service, DS it . This decomposition on the revenue side allows us to estimate the role of grants in the adjustment process. All the variables have been deflated and are expressed in per capita terms9 . Table1reports the definition of the four fiscal variables used in the analysis as well as their summary statistics.

		Table 1: Summary statistics and definition of the variables (€ 2006 per capita)
			Mean	St.Dev.	Definition 1
	R	Own Revenues	533.988 436.905 Items I, II, III,V and VI of Revenue Budget
	G	Grants	346.779 479.534 Items IV and VII of Revenue Budget
	E	Expenditures	805.668 627.609 Items I, II, IV, VI and VII of Exp. Budget
	DS Debt service	34.496	73.276 Item III of Expenditure Budget
	D	Deficit	-39.603 403.677 E it + DS it -R it -G it
	Note: The definition of the fiscal variables is based in the chapters of the economic classification of the budget. Revenues: I: direct taxes; II: indirect taxes; III: user charges; IV: current grants; V: assets' revenues; VI: real investment sales; VII: capital grants. Expenditures: I: wages and salaries; II: purchases o r of goods and services; III: debt service; IV: current grants; VI real investment; VII: capital grants.
	Model specification. Before estimating the model, it is important to check whether P the basic hypothesis of the model holds, i.e., whether each of the fiscal variables in first e r e differences as well as the deficit is stationary. We compute the Im, Pesaran and Shin
				R
	8 This information has been provided by the Public Audit Office of Catalonia (Sindicatura de e Comptes de Catalunya), for the period 1988-2005, and by the Spanish Ministry of Economics and Finance, for the final year, 2006. This sample does not include information about the city of v e i Barcelona.
				w
				7

Table 2 :

 2 Unit root tests

		Im, Pesaran and Shin (2003)	Pesaran (2007)
		p=0	p=1	p=2	f=1	f=2
	∆ R	-79.761 [0.000]	-36.531 [0.000]	-20.849 [0.000]	-29.325 [0.000]	-11.326 [0.000]
	∆ G	-80.438 [0.000]	-40.142 [0.000]	-19.151 [0.000]	-34.126 [0.000]	-12.107 [0.000]
	∆ E	-78.238 [0.000]	-41.960 [0.000]	-19.597 [0.000]	-35.157 [0.000]	-14.901 [0.000]
	∆ DS	-5.014 [0.000]	-4.159 [0.000]	-3.542 [0.000]	-11.932 [0.000]	-8.268 [0.000]
	D	-30.529 [0.000]	-9.500 [0.000]	-5.328 [0.000]	-16.203 [0.000]	-6.077 [0.000]
	R	-0.156 [0.438]	0.032 [0.513]	0.654 [0.743]	3.415 [1.000]	7.488 [1.000]
	G	-8.464 [0.000]	-5.565 [0.000]	-5.180 [0.000]	1.742 [0.913]	2.744 [0.997]
	E	7.190 [1.000]	8.129 [1.000]	7.289 [1.000]	2.014 [1.000]	1.618 [0.947]
	DS	-11.973 [0.000]	-9.632 [0.000]	-9.095 [0.000]	1.082 [0.860]	5.096 [1.000]

Table 3 :

 3 Specification tests

	a.-Municipality-fixed effects?
		With lag length= 3	With lag length= 2
	χ 2 (1,032)	953.57 [0.961]	857.28 [1.000]
	b.-Lag order
		3 → 2	2 → 1
	χ 2 (16)	66.94 [0.000]	87.13 [0.000]

Note: (1) Likelihood-ratio statistics on cross-equation restrictions; (2) [ ]: P-value.

Table 4 :

 4 Estimates for the error correction term

	Grants (G)	0.358 *** (0.149)
	Debt service (DS)	0.021 **	(0.010)

Equation γ

Own Revenues (R) 0.294 *** (0.102)

Expenditures (E) -0.523 *** (0.164)

Notes: (1) Heteroscedasticity robust standard errors in parentheses.

Table 5 :

 5 Present value generalized impulse response functions

		Innovation to:
	Response of:	R	E	G	DS
	Own Revenues (R)	-0.709 ***	0.085 **	-0.018	0.515 *
		(0.038)	(0.042)	(0.016)	(0.286)
	Expenditures (E)	0.261 ***	-0.729 ***	0.289 ***	-0.080
		(0.036)	(0.027)	(0.049)	(0.496)
	Grants (G)	-0.007	0.158 ***	-0.726 ***	0.229
		(0.046)	(0.047)	(0.062)	(0.332)
	Debt service (DS)	0.024	-0.027	0.003	-0.450 **
		(0.015)	(0.017)	(0.008)	(0.129)
		Response to permanent increase
	Own Revenues (R)		0.314 **	-0.066	0.776 *
			(0.047)	(0.041)	(0.169)
	Expenditures (E)	0.896 ***		1.055 ***	-0.121
		(0.029)		(0.030)	(0.220)
	Grants (G)	-0.026	0.583 ***		0.345
		(0.036)	(0.035)		(0.301)
	Debt service (DS)	0.082	-0.099	0.011
		(0.078)	(0.063)	(0.016)

Table 6 :

 6 Present value generalized impulse response functions: selected coefficients Each cell in this row has been obtained by estimating the model with a different sample; (2) The coefficients of current and capital grants has been estimated from a model which includes both variables at the same time; (3) Results obtaining after controlling for time-effects.

		Innovation to own revenues	Innovation to expenditures
			Current	Capital		Current	Capital	Own
	Response of Grants	Grants (2)	Grants (2)	Grants	Grants (2)	Grants (2)	revenues (2)
	All sample	-0.007	0.008	-0.015 *	0.158 ***	0.042 *	0.117 ***	0.085 **
		(0.046)	(0.051)	(0.009)	(0.047)	(0.025)	(0.041)	(0.042)
	Small mun (1) -0.038 *	-0.011 *	-0.019 **	0.178 ***	0.038 *	0.141 ***	0.038 **
		(0.023)	(0.006)	(0.009)	(0.039)	(0.021)	(0.039)	(0.019)
	Response of	Idiosyncratic innovation to own rev. (3)	Idiosyncratic innovation to expenditures (3)
			Current	Capital		Current	Capital	Own
	Response of Grants	Grants	Grants	Grants	Grants (2)	Grants (2)	revenues (2)
	All sample	-0.054 *	-0.015 *	-0.023 **	0.213 ***	0.038 *	0.169 ***	0.087 **
		(0.029)	(0.009)	(0.011)	(0.052)	(0.023)	(0.045)	(0.041)
	Small mun (1) -0.074 ***	-0.027 *	-0.021 ***	0.226 ***	0.040 *	0.189 ***	0.066 ***
		(0.031)	(0.015)	(0.009)	(0.054)	(0.022)	(0.049)	(0.028)
	Notes: (1)

Table A1 :

 A1 Detailed estimation results for the basic model

		R it	E it	G it	DS it
	D it-1	0.294 ***	-0.523 ***	0.358 **	0.021 **
		(0.101)	(0.164)	(0.149)	(0.010)
	∆ R it-1	-0.453 ***	-0.348 **	0.230	0.008
		(0.099)	(0.162)	(0.141)	(0.011)
	∆ E it-1	-0.218 ***	-0.476 ***	-0.313 **	-0.002
		(0.084)	(0.145)	(0.142)	(0.010)
	∆ G it-1	0.307 ***	-0.214	-0.499 ***	-0.004
		(0.086)	(0.144)	(0.143)	(0.009)
	∆ DS it-1	-1.055	-0.281	-0.115	0.011
		(0.666)	(0.897)	(0.670)	(0.174)
	∆ R it-2	-0.252 ***	-0.485 ***	-0.022	0.028 ***
		(0.094)	(0.160)	(0.123)	(0.009)
	∆ E it-2	-0.159 **	-0.068	0.007	-0.024 ***
	(0.072) 0.195 ** (0.076) -0.019 (0.623) -0.132 *** F ∆ G it-2 ∆ DS it-2 ∆ R it-3 o r	(0.110) -0.203 * (0.116) 0.674 (0.845) -0.321 ***	(0.103) -0.390 *** (0.120) -0.685 (0.734) -0.076	(0.008) 0.013 * (0.007) -0.101 (0.074) 0.007
		(0.051)	(0.112)	(0.098)	(0.007)
	∆ E it-3 ∆ G it-3 ∆ DS it-3 Constant	-0.061 (0.045) 0.093 * P 0.008 (0.072) -0.192 ** (0.050) (0.080) 1.524 *** 3.108 *** e (0.433) (0.985) 45.897 *** 17.739 * (4.943) (9.133) e 0.024 (0.083) -0.268 ** (0.104) 1.021 (0.699) 38.837 *** (7.180) r	-0.006 (0.005) -0.000 (0.004) -0.075 (0.085) 17.194 *** (1.231)
	Obs. R-squared	3 870 0.325	3 870 0.425	3 870 0.463 R	3 870 0.085
	Note: Heteroscedasticity robust standard errors in parenthesis. e
				v i e
					w

The dynamic adjustment of local government budgets: does Spain behave differently?

	Albert Solé-Ollé & Pilar Sorribas-Navarro *

  an adjustment 3 . So, in short, Spanish local governments have similar responsibilities and tax possibilities to those enjoyed by the U.S. cities and what would

	deficits to make
	F o r
	P
	e
	e r
	R
	e
	v i e
	w
	1 Unlike its German counterpart, Spain's local business tax (Impuesto sobre Actividades
	Económicas) is a presumptive tax, with a tax base computed using simple indicators of
	economic activity (e.g., surface area, electricity usage, number of workers, sectoral
	classification, see Jofre-Monseny and Solé-Ollé, 2008), which makes it less volatile than the
	German tax.
	4

2

Other local taxes are a construction tax and a tax on land value improvements, which tend to become important during housing booms, and as such are quite volatile. This would seem to modify our conclusion, therefore, regarding the elasticity of the main taxes.

Table 1 :

 1 Summary statistics and definition of the variables(€ 2006 per capita)

			Mean	St.Dev.	Definition 1
	R	Own Revenues	533.988 436.905 Items I, II, III,V and VI of Revenue Budget
	G	Grants	346.779 479.534 Items IV and VII of Revenue Budget
	E	Expenditures	805.668 627.609 Items I, II, IV, VI and VII of Exp. Budget
	DS	Debt service	34.496	73.276 Item III of Expenditure Budget
	D	Deficit	-39.603 403.677 E

it + DS it -R it -G it

Note: The definition of the fiscal variables is based in the chapters of the economic classification of the budget. Revenues: I: direct taxes; II: indirect taxes; III: user charges; IV: current grants; V: assets' revenues; VI: real investment sales; VII: capital grants. Expenditures: I: wages and salaries; II: purchases of goods and services; III: debt service; IV: current grants; VI real investment; VII: capital grants.

Table 2 :

 2 Unit root tests

		Im, Pesaran and Shin (2003)	Pesaran (2007)
		p=0	p=1	p=2	f=1	f=2
	∆ R	-79.761 [0.000]	-36.531 [0.000]	-20.849 [0.000]	-29.325 [0.000]	-11.326 [0.000]
	∆ G	-80.438 [0.000]	-40.142 [0.000]	-19.151 [0.000]	-34.126 [0.000]	-12.107 [0.000]
	∆ E	-78.238 [0.000]	-41.960 [0.000]	-19.597 [0.000]	-35.157 [0.000]	-14.901 [0.000]
	∆ DS	-5.014 [0.000]	-4.159 [0.000]	-3.542 [0.000]	-11.932 [0.000]	-8.268 [0.000]
	D	-30.529 [0.000]	-9.500 [0.000]	-5.328 [0.000]	-16.203 [0.000]	-6.077 [0.000]
	R	-0.156 [0.438]	0.032 [0.513]	0.654 [0.743]	3.415 [1.000]	7.488 [1.000]
	G	-8.464 [0.000]	-5.565 [0.000]	-5.180 [0.000]	1.742 [0.913]	2.744 [0.997]
	E	7.190 [1.000]	8.129 [1.000]	7.289 [1.000]	2.014 [1.000]	1.618 [0.947]
	DS	-11.973 [0.000]	-9.632 [0.000]	-9.095 [0.000]	1.082 [0.860]	5.096 [1.000]

Table 3 :

 3 Specification tests

	a.-Municipality-fixed effects?
		With lag length= 3	With lag length= 2
	χ 2 (1,032)	953.57 [0.961]	857.28 [1.000]
	b.-Lag order
		3 → 2	2 → 1
	χ 2 (16)	66.94 [0.000]	87.13 [0.000]
	Note: (1) Likelihood-ratio statistics on cross-equation restrictions; (2)
	[ ]: P-value.

Table 4 :

 4 Estimates for the error correction term

	Equation	γ
	Own Revenues (R)	0.294 *** (0.102)
	Expenditures (E)	-0.523 *** (0.164)
	Grants (G)	0.358 *** (0.149)
	Debt service (DS)	0.021 ** (0.010)
	Notes: (1) Heteroscedasticity robust standard errors in parentheses.
	(2) *** , ** & * = statistically significant at the 99, 95 and 90% levels.

Table 5

 5 reports the present value of the GIRFs 15 computed from the estimates of the VECM 16 by fixing the discount rate at 3% and considering a ten-year period 17 . The 15 Each column of the table shows the present value response of all fiscal variables to a shock recorded in a given fiscal variable. Each row in the table captures how responsive a given fiscal variable is to shocks to itself and to other fiscal variables.

16

Table

Table 5 :

 5 Present value generalized impulse response functions

		Innovation to:
	Response of:	R	E	G	DS
	Own Revenues (R)	-0.709 ***	0.085 **	-0.018	0.515 *
		(0.038)	(0.042)	(0.016)	(0.286)
	Expenditures (E)	0.261 ***	-0.729 ***	0.289 ***	-0.080
		(0.036)	(0.027)	(0.049)	(0.496)
	Grants (G)	-0.007	0.158 ***	-0.726 ***	0.229
		(0.046)	(0.047)	(0.062)	(0.332)
	Debt service (DS)	0.024	-0.027	0.003	-0.450 **
		(0.015)	(0.017)	(0.008)	(0.129)
		Response to permanent increase
	Own Revenues (R)		0.314 **	-0.066	0.776 *
			(0.047)	(0.041)	(0.169)
	Expenditures (E)	0.896 ***		1.055 ***	-0.121
		(0.029)		(0.030)	(0.220)
	Grants (G)	-0.026	0.583 ***		0.345
		(0.036)	(0.035)		(0.301)
	Debt service (DS)	0.082	-0.099	0.011
		(0.078)	(0.063)	(0.016)

Table 6 :

 6 Present value generalized impulse response functions: selected coefficients Each cell in this row has been obtained by estimating the model with a different sample; (2) The coefficients of current and capital grants has been estimated from a model which includes both variables at the same time; (3) Results obtaining after controlling for time-effects.

		Innovation to own revenues	Innovation to expenditures
			Current	Capital		Current	Capital	Own
	Response of Grants	Grants (2)	Grants (2)	Grants	Grants (2)	Grants (2)	revenues (2)
	All sample	-0.007	0.008	-0.015 *	0.158 ***	0.042 *	0.117 ***	0.085 **
		(0.046)	(0.051)	(0.009)	(0.047)	(0.025)	(0.041)	(0.042)
	Small mun (1) -0.038 *	-0.011 *	-0.019 **	0.178 ***	0.038 *	0.141 ***	0.038 **
		(0.023)	(0.006)	(0.009)	(0.039)	(0.021)	(0.039)	(0.019)
	Response of	Idiosyncratic innovation to own rev. (3)	Idiosyncratic innovation to expenditures (3)
			Current	Capital		Current	Capital	Own
	Response of Grants	Grants	Grants	Grants	Grants (2)	Grants (2)	revenues (2)
	All sample	-0.054 *	-0.015 *	-0.023 **	0.213 ***	0.038 *	0.169 ***	0.087 **
		(0.029)	(0.009)	(0.011)	(0.052)	(0.023)	(0.045)	(0.041)
	Small mun (1) -0.074 ***	-0.027 *	-0.021 ***	0.226 ***	0.040 *	0.189 ***	0.066 ***
		(0.031)	(0.015)	(0.009)	(0.054)	(0.022)	(0.049)	(0.028)
	Notes: (1)

Table A1 :

 A1 Detailed estimation results for the basic model

		R it	E it	G it	DS it
	D it-1	0.294 ***	-0.523 ***	0.358 **	0.021 **
		(0.101)	(0.164)	(0.149)	(0.010)
	∆ R it-1	-0.453 ***	-0.348 **	0.230	0.008
		(0.099)	(0.162)	(0.141)	(0.011)
	∆ E it-1	-0.218 ***	-0.476 ***	-0.313 **	-0.002
		(0.084)	(0.145)	(0.142)	(0.010)
	∆ G it-1	0.307 ***	-0.214	-0.499 ***	-0.004
		(0.086)	(0.144)	(0.143)	(0.009)
	∆ DS it-1	-1.055	-0.281	-0.115	0.011
		(0.666)	(0.897)	(0.670)	(0.174)
	∆ R it-2	-0.252 ***	-0.485 ***	-0.022	0.028 ***
		(0.094)	(0.160)	(0.123)	(0.009)
	∆ E it-2	-0.159 **	-0.068	0.007	-0.024 ***
		(0.072)	(0.110)	(0.103)	(0.008)
	∆ G it-2	0.195 **	-0.203 *	-0.390 ***	0.013 *
		(0.076)	(0.116)	(0.120)	(0.007)
	∆ DS it-2	-0.019	0.674	-0.685	-0.101
		(0.623)	(0.845)	(0.734)	(0.074)
	∆ R it-3	-0.132 ***	-0.321 ***	-0.076	0.007
		(0.051)	(0.112)	(0.098)	(0.007)
	∆ E it-3	-0.061	0.008	0.024	-0.006
		(0.045)	(0.072)	(0.083)	(0.005)
	∆ G it-3	0.093 *	-0.192 **	-0.268 **	-0.000
		(0.050)	(0.080)	(0.104)	(0.004)
	∆ DS it-3	1.524 ***	3.108 ***	1.021	-0.075
		(0.433)	(0.985)	(0.699)	(0.085)
	Constant	45.897 ***	17.739 *	38.837 ***	17.194 ***
		(4.943)	(9.133)	(7.180)	(1.231)
	Obs.	3 870	3 870	3 870	3 870
	R-squared	0.325	0.425	0.463	0.085

Note: Heteroscedasticity robust standard errors in parenthesis.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

Note that having computed the GIRFs, we do not then analyze the effect of a shock on one fiscal variable assuming that the other fiscal variables remain constant, but rather we take into account the correlation between the fiscal variables.

This means that the level of own-source revenues, after the adjustment process, is 29 cents above the level before the shock occurred.

As a robustness check, we have estimated the model with 4 lags and the GIRF computed are not significantly different from those obtained with 3 lags.

This test has been performed after estimating the equations by OLS, since the time dimension of our sample suggests that theNickell (1981) bias should not be a major problem. Moreover, the performance of the GMM estimator with a relatively small number of municipalities is questionable.

H70 -General < H7 -State and Local Government|Intergovernmental Relations < H -Public Economics, H72 -State and Local Budget and Expenditures < H7 -State and Local Government|Intergovernmental Relations < H -Public Economics, We acknowledge the comments made by Alejandro Esteller-Moré and Jordi Jofre-Monseny. This paper has benefited from the financial support of ECO2009-12680/ECON (Spanish Ministry of Education and Science) and the project SGR 2009 2013 (Generalitat de Catalunya). to cut expenditures, with a minor role being played by grant financing. By contrast, adjustments to expenditure shocks are shared on largely equal terms by the municipality -through the raising of taxes-and higher tiers of government -through the raising of grants. * We acknowledge the comments made by Alejandro Esteller-Moré and Jordi Jofre-Monseny. This paper has benefited from the financial support of ECO2009-12680/ECON (Spanish Ministry of Education and Science) and the project SGR 2009 2013 (Generalitat de Catalunya).

most of the adjustment to a revenue shock is borne by the municipalities themselves as they proceed