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International Tax and Public Finance

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02-02-2017

The effects of agglomeration on tax competition: evidence from a two-regime spatial panel model on French data

Authors: Sandy Fréret, Denis Maguain

Published in: International Tax and Public Finance | Issue 6/2017

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Abstract

This article studies how agglomeration economies affect tax competition between local jurisdictions. We develop a theoretical model with two main testable predictions: in a setting where agglomeration forces lessen the responsiveness of capital to tax, high-regime agglomeration jurisdictions should adopt a rent-taxing behavior, and they should react less to their neighbors’ tax policies. The panel dataset spans the period from 1995 to 2007 and focuses on the local business taxes set at the French mid-subnational jurisdiction level of départements. First, instrumental variables estimates indicate that attractive jurisdictions capture a significant part of firms’ agglomeration rent by levying higher tax rates. An increase by 1% of the localization economies indicator (a specialization index) leads to increasing the business tax rate by 0.43%. Second, local tax setting behaviors are characterized by a mimetic behavior, with best response functions that slope upwards. We propose a two-agglomeration-regime spatial lag model to estimate through ML the relationship between tax competition and attractiveness. Our main result shows that both are linked and tax mimicry is less pronounced if a jurisdiction is agglomerated. Specifically, in response to a decrease in the tax rate of neighboring local governments by 1%, local governments with strong agglomeration economies reduce their tax rate by 0.4% against 0.6% for local government characterized by a low-agglomeration regime. We show that the classical one-size-fits-all-case of a single regime of agglomeration suffers from a 40% downward bias for low-agglomeration jurisdictions. We draw the link to policy praxis by discussing the optimal design of equalization schemes.

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See Tiebout (1956).

See Wilson (1999) for a survey.

Under-provision of the public good and suboptimal levels of taxation.

For instance Devereux et al. (2008) found evidence of a fall of statutory tax rates in the 1980s and 1990s, whereas Garrett and Mitchell (2001) or Slemrod (2004) did not find such a pattern (see also Krogstrup 2003 for a recension).

For intermediate trade costs where the effect of agglomeration (here the market access effect) is stronger. Tax competition forces follow a U-shaped pattern in the degree of economic integration related to a \(\cap \)-shaped agglomeration rent. Under some conditions, the tax differential is also hump-shaped and the agglomeration rent is said to be taxable, see Kind et al. (2000), Ludema and Wooton (2000), Baldwin and Krugman (2004).

Local tax revenues have been reformed in 2010 in France, with a business tax deeply reshaped. Following the reform, local governments cannot choose their tax rates anymore and the “new business tax” is mainly based on the firm’s value-added. This reform is outside our period of analysis.

Knowledge spillovers are generally thought to be more localized, without be it set in stone.

Agglomeration measures highlight a low variation in the time dimension (in line with previous studies showing the time persistence of agglomeration measures, see Duranton and Overman 2005) so that we chose not to introduce jurisdiction (département) fixed effects in our main specifications.

Jurisdiction or département fixed effects are equivalent to individual or still spatial fixed effects in our setting as reference may be made to in the spatial econometrics literature see Elhorst (2010).

This result is obtained by having rejected in a preliminary step the presence of vertical interactions (where the tax rate of a given level of local government depends on the one chosen by the other levels) that would lead to over-taxation and could interfere with horizontal effects.

Except for the proportion of elderly, probably due to its small variation in the time dimension. As we will see, specifications with département fixed effects are more appropriate to gauge the genuine effects of controls.

Bischoff and Krabel (2016), still for Germany, illustrate in a different context how tax setting is adapted according to the local power of dominant firms (in terms of their contribution to fiscal revenues of municipalities), also using spatial panel econometrics techniques.

These authors found that municipalities in larger urban areas set higher tax rates but that, within urban areas, municipal tax rates are disconnected to the size of economic activity within and surrounding municipalities. Tax rates are however positively related to the size of the political jurisdiction. Luthi and Schmidheiny (2014) interpret these results in the light of the asymmetric jurisdictions theory of tax competition.

Lyytikäinen (2012) for instance argued that changes in the statutory lower limit to property taxes could be used as a source of exogenous variation in tax rates to identify tax competition among local governments in Finland. Parchet (2014) made use of fiscal reforms at the canton level in Switzerland to instrument taxes for municipalities located on the other side of the administrative border and found that strategic substitutability is the common situation (strategic complementarity is the exception, only present in the case of large tax cuts.)

As a by-product, a Matlab \(^{\copyright }\) routine of the estimation procedure for best response tax functions has been designed, with a potential widespread application of the methodology.

See also Fernandez (2005), Burbidge and Cuff (2005) and Krogstrup (2008) for extensions of NEG results to the standard tax competition model. Fernandez (2005) proved the fiercer tax competition result with moderated and uniform agglomeration (see Jofre-Monseny and Sollé-Ollé 2012 for an empirical investigation of this question in a NEG-modeling). Krogstrup (2008) replicated the case of catastrophic agglomeration.

Note that the same qualitative results of the model will still hold if \(a_i\) would be a function of the total stock of capital (per head) in the jurisdiction, as in Fernandez (2005) for instance.

A direct extension of the model dealing with the case of catastrophic agglomeration and mimicking the most famous NEG result would be to pose \(f''>0\) or, alternatively, to make \(a_{i}\) depend on \(k_{i}\) with the assumption \(\frac{\partial }{\partial k_{i}}[f'(k_{i}).a_{i}(k_{i})]>0\) under \(f''<0\) with \(a_{i}'>0\). This assumption would create a new order in which agglomeration forces are stronger than the dispersion ones, preventing any equalizing adjustment scheme for the return of capital to hold. Nash equilibrium in tax rates would be hence characterized by a situation in which tax competition pressures are undone leading trivially to a degenerated reaction function with a zero slope for the jurisdiction with strong agglomeration. This situation in which all the production is located in only one jurisdiction (the most attractive) is however not well adapted to analyze competition between multiple jurisdictions (see Ottaviano and van Ypersele (2005)) and is not considered here. See Krogstrup (2008) for the analysis of this case.

We rule out head taxes because of their artificial character and the fact that they would completely break the link between fiscal competition and under-provision (and thus the rat race leading to lesser resources).

This assumption is necessary to make the model non-trivial under the budget constraint and the ruling out of head taxes. We choose to introduce heterogeneity as in Brueckner and Saavedra (2001).

We can indeed expect positive correlates between agglomeration and the needs for public goods (infrastructures, roads and so on) so that \(\eta _{1}>\eta _{2}\) whenever \(a_{1}>a_{2}\).

DePater and Myers (1994) introduce a lump-sum tax (a head tax) as a second instrument.

Each jurisdiction has a compact and convex strategy space. Therefore a Nash equilibrium exists (Fudenberg and Tirole 1991, p. 34). Utility is quasi-concave and continuous. As a result, first-order conditions characterize best response functions.

As it is well known, the slope of best response functions cannot be signed in general (even without agglomerating forces).

The classical result of a lower slope (in absolute value) for the reaction function and a higher tax rate for the larger jurisdiction (Bucovetsky 1991; Wilson 1991) is also recovered in the standard asymmetric version of the model (when \(a_{i}=1\) for \(i=1,2\) and say \(N_{1}>N_{2}\)). As shown by the expressions in the body of the text, in the NEG version of the model with partial agglomeration (\(f''<0\) and \(a_{1}>a_{2}> 1\)), these results crucially depend on parameters a and on their relative magnitude compared to those of \(\eta \)s and Ns (an extension of the result of Brueckner and Saavedra 2001, p. 210).

Data that come from INSEE (the French National institute of statistics) are only available at the départements level for sectors of activities.

French Local tax revenues have been deeply reformed in 2010. The reform has created a new tax revenue on capital (“contribution économique territoriale”, CET) made up of two parts: a main part based on firms’ value-added (“cotisation sur la valeur ajoutée”, CVAE) and a residual part based on firms’ property (“cotisation foncière des entreprises”, CFE). The CVAE gives now no leeway to local jurisdictions to choose their tax rates and thus precludes any possibility of tax competition to attract capital. Note that the year 2009 was a transition year where the “old business” tax was cut and local governments got a transitional grant covering previous tax revenues. The date of entry into force of the reform have governed our choice of the final year for the period of analysis.

In addition to 2010 tax reform (by neutralizing the transitional year 2009), the summary economic classification of the French institute of statistics (INSEE) in 36 sectors has been profoundly modified in 2008 occasioning a break in series that year and explaining the choice of the year 2007 as end point.

It could be argued that business tax is not entirely determined through the demand for local public goods and that supply-driven arguments exist (lobbies, trade-off between different local taxes, etc.). However, there is a safe bet that such factors remain marginal in our setting (welfare expenditures), as it is shown by the absence of vertical interactions.

Vertical effects characterize a situation where the tax rate of a locale (here départements) would depend on those chosen by the other local levels.

The absence of vertical effects is supported by the French empirical literature on fiscal competition, see Leprince et al. (2005).

The relatively low specialization index for Haute–Garonne in map 3 comes from the quirks of the INSEE’s sectoral breakdown with many aeronautic jobs split in different items. The high value for Lozère comes from the high share of jobs in the health and social sector.

The Hausman specification test refutes orthogonality between random individual effects and explanatory variables (with a \(\chi ^{2}\) equal to 66.53 for 6 df and p<0.01) and, hence, validates a specification with fixed effects. According to Fisher test, we should introduce both jurisdiction and time-period fixed effects (F(105,1109) = 163.26, \(p<0.01\)). However, in line with the aim of this paper and data, it did not seem relevant to introducing département fixed effects in the main specifications.

More precisely, \(t_{it}= L_{it}\beta _{L}+ U_{it}\beta _{U}+\alpha + \mathbf{X}'_{it}\beta _{X}+\mu _{i}+\epsilon _{it}\) with jurisdiction fixed effects \(\mu _{i}\) accounting for unobservable heterogeneity across locations. Year dummies for 2003, 2005 and 2006 are here introduced in the vector \(\mathbf {X}_{ it}\) following the Chow test for structural stability. To avoid dummy variables traps, \(\sum _{i} \mu _{i}=0\). Note that due to data available from INSEE, we cannot properly instrument agglomeration’s variables when jurisdiction fixed effects are present. First, the breakdown by sector and département simply does not exist at INSEE before the year 1989 to construct the localization index, with consequently little hindsight to construct a credible “rolling panel” instrumentation (which avoids overlaps); note that the same problems would arise when using Bartik-type instruments as in Luthi and Schmidheiny (2014). Second, as already mentioned, indicators feature little variation over time.

The proportion of young people (less than 19) is not significant and not integrated as a control. The explanations of this non-significance are that the database is ill-suited to recover the legal age threshold from which benefits are allowed and that age is probably not the best criterion to approximate potential young beneficiaries of welfare in France.

These findings are in line with Buettner (2001) where it is shown that large population jurisdictions in Germany set higher capital tax rates in inter-jurisdictional competition, or with Exbrayat (2007) in an international context, where the market size of OECD countries positively and significantly impacts the levels of corporate tax rates set nationally.

Whose negative sign can be explained by its weak variation in the time dimension so that its effect is captured by jurisdiction fixed effects.

A robustness check, available upon request from the authors, has been performed with a spatial matrix based on euclidean distance.

In order to minimize omitted variable bias, these tests have been run with two-way fixed effects.

Denoting \(\hbox {LM}_{\rho }\) and \(\hbox {RLM}_{\rho }\) respectively Lagrange multiplier tests and their robust version of a model without a spatial dimension against the spatial lag model and \(\hbox {LM}_{\lambda }\) and \(\hbox {RLM}_{\lambda }\) Lagrange multiplier tests of a model without a spatial dimension against the spatial error model, decision rules are the following: If \(\hbox {LM}_{\rho }\) is more significant than \(\hbox {LM}_{\lambda }\) and \(\hbox {RLM}_{\rho }\) is significant whereas \(\hbox {RLM}_{\lambda }\) is not, then the appropriate specification is the spatial lag model.

These authors test political yardstick competition with a two-regime spatial Durbin model with fixed effects where regimes reflect the level of confidence of local governments in their reelection prospects. The Durbin specification, where spatially lagged independent variables are introduced in addition to spatially lagged endogeneous variables (and exogenous characteristics), has been tested and does not impact estimates. In our setting (tax competition), the SAR model is more adapted, in particular, for the treatment of endogeneity. Note that in the SAR model, neighbors’ covariates are also included in the reduced form through the spatial multiplier.

Introducing lagged strategic interaction and agglomeration variables with a 1-year time lag to treat endogeneity does not change the results. The same remark applies to Eq. (8).

The two-regime modeling is suited for capturing (or not) the main lessons from theory of the low homogeneous agglomeration case versus the high-agglomeration case.

The \(\varPhi \)s functions having the “good properties”, there exists q such that \(q=\varPhi ^{L-1}(\tau )\) (the same is true for U-indicator).

The proportion of young people (less than 19) being not significant, it is excluded from controls.

A related problem is the one of false evidence of strategic interactions when, for instance, unobservable determinants of tax rates are correlated across jurisdictions due to correlated shocks. As shown by testing for spatial residual auto-correlation (and spatial lag exogenous), this problem is absent in our data set.

An alternative way to fix the potential persistence problem would have been to adopt a Quasi-Maximum Likelihood (QML) approach. However, with serially correlated error terms within jurisdictions, QMLE would not be consistent in general (see White 1982) and would necessitate to specify the unknown form of auto-correlation(s) (which has never been done in the literature in the spatial case (see Lee 2004)).

A frequent critique against spatial ML-estimates is that the Jacobian may become computationally unstable if N is greater than 1000, Anselin (2005). With \(N=94\) spatial units, we are immune to this criticism.

This coefficient equals to 0.33 when jurisdiction fixed effects are introduced as well as time dummies (see Table 5 in the Appendix). The large empirical literature on tax competition, be it whether on panel data or on cross-sectional data, using either maximum likelihood (ML), generalized method of moments (GMM) or instrumental variables (IV) methods, generally find a strategic complementarity between neighbors’ tax rates. Related to our setting, see for instance Besley and Case (1995) or Hernández-Murillo (2003) on US states; Revelli (2001) and Revelli (2002) on English districts; Feld and Reulier (2009) on Swiss Cantons; Heydenls and Vuchelen (1998) for Belgium municipalities; Leprince et al. (2005) and Jayet et al. (2002) for the three levels of French jurisdictions.

Of the 117 observations in the strong urbanization agglomeration group (with \(Q_{0.9}^{U}\) as threshold), only 39 do not adhere to the cutoff and can really be differentiated.

With the following specification: \(t_{it}=\rho _{1}d_{it} \sum _{j=1}^{N}w_{ij} t_{jt} + \rho _{2}(1-d_{it}) \sum _{j=1}^{N}w_{ij} t_{jt}+\alpha +{\mathbf{X}}'_{it}\beta + \mu _{i} + \epsilon _{it}\), with \(\mu _{i}\) the jurisdiction fixed effects, year dummies defined earlier, and political dummies are integrated in \(\mathbf{X}_{ it}\).

In this case, neighbors’ tax rates are instrumented along the lines aforementioned. Agglomeration indicators cannot be properly instrumented with 2SLS when jurisdiction fixed effects are introduced since variables used to instrument agglomeration indicators do not vary over time.

Lyytikäinen (2012) finds the quite surprising result of zero-slope tax reaction functions under exogenous source of variation opposed to positive slopes with spatial econometric techniques.

Results of estimations are not reported here and are available upon request from the authors.

We adopt here a more natural norm than the one chosen in Duranton and Puga (2000) by selecting the sum instead of the max operator.

See Anselin and Hudak (1992) for the case of a spatial lag model with one coefficient of interaction (“single regime”) with cross-sectional data.

The (log-)Jacobian determinant of \(\mathbf \epsilon \) with respect to \(\mathbf t\) under the spatial filter (of dimension \(NT\times NT\)) simplifies to a product of T N-dimensional determinants (Ord 1975). With such a decomposition, eigenvalues are only computed once for all and iterating over \(\rho _{i}\)-values becomes straightforward. Several methods exist to evaluate these N-dimensional determinants. We use the one proposed by Pace and Barry (1997) who compute the determinant over a grid of values for the parameter \(\rho _{i}\) ranging from \(1/\omega _{min}\) to 1 prior to estimations (\(\omega _{min}\) being the smallest eigenvalue of \(\mathbf {W}_{N}\) matrix). We adopt a grid based on 0.001 increments for \(\rho _{i}\) over the feasible range. Given these predetermined values, one can quickly evaluate the concentrated log-likelihood function for all values of \(\rho _{i}\) in the grid and determine the optimal value of \(\rho _{i}\) that maximizes the concentrated log-likelihood function over the grid.

This matrix being symmetric, the lower diagonal elements are omitted.

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Title: The effects of agglomeration on tax competition: evidence from a two-regime spatial panel model on French data
Authors: Sandy Fréret
Denis Maguain
Publication date: 02-02-2017
Publisher: Springer US
Published in: International Tax and Public Finance / Issue 6/2017
Print ISSN: 0927-5940
Electronic ISSN: 1573-6970
DOI: https://doi.org/10.1007/s10797-016-9429-9

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