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Tax Structure and Economic Growth: A Panel Cointegrated VAR Analysis

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Abstract

The paper is aimed to re-evaluate the relationship between tax structure and economic growth relying on linear and non-linear panel cointegrated VAR models. The asymmetric impact of tax changes on growth is estimated adapting the threshold cointegration methodology proposed by Hansen and Byeongseon (J Econom 110:293–318, 2002) to the panel framework. The tests indicate that the weak exogeneity and linearity hypotheses are not supported by data. Thus, the empirical results obtained by previous literature in a linear single-equation framework must be interpreted with caution. We find that recurrent taxes on immovable property seem to be the least harmful for the growth, while we do not found compelling evidence favouring consumption taxes over income taxes. Therefore, our results do not fully support the policy prescriptions proposed by many international organizations aimed at shifting the tax burden from income to consumption and property. Moreover, these findings are robust and significant when the tax burden is above the threshold value of around 30%, which is the case for the tax revenue to GDP ratio for the most of European countries in the sample. Policy conclusions are also discussed.

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Notes

  1. This condition implies that any change in a tax structure indicator is compensated by an equivalent change in another indicator to keep the total tax revenue as a share of GDP unchanged, other things being equal.

    It is worth noting that there are also empirical studies that in the analysis of the growth effects of the tax structure do not adopt the hypothesis of tax revenue neutrality (see Kneller et al. 1999; Lee and Gordon 2005). In this case, the influence of the tax structure on the economic growth becomes less evident.

  2. For a more comprehensive reading, we remind to some empirical studies regarding fiscal policy asymmetries (Auerbach and Gorodnichenko 2012; Baum et al. 2012).

  3. The MG estimator may be sensitive to the presence of country-specific estimates with extreme values. To avoid this problem, we use the strategy proposed by Bond et al. (2010) that allows to obtain an outlier-robust MG estimator.

  4. For an extensive discussion of threshold regression models, we refer to Tong (1990).

  5. See Di Sanzo and Pérez-Alonso (2011) for details about Monte Carlo and bootstrap simulations in threshold models.

  6. We also checked if the empirical results depend from the choice of non-fiscal growth determinants. Using different sets of non-fiscal variables (such as trade openness indicators etc.) we found similar estimates, thus we settle on this parsimonious specification of the model.

  7. Country and estimation period is dictated by data availability only and more precisely, for Australia, Greece, Japan, Netherlands and Switzerland the full sample period is 1970–2011, while for Portugal the sample reduced to 1989–2012.

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Correspondence to Silvestro Di Sanzo.

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Di Sanzo, S., Bella, M. & Graziano, G. Tax Structure and Economic Growth: A Panel Cointegrated VAR Analysis. Ital Econ J 3, 239–253 (2017). https://doi.org/10.1007/s40797-017-0056-0

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