Control Variables

In addition to the main interesting explanatory variables I include some economic, political and institutional control variables that have been found to be theoretically interesting or to exert a statistically significant impact on domestic taxation. I add the one year lagged domestic unemployment rate provided by the World Bank as part of the World Development Indicators

(WDI 2006) which can have different impacts on taxation. On the one hand, high unemployment makes it difficult for governments to shift taxation towards the immobile factor and, therefore, politicians are less likely to engage in tax competition and cut back capital tax rates (Ganghof 2000b).

On the other hand high unemployment might create an incentive for wasteful tax competition because governments benefit from the employment effects of additional capital (Huang 1992). Swank and Steinmo (2002) find a significant negative effect of structural unemployment on effective capital tax rates and a positive effect of the unemployment rate on effective labour taxation.

Moreover, I include the one year lagged annual growth rate of GDP (WDI 2006) to account for economic size and wealth effects. Swank and Steinmo's (2002) results indicate a positive marginal significant impact on effective capital tax rates. Basinger and Hallerberg (2004) support these estimates;

they get a positive significant coefficient of growth for changes in effective capital tax rates but no effect for central and general rates. Moreover, the impact of economic growth on labour taxation is less straightforward (Swank and Steinmo 2002). The empirical results so far are inconclusive.

I control for the population share of elderly people (over 65 years) because this variable has been found to augment capital taxation significantly, whereas no or no significant effect on labour taxation was detected (Swank and Steinmo 2002). One would expect, however, that the share of old people drives both capital taxation and labour taxation up and also increases tax symmetry as a high dependency ratio exerts pressure on the social security systems, especially on public pension systems. Governments have to collect

sufficient tax revenue to feed money into these systems. This variable is taken from the World Bank's World Development Indicators (2006).

It has been widely argued that the liberalization of capital and product markets accelerate the international competitive pressure. The empirical results connecting trade openness and capital mobility to capital taxation are ambiguous at best (Quinn 1997, Garrett 1995, Rodrik 1997, Swank 1997, Swank and Steinmo 2002, Basinger and Hallerberg 2004, Hays 2003). I analyze the effects of trade openness measured by overall trade as percentage of GDP (taken from WDI 2006) and the impact of capital mobility on capital and labour taxation. The measure for legal capital mobility stems from Quinn (1997) and is called capital account regulation.

It ranges between 0 and 4, where 0 stands for a large number of restriction indicating a closed economy, and 4 denotes no restrictions to capital account transactions which means that the country is rather open. Quinn gathered the data from the IMF Annual reports of Exchange Arrangements and Exchange Restrictions.⁶⁸ Since Basinger and Hallerberg (2004) also report that lower capital restrictions abroad lead do capital tax reductions, I add the average spatial lag of the 'Quinn-measure' to the right hand side of the empirical model.

In order to be able to reproduce some of the findings in the literature, I examine how several political and institutional variables affect domestic taxation. Most importantly, political scientists often claim that party politics make a difference in taxation (Oates 1972, Hays 2003, Swank 1997 among

68 I also use the capital mobility measures provided by Miniane (2004) and Lane and Milesi-Ferretti (2001) with essentially the same results; these two measures, however, are available for much fewer observations.

others).⁶⁹ Analyzing a partisan variable within my empirical model, hence, seems reasonable. To do so, I construct a categorical variable measuring whether the majority of the government in power is ruled by a left-wing party (1) a centrist party (2) or a right-wing party (3). The data comes from Keefer's (2005)⁷⁰ database of political institutions and the Comparative Welfare States Data Set (Huber et al. 1997, updated by Brady et al. 2004).

Following Basinger and Hallerberg (2004), I include an arbitrarily weighted spatial lag of this variable to the right hand side of the model as well.

Another well known argument states that veto players can reduce political flexibility and constrict policy makers, preventing reform and political change in general and – as has been argued in the tax competition literature – therefore tax reduction reforms (Hallerberg and Basinger 1999, Basinger and Hallerberg 2004, Wagschal 1999a,b; Genschel 2002). Still, the empirical results remain inconclusive (and Basinger 1999, Basinger and Hallerberg 2004, vs. Ganghof 1999b). To measure not just the number of veto points but the effective restrictions to the policy maker I use the executive constraints variable (xconst) provided by Henisz (2002, 2005) based on Gurr's (1990) specification. This variable operationally refers to the extent of institutionalized constraints to the decision making powers of chief executives. It mainly accounts for the checks and balances imposed by the various players in the decision making process. The measure is based on

69 Swank (2004), Hays (2003) and Basinger and Hallerberg (2004) generate some empirical support for this hypothesis. Ganghof (2004) shows for the Australian case that the partisan composition of the government strongly influenced tax policy making.

Basinger and Hallerberg (2004) even maintain that domestic governments are more or less constraint by the partisanship of governments in other countries.

70 See also Beck et al. (2001).

seven distinctive categories with higher values indicating stronger constraints.

In addition, to operationalize political polarization between parties participating in the decision making process (Basinger and Hallerberg 2004), I employ the polarization measure provided in Keefer's (2005) political institutions database. This variable captures the maximum difference between the ideological position of the chief executive's party and the position of the three largest government parties and the largest opposition party.

Finally, two election variables distinguish between legislative and executive elections and account for possible political business cycle effects, namely that government cut taxes to buy votes before elections (Nordhaus 1975, Alesina 1997, Drazen 2000b). The two variables are coded as dummies displaying a 1 in the year in which a legislative or executive election takes place and 0 otherwise. Election data come from the Keefer et al. data set (World Bank 2005) for the period from 1980 – 2000 and from www.Electionguide.de for 2000 – 2005.

Including different sets of control variables into the empirical estimation should allow capturing other influences of domestic tax policy making.

Nevertheless, there is always a conflict of objectives when adding more variables to the right hand side of the model. On the one hand, controls should be included in order to reduce omitted variable bias. On the other hand, this also increases multicollinearity between explanatory variables which reduces efficiency of the estimation leading not only to larger standard errors but also to less reliable point estimates. Based on this insight, I add controls successively to the baseline model in order to observe

effects on coefficients and significance levels of the main theoretical interesting variables.