Martin Thomsena, Robert Ullmanna, and Christoph Watrina

WHAT HAPPENS WHEN TAX HAVENS ARE SHUT DOWN?

AN ANALYSIS OF ACCOUNTING DECISIONS AND LOCATION DECISIONS

a School of Business and Economics, University of Muenster, Germany

(February 2014)

Abstract

There is an ongoing debate about the consequences of shutting down tax havens. By using a unique setting with real tax data, we are able to draw new inferences regarding this question. In our research, we identify a natural experiment in the German tax regime in which all local tax havens are exogenously and simultaneously shut down by the German federal government; this shutdown was achieved by setting a nationwide minimum tax rate at the municipality level. In general, trade taxes can be set independently by each of the 12,268 German municipalities. However, with respect to tax base allocation among municipalities, the German trade tax system has the peculiarity that some firms are subject to separate accounting, whereas other firms are subject to formulary apportionment. Using a unique panel data set of confidential tax return data, we were thus able to observe both accounting decisions and location decisions aimed at reallocating the tax base in reaction to the tax haven shutdown. We find that both accounting decisions and location decisions are used to shift the tax base away from tax havens that have been shut down. For both channels of income shifting, we show that the largest effects of income shifting occur in the short run and find that there is no further incremental effect thereafter. Finally, we report that firms that are subject to separate accounting do not significantly react to tax haven shutdowns by completely closing their places of business; instead, they shift income within their existing structures.

We are deeply indebted to Manuel Boos and Alexander Richter from the German Research Data Center for their continued support and expert analyses of the confidential data with all its constraints. We are also thankful for comments by Johannes Becker, Dominika Langenmayr, Mark Trede, Andrea Schneider, Ulrich Schreiber, Lisa de Simone, and Alfons Weichenrieder, in addition to comments by participants at the Colloquium of the Muen- ster Institute of Public Finance I 2013, the Conference on Multinational Taxation in Mannheim 2013 and the 2012 and 2013 Brownbag Series of the Muenster Institute of Accounting and Taxation.

Keywords: Tax Haven, Income Shifting, Separate Accounting, Formulary Apportionment

1 Introduction

What would happen to Apple and Google if Ireland was shut down as a tax haven?

Tax havens potentially compromise the welfare of developed countries. Moreover, scandals such as offshore leaks have attracted a considerable amount of public attention to tax havens because tax havens are apparently widely utilized by both firms and individuals. Developed countries are increasing their efforts to specifically attack tax haven activity on a global scale, which is evidenced by the current OECD initiative against base erosion and profit shifting

(BEPS).

Despite this attention to tax havens in the field of international taxation, the effects of tax havens on developed countries are little understood. Tax havens are argued to have two counteracting economic effects. On the one hand, some scholars contend that tax havens negatively impact developed countries by inducing domestic firms to reallocate tax bases out of local headquarters to save taxes, which directly decreases developed countries’ tax revenues.

This strategy may be particularly relevant for the mobile part of firms’ income (Becker and

Fuest 2007, 2012a). On the other hand, tax havens might have a positive effect on developed countries. It has repeatedly been argued that tax base reallocation is largely undertaken by means of accounting decisions, i.e., merely by utilizing available accounting discretion (e.g.,

Harris 1993; Klassen et al. 1993; Shackelford and Shevlin 2001; Devereux and Maffini 2007;

Huizinga and Laeven 2008). In this context, tax havens have limited direct impact on the overall real activity of domestic firms in their home countries. Moreover, lower total costs of capital (a result of the lower tax burden in the tax haven) increase firms’ investment budgets and might therefore indirectly increase real investments in the firms’ home countries. Theo- retically, both effects can be dominant.

However, the channels of tax base reallocation—and the resulting net effects of tax havens on developed countries—are not yet well understood. Research in this area is generally hindered by data availability. As a consequence, most available research investigates 2 whether tax base reallocation related to tax havens occurs on its merits with no detailed investigation of the channels of income shifting. It has, for instance, been demonstrated that multinationals with headquarters based in a tax haven face the lowest effective tax rates globally

(Markle and Shackelford 2012) and that owning even just one subsidiary in a tax haven country is associated with a decrease in a firm’s consolidated effective tax rates (Dyreng and

Lindsey 2009; Seida and Wempe 2004).

The previous literature regarding the precise channels of tax base reallocation has focused largely on accounting decisions that result in income shifting to low tax jurisdictions.

The most prominent examples of such literature have focused on changes in transfer pricing

(e.g., Newberry and Dhaliwal 2001; Mills and Newberry 2004; Blouin et al. 2012) and the intentional location of debt (e.g., Froot and Hines 1995; Newberry and Dhaliwal 2001) and intangibles (Dischinger and Riedel 2011; Karkinsky and Riedel 2012). Conversely, the body of research on firms’ location decisions as a channel of tax base reallocation is considerably smaller, primarily because the limitations on data availability are particularly strong in this field (Shevlin et al. 2012; Mintz and Smart 2004). Nonetheless, recent research confirms that firms react to differences in tax rates and tax rate changes over time with tangible business decisions (Thomsen et al. 2013), both quantitatively and qualitatively (Becker et al. 2012).

Building on the seminal work by Mintz and Smart 2004, who investigate firm behavior in subnational regions in Canada, we contribute to lines of research into both accounting decisions and location decisions. We do so by using the peculiar setting of tax rate competition among different regions within Germany—the trade tax regime of Germany’s municipalities. We analyze an exogenous shock from a federal tax law change that required municipalities to set a minimum trade tax rate and thereby effectively shut down all domestic trade tax havens at once (Elsayyad and Konrad 2012). The specific advantage of our study is that all the firms in our sample belong to one of the following two categories: Firms that are either able to shift income only by means of accounting decisions (separate accounting firms) or are 3 able to shift income only by means of location decisions (formulary apportionment firms).

Thus, we investigate the following three questions:

1. Do separate accounting firms (those firms that use separate accounting for allocating

their trade tax base among municipalities) react to the shutdown of tax havens?

2. Do formulary apportionment firms (those firms that use formulary apportionment for

allocating their trade tax base among municipalities) react to the shutdown of tax ha-

vens?

3. Is there a difference in the reaction between separate accounting firms and formulary

apportionment firms with respect to the shutdown of tax havens?

To answer these questions, we examine a confidential dataset from the German fiscal authorities that includes full trade tax returns for all German-based commercial firms for the years 2001, 2004 and 2007 (5,116,719 firms). We then identify tax havens in our data based on the minimum trade tax rate that was set as part of the change in the national tax law (discussed above) and imposed by the German federal government in 2004. Given these data, we observe the abovementioned effects in cross-sectional and panel analyses. Against this background, our analysis arguably does not suffer from self-selection bias because we obtained data on all commercial firms in Germany. Furthermore, we use genuine tax data; therefore, we did not estimate tax effects from accounting data.

We report four distinct results. First, both accounting decisions and location decisions are used to shift income out of tax havens after the shutdown of the tax haven. Second, separate accounting firms shift income (through accounting decisions) out of the tax haven municipalities immediately after the shutdown but do not significantly shift additional tax base thereafter. This finding underlines the conjecture that income shifting via accounting decisions can be implemented quickly with little cost. Third, formulary apportionment firms also 4 shift income (through location decisions) out of tax haven municipalities immediately after the shutdown and also do not significantly shift additional tax base thereafter. On the surface, this finding is contrary to general expectations because location decisions would typically be expected to occur at a relatively slow pace—they would typically be expected to be more pronounced in the long run than in the short run—because location decisions are relatively costly to implement and to reverse. However, upon closer analysis, the exogenous intervention of the German federal government by changing the law was widely accepted, politically speaking. Consequently, firms had no reason to believe that the threshold rate would be eliminated at some future date, which might explain why even formulary apportionment firms reacted resolutely and swiftly to the shutdown. Fourth, we find that separate accounting firms do not close entire legal entities in tax havens after the shutdown at a statistically significant level. In contrast, firms subject to formulary apportionment entirely shut down their permanent establishments. This finding suggests that the tax base can be transferred quickly by separate accounting firms to a large extent by means available to such firms, such as transfer pricing, location of debt and location of intangibles, without actually closing down the place of business in the tax haven municipality.

The remainder of this paper is organized as follows. Section 2 provides an overview of the institutional details of the German trade tax system, and Section 3 presents a literature review. We develop our hypotheses in Section 4 and subsequently describe the data and our research design in Section 5. The results, a descriptive analysis and a robustness test are presented in Section 6. Section 7 concludes.

2 Institutional Details

The Federal Republic of Germany has 16 states, and each state has several districts (in

2007, Germany had a total of 443 districts). Each district is subdivided into municipalities— in 2007, there were a total of 12,268 municipalities. Trade taxes are collected by and available to the municipalities directly and represent a major source of public financing. Every municipality has the right to set its trade tax rate independently but may only collect taxes from firms that have a permanent establishment in its geographic area. Consequently, competition is fierce among municipal governments to encourage firms to establish facilities in their municipalities.

In terms of tax rate competition, economically successful municipalities—such as

Munich and Cologne—generally have higher trade tax rates (approximately 19.7%) than less prosperous municipalities, which are mostly located in rural areas (some have tax rates as low as 0% in an attempt to attract businesses).1 Until 2003, municipalities faced no legal constraints in setting their trade tax rates. However, in 2004, the German federal government passed national legislation that disallowed trade tax rates that were below 9.1% (which is consistent with a trade tax levy rate of 200%); the explicit objective of the law was to shut down domestic tax havens. Consequently, before this change in the law, there were a number of

German municipality tax havens, and these domestic tax havens interacted directly with the higher taxed, more economically developed municipalities (because of Germany’s relatively small geographic dimensions). Thus, until 2004, the German trade tax regime mirrored the landscape of tax competition between tax haven countries and developed countries.

This exogenous shock to the German trade tax regime is a well-suited natural experiment for the intended research on the real effects of tax havens for several reasons. First, the

1 To calculate the trade tax rate, we compute the following: trade tax rate = trade tax levy rate / (trade tax levy rate + 2000%). This computation correctly considers the marginal statutory basic federal rate in our sample period of 5% (paragraph 11 of section 2 of the trade tax code) and the fact that the trade tax is deductible from its own tax base (known as the circularity problem of German trade tax). Trade tax levy rates in our sample period varied between 0% and 900%, with a mean of approximately 333%. 6 wording and application of the trade tax law is identical for each municipality; thus, variation in the trade taxation regimes among municipalities derives solely from differences in trade tax rates. Furthermore, tax audits are conducted at the firm level; thus, the total trade tax base is not affected by allocation among municipalities. Second, wages paid affect only the allocation of the trade tax base; other taxes are not affected. Third, other tax laws (e.g., corporate tax, labor tax, and value added tax) and non-tax laws (including labor laws) are largely identical among municipalities because the relevant laws are created on a national level, and there are national courts that specialize in different areas of the law to guarantee their homogenous application (e.g., there is one national court for tax law, one national court for labor law and a supreme court). Fourth, trade taxes are economically relevant to firms. Roughly speaking, trade taxes account for approximately 40% of the corporate income tax burden and approximately 30% of the income tax burden on other types of business entities (e.g., sole proprietorships). Fifth, general institutional factors, such as the stability of the government (central and local), the functionality of public authorities, infrastructure, availability of finance, unemployment support, and antitrust regulations, are similar throughout Germany. Finally, because of Germany’s relatively small geographic dimensions (886 kilometers from north to south and

636 kilometers from east to west), any unobservable variables—such as tax-paying mentali- ty—are likely to be more similar in our data than in cross-border studies (e.g., Klassen and

Laplante 2012) or in within-country studies in geographically larger and culturally more het- erogeneous countries, such as China (e.g., Shevlin et al. 2012) or the U.S. (e.g., Gupta and

Mills 2002).

As a further unique feature, formulary apportionment is used for certain subsets of firms in the trade tax regime. More specifically, when a firm has permanent establishments in more than one municipality, the firm-level trade tax base is allocated under a formulary apportionment regime with respect to the different municipalities, and trade taxes are paid di-

7 rectly to the municipalities accordingly. The sole allocation key in this regard is wages paid.2

Ceteris paribus, the allocation of wages paid among municipalities, has no direct impact on a firm’s financial statements, whereas a potential decrease in the trade tax has an indirect impact on net income. If a firm has only one permanent establishment, wages paid are irrelevant in the calculation of the trade tax burden.

We note that wages paid are a particularly well-suited proxy for investigating tax- induced location decisions for several reasons. First, wages paid can be measured with mini- mal error. Most particularly, wage taxes in Germany are levied directly on the source firm, such that the data are not estimated or rounded. Moreover, the data are explicitly audited by the tax authorities. Second, wages paid cannot realistically be shifted without actual changes in headcount, i.e., without changes in location decisions.3 Finally, wages paid are a better proxy for tangible business activity than other measures that are also frequently discussed as allocation keys in formulary apportionment, such as sales or total assets. Sales can be manipu- lated without difficulty by adjusting intragroup trades, and total assets are generally subject to considerable discretion for accounting purposes, such as the assessment of fair value.

As a result, when considering individual firms with permanent establishments in more than one municipality, income shifting for trade tax purposes is only possible by relocating employees. In particular, changes in transfer prices on transactions among several permanent establishments or the deliberate allocation of debt and intangible property has no impact on the allocation of the trade tax base among a firm’s permanent establishments. Therefore, the

2 We note that there are rare and exceptional cases, such as firms that own wind power stations (which generally have limited permanent personnel), in which allocations are based on both wages paid (30% weight) and the value of property, plants, and equipment (70% weight). 3 We note that tax planning based on accounting decisions theoretically is also possible by simply increasing the wages of employees in municipalities with low trade tax levy rates. However, wages (and ancillary wage costs) are actually paid out in full to a third party (i.e., the employee) and are therefore full expenses from the perspectives of both the firm and the entire consolidated group (a slightly different rationale might hold in the case of the employment of family members or close friends, but these rare, and arguably negligible cases are not addressed here). Moreover, given Germany’s strong labor laws, increases in wages cannot generally be reversed; thus, such a strategy would be almost prohibitively inflexible. In sum, the strategy of purposefully increasing the wages of selected individuals for purposes of a firm’s trade tax planning is not an economically sensible strategy and is even anecdotally unheard of. 8

German trade tax system offers a unique natural experiment to analyze the effect of tax havens (and their abolishment) on location decisions.

3 Literature Review a) Overview and Potential Welfare Implications

Tax competition is not a negative phenomenon in and of itself. Instead, it can have both positive and negative effects on developed and developing countries on the one hand and on tax havens on the other.

With respect to developed countries, tax haven availability can increase efficiency in the provision of public goods (OECD 2001, § 1). This policy argument is consistent with the view of Tiebout 1956, who argues that tax havens are merely one specific form of tax system competition among countries—and that tax system competition is generally positive. Apart from the efficient provision of public goods, the availability of tax havens may also allow firms in high-tax jurisdictions to increase their global competitiveness by decreasing their tax burdens (Hong and Smart 2010).

Critics of the tax haven industry argue that, as opposed to the assumptions of Tiebout

1956, firms do not use tax havens because of their attractive mixture of public goods and tax burden but because they gain the advantage of a low tax burden in the tax havens while re- taining the advantage of a high level of public goods and services in their domestic countries.

Tax havens thus lead to unfairness in tax competition, which results in an inefficient under- supply of public goods in developed countries (OECD 1998). In particular, a firm may use mere accounting decisions to allocate its tax base into a tax haven, i.e., using the accounting discretion that is available to it without relocating any real activity. This directly decreases the tax revenue of the developed country without decreasing its cost in providing public goods.

According to recent estimates, the U.S. lost approximately 90 billion USD in tax revenue in

2008 resulting from income shifting to low-tax jurisdictions—including (but not limited to) tax havens (Clausing 2011). For the EU, the estimates are that approximately 150 billion EUR in tax revenue is lost annually (Murphy 2011). Additionally, firms might even shift real eco-

10 nomic activity into tax havens, thereby additionally decreasing domestic employment and investment (see Hines 2010 for a profound discussion on relevant studies in this area).

For developing countries, the welfare effects of tax haven activity are structurally similar to those of developed countries. However, these effects are generally greater in economic magnitude because developing countries are in direct competition with tax havens for investments from developed countries (Oxfam 2000). Moreover, developing countries generally do not have sufficient institutions to avoid improper income shifting to tax havens (see McLure

2006).

Finally, the welfare effects in the tax havens themselves are also ambiguous, to some extent. On the one hand, tax havens do appear to reach their goals of attracting the tax base from more affluent countries and creating local jobs (Hines 2005), and each of these effects potentially increases the tax haven’s welfare. On the other hand, jobs created by the tax haven industry are generally highly specialized and are frequently filled by nondomestic employees

(Irish 1982). In addition, the tax haven industry is regularly perceived to crowd out other national industries (Hampton and Christensen 2002). b) Relevant Theoretical Research on Tax Havens

The key for non-tax haven countries to limit pressure from tax havens is often seen in the ability to distinguish between mobile capital and immobile capital and in the ability to impose differential taxation. A firm’s mobile capital can be shifted among jurisdictions at little or no cost. Various tax policies in tax havens that address the two types of capital therefore generally lead to a relatively low (or no) tax burden on mobile capital and a corresponding increase in the tax burden on immobile capital to offset the effect of the former policy on tax revenue. Against this background, it appears to be a natural consequence that the identifi- cation and separate taxation of mobile and immobile capital substantially decreases the pressure that tax havens put on developed countries’ tax systems (e.g., Keen 2001). To this end,

Peralta et al. 2006 show that the availability of income shifting to multinational enterprises has approximately the same effect as separate taxation of mobile and immobile capital. Most particularly, tax competition is similarly reduced. Along the same lines, Becker and Fuest

2012b show that strict transfer pricing guidelines initially decrease income shifting through accounting decisions but also lead to higher tax rate competition in the long run because tax havens are incentivized to compete more aggressively for the tax base of firms that are domi- ciled in developed countries. Consequently, Becker and Fuest 2012b expect that relaxed transfer pricing guidelines lower tax rate competition in the long run. Countries might therefore even strategically choose to open loopholes for multinational firms to deploy their mobile capital elsewhere rather than tax mobile and immobile capital differently; such strategic ac- tions might reduce public scrutiny of the country's tax policies.

Conversely, Slemrod and Wilson 2009 explicitly model the strategy of relatively small countries that act as ‘parasitic’ tax havens with regard to developed countries. Moreover, they include in their model the real resource consumption that results both from firms aiming to use tax havens and from a developed country's attempts to avoid erosion of its tax base. They show that tax havens do, in fact, drive developed countries to choose a mix of taxes on mobile capital and immobile capital that results in an inefficiently low level of taxation on mobile capital and leads in turn to an inefficiently low provision of public goods. They also show that the purposeful elimination of a sufficiently small number of tax havens would make all countries—both tax havens and non-tax havens—better off. Finally, eliminating all tax havens would increase the welfare of all non-tax havens, according to their model. However, previous research has also shown that the elimination of all tax havens is a somewhat unrealistic option—at least when it is attempted country-by-country in bilateral negotiations (Elsayyad and Konrad 2012)—because the competition among remaining tax havens decreases with the number of tax havens, which directly increases the gross benefits of a country’s tax haven strategy. 12 c) Relevant Empirical Research on Tax Havens

When considered at the firm level, the notion of mobile capital is strongly connected to the availability of income-shifting opportunities that utilize accounting discretion. Similar- ly, the notion of immobile capital is strongly connected to the optimal location of a firm’s real business activity. The empirical literature investigates a variety of measures as proxies for the channels of tax base allocation.

Regarding activities involving mere accounting decisions, the literature demonstrates that the most prominent transactions involve changes in intragroup transfer pricing (e.g.,

Newberry and Dhaliwal 2001; Mills and Newberry 2004; Blouin et al. 2012) and the intentional location of debt (e.g., Froot and Hines 1995; Newberry and Dhaliwal 2001) and intangibles (Dischinger and Riedel 2011; Karkinsky and Riedel 2012). It is generally accepted that these strategies are widely used to allocate a firm's tax base to low-tax jurisdictions at little or no cost, which is typical of such paper transactions (Hanlon and Heitzman 2010).

With regard to firms’ group structures, the previous literature shows that foreign tax rates are negatively associated both with the propensity to locate a subsidiary in a tax haven or low-tax jurisdiction (Buettner and Ruf 2007, Gumpert et al. 2011 and Barrios et al. 2012) and with the propensity to relocate firm headquarters (Voget 2011).

Another sizable body of literature focuses on foreign direct investments (Hanlon and

Heitzman 2010). Most studies in this area confirm that the tax rate in a subsidiary’s country is a significant factor in placing foreign direct investment (e.g., Hartman 1985; Grubert and

Mutti 1991; Hines and Rice 1994; Swenson 2001). We also note that in this regard, the Ger- man Federal Reserve Bank makes a dataset available that pertains to the foreign direct investments of domestic German firms with foreign subsidiaries and of foreign firms investing in Germany (MiDi database). Research using this specific database indicates that tax rates in a given location are negatively associated with firms’ investment decisions in that location

(Weichenrieder 2009, Weichenrieder and Ruf 2012). 13

Any cross-border research on location decisions faces the issue of heterogeneity among countries. Similarly, the literature has shown that domestic regions can act as tax havens and play a significant role in firms’ tax planning strategies (e.g., Delaware in the U.S., see Dyreng et al. 2013). Feld and Kirchgaessner 2003 investigate how firms react to differences in tax rates within a single country in a setting in which most non-tax factors are largely similar among regions. In an analysis of Switzerland, they report that corporate tax rates in the cantons are negatively associated with the number of firms located therein. They also find that this effect spills over into the cantonal employment rate, which is evidence for real effects on cantonal-level economies. In general, Feld and Kirchgaessner 2003 show that tax rates influence firms' location decisions among cantons in a manner that is similar to their impact on location decisions across borders. In more recent research, Thomsen et al. 2013 focus on municipalities in Germany. In their investigation of a specific sample of German commercial firms that are subject to formulary apportionment, they employ both cross-border and panel analyses and find that firms use location decisions to reallocate tax base to low-tax jurisdictions. Moreover, they report that reactions to tax rate changes over time are relatively slow and that firms react faster to a tax rate decrease than to a tax rate increase. Finally, Mintz and

Smart 2004 rely on a setting within Canada to compare firms that use separate accounting

(i.e., accounting decisions) to allocate tax base among subnational jurisdictions with firms that use formulary apportionment (i.e., location decisions). Following a detailed analysis, they conclude that the first group of firms has a significantly higher tax rate elasticity in its tax base than the latter group. Their research provides a solid basis for our study.

In light of the studies discussed above, we note that the majority of empirical research must rely on proxies that potentially detect both accounting decisions and location decisions related to tax havens. For instance, consider a wholly owned foreign subsidiary that is founded in a tax haven with cash as equity that is used to provide debt financing to affiliated subsidiaries in the parent's group that are located in high-tax jurisdictions. This would be considered 14 both a tax haven subsidiary and a foreign direct investment into a tax haven but would not be considered real activity from an economic point of view. Firm headquarters might also theoretically be relocated through mere paper transactions, although anecdotal evidence suggests that domestic tax authorities would closely scrutinize such transactions.

For these reasons, we claim that our particular research setting of firms that use formulary apportionment allows us to observe firms’ isolated location decisions in response to tax haven shutdowns, which is rare in this research area until now. With respect to the firms that use separate accounting in our setting, we rely on previous research for intragroup income shifting channels. In addition, our setting allows us to minimize the heterogeneity of non-tax factors between jurisdictions, which lends our research design strong internal validity. Finally, we observe the effects of tax base allocation not only in tax havens themselves but also in nearby or otherwise similar regions, and we thus include available information on geographic proximity in our analysis.

4 Hypotheses Development

In the following, we use the term ‘tax haven municipality’ to indicate a municipality that is identified as a tax haven, using data from 2001. Moreover, we use the term ‘tax haven district’ to indicate a district that is home to at least one tax haven municipality. We use a trade tax rate of approximately 9.1% for fiscal year 2001 as the upper bound for a tax haven municipality. The rationale for this threshold is that the German federal government disallowed trade tax rates below 9.1% (i.e., a 200% trade tax levy rate) beginning in fiscal year

2004 and explicitly argued that these municipalities were merely acting as domestic tax havens and that they were to be shut down. Thus, we conform to this definition of a domestic trade tax haven and thereby gain the statistical advantage that the change in the tax law was an exogenous shock to the municipalities’ trade tax rate strategy, which yields a straightforward natural experiment. To clearly investigate this setting for both the short-run and long-run effects of the federal tax rate threshold, we include only those tax haven municipalities that actually levied the minimum possible trade tax rate of 9.1% in both 2004 and 2007, i.e., those municipalities that did not actively increase their trade tax rate above the new minimum threshold.

As an overview, Figure 1 schematically represents the development of trade tax levy rates in the tax haven municipalities, and Figure 2 graphically depicts the corresponding expected effects on firm behavior:

Figure 1: Trade Tax Levy Rates in Tax Haven Municipalities

Figure 2: Expected Firm Responses to Tax Haven Shutdown

Generally speaking, we expect firms to react to the tax rate increases by allocating tax base out of the tax haven municipalities by means of both accounting and location decisions.

However, we expect reactions to be different for accounting decisions and location decisions, simply because accounting decisions are arguably cheaper and faster to implement. Therefore, we expect that tax base reductions by means of accounting decisions were immediately im- 17 plemented in 2004 (Figure 2.1) and that such firms were quickly back at their tax strategy equilibrium under the new trade tax regime. Consequently, our prediction is that there are no further changes in accounting decisions after 2004. Conversely, we expect that tax base reductions by means of location decisions can only be conducted at a relatively slow pace (Figure

2.2). The major argument in this respect is that location decisions must be well-considered and are costly to reverse. Consequently, firms that are subject to formulary apportionment shift an increasing number of employees out of tax haven municipalities over time. Thus, we hypothesize the following (all hypotheses are presented as economic expectations):

H1: Both firms that use separate accounting and firms that use formulary ap-

portionment react to the shutdown of tax haven municipalities by reducing tax

base in such municipalities.

With respect to the time pattern of the effect, we assume the following: If a firm is able to react to the tax rate increase with accounting decisions (e.g., setting tax-optimal transfer prices or optimizing the location of debt and intangibles), we assume that the reactions to the shutdown of the tax haven municipality will occur rather quickly. This follows the rationale that paper transactions can be implemented at low cost and high speed. Thus, optimal tax strategies in this regard would likely be fully implemented as soon as possible. Conse- quently, we expect a notable decrease in the relevant tax base in tax haven municipalities in the short run (i.e., from 2001 to 2004) but negligible or small changes from 2004 until 2007.

We therefore technically predict the following:

H2a: Firm reactions to reduce tax base in response to the shutdown of tax ha-

ven municipalities by means of accounting decisions are not significantly dif-

ferent for short run observations and for long run observations.

Regarding the timing pattern of firms that are subject to formulary apportionment, we specifically expect small amounts of tax base reallocation by means of location decisions in the short run (i.e., during the period from 2001 to 2004). However, in the long run (i.e., over the 2001 to 2007 period), firms are expected to demonstrate substantial reaction to the tax haven shutdown by means of location decisions. Thus, we hypothesize the following:

H2b: Firm reactions to reduce tax base in response to the shutdown of tax ha-

ven municipalities by means of location decisions are less pronounced over the

short run and more pronounced over the long run.

We also consider the number of places of business in a given municipality, i.e., the number of legal entities and permanent establishments, over time. Firms may not only shift income out of existing places of business when tax haven municipalities are shut down but also may opt to close them altogether. Thus, we hypothesize the following:

H3: Both firms that use separate accounting and firms that use formulary ap-

portionment react to the shutdown of tax haven municipalities by closing plac-

es of business in such municipalities.

For firms that use separate accounting, we assume the following for the timing of this effect (Figure 2.3). It is not necessary to shut down the entire firm because the tax burden can be transferred quickly and to a large extent by means such as transfer pricing, relocating debt and relocating intangibles. In fact, closing down a firm that is subject to separate accounting demands additional effort (e.g., engaging a notary for closing down the corporation), whereas maintaining the legal shell comes at virtually no cost. Nevertheless, firms are likely to be closed down in the long run when there is no further use for them.

H4a: Firm closings of legal entities in response to the shutdown of tax haven

municipalities are negligible in short-run observations and relatively larger in

long-run observations (separate accounting firms).

For firms that are subject to formulary apportionment, we argue the following (Figure

2.4): The only possibility to save taxes in reaction to the exogenous shock is by shifting employees out of the tax haven municipality into other firm facilities. Moreover, maintaining a permanent establishment is subject to a firm’s real circumstances—as opposed to maintaining a shell company. When all economic activity is pulled out of a permanent establishment, it ceases to exist, which is not the case with shell companies that are subject to separate accounting. However, because location decisions are costly and arguably require long-term planning, we predict that firms’ reactions to the tax rate increase will be made at a relatively slow pace. Specifically, we repeat our prediction that only a small number of permanent establishments are fully closed down in the short run. In the long run, however, the number of final shutdowns of permanent establishments should increase. Consequently, we hypothesize the following:

H4b: There are fewer firm closings of permanent establishments in response to

the shutdown of tax haven municipalities in short-run observations than in

long-run observations (formulary apportionment firms).

5 Data & Research Design a) Data

We use a unique dataset provided by the German fiscal authorities that contains confidential tax return data for the full population of all German commercial firms subject to trade tax in 20014, 2004, and 2007. This dataset includes data from corporations, partnerships and sole proprietorships. Data are available at the level of single taxpayers (single firms) but ex- clude any identifying information. We merged this confidential dataset with a regional database to insert relevant economic variables at the district level into our analyses. Our initial sample contains 5,116,719 firms (9,720,291 firm-years), out of which 278,918 firms

(2,012,817 permanent establishment-years) are subject to formulary apportionment. The variables available in that data set are briefly described in Table 1.

[Insert Table 1 about here] b) Research Design

We rely on two different independent variables for our analysis. First, we investigate

TaxBasei,j,t, which contains information on the trade tax base that is available in our data set of firm i allocated to municipality j in year t, separately for the channel of accounting decisions and the channel of location decisions. Secondly, we use Existencei,j,t, which is a dichotomous variable taking the value of one if firm i has a legal entity or permanent establishment in municipality j in year t and zero otherwise. The results for the endogenous variable Exist- encei,j,t are again computed separately for the subsample of firms subject to separate accounting and those subject to formulary apportionment.

Next, we create a full, balanced panel to control for the fact that legal entities and permanent establishments may be newly founded or have closed down over time. Thus, we

4 We convert 2001 values, which are in Deutsche Marks, to the Euro by dividing the Deutsche Mark values by the relevant factor 1.95583. 21 add observations such that each legal entity or permanent establishment that occurs at least once in our data is observed in each of the three available years. If a given legal entity or permanent establishment does not exist in a given year, i.e., if we had to add the respective observation into the sample, we set the observed value equal to zero for both TaxBasei,j,t and

Existencei,j,t. We can perform this action because we have complete data on all German firms and high-quality, genuine tax return data; thus, if we do not observe a legal entity or permanent establishment in a given year, the most likely reason is that it in fact did not exist during that year. Data quality or sample selection bias is the cause of such missing observations only in exceptional cases.

We begin our discussion with the research design that uses TaxBasei,j,t as the endogenous variable and run the following OLS regression:

��,, = � + �� + ��2004 + ��2007 + ��,

+ ��, ∗ �� + ��, ∗ ��2004 + ��,

∗ ��2007 + ��, ∗ �� ∗ ��2004 + ��,

∗ �� ∗ ��2007 + ∑��,

+ ∑��, + ∑��, + � (1)

where TaxHavenj is a dichotomous variable that takes the value of one for all years for municipality j that has a trade tax rate lower than 9.1% in 2001 and zero otherwise. FE2004t and FE2007t are year-fixed effects. TaxRatej,t is the trade tax levy rate of municipality j in year t. The regression was run separately for the two subsamples of firms subject to separate accounting and firms subject to formulary apportionment.

To account for unobserved variables, we consider not only the tax haven municipalities themselves as our direct treatment group to the exogenous shock but also the municipali-

22 ties that are in the same district as the tax haven municipalities as our control group (together,

‘tax haven districts’). In this manner, we ensure the geographic proximity of the treatment group and control group municipalities and thus ensure a certain degree of comparability among the unobserved characteristics of the investigated jurisdictions.

Consistent with H1, the coefficients for β8 or β9 are expected to have a negative sign in both of the two subsamples, i.e., for firms subject to separate accounting and for firms subject to formulary apportionment. For each subsample, a negative coefficient for β8 or β9 would indicate that firms react to the shutdown of tax haven municipalities by reducing their tax base in tax havens. Moreover, our data would not disprove our hypothesis H2a if β8 and β9 were not significantly different from one another in the subsample of firms subject to separate accounting. It is clear that H2a (i.e., no significant difference between short- and long-run observations when accounting decisions are used) ultimately cannot be technically tested because it assumes the equality of coefficients in the statistical alternative hypothesis. However, we argue that the high data quality and large size of our sample provide our tests of difference between β8 and β9 with reasonable power (i.e., low type II error) and thus that non- significance yields an indication of equality to some extent. Regarding H2b, we also expect that β9 is significantly larger in absolute value than β8 in the sample of firms subject to formulary apportionment.

The analysis for Existencei,j,t followed structurally the same pattern as before. We ran the following logit regression.

��,, = � + �� + ��2004 + ��2007 + ��,

+ ��, ∗ �� + ��, ∗ ��2004 + ��,

∗ ��2007 + ��, ∗ �� ∗ ��2004 + ��,

∗ �� ∗ ��2007 + ∑��,

+ ∑��, + ∑��, + � (2)

Following the discussion of H1, we expect H3 to have significant and negative coefficients β8 or β9 in both subsamples, i.e., both for firms subject to separate accounting and for firms subject to formulary apportionment. Such a general finding indicates that firms react to the tax haven shutdown by closing down places of business in the tax haven municipalities.

With regard to H4a, we expect that β8, in the sample of separate accounting firms, is insignificant or economically negligible and that β9 is significantly larger in absolute value than β8.

Finally, H4b is supported if β9 is significantly larger in absolute value than β8 in the subsample of firms that are subject to formulary apportionment.

Technically, we run four different models for each regression, with the models differ- ing in the extent to which control variables are included (refer to Table 1 for more details).

Model 1 includes only the exogenous variables of interest and the four available firm controls.

Including additional control variables at the municipality and district levels allows us to control for the general economic environment of a particular region, which in turn allows us to control for any remaining heterogeneities among the tax haven municipalities that might explain differences in tax-induced income shifting activity on their own. Therefore, in Model 2, we add selected municipality-level controls. Model 3 then further includes district-level controls on an aggregated level. Finally, Model 4 includes district controls on a disaggregated level and additional district-fixed effects (i.e., 16 different district indicator variables). All models include industry-fixed effects.

6 Descriptive Analysis, Results and Robustness Tests

6.1 Descriptive Analysis

We begin our analysis by exploring selected characteristics of the tax haven municipalities. First, we focus on the number of inhabitants and the surface area in 2001 for all Ger- man municipalities and for tax haven and non-tax haven municipalities separately. Figure 3 shows the respective scatter plots against the trade tax levy rates.

Figure 3: Characteristics of Tax Haven Compared with Non-Tax Haven Municipalities

The average municipality in Germany has 4,020 inhabitants. We find that the majority of the 22 tax havens have fewer than 4,020 inhabitants; only three municipalities have more than this threshold (4,641, 7,360 and 23,782 inhabitants). The mean of all 22 tax havens in our sample is 2,399 inhabitants. We note that the mean in the tax haven municipality sample is particularly influenced by outliers because of the small sample size. Additionally, tax haven municipalities have relatively small surface areas: most of the observed municipalities have a surface area smaller than the average German municipality (30.33 square kilometers). The smallest surface area of a tax haven is 4.3 square kilometers, whereas the largest surface area is approximately 337.84 square kilometers.

Second, we analyze the geographic locations of the tax havens. Specifically, we first investigate the geographic distance of each tax haven municipality from both its regional

25 capital and the federal capital, Berlin. Figure 4 shows the respective scatter plots against the trade tax levy rates.

Figure 4: Distance Analysis of Tax Haven Municipalities

The distances between the tax haven municipalities and their corresponding regional capitals vary from 14 kilometers to 238 kilometers, with a mean distance of 82 kilometers.

Finally, nearly all the tax haven municipalities are less than 250 kilometers from Berlin

(mean: 144 kilometers). Following up on the latter observation, Figure 5 is a map of Germany that shows the geographic locations of the 22 tax haven municipalities identified.

636 kilometers 886 kilometers

Figure 5: Map of Tax Haven Municipalities in Germany

It is apparent from this map that most of Germany’s tax haven municipalities are located in those German states that historically were part of the German Democratic Republic

(Eastern Germany) and that remain economically underdeveloped compared with the more 26 affluent states that historically were part of the Federal Republic of Germany (Western Ger- many). In summary, Germany’s domestic tax haven municipalities exhibit many of the characteristics that are also attributed to tax havens in the global context. Specifically, they are relatively small in population and geographic size, and their economies are relatively less developed. Consequently, it appears that the process involved in becoming a domestic tax haven is somewhat similar to the process involved in becoming an international tax haven.

Next, we investigate the development of trade tax burden in the tax haven municipalities after the minimum threshold trade tax rate was set to 9.1% by the German federal government in 2004 (which corresponds to a 200% trade tax levy rate). Figure 6 shows the results.

Figure 6: Development of Tax Haven Municipalities’ Trade Tax Levy Rates over Time

Figure 6 presents three different groups of tax haven municipalities:

- tax haven municipalities that increased their trade tax rate exactly to the national

minimum threshold of 9.1% in 2004 and stayed at this tax rate until 2007 (red solid

lines in Figure 6);

- tax haven municipalities that increased their trade tax rate exactly to the national

minimum threshold of 9.1% in 2004 but that increased their tax rate further by

2007 (orange solid lines in Figure 6); and

- tax haven municipalities that had increased their trade tax rates above the mini-

mum threshold of 9.1% by 2004; most of these municipalities maintained their

trade tax rates until 2007, although some municipalities increased their rates fur-

ther (black dashed lines in Figure 6).

We focus our analysis only on the first group of tax haven municipalities.

6.2 Results a) Tax Base as the Endogenous Variable

Results are reported for four different models in all cases. The analyses relying on

TaxBasei,j,t are presented in Table 2.

[Insert Table 2 about here]

Regarding H1, we observe in Panel A of Table 2 (i.e., for the firms that rely on separate accounting) that both β8 and β9 are highly significant and negative in all models. Identical results can be observed for Panel B (i.e., for firms that are subject to formulary apportionment). As a result, we report strong and robust findings for our most general prediction, i.e., that firms react to the shutdown of tax haven municipalities by transferring away their tax base.

With regard to H2a, we observe from Panel A in Table 2 that the coefficients for β8 and β9 are economically similar to one another in all four models. In support of this first-sight observation, F-tests for the difference in coefficient between β8 and β9 are insignificant in all

28 four models and thus, as we predicted, our data do not contradict H2a. With respect to the relatively large sample sizes in the analysis of H2a (greater than 120,000 in all four models), we argue that type II error is likely to be small. From this, we conclude that reactions do not differ for separate accounting firms in the long run compared with the short run. In economic terms, we thus find that virtually all the relevant adjustments of the optimal tax strategy for firms subject to separate accounting were undertaken almost immediately in 2004 and that no further adjustments are significantly observable between 2004 and 2007.

We find structurally identical results for H2b. This is unexpected and does not support our hypothesis H2b. Most particularly, F-tests for differences in coefficients among the short- run observations (β8) and the long-run observations (β9) are insignificant in all four models.

Thus, we find that firms subject to formulary apportionment altered their tax strategy almost immediately by means of location decisions in 2004 and did not undertake significant further adjustments between 2004 and 2007. b) Existence as the Endogenous Variable

Results are reported for four different models in all cases. The analyses relying on Ex- istencei,j,t are presented in Table 3.

[Insert Table 3 about here]

Regarding H3, Panel A of Table 3 (i.e., for the firms subject to separate accounting) shows that both β8 and β9 are insignificant in all models. Consequently, H3 is not supported in connection with accounting decisions. Conversely—and similar to H1—we find highly significant negative coefficients β8 and β9 in Panel B of Table 3 for two of the four models and thus for firms that rely on formulary apportionment. This finding implies that the shutdown of tax

29 havens is associated with a shutdown of permanent establishments by multipermanent establishment firms but not with a shutdown of single-permanent establishment firms altogether.

With respect to H4a, we note that the F-tests for differences in coefficients between β8 and β9 are not significantly different from one another. Thus, and partially in contrast to our hypothesis H4a, we find no effect of tax haven shutdown on the number of separate accounting firms, either in the short run or in the long run. Considering H4b, we find again that F- tests are non-significant and that β8 and β9 are thus not significantly different from one another. This indicates that closures of permanent establishments in response to the shutdown of the tax haven municipality were conducted immediately in 2004 and that the additional effects between 2004 and 2007 were negligible. This result for H4b is consistent with our previous findings from H2b. c) Discussion

Considering our results altogether, we find in H1 that both separate accounting firms and formulary apportionment firms react to the shutdown of tax havens by allocating tax base out of the respective municipalities in which the exogenous tax rate increase occurs. Conse- quently, both accounting decisions and location decisions are used for tax-induced income shifting on the merits. Moreover, for both groups of firms, we find in H2a and H2b that this effect appears to be the strongest in the 2001-2004 period and is negligible for the subsequent

2004-2007 period. We conclude that firms’ tax strategy adjustments appear to have been conducted almost immediately and completely after the tax rate increase in 2004 and then re- mained relatively stable at the new equilibrium. This finding is unexpected for firms that are subject to formulary apportionment because location decisions are generally expected to be implemented relatively slowly. We believe that these firms might have anticipated the federal tax rate change that was hotly debated in the political arena and that they thus adapted their

30 tax strategy accordingly prior to the actual implementation of the minimum trade tax threshold of 9.1%.

Regarding the number of places of business (instead of the tax base), we find in H3 that only formulary apportionment firms react to the tax rate increase in tax haven municipalities by closing down permanent establishments. This indicates that firms that are subject to separate accounting are kept legally active, despite the fact that tax base is shifted out. We argue that this shows the powerful means of income shifting that separate accounting firms have, such as transfer pricing, debt reallocation and the reallocation of intangibles. These means enable the separate accounting firms to quickly strip income from firms located in tax haven municipalities without closing down their legal shells. Conversely, the existence of a permanent establishment is subject to an analysis of the factual circumstances of each case: when all economic activity is pulled out of a permanent establishment, the permanent establishment ceases to exist without the possibility of maintaining its legal shell. We conclude that this overall finding indicates the artificial nature of accounting decisions and tax-induced income shifting of separate accounting firms.

6.3 Robustness Tests

We conduct robustness tests to evaluate our reported results. In these tests, we alter the control variables included in our models to determine how sensitive our results are to those changes (not tabulated). We find virtually identical results as in our baseline specifications.

This holds for both the economic and statistical significance of our findings.

Moreover, when we repeat the analysis above for all tax haven municipalities in our dataset, i.e., not limiting our analysis to those municipalities that show a trade tax rate of 9.1% in 2001 and that made no subsequent changes after 2004, we find virtually identical results

(not tabulated). In particular, further changes in the tax rate above the 9.1% threshold, either

31 immediately in 2004 or thereafter, are not strong enough to provide incentives that are compa- rable to those of the exogenous tax rate increase by the federal government in 2004.

7 Conclusion

We investigate the effect of a shutdown of tax havens on firms’ behavior by using a peculiarity of the German trade tax regime in which municipalities compete using their business tax rates, specifically their trade tax rates. In this setting, tax haven municipalities offer trade tax rates as low as 0%, whereas the average trade tax rate of all German municipalities is 13.1%. These tax haven municipalities have similar competitive objectives as foreign tax havens, namely, to attract tax base from higher tax jurisdictions. Based explicitly on the political aim to shut down domestic tax haven activity, the German federal government decided that all municipalities must set a minimum trade tax rate of 9.1% beginning in 2004. This policy change presented an exogenous shock to Germany’s tax haven municipalities.

We use this shock to investigate the response by businesses in the tax haven municipalities, and we distinguish among firms subject to separate accounting and firms subject to formulary apportionment. We find that both groups of firms reacted to the tax haven shutdowns. More specifically, we find that firms subject to either separate accounting or formulary apportionment both reacted quickly to the tax haven shutdown and that incremental, long-run reactions are not statistically significant. There are myriad reasons for the rapid, short-run reaction of both groups: firms subject to separate accounting can react relatively quickly because accounting decisions (i.e., transfer pricing and the allocation of debt or intangibles) can be implemented quickly with relatively little cost. Both groups of firms can react relatively quickly to this exogenous shut down because the change in the law was known somewhat ahead of actual implementation and a rescission of the law was highly unlikely.

Additionally, we find that firms subject to formulary apportionment also closed a significant number of permanent establishments as a consequence of tax haven shutdowns by the federal government, whereas firms subject to separate accounting did not significantly decrease in number. We conjecture that the latter result is related to the fact that accounting decisions can

33 be used to reallocate tax base to a relatively large extent and, thus, that there are only limited reasons for completely closing the respective entities.

This paper contributes to the ongoing debate about the channels of income shifting.

Our results show that both accounting decisions and location decisions are viable channels of income shifting and that both channels are used in response to the shutdown of a tax haven.

This result indicates that they are also used to shift income into tax havens in the first place.

Finally, our findings suggests that both accounting decisions—such as transfer pricing policy and the location of debt or intangibles—and location decisions should be taken into account by developed countries that aim to shut down tax havens.

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Table 1 Variable Explanations Trade tax base of a firm i allocated to municipality j in year t; separately for the channel of accounting Tax Base decisions and the channel of location decisions Dichotomous variable taking value one if firm i has a legal entity or permanent establishment in municipality j Exis tence in year t; and zero otherwise TaxRate trade tax rate of the municipality j a given municipality is identified as a tax haven according to its 2001 characteristics; TaxHaven labeled as tax haven municipality (or: THM) tax haven district a district in which at least one tax haven is located year04 Dummy Variable taking the value 1 if the observation is from fiscal year 2004, 0 otherwise year07 Dummy Variable taking the value 1 if the observation is from fiscal year 2007, 0 otherwise Firm Controls High Real Estate Dummy Variable taking the value 1 if firm i has more real estate than the mean of the full sample, 0 otherwise High Donations Dummy Variable taking the value 1 if firm i has more donations than the mean of the full sample, 0 otherwise No. of facilities Number of facilities of a firm i Leverage Dummy Variable taking the value 1 if payments for permanent debt are greater than zero, 0 otherwise Municipality Controls Inhabitants Number of inhabitants in municipality j Real Property Tax A Real Property Tax for agriculture, measured in % Real Property Tax B Real Property Tax for architectural purposes, measured in % District Controls Size of district Size of a district k, measured in squared kilometres (km ) Birth - Total Births of all genders in a district k Cash Result Cash Result is the result of operting income in a district k less operating expenses in the same district k Average Purchase Price Land Average purchase price per squared meter (m ) in one year in district k in ths. Euros - total GDP p er In h ab it an t s UnemploymentGross domestic calculatedproduct per as inhabitant the ratio of unemployed persons and the whole employable population in Unemployment Rate district k Available Income per Household Average income per household in district k Moving In Immigration over a district border k age under 18 age 18-25 age 25-30 Segmentation in different age groups age 30-50 age 50-65 age > 65 Total Sum of all moving ins into district k Moving Out Emigration over a district border k age under 18 age 18-25 age 25-30 Segmentation in different age groups age 30-50 age 50-65 age > 65 Total Sum of all moving outs out of district k Business Registration Umbrella term for all business registrations in one year in district k for different reasons Reconstruction Business Registrations due to reconstruction in one year in district k Moving In Business Registrations due to moving in in one year in district k Moving Out Business Registrations due to moving out in one year in district k Total Sum of all business registrations in one year in district k Business Cancellation Umbrella term for all business cancellations in one year in district k for different reasons Abandonment Business Cancellations due to abandonment in one year in district k Moving Out Business Cancellations due to moving out in one year in district k Transfer Business Cancellations due to transfer in one year in district k Total Sum of all business cancellations in one year in district k Areas Umbrella term for all areas Land Area Land area is the sum of Settlement and Traffic Area, Farmland, Wood Area, Water Area and Mining Land Building Open Area Housing Building Open Area Housing in district k Building Open Area Business Building Open Area Business in district k Plant Area Plant Area in district k without Mining Land Traffic Area Traffic Area in district k Farmland Area of agriculture (marsh and moorland among others) Tourism Umbrella term for tourism key figures in district k Beds Offered guest beds in district k Guests Overnight Stay Guests Overnight Stay in district k

Table 2 The closure of Tax Havens (H1 and H2)

PANEL A: Tax Base and Separate Accounting

��,� ,� = �0 + �1�� + �2��2004� + �3��2007� + �4�� ,� + �5��,� ∗ �� + �6�� ,� ∗ ��2004� + �7�� ,�

∗ ��2007� + �8��,� ∗ �� ∗ ��2004� + �9��,� ∗ �� ∗ ��2007� + ∑��,�

+ ∑�� ,� + ∑�� ,� + � (1)

Independent Variable Pred. Sign Model 1 Model 2 Model 3 Model 4

Intercept 10,359.86 19,288.91 98,257.36 57,803.06 Tax Rate -25.90*** -17.39*** -2.83 -0.46 Year04 -3,978.83* -3,363.90 1,948.87 0.00 Year07 -3,163.63 -3,177.31 6,010.45** 0.00 Tax Haven 12,988.40*** 11,119.65*** -1,892.47 -2,195.29 Tax Rate * Year04 13.22* 11.89 -10.94 -14.70 Tax Rate * Year07 11.19 12.72 -16.98* -22.58** 280.75*** 287.25*** 327.97*** 325.45*** Tax Rate * Tax Haven + (18,61) (18.84) (19.37) (18.98) -266.48*** -269.65*** -289.70*** -282.96*** Tax Rate * Tax Haven * Year04 - (-14.71) (-14.87) (-14.79) (-14.16) -278.91*** -286.75*** -317.13*** -315.10*** Tax Rate * Tax Haven * Year07 - (-17.25) (-17.59) (-17.81) (-17.43) Firm Controls yes yes yes yes Municipality Controls no yes yes yes District Controls (aggregated) no no yes no District Controls (disaggregated) no no no yes Industry fixed effects yes yes yes yes District fixed effects no no no yes Adj. R 0.86% 0.91% 1.08% 1.09% N 137,237 137,237 120,932 120,932

Each of the variables is defined in Table 1.

*, **, *** significant at the 10%, 5% and 1% level (all p-values are based on two-tailed t-tests). (t-values in parantheses)

Table 2 The closure of Tax Havens (H1 and H2)

PANEL B: Tax Base and Formulary Apportionment

��,� ,� = �0 + �1�� + �2��2004� + �3��2007� + �4�� ,� + �5��,� ∗ �� + �6�� ,� ∗ ��2004� + �7�� ,�

∗ ��2007� + �8��,� ∗ �� ∗ ��2004� + �9��,� ∗ �� ∗ ��2007� + ∑��,�

+ ∑�� ,� + ∑�� ,� + � (1)

Independent Variable Pred. Sign Model 1 Model 2 Model 3 Model 4

Intercept 443,845.40 860,623.30 -330,775.50 4,644,315.00 Tax Rate -1,518.52 -930.97 1,040.54 1,070.84 Year04 -693,848.80 -625,012.70 -4,241.13 0.00 Year07 199,031.90 112,511.10 766,429.80 0.00 Tax Haven 1,067,812.00 1,196,863.00* -2,351,990.00*** -2,383,122.00*** Tax Rate * Year04 2,356.34 2,189.18 108.25 13.34 Tax Rate * Year07 948.08 778.95 -2,191.79 -2,657.51 90,907.56*** 91,164.34*** 93,066.87*** 92,952.88*** Tax Rate * Tax Haven + (18.64) (18.56) (17.32) (17.23) --87,661.03*** -87,769.76*** -88,028.71*** -87,600.53*** Tax Rate * Tax Haven * Year04 - (--15.08) (-15.09) (-14.02) (-13.86) -89,261.88*** -89,713.95*** -91,178.42*** -91,194.24*** Tax Rate * Tax Haven * Year07 - (-17.10) (-17.08) (-16.00) (-15.94) Firm Controls yes yes yes yes Municipality Controls no yes yes yes District Controls (aggregated) no no yes no District Controls (disaggregated) no no no yes Industry fixed effects yes yes yes yes District fixed effects no no no yes Adj. R 2.66% 3.13% 2.75% 2.70% N 20,151 20,151 17,257 17,257

Each of the variables is defined in Table 1.

*, **, *** significant at the 10%, 5% and 1% level (all p-values are based on two-tailed t-tests). (t-values in parantheses)

Table 3 The closure of Tax Havens (H3 and H4)

PANEL A: Existence (Number of Firms) and Separate Accounting

��,� ,� = �0 + �1�� + �2��2004� + �3��2007� + �4�� ,� + �5��,� ∗ �� + �6�� ,� ∗ ��2004� + �7��,�

∗ ��2007� + �8��,� ∗ �� ∗ ��2004� + �9��,� ∗ �� ∗ ��2007� + ∑��,�

+ ∑�� ,� + ∑�� ,� + � (2)

Independent Variable Pred. Sign Model 1 Model 2 Model 3 Model 4

Intercept -1.34*** -1.51*** -4.53*** -6.70*** Tax Rate 0.01*** 0.01*** 0.01*** -0.01*** Year04 1.28*** 1.28*** 1.64*** -0.69*** Year07 1.75*** 1.76*** 1.77*** -1.30*** Tax Haven 0.53*** 0.61*** -0.34** -0.27* Tax Rate * Year04 0.01*** -0.01*** -0.01*** -0.01*** Tax Rate * Year07 0.01*** -0.01*** -0.01*** -0.01*** 0.17 0.17 0.17 0.19 Tax Rate * Tax Haven + (0.03) (0.03) (0.04) (0.02) -0.18 -0.18 -0.18 -0.19 Tax Rate * Tax Haven * Year04 - (-0.03) (-0.03) (-0.04) (-0.02) -0.18 -0.18 -0.18 -0.19 Tax Rate * Tax Haven * Year07 - (-0.03) (-0.03) (-0.04) (-0.02) Firm Controls yes yes yes yes Municipality Controls no yes yes yes District Controls (aggregated) no no yes no District Controls (disaggregated) no no no yes Industry fixed effects yes yes yes yes District fixed effects no no no yes Adj. R 1.21% 1.23% 2.11% 2.46% N 103,983 103,983 92,677 92,677

Each of the variables is defined in Table 1.

*, **, *** significant at the 10%, 5% and 1% level (all p-values are based on two-tailed t-tests). (t-values in parantheses)

Table 3 The closure of Tax Havens (H3 and H4)

PANEL B: Existence (Number of Perm. Establishments) and Formulary Apportionment

��,� ,� = �0 + �1�� + �2��2004� + �3��2007� + �4�� ,� + �5��,� ∗ �� + �6�� ,� ∗ ��2004� + �7��,�

∗ ��2007� + �8��,� ∗ �� ∗ ��2004� + �9��,� ∗ �� ∗ ��2007� + ∑��,�

+ ∑�� ,� + ∑�� ,� + � (2)

Independent Variable Pred. Sign Model 1 Model 2 Model 3 Model 4

Intercept -1.48 -1.73 -3.71** 2.89 Tax Rate 0.01 0.01 0.01 0.01 Year04 0.62 0.58 0.67 0.05 Year07 1.39*** 1.35*** 1.92*** 2.72*** Tax Haven 1.44*** 1.56*** 0.12 0.24 Tax Rate * Year04 -0.01 -0.01 -0.01 -0.01 Tax Rate * Year07 -0.01 -0.01 -0.01 -0.01 0.20*** 0.20*** 0.15 0.17 Tax Rate * Tax Haven + (70.38) (67.90) (0.03) (0.01) +++ +++ -0.15 -0.17 Tax Rate * Tax Haven * Year04 - -0.21 -0.21 (n/a) (n/a) (-0.03) (-0.01) -0.21*** -0.21*** -0.15 -0.17 Tax Rate * Tax Haven * Year07 - (-67.58) (-66.18) (-0.03) (-0.01) Firm Controls yes yes yes yes Municipality Controls no yes yes yes District Controls (aggregated) no no yes no District Controls (disaggregated) no no no yes Industry fixed effects yes yes yes yes District fixed effects no no no yes Adj. R 6.00% 6.03% 8.37% 9.20% N 12,372 12,372 10,478 10,478

Each of the variables is defined in Table 1.

*, **, *** significant at the 10%, 5% and 1% level (all p-values are based on two-tailed t-tests). (t-values in parantheses)