457 research outputs found

    Taxation and Capital Structure Choice – Evidence from a Panel of German Multinationals

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    This paper analyzes the impact of taxes and lending conditions on the financial structure of multinationals' foreign affiliates. The empirical analysis employs a large panel of affiliates of German multinationals in 26 countries in the period from 1996 until 2003. In accordance with the theoretical predictions, the effect of local taxes on leverage is positive for both types of debt. Moreover, while adverse local credit market conditions are found to reduce external borrowing, internal debt is increasing, supporting the view that the two channels of debt finance are substitutes.corporate income tax, multinationals, capital structure, firm-level data

    The Impact of Thin-Capitalization Rules on Multinationals' Financing and Investment Decisions

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    This paper analyzes the role of Thin-Capitalization rules for capital structure choice and investment decisions of multinationals. A theoretical analysis shows that the imposition of such rules tends to affect not only the leverage and the level of investment but also their tax-sensitivity. An empirical investigation of leverage and investment reported for affiliates of German multinationals in 24 countries in the period between 1996 and 2004 offers some support for the theoretical predictions. While Thin-Capitalization rules are found to be effective in restricting debt finance, investment is found to be more sensitive to taxes if debt finance is restricted.Corporate Income Tax, Multinationals, Leverage, Thin-Capitalization Rules, Firm-Level Data

    Anti Profit-Shifting Rules and Foreign Direct Investment

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    This paper explores the effects of tax provisions aimed at restricting multinationals’ tax planning on foreign direct investment (FDI). Using a unique dataset which allows us to observe the worldwide activities of a large panel of multinational firms, we test how limitations of interest tax deductibility, so-called thin-capitalization rules, and regulations of transfer pricing by the host country affect investment and employment of foreign subsidiaries. The results indicate that, compared with the unrestricted case, in the presence of a typical thin-capitalization rule, the tax-rate sensitivity of FDI is about twice as large. Moreover, introducing such a rule or making it more tight exerts significant adverse effects on the level of FDI in high-tax countries. Regulations of transfer pricing, however, are not found to exert significant effects on FDI

    The Impact of Thin-Capitalization Rules on Multinationals’ Financing and Investment Decisions

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    This paper analyzes the role of Thin-Capitalization rules for capital structure choice and investment decisions of multinationals. A theoretical analysis shows that the imposition of such rules tends to affect not only the leverage and the level of investment but also their tax-sensitivity. An empirical investigation of leverage and investment reported for affiliates of German multinationals in 24 countries in the period between 1996 and 2004 offers some support for the theoretical predictions. While Thin-Capitalization rules are found to be effective in restricting debt finance, investment is found to be more sensitive to taxes if debt finance is restricted

    Taxation and Capital Structure Choice – Evidence from a Panel of German Multinationals

    Full text link
    This paper analyzes the impact of taxes and lending conditions on the financial structure of multinationals’ foreign affiliates. The empirical analysis employs a large panel of affiliates of German multinationals in 26 countries in the period from 1996 until 2003. In accordance with the theoretical predictions, the effect of local taxes on leverage is positive for both types of debt. Moreover, while adverse local credit market conditions are found to reduce external borrowing, internal debt is increasing, supporting the view that the two channels of debt finance are substitutes

    Machine Learning Based Diagnostics of Developmental Coordination Disorder using Electroencephalographic Data

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    We report on promising results concerning the fast and accurate diagnosis of developmental coordination disorder (DCD) which heavily impacts the life of affected children with emotional and behavioral issues. Using a machine learning classifier on spectral data of electroencephalography (EEG) recordings and unfolding the traditional frequency bandwidth in a fine-graded equidistant 99-point spectrum we were able to reach an accuracy of over 99.35 percent having only one misclassification. Our machine learning work contributes to healthcare and information systems research. While current diagnostic methods in use are either complicated, time-consuming, or inaccurate, our automated machine-based approach is accurate and reliable. Our results also provide more insights into the relationship between DCD and brain activity which could stimulate future work in medicine
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