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Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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The Evaluation of Efficiency of Corporate Inversions

P. 54–55.
Makarova V. A., Dalal A.

The study considers corporate inversion, also known as tax inversion, which involves companies to move their operations overseas in order to avoid tax burden in the domestic country. Although the following strategy gains popularity among corporate managers, experts emphasize its’ controversial and risky nature (Lusch et al., 2016). The aim of this paper is twofold. First, we consider previous literature and market trends to create a classification of corporate inversions. Second, the efficiency of inversions is measured using event study method and Monte-Carlo tool. Data sample was collected from Compustat and Thomson Reuters; it covers 18 firms that undertook inversion strategy in the period from 2008 to 2014. The first part of the study reveals that although corporate inversions are a subject of comprehensive research efforts, the consensus regarding its’ effect on firm’s prospects has not yet been reached among academic scholars. It was seen that in long-term perspective inversions hamper business sustainability due to lack of administration in the company’s new domicile (Cortes et al., 2016; Laing et al., 2019). At the same time, shareholders’ positive attitude towards this strategy is observed which casts doubt on their rationality. However, we found studies that highlight strongly positive impact of inversions on share prices of firms which lowered corporate tax rate and saved best practices of corporate control (Col et al., 2016). This fact explains why shareholders vote in favour of these arrangements.

We found that discrepancy in previous research is due to chosen data. To achieve the first aim and for the sake of our empirical study, we divided previous deals in two groups according to their purposes, structure and headquarters country. The first group consists of transactions in the times when market was in its’ infancy, such schemes are not used in recent deals. Including this group in our sample may provide irrelevant results, as it was seen in previous studies. Final sample included inversions announced in the period from July 2008 to June 2014. Data was limited to U.S. public companies to make it comparable. At the first stage, we considered market reaction to the announcement of inversion using event study method. Under assumption of efficient markets, the cumulative abnormal return (CAR) of company’s share prices is considered to be a robust indicator of inversion’s efficiency. Further, we integrated the whole sample using average of each company’s CAR (CAAR). In order to consider not only immediate effect of the deal but also its’ long-run consequences, our methodology includes the analysis of the event, three months prior to it and subsequent seven months. We found that CAAR is positive during the studied period, significant at 1% confidence level and growing few months before the inversion in announced. The observed phenomenon may stem from investors expectations of the deal due to noticed internal changes in the company. At the second stage, Monte-Carlo method was implemented to run simulations based on calculated returns. CAAR was seen to be positive with increasing trend throughout the observation window. The analysis showed 9% probability of a negative CAAR and 41% chance of CAAR to be around 0.04. Our results support the view that inversions are an efficient corporate tool in investors opinion, as it is seen from the hike of company’s value in the period of deal announcement. The main limitation of this study is that the results are hardly extrapolated to other samples, since inversions are dynamic and change when companies need to adapt to new regulatory environment. Nevertheless, the algorithm of the evaluation of these deals is versatile and may be applied to different types of corporate inversions, which is the primary contribution of the paper.

Language: English
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Keywords: метод Монте-КарлоMonte Carlo methodанализ событий event studycorporate inversiontax inversionкорпоративная инверсияналоговая инверсия

In book

III International Science Conference SER 2020. New Trends and Best Practices in Socioeconomic Research
III International Science Conference SER 2020. New Trends and Best Practices in Socioeconomic Research
Podgorica: Economic Laboratory for Transition Research, Podgorica, Montenegro, 2020.
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