Are foreign investors locusts? The long-term effects of foreign institutional ownership

Bena, Jan; Ferreira, Miguel A.; Matos, Pedro; Pires, Pedro

doi:10.1016/j.jfineco.2017.07.005

Cited by 487 publications

(206 citation statements)

References 69 publications

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“…Evidence of a positive relationship between foreign ownership and innovation has been previously found for China by Choi et al (2011), European countries by Falk (2008) and for a worldwide sample of firms by Bena, Ferreira, Matos, and Pires (2017). We find that for Indian firms, foreign ownership is associated with the conditional odds ratio of research-activity being smaller by 800%.…”

supporting

confidence: 68%

Collaboration and innovation: An empirical study of Indian technological enterprises

Heaton

Kolluru

Mukhopadhaya

2020

Econ of Transit and Inst Chang

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In 2010, the Indian government declared 2010–2020 to be the ‘Decade of Innovation’ and established the State Innovation Councils and Sectoral Innovation Councils to encourage and facilitate innovation by technological firms. In this paper, we study the relationship between collaboration and innovation in a cross‐section of Indian firms, paying particular attention to the impact of the innovation councils. Our results suggest that domestic collaborations have an important impact on firm innovation, as do the innovation councils, but that the impact of the councils is less for firms that collaborate.

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supporting

confidence: 68%

Collaboration and innovation: An empirical study of Indian technological enterprises

Heaton

Kolluru

Mukhopadhaya

2020

Econ of Transit and Inst Chang

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“…For the relevant studies, Aggarwal et al (2011) found that firms with higher institutional ownership are more likely to terminate poorly performing Chief Executive Officers (CEOs) and exhibit improvements in valuation over time, indicating that international portfolio invested by institutional investors promotes good corporate governance practices around the world. Bena et al (2017) argued that greater foreign institutional ownership fosters long-term investment in tangible, intangible, as well as human capital and leads to significant increases in innovation output. Feng, Zhou, and Chan (2014) documented that institutional investors exhibit a smart money effect that can move new money into (out of) future good (poor) performers.…”

Section: Institutional Investorsmentioning

confidence: 99%

Does “Resetting” by Changing Corporate Name or Industry Category Appeals to Institutional Investments?

Huang¹,

Cheng

2020

CMR

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We investigate whether firms changing their names or industry categories once and more than once would affect institutional shareholdings. By utilizing 5,733 observations of the Taiwan Stock Exchange listed firms, we apply multiple regression models firstly and Petersen regression models for further investigation to enhance the robustness of the empirical results. We then disclose several important findings as follows. First, institutional investors might not prefer holding the shares of the firms changing their names more than once. We infer that the performances of the firms changing names more than once might be doubtful. Second, institutional investors might decrease the shareholdings of the firms with industry categories changed. We claim that institutional investors might suspect these firms probably existing corporate governance issues. Besides, we argue that, to our best understanding, this study might fill the gap in the existing literature due to that the issues, firms changing their names or industry categories once or more than once, seem rarely explored in the relevant studies.

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“…Recent examples include Bena et al . () and Tarasconi and Menon (). The general term for these approximate methods is probabilistic record linkage , which was first proposed in the seminal work by Fellegi and Sunter ().…”

Section: Introductionmentioning

confidence: 97%

A Data-Driven Supply-Side Approach for Estimating Cross-Border Internet Purchases Within the European Union

Meertens

Diks

Herik

et al. 2019

Journal of the Royal Statistical Society Series A: Statistics in Society

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Summary The digital economy is a highly relevant item on the European Union's policy agenda. We focus on cross‐border Internet purchases, as part of the digital economy, the total value of which cannot be accurately estimated by using existing consumer survey approaches. In fact, they lead to a serious underestimation. To obtain an accurate estimate, we propose a three‐step data‐driven approach based on supply‐side data. For the first step, we develop a data‐driven generic method for firm level probabilistic record linkage of tax data and business registers. In the second step, we use machine learning to identify webshops based on website data. Then, in the third step, we implement recently developed bias correction techniques that have hitherto been overlooked by the machine learning community. Subsequently, we claim that our three‐step approach can be applied to any European Union member state, leading to more accurate estimates of cross‐border Internet purchases than those obtained by currently existing approaches. To justify the claim, we apply our approach to the Netherlands for the year 2016 and find an estimate that is six times as high as current estimates, having a standard deviation of 8%. Hence, we may conclude that our new approach deserves more investigation and applications.

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Are foreign investors locusts? The long-term effects of foreign institutional ownership

Cited by 487 publications

References 69 publications

Collaboration and innovation: An empirical study of Indian technological enterprises

Collaboration and innovation: An empirical study of Indian technological enterprises

Does “Resetting” by Changing Corporate Name or Industry Category Appeals to Institutional Investments?

A Data-Driven Supply-Side Approach for Estimating Cross-Border Internet Purchases Within the European Union

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