Intangible Assets and Capital Structure

Lim, Steve C.; Macias, Antonio J.; Moeller, Thomas

doi:10.2139/ssrn.2514551

Cited by 58 publications

(58 citation statements)

References 9 publications

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“…Proof of Proposition 5: Let us first prove (47). From optimal control theory, we know that the value function ζ that maximizes (A.31) is the one that involves maximizing the integral pointwise.…”

Section: Appendixmentioning

confidence: 98%

Optimal Financing for R&D-Intensive Firms

Thakor

2017

SSRN Journal

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Raj Singh, and seminar participants at MIT and the 2017 American Finance Association Meetings for helpful comments and discussions. We also thank Xuelin Li for research assistance. Any remaining errors are our own. Research support from the MIT Laboratory for Financial Engineering is gratefully acknowledged. The views and opinions expressed in this article are those of the authors only and do not necessarily represent the views and opinions of any other organizations, any of their affiliates or employees, any of the individuals acknowledged above, or the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w23831.ack NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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Section: Appendixmentioning

confidence: 98%

Optimal Financing for R&D-Intensive Firms

Thakor

2017

SSRN Journal

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“…As Lim et al (2020) indicate, internally generated intangible assets are reported in balance sheets and other companies' reports. For that reason, it is very difficult to evaluate the impact of intangibles on financial leverage (under accounting rules, most of the internally generated intangible assets are not recognized on the balance sheet).…”

Section: Intangibilitymentioning

confidence: 99%

“…The accounting approach is different from externally acquired intangible assets that are capitalized. Lim et al (2020) also point out that intangible assets may discourage debt financing because of poor collateralizibility and high valuation risk. However, they come to the conclusions that identifiable intangible assets have the same positive influence on financial leverage as tangible assets, and that they support debt.…”

Section: Intangibilitymentioning

confidence: 99%

Capital Structure Choices in Technology Firms: Empirical Results from Polish Listed Companies

Kędzior

Grabińska

Grabiński

et al. 2020

JRFM

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The main aim of the paper is the identification of capital structure determinants, with a special emphasis on investments in the innovativeness of Polish New Technology-Based Firms (NTBFs). Poland is a unique country in that it is an emerging market that was also promoted in 2018 to the status of a developed country. The study sample consisted of 31 companies listed in the Warsaw Stock Exchange that are classified as high-tech firms and covers the period 2014–2018. The following factors influencing the capital structure were analyzed: internal and external innovativeness and the firm’s size, liquidity, intangibility, age, profitability, and growth opportunities. The results of the research provide empirical evidence that liquidity, age, and investments in innovativeness determine capital structure, which provides an additional argument supporting the trade-off theory and the modified version of the pecking order theory. More specifically, the results suggest that companies whose process of investment in innovativeness is based on the external acquisition of technology are able to attract external financing, while the process based on internally generated innovativeness (R&D activity) deters external capital. The results are interesting for policymakers in emerging markets.

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“…Their value is more sensitive to who owns and employs them. This makes many intangible assets poor collateral and favour financing with equity instead of debt [71].…”

Section: Variablesmentioning

confidence: 99%

Untitled

2019

IJUR

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The purpose of this research is to contribute to the finance literature by providing further evidence on the determinants of capital structure. This research is novel given the fact that not many researches has been done on firms classified as financially distressed. In this research, firm level yearly data of firms listed as financially distressed under the requirement of Practice Notes 4, Amended Practice Notes 17 and Practice Notes 17 were used. The final sample consists of 190 observations. Static panel data analysis techniques were considered in analyzing the data. The results of the regression suggest that firm's changes in investment, investment opportunity, tangible assets, intangible assets and liquid assets is the independent variable found to have a statistically significant relationship with capital structure. The remaining independent variables do not appear to have a statistically significant relationship with capital structure.

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Intangible Assets and Capital Structure

Cited by 58 publications

References 9 publications

Optimal Financing for R&D-Intensive Firms

Optimal Financing for R&D-Intensive Firms

Capital Structure Choices in Technology Firms: Empirical Results from Polish Listed Companies

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