To read this content please select one of the options below:
Please note you do not have access to teaching notes, research on capital structure determinants: a review and future directions.
International Journal of Managerial Finance
ISSN : 1743-9132
Article publication date: 3 April 2017
The purpose of this paper is to study the status of studies on capital structure determinants in the past 40 years. This paper highlights the major gaps in the literature on determinants of capital structure and also aims to raise specific questions for future research.
![](http://academichelp.site/777/templates/cheerup/res/banner1.gif)
Design/methodology/approach
The prominence of research is assessed by studying the year of publication and region, level of economic development, firm size, data collection methods, data analysis techniques and theoretical models of capital structure from the selected papers. The review is based on 167 papers published from 1972 to 2013 in various peer-reviewed journals. The relationship of determinants of capital structure is analyzed with the help of meta-analysis.
Major findings show an increase of interest in research on determinants of capital structure of the firms located in emerging markets. However, it is observed that these regions are still under-examined which provides more scope for research both empirical and survey-based studies. Majority of research studies are conducted on large-sized firms by using secondary data and regression-based models for the analysis, whereas studies on small-sized firms are very meager. As majority of the research papers are written only at the organizational level, the impact of leverage on various industries is yet to be examined. The review highlights the major determinants of capital structure and their relationship with leverage. It also reveals the dominance of pecking order theory in explaining capital structure of firms theoretically as well as statistically.
Originality/value
The paper covers a considerable period of time (1972-2013). Among very few review papers on capital structure research, to the best of authors’ knowledge; this is the first review to identify what is missing in the literature on the determinants of capital structure while offering recommendations for future studies. It also synthesize the findings of empirical studies on determinants of capital structure statistically.
- Literature review
- Meta-analysis
- Capital structure
- Pecking order
Kumar, S. , Colombage, S. and Rao, P. (2017), "Research on capital structure determinants: a review and future directions", International Journal of Managerial Finance , Vol. 13 No. 2, pp. 106-132. https://doi.org/10.1108/IJMF-09-2014-0135
Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited
Related articles
All feedback is valuable.
Please share your general feedback
Report an issue or find answers to frequently asked questions
Contact Customer Support
Last updated 27/06/24: Online ordering is currently unavailable due to technical issues. We apologise for any delays responding to customers while we resolve this. For further updates please visit our website: https://www.cambridge.org/news-and-insights/technical-incident
We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings .
Login Alert
![determinants of capital structure literature review determinants of capital structure literature review](https://www.cambridge.org/core/cambridge-core/public/images/logo_core.png)
- > Journals
- > Journal of Financial and Quantitative Analysis
- > Volume 58 Issue 6
- > Determinants of Capital Structure: An Expanded Assessment
![determinants of capital structure literature review determinants of capital structure literature review](https://static.cambridge.org/covers/JFQ_0_0_0/journal-of-financial-and-quantitative-analysis.jpg)
Article contents
Determinants of capital structure: an expanded assessment.
Published online by Cambridge University Press: 09 December 2022
- Supplementary materials
Using a standardized methodology, we empirically evaluate 55 proposed determinants of capital structure in terms of statistical significance, economic significance, and identification. We find that robust and economically important determinants of debt ratios are relatively few in number. Nevertheless, because each determinant relates to one of five market imperfections—taxes, distress costs, information asymmetry, agency costs, or supply frictions—we draw conclusions from the evidence as a whole regarding the explanatory power of different capital structure theories. We find greater support for pecking order theory and supply-related theories, with less support for traditional tradeoff theory and agency theory.
Access options
For generously sharing data, we thank Ramin Baghai, Lucian Bebchuk, Efraim Benmelech, Adam Bonica, Filipe Campante, Quoc-Anh Do, John Graham, Barry Hirsch, Gerard Hoberg, Jay Li, David Macpherson, Stephen McKeon, Lalitha Naveen, Renana Peres, Gordon Phillips, Alessio Saretto, Matthew Serfling, Jared Smith, Robert Tumarkin, Philip Valta, Ekaterina Volkova, Jing Wang, Jin Xu, and Ayako Yasuda. For helpful comments, we thank an anonymous referee, Lee Biggerstaff, François Derrien, Brad Goldie, John Graham, Ben Iverson, Jonathan Karpoff, Jared Smith, Serafeim Tsoukas, Ekaterina Volkova, and David Yin. For excellent research assistance, we thank Greg Adams, Troy Carpenter, Spencer Crawford, Paige Nelson, Marshall Ringwood, and Logan Smith.
Filippou et al. supplementary material
![determinants of capital structure literature review Crossref logo](https://assets.crossref.org/logo/crossref-logo-100.png)
No CrossRef data available.
View all Google Scholar citations for this article.
Save article to Kindle
To save this article to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle .
Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Find out more about the Kindle Personal Document Service.
- Volume 58, Issue 6
- Toshinori Fukui (a1) , Todd Mitton (a2) and Robert Schonlau (a3)
- DOI: https://doi.org/10.1017/S0022109022001405
Save article to Dropbox
To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox .
Save article to Google Drive
To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive .
Reply to: Submit a response
- No HTML tags allowed - Web page URLs will display as text only - Lines and paragraphs break automatically - Attachments, images or tables are not permitted
Your details
Your email address will be used in order to notify you when your comment has been reviewed by the moderator and in case the author(s) of the article or the moderator need to contact you directly.
You have entered the maximum number of contributors
Conflicting interests.
Please list any fees and grants from, employment by, consultancy for, shared ownership in or any close relationship with, at any time over the preceding 36 months, any organisation whose interests may be affected by the publication of the response. Please also list any non-financial associations or interests (personal, professional, political, institutional, religious or other) that a reasonable reader would want to know about in relation to the submitted work. This pertains to all the authors of the piece, their spouses or partners.
Browse Econ Literature
- Working papers
- Software components
- Book chapters
- JEL classification
More features
- Subscribe to new research
RePEc Biblio
Author registration.
- Economics Virtual Seminar Calendar NEW!
![determinants of capital structure literature review IDEAS home](https://ideas.repec.org/ideas4.jpg)
Capital structure determinants: a literature review
- Author & abstract
- 4 Citations
- Related works & more
Corrections
- Asheesh Pandey
- Madan Singh
Suggested Citation
Download full text from publisher.
Follow serials, authors, keywords & more
Public profiles for Economics researchers
Various research rankings in Economics
RePEc Genealogy
Who was a student of whom, using RePEc
Curated articles & papers on economics topics
Upload your paper to be listed on RePEc and IDEAS
New papers by email
Subscribe to new additions to RePEc
EconAcademics
Blog aggregator for economics research
Cases of plagiarism in Economics
About RePEc
Initiative for open bibliographies in Economics
News about RePEc
Questions about IDEAS and RePEc
RePEc volunteers
Participating archives
Publishers indexing in RePEc
Privacy statement
Found an error or omission?
Opportunities to help RePEc
Get papers listed
Have your research listed on RePEc
Open a RePEc archive
Have your institution's/publisher's output listed on RePEc
Get RePEc data
Use data assembled by RePEc
- Help & FAQ
Research on capital structure determinants: a review and future directions
Research output : Contribution to journal › Review Article › Research › peer-review
Purpose: The purpose of this paper is to study the status of studies on capital structure determinants in the past 40 years. This paper highlights the major gaps in the literature on determinants of capital structure and also aims to raise specific questions for future research. Design/methodology/approach: The prominence of research is assessed by studying the year of publication and region, level of economic development, firm size, data collection methods, data analysis techniques and theoretical models of capital structure from the selected papers. The review is based on 167 papers published from 1972 to 2013 in various peer-reviewed journals. The relationship of determinants of capital structure is analyzed with the help of meta-analysis. Findings: Major findings show an increase of interest in research on determinants of capital structure of the firms located in emerging markets. However, it is observed that these regions are still under-examined which provides more scope for research both empirical and survey-based studies. Majority of research studies are conducted on large-sized firms by using secondary data and regression-based models for the analysis, whereas studies on small-sized firms are very meager. As majority of the research papers are written only at the organizational level, the impact of leverage on various industries is yet to be examined. The review highlights the major determinants of capital structure and their relationship with leverage. It also reveals the dominance of pecking order theory in explaining capital structure of firms theoretically as well as statistically. Originality/value: The paper covers a considerable period of time (1972-2013). Among very few review papers on capital structure research, to the best of authors’ knowledge; this is the first review to identify what is missing in the literature on the determinants of capital structure while offering recommendations for future studies. It also synthesize the findings of empirical studies on determinants of capital structure statistically.
Original language | English |
---|---|
Pages (from-to) | 106-132 |
Number of pages | 27 |
Journal | |
Volume | 13 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2017 |
- Capital structure
- Literature review
- Meta-analysis
- Pecking order
This output contributes to the following UN Sustainable Development Goals (SDGs)
Access to Document
- 10.1108/IJMF-09-2014-0135
Other files and links
- Link to publication in Scopus
T1 - Research on capital structure determinants
T2 - a review and future directions
AU - Kumar, Satish
AU - Colombage, Sisira
AU - Rao-Melancini, Purnima
N2 - Purpose: The purpose of this paper is to study the status of studies on capital structure determinants in the past 40 years. This paper highlights the major gaps in the literature on determinants of capital structure and also aims to raise specific questions for future research. Design/methodology/approach: The prominence of research is assessed by studying the year of publication and region, level of economic development, firm size, data collection methods, data analysis techniques and theoretical models of capital structure from the selected papers. The review is based on 167 papers published from 1972 to 2013 in various peer-reviewed journals. The relationship of determinants of capital structure is analyzed with the help of meta-analysis. Findings: Major findings show an increase of interest in research on determinants of capital structure of the firms located in emerging markets. However, it is observed that these regions are still under-examined which provides more scope for research both empirical and survey-based studies. Majority of research studies are conducted on large-sized firms by using secondary data and regression-based models for the analysis, whereas studies on small-sized firms are very meager. As majority of the research papers are written only at the organizational level, the impact of leverage on various industries is yet to be examined. The review highlights the major determinants of capital structure and their relationship with leverage. It also reveals the dominance of pecking order theory in explaining capital structure of firms theoretically as well as statistically. Originality/value: The paper covers a considerable period of time (1972-2013). Among very few review papers on capital structure research, to the best of authors’ knowledge; this is the first review to identify what is missing in the literature on the determinants of capital structure while offering recommendations for future studies. It also synthesize the findings of empirical studies on determinants of capital structure statistically.
AB - Purpose: The purpose of this paper is to study the status of studies on capital structure determinants in the past 40 years. This paper highlights the major gaps in the literature on determinants of capital structure and also aims to raise specific questions for future research. Design/methodology/approach: The prominence of research is assessed by studying the year of publication and region, level of economic development, firm size, data collection methods, data analysis techniques and theoretical models of capital structure from the selected papers. The review is based on 167 papers published from 1972 to 2013 in various peer-reviewed journals. The relationship of determinants of capital structure is analyzed with the help of meta-analysis. Findings: Major findings show an increase of interest in research on determinants of capital structure of the firms located in emerging markets. However, it is observed that these regions are still under-examined which provides more scope for research both empirical and survey-based studies. Majority of research studies are conducted on large-sized firms by using secondary data and regression-based models for the analysis, whereas studies on small-sized firms are very meager. As majority of the research papers are written only at the organizational level, the impact of leverage on various industries is yet to be examined. The review highlights the major determinants of capital structure and their relationship with leverage. It also reveals the dominance of pecking order theory in explaining capital structure of firms theoretically as well as statistically. Originality/value: The paper covers a considerable period of time (1972-2013). Among very few review papers on capital structure research, to the best of authors’ knowledge; this is the first review to identify what is missing in the literature on the determinants of capital structure while offering recommendations for future studies. It also synthesize the findings of empirical studies on determinants of capital structure statistically.
KW - Capital structure
KW - Leverage
KW - Literature review
KW - Meta-analysis
KW - Pecking order
UR - http://www.scopus.com/inward/record.url?scp=85015743903&partnerID=8YFLogxK
U2 - 10.1108/IJMF-09-2014-0135
DO - 10.1108/IJMF-09-2014-0135
M3 - Review Article
AN - SCOPUS:85015743903
SN - 1743-9132
JO - International Journal of Managerial Finance
JF - International Journal of Managerial Finance
- DOI: 10.1504/ajaaf.2015.072226
- Corpus ID: 167620775
![](http://academichelp.site/777/templates/cheerup/res/banner1.gif)
Capital structure determinants: a literature review
- Asheesh Pandey , M. Singh
- Published 6 October 2015
9 Citations
Determinants of capital structure: a literature review, a study on analysis of i-reits and their capital structure, measurement matters – a meta-study of the determinants of corporate capital structure, determinants of capital structure in banking sector: a bangladesh perspective, capital structure management by share repurchase for companies in emerging markets, a panel data analysis on the capital structure determinants of construction companies listed in s&p bse 500, determinants of european telecom operators' capital structure, determinants of capital structure in nigerian oil and gas sector, dr. adepoju adeoba asaolu determinants of capital structure in nigerian oil and gas sector, 44 references, determinants of capital structure in india (1990-1998): a dynamic panel data approach, an empirical analysis of capital structure determinants: evidence from the indian corporate sector, determinants of corporate capital structure in nigeria, a study on determinants of capital structure in india, factors affecting capital structure decisions: empirical evidence from selected indian firms, the determinants of corporate capital structure: evidence from japanese manufacturing companies, determinants of capital structure: evidence from banking sector in albania, determinants of capital structure of a-reits and the global financial crisis, determinants of capital structure: comparison of empirical evidence for the use of different estimators, determinants of capital structure: a case study of listed companies of nepal, related papers.
Showing 1 through 3 of 0 Related Papers
Information
- Author Services
Initiatives
You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .
Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.
Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.
Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.
Original Submission Date Received: .
- Active Journals
- Find a Journal
- Proceedings Series
- For Authors
- For Reviewers
- For Editors
- For Librarians
- For Publishers
- For Societies
- For Conference Organizers
- Open Access Policy
- Institutional Open Access Program
- Special Issues Guidelines
- Editorial Process
- Research and Publication Ethics
- Article Processing Charges
- Testimonials
- Preprints.org
- SciProfiles
- Encyclopedia
![Sustainability sustainability-logo](https://pub.mdpi-res.com/img/journals/sustainability-logo.png?8600e93ff98dbf14)
Article Menu
![determinants of capital structure literature review determinants of capital structure literature review](https://www.mdpi.com/bundles/mdpisciprofileslink/img/unknown-user.png)
- Subscribe SciFeed
- Recommended Articles
- Google Scholar
- on Google Scholar
- Table of Contents
Find support for a specific problem in the support section of our website.
Please let us know what you think of our products and services.
Visit our dedicated information section to learn more about MDPI.
JSmol Viewer
Firms’ capital structure during crises: evidence from the united kingdom, 1. introduction, 2. materials and methods, 4. conclusions and discussion, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.
Variables | Definition | Source |
---|---|---|
Dependent variables | ||
Accounting measurements | ||
ROA | Return on asset: measures how a firm efficiently uses its assets and generates gains. =(Net Income − Bottom Line + ((Interest Expense on Debt-Interest Capitalized) × (1 − Tax Rate)))/Average of Last Year’s and Current Year’s Total Assets × 100. | LSEG |
ROE | Return on equity: measures how well a firm makes returns from its equity. =((Net Income − Bottom Line − Preferred Dividend Requirement)/Average of Last Year’s and Current Year’s Common Equity × 100). | LSEG |
Market measurement | ||
LNQ | The natural logarithm of Tobin’s Q. Tobin’s Q is long-term financial performance expectations that stem from shareholder-related financial performance. =LN ((The market value of equity + book value of assets − book value of equity—deferred taxes)/book value of assets). | Authors’ calculation |
Explanatory variables | ||
CSR measurements | ||
ESG | A relative sum of the environmental, social, and governance pillars. | LSEG |
E | The weighted average relative rating of resource use, emission, and innovation related to company reports on their environmental activities. | LSEG |
S | The weighted average relative rating of the workforce, human rights, community, and product responsibility is interrelated to companies’ social commentary. | LSEG |
G | Based on company governance details, the weighted average relative rating of management, shareholders, and CSR strategy is formed. provides more information on each pillar. | LSEG |
Capital structure measurements | ||
SDA | The short-term debt ratio. =(The portion of debt payable within one fiscal year consisting of the current portion of long-term debt and sinking fund obligations of preferred stock or Debentures)/the book value of total assets. | Authors’ calculation |
LDA | The long-term debt ratio is = (all interest-bearing financial obligations, not including amounts demanded within one fiscal year. It is shown net of premium or discount)/the book value of total assets. | Authors’ calculation |
TDA | The total debt ratio represents all interest-bearing and capitalized lease obligations. =(Sum of long and short-term debt)/the book value of total assets. | Authors’ calculation |
Control variables | ||
MB | Growth = market value of the company/total shareholder’s equity | Authors’ calculation |
PPETA | Tangibility represented by fixed assets (Property + plant + and equipment)/the book value of total asset | LSEG |
CR | The current ratio measures firm liquidity. =current assets (Denotes cash and other assets, sold, or estimated to turn to cash, sold or consumed within one fiscal year or one operating cycle)/current liabilities (represents a debt or other requirements that the firm assumes to fulfill within one fiscal year). | LSEG |
LNTA | The natural logarithm of the firm’s total assets and measures the size. | Authors’ calculation |
Beta | Systematic risk (beta) measures a stock’s volatility concerning the overall market volatility. =percent changes of end price between 23 and 35 consecutive months related to the local market index. | LSEG |
COVID-19 | The dummy variable takes the value of one for the period 2020–2021 and zero otherwise. | Authors’ calculation |
Industry dummies | Basic Materials (D1), Consumer Discretionary (D2), Consumer Staples (D3), Energy (D4), Health Care (D5), Industrials (D6), Technology (D7), and Telecommunications (D8). These are based on the London Stock Exchange ICB Industry classifications. Each dummy takes the value of one if it is related to a specific industry and zero otherwise. | Authors’ calculation |
ESG Pillar Subcategories | Score | Definition |
---|---|---|
Environment | Resource use | Reflects a company’s performance and capacity to reduce the use of materials, energy, or water and find more eco-efficient solutions by improving supply chain management. |
Emissions reduction | Measures a company’s commitment to and effectiveness in reducing environmental emissions in its production and operational processes. | |
Innovation | Reflects a company’s capacity to reduce its customers’ environmental costs and burdens, thereby creating new market opportunities through new environmental technologies and processes or eco-designed products. | |
Social | Workforce | Measures a company’s effectiveness in providing job satisfaction and a healthy and safe workplace, maintaining diversity and equal opportunities, and development opportunities for its workforce. |
Human rights | Measures a company’s effectiveness in terms of respecting fundamental human rights conventions. | |
Community | Measures a company’s commitment to being a good citizen, protecting public health, and respecting business ethics. | |
Product responsibility | Reflects a company’s capacity to produce quality goods and services, integrating the customers’ health and safety, integrity, and data privacy. | |
Governance | Management | Measures a company’s commitment to and effectiveness in following best practice corporate governance principles. |
Shareholders | Measures a company’s effectiveness in the equal treatment of shareholders and the use of anti-takeover devices. | |
CSR strategy | Reflects a company’s practices to communicate that it integrates economic (financial), social, and environmental dimensions into its day-to-day decision-making processes. |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
VARIIABLE | SDA | SDA | SDA | LDA | LDA | LDA | TDA | TDA | TDA |
L.SDA | 0.645 *** | 0.642 *** | 0.656 *** | ||||||
(0.00248) | (0.00292) | (0.00213) | |||||||
L.LDA | 0.798 *** | 0.595 *** | 0.790 *** | ||||||
(0.00446) | (0.00544) | (0.00390) | |||||||
L.TDA | 0.719 *** | 0.552 *** | 0.760 *** | ||||||
(0.00440) | (0.00552) | (0.00472) | |||||||
*** | *** | *** | |||||||
) | ) | ) | |||||||
*** | *** | *** | |||||||
) | |||||||||
*** | *** | ||||||||
) | ) | ) | |||||||
*** | *** | ** | *** | *** | *** | *** | ** | *** | |
) | ) | ) | ) | ) | ) | ) | ) | ) | |
*** | ** | *** | *** | *** | * | *** | |||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
Controls | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Sectors | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Constant | YES | YES | YES | YES | YES | YES | YES | YES | YES |
F-Stat | 16,448 | 20,267 | 38,345 | 62,081 | 11,637 | 81,732 | 43,538 | 35,426 | 45,351 |
Prob > F | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
AR (1) | 0.0212 | 0.0322 | 0.0219 | 1.98 × 10 | 6.73 × 10 | 1.82 × 10 | 1.34 × 10 | 1.18 × 10 | 1.47 × 10 |
AR (2) | 0.791 | 0.946 | 0.849 | 0.0127 | 0.407 | 0.0121 | 0.107 | 0.303 | 0.0225 |
Hansen | 0.116 | 0.191 | 0.150 | 0.309 | 0.266 | 0.221 | 0.0494 | 0.125 | 0.102 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
VARIABLES | SDA | SDA | SDA | LDA | LDA | LDA | TDA | TDA | TDA |
L.SDA | 0.645 *** | 0.636 *** | 0.657 *** | ||||||
(0.00251) | (0.00267) | (0.00230) | |||||||
L.LDA | 0.794 *** | 0.597 *** | 0.789 *** | ||||||
(0.00446) | (0.00601) | (0.00462) | |||||||
L.TDA | 0.732 *** | 0.561 *** | 0.763 *** | ||||||
(0.00483) | (0.00540) | (0.00481) | |||||||
*** | ** | *** | |||||||
) | ) | ) | |||||||
*** | *** | *** | |||||||
) | ) | ) | |||||||
*** | *** | *** | |||||||
) | ) | ) | |||||||
*** | *** | *** | *** | *** | *** | ** | *** | ||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
*** | *** | *** | *** | *** | *** | *** | |||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
Controls | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Sectors | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Constant | YES | YES | YES | YES | YES | YES | YES | YES | YES |
F-Stat | 19,646 | 15,370 | 35,077 | 37,527 | 14,064 | 54,491 | 38,850 | 21,925 | 45,269 |
Prob > F | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
AR (1) | 0.0208 | 0.0321 | 0.0223 | 1.90 × 10 | 7.50 × 10 | 1.73 × 10 | 1.25 × 10 | 1.10 × 10 | 1.34 × 10 |
AR (2) | 0.894 | 0.949 | 0.718 | 0.0160 | 0.387 | 0.00984 | 0.0879 | 0.280 | 0.0225 |
Hansen | 0.116 | 0.137 | 0.191 | 0.272 | 0.188 | 0.234 | 0.0685 | 0.117 | 0.0970 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
VARIABLES | SDA | SDA | SDA | LDA | LDA | LDA | TDA | TDA | TDA |
L.SDA | 0.695 *** | 0.736 *** | 0.782 *** | ||||||
(0.00278) | (0.00240) | (0.00348) | |||||||
L.LDA | 0.874 *** | 0.725 *** | 0.903 *** | ||||||
(0.00286) | (0.00451) | (0.00330) | |||||||
L.TDA | 0.872 *** | 0.802 *** | 0.895 *** | ||||||
(0.00444) | (0.00468) | (0.00305) | |||||||
*** | *** | *** | |||||||
) | ) | ) | |||||||
*** | *** | *** | |||||||
) | ) | ) | |||||||
** | |||||||||
) | ) | ) | |||||||
*** | ** | *** | ** | *** | *** | ||||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
*** | *** | *** | *** | *** | *** | *** | *** | ||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
Controls | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Sectors | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Constant | YES | YES | YES | YES | YES | YES | YES | YES | YES |
F-Stat | 27,161 | 23,819 | 120,683 | 279,318 | 164,378 | 388,153 | 121,309 | 114,797 | 215,227 |
Prob > F | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
AR (1) | 7.46 × 10 | 3.84 × 10 | 4.78 × 10 | 1.82 × 10 | 1.10 × 10 | 1.86 × 10 | 1.26 × 10 | 5.38 × 10 | 1.97 × 10 |
AR (2) | 0.357 | 0.405 | 0.265 | 0.113 | 0.691 | 0.0792 | 0.150 | 0.311 | 0.0719 |
Hansen | 0.299 | 0.354 | 0.271 | 0.378 | 0.128 | 0.288 | 0.228 | 0.211 | 0.280 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
VARIABLES | SDA | SDA | SDA | LDA | LDA | LDA | TDA | TDA | TDA |
L.SDA | 0.637 *** | 0.629 *** | 0.669 *** | ||||||
(0.00217) | (0.00258) | (0.00198) | |||||||
L.LDA | 0.794 *** | 0.618 *** | 0.789 *** | ||||||
(0.00367) | (0.00508) | (0.00350) | |||||||
L.TDA | 0.719 *** | 0.586 *** | 0.764 *** | ||||||
(0.00395) | (0.00423) | (0.00396) | |||||||
ROA | −3.82 × 10 *** | −1.13 × 10 *** | −4.43 × 10 *** | ||||||
(2.09 × 10 ) | (2.24 × 10 ) | (3.01 × 10 ) | |||||||
ROE | −2.59 × 10 *** | −4.70 × 10 *** | −1.96 × 10 *** | ||||||
(7.09 × 10 ) | (1.38 × 10 ) | (1.41 × 10 ) | |||||||
LNQ | −3.15 × 10 *** | −1.13 × 10 ** | −3.07 × 10 *** | ||||||
(2.24 × 10 ) | (5.64 × 10 ) | (5.47 × 10 ) | |||||||
E | −4.08 × 10 *** | −1.65 × 10 | 9.86 × 10 *** | −1.97 × 10 *** | 2.13 × 10 | −2.11 × 10 *** | −2.14 × 10 *** | 1.40 × 10 *** | −1.12 × 10 *** |
(9.60 × 10 ) | (1.10 × 10 ) | (9.60 × 10 ) | (2.45 × 10 ) | (2.99 × 10 ) | (2.16 × 10 ) | (3.10 × 10 ) | (4.52 × 10 ) | (2.50 × 10 ) | |
COVID-19 | 0.00410 *** | 0.00663 *** | 0.00342 *** | −0.0124 *** | −0.00506 *** | −0.0142 *** | −0.00657 *** | 0.00161 | −0.00930 ** |
(0.000560) | (0.000587) | (0.000369) | (0.000993) | (0.00140) | (0.00129) | (0.00150) | (0.00145) | (0.00131) | |
*** | *** | *** | *** | *** | *** | ** | |||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
Controls | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Sectors | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Constant | YES | YES | YES | YES | YES | YES | YES | YES | YES |
F-Stat | 20,443 | 27,024 | 42,846 | 75,999 | 25,525 | 92,942 | 56,055 | 56,459 | 62,621 |
Prob > F | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
AR (1) | 0.0214 | 0.0326 | 0.0220 | 1.76 × 10 | 5.11 × 10 | 1.54 × 10 | 1.42 × 10 | 8.98 × 10 | 1.35 × 10 |
AR (2) | 0.859 | 0.826 | 0.966 | 0.0495 | 0.299 | 0.0354 | 0.0952 | 0.199 | 0.0168 |
Hansen | 0.218 | 0.331 | 0.294 | 0.380 | 0.351 | 0.283 | 0.0687 | 0.248 | 0.109 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
VARIABLES | SDA | SDA | SDA | LDA | LDA | LDA | TDA | TDA | TDA |
L.SDA | 0.641 *** | 0.633 *** | 0.663 *** | ||||||
(0.00228) | (0.00270) | (0.00202) | |||||||
L.LDA | 0.795 *** | 0.620 *** | 0.788 *** | ||||||
(0.00399) | (0.00535) | (0.00431) | |||||||
L.TDA | 0.724 *** | 0.589 *** | 0.761 *** | ||||||
(0.00376) | (0.00469) | (0.00413) | |||||||
ROA | −4.61 × 10 *** | −6.02 × 10 ** | −5.59 × 10 *** | ||||||
(2.19 × 10 ) | (2.95 × 10 ) | (3.09 × 10 ) | |||||||
ROE | −2.38 × 10 *** | −8.35 × 10 *** | −2.93 × 10 *** | ||||||
(5.93 × 10 ) | (1.45 × 10 ) | (1.26 × 10 ) | |||||||
LNQ | −3.48 × 10 *** | −1.59 × 10 *** | −3.87 × 10 *** | ||||||
(2.15 × 10 ) | (4.87 × 10 ) | (5.16 × 10 ) | |||||||
S | −4.90 × 10 *** | −1.60 × 10 | 3.32 × 10 *** | −1.45 × 10 *** | 1.38 × 10 | −1.80 × 10 *** | −2.32 × 10 *** | −2.17 × 10 | −1.61 × 10 *** |
(1.06 × 10 ) | (9.94 × 10 ) | (9.40 × 10 ) | (2.44 × 10 ) | (3.05 × 10 ) | (3.26 × 10 ) | (3.47 × 10 ) | (3.59 × 10 ) | (3.14 × 10 ) | |
COVID-19 | 0.000425 | 0.00279 *** | −0.000385 | −0.0111 *** | −0.00543 *** | −0.0132 *** | −0.0119 *** | −0.00269 | −0.0141 *** |
(0.000655) | (0.000623) | (0.000571) | (0.00135) | (0.00140) | (0.00171) | (0.00172) | (0.00170) | (0.00180) | |
** | *** | *** | *** | *** | *** | *** | |||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
Controls | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Sectors | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Constant | YES | YES | YES | YES | YES | YES | YES | YES | YES |
F-Stat | 23,589 | 19,307 | 58,258 | 64,238 | 26,548 | 84,378 | 67,067 | 74,876 | 69,728 |
Prob > F | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
AR (1) | 0.0210 | 0.0323 | 0.0222 | 1.77 × 10 | 5.15 × 10 | 1.64 × 10 | 1.66 × 10 | 6.89 × 10 | 1.36 × 10 |
AR (2) | 0.240 | 0.268 | 0.757 | 0.0272 | 0.202 | 0.0212 | 0.110 | 0.172 | 0.0205 |
Hansen | 0.128 | 0.216 | 0.119 | 0.393 | 0.270 | 0.300 | 0.0463 | 0.112 | 0.0815 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
VARIABLES | SDA | SDA | SDA | LDA | LDA | LDA | TDA | TDA | TDA |
L.SDA | 0.696 *** | 0.734 *** | 0.778 *** | ||||||
(0.00256) | (0.00211) | (0.00265) | |||||||
L.LDA | 0.876 *** | 0.740 *** | 0.904 *** | ||||||
(0.00272) | (0.00380) | (0.00294) | |||||||
L.TDA | 0.869 *** | 0.808 *** | 0.894 *** | ||||||
(0.00357) | (0.00330) | (0.00232) | |||||||
ROA | −2.63 × 10 *** | −1.17 × 10 *** | −2.93 × 10 *** | ||||||
(1.96 × 10 ) | (3.09 × 10 ) | (3.52 × 10 ) | |||||||
ROE | −1.24 × 10 *** | −5.18 × 10 *** | −9.66 × 10 *** | ||||||
(3.23 × 10 ) | (1.11 × 10 ) | (8.00 × 10 ) | |||||||
LNQ | −1.13 × 10 *** | −4.71 × 10 | −5.58 × 10 | ||||||
(2.55 × 10 ) | (5.47 × 10 ) | (5.78 × 10 ) | |||||||
G | −1.56 × 10 ** | 1.24 × 10 * | −4.44 × 10 *** | 5.65 × 10 *** | 1.25 × 10 *** | 1.24 × 10 *** | 1.41 × 10 | 9.83 × 10 *** | 4.33 × 10 *** |
(7.21 × 10 ) | (6.36 × 10 ) | (7.54 × 10 ) | (1.18 × 10 ) | (1.47 × 10 ) | (1.65 × 10 ) | (1.47 × 10 ) | (1.59 × 10 ) | (1.54 × 10 ) | |
COVID-19 | −0.00261 *** | 0.000318 | −0.000765 | −0.00388 *** | 0.00425 *** | −0.00519 *** | −0.00626 *** | 0.00102 | −0.00695 *** |
(0.000589) | (0.000492) | (0.000569) | (0.000868) | (0.000910) | (0.00116) | (0.00139) | (0.00142) | (0.00136) | |
*** | *** | *** | ** | * | *** | ** | |||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
Controls | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Sectors | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Constant | YES | YES | YES | YES | YES | YES | YES | YES | YES |
F-Stat | 41,462 | 32,389 | 132,931 | 404,937 | 250,876 | 535,344 | 174,330 | 194,306 | 516,418 |
Prob > F | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
AR (1) | 7.10 × 10 | 3.65 × 10 | 5.57 × 10 | 1.77 × 10 | 8.83 × 10 | 1.74 × 10 | 1.35 × 10 | 5.33 × 10 | 1.96 × 10 |
AR (2) | 0.377 | 0.142 | 0.209 | 0.0619 | 0.374 | 0.0443 | 0.102 | 0.127 | 0.0471 |
Hansen | 0.249 | 0.360 | 0.246 | 0.455 | 0.221 | 0.547 | 0.236 | 0.269 | 0.195 |
- WHO. A Timeline of WHO’s COVID-19 Response in the WHO European Region: A Living Document (Version 3.0, from 31 December 2019 to 31 December 2021) ; Regional Office for Europe UN City, Marmorvej 51, DK-2100 Copenhagen Ø, Denmark; World Health Organization: Geneva, Switzerland, 2022. [ Google Scholar ]
- Goodell, J.W. COVID-19 and finance: Agendas for future research. Financ. Res. Lett. 2020 , 35 , 101512. [ Google Scholar ] [ CrossRef ] [ PubMed ]
- OECD. Social Economy and the COVID-19 Crisis: Current and Future Roles ; OECD Publishing: Paris, France, 2020; Available online: https://www.oecd-ilibrary.org/social-issues-migration-health/social-economy-and-the-covid-19-crisis-current-and-future-roles_f904b89f-en (accessed on 25 February 2024).
- Tiwari, A.K.; Abakah, E.J.A.; Karikari, N.K.; Gil-Alana, L.A. The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets. N. Am. J. Econ. Financ. 2022 , 62 , 101735. [ Google Scholar ] [ CrossRef ]
- Liu, Y.; Qiu, B.; Wang, T. Debt rollover risk, credit default swap spread and stock returns: Evidence from the COVID-19 crisis. J. Financ. Stab. 2021 , 53 , 100855. [ Google Scholar ] [ CrossRef ]
- Duval, R.; Hong, G.H.; Timmer, Y. Financial frictions and the great productivity slowdown. Rev. Financ. Stud. 2020 , 33 , 475–503. [ Google Scholar ] [ CrossRef ]
- Ebeke MC, H.; Jovanovic, N.; Valderrama, M.L.; Zhou, J. Corporate Liquidity and Solvency in Europe during COVID-19: The Role of Policies ; International Monetary Fund: Washington, DC, USA, 2021. [ Google Scholar ]
- Hotchkiss, E.S.; Nini, G.; Smith, D.C. Corporate Capital Raising during the COVID Crisis ; SSRN Library: Charlottesville, VA, USA, 2020. [ Google Scholar ]
- O’Hara, M.; Zhou, X.A. Anatomy of a liquidity crisis: Corporate bonds in the COVID-19 crisis. J. Financ. Econ. 2021 , 142 , 46–68. [ Google Scholar ] [ CrossRef ] [ PubMed ]
- Kargar, M.; Lester, B.; Lindsay, D.; Liu, S.; Weill, P.O.; Zúñiga, D. Corporate bond liquidity during the COVID-19 crisis. Rev. Financ. Stud. 2021 , 34 , 5352–5401. [ Google Scholar ] [ CrossRef ]
- Duchin, R.; Harford, J. The Covid-19 Crisis and the Allocation of Capital. J. Financ. Quant. Anal. 2021 , 56 , 2309–2319. [ Google Scholar ] [ CrossRef ]
- Ding, W.; Levine, R.; Lin, C.; Xie, W. Corporate immunity to the COVID-19 pandemic. J. Financ. Econ. 2021 , 141 , 802–830. [ Google Scholar ] [ CrossRef ]
- Harjoto, M.A.; Rossi, F.; Lee, R.; Sergi, B.S. How do equity markets react to COVID-19? Evidence from emerging and developed countries. J. Econ. Bus. 2021 , 115 , 105966. [ Google Scholar ] [ CrossRef ]
- Baker, S.R.; Bloom, N.; Davis, S.J.; Kost, K.; Sammon, M.; Viratyosin, T. The unprecedented stock market reaction to COVID-19. Rev. Asset Pricing Stud. 2020 , 10 , 742–758. [ Google Scholar ] [ CrossRef ]
- Bretscher, L.; Hsu, A.; Simasek, P.; Tamoni, A. COVID-19 and the cross-section of equity returns: Impact and transmission. Rev. Asset Pricing Stud. 2020 , 10 , 705–741. [ Google Scholar ] [ CrossRef ]
- Hasan, I.; Marra, M.; To, T.Y.; Wu, E.; Zhang, G. COVID-19 pandemic and global corporate CDS spreads. J. Bank. Financ. 2023 , 147 , 106618. [ Google Scholar ] [ CrossRef ]
- Li, K.; Mai, F.; Shen, R.; Yan, X. Measuring corporate culture using machine learning. Rev. Financ. Stud. 2021 , 34 , 3265–3315. [ Google Scholar ] [ CrossRef ]
- Ramelli, S.; Wagner, A.F. Feverish stock price reactions to COVID-19. Rev. Corp. Financ. Stud. 2020 , 9 , 622–655. [ Google Scholar ] [ CrossRef ]
- Zaremba, A.; Kizys, R.; Aharon, D.Y.; Demir, E. Infected markets: Novel coronavirus, government interventions, and stock return volatility around the globe. Financ. Res. Lett. 2020 , 35 , 101597. [ Google Scholar ] [ CrossRef ] [ PubMed ]
- Li, L.; Strahan, P.E.; Zhang, S. Banks as lenders of first resort: Evidence from the COVID-19 crisis. Rev. Corp. Financ. Stud. 2020 , 9 , 472–500. [ Google Scholar ] [ CrossRef ]
- Acharya, V.V.; Steffen, S. The risk of being a fallen angel and the corporate dash for cash amid COVID-19. Rev. Corp. Financ. Stud. 2020 , 9 , 430–471. [ Google Scholar ] [ CrossRef ]
- Halling, M.; Yu, J.; Zechner, J. How did COVID-19 affect firms’ access to public capital markets? Rev. Corp. Financ. Stud. 2020 , 9 , 501–533. [ Google Scholar ] [ CrossRef ]
- Modigliani, F.; Miller, M.H. The cost of capital, corporation finance and the theory of investment. Am. Econ. Rev. 1958 , 48 , 261–297. [ Google Scholar ]
- Kopecky, K.J.; Li, Z.; Sugrue, T.F.; Tucker, A.L. Revisiting M&M with taxes: An alternative equilibrating process. Int. J. Financ. Stud. 2018 , 6 , 10. [ Google Scholar ] [ CrossRef ]
- Anderson, R.C.; Mansi, S.A.; Reeb, D.M. Founding family ownership and the agency cost of debt. J. Financ. Econ. 2003 , 68 , 263–285. [ Google Scholar ] [ CrossRef ]
- Jensen, M.C. Agency costs of free cash flow, corporate finance, and takeovers. Am. Econ. Rev. 1986 , 76 , 323–329. [ Google Scholar ]
- Lins, K.V.; Servaes, H.; Tamayo, A. Social capital, trust, and firm performance: The value of corporate social responsibility during the financial crisis. J. Financ. 2017 , 72 , 1785–1824. [ Google Scholar ] [ CrossRef ]
- Myers, S.C.; Majluf, N.S. Corporate financing and investment decisions when firms have information that investors do not have. J. Financ. Econ. 1984 , 13 , 187–221. [ Google Scholar ] [ CrossRef ]
- Jensen, M.C.; Meckling, W.H. Theory of the firm: Managerial behavior, agency costs, and ownership structure. J. Financ. Econ. 1976 , 3 , 305–360. [ Google Scholar ] [ CrossRef ]
- Myers, S.C. Determinants of corporate borrowing. J. Financ. Econ. 1977 , 5 , 147–175. [ Google Scholar ] [ CrossRef ]
- Fahlenbrach, R.; Rageth, K.; Stulz, R.M. How valuable is financial flexibility when revenue stops? Evidence from the COVID-19 crisis. Rev. Financ. Stud. 2021 , 34 , 5474–5521. [ Google Scholar ] [ CrossRef ]
- Haddad, V.; Moreira, A.; Muir, T. When selling becomes viral: Disruptions in debt markets in the COVID-19 crisis and the Fed’s response. Rev. Financ. Stud. 2021 , 34 , 5309–5351. [ Google Scholar ] [ CrossRef ]
- Kraus, A.; Litzenberger, R.H. A state-preference model of optimal financial leverage. J. Financ. 1973 , 28 , 911–922. [ Google Scholar ] [ CrossRef ]
- Bae, K.H.; El Ghoul, S.; Guedhami, O.; Kwok, C.C.; Zheng, Y. Does corporate social responsibility reduce the costs of high leverage? Evidence from capital structure and product market interactions. J. Bank. Financ. 2019 , 100 , 135–150. [ Google Scholar ] [ CrossRef ]
- Kapstein, E.B. The corporate ethics crusade. Foreign Aff. 2001 , 80 , 105. [ Google Scholar ] [ CrossRef ]
- Cochran, P.L.; Wood, R.A. Corporate social responsibility and financial performance. Acad. Manag. J. 1984 , 27 , 42–56. [ Google Scholar ] [ CrossRef ]
- Waddock, S.A.; Graves, S.B. The corporate social performance–financial performance link. Strateg. Manag. J. 1997 , 18 , 303–319. [ Google Scholar ] [ CrossRef ]
- Dhaliwal, D.S.; Li, O.Z.; Tsang, A.; Yang, Y.G. Voluntary nonfinancial disclosure and the cost of equity capital: The initiation of corporate social responsibility reporting. Account. Rev. 2011 , 86 , 59–100. [ Google Scholar ] [ CrossRef ]
- Cheng, B.; Ioannou, I.; Serafeim, G. Corporate social responsibility and access to finance. Strateg. Manag. J. 2014 , 35 , 1–23. [ Google Scholar ] [ CrossRef ]
- Vanhamme, J.; Grobben, B. “Too good to be true!” The effectiveness of CSR history in countering negative publicity. J. Bus. Ethics 2009 , 85 , 273–283. [ Google Scholar ] [ CrossRef ]
- Goss, A.; Roberts, G.S. The impact of corporate social responsibility on the cost of bank loans. J. Bank. Financ. 2011 , 35 , 1794–1810. [ Google Scholar ] [ CrossRef ]
- Boubaker, S.; Cellier, A.; Manita, R.; Saeed, A. Does corporate social responsibility reduce financial distress risk? Econ. Model. 2020 , 91 , 835–851. [ Google Scholar ] [ CrossRef ]
- Godfrey, P.C. The relationship between corporate philanthropy and shareholder wealth: A risk management perspective. Acad. Manag. Rev. 2005 , 30 , 777–798. [ Google Scholar ] [ CrossRef ]
- Godfrey, P.C.; Merrill, C.B.; Hansen, J.M. The relationship between corporate social responsibility and shareholder value: An empirical test of the risk management hypothesis. Strateg. Manag. J. 2009 , 30 , 425–445. [ Google Scholar ] [ CrossRef ]
- Peloza, J. Using corporate social responsibility as insurance for financial performance. Calif. Manag. Rev. 2006 , 48 , 52–72. [ Google Scholar ] [ CrossRef ]
- Huang, H.; Ye, Y. Rethinking capital structure decision and corporate social responsibility in response to COVID-19. Account. Financ. 2021 , 61 , 4757–4788. [ Google Scholar ] [ CrossRef ]
- Li, K.; Liu, X.; Mai, F.; Zhang, T. The role of corporate culture in inconvenient times: Evidence from the COVID-19 pandemic. J. Financ. Quant. Anal. 2021 , 56 , 2545–2583. [ Google Scholar ] [ CrossRef ]
- Becchetti, L.; Ciciretti, R.; Hasan, I. Corporate social responsibility, stakeholder risk, and idiosyncratic volatility. J. Corp. Financ. 2015 , 35 , 297–309. [ Google Scholar ] [ CrossRef ]
- Bassen, A.; Meyer, K.; Hölz, H.M.; Zamostny, A.; Schlange, J. The influence of corporate responsibility on the cost of capital. SSRN Electron. J. 2006. [ CrossRef ]
- Benlemlih, M.; Shaukat, A.; Qiu, Y.; Trojanowski, G. Environmental and social disclosures and firm risk. J. Bus. Ethics 2018 , 152 , 613–626. [ Google Scholar ] [ CrossRef ]
- Albuquerque, R.; Koskinen, Y.; Yang, S.; Zhang, C. Resiliency of environmental and social stocks: An analysis of the exogenous COVID-19 market crash. Rev. Corp. Financ. Stud. 2020 , 9 , 593–621. [ Google Scholar ] [ CrossRef ]
- Our World in Data. 2021. Available online: https://ourworldindata.org/covid-cases?country=~GBR (accessed on 5 February 2024).
- Office for National Statistics (ONS). Blue Book 2022—Revised Impacts of the Coronavirus (COVID-19) Pandemic on the UK Economy ; Office for National Statistics (ONS): London, UK, 2022.
- Bank of England. 2021. Available online: https://www.bankofengland.co.uk/financial-policy-summary-and-record/2021/october-2021/financial-stability-in-focus (accessed on 30 January 2024).
- Halling, M.; Yu, J.; Zechner, J. The Dynamics of Corporate Debt Structure ; Swedish House of Finance Research Paper; CEPR Press: London, UK, 2022. [ Google Scholar ]
- Kellard, N.M.; Kontonikas, A.; Lamla, M.; Maiani, S. Deal or no deal? Modelling the impact of Brexit uncertainty on UK private equity activity. Br. J. Manag. 2022 , 33 , 46–68. [ Google Scholar ] [ CrossRef ]
- Arellano, M.; Bover, O. Another look at the instrumental variable estimation of error-components models. J. Econom. 1995 , 68 , 29–51. [ Google Scholar ] [ CrossRef ]
- Blundell, R.; Bond, S. Initial conditions and moment restrictions in dynamic panel data models. J. Econom. 1998 , 87 , 115–143. [ Google Scholar ] [ CrossRef ]
- Roodman, D. How to do xtabond2: An introduction to difference and system GMM in Stata. Stata J. 2009 , 9 , 86–136. [ Google Scholar ] [ CrossRef ]
- Wintoki, M.B.; Linck, J.S.; Netter, J.M. Endogeneity and the dynamics of internal corporate governance. J. Financ. Econ. 2012 , 105 , 581–606. [ Google Scholar ] [ CrossRef ]
- Gujarati, D.N.; Porter, D.C. (Eds.) Basic Econometrics ; McGrew Hill Book Co.: Singapore, 2003. [ Google Scholar ]
- Ghosh, D.; Olsen, L. Environmental uncertainty and managers’ use of discretionary accruals. Account. Organ. Soc. 2009 , 34 , 188–205. [ Google Scholar ] [ CrossRef ]
- Huang, Z.; Gao, W.; Chen, L. Does the external environment matter for the persistence of firms’ debt policy? Financ. Res. Lett. 2020 , 32 , 101073. [ Google Scholar ] [ CrossRef ]
- Wu, X.; Yeung, C.K.A. Firm growth type and capital structure persistence. J. Bank. Financ. 2012 , 36 , 3427–3443. [ Google Scholar ] [ CrossRef ]
- Demirgüç-Kunt, A.; Peria, M.S.M.; Tressel, T. The global financial crisis and the capital structure of firms: Was the impact more severe among SMEs and non-listed firms? J. Corp. Financ. 2020 , 60 , 101514. [ Google Scholar ] [ CrossRef ]
- Rajan, R.G.; Zingales, L. What do we know about capital structure? Some evidence from international data. J. Financ. 1995 , 50 , 1421–1460. [ Google Scholar ] [ CrossRef ]
- Broadstock, D.C.; Chan, K.; Cheng, L.T.; Wang, X. The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China. Financ. Res. Lett. 2021 , 38 , 101716. [ Google Scholar ] [ CrossRef ] [ PubMed ]
- Cornett, M.M.; Erhemjamts, O.; Tehranian, H. Greed or good deeds: An examination of the relation between corporate social responsibility and the financial performance of US commercial banks around the financial crisis. J. Bank. Financ. 2016 , 70 , 137–159. [ Google Scholar ] [ CrossRef ]
- Qiu, Y.; Shaukat, A.; Tharyan, R. Environmental and social disclosures: Link with corporate financial performance. Br. Account. Rev. 2016 , 48 , 102–116. [ Google Scholar ] [ CrossRef ]
- Ho, L.; Bai, M.; Lu, Y.; Qin, Y. The effect of corporate sustainability performance on leverage adjustments. Br. Account. Rev. 2021 , 53 , 100989. [ Google Scholar ] [ CrossRef ]
- Pagano, M.; Wagner, C.; Zechner, J. Disaster resilience and asset prices. J. Financ. Econ. 2023 , 150 , 103712. [ Google Scholar ] [ CrossRef ]
- Pagano, M.; Zechner, J. COVID-19 and corporate finance. Rev. Corp. Financ. Stud. 2022 , 11 , 849–879. [ Google Scholar ] [ CrossRef ]
Min | Mean | Max | Skewness | Kurtosis | Std. Dev. | p25 | Median | p75 | |
---|---|---|---|---|---|---|---|---|---|
SDA | 0 | 0.0618 | 0.722 | 3.5 | 17.3 | 0.115 | 0.0024 | 0.0195 | 0.0628 |
LDA | 0 | 0.155 | 1.06 | 1.94 | 8.08 | 0.191 | 0.00356 | 0.0858 | 0.251 |
TDA | 0 | 0.228 | 2.11 | 3.44 | 20.6 | 0.292 | 0.0251 | 0.165 | 0.321 |
ROA | −198 | −6.53 | 43.8 | −3.67 | 19.8 | 32.2 | −9.17 | 2.13 | 6.95 |
ROE | −365 | −11.6 | 107 | −3.38 | 18.2 | 61.2 | −17.3 | 2.47 | 13.2 |
LNQ | −0.0691 | 4.45 | 7.45 | −0.796 | 5.15 | 1.26 | 3.83 | 4.52 | 5.18 |
ESG | 2.3 | 44 | 89.5 | −0.0839 | 2.37 | 21.7 | 29.4 | 44.8 | 58.8 |
E | 1.19 | 40.2 | 91.9 | 0.26 | 2.05 | 25.3 | 18.7 | 38.2 | 58.8 |
S | 3.2 | 45 | 93.9 | 0.0905 | 2.1 | 25 | 27.4 | 43.9 | 63.3 |
G | 3.8 | 50.4 | 95.6 | −0.263 | 1.97 | 26.1 | 29.6 | 53.8 | 71.7 |
MB | −829 | 15.9 | 55,943 | 74 | 5,516 | 751 | 0.82 | 1.7 | 3.47 |
PPETA | 0 | 0.25 | 0.952 | 1.1 | 3.42 | 0.245 | 0.046 | 0.178 | 0.384 |
CR | 0 | 2.92 | 36.3 | 4.76 | 28.8 | 4.98 | 0.95 | 1.56 | 2.76 |
LNTA | 5.73 | 11.7 | 17.7 | 0.124 | 2.59 | 2.6 | 9.76 | 11.6 | 13.3 |
Beta | −1.44 | 0.616 | 2.76 | 0.11 | 4.23 | 0.688 | 0.22 | 0.6 | 1 |
COVID-19 | 0 | 0.504 | 1 | −0.0146 | 1 | 0.5 | 0 | 1 | 1 |
Variables | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | (13) | (14) | (15) | (16) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
(1) SDA | 1.000 | |||||||||||||||
(2) LDA | 0.133 *** | 1.000 | ||||||||||||||
(3) TDA | 0.602 *** | 0.797 *** | 1.000 | |||||||||||||
(4) ROA | −0.067 *** | −0.024 * | −0.115 *** | 1.000 | ||||||||||||
(5) ROE | −0.146 *** | 0.015 | −0.038 *** | 0.766 *** | 1.000 | |||||||||||
(6) LNQ | −0.149 *** | −0.100 *** | −0.059 *** | −0.205 *** | −0.039 *** | 1.000 | ||||||||||
(7) ESG | −0.048 ** | 0.109 *** | 0.077 *** | 0.079 *** | 0.143 *** | −0.027 | 1.000 | |||||||||
(8) E | −0.044 ** | 0.155 *** | 0.120 *** | 0.089 *** | 0.158 *** | −0.030 | 0.559 *** | 1.000 | ||||||||
(9) S | −0.037 * | 0.146 *** | 0.111 *** | 0.029 | 0.058 *** | −0.086 *** | 0.566 *** | 0.519 *** | 1.000 | |||||||
(10) G | −0.015 | 0.041 ** | 0.028 | 0.041 ** | 0.100 *** | −0.059 *** | 0.387 *** | 0.324 *** | 0.334 *** | 1.000 | ||||||
(11) MB | −0.006 | −0.012 | −0.011 | −0.009 | −0.007 | 0.035 ** | 0.014 | −0.051 ** | −0.081 *** | 0.029 | 1.000 | |||||
(12) PPETA | 0.125 *** | 0.199 *** | 0.164 *** | 0.121 *** | 0.058 *** | −0.226 *** | −0.071 *** | −0.051 ** | 0.013 | 0.015 | −0.017 | 1.000 | ||||
(13) CR | −0.201 *** | −0.162 *** | −0.203 *** | −0.017 | 0.006 | 0.070 *** | −0.115 *** | −0.113 *** | −0.080 *** | −0.080 *** | 0.001 | −0.160 *** | 1.000 | |||
(14) LNTA | −0.143 *** | 0.216 *** | 0.024 * | 0.483 *** | 0.394 *** | −0.288 *** | 0.473 *** | 0.608 *** | 0.529 *** | 0.374 *** | −0.023 * | 0.168 *** | −0.186 *** | 1.000 | ||
(15) Beta | −0.078 *** | 0.098 *** | 0.005 | 0.026 * | −0.043 *** | −0.010 | 0.160 *** | 0.191 *** | 0.221 *** | 0.173 *** | 0.021 | −0.011 | 0.032 ** | 0.231 *** | 1.000 | |
(16) COVID-19 | −0.007 | 0.029 ** | 0.022 * | 0.032 ** | 0.022 * | −0.012 | −0.030 | −0.028 | −0.063 *** | 0.017 | 0.013 | 0.035 *** | 0.063 *** | 0.031 ** | 0.169 *** | 1.000 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
VARIABLES | SDA | SDA | SDA | LDA | LDA | LDA | TDA | TDA | TDA |
L.SDA | 0.710 *** | 0.729 *** | 0.727 *** | ||||||
(0.00306) | (0.00296) | (0.00299) | |||||||
L.LDA | 0.850 *** | 0.683 *** | 0.839 *** | ||||||
(0.00349) | (0.00617) | (0.00382) | |||||||
L.TDA | 0.800 *** | 0.663 *** | 0.833 *** | ||||||
(0.00563) | (0.00771) | (0.00501) | |||||||
*** | *** | *** | |||||||
) | ) | ) | |||||||
*** | *** | *** | |||||||
) | ) | ) | |||||||
*** | * | ||||||||
) | ) | ) | |||||||
*** | *** | *** | *** | *** | *** | *** | |||
) | ) | ) | ) | ) | ) | ) | ) | ) | |
) | ) | ) | ) | ) | ) | ) | ) | ) | |
MB | 1.80 × 10 *** | 4.06 × 10 *** | 6.46 × 10 *** | 3.46 × 10 ** | 6.31 × 10 *** | −8.47 × 10 | 1.58 × 10 *** | 0.000105 *** | −4.04 × 10 *** |
(8.85 × 10 ) | (5.11 × 10 ) | (7.72 × 10 ) | (1.58 × 10 ) | (2.74 × 10 ) | (1.36 × 10 ) | (2.37 × 10 ) | (6.83 × 10 ) | (1.24 × 10 ) | |
PPETA | 0.0670 *** | 0.0549 *** | 0.0503 *** | 0.0706 *** | 0.210 *** | 0.0809 *** | 0.164 *** | 0.288 *** | 0.132 *** |
(0.00351) | (0.00323) | (0.00324) | (0.00604) | (0.00979) | (0.00580) | (0.00976) | (0.0133) | (0.00776) | |
CR | −0.000386 *** | −0.000386 ** | −0.000398 ** | 0.00192 *** | 0.00366 *** | 0.000922 *** | 0.00325 *** | 0.00329 *** | 0.00143 *** |
(0.000147) | (0.000154) | (0.000166) | (0.000281) | (0.000422) | (0.000318) | (0.000365) | (0.000405) | (0.000300) | |
LNTA | 0.000437 | 0.000797* | −0.00319 *** | 0.00553 *** | 0.00946 *** | 0.00579 *** | 0.00864 *** | 0.0120 *** | 0.00281 *** |
(0.000462) | (0.000425) | (0.000414) | (0.000693) | (0.00138) | (0.000669) | (0.00123) | (0.00153) | (0.00103) | |
Beta | −0.000611 | −0.000201 | −0.000854 ** | −0.00209 ** | −0.00918 *** | −0.00400 *** | −0.00805 *** | −0.00969 *** | −0.00775 *** |
(0.000425) | (0.000363) | (0.000339) | (0.000992) | (0.00119) | (0.000896) | (0.00108) | (0.00137) | (0.00104) | |
D1 Basic Materials | −0.0194 *** | −0.0159 *** | −0.0186 *** | −0.0384 *** | −0.0910 *** | −0.0470 *** | −0.0733 *** | −0.114 *** | −0.0643 *** |
(0.00161) | (0.00152) | (0.00202) | (0.00284) | (0.00583) | (0.00348) | (0.00484) | (0.00748) | (0.00458) | |
D2 Consumer Discr. | |||||||||
D3 Consumer Staples | −0.0124 *** | −0.00987 *** | −0.00810 *** | −0.0158 *** | −0.0317 *** | −0.0196 *** | −0.0330 *** | −0.0513 *** | −0.0267 *** |
(0.00166) | (0.00150) | (0.00168) | (0.00291) | (0.00578) | (0.00297) | (0.00417) | (0.00685) | (0.00366) | |
D4 Energy | −0.00867 *** | −0.00625 *** | −0.00631 *** | −0.0218 *** | −0.0196 ** | −0.0147 ** | −0.0439 *** | −0.0467 *** | −0.0259 *** |
(0.00209) | (0.00183) | (0.00148) | (0.00483) | (0.00866) | (0.00690) | (0.00812) | (0.0133) | (0.00901) | |
D5 Health Care | −0.00852 * | −0.00931 ** | −0.00922 ** | −0.0101 ** | −0.00461 | −0.0114 *** | −0.0213 *** | −0.0254 ** | −0.0177 ** |
(0.00464) | (0.00407) | (0.00408) | (0.00422) | (0.00846) | (0.00395) | (0.00668) | (0.0108) | (0.00729) | |
D6 Industrials | −0.00473 *** | −0.00496 *** | −0.00303 *** | −0.0169 *** | −0.0279 *** | −0.0179 *** | −0.0258 *** | −0.0386 *** | −0.0208 *** |
(0.000752) | (0.000696) | (0.000781) | (0.00126) | (0.00200) | (0.00114) | (0.00321) | (0.00385) | (0.00255) | |
D7 Technology | −0.0114 *** | −0.00916 *** | −0.0146 *** | −0.0144 *** | −0.0210 ** | −0.0136 *** | −0.0278 *** | −0.0430 *** | −0.0288 *** |
(0.00272) | (0.00236) | (0.00260) | (0.00371) | (0.0103) | (0.00418) | (0.00691) | (0.0127) | (0.00663) | |
D8 Telecom | 0.00982 ** | 0.00716 *** | 0.0103 *** | −0.00948 ** | −0.00230 | −0.0121 ** | −0.00701 | −0.00715 | 0.00241 |
(0.00381) | (0.00264) | (0.00378) | (0.00444) | (0.00756) | (0.00515) | (0.00545) | (0.00764) | (0.00532) | |
Constant | 0.00152 | −0.00270 | 0.0716 *** | −0.0473 *** | −0.0952 *** | −0.0429 *** | −0.0781 *** | −0.115 *** | 0.00994 |
(0.00600) | (0.00580) | (0.00540) | (0.00851) | (0.0186) | (0.00848) | (0.0168) | (0.0210) | (0.0133) | |
F-Stat | 18,095 | 21,854 | 33,139 | 62,461 | 21,926 | 41,513 | 21,566 | 23,826 | 26,951 |
Prob > F | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
AR (1) | 4.60 × 10 | 2.72 × 10 | 4.99 × 10 | 1.97 × 10 | 1.19 × 10 | 1.94 × 10 | 1.71 × 10 | 2.07 × 10 | 1.73 × 10 |
AR (2) | 0.463 | 0.493 | 0.365 | 0.0223 | 0.271 | 0.0210 | 0.0380 | 0.193 | 0.0194 |
Hansen | 0.438 | 0.377 | 0.0852 | 0.416 | 0.110 | 0.153 | 0.105 | 0.249 | 0.0839 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
VARIABLES | SDA | SDA | SDA | LDA | LDA | LDA | TDA | TDA | TDA |
L.SDA | 0.701 *** | 0.719 *** | 0.747 *** | ||||||
(0.00270) | (0.00277) | (0.00284) | |||||||
L.LDA | 0.848 *** | 0.703 *** | 0.838 *** | ||||||
(0.00409) | (0.00565) | (0.00399) | |||||||
L.TDA | 0.804 *** | 0.696 *** | 0.837 *** | ||||||
(0.00507) | (0.00669) | (0.00439) | |||||||
ROA | −2.93 × 10 *** | −2.93 × 10 *** | −5.16 × 10 *** | ||||||
(2.35 × 10 ) | (2.99 × 10 ) | (4.94 × 10 ) | |||||||
ROE | 1.68 × 10 *** | −1.34 × 10 *** | −2.68 × 10 *** | ||||||
(4.30 × 10 ) | (1.14 × 10 ) | (1.01 × 10 ) | |||||||
LNQ | −2.93 × 10 *** | −1.20 × 10 ** | −2.50 × 10 *** | ||||||
(2.47 × 10 ) | (5.28 × 10 ) | (6.37 × 10 ) | |||||||
ESG | −3.84 × 10 *** | 1.82 × 10 | 3.83 × 10 *** | −7.01 × 10 *** | −1.65 × 10 | −0.000113 *** | −9.43 × 10 *** | 1.09 × 10 | −8.54 × 10 *** |
(1.23 × 10 ) | (1.10 × 10 ) | (8.33 × 10 ) | (2.58 × 10 ) | (2.68 × 10 ) | (2.45 × 10 ) | (2.69 × 10 ) | (2.81 × 10 ) | (2.56 × 10 ) | |
COVID-19 | 0.00243 *** | 0.00348 *** | 0.00275 *** | −0.0158 *** | −0.00822 *** | −0.0203 *** | −0.0139 *** | −0.000469 | −0.0199 *** |
(0.000676) | (0.000575) | (0.000541) | (0.00163) | (0.00126) | (0.00156) | (0.00186) | (0.00166) | (0.00164) | |
*** | *** | *** | *** | ** | *** | ** | *** | *** | |
) | ) | ) | ) | ) | ) | ) | ) | ) | |
MB | 2.11 × 10 *** | 4.60 × 10 | 6.55 × 10 *** | −5.77 × 10 *** | 5.24 × 10 *** | −8.56 × 10 *** | 6.73 × 10 *** | 9.36 × 10 *** | −1.24 × 10 *** |
(7.88 × 10 ) | (4.52 × 10 ) | (6.56 × 10 ) | (1.46 × 10 ) | (2.62 × 10 ) | (1.16 × 10 ) | (1.42 × 10 ) | (5.29 × 10 ) | (1.01 × 10 ) | |
PPETA | 0.0617 *** | 0.0547 *** | 0.0439 *** | 0.0794 *** | 0.182 *** | 0.0906 *** | 0.161 *** | 0.242 *** | 0.128 *** |
(0.00269) | (0.00255) | (0.00202) | (0.00597) | (0.00827) | (0.00565) | (0.00774) | (0.0109) | (0.00624) | |
CR | −0.000663 *** | −0.000608 *** | −0.000614 *** | 0.00239 *** | 0.00308 *** | 0.00133 *** | 0.00326 *** | 0.00273 *** | 0.00141 *** |
(0.000129) | (0.000147) | (0.000163) | (0.000273) | (0.000315) | (0.000299) | (0.000306) | (0.000321) | (0.000268) | |
LNTA | 0.00130 *** | 0.00114 *** | −0.000789 *** | 0.00394 *** | 0.0109 *** | 0.00370 *** | 0.00768 *** | 0.0130 *** | 0.00301 *** |
(0.000352) | (0.000333) | (0.000294) | (0.000661) | (0.00104) | (0.000639) | (0.00101) | (0.00110) | (0.000798) | |
Beta | −0.000550 | −0.000576 | −0.000614 * | −0.00214 ** | −0.00755 *** | −0.00298 *** | −0.00825 *** | −0.00867 *** | −0.00751 *** |
(0.000457) | (0.000393) | (0.000348) | (0.000947) | (0.00108) | (0.000897) | (0.000963) | (0.00110) | (0.000895) | |
D1 Basic Materials | −0.0180 *** | −0.0155 *** | −0.0156 *** | −0.0423 *** | −0.0828 *** | −0.0500 *** | −0.0746 *** | −0.103 *** | −0.0625 *** |
(0.00143) | (0.00135) | (0.00133) | (0.00271) | (0.00456) | (0.00309) | (0.00423) | (0.00571) | (0.00415) | |
D2 Consumer Discr. | |||||||||
D3 Consumer Staples | −0.0119 *** | −0.0106 *** | −0.0101 *** | −0.0148 *** | −0.0308 *** | −0.0192 *** | −0.0325 *** | −0.0468 *** | −0.0259 *** |
(0.00139) | (0.00122) | (0.00132) | (0.00327) | (0.00475) | (0.00310) | (0.00391) | (0.00564) | (0.00332) | |
D4 Energy | −0.00749 *** | −0.00684 *** | −0.00234 | −0.0239 *** | −0.0245 *** | −0.0151 ** | −0.0468 *** | −0.0433 *** | −0.0259 *** |
(0.00191) | (0.00170) | (0.00162) | (0.00485) | (0.00697) | (0.00621) | (0.00719) | (0.0112) | (0.00695) | |
D5 Health Care | −0.00842 ** | −0.00933 ** | −0.00641 ** | −0.00896 ** | −0.00756 | −0.0115 *** | −0.0224 *** | −0.0236 *** | −0.0201 *** |
(0.00393) | (0.00372) | (0.00276) | (0.00431) | (0.00575) | (0.00397) | (0.00640) | (0.00796) | (0.00596) | |
D6 Industrials | −0.00495 *** | −0.00519 *** | −0.00314 *** | −0.0152 *** | −0.0267 *** | −0.0178 *** | −0.0252 *** | −0.0349 *** | −0.0215 *** |
(0.000654) | (0.000657) | (0.000593) | (0.00114) | (0.00173) | (0.00125) | (0.00302) | (0.00302) | (0.00204) | |
D7 Technology | −0.00996 *** | −0.00862 *** | −0.00802 *** | −0.0149 *** | −0.0198 ** | −0.0172 *** | −0.0313 *** | −0.0311 *** | −0.0250 *** |
(0.00243) | (0.00215) | (0.00177) | (0.00373) | (0.00801) | (0.00373) | (0.00637) | (0.00998) | (0.00560) | |
D8 Telecom | 0.00782 ** | 0.00579 ** | 0.000564 | −0.00997 ** | −0.0100 | −0.00892 * | −0.00679 | −0.0126* | 0.00239 |
(0.00319) | (0.00225) | (0.00321) | (0.00446) | (0.00697) | (0.00512) | (0.00504) | (0.00653) | (0.00537) | |
Constant | −0.0100 ** | −0.00915 ** | 0.0280 *** | −0.0259 *** | −0.115 *** | −0.0116 | −0.0646 *** | −0.135 *** | 0.00841 |
(0.00450) | (0.00429) | (0.00386) | (0.00864) | (0.0139) | (0.00891) | (0.0137) | (0.0152) | (0.0104) | |
F-Stat | 25,640 | 22,360 | 43,476 | 79,857 | 52,245 | 59,174 | 19,213 | 53,581 | 29,484 |
Prob > F | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
AR (1) | 5.22 × 10 | 3.00 × 10 | 5.16 × 10 | 1.85 × 10 | 1.02 × 10 | 1.79 × 10 | 1.64 × 10 | 1.51 × 10 | 1.67 × 10 |
AR (2) | 0.224 | 0.148 | 0.380 | 0.0564 | 0.234 | 0.0657 | 0.0493 | 0.0757 | 0.0281 |
Hansen | 0.388 | 0.432 | 0.319 | 0.427 | 0.138 | 0.229 | 0.181 | 0.320 | 0.164 |
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
Share and Cite
Alhajjeah, D.; Besim, M. Firms’ Capital Structure during Crises: Evidence from the United Kingdom. Sustainability 2024 , 16 , 5469. https://doi.org/10.3390/su16135469
Alhajjeah D, Besim M. Firms’ Capital Structure during Crises: Evidence from the United Kingdom. Sustainability . 2024; 16(13):5469. https://doi.org/10.3390/su16135469
Alhajjeah, Diana, and Mustafa Besim. 2024. "Firms’ Capital Structure during Crises: Evidence from the United Kingdom" Sustainability 16, no. 13: 5469. https://doi.org/10.3390/su16135469
Article Metrics
Article access statistics, further information, mdpi initiatives, follow mdpi.
![MDPI Open Access Journals MDPI](https://pub.mdpi-res.com/img/design/mdpi-pub-logo-white-small.png?71d18e5f805839ab?1719563568)
Subscribe to receive issue release notifications and newsletters from MDPI journals
Review on the effects of biochar amendment on soil microorganisms and enzyme activity
- Soils, Sec 1 • Soil Organic Matter Dynamics and Nutrient Cycling • Research Article
- Published: 21 June 2024
Cite this article
- Xinxin Jin 1 , 2 , 3 na1 ,
- Tongxin Zhang 2 na1 ,
- Yuetong Hou 2 ,
- Roland Bol 3 ,
- Xiaojie Zhang 2 ,
- Min Zhang 4 ,
- Jun Meng 1 ,
- Hongtao Zou ORCID: orcid.org/0000-0001-6772-5338 2 &
- Jingkuan Wang 2
73 Accesses
Explore all metrics
The multiple benefits of biochar use as a soil amendment has garnered global attention. Biochar addition is a crucial factor to improve soil biomass, soil enzyme activities, microbial biomass and improve soil nutrient utilization rate. However, the precise mechanism of effects of biochar addition on microbial community structure and diversity, as well as enzyme activity, remains unclear, especially for biochar obtained from different pyrolysis temperatures and variable quantities in which it is applied to soil.
Materials and methods
We compiled and summarized the existing literature on the impacts of biochar on microorganisms and enzymes, with a specific on articles published over a five-year period (2018–2022). This review provides a comprehensive review of the relevant literature on enzyme activity, microbial diversity, community structure and abundance following biochar amendment in soil, and further elucidates the underlying mechanisms of biochar-induced effects on various factors.
Results and discussion
The impact of biochar on soil microorganisms could be categorized into three aspects: (1) biochar, due to its porous structure and high surface area, functions as a sanctuary for soil microorganisms; (2) biochar provides essential elements such as carbon (C) and nitrogen (N) sources to soil microorganisms, and finally (3) biochar improves the survival conditions of soil microorganisms by modifying soil pH, CEC, aggregation, and enzyme activity. Importantly, biochar produced at lower pyrolysis temperatures provides valuable C and N for soil microorganisms. Whereas biochar obtained at higher pyrolysis temperatures contains much less active C and N. However, it still contributes to microbial nutrition through diverse mechanisms, e.g., nutrient immobilization and increased nutrients residence time through its bonding with soil labile C.
Conclusions
This review found that the type of source material and pyrolysis temperature were the primary determinants in the impacts of biochar on soil microbial abundance, community structure, and diversity.
This is a preview of subscription content, log in via an institution to check access.
Access this article
Price includes VAT (Russian Federation)
Instant access to the full article PDF.
Rent this article via DeepDyve
Institutional subscriptions
![determinants of capital structure literature review](https://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11368-024-03841-7/MediaObjects/11368_2024_3841_Fig1_HTML.png)
Similar content being viewed by others
![determinants of capital structure literature review determinants of capital structure literature review](https://media.springernature.com/w215h120/springer-static/image/art%3A10.1007%2Fs11157-020-09523-3/MediaObjects/11157_2020_9523_Fig1_HTML.png)
Biochar physicochemical properties: pyrolysis temperature and feedstock kind effects
![determinants of capital structure literature review determinants of capital structure literature review](https://media.springernature.com/w215h120/springer-static/image/art%3A10.1007%2Fs42773-023-00296-w/MediaObjects/42773_2023_296_Figa_HTML.png)
Biochar and organic fertilizer applications enhance soil functional microbial abundance and agroecosystem multifunctionality
![determinants of capital structure literature review determinants of capital structure literature review](https://media.springernature.com/w215h120/springer-static/image/art%3A10.1007%2Fs42773-024-00346-x/MediaObjects/42773_2024_346_Figa_HTML.png)
High-efficiency remediation of Hg and Cd co-contaminated paddy soils by Fe–Mn oxide modified biochar and its microbial community responses
Abbas T, Rizwan M, Ali S, Adrees M, Mahmood A, Zia-urRehman M, Ibrahim M, Arshad M, Qayyum MF (2018) Biochar application increased the growth and yield and reduced cadmium in drought stressed wheat grown in an aged contaminated soil. Ecotox Environ Safe 148:825–833
Article CAS Google Scholar
Abou Jaoude L, Castaldi P, Nassif N, Pinna MV, Garau G (2020) Biochar and compost as gentle remediation options for the recovery of trace elementscontaminated soils. Sci Total Environ 711:134511
Abujabhah IS, Doyle R, Bound SA, Bowman JP (2016) The effect of biochar loading rates on soil fertility, soil biomass, potential nitrification, and soil community metabolic profiles in three different soils. J Soils Sediments 16:2211–2222
Allison VJ, Condron LM, Peltzer DA, Richardson SJ, Turner BL (2007) Changes in enzyme activities and soil microbial community composition along carbon and nutrient gradients at the Franz Josef chronosequence. New Zealand Soil Biol Biochem 39(7):1770–1781
Allison SD, Weintraub MN, Gartner TB, Waldrop MP (2011) Evolutionary Evolutionary economic principles as regulators of soil enzyme production and ecosystem function. Soil Enzymology 229–243
Ameloot N, De Neve S, Jegajeevagan K, Yildiz G, Buchan D, Funkuin YN, Prins W, Bouckaert L, Sleutel S (2013a) Short-term CO 2 and N 2 O emissions and microbial properties of biochar amended sandy loam soils. Soil Biol Biochem 57:401–410
Ameloot N, Graber ER, Verheijen FGA, Neve SD (2013b) Interactions between biochar stability and soil organisms: review and research needs. Eur J Soil Sci 64:379–390
Anderson CR, Condron LM, Clough TJ, Fiers M, Stewart A, Hill RA, Sherlock RR (2011) Biochar induced soil microbial community change: Implications for biogeochemical cycling of carbon, nitrogen and phosphorus. Pedobiologia 54:309–320
Atkinson CJ, Fitzgerald JD, Hipps NA (2010) Potential mechanisms for achieving agricultural benefits from biochar application to temperate soils: a review. Plant Soil 337(1):1–18
Awad YM, Evgenia BA, Ok YS, Kuzyakov Y (2012) Effects of polyacrylamide, biopolymer, and biochar on decomposition of soil organic matter and plant residues as determined by C-14 and enzyme activities. Eur J Soil Biol 48:1–10
Awad YM, Lee SS, Kim KH, Ok YS, Kuzyakov Y (2018) Carbon and nitrogen mineralization and enzyme activities in soil aggregate-size classes: Effects of biochar, oyster shells, and polymers. Chemosphere 198:40–48
Bailey VL, Fansler SJ, Smith JL, Bolton H (2011) Reconciling apparent variability in effects of biochar amendment on soil enzyme activities by assay optimization. Soil Biol Biochem 43:296–301
Bhaduri D, Saha A, Desai D, Meena HN (2016) Restoration of carbon and microbial activity in salt-induced soil by application of peanut shell biochar during short-term incubation study. Chemosphere 148:86–98
Caldwell BA (2005) Enzyme activities as a component of soil biodiversity: a review. Pedobiologia. 49(6):637–644
Cao T, Fang Y, Chen Y, Kong X, Yang J, Alharbi H, Kuzyakov Y, Tian X (2022) Synergy of saprotrophs with mycorrhiza for litter decomposition and hotspot formation depends on nutrient availability in the rhizosphere. Geoderma 410:115662
Cao Q, Wang C, Tang D, Zhang X, Wu P, Zhang Y, Liu H, Zheng Z (2023) Enhanced elemental mercury removal in coal-fired flue gas by modified algal waste-derived biochar: Performance and mechanism. J Environ Manage 325:116427
Chen W, Meng J, Han X, Lan Y, Zhang W (2019a) Past, present, and future of biochar. Biochar 1:75–87
Article Google Scholar
Chen Y, Chen J, Luo Y (2019b) Data-driven Enzyme (Denzy) model represents soil organic carbon dynamics in forests impacted by nitrogen deposition. Soil Biol Biochem 138:107575
Cheng C, Lehmann J, Thies JE, Burton SD (2008) Stability of black carbon in soils across a climatic gradient. J Geophys Research-Biogeo 113
Chimento C, Almagro M, Amaducci S (2016) Carbon sequestration potential in perennial bioenergy crops: the importance of organic matter inputs and its physical protection. Global Change Biol Bioenergy 8:111–121
Cooper J, Greenberg I, Ludwig B, Hippich L, Fischer D, Glaser B, Kaiser M (2020) Effect of biochar and compost on soil properties and organic matter in aggregate size fractions under field conditions. Agric Ecosyst Environ 295:106882
Cotrufo MF, Wallenstein MD, Boot CM, Denef P (2013) The microbial efficiency-matrix stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter? Glob Chang Biol 19(4):988–995
Crombie K, Masek O, Sohi SP, Brownsort P, Cross A (2013) The effect of pyrolysis conditions on biochar stability as determined by three methods. Glob Chang Biol Bioenergy 5:122–131
Deluca TH, Mackenzie MD, Gundale MJ, Holben WE (2006) Wildfire-produced charcoal directly influences nitrogen cy-cling in ponderosa pine forests. Soil Sci Soc Am J 70:448–453
Demisie W, Liu Z, Zhang M (2014) Effect of biochar on carbon fractions and enzyme activity of red soil. CATENA 121:214–221
Dempster DN, Gleeson DB, Solaiman ZM, Jones DL, Murphy DV (2012) Decreased soil microbial biomass and nitrogen mineralisation with Eucalyptus biochar addition to a coarse textured soil. Plan Soil 354:311–324
Deng L, Peng C, Huang C, Wang K, Shangguan Z (2019) Drivers of soil microbial metabolic limitation changes along a vegetation restoration gradient on the Loess Plateau, China. Geoderma 353:188–200
Ding Y, Liu Y, Liu S, Li Z, Tan X, Huang X, Zeng G, Zhou L, Zheng B (2016) Biochar to improve soil fertility. A Review Agron Sustain Dev 36:36
Elzobair KA, Stromberger ME, Ippolito JA, Lentz RD (2015) Contrasting effects of biochar versus manure on soil microbial communities and enzyme activities in an Aridisol. Chemosphere 142:145–152
Elzobair KA, Stromberger ME, Ippolito JA (2016a) Stabilizing effect of biochar on soil extracellular enzymes after a denaturing stress. Chemosphere 142:114–119
Elzobair KA, Stromberger ME, Ippolito JA, Lentz RD (2016b) Contrasting effects of biochar versus manure on soil microbial communities and enzyme activities in an Aridisol. Chemosphere 142:145–152
Fan L (2021) Effects of biochar addition on soil carbon pool dynamics and enzyme activity in coal mine reclamation. Taiyuan University of Technology
Foster EJ, Hansen N, Wallenstein M, Cotrufo MF (2016) Biochar and manure amendments impact soil nutrients and microbial enzymatic activities in a semi-arid irrigated maize cropping system. Agric Ecosyst Environ 233:404–414
Gerdelidani AF, Hosseini HM (2018) Effects of sugar cane bagasse biochar and spent mushroom compost on phosphorus fractionation in calcareous soils. Soil Res 56:136–144
Gomez JD, Denef K, Stewart CE, Zheng J, Cotrufo MF (2014) Biochar addition rate influences soil microbial abundance and activity in temperate soils. Eur J Soil Sci 65:28–39
Grossman JM, O’Neill BE, Tsai SM, Liang B, Neves E, Lehmann J, Thies JE (2010) Amazonian anthrosols support similar microbial communities that differ distinctly from those extant in adjacent, unmodified soils of the same mineralogy. Microb Ecol 60:192–205
Hale S, Hanley K, Lehmann J, Zimmerman A, Cornelissen G (2011) Effects of chemical, biological, and physical aging as well as soil addition on the sorption of pyrene to activated carbon and biochar. Environ Sci Technol 45:10445–10453
Hale SE, Lehmann J, Rutherford D, Zimmerman AR, Bachmann RT, Shitumbanuma V, O’Toole A, Sundqvist KL, Arp HPH, Cornelissen G (2012) Quantifying the total and bioavailable polycyclic aromatic hydrocarbons and dioxins in biochars. Environ Sci Technol 46:2830–2838
Halmi MF, Simarani K (2021) Responses of Soil Microbial Population and Lignocellulolytic Enzyme Activities to Palm Kernel Shell Biochar Amendment. Eurasian Soil Sc 54:1903–1911
Hanif MA, Ibrahim N, Dahalan FA, Md Ali UF, Hasan M, Azhari AW, Jalil AA (2023) Microplastics in facial cleanser: extraction, identification, potential toxicity, and continuous-flow removal using agricultural waste–based biochar. Environ Sci Pollut Res 30:60106
Herath HMSK, Camps-Arbestain M, Hedley M (2013) Effect of biochar on soil physical properties in two contrasting soils: An Alfisol and an Andisol. Geoderma 209:188–197
Hossain MZ, Bahar MM, Sarkar B, Donne SW, Ok YS, Palansooriya KN, Kirkham MB, Chowdhury S, Bolan N (2020) Biochar and its importance on nutrient dynamics in soil and plant. Biochar 2:379–420
Huang J (2012) Effects of biochar on soil microbial biomass and soil enzymes. PhD thesis. Chinese Academy of Agricultural Sciences
Imparato V, Veronika H, Susana SN, Tue KG, Laura G, Henrik H, Anders J, Giancarlo R, Anne W (2016) Gasification biochar has limited effects on functional and structural diversity of soil microbial communities in a temperate agroecosystem. Soil Biol Biochem 99:128–136
Ippolito JA, Stromberger ME, Lentz RD, Dungan RS (2016) Hardwood biochar and manure co-application to a calcareous soil. Chemosphere 142:84–91
Jeong CY, Dodla SK, Wang JJ (2016) Fundamental and molecular composition characteristics of biochars produced from sugarcane and rice crop residues and byproducts. Chemosphere 142:4–13
Jiang Y, Wang X, Zhao Y, Zhang C, Jin Z, Shan S, Ping L (2021) Effects of Biochar Application on Enzyme Activities in Tea Garden Soil. Front Bioeng Biotechnol 9:728530
Kasozi GN, Zimmerman AR, Nkedi-Kizza P, Gao B (2010) Catechol and humic acid sorption onto a range of laboratory-produced black carbons (biochars). Environ Sci Technol 44:6189–6195
Keiluweit M, Nico PS, Johnson MG, Kleber M (2010) Dynamic molecular structure of plant biomass-derived black carbon (biochar). Environ Sci Technol 44:1247–1253
Khodadad CLM, Zimmerman AR, Green SJ, Uthandi S, Foster JS (2011) Taxaspecific changes in soil microbial community composition induced by pyrogenic carbon amendments. Soil Biol Biochem 43:385–392
Kim JS, Sparovek G, Longo RM, De Melo WJ, Crowley D (2007) Bacterial diversity of terra preta and pristine forest soil from the Western Amazon. Soil Biol Biochem 39:684–690
Klibanov AM (1983) Stabilization of enzymes against thermal inactivation. Adv Appl Microbiol 29:1–28
Knicker H (2007) How does fire affect the nature and stability of soil organic nitrogen and carbon? A review. Biogeochemistry 85:91–118
Kolb SE, Fermanich KJ, Dornbush ME (2009) Effect of Charcoal Quantity on Microbial Biomass and Activity in Temperate Soils. Soil Sci Soc Am J 73:1173–1181
Kolton M, Harel YM, Pasternak Z, Graber RE, Elad Y, Cytryn E (2011a) Impact of biochar application to soil on the root-associated bacterial community structure of fully developed greenhouse pepper plants. Appl Environ Microb 77(14):4924–4930
Kolton M, Meller Harel Y, Pasternak Z, Graber ER, Elad Y, Cytryn E (2011b) Impact of Biochar Application to Soil on the Root-Associated Bacterial Community Structure of Fully Developed Greenhouse Pepper Plants. Appl Environ Microb 77:4924
Krause HM, Hüppi R, Leifeld J, El-Hadidi M, Harter J, Kappler A, Hartmann M, Behrens S, Mäder P, Gattinger A (2018) Biochar affects community composition of nitrous oxide reducers in a field experiment. Soil Biol Biochem 119:143–151
Lehmann J, Rillig MC, Thies J, Masiello CA, Hockaday WC, Crowley D (2011) Biochar effects on soil biota—A review. Soil Biol Biochem 43(9):1812–1836
Li W, Hou Y, Long M, Wen X, Han J, Liao Y (2023) Long-term effects of biochar application on rhizobacteria community and winter wheat growth on the Loess Plateau in China. Geoderma 429:116250
Liang B, Lehmann J, Solomon D, Kinyangi J, Grossman J, O"Neill B, Skjemstad JO, Thies J, Luizão FJ, Petersen J, Neves EG, (2006) Black Carbon increases cation exchange capacity in soils. Soil Sci Soc Am J 70:1719–1730
Liang C, Schimel JP, Jastrow JD (2017) The importance of anabolism in microbial control over soil carbon storage. Nat Microbiol 2(8):17105
Liao X, Kang H, Haidar G, Wang W, Malghani S (2022) The impact of biochar on the activities of soil nutrients acquisition enzymes is potentially controlled by the pyrolysis temperature: A meta-analysis. Geoderma 411:115692
Lin X, Cheng Y, Wang B, He S, Huang S, Zhou J, Cai X, Huang Q (2023) Effects of continuous biochar application on bacterial community structure in upland red soil. Soil Fert Sci China 10:28–35
Google Scholar
Liu X, Zhang X (2012) Effect of Biochar on pH of Alkaline Soils in the Loess Plateau: Results from Incubation Experiments. Int J Agric Biol 14:745–750
CAS Google Scholar
Liu P, Ptacek CJ, Blowes DW, Berti WR, Landis RC (2015) Aqueous leaching of organic acids and dissolved organic carbon from various biochars prepared at different temperatures. J Environ Qual 44:684
Liu G, Zhang X, Wang X, Shao H, Yang J, Wang X (2017) Soil enzymes as indicators of saline soil fertility under various soil amendment. Agr Ecosyst Environ 237:274–279
Liu Y, Dai Q, Jin X, Dong X, Peng J, Wu M, Liang N, Pan B, Xing B (2018) Negative Impacts of Biochars on Urease Activity: High pH, Heavy Metals, Polycyclic Aromatic Hydrocarbons, or Free Radicals? Environ Sci Technol 52(21):12740–12747
Liu Y, Guo K, Zhao Y, Li S, Wu Q, Liang C, Sun X, Xun Q, Qin H (2020) Change in composition and function of microbial communities in an acid bamboo (Phyllostachys praecox) plantation soil with the addition of three different biochars. For Ecol Manag 473:118336
Liu B, Li H, Li H, Zhang A, Rengel Z (2021) Long-term biochar application promotes rice productivity by regulating root dynamic development and reducing nitrogen leaching. GCB Bioenergy 13(1):257–268
Liu B, Xia H, Jiang C, Riaz M, Yang L, Chen Y, Fan X, Xia X (2022) 14 year applications of chemical fertilizers and crop straw effects on soil labile organic carbon fractions, enzyme activities and microbial community in rice-wheat rotation of middle china. Sci Total Environ 841:156608
Lopes R, Reis MM, Frazo LA, Terra LEDM, Fernandes LA (2021) Biochar increases enzyme activity and total microbial quality of soil grown with sugarcane. Environ Technol Innovation 21:101270
Lu X, Zheng Y, Chen X, Han X, Zou W, Dong B, Yan J (2022) Effects of application of biochar and organic fertilizer on soil enzyme activity in alsols. J Agri Environ Sci 41(03):568–574
Luo S, Wang S, Tian L, Li S, Li X, Shen Y, Tian C (2017a) Long-term biochar application influences soil microbial community and its potential roles in semiarid farmland. Appl Soil Ecol 117–118:10–15
Luo Y, Lin Q, Durenkamp M, Dungait AJ, Brookes PC (2017b) Soil priming effects following substrates addition to biochar-treated soils after 431days of pre-incubation. Biol Fert Soils 53:315–326
Manirakiza E, Ziadi N, Luce MS, Hamel C, Antoun H, Karam A (2019) Nitrogen mineralization and microbial biomass carbon and nitrogen in response to co-application of biochar and paper mill biosolids. Appl Soil Ecol 142:90–98
McCafferty KW, Purswell JL (2023) Applied Research Note: Effects of various concentrations of supplemental biochar on ileal digestible energy and live performance of broilers during an 8-wk production period. J Appl Poultry Res 32(1):100323
McCormack SA, Ostle N, Bardgett RD, Hopkins DW, Vanbergen AJ (2013) Biochar in bioenergy cropping systems: Impacts on soil faunal communities and linked ecosystem processes. GCB Bioenergy 5(2):81–95
Mitchell PJ, Simpson AJ, Soong R, Simpson MJ (2015) Shifts in microbial community and water-extractable organic matter composition with biochar amendment in a temperate forest soil. Soil Biol Biochem 81:244–254
Mohan C, Annachhatre A (2023) Role of pine needle biochar in operation and stability of anaerobic processes. Biodegradation 34(1):53–71
Munera-Echeverri JL, Martinsen V, Strand LT, Zivanovic V, Cornelissen G, Mulder J (2018) Cation exchange capacity of biochar: an urgent method modification. Sci Total Environ 642:190
Ndoun MC, Knopf A, Preisendanz HE, Vozenilek N, Elliott HA, Mashtare ML, Velegol S, Veith TL, Williams CF (2023) Fixed bed column experiments using cotton gin waste and walnut shells-derived biochar as low-cost solutions to removing pharmaceuticals from aqueous solutions. Chemosphere 330:138591
Neogi S, Sharma V, Khan N, Chaurasia D, Ahmad A, Chauhan S, Singh A, You S, Pandey A, Chaturvedi P (2022) Bhargava Sustainable biochar: A facile strategy for soil and environmental restoration, energy generation, mitigation of global climate change and circular bioeconomy. Chemosphere 293:133474
Nie C, Yang X, Niazi NK, Xu X, Wen Y, Rinklebe J, Ok YS, Xu S, Wang H (2018) Impact of sugarcane bagasse-derived biochar on heavy metal availability and microbial activity: A field study. Chemosphere 200:274–282
Novak JM, Busscher WJ, Laird DL, Ahmedna M, Watts DW, Niandou MAS (2009) Impact of Biochar Amendment on Fertility of a Southeastern Coastal Plain Soil. Soil Sci 174(2):105–112
Oleszczuk P, Jośko I, Futa B, Pasieczna-Patkowska S, Pałys E, Kraska P (2014) Effect of pesticides on microorganisms, enzymatic activity and plant in biochar amended soil. Geoderma 214:10–18
Palansooriya KN, Ok YS, Awad YM, Lee SS, Sung JK, Koutsospyros A, Moon DH (2019) Impacts of biochar application on upland agriculture: A review. J Environ Manage 234:52–64
Pandey B, Suthar S, Chand N (2022) Effect of biochar amendment on metal mobility, phytotoxicity, soil enzymes, and metal-uptakes by wheat (Triticum aestivum) in contaminated soils. Chemosphere 307:135889
Perez-Cruzado C, Merino A, Rodriguez-Soalleiro R (2011) A management tool for estimating bioenergy production and carbon sequestration in Eucalyptus globulus and Eucalyptus nitens grown as short rotation woody crops in north-west Spain. Biomass Bioenerg 35:2839–2851
Pokharel P, Ma Z, Chang S (2020) Biochar increases soil microbial biomass with changes in extra- and intracellular enzyme activities: a global meta-analysis. Biochar 2:65–79
Prayogo C, Jones JE, Baeyens J, Gary D (2014) Impact of biochar on mineralisation of C and N from soil and willow litter and its relationship with microbial community biomass and structure Bending. Biol Fertil Soils 50:695–702
Prendergast-Miller MT, Duvall M, Sohi SP (2014) Biochar-root interactions are mediated by biochar nutrient content and impacts on soil nutrient availability. Eur J Soil Sci 65(1):173–185
Purakayastha TJ, Bera T, Bhaduri D, Sarkar B, Mandal S, Wade P, Kumari S, Biswas S, Menon M, Pathak H, Tsang DC (2019) A review on biochar modulated soil condition improvements and nutrient dynamics concerning crop yields: Pathways to climate change mitigation and global food security. Chemosphere 227:345–365
Rasul M, Cho J, Shin HS, Hur J (2022) Biochar-induced priming effects in soil via modifying the status of soil organic matter and microflora: a review. Sci Total Environ 805:150304
Roberts DA, Cole AJ, Paul NA, de Nys R (2015) Algal biochar enhances the revegetation of stockpiled mine soils with native grass. J Environ Manage 161:173–180
Rondon MA, Lehmann J, Ramirez J, Hurtado M (2007) Biological nitrogen fixation by common beans (Phaseolus vulgaris L.) increases with bio-char additions. Biol Fertil Soils 43:699–708
Sarfraz R, Yang W, Wang SS, Zhou BQ, Xing SH (2020) Short term effects of biochar with different particle sizes on phosphorous availability and microbial communities. Chemosphere 256:126862
Smith JL, Collins HP, Bailey VL (2010) The effect of young biochar on soil respiration. Soil Biol Biochem 42:2345–2347
Sohi S, Lopez-Capel E, Krull E, Bol R (2009) Biochar, climate change and soil: A review to guide future research. CSIRO Land and Water Science Report 5(9):17–31
Sohi S, Krull E, Lopez-Capel E, Bol R (2010) A review of biochar and its use and function in soil. Adv Agron 105:47–82
Song Y, Tahmasebi A, Yu J (2014) Co-pyrolysis of pine sawdust and lignite in a thermogravimetric analyzer and a fixed-bed reactor. Bioresour Technol 174:204–211
Song X, Razavi BS, Ludwig B, Zamanian K, Zang H, Kuzyakov Y, Dippold MA, Gunina A (2020) Combined biochar and nitrogen application stimulates enzyme activity and root plasticity. Sci Total Environ 735:139393
Spokas KA, Novak JM, Stewart CE, Cantrell KB, Uchimiya M, DuSaire MG, Ro KS (2011) Qualitative analysis of volatile organic compounds on biochar. Chemosphere 85:869–882
Sun J, Li H, Wang Y, Du Z, Rengel Z, Zhang A (2022) Biochar and nitrogen fertilizer promote rice yield by altering soil enzyme activity and microbial community structure. GCB Bioenergy 00:1–15
Tang B, Xu H, Song F, Ge H, Yue S (2022) Effects of heavy metals on microorganisms and enzymes in soils of lead–zinc tailing ponds. Environ Res 207:112174
Tian X, Lu G, Gao N, Yang J, Yu J, Han G, Guan B (2020) Response of soil enzyme activity in heavily salinized wetlands to biochar addition and shallow tillage. Soil Bulletin 51(05):1189–1195
Trivedi P, Delgado-Baquerizo M, Jeffries TC, Trivedi C, Anderson IC, Mcnee M, Flower K, Pal Singh B, Minkey D, Singh BK (2017) Soil aggregation and associated microbial communities modify the impact of agricultural management on carbon content. Environ Microbiol 19:3070–3086
Tryon EH (1948) Effect of charcoal on certain physical, chemical, and biological properties of forest soils. Ecol Monogr 18(1):81–115
Van Zwieten L, Singh BP, Kimber SWL, Murphy DV, Macdonald LM, Rust J, Morris S (2014) An incubation study investigating the mechanisms that impact N2O fl ux from soil following biochar application. Agr Ecosyst Environ 191:53–63
Verheijen FGA, Jeffery S, Bastos AC, Velde M, Diafas IVD (2009) Biochar Application to Soils - A Critical Scientific Review of Effects on Soil Properties, Processes and Functions
Wang Z, Zong H, Zheng H, Liu G, Chen L, Xing B (2015) Reduced Nitrification and Abundance of Ammonia-Oxidizing Bacteria in Acidic Soil Amendedwith Biochar. Chemosphere 138:56–583
Wang C, Lu X, Mori T, Mao Q, Zhou K, Zhou G, Nie Y, Mo J (2018) Responses of soil microbial community to continuous experimental nitrogen additions for 13 years in a nitrogen-rich tropical forest. Soil Biol Biochem 121:103–112
Wang Y. (2019) Localization of effects of biochar addition on soil enzyme activity and bacterial diversity in semi-arid areas. Northwest Agriculture and Forestry University
Wardle DA, Nilsson MC, Zackrisson O (2008) Fire-derived charcoal causes loss of forest humus. Science 320:629
Warnock DD, Mummey DL, Mcbride B, Major J, Lehmann J, Rillig MC (2010a) Influences of non-herbaceous biochar on arbuscular mycorrhizal fungal abundances in roots and soils: results from growth- chamber and field experiments. Appl Soil Ecol 46(3):450–456
Warnock DD, Mummey DL, McBride B, Major J, Lehmann J, Rillig MC (2010b) Influences of non-herbaceous biochar on arbuscular mycorrhizal fungal abundances in roots and soils: Results from growth-chamber and field experiments. Appl Soil Ecol 46:450–456
Watzinger A, Feichtmair S, Kitzler B, Zehetner F, Kloss S, Wimmer B, Zechmeister-Boltenstern S, Soja G (2014) Soil microbial communities responded to biochar application in temperate soils and slowly metabolized 13 C-labelled biochar as revealed by 13 C PLFA analyses: results from a short-term incubation and pot experiment. Eur J Soil Sci 65:40–51
Wei J, Li Y (2023) Research Progress on the Effects of Biochar Addition on Rhizosphere Soil Microbial Communities. J Hunan Ecol Sci 10(2):101–108
Whalen ED, Grandy AS, Sokol NW, Keiluweit M, Ernakovich J, Smith RG, Frey SD (2022) Clarifying the evidence for microbial- and plant-derived soil organic matter, and the path towards a more quantitative understanding. Global Change Biol 28(24):7167–7185
Windeatt JH, Ross AB, Williams PT, Forster PM, Nahil MA, Singh S (2014) Characteristics of biochars from crop residues: Potential for carbon sequestration and soil amendment. J Environ Manage 146:189–197
Wu C, Hou Y, Bie Y, Chen X, Lin L (2020) Effects of Biochar on Soil Water-Soluble Sodium, Calcium, Magnesium and Soil Enzyme Activity of Peach Seedlings. IOP Publishing Ltd IOP Publishing Ltd 446:032007
Yamato M, Okimori Y, Wibowo IF, Anshori S, Ogawa M (2006) Effects of the application of charred bark of Acacia mangium on the yield of maize, cowpea and peanut, and soil chemical properties in South Sumatra. Indonesia Soil Sci Plan Nutr 52(4):489–495
Yang C, Liu J, Ying H, Lu S (2022a) Soil pore structure changes induced by biochar affect microbial diversity and community structure in an Ultisol. Soil till Res 224:105505
Yang X, Sun Q, Yuan J, Fu S, Lan Y, Jiang X, Meng J, Han X, Chen W (2022b) Successive corn stover and biochar applications mitigate N 2 O emissions by altering soil physicochemical properties and N-cycling-related enzyme activities: A five-year field study in Northeast China. Agr Eco Environ 340:108183
You JJ, Sun L, Liu X, Hu XL, Xu Q (2019) Effects of Sewage Sludge Biochar on Soil Characteristics and Crop Yield in Loamy Sand Soil. Polish J Environ Stud 28:2973–2980
Yuan F, Li KY, Yang H, Deng CJ, Liang H, Song LH (2022) Effects of Biochar Application on Yellow Soil Nutrients and Enzyme Activities. Huan Jing Ke Xue 43(9):4655–4661 (Chinese)
Yuan M, Zhu X, Sun H, Song J, Li C, Shen Y, Li S (2023) The addition of biochar and nitrogen alters the microbial community and their cooccurrence network by affecting soil properties. Chemosphere 312:137101
Zeelie A (2012) Effect of Biochar on Selected Soil Physical Properties of Sandy Soil with Low Agricultural Suitability [D]. Stellenbosch University, Stellenbosch
Zhang Y, Wang J, Feng Y (2021) The effects of biochar addition on soil physicochemical properties: A review. CATENA 202:105284
Zheng W, Zhao ZY, Gong QL, Zhai BN, Li ZY (2018) Responses of fungal–bacterial community and network to organic inputs vary among different spatial habitats in soil. Soil Biol Biochem 125:54–63
Zheng Q, Hu Y, Zhang S, Noll L, Böckle T, Dietrich M, Herbold CW, Eichorst SA, Woebken D, Richter A (2019) Soil multifunctionality is affected by the soil environment and by microbial community composition and diversity. Soil Biol Biochem 136:107521
Zheng L, Tong C, Gao J, Xiao R (2022a) Effects of wetland plant biochars on heavy metal immobilization and enzyme activity in soils from the Yellow River estuary. Environ Sci Pollut Res Int 29(27):40796–40811
Zheng X, Xu W, Dong J, Yang T, Shangguan Z, Qu J, Li X, Tan X (2022b) The effects of biochar and its applications in the microbial remediation of contaminated soil: A review. J Hazard Mater 438:129557
Zhuang Y, Wang J (2021) A Review of the Effects of Biochar and Fertilizer on Soil Physical and Chemical Properties and Crop Growth. J Water Reso and Arch Engi 19(4):186–193
Download references
This study was supported by the National Key Research and Development Program of China (2022YFD1500600), the Guiding Fund of the Central Government for Local Science and Technology Development, China (2023JH6/100100056), the Science and Technology Plan Project of Shenyang, China (22–317-2–08), the Earmarked Fund for Modern Agroindustry Technology Research System, China (CARS-01–51). Partial support was provided by the Doctoral Research Start-Up Funding of Shenyang Agricultural University (880418059, 880418058).
Author information
Xinxin Jin and Tongxin Zhang these authors contributed equally to this paper.
Authors and Affiliations
Postdoctoral Station of Crop Science and Tillage, Agronomy College, Shenyang Agricultural University, Shenhe District, NO 120 Dongling Road, Shenyang, 110866, Liaoning Province, China
Xinxin Jin & Jun Meng
Key Laboratory of Arable Land Conservation in Northeast China, Ministry of Agriculture and Rural Affairs, College of Land and Environment, Shenyang Agricultural University, P. R, Shenyang, 110866, China
Xinxin Jin, Tongxin Zhang, Yuetong Hou, Xiaojie Zhang, Na Yu, Hongtao Zou & Jingkuan Wang
Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Agrosphere (IBG-3), Wilhelm-Johnen-Straße, 52428, Jülich, Germany
Xinxin Jin & Roland Bol
College of Engineering, Shenyang Agricultural University, Shenyang, 110866, China
You can also search for this author in PubMed Google Scholar
Corresponding authors
Correspondence to Jun Meng or Hongtao Zou .
Ethics declarations
Conflict of interest.
No conflict of interest exists in the submission of this manuscript, and manuscript is approved by all authors for publication.
Additional information
Responsible editor: Shahla Hosseini Bai
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
• Biochar provides nutrients such as carbon and nitrogen sources for soil microorganisms.
• Biochar improve soil enzyme activity by improving the quantity and reproductive capacity of microorganisms.
• Soil microorganisms and enzymes mutually influence and constrain each other.
• Biochar type and formation pyrolysis temperature control on soil microbial community and enzymes activity
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Reprints and permissions
About this article
Jin, X., Zhang, T., Hou, Y. et al. Review on the effects of biochar amendment on soil microorganisms and enzyme activity. J Soils Sediments (2024). https://doi.org/10.1007/s11368-024-03841-7
Download citation
Received : 12 June 2023
Accepted : 03 June 2024
Published : 21 June 2024
DOI : https://doi.org/10.1007/s11368-024-03841-7
Share this article
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative
- Biochar amendment
- Soil microorganisms
- Soil enzyme
- Find a journal
- Publish with us
- Track your research
View: Session 9A: Percolator: Theory and Praxis of Liberatory Justice in Public Service Organizations: Rewards, Challenges, and the Way Forward
![]() Chemical Society ReviewsReactive capture and electrochemical conversion of co 2 with ionic liquids and deep eutectic solvents. ![]() * Corresponding authors a Chemical and Biomolecular Engineering, Case Western Reserve University, Cleveland, OH, USA E-mail: [email protected] b Department of Chemical and Biological Engineering, Koç University, Rumelifeneri Yolu, Sariyer, 34450 Istanbul, Turkey c Koç University TÜPRAŞ Energy Center (KUTEM), Koç University, Rumelifeneri Yolu, Sariyer, 34450 Istanbul, Turkey d Department of Materials Science and Technology, Faculty of Science, Turkish-German University, Sahinkaya Cad., Beykoz, 34820 Istanbul, Turkey e Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA f Conn Center for Renewable Energy Research, University of Louisville, Louisville, KY 40292, USA g Materials Science Division, Lawrence Livermore National Laboratory, Livermore, CA, USA h Department of Chemistry, University of California, Irvine, Irvine, CA 92697, USA i Department of Chemistry, University of California, Davis, Davis, CA 95616, USA j Department of Mathematics, Computer Science, & Engineering Technology, Elizabeth City State University, 1704 Weeksville Road, Elizabeth City, NC 27909, USA k Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA l Koç University Surface Science and Technology Center (KUYTAM), Koç University, Rumelifeneri Yolu, Sariyer, 34450 Istanbul, Turkey Ionic liquids (ILs) and deep eutectic solvents (DESs) have tremendous potential for reactive capture and conversion (RCC) of CO 2 due to their wide electrochemical stability window, low volatility, and high CO 2 solubility. There is environmental and economic interest in the direct utilization of the captured CO 2 using electrified and modular processes that forgo the thermal- or pressure-swing regeneration steps to concentrate CO 2 , eliminating the need to compress, transport, or store the gas. The conventional electrochemical conversion of CO 2 with aqueous electrolytes presents limited CO 2 solubility and high energy requirement to achieve industrially relevant products. Additionally, aqueous systems have competitive hydrogen evolution. In the past decade, there has been significant progress toward the design of ILs and DESs, and their composites to separate CO 2 from dilute streams. In parallel, but not necessarily in synergy, there have been studies focused on a few select ILs and DESs for electrochemical reduction of CO 2 , often diluting them with aqueous or non-aqueous solvents. The resulting electrode–electrolyte interfaces present a complex speciation for RCC. In this review, we describe how the ILs and DESs are tuned for RCC and specifically address the CO 2 chemisorption and electroreduction mechanisms. Critical bulk and interfacial properties of ILs and DESs are discussed in the context of RCC, and the potential of these electrolytes are presented through a techno-economic evaluation. Article information![]() Download CitationPermissions. ![]() S. Dongare, M. Zeeshan, A. S. Aydogdu, R. Dikki, S. F. Kurtoğlu-Öztulum, O. K. Coskun, M. Muñoz, A. Banerjee, M. Gautam, R. D. Ross, J. S. Stanley, R. S. Brower, B. Muchharla, R. L. Sacci, J. M. Velázquez, B. Kumar, J. Y. Yang, C. Hahn, S. Keskin, C. G. Morales-Guio, A. Uzun, J. M. Spurgeon and B. Gurkan, Chem. Soc. Rev. , 2024, Advance Article , DOI: 10.1039/D4CS00390J This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence . You can use material from this article in other publications, without requesting further permission from the RSC, provided that the correct acknowledgement is given and it is not used for commercial purposes. To request permission to reproduce material from this article in a commercial publication , please go to the Copyright Clearance Center request page . If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given. If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party commercial publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page . Read more about how to correctly acknowledge RSC content . Social activitySearch articles by author. This article has not yet been cited. Advertisements![]() |
IMAGES
VIDEO
COMMENTS
DETERMINANTS OF CAPITAL STRUCTURE: A. LITERATURE REVIEW. Athenia Bongani Sibindi*. *University of South Africa, Department of F inance, Risk Management and Banking, P.O Box 392, UNI SA, South ...
The journal articles chosen for this capital structure determinants literature review study cover a time span of 7 years that is, from 2014 to 2020. This time scope criterion was drawn from the review of literature on the determinants of capital structure conducted by Kumar et al. (Citation 2017) from the period 1972 to 2013.
Pandey and Singh (2015) review the literature of capital structure determinants and find size, growth, tangibility, profitability, business risk, non-debt tax shield, age, dividend pay-out ratio ...
Determinants of the adjustment speed of capital structure. Tesfaye T. Lemma M. Negash. Economics, Business. 2014. Purpose - The purpose of this paper is to examine the role of institutional, macroeconomic, industry, and firm characteristics on the adjustment speed of corporate capital structure within the….
the literature review in the area of capital structure comprising capital structure theories, capital structure common empirical determinants. Section 3 takes into account methodology of the
Economics, Business. Financial decision is one of the most crucial decisions in corporate finance. Financial managers want to know the optimum level of debt and equity. In this paper the literatures on determinants of capital structure studied by the Indian and international researchers are reviewed. The paper is divided in two parts.
Determinants of Capital Structure: A Literature Review. Capital structure decisions are significant financial decisions of the corporate firms as they influence the return as well as the risk of equity shareholders. A vast volume of work has empirically investigated the capital structure decisions in India and abroad.
The paper covers a considerable period of time (1972-2013). Among very few review papers on capital structure research, to the best of authors' knowledge; this is the first review to identify what is missing in the literature on the determinants of capital structure while offering recommendations for future studies.
Using a standardized methodology, we empirically evaluate 55 proposed determinants of capital structure in terms of statistical significance, economic significance, and identification. We find that robust and economically important determinants of debt ratios are relatively few in number. ... " A Review of Empirical Capital Structure Research ...
Capital structure has been an important focus point in the literature since MM started publishing their research about it in 1958.Capital structure is a remarkable topic because it has researched in both academic level and corporate level since the financing decisions of a firm
This study presents a literature review on 'determinants of capital structure' conducted by the researchers in India and abroad for the period 2000 to 2015. This paper is divided into three sections. In section 1, the researcher reviews capital structure determinants of international studies.
2. Literature review on capital structure theory. Modigliani and Miller (Citation 1958) have pioneered research on the capital structure and its relation to firm value. Based on the strict conditions of competitive, frictionless and perfect market capital, the firm's market value is independent of its capital structure choices whereas the ...
Determinants of capital structure 257 and total leverage, respectively. Industry median leverage and inflation also play a notable but smaller role when compared to firm size, profitability, tangi-bility, and tax-related determinants. We next carry out a rare exercise in the literature on corporate capital structure in developing econo-mies.
the evidence that relates to the cross-sectional determinants of capital structure. This literature identifies and discusses the characteristics of firms that tend to be associated with different debt ratios. In the second part, we review the literature that examines changes in capi-tal structure.
review of the extant studies of capital structure that have been conducted during the period 1950-2015. The rest of this paper is arranged as follows: Section 2 considers the firm level determinants of capital structure. Section 3 reviews the empirical literature on the determinants of capital structure. Section 4 concludes the paper. 2.
Downloadable (with restrictions)! In this paper, we present the literature review on determinants of capital structure of the research being done, both in India as well as internationally, in the last one and a half decade. We divide our study in two ways: one review for international research and second from Indian research. We further subdivide the research (both Indian as well as ...
Abstract. Purpose: The purpose of this paper is to study the status of studies on capital structure determinants in the past 40 years. This paper highlights the major gaps in the literature on determinants of capital structure and also aims to raise specific questions for future research. Design/methodology/approach: The prominence of research ...
Again, in the capital structure literature, some studies have centered on the determination of an optimal capital structure for a specific firm (Leland, 2019) as well as whether the quantum of ...
In this paper, we present the literature review on determinants of capital structure of the research being done, both in India as well as internationally, in the last one and a half decade. We divide our study in two ways: one review for international research and second from Indian research. We further subdivide the research (both Indian as well as international) in two parts. In first part ...
In this paper, we present the literature review on determinants of capital structure of the research being done, both in India as well as internationally, in the last one and a half decade. We divide our study in two ways: one review for international research and second from Indian research. We further subdivide the research (both Indian as well as international) in two parts. In first part ...
being theoretical support. Second, through a literature review of previous studies on the determinants of capital structure, this thesis summarizes the results fróm those studies. Third, I will compare listed determinants with the three main theories of capital structure, and find the capital structure theories and empirical evidence on the
potentially impact the capital structure decisions. Testing a wide range of determinants will possibly give a broader understanding of what determines the capital structure in listed Swedish firms. Modigliani and Miller (1958) are known to be among the first to publish research about capital structure and firm value (Baker and Martin, 2011, p. 2).
Keywords: Capital structure determinants; literature review; pecking order theory; ... aid in ascertaining much insights in the area of capital structure determinants is through systema-tic review approach, and this research approach is mostly employed to explain major findings of the review, thereby highlighting the gaps in the literature ...
A literature review on this subject has shown that most previous studies focused on the US (i.e., [20,21,22,55]). By contrast, the London Stock Exchange has not been extensively investigated. ... The COVID-19 dummy and most capital structure determinants and industries contributed to decreasing debt during the pandemic. GMM restrictions were ...
2 Literature Review. ... Human capital is an integral part of the digital government of the state. Rabbani and Maksymenko ... DG and some other institutional structure determinants such as corruption, democratic accountability, and institutional governance can be added to analyze their impacts on PHS in Asian economies. Thus, a region or ...
Purpose The multiple benefits of biochar use as a soil amendment has garnered global attention. Biochar addition is a crucial factor to improve soil biomass, soil enzyme activities, microbial biomass and improve soil nutrient utilization rate. However, the precise mechanism of effects of biochar addition on microbial community structure and diversity, as well as enzyme activity, remains ...
The initial contributions of Modigliani and Miller (Citation 1958) have sparked arguments on the capital structure determinants. One aspect of such determinants is the board composition. ... Theoretical literature review. The study views the link between capital structure and board gender from an agency theory and resource dependency perspective.
PBF literature reveals several gaps in understanding the consequences of PBF policies: (1) most previous studies focus on PBF policy design variation, thereby ignoring the complex nature of governance structure and how that structure influences organizational behavior; (2) scholars commonly conceptualize governance structure as a continuum ...
Ionic liquids (ILs) and deep eutectic solvents (DESs) have tremendous potential for reactive capture and conversion (RCC) of CO 2 due to their wide electrochemical stability window, low volatility, and high CO 2 solubility. There is environmental and economic interest in the direct utilization of the captured CO 2 using electrified and modular processes that forgo the thermal- or pressure ...