Questions related to Capital Structure
I am doing a research project to study the determinants of capital structure. However, I've run into two issues.
After downloading data from Compustat, I noticed there are a lot of missing values amongst the data, and I wonder how I can deal with this data? How is it usually done in finance literature?
The other problem I came across is strange to me, and one of my variables, Interest expsense, includes zero values and sometimes also negative values, which not only does not make sense but also poses issues in calculating coverage ratio. What do you suggest me to do in this case?
I highly appreicate your response.
research done on third world countries on the relationship between capital structure and financial performance in different industries
How do you measure the capital structure for an insurance company when it is by nature leveraged?
My argument is that the debt/equity ratio is problematic for financial firms.
I intend to use the QCA (qualitative Comparative Analysis) to compare the impact of banking regulation on Islamic and conventional banks, I would like to have your opinion and is what I can combine it with the DEA and regression
The theories mobilized :
*The theory of capital structure
*The theory of financial intermediation
The methods used:
Z-score for stability
DEA to measure efficiency
Capital Structure is the particular mix of debt and equity used by a company to finance its overall operations and growth. There is an optimal capital structure for a given firm, that is the mix of debt and equity financing matters. The optimal capital structure is the optimal mix of debt and equity financing that lowers the firm's overall weighted average cost of capital and maximizes its value. Corporate Strategy is a portfolio approach to srategic decision making. It takes a look across all the firm's businesses to assess how to create the most value. To develop a corporate strategy, a firm must investigate how the various pieces of the business fit together, how they impact each other, and how the parent company is structured, in order to optimize human capital, processes, and governance. Corporate strategy builds on top of business strategy which is concerned with the strategic decision making for an individual business.
Is there a connection between Corporate Strategy and Capital Structure?
From the beginning of the industrial revolution and the description of the functioning of enterprises in the conditions of market structures, in the trend of classical economics, three types of production factors dominated in the production processes defined by three slogans: land, labor, capital.
However, successively with the development of industry and technological progress in the 20th century, other categories of production factors, typical for economies largely based on information, are added to these classic factors of production.
These factors of production, whose role in many industries has been growing since the 1960s include: knowledge, information, technology and innovation.
In view of the above, the current question is: In what branches of industry such production factors as knowledge, information, technology and innovation are currently or become the most important?
Please, answer, comments. I invite you to the discussion.
Hello, I'm trying to run an OLS regression to test whether firms’ capital structure changes more during the 2007-2008 financial crisis according to their pre-crisis liquidity.
My quarterly data runs from 2000 - 2020. I create a dummy variable CRISIS_DUM for the crisis period 2007Q3 - 2008Q2. I also create a dummy variable PRECRISIS_DUM for the pre-crisis quarter 2007Q2. My baseline model is something like this:
LEVERAGE = LIQUIDITY + PRECRISIS_DUM + CRISIS_DUM + LIQUIDITY x PRECRISIS_DUM + CONTROLS (PROFITABILITY, ASSET TANGIBILITY, SIZE, MARKET-TO-BOOK)
My variable of interest is LIQUIDITY x PRECRISIS_DUM but the OLS estimator results insignificance.
I have a few concerns regarding the model:
- Is this model adequate in testing the relationship between pre-crisis liquidity and leverage during the financial crisis?
- Should I include Firm Fixed Effects, given the controls included in the model?
- Should I reduce the time period?
Any advice and comment is greatly appreciated. Thank you!
My topic is Financial performance of SMEs using Islamic versus Conventional Financing.
I have two financial performance variables of ROA and ROE, and Three predictors, Debt to Equity, Short-term Debt and Long-term Debt with two control variables of Tangibility and Growth. I want to add Liquidity in my model. Shall I add it as predictors or control variables?
Looking for your suggestions. Thank You
What kind of scientific research dominate in the field of Analysis of the effectiveness of stock exchange markets?
Please, provide your suggestions for a question, problem or research thesis in the issues: Analysis of the effectiveness of stock exchange markets.
I invite you to the discussion
Thank you very much
1. Variables of Capital Structure are Total Debt, Short-term debt & Long-term debt Whereas,
2. Financial Performance measured by ROA & ROE
3. Firm Characteristics i.e. Age, Size, Location, Sector & Ownership structure.
4. Owner-manager Characteristics like, Age, Gender, Education, Experience & Ethical background
Your suggestions that how the Firm Characteristics and Owner-manager Characteristics are measured? and which estimation techniques uses for this type of data?
Capital Structure Theories like MM Theorem, Trade-off, POT and so on fall under what categories.
i.e. Net Income Approach, Net Operating Approach, Traditional Approach etc.
Hi, I have recently conducting a research on the determinant of securities offering. And I have about 1500 companies at different announcement dates (From 2000- 2018). However, I need to collect financial information for compaines prior to their annoucement.
For example, if a firm annouced to issue convertible bond at June 1st 2012, it does not make sense to use financial information after that. I have seen little references to deal with this issue in the literatures.
My question is, how to I solve this issue without manually going through all 1500 companies.
Thanks for your help !
Does deepening the liberalization of the rules of conducting transactions in financial markets, banking lobbying in rating agencies, moral hazard in investment banking, failure to observe prudential procedures, neglecting the methodology of creditworthiness analysis in the process of verification of potential borrowers and violation of ethics in business can be the main factor in the next global financial crisis?
And these types of factors at the transactional and procedural level were, in addition to the mild monetary policy of central banking, indicated by economists as the key determinants of generating the global financial crisis in 2008.
Please, answer, comments.
I invite you to the discussion.
Dear Friends and Colleagues of RG,
The issues of risk management in the context of determinants of the global financial crisis, globalization processes, technological progress and other factors I described in the publications:
I invite you to discussion and cooperation.
I'm interested in estimating the impact of business risk on capital structure (CS) and dividend policy (DP). My study focused on three hypotheses. The first and second hypotheses focused on estimating panel regression to examine impact of business risk on CS, and impact of business risk on DP. Now in the third hypothesis, i want to estimate impact of business risk on CS and DP in one analysis using eviews. Is there a way to do that?
Are the supra-national investment investments in investment banking an important factor in the ongoing process of economic globalization?
If the increase in the scale of transnational investment investments in investment banking is faster than the rate of economic growth of the countries expressed, for example, in the Gross Domestic Product, is this the way in which economic globalization can generate additional systemic credit risks?
If in the context of these processes the diversification in profitability and income between investment banking and other types of financial institutions and non-financial business entities increases, can this situation be one of the symptoms of increasing systemic risk and the probability of the next global financial crisis appearing in the next several years?
How the bank credit influence the corporate working capital management policies of commercial and industrial sector of Pakistan?
What kind of different proxies (Operational Variable) would be considered, when I shall make hypothesis, sample design, collection of data and analysis the data?
No benefit of financial leverage, but still a great peace of mind due to low proportion of debt component in the capital structure of a company.
I am running panel data analysis and facing some difficulties. My goal is to find out drivers of firms' decision on leverage. I am using Eviews software for my analysis.
My data has 9 years timespan with yearly frequency and consists of 75 companies, represented by 23 industries.
My dependent variables are: long-term debt, short-term debt .
Independent variables: profitability(x1), size(x2), tangibility(x3), liquidity(x4), non-debt tax shield(x5) median industry leverage(x6). All my variables are appropriately transformed.
I estimated Y C X1 X2 X3 X4 X5 X6 random effect equation (as suggested by Hausman test) and got satisfying result. Next, I decided to include dummy variables (k-1) for each industry to control individual intercept and find out effect of each industry.
The problem is that I can no more
estimate an equation as Eviews gives me 'Near singular matrix'. I dropped variable X6 and managed to estimate pooled regression. However, random effect regression can no longer be estimated as 'there are not enough cross-sections'. From now on Eviews allows just for fixed effect regression.
After introduction of dummy variables, Eviews does not let me to conduct Heteroscedasticity and Hausman tests.
Thank you for dedicating your time to read this question. Any help is appreciated.
Dear all, I want to conduct a research on the determinants of capital structure of commercial Banks. Their capital structure is regulated by national Banks. So, is it recommended to conduct a study on this topic?
Almost all the Micro Finance Literature on Capital structure, governance and Performance shows that data is collected from Mix Market. Is this Data available on DATA STREAM ??
Hi. I am writing my master thesis about the influense of market timing on capital structure. In doing this, I am using the paper by Baker and Wurgler (2002) as inspiration. They have panel data of many US firms and multiple years.
To test the effect of market timing, they construct a variable EFWAMB which is the "weighted average market-to-book ratio" weighted by the sum of external finance in any given year divided by the total of external finance issued up untill that point from year 0 in the sample.
Then they run a pooled OLS with White SE:
Book leverage = EFWAMB (t-1) + MB(t-1) + Tangibility(t-1) + Profitability(t-1) + size(t-1)
However, they do not give any reasoning for pooling the data and breaking the panel structure. Why are they not concerned with serial correlation in the residuals?
In all fairness, I am worried about unobservable fixed factors such as managerial ability or attitudes towards risk. At the same time, I am worried about time-specific effects such as the interest rates and demand.
Could anyone please give me some advise on which model to pick? Can I use fixed effect regressions in this circumstance? Because, using fixed effects, I get an insignificant EFWAMB. Using pooled OLS, I get a significant EFWAMB, similar to Baker and Wurgler (2002).
Any advice would be very much appreciated.
For research in the above area, one have to access to number of proxies used for the measure of relationship mentioned above. For the proxies DATA is needed which must be a reliable data. One information is Mix-Market, Can someone guide for any other source? Would it be paid source or free available?
Dear Research Gate community,
I am looking for capital structure data of listed firms in Bloomberg dataset. I could find data on SBF120 index but cannot get access to all firms’ information, probably because of my awkward use of Bloomberg. Any help/advice could be valuable.
To estimate the relationship between capital structure and performance variables I have selected three profitability ratios i.e. net profit margin, return on assets and return on capital employed, whereas for capital structure I am working on DE ratio.
I m working to fine the effects of capital structure on dividend policy but I have a question in my mind that what is the main relationship between capital structure and dividend policy? Give reasons.
I wanted to know how Governance risk originate.
I am recently confused as to what or where to classify Governance Risk.
As it does not deals with either the Capital structure (Financial risks) or operating structure (Business risk) of banks.
I need some argument and clarifications please.
I m using Pooled OLS type of Panel data. Panel data facilitates of cross sectional and time series data. I will collected five year data of Cement industry from Pakistan Stock Exchange to find the effectiveness of Capital Structure and Corporate Governance on Dividend Policy. I will use Debt Ratio and Debt to Equity Ratio indicators for CS. And Managerial Ownership and Institutional Ownership indicator for CG. but my question is that before using Pooled OLS type of Panel data analysis, is it necessary to check the Fixed or random effect test???
Please answer me in a simple words.
Thanks in advance.
How can we measure corporate governance/ capital structure variables using Primary data ? Most of the available measures are based on the secondary data. Any suggestion or sending good papers in this regard will be highly appreciated. Thanks
EBITDA has been widely in finance as metric for both valuation and securities pricing analysis. Pundits for EBITDA argue that it is a sound measure of valuation as it clearly delineates profitability (devoid of impact of accounting policies, capital structure, and taxation regimes) and pure operating performance of a going concern. However some financial analyst loudly think that that EBITDA exaggerate cash flow because it does not take into consideration all the non-cash gains and expenses in addition to changes in working capital. As a result, using EBITDA as a metric for valuation is therefore "highly questionable". Thus, the question is: Is EBITDA an incredulous (dubious) valuation metric?
I am working on impact of Capital structure on the profitability of quoted firms. I am using 100 quoted firms and a duration of 10 years. i want to run the analysis using the Eviews software. Can someone show me how to run this analysis?
The first var affecting the second var and the total variances explained by the second var affecting the third var.
I am doing a research in which i have to separate our sample to financially constrained and non financially constrained firms. I plan to use "distance to default" as an indicator for measuring financial constraint. I highly appreciate if any one of you could help guide me how to estimate that indicator. Thank you so much.
I have got panel data of 200 companies for 10 years, i.e. 2000 observations. For example, if I collect macro-economic data of GDP (per year data) for 10 years it will be 10 observations . How do I regress my panel data over macro-economic data? Which econometric/statistical model will be used and how?
Board Independence. How can we measure the independence of a board. what variables should be considered and how can each be measured?
The impact of change in capital structure on stock prices.
I'm currently doing a study on the impact of capital change on stock price for South African companies listed on Johannesburg Stock Exchange. I would really appreciate if I can be advise about useful sources that will enable me to retrieve data.
We cannot use weighted average of financing cost of the two systems since capital structure can change any time in the future for on-going operating projects.
instead of dominant shareholder if there exists some other major shareholder in the same firm, can they effect the capital structure decision of the firm?
I want to examine the modern capital structure and the possible of reversal from performance to capital structure thereby test the efficiency-risk and franchise value hypotheses. Most of the techniques I have come across like the two stage least squares can not account for the dynamic heterogenous non stationary panel data.The same problem is applicable to GMM.These common estimators do not account for cross sectional dependence and the heterogenous nature of the cross sectional element. They assumed they are homogeneous although they account for endogeneity and simultaneity bias. But the nature of my samples are cross sections of firms that have different characteristics and they are of different age and size and they belong to different industry. The kind of series of the parameter is not likely to be stationary. I was thinking there could be causal panel method that can be use to estimate the causal relationship between capital structure and firm performance.
In “pecking order hypothesis”, the notion that firms has a preferred order of raising capital which starts from preferring internal financing and then debt financing and then equity as a last resort, is somehow weak.
In real life mostly firms will shop around for than one or two companion at the same time.
What do you think?
Could you please explain me shortly that can i take capital structure an independent variable?.if yes then how it effect the financial performance of a bank (Return on Assets,Return on Equity and Dividend payout?
Despite the tax-shield benefits of debt, some firms use zero level of debt in their capital structure. It appears that existing capital structure theories are unable to explain this zero debt puzzle, well. What theory explains why some firms use zero debt in their capital structure? Your contributions are welcome.
in my research, I am attempting to analyze the financial decision behavior of Shari’ah compliant companies compared to their non-compliant peers on selected countries, i.e. US, UK, Canada, Japan, Taiwan, S.Korea and India. I have chosen Dow Jones Islamic Market World Index as a source for the Shari’ah compliant companies, as it covers starting from 1996.
For me to conduct such a research it is utmost important to have the historical information of DJIM index with its constituent companies. In specific, this research requires the information about those companies which were included/excluded (joiners/leavers) into DJIM index between the years 1996-2014 (on annual basis).
Any suggestions from where to collect the data? I would appreciate it very much if anyone could share these data.
Note: within 'Thomson Datastream' any DJIMxx-Serie, e.g. DJIMUS$ provides the constituent list as of today ONLY.
Hope I could express well enough my request and hope for support.
Best regards and thank you in advance.
Some researchers suggest that it is necessary to conduct a panel unit root tests on a firm-level studies (e.g. capital structure study) that uses 9 years observation. For more than 10 years observation, it appears necessary to conduct panel unit root tests. However, the reasons for conducting panel unit root tests with 9 years or lesser observation are not very clear. Panel unit root tests are usually conducted on macro-level studies that use panel data method with longer time periods. Is it necessary to conduct a panel unit root tests on a firm-level study with 9 years or lesser observation? Your contribution are welcome.
We are doing research on capital structure. To the best of my knowledge, researchers usually applied panel with fixed of random effect. Few studies use SUR when they focused on macro variables. When should we use SUR in stead of panel with fixed or random effect? As the results I got quite different when running SUR. Many thanks
Unlike previous years, risks managers now are taking their position among the top management teams contributing to strategic planning relating to risk. The markets are now interconnected suggesting that risk can crop up suddenly from anywhere around the world and increase the pressure on risk managers. There is need to consider a variety of issues such as systematic risk, operating risk, financial risk, governance, and risk modeling techniques in particular, among others. How does ‘risk management issues’ change the way risk managers and researchers model risk today?
Finance and Economics research are mostly driven by advancement in econometrics. Some econometrics issues such as reverse causality between variables or endogenous variables (especially among finance and economics variables) make traditional Ordinary Least Squares (OLS) Method appears irrelevant or obsolete. But OLS seems applicable to investigate issues that are cross-sectional in nature. If research should be mainly driven by real issues, then OLS may still be relevant. Specifically, I have come across interesting research applying Ordinary Least Squares (OLS) method to investigate relationship between cultures and corporate decisions such as dividend policy and capital structure etc. What is the relevance of Ordinary Least Squares Method in Economics and Finance research today? Your contributions are welcome
The coefficient of lagged debt ratio has economic meaning in capital structure research that makes use of dynamic model specification. From the coefficient of the lagged debt variable, researchers usually calculate the speed of adjustment to the target debt (capital structure) level. But the coefficient of this lagged debt ratio is usually constrained between positive one and zero. Can the coefficient of lagged debt variable be negative in capital structure model? if yes, does it indicates negative adjustment to target debt (capital structure) level.
We find that many SMEs struggle to keep their cash flow smooth. They keep taking working capital loans but use it for long term investment. They find it difficult to promptly collect dues from debtors but are not able to purchase at long credit term.
I am currently working with an unbalanced panel data set in order to analyse capital structure decisions and determinants. I am using STATA to conduct the analysis. So far I have done the following steps:
1. Fixed-Effect Regression (xtreg)
Nevertheless, the results were mostly insignificant despite tons of empirical evidence in literature and a large data set under analysis.
2. Testing for Heterosced. (xttest3) and Serial Correlation (within the panels) (xtserial)
Result: Heterosced. And Serial Correl.
3. Winsorization oft he data set
4. Fixed-Effect Regression (xtreg) with Clustered Std. Errors.
Improved results, more significant coefficients.
5. GLS-Panel Regression (xtgls) with Hetero and AR(1)
Now, I am not sure which of the models, 4 or 5 I should use.
How can one choose between these two models?
Further, according to Petersen (2009) one should include a Time-Dummy to account for cross-sectional (between panel, over time) correlations. However, this destroys the results. In addition, I am not sure if cross-sect. Correlation exists as I was not able to test for it due to a highly unbalanced sample.
Do I have to include the Time-Dummies? Is there another way to test for cross sect correl instead of XTTEST2 or XTCSD, Pesaran?
Input would be highly appreciated!
Do you think that if a firm increases debt in its capital structure by issuing Islamic bond, it is going to affect the agency environment differently (compared to conventional bonds)?
I'm planning to conduct a comparative analysis about capital structure and employee productivity between China and Malaysia. Is there anyone who would be interested in working with me?