scholarly journals The Effect of Lease Accounting on Credit Rating and Cost of Debt: Evidence from Firms in Korea

2018 ◽  
Vol 7 (9) ◽  
pp. 154
Author(s):  
Younghee Park ◽  
Kyunga Na
Keyword(s):  
Regression Model ◽  
Credit Rating ◽  
Credit Ratings ◽  
Sample Selection ◽  
Least Square ◽  
Cost Of Debt ◽  
Probit Regression ◽  
Explanatory Variables ◽  
Operating Leases ◽  
The Cost

This study examines the effect of capital lease and operating lease options in accounting on credit ratings and the cost of debt using data for 13 years (2001 to 2013) on 6133 listed and unlisted domestic firms in Korea that recognize leases on financial statements. We use the Heckman two-stage model to control for sample selection bias from lease selection. The first stage is the probit regression in which the dependent variable is a dummy variable on the lease selection and the explanatory variables are factors known to affect lease selection. The second stage consists of the ordered probit regression model and the ordinary least square regression model where the dependent variables are credit rating and cost of debt, respectively. The results show that lease selection does not significantly affect corporate credit ratings—however, in terms of the cost of debt, enterprises that adopt operating leases spend considerably less than firms that engage in capital leases. Further analysis suggests that the results for credit ratings do not differ by listing status. However, the cost of debt for listed companies does not seem to differ by lease selection, while unlisted firms see a sharp decline in their cost of debt when they choose operating leases over capital leases.

scholarly journals ESG Scores and the Credit Market

2020 ◽  
Vol 12 (8) ◽  
pp. 3456 ◽  
Author(s):  
Ga-Young Jang ◽  
Hyoung-Goo Kang ◽  
Ju-Yeong Lee ◽  
Kyounghun Bae
Keyword(s):  
Small Firms ◽  
Credit Rating ◽  
Credit Ratings ◽  
Debt Financing ◽  
Corporate Bond ◽  
Cost Of Debt ◽  
Rating Agencies ◽  
Bond Returns ◽  
The Cost ◽  
The Relationship

This study analyzes the relationship between Environmental, Social and Governance (ESG) scores and bond returns using the corporate bond data in Korea during the period of 2010 to 2015. We find that ESG scores include valuable information about the downside risk of firms. This effect is particularly salient for the firms with high information asymmetry such as small firms. Interestingly, of the three ESG criteria, only environmental scores show a significant impact on bond returns when interacted with the firm size, suggesting that high environmental scores lower the cost of debt financing for small firms. Finally, ESG is complementary to credit ratings in assessing credit quality as credit ratings cannot explain away ESG effects in predicting future bond returns. This result suggests that credit rating agencies should either integrate ESG scores into their current rating process or produce separate ESG scores which bond investors integrate with the existing credit ratings by themselves.

Fiscal transparency and the cost of sovereign debt

2016 ◽  
Vol 83 (1) ◽  
pp. 106-128 ◽  
Author(s):  
Francisco Bastida ◽  
María-Dolores Guillamón ◽  
Bernardino Benito
Keyword(s):  
Interest Rates ◽  
Public Management ◽  
Sovereign Debt ◽  
Credit Rating ◽  
Credit Ratings ◽  
Political Trust ◽  
Cost Of Debt ◽  
Budget Deficits ◽  
Fiscal Transparency ◽  
The Cost

This article analyses the factors that seem to play an important role in determining the cost of sovereign debt. Specifically, we evaluate to what extent transparency, the level of corruption, citizens’ trust in politicians and credit ratings affect interest rates. For that purpose, we create a transparency index matching the 2007 Organisation for Economic Co-operation and Development/World Bank Budgeting Database items with the Organisation for Economic Co-operation and Development Best Practices for Budget Transparency sections. We also check our assumptions with the International Budget Partnership’s Open Budget Index and with a non-linear transformation of our index. Furthermore, we use several control variables for a sample of 103 countries in the year 2008. Our results show that better fiscal transparency, political trust and credit ratings are connected with a lower cost of sovereign debt. Finally, as expected, higher corruption, budget deficits, current account deficits and unemployment make sovereign interest rates increase. Points for practitioners The key implications for professionals working in public management and administration are twofold. First, despite the criticism raised by credit ratings, it is clear that poorer ratings are connected with higher financing costs for governments. Therefore, governments should enhance those indicators that impact the credit rating of their sovereign debt. Second, governments should seek to be more transparent, since transparency reduces uncertainty about the degree of cheating, improves decision-making and therefore decreases the cost of debt. Transparency reduces information asymmetries between governments and financial markets, which, in turn, diminishes the spread requested by investors.

scholarly journals The Linkage between ESG Performance and Credit Ratings: A Firm-Level Perspective Analysis

2017 ◽  
Vol 12 (9) ◽  
pp. 53 ◽  
Author(s):  
Alain Devalle ◽  
Simona Fiandrino ◽  
Valter Cantino
Keyword(s):  
Credit Rating ◽  
Credit Ratings ◽  
Cash Flows ◽  
Cost Of Debt ◽  
Firm Level ◽  
Public Firms ◽  
Clear Cut ◽  
Final Sample ◽  
Decision Making Processes ◽  
The Cost

This paper investigates the effect of environmental, social, and governance (ESG) performance on credit ratings. We argue that ESG factors should be considered in the credit analysis and the creditworthiness evaluation of borrowers because they affect borrowers’ cash flows and the likelihood of default on their debt obligations. Consequently, we develop our research by firstly reviewing the literature regarding ESG commitments within financial decision-making processes and then addressing the relation between ESG performance and the cost of debt financing. We reveal no unanimous results and no clear-cut boundaries on this matter yet. Secondly, to disentangle this relationship, which is not well defined by scholars, we empirically investigate the nexus between ESG performance and credit rating issues on a sample of 56 Italian and Spanish public firms for which ESG performance in 2015 was achieved. Our final sample includes 15 variables for 56 observations: 840 items are under analysis. Our findings suggest that ESG performance, especially concerning social and governance metrics, meaningfully affects credit ratings. We do not sort out significant results referring to environmental scores, so further research is needed to investigate this ever-growing matter and strengthen this considerable nexus.

Managerial Ability, Credit Ratings, and the Cost of Debt

2014 ◽  
Author(s):  
Kimberly Rodgers Cornaggia ◽  
Gopal V. Krishnan ◽  
Changjiang (John) Wang
Keyword(s):  
Credit Ratings ◽  
Cost Of Debt ◽  
Managerial Ability ◽  
The Cost

scholarly journals EFFECT OF CREDIT RATING ON CAPITAL STRUCTURE: A STUDY ON NON-FINANCIAL FIRMS IN PAKISTAN

2012 ◽  
Vol 12 (1) ◽  
Author(s):  
Keyword(s):  
Capital Structure ◽  
Credit Rating ◽  
Stock Exchange ◽  
Credit Ratings ◽  
Least Square ◽  
Statistical Tool ◽  
Ordinary Least Square ◽  
Optimal Capital Structure ◽  
Financial Firms ◽  
The Impact

Purpose- Aim of this study was to investigate whether the credit rating is an important determinant other than the firm's characteristic to obtain optimal capital structure focusing on the research hypothesis that the firms with higher credit along with the other factors (FTOA, ROA and Size) tend to have more debt in their capital structure of firms rated by P?CR? and Karachi Stock Exchange (KSE). Methodology/Sample- For this research, sample size of 48 observations (3 years data of 16 firms) was taken on the basis of convenience sampling. Results obtained by using Ordinary Least Square Model (OLS) as statistical tool to test the hypothesis Findings- Analysis clearly suggested that credit ratings do have an impact on firm's capital structure. It was concluded that firms with higher credit ratings along with other factors (FTOA, ROA and Size) do not tend to have more debt in their capital structure. Implications- Outcomes of this research might help investors, debtors and other stakeholders of the firms (rated by PACRA) to understand the impact of credit rating on firm's debt ratio and the overall dynamics and mechanism of capital structure.

scholarly journals Forecasting Credit Ratings of EU Banks

2020 ◽  
Vol 8 (3) ◽  
pp. 49
Author(s):  
Vasilios Plakandaras ◽  
Periklis Gogas ◽  
Theophilos Papadimitriou ◽  
Efterpi Doumpa ◽  
Maria Stefanidou
Keyword(s):  
Credit Rating ◽  
Credit Ratings ◽  
Support Vector ◽  
Credit Rating Agencies ◽  
Selection Scheme ◽  
Explanatory Variables ◽  
Rating Agencies ◽  
Financial Variables ◽  
Forecasting Models ◽  
Banking Institutions

The aim of this study is to forecast credit ratings of E.U. banking institutions, as dictated by Credit Rating Agencies (CRAs). To do so, we developed alternative forecasting models that determine the non-disclosed criteria used in rating. We compiled a sample of 112 E.U. banking institutions, including their Fitch assigned ratings for 2017 and the publicly available information from their corresponding financial statements spanning the period 2013 to 2016, that lead to the corresponding ratings. Our assessment is based on identifying the financial variables that are relevant to forecasting the ratings and the rating methodology used. In the empirical section, we employed a vigorous variable selection scheme prior to training both Probit and Support Vector Machines (SVM) models, given that the latter originates from the area of machine learning and is gaining popularity among economists and CRAs. Our results show that the most accurate, in terms of in-sample forecasting, is an SVM model coupled with the nonlinear RBF kernel that identifies correctly 91.07% of the banks’ ratings, using only 8 explanatory variables. Our findings suggest that a forecasting model based solely on publicly available financial information can adhere closely to the official ratings produced by Fitch. This provides evidence that the actual assessment procedures of the Credit Rating Agencies can be fairly accurately proxied by forecasting models based on freely available data and information on undisclosed information is of lower importance.

scholarly journals Forecasting bank credit ratings

2014 ◽  
Vol 15 (2) ◽  
pp. 195-209 ◽  
Author(s):  
Periklis Gogas ◽  
Theophilos Papadimitriou ◽  
Anna Agrapetidou
Keyword(s):  
Credit Ratings ◽  
Financial Statements ◽  
Bank Credit ◽  
Probit Regression ◽  
Content Type ◽  
Explanatory Variables ◽  
Financial Variables ◽  
Annual Frequency ◽  
Available Information

Purpose – This study aims to present an empirical model designed to forecast bank credit ratings using only quantitative and publicly available information from their financial statements. For this reason, the authors use the long-term ratings provided by Fitch in 2012. The sample consists of 92 US banks and publicly available information in annual frequency from their financial statements from 2008 to 2011. Design/methodology/approach – First, in the effort to select the most informative regressors from a long list of financial variables and ratios, the authors use stepwise least squares and select several alternative sets of variables. Then, these sets of variables are used in an ordered probit regression setting to forecast the long-term credit ratings. Findings – Under this scheme, the forecasting accuracy of the best model reaches 83.70 percent when nine explanatory variables are used. Originality/value – The results indicate that bank credit ratings largely rely on historical data making them respond sluggishly and after any financial problems are already known to the public.

scholarly journals Solving Multicollinearity Problem in Linear Regression Model: The Review Suggests New Idea of Partitioning and Extraction of the Explanatory Variables

2021 ◽  
Vol 2 (1) ◽  
pp. 12-20
Author(s):  
Kayode Ayinde, Olusegun O. Alabi ◽  
Ugochinyere Ihuoma Nwosu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Real Data ◽  
Least Square ◽  
Model Parameters ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Wide Range ◽  
High Level

Multicollinearity has remained a major problem in regression analysis and should be sustainably addressed. Problems associated with multicollinearity are worse when it occurs at high level among regressors. This review revealed that studies on the subject have focused on developing estimators regardless of effect of differences in levels of multicollinearity among regressors. Studies have considered single-estimator and combined-estimator approaches without sustainable solution to multicollinearity problems. The possible influence of partitioning the regressors according to multicollinearity levels and extracting from each group to develop estimators that will estimate the parameters of a linear regression model when multicollinearity occurs is a new econometrics idea and therefore requires attention. The results of new studies should be compared with existing methods namely principal components estimator, partial least squares estimator, ridge regression estimator and the ordinary least square estimators using wide range of criteria by ranking their performances at each level of multicollinearity parameter and sample size. Based on a recent clue in literature, it is possible to develop innovative estimator that will sustainably solve the problem of multicollinearity through partitioning and extraction of explanatory variables approaches and identify situations where the innovative estimator will produce most efficient result of the model parameters. The new estimator should be applied to real data and popularized for use.

scholarly journals PENGARUH KUALITAS AUDIT DAN KEPEMILIKAN INSTITUSIONAL TERHADAP COST OF DEBT (Studi Empiris Pada Perusahaan Manufaktur Yang Terdaftar Di BEI Periode 2012-2015)

2019 ◽  
Vol 7 (1) ◽  
pp. 1-9
Author(s):  
Anton Robiansyah ◽  
Dwi Novita ◽  
Furqonti Ranidiah
Keyword(s):  
Audit Quality ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Institutional Ownership ◽  
Least Square ◽  
Cost Of Debt ◽  
Analysis Tool ◽  
Manufacturing Companies ◽  
Significance Level ◽  
The Cost

Anton Robiansyah, Dwi Novita, Furqonti Ranidiah; This study aims to analyze the effect of audit quality and institutional ownership on the cost of debt. The population in this study are all manufacturing companies listed on the Stock Exchange in 2011-2014. The type of research used in this study is empirical research. The sampling technique used was purposive sample and selected 72 unit analysis companies. The data analysis tool in this test uses OLS (ordinary least square), which wants to see the effect of audit quality and institutional ownership on the cost of debt.Based on the results of this study indicate that audit quality has a negative effect on the cost of debt with a significance level of 0.014 which means that the company that chooses the BIG4 KAP has a good reputation and this is seen as a positive thing for the creditor. Whereas institutional ownership does not affect the cost of debt with a significance level of 0.847 indicating that the presence or absence of institutional ownership of companies - companies in Indonesia does not affect the institutional ownership relationship and the cost of debt.

scholarly journals The Effect Of IFRS Non-Audit Consulting Services On Cost Of Debt: Evidence From Korea

2015 ◽  
Vol 31 (5) ◽  
pp. 1889
Author(s):  
Seung Uk Choi ◽  
Woo Jae Lee
Keyword(s):  
Interest Rate ◽  
Financial Reporting ◽  
Credit Rating ◽  
Financial Statements ◽  
Cost Of Debt ◽  
Reporting Standards ◽  
Listed Firms ◽  
Financial Reporting Standards ◽  
Consulting Services ◽  
The Cost

Korean listed firms have been required to disclose their financial statements based on the International Financial Reporting Standards (IFRS) since 2011. Using pre- and post-IFRS reporting periods, we investigate the relation between IFRS non-audit consulting services provided by incumbent auditor and the cost of debt of its client for firms in the Korean Stock Market. We find evidence that IFRS non-audit consulting services are related to the decrease in cost of debt only during the post-IFRS period. In particular, receiving non-audit consulting services is positively associated with a clients bond credit rating and negatively associated with interest rate. The result generally holds when we use alternative proxies of IFRS non-audit consulting services. Finally, our results are robust to potential endogeneity issues in selecting non-audit services.

Sign in / Sign up

Export Citation Format

Share Document