Adjustment of the WACC with Subsidized Debt in the Presence of Corporate Taxes: The Finite-Horizon Case

When discounting free-cash flows (FCF) at the Weighted Average Cost of Capital (WACC), we assume that the cost of debt is the market, unsubsidized rate. With debt at the market rate and perfect capital markets, debt only creates value in the presence of taxes through the tax shield. In some cases, the firm may be able to obtain a loan at a rate that is below the market rate. With subsidized debt and taxes, there would be a benefit to debt financing, and the unleveraged and leveraged values of the cash flows would differ. The benefit of lower tax savings are offset by the benefit of the subsidy. These two benefits have to be introduced explicitly. In this article, we present the necessary adjustments to the WACC and the cost of leveraged equity under the existence of subsidized debt and taxes in a multiple-period setting. We analyze the cases of the WACC applied to the FCF and the WACC applied to the capital-cash flows (CCF). We also utilize the Adjusted Present Value (APV) to consider both the tax savings and the subsidy. We show that all these different approaches give the same answer.

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International Real Estate Review

International Real Estate Review ◽

10.53383/100132 ◽

2011 ◽

Vol 14 (1) ◽

pp. 1-26

Author(s):

Jyh-Bang Jou ◽

◽

Tan (Charlene) Lee ◽

Keyword(s):

Real Estate ◽

Debt Financing ◽

Cost Of Debt ◽

Real Estate Investment ◽

Tax Rate ◽

Optimal Capital Structure ◽

Tax Shield ◽

Real Options Approach ◽

Optimal Capital ◽

The Cost

This article employs a real options approach to investigate the determinants of an optimal capital structure in real estate investment. An investor has the option to delay the purchase of an income-producing property because the investor incurs sunk transaction costs and receives stochastic rental income. At the date of purchase, the investor also chooses a loan-to-value ratio, which balances the tax shield benefit against the cost of debt financing resulting from a higher borrowing rate and a lower rental income. An increase in the sunk cost or the risk of investment will not affect the financing decision, but will delay investment. An increase in the income tax rate or a decrease in the depreciation allowance will encourage borrowing and delay investment, while an increase in the penalty from borrowing, a decrease in the investor's required rate of return, or worse real estate performance through borrowing, will discourage borrowing and delay investment.

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Extending the benefits of ESG disclosure: The effect on the cost of debt financing

Corporate Social Responsibility and Environmental Management ◽

10.1002/csr.2134 ◽

2021 ◽

Author(s):

Nicola Raimo ◽

Alessandra Caragnano ◽

Marianna Zito ◽

Filippo Vitolla ◽

Massimo Mariani

Keyword(s):

Debt Financing ◽

Cost Of Debt ◽

The Cost

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A Scorecard to Detect Financial Leverage Profitability

International Journal of Business and Management ◽

10.5539/ijbm.v13n3p244 ◽

2018 ◽

Vol 13 (3) ◽

pp. 244

Author(s):

Laura Broccardo ◽

Luisa Tibiletti ◽

Pertti Vilpas

Keyword(s):

Net Present Value ◽

Economic Value ◽

Weighted Average ◽

Cost Of Debt ◽

Corporate Management ◽

External Financing ◽

Present Value ◽

Financial Decisions ◽

Proposed Model ◽

The Cost

This study investigates how balancing internal and external financing sources can create economic value. We set a financial scorecard, consisting of the Cost of Debt (COD), Return on Investment (ROI), and the Cost of Equity (COE). We show that COE should be a cap for COD and a floor for ROI in order to increase the Net Present Value at Weighted Average Cost of Capital and the Adjusted Present Value of the levered investment. However, leverage should be carefully monitored if COD and ROI go off the grid. Situations where leverage has the opposite effect on value creation and the Equity Internal Rate of Return are also discussed. Illustrative examples are given. The proposed model aims to help corporate management in financial decisions.

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Turning Around Distressed Project Finance Assets in India: What More Needs to Be Done?

The Journal of Structured Finance ◽

10.3905/jsf.2018.1.068 ◽

2018 ◽

Keyword(s):

Cash Flows ◽

Project Finance ◽

Cost Of Debt ◽

Risk Allocation ◽

Debt Overhang ◽

Balance Sheets ◽

Infrastructure Project ◽

Bankruptcy Code ◽

The Cost ◽

Future Cash Flows

With the Insolvency and Bankruptcy Code firmly in place, India’s distressed project finance assets are turning out to be attractive to institutional investors. Project finance assets need asset-and deal-specific financing solutions in order to achieve successful turnarounds. The turnaround solution must ensure optimum risk allocation and mitigation leading to the buildup of future cash flows. This will, in turn, lead to deleveraging of stressed balance sheets. The authors present a conceptual model and argue that even now the political and regulatory risks for infrastructure project loans in India have not been completely mitigated. This has resulted in a situation of a debt overhang, wherein even economically viable projects may not attract fresh funding. To address this, the article suggests the possible use of priority funding structures, where existing lenders cede charge of the assets in favor of a new lender as a way to reduce the cost of debt and unlock shareholder value. This solution will also ensure that the restructuring package is properly priced (from the project finance lender’s perspective), resulting in the efficiency and viability of the restructured asset.

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Does opening high-speed railways affect the cost of debt financing? A quasi-natural experiment

China Finance Review International ◽

10.1108/cfri-06-2019-0083 ◽

2020 ◽

Vol 10 (4) ◽

pp. 473-496

Author(s):

Hongling Guo ◽

Keping Wu

Keyword(s):

High Speed ◽

Geographical Location ◽

Debt Financing ◽

Cost Of Debt ◽

High Speed Railway ◽

Content Type ◽

Financing Cost ◽

Debt Market ◽

The Cost ◽

The Impact

PurposeThis study aims to investigate how opening high-speed railways affects the cost of debt financing based on China's background.Design/methodology/approachUsing panel data on Chinese listed firms from 2008 to 2017, this study constructs a quasi-natural experiment and adopts a difference-in-difference model with multiple time periods to empirically examine the relation between the high-speed railway openings and debt financing cost.FindingsOur results show that opening high-speed railways reduces the cost of debt financing, and this negative correlation is more significant in non-state firms, firms with weaker internal control, and firms that hire non-Big Four auditors. Besides, we explore the impact mechanisms and find that opening high-speed railways improves analyst attention, institutional investor participation, and information disclosure quality, which in turn lowers the cost of debt financing.Research limitations/implicationsThe results imply that the opening of high-speed railways helps to alleviate the information asymmetry and adverse selection between firms and creditors and ultimately reduces the cost of corporate debt financing.Practical implicationsThis paper can inform firms and stakeholders about the impact of opening high-speed railways on debt financing cost: it improves the information environment, reduces the geographical location restrictions of debt financing, ensures the reasonable pricing of corporate debt, and thus promotes the healthy and sound development of the debt market.Originality/valueThis paper provides theoretical support and empirical evidence for the impact of infrastructure construction on the information environment of the debt market in China, which enriches the research on the “high-speed railway economy.” In addition, as an exogenous event, the opening of high-speed railways instantly shortens the time distance between firms and external stakeholders, which gives us a natural environment to conduct empirical research, thus providing a new perspective for financial research on firms' geographical location.

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Market value calculation and the solution of circularity between value and the weighted average cost of capital WACC

RAM Revista de Administração Mackenzie ◽

10.1590/s1678-69712009000600007 ◽

2009 ◽

Vol 10 (6) ◽

pp. 101-131 ◽

Cited By ~ 10

Author(s):

Ignacio Vélez-Pareja ◽

Joseph Tham

Keyword(s):

Average Cost ◽

Cost Of Capital ◽

Weighted Average ◽

Cost Of Debt ◽

Cost Of Equity ◽

Tax Rate ◽

Market Values ◽

Equity Cost ◽

Tax Payments ◽

The Cost

Most finance textbooks present the Weighted Average Cost of Capital (WACC) calculation as: WACC = Kd×(1-T)×D% + Ke×E%, where Kd is the cost of debt before taxes, T is the tax rate, D% is the percentage of debt on total value, Ke is the cost of equity and E% is the percentage of equity on total value. All of them precise (but not with enough emphasis) that the values to calculate D% y E% are market values. Although they devote special space and thought to calculate Kd and Ke, little effort is made to the correct calculation of market values. This means that there are several points that are not sufficiently dealt with: Market values, location in time, occurrence of tax payments, WACC changes in time and the circularity in calculating WACC. The purpose of this note is to clear up these ideas, solve the circularity problem and emphasize in some ideas that usually are looked over. Also, some suggestions are presented on how to calculate, or estimate, the equity cost of capital.

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ESG Scores and the Credit Market

Sustainability ◽

10.3390/su12083456 ◽

2020 ◽

Vol 12 (8) ◽

pp. 3456 ◽

Cited By ~ 4

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.

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