Indirect Costs of Financial Distress* Review of Finance

Lower quality management and corporate governance lead to a higher probability of financial distress. The results are also consistent with the notion that the negative effect for suppliers of specific goods is mitigated by the fact that clients may build up inventory of the supplier’s goods for precautionary reasons. We use real estate prices as financial shocks, which should be valid regardless of whether the firm raises unsecured or secured debt following a rise in the value of real estate assets. However, the effect of a drop in the value of real estate assets could be more pronounced if the firm holds more secured debt. In Panel B, we assume that firms file for bankruptcy and cannot continue to operate following distress. In this case, the expected value of indirect costs of distress at time t is given by (1-pq)t-1pM⁠.

The findings of this study provide more insight to corporate managers and investors about the association between firm-specific financial characteristics and IFDC concerning Pakistani firms. Furthermore, this study contributes to the existing literature by adding new evidence from developing countries such as Pakistan which are helpful for regulatory bodies and policymakers in the formulation of long-term strategies to manage the financial distress costs. The findings of this study show that the average size of IFDC for the sample observations is 6.70%.

Forecasting default with the Merton distance to default model

Supplementary Appendix Table IA.18 reports the results when we exclude the sample industries with high exposure to RE shocks based on the RE variable. In the regressions in Columns (1)–(5), we exclude energy, utilities, telecoms, shops, and manufacturing, respectively. The results are consistent with our baseline results in Table IV with point estimates between –14% and –10.8%.

We find that the magnitude of the triple interaction coefficient is larger than in Table IV, and equals –21%. Some firms will be able to continue operating after suffering distress due to RE shocks, and others will not. Therefore, the costs of distress in the first case provide an upper bound of the total indirect costs of distress, and the costs in the second case provide a lower bound. According to Modigliani and Miller’s theory, as a company’s capital structure cost of financial distress is composed of more and more debt a point is reached where equity cost and debt cost increase beyond that predicted by pure arbitrage of the appropriate cost of capital for the business. As a first step, we will conduct an analysis of the process of financial distress of companies to better understand the path of failure under the financial, economic and legal perspectives. Then, we will examine the costs of the financial distress and their impact on companies.

Taken together, the results in this section mitigate the concern that our results are mostly driven by omitted economic conditions at the location of the supplier. This extra cost is described as the cost of financial distress; potentially the cost of dealing with a near-insolvency situation. However, if the company faces financial problems that are not temporary it can affect the company’s terminal value. Because non-temporary financial distress is less common, it can be hard for analysts to evaluate a company, since it’s significantly more difficult to understand how distress will impact future cash flows. They may also find their market value and stock price dropping significantly, customers cutting back orders, and corporate raiders circling.

Bankruptcy costs

We use the market value of RE assets in 1993 multiplied by the change in the HP Index from 1993 to a given year following Chaney, Sraer, and Thesmar (2012). The market value of RE assets in 1993 is obtained by inflating the historical cost of a firm’s RE assets from the year of acquisition using the HP Index. The average age of a firm’s RE assets in 1993 is given by the value of accumulated depreciation divided by the historical cost multiplied by a depreciable life of 40 years.

• However, when we allow firms to experience even modest (e.g., 1–2% annualized) financial distress costs prior to bankruptcy, the cumulative present value of such costs can easily offset the tax benefits.
• As a first step, we will conduct an analysis of the process of financial distress of companies to better understand the path of failure under the financial, economic and legal perspectives.
• In the regression for Column (4), we use an industry-adjusted measure of RE assets (Industry RE).
• Taken together, the results in this section mitigate the concern that our results are mostly driven by omitted economic conditions at the location of the supplier.
• The authors also find no convincing evidence that either the firm’s growth or financial health could influence or moderate this interrelationship.

Our results suggest that clients reduce their exposure to suppliers in financial distress. In Table XII, Columns (1) and (2) present results for the sample firms split into low and high trade credit provision in the firm’s industry according to the median value of the distribution of the average ratio of accounts receivable to sales by industry. We find that the triple interaction coefficient is similar in both groups, although the coefficient is more precisely estimated in the low receivable group.

Data Availability

However, when we allow firms to experience even modest (e.g., 1–2% annualized) financial distress costs prior to bankruptcy, the cumulative present value of such costs can easily offset the tax benefits. The costs of financial distress are an important deviation from the Modigliani and Miller (1958) framework with no frictions. We provide evidence that the indirect costs of financial distress are sizable and thus should be an important consideration of capital structure decisions. Our baseline estimate of the expected indirect costs of distress lies between 3.1% and 3.6% of total firm value, in present value terms, and can go up to 20% in a downturn. These costs are additional to the direct costs of default, and only consider RE shocks as a trigger of financial distress.

In the regression for Column (6), ΔHP is a dummy variable that takes a value of one if the change between years t – 2 and t – 1 in HP is negative, and is zero otherwise. The dependent variable in all specifications is the percentage change in the supplier’s sales to each client (⁠Δln⁡Salesijt)⁠. Overall, our results suggest that a supplier’s financial distress driven by local RE prices can generate significant costs as measured by lost sales. We conclude that the indirect costs of financial distress are sufficiently sizable to be an important consideration in capital structure decisions.

Does firm value move too much to be justified by subsequent changes in cash flow?

Our mission is to produce effective learning materials and to present them in a way that is suitable for busy professionals to consume in their pockets of time. PrepNuggets is a creator of CFA® program study materials to aid candidates who are looking for more concise materials for their exam preparation. The coefficients in Table V correspond to the specification in Column (2) of Table IV.

Supplementary Appendix Table IA.3 shows the results of our baseline regression when we cluster standard errors at the county level (Panel A) and double cluster at the client and supplier levels (Panel B). Standard errors are similar to those in baseline regressions when we cluster at the county level and smaller in all specifications when we double cluster at the client and supplier levels. The mechanism that we explore is more likely when there are large negative changes in RE prices such as those that took place during the 2007–09 financial crisis and the 2007–11 RE crisis.

Empirical evidence of risk shifting in financially distressed firms

Across industries, CFD are driven primarily by the potential for debt overhang problems and distressed asset fire-sales. There is considerable empirical support for the hypothesis that firms choose a leverage ratio based on the trade-off between tax benefits and CFD. The results do not confirm the under-leverage puzzle for firms with publicly traded debt.

The coefficients estimated in Table IV suggest that shocks to RE prices can lead to a baseline 13% reduction in sales of distressed firms, and to larger reductions for firms with low market share, standardized products, or selling durable goods. This average effect would depend on how much of the reduction in sales represents a drop in quantities versus a drop in prices, as well as the supplier’s fixed and variable cost structure, which for simplicity we assume to be proportional. Is this effect large enough to help explain the seemingly low leverage observed among public firms? I estimate the market’s opinion of ex-ante costs of financial distress (CFD) from a structurally motivated model of the industry, using a panel dataset of monthly market values of debt and equity for 269 firms in 23 industries between 1994 and 2004. The market expects costs of financial distress of 5% of firm value for observed leverage ratios.

On the existence of an optimal capital structure: theory and evidence

We conjecture that precautionary behavior with respect to important suppliers might be more pronounced for the ones located further away. Distant suppliers are less likely to be part of a local production network; thus, their clients are more likely to have a transactional relationship and low switching costs. As such, we further split the samples of low and high supplier weight into client–supplier pairs in which the geographical distance between supplier and client is below the median (Columns (3) and (5)) and above the median (Columns (4) and (6)). Column (4) shows that the negative effect of financial distress when the client is more dependent on one supplier is driven by client–suppliers located further away from each other (high distance sample). We conclude that clients want to hedge against a potential disruption in their supply chain by reducing their dependence on financially distressed suppliers that are further away.

First, we test the prediction that the negative effect of a supplier’s financial distress on a client’s purchases should be more pronounced when the supplier has a lower market share (calculated at the three-digit SIC code level). Suppliers with high market share are likely to have more market power and bargaining power, which could allow them to impose higher switching costs on their clients (Klemperer, 1987). Therefore, suppliers with a lower market share might suffer a more pronounced drop in a client’s purchases relative to suppliers with higher market share.