Master thesis
Firm performance, leverage and corporate restructuring in
the European automotive industry during the financial crisis
University of Groningen
International Business & Management Specialization International Financial Management
University of Uppsala
Economics & Business
Date 1 June 2011
Student Miha Sebenik (s1940333)
Keywords
Abstract
Table of content
1. Introduction ... 1
2. Literature review and hypotheses... 5
2.1. Leverage and firm performance ... 5
2.2. Leverage and performance in cyclical economic environment ... 10
2.3. Corporate restructuring... 11
3. Data and methodology ... 15
3.1. Measuring firm performance ... 15
3.2. Data selection ... 17
3.3. Sample description ... 18
3.4. Empirical model ... 19
4. Results and discussion ... 23
4.1. Leverage and firm performance ... 23
4.2. Corporate restructuring... 25
4.3. Discussion ... 30
5. Conclusion ... 35
Table of figures
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1. Introduction
“It is not the strongest of the species that survives, nor the most intelligent. It is the one that is the most adaptable to change.”
Charles Darwin
Businesses worldwide perceive financing as a priority to start and maintain a desired business model. Firm’s capital basically represents funds provided by owners or lenders to purchase goods and transform them into finished products and services, which are later offered to potential customers. Modigliani and Miller (1958) explain that the capital of the company consists of equity and debt. Capital structure considerably varies across industries, and many studies exist which show significant relationships between capital structure and firm value. Modern capital structure theory began in 1958, when Modigliani and Miller published an article, which has been perceived as the most influential financial article ever written. At first they show that the choice between debt and equity does not influence the firm’s value. This finding holds if there are no corporate taxes, no brokerage costs, no bankruptcy costs and when all information is publicly available. In that case the capital structure does not matter and does not have any implication on the total firm value. However, the situation with no taxes and costs of risk does not exist in a real world and therefore Modigliani and Miller (1963) concluded that in presence of corporate taxation, higher proportion of debt leads to a higher firm value due to tax deductible interest payments. Following this theory, firms should finance exclusively with debt if they want to maximize their value. Nevertheless, as already mentioned, companies across and even within the same industries have different capital structures. The question, which occupies many researchers, is whether firms change capital structure to achieve better performance.
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efficient and therefore performs better comparing to its peer companies. These results confirm the agency costs theory and clearly show that increased debt lowers the agency costs.
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organizational flexibility, which helps to quickly adapt and respond to changed economic conditions, have the opportunity to remain or even improve their performance. The research reveals that managers see the capital agenda as heart of all strategic boardroom and management decisions. More successful companies have the proactive portfolio management and try to add flexibility into capital structure.
How can a company achieve desired flexibility and prompt adjustment? The answer lies in corporate restructuring. According to Renneboog and Szilagyi (2006), corporate restructuring is encouraged by deregulating markets, financial crisis, decreased trustworthiness and intense competition for capital supply. Corporate restructuring can combine a broad range of activities such as negotiating debt, selling business lines, mergers and acquisitions, changing internal organizations and reducing costs to adapt to current economic conditions. All these transactions have direct or indirect influence on firm performance. Jensen (1989) reveals that companies with higher leverage are forced to revalue operations and business activities more frequently and therefore use more corporate restructuring. Additionally, Ofek (1993) explains that high debt forces firms to restructure and refocus, because a slight decline in firm performance can seriously endanger ability to repay the outstanding debt.
The question that remains and has not been yet answered is whether leverage significantly influences the firm performance in time of crisis. If a high leverage ratio triggers restructuring activity and if restructuring actions significantly improve firm performance, I claim that a firm can “immunize” itself from a global crisis with a proper capital structure. Can a firm be successful if it promptly adjusts to new economic conditions by using corporate restructuring? Addressing the obscurity mentioned above, I state my research question as follows:
Does a high-leverage in the time prior to the recession cause frequent restructuring activity and therefore provoke a better firm performance during the global recession?
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Additionally, my study will show that managers need to promptly adjust to changes by using corporate restructuring - thus these financial and operational decisions can have a major impact on firm performance and therefore competitive advantage. Managers should consider carefully how to finance during expansion as well as contraction. My research will show the effect of capital structure choice on various restructuring actions and to firm performance during the time of crisis, which is still a more or less under researched topic.
2. Literature review and hypotheses
2.1. Leverage and firm performanceThe theory of maximizing the shareholder wealth defines the optimal capital structure as the structure that produces the highest firm value (Ross et al., 2008). On the other hand, the theory of Modigliani and Miller (1958) has a convincing argument that changing the capital structure has no influence on the firm value. Adding debt to existing capital structure will force the remaining equity to become riskier and consequently more expensive. However, in the presence of corporate taxes, the firm value is positively correlated to debt, because interest payments reduce the taxable basis and consequently the company lowers its tax liability (Modigliani and Miller, 1963). The modern finance theory should be able to explain why tax savings, generated by debt, do not lead companies to finance themselves exclusively with debt. Furthermore, the theory should explain why some companies borrow more than other, why some take more short-term and some more long-term debt. A variety of ideas have been developed to answer these questions. Following the findings of Modigliani and Miller, Myers (1977) passes three important implications. Firstly, the tax advantage can be offset due to personal taxes, secondly the bankruptcy costs can discourage borrowing and lastly he shows that corporate borrowing is influenced by asset characteristics.
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and it describes in detail the conflict of interests between managers and shareholders. The founders of the agency cost theory are Jensen and Meckling (1976). They were the first who illustrated the relationship between principals and agents. They define the agency relationship as a contract where one person (the principal, owner) engages the other person (the agent, manager) to perform service in his/her behalf, and where the agents have the authority to delegate several decisions. Jensen and Meckling reveal that the agent will not always act in the best interest of the principal, if both parties are utility maximizers. Managers, acting a role of agents, tend to maximize their own utility rather than to maximize the firm value. By following their own preferences, they exert insufficient work effort, choose false risk policies and extremely indulge in perquisites. In order to minimize the agent’s self-utilization, Jensen and Meckling suggest that the agent and the principal engage in specific actions. They name these actions as positive monitoring and bonding costs. Still, a residual loss remains between the agent’s decision and the decision that would maximize the welfare of the principal. The sum of monitoring, bonding costs and residual loss is according to Jensen and Meckling perceived as agency costs. Agency costs reduce the firm value and harm the firm’s competitive position. Since the paper of Jensen and Meckling, a vast literature on agency costs and capital structure theory has developed (see Grossman and Hart 1982; Williams, 1987; Jensen 1989; Harris and Raviv, 1991; Myers 2001).
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leveraged special dividend is a transaction that increases the company’s debt and pays to shareholders a huge cash dividend. Prior to the transaction, the company had a substantial free cash flow and the firm performance valued by the stock returns was very low. The result of a new capital structure was improved internal control of the company, which created an environment to stimulate more competitive future. The company reported better performance on the short and on the long term.
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proportion of input-output. To calculate the firm efficiency, Färe and Grosskopf introduced the data envelopment analysis (DEA). DEA, according to Emrouznejad (2001), is a linear programming based technique for measuring the relative performance of organizational units, where the presence of multiple inputs and outputs makes comparison difficult. DEA estimates the empirical efficient frontier of used inputs and outputs, which represents the “best practice” frontier determined by several observations (Zhu, 2002). This “best practice” frontier shows the measure of relative efficiency of each target unit, which considers the proportion of used inputs and outputs of all observed units in the sample.
By using the firm efficiency both Berger and Bonaccorsi di Patti (2006) and Margaritis and Psillaki (2009) observed a positive relationship between leverage and firm performance. Berger and Bonaccorsi di Patti studied the connection between leverage and firm performance in the banking industry. They tested the agency cost hypothesis by regressing the firm efficiency to equity capital ratio. As a result, they come across significant results showing that a higher leverage increased the firm efficiency of observed banks in the sample. Similarly, Margaritis and Psillaki researched the influence of capital structure and equity ownership on firm efficiency. Their results overlap with prior findings, however they show that a significant positive relationship exists between the firm efficiency and a high leverage ratio in a sample of French manufacturing firms. Furthermore, they explain that a firm’s ability to achieve “best practice” efficiency comparing to its peer firms, is endangered in situations when a company invests in non-valuable projects, participate in uneconomic activities and is involved in several organizational inefficiencies. One of the reasons of participating in these resource misallocations is an agent-principal conflict. Due to agency costs, companies with similar technology can have completely different scores of efficiency. To conclude, it is believed that companies which minimize agency costs will be closer to their best practice frontier and therefore will be more efficient.
With support of the agency cost theory and the results of previous studies, my first hypothesis is stated as follows:
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2.2. Leverage and performance in cyclical economic environment
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seriously affect the company’s incentive (or ability) to compete, resulting in changed firm performance.
According to the theories above, how macroeconomic conditions force companies to adjust their capital structure in order to sustain performance, I state my second hypothesis:
Hypothesis 2: During recession times, firms with lower leverage have a significantly better performance.
2.3. Corporate restructuring
Changing economic conditions force companies to constantly value their core business and finance position, to be able to sustain performance and to stay competitive in a fierce environment. An economic downturn usually brings companies to experience poorer performance.
A reaction to worsening firm performance is corporate restructuring. Corporate restructuring is a complex and multidimensional activity, which can encompass a broad range of transactions including selling lines, mergers and acquisitions, changing the internal organization and changing the capital structure (Bowman & Singh, 1993). According to Renneboog and Szilagyi (2006), deregulating markets, financial crisis, decreased trustworthiness and intense competition for capital supply, are major incentives for a company to revalue its business and financial strategies. Restructuring activity is generally associated with three motivations, namely, to address poor performance, to exploit strategic opportunities and to correct valuation errors.
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real increases in operating efficiencies. Jensen is surprised by the results that the same leaders under various control policies can even double productivity and value of the firm. Jensen’s main conclusion is that leverage is important control policy, which prevents drastic decline in corporate performance. However, Jensen continues and states that a minor decline in firm performance can seriously endanger firm’s ability to repay its debt. Higher leverage plays a role of a control mechanism, which ensures that a firm will respond faster and more efficient to the slight decline of its performance. Companies with a higher leverage frequently revalue their core businesses and financial claims and thus quickly adapt to current economic situations. Jensen’s argument implies a positive relationship between leverage and corporate restructuring. Higher debt forces companies to constantly consider various corporate restructuring actions, due to higher bankruptcy risk. Even a slight decrease of firm performance can seriously endanger a firm’s ability to meet its financial obligations. Corporate restructuring is therefore a reaction to changing firm performance. From that argument, I conclude that corporate restructuring and firm’s performance are intertwined. The study of Bharma et al. (2008) stresses the importance of considering different actions of restructuring and its impact on the firm performance in cyclical macroeconomic conditions. It provides an explanation that leverage dynamics are asymmetric, since it is more difficult to restructure in time of a depression, because the restructuring activity in time of crisis is much more expensive. Therefore, the important implication is that companies need to assess their financial decisions carefully in boom as well as in contraction states. The results reveal that successful companies restructure frequently, while unsuccessful ones tend to delay their financial decisions. Restructuring activity indicates path dependence, because companies do not depend only on the current economic state, but also on the state of the previous restructuring activity. Following the findings of Jensen and Bharma et al., I conclude that successful companies are constantly assessing their financial position and are prone to frequent corporate restructuring. However, companies that constantly assess and restructure have according to Jensen significantly higher leverage compared to their peer companies. Inspired by above research findings, my next hypothesis is:
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Renneboog and Szilagyi (2006) examine the influence of corporate restructuring on bondholder’s wealth. They argue that corporate restructuring affects creditors through two main channels: operational performance and changes in capital structure. The literature mainly distinguishes between two types of restructuring: operational actions and financial actions (Ofek, 1993; Lai and Sudarsanam, 1997; Renneboog and Szilagyi, 2006). Operational actions are taken, when a company needs to increase its business efficiency and profitability. Operational restructuring mainly comprises of cost reductions, employee layoffs, asset restructuring and management replacements. Financial actions are taken when a company wants to raise cash to meet its financial commitments, to renegotiate debt to lower its current debt burden, to issue new equity to finance operations, or to reconfigure corporate strategy (Lai and Sudarsanam, 1997; Renneboog and Szilagyi, 2006). Financial restructuring is directly aimed at changing the capital structure and thus usually includes debt restructuring, equity issues and dividend cuts.
Ofek (1993) follows Jensen’s research and enriches it by describing the relation between capital structure and a firm’s operational and financial response to distress. He studies companies that experience a year average or above average performance followed by a year of significantly poorer performance. Consistent with the Jensen’s argument, Ofek’s empirical results show that the firm leverage in the year prior to the recession has a positive and significant effect on the probability that operational action will be taken in a distress year, such as employee layoffs and assets restructuring. Similar results are observed with the financial restructuring. Higher leverage significantly influences the probability of financial restructuring, such as dividend cut and debt renegotiations. According to the results, highly leveraged companies are more likely to respond to short-term distress with corporate restructuring compared to their less-leveraged counterparts. These results confirm Jensen’s study that leverage is positively connected to corporate restructuring activity and that highly-leveraged firms react faster to a decline in firm performance. Further, Ofek shows that debt provides discipline to a firm. It namely helps to avoid long period of losses with no response and helps to preserve the firm’s going-concern value.
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the study is that various stakeholders have different preferences for restructuring activity, they found significant results that when firm performance deteriorates, U.K. companies use more operational restructuring than financial restructuring. The most frequently adopted action is cost reduction and asset restructuring. In the observed sample, 59% of observed companies used cost reductions and employee layoffs comparing to 23% and 2% of the observed companies that used dividend cuts and debt restructuring, respectively. Firms substantially decrease their reliance on debt in bad times, because debt restructuring becomes more expensive for firms in time of recession (Bharma et al., 2008). Companies use operating restructuring to improve their existing efficiency and profitability, while they use financial restructuring to relieve the immediate burden of financial commitments. The result of financial restructuring in the short-term is not increased firm performance, but the ability of a firm to survive and not go to bankrupt. In the long term, the mix of undertaken operational and financial restructuring enables a firm to have an optimal performance.
Inspired by studies and results of Ofek and Lai and Sudarsanam, I state my last two hypotheses:
Hypothesis 4: Firms that use one of the corporate restructuring activities have better performance during a recession compared to their counterparts.
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3. Data and methodology
In this section I will explain how I measured the firm efficiency, which is used to asses firm performance. Firm efficiency is a measure, which values the efficient usage of a firm’s inputs and outputs. Further, I will explain the selection and the description of the data used for the analysis. At last I will provide the empirical model, which is used for statistical methodology.
3.1. Measuring firm performance
This part outlines the specification of the efficiency measure. Directional distance functions are used as alternative to production technology (Margaritis and Psillaki, 2009). An extensive explanation regarding the theory and application of directional distance functions is provided in the study of Färe and Grosskopf (2000). The duality between distance functions and production functions was initially discovered by Chambers, Chung and Färe (1998) and Färe, Grosskopf and Weber (1999). According to Färe and Grosskopf (2000), the directional distance function has shown to be very useful in modelling desired production. Directional distance function reveals the undesirable outputs and corresponding performance of such outputs.
Färe and Grosskopf name a random technology as T, and assume that a firm employs N inputs, denoted by x = (x1, …, xN) ∈ RN+ , and produces M outputs, denoted by y = (y1, …,
yM) ∈ RM+. Technology is denoted as:
T = {(x, y): x can produce y}, ∈ RN
+. (1)
The technology set is assumed to satisfy special properties. It is assumed to be a convex, closed set and inputs and outputs are freely disposable.1 Following Färe and Grosskopf, there is a need to define a distance directional function on the technology T, which is denoted by the “directional” vector g = ( - gx, gy). This vector determines the direction in which efficiency
1 Convexity and closedness of the technology is assumed for duality between directional distance and profit
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is assessed (Margaritis and Psillaki, 2009). The directional distance function (D→
T) is defined
as:
D→T (x, y; - gx, gy) = sub{β: (x – βgx, y – βgy) ∈ T}. (2)
As seen from this equitation, a distance function is created to seek outputs expanding and inputs contracting to the frontier T. If the observed mix between inputs and outputs is technically efficient, the value of the distance function equals zero. Thus, if the mix of observed input and outputs is interior in technology T, the mean distance function is more than zero, implying that a firm is technically inefficient.
According to Zhu (2002), Data Envelopment Analysis (DEA) is a mathematical programming envelopment technique under variables returns to scale (VRS). It is a useful tool to identify mentioned frontiers in evaluating relative efficiency of a given inputs and outputs. The directional distance function can be estimated non-parametrically using DEA as follows: D→
T (x, y; - gx, gy) = min β, (3)
and is subject to:
∑Kk=1 λkxkn ≤ xkn – βgx, n = 1, …, N,
∑Kk=1 λkykn ≥ y km – βgy, m = 1, …, M,
∑K
k=1 λk = 1, λk ≥ 0, k = 1, …, K.
The DEA model above is an input-oriented model, where the inputs are minimized and the outputs are kept at their current levels. The combination of inputs and outputs of the firm’s sample is formed by intensity variables (λk), namely one for each activity or observation.
These are non-negative variables whose solution values can be explained as the extent to which an activity is involved in frontier production. According to those variables, DEA identifies a peer group of “best practice” firms (those with non-zero λk) (Margaritis and
Psillaki, 2009).
In my study the firm efficiency is calculated by the using DEA Solver, which was defined and created by Zhu (2002). Efficiency (EFF) is denoted as follows:
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3.2. Data selection
The essence of this research is to examine how leverage and restructuring actions influence the firm’s efficiency prior and during the crisis. It is aimed to examine an industry which is highly dependent on global economic conditions. The automotive industry is perceived as a significantly cyclical industry, which highly depends on economic conditions. Economic growth percentages of real GDP of 2%, 3.3% and 3% were seen in the European Union in 2005, 2006 and 2007, respectively (OECD, 2011). Similar, a steady growth of sales in automotive industry of 5.7% and 3.7% were observed in 2006 and 2007, respectively (Datamonitor, 2010). In the period from 2001 to 2007, high borrowing due to relaxed lending criteria was present. After this period, a period of sudden loss of confidence in financial market followed, resulting in sharp contraction in inter-bank lending. The loss of confidence in financial markets and globally leading financial institutions caused a decline in global liquidity. Credit conditions had deteriorated and capital became much more expensive. Many banks and financial institutions reported huge losses and struggled with liquidity issues (The Economist, 2008). The global economic crisis started in September 2008 with the fall of Lehman Brothers and the nationalization of two important American real-estate funds. The “capital” problem has transferred to the real sector, for which less capital was available for investments. The growth of real GDP in European States was 0.4% and -4.2% in 2008 and 2009 respectively, which evidenced the presence of a global economic crisis (OECD, 2011). Simultaneously, the automotive industry suffered the decline of sales values of 0.5% in 2008, and 5.4% in 2009 (Datamonitor, 2010). The industry mostly suffered from a surge of used cars. In the recent economic crisis, people were more cautious when deciding to make an investment or just simply could not afford to buy a new car.
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companies with a known value for the time period selected, I formed a sample of 246 European companies operating in the automotive industry to analyse.
3.3. Sample description
Business activity demands investment of several inputs in order to produce an output. In my study, the measure of firm efficiency incorporates three inputs and one output. Labour, tangibles and equity are the inputs that produce the corresponding output, which is value-added. Labour is the number of employees, tangibles are fix tangible assets at the end of financial period, while value-added is calculated as total employee’s expense plus earnings before interest and taxes (EBIT) plus depreciation. The summary statistics of the sampled companies is seen in Table 1.
Table 1: Summary statistics of selected companies
The summary statistics in Panel A of Table 1 represents the data from 2008 and 2009, which was the time of crisis. In Panel B of Table 1 data are from time prior the recession. The sample includes 246 companies operating in the European automotive industry. The
Mean Std. Dev. Mean Std. Dev.
Value-added (Output) 3,863 10,807 4,944 11,452 Tangibles (Input) 2,523 5,640 2,631 5,509 Equity (Input) 4,998 11,699 5,000 11,327 Sales 17,149 45,979 21,943 49,984 Profit 371 2,934 1,156 3,465 Total assets 12,930 30,641 13,856 29,691
Labor (Input) - no.of employees 85 196 88 179
Panel A: Time of recession 2008 - 2009
2009 2008
Summary statistics in 1000 €
Mean Std. Dev. Mean Std. Dev. Mean Std. Dev.
Value-added (Output) 4,767 11,115 4,465 10,139 4,465 10,139 Tangibles (Input) 2,288 4,821 2,209 4,794 2,137 4,664 Equity (Input) 4,625 10,774 4,394 10,249 4,050 9,354 Sales 22,200 49,295 19,494 42,359 18,092 39,279 Profit 1,071 3,567 1,013 3,145 864 2,616 Total assets 13,627 28,903 12,594 26,814 11,162 22,600
Labor (Input) - no.of employees 87 168 83 155 82 151
2005
Summary statistics in 1000 €
Panel B: Time prior the recession 2005 - 2007
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arithmetic mean of total assets in observed companies is from EUR 11.2 million in 2005 to EUR 12.9 million in 2009, which indicates that the sample includes medium-sized companies. Companies had in average EUR 4.9 million in equity in 2009, which is higher comparing to EUR 4.1 million in 2005. The highest average profit of EUR 1.2 million is observed in 2008. There is a noticeable decrease of average profit for 211% in 2009 to EUR 371 thousand. The profit in 2009 for observed companies is consistently lower comparing to prior years, which indicates the presence of downturn in automobile industry. The profit could be even lower, however, because the stated value correlates with the calculation of efficiency. As discussed in Section 3, all the inputs and outputs used in efficiency calculations have to be non-negative values. Therefore many companies with significant loss are not included. This might have an impact on later calculations. The highest average sales value of EUR 22.2 million is observed in 2007. Later I observed a negative growth of average sales of 1.17% and 27.95% in 2008 and 2009, respectively. On average, observed companies employed 82 workers in 2005 and 85 workers in 2009.
3.4. Empirical model
I tested the previously stated Hypotheses 1, 2 and 3 that leverage is significantly associated with reduction of agency costs and firm performance by regressing the firm efficiency and the leverage ratio plus control variables. To determine the appropriate values of the coefficients of regression analysis the ordinary least squares (OLS) method is used. The regression equation for the firm performance model is given by:
EFFi,j = α0 + α1 LEVi + α2 Zj+ εji, (5)
where EFF is the firm’s efficiency, LEV is a leverage measure, Z is a vector of control variables and ε is stochastic error term.
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The variables included in Zj are control variables to control firm characteristics. Supported by
prior studies, I assumed that profitability, asset structure and size of the company significantly influence the firm efficiency.
Profitability (PR) is measured as the ratio of profits (EBIT) to total assets. According to Margaritis (2010), more profitable companies are better managed and therefore they are more efficient. Therefore I expect a positive relationship between profitability and firm efficiency. Intangibility (INTG) is calculated as ratio of intangible assets to total assets. This ratio is considered as indicator of future growth opportunities (Margaritis et al., 2009).
Tangiblitiy (TANG) is measured as the ratio of fix tangible assets to total assets. Tangibles are easily calculated and monitored. They represent good collateral and are thus used to mitigate agency conflicts (Margaritis et al., 2009).
Firm size (LNSALES) is measured as the natural logarithm of total sales. Larger companies are expected to have easier and better access to technology, are better managed and operate globally, what makes them more efficient. On the other hand, larger companies are more difficult to control, which consequently incurs higher monitoring costs (Williamson, 1967). For the regression equation for Hypothesis 1, where I want to test a positive relationship between leverage and firm efficiency, I used data from 2005 to 2007. I considered these years as the period prior to the recession. Following the explanation above that recession started in the middle of 2008 and was still evident in 2009, I used data from this period (i.e. 2008 and 2009) to test my Hypothesis 2, where I want to prove negative relationship between leverage and firm efficiency.
Hypothesis 3 claims that firms with higher leverage prior to the recession enjoy improved firm efficiency during the recession. Therefore I used the leverage data from 2007 and compare them with the firm efficiency observed in 2008 and 2009.
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specific company information to determine restructuring activity. In my research, operational restructuring comprises of:
· Employee layoffs: defined to occur if the firm reduces the number of employees for more than 10% comparing to prior financial year. Brockner et al. (1993) claims that important restructuring activity is employee layoff, especially in declining organizations.
· Decrease of costs per employee: defined to occur if a company reduces labour costs per employee comparing to prior financial year;
· Assets sale and positive cash flow: defined to occur if a company reduces its fixed tangible assets for more than 15% and simultaneously increases its cash flow comparing to prior financial year. Assets sale comprises of the sale of substantial part of the firm’s operating or non-operating assets or line of business.
If operational actions include reduction of costs, increase of cash flows, sale of various investments and divestures, it is the aim of financial restructuring to change the capital structure. Other studies recognized financial restructuring as leverage buyouts, creation of debt to pay off equity holders, decrease debt in order to meet the current liabilities, green mail, white knights, dividends cuts, bankruptcy filings and debt restructurings (Ofek, 1993; Schendel, 1993; Lai and Sudarsnam, 1997). Debt restructuring occurs if the firm restructures its debt to avoid default (Ofek, 1993). I identified financial restructuring when a company uses the following actions:
· Debt restructuring: renegotiate and change the maturity of existing debt – defined to occur if a company uses more short term debt than long term debt comparing to prior financial year. Ofek (1993) claims that a firm takes more short-term debt in bad time to avoid a default. Billet et al. (2007) finds that short-term debt positively affects growth opportunities, because it is more flexible and adapted to current firm needs. · Leverage decrease: defined to occur if a company decreases a leverage ratio by 20%
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4. Results and discussion
In this section I will confront the empirical results with the hypotheses stated in Section 2. As stated in the introduction, I am interested in examining the relationship between a firm’s capital structure, various restructuring actions and the firm efficiency. As described in Section 3, I measured firm efficiency by using directional distance function.
4.1. Leverage and firm performance
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sample of automotive companies seems to be very low and not normally distributed through the sample. The distribution of intangibility is skewed, which indicates non-normality. All other variables, which are later used in regression analysis, are also not normally distributed, but however stay in normal levels (i.e. skewness = +-1 and kurtosis = 2-3.5).
Table 2: Descriptive statistics of observed firms in automotive industry
Table 3 reports the least square estimates of independent variables with standard errors. The regression analysis examines the relationship between firm efficiency and the capital structure. The explained variable is the firm efficiency (EFF) and explanatory variables are as follows: leverage (LEV), profitability (PR), intangibility (INTG), tangibility (TANG) and firm size (LNSALES).
The results in Table 3 evidently indicate that the leverage ratio is positively associated with the firm efficiency. The results are significant (p = 0.00) for all the years considered prior to the recession, i.e. from 2005 to 2007. Similarly, the sample reveals that firms, which had higher debt structure in time of the recession, i.e. in 2008 and 2009, were significantly more
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efficient than firms with a lower leverage ratio during the time of the recession. This is a surprising result, but nevertheless the 2009 coefficient (α1 = 0.19, p = 0.00) is significantly
lower comparing to 2006 (α1 = 0.41, p = 0.00).
Profitability also has a positive and significant effect on efficiency for all observed periods. The opposite effect is observed between tangibility and efficiency. Although tangible fixed assets represent good collateral and are easily monitored and should therefore mitigate agency costs, the observed sample shows lower efficiency for firms with higher TANG. Similarly, size of the company does not favourably influence the firm efficiency. Although larger firms use new technology and can enjoy economics of scale, firm size can incur higher monitoring costs and can suffer from hierarchical managerial inefficiencies. In my sample it seems that the inefficiencies prevail, because LNSALES significantly negatively influences the EFF from 2005 to 2009. According to my results, fixed tangible assets and firm size are perceived as a burden for companies in the automotive industry, which lowers the firm efficiency.
Table 3: The relationship between firm efficiency, capital structure and control variables
4.2. Corporate restructuring
My study considers corporate restructuring when the first sign of recession was evident. As explained in Section 3, the recession for automotive industry started in 2008. However, the effect of the crisis was not apparent immediately. As shown in Table 1, where summary statistics of the selected firms are presented, average profits in 2008 were higher compared to one financial year before. Therefore, profits did not show any presence of cyclical downturn
Regressand: EFF
Coefficient SE Coefficient SE Coefficient SE Coefficient SE Coefficient SE
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in automotive industry. If we further examine the statistics, we notice that average sales in 2008 were actually lower compared to a year before. That indicates that firms in automotive industry enjoyed high profits from sales orders concluded in previous years. In 2008, firms in automotive industry experienced a strong decline in new orders, which was evident support for an upcoming recession. Supporting this explanation, I believe that firms, which recognized the coming decline and try to be competitive, focused on restructuring activities in 2008. Table 4 provides the number of companies that used various restructuring actions in time of the recession. In 2008, the majority of selected firms used operational restructuring, comprised of employee layoffs, decreasing of labour costs and sales of assets. Only operational restructuring was used by 45% of firms in selected sample. Financial restructuring actions comprise of debt restructuring and leverage decrease. These actions were considered by 8% of the selected firms. Slightly more than a third of the selected companies used both operational and financial actions. The other 10% of sampled firms used no restructuring activity. In 2009, surprisingly more firms used financial restructuring (29%) and on the other hand much less firms use operational restructuring (17%). Additionally, there is also a significant increase of firms that used no restructuring at all (27%).
Table 4: Corporate restructuring actions used in 2008 and 2009
Further, in my research, I tried to examine whether a leverage ratio in a base year triggers the restructuring action in the following year, which is the year of the recession. Table 5 reports the relation between the leverage ratio in the base year and taken restructuring action in the following year. The results show a positive, but insignificant relation between the leverage ratio in the period from 2007 to 2008 and operational actions in the following year. Of the operational actions taken by the firm, assets sale was significantly more likely in high leveraged firms than in those with less debt. Further, employee layoffs in 2008 are positively, but insignificantly (p=0.12) related to firms that hold more debt in their capital structure in 2008. Overall, due to insignificance, these results fail to show that highly-leveraged firms use
Restructuring activity No. As % No. As %
Operational restructuring 111 45.12% 42 17.07%
Financial Restructuring 20 8.13% 73 29.67%
Operaing and Financial Rest. 90 36.59% 64 26.02%
No Restructuring 25 10.16% 67 27.24%
Total 246 100.00% 246 100.00%
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more operational restructuring than less-leveraged peers, when the economic conditions deteriorate. Conversely, leverage ratio in the base year is significantly related to the financial restructuring, which comprises of debt restructuring and leverage decrease in the following year. Firms with more debt are less likely to use financial restructuring in 2008, but not in 2009. This is definitely a surprising result, but it is significant. The probability that firms with more debt prior to the recession decrease their leverage is unlikely, but it was also significant.
Table 5: The relationship between leverage ratio and corporate restructuring actions
Table 6 presents the results of the regression analysis, which examines the relation between pre-distress leverage ratio and the firm efficiency in the following two years of the recession. Results indicate that firms would have reported better firm efficiency in 2008 and 2009, if they had a higher leverage ratio in 2007. Firms with a higher leverage ratio before the crisis evidently were more efficient during the crisis. In line with expectations that highly-leveraged firms restructure frequently, I find significant a positive effect (p=0.00) on firm efficiency in 2008, if firms used any restructuring activity (RES) in the same year. The same positive effect of RES in 2008 is observed for the firm efficiency in 2009, but the finding is not significant (p=0.15). Interestingly, the effect of RES 2009 on EFF 2009 deteriorates and becomes negative (p=0.06).
Table 6: The relationship between leverage ratio prior to the recession, corporate restructuring actions and firm efficiency during the recession
Regressor: Leverage (LEV)
Regressands Coefficient SE sig. Coefficient SE sig.
Operational restructuring 0.011 0.02 0.66 0.040 0.03 0.22
Employee layoff 0.054 0.03 0.12 -0.007 0.03 0.80
Cost per employee 0.002 0.03 0.94 -0.024 0.03 0.45
Asset Sale 0.016 0.02 0.03 0.155 0.01 0.01
Financial restructuring -0.062 0.02 0.01 -0.118 0.03 0.00
Debt Restructuring 0.015 0.02 0.51 -0.085 0.03 0.00
Leverage Decrease -0.154 0.03 0.00 -0.156 0.04 0.00
LEV 2007 LEV 2008
Regressand: Firm efficincy (EFF)
Regressors Coefficient SE Regressors Coefficient SE Regressors Coefficient SE
LEV 2007 0.297* 0.05 LEV 2007 0.146* 0.05 LEV 2007 0.134* 0.05
RES 2008 0.045** 0.03 RES 2008 0.033 0.02 RES 2009 -0.065*** 0.03
PR 2008 1.004* 0.15 PR 2009 1.009* 0.11 PR 2009 0.969* 0.12
TANG 2008 -0.507* 0.05 TANG 2009 -0.382* 0.06 TANG 2009 -0.367* 0.06
LNSALES 2008 -0.031* 0.01 LNSALES 2009 -0.018* 0.01 LNSALES 2009 -0.021* 0.01
* Significant at 0% ** Significant at 1% *** Significant at 10%
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Table 7 represents average firm efficiency for individual restructuring actions. Additionally, to support the efficiency scores, I conducted a regression analysis to prove the relationship between firm efficiency and various restructuring actions and the results are reported in Table 8. Firms that used only operational restructuring in 2008 reported an efficiency score of 46% in 2008 and 2009. Regression analyses show a positive, but insignificant effect of operational restructuring in 2008 on EFF 2008, and a slightly negative effect on EFF 2009. Similar to 2008, the average efficiency score in 2009 is 46%. The effect of operational restructuring carried out in 2009 had positive and insignificant influence on firm efficiency observed in 2009. Firms that restructured financially in 2008, did not improve their efficiency from 2008 to 2009. The average firm efficiency was 46% and 45% in 2008 and 2009, respectively. This is in line with the outcome of the regression seen in Table 8, where the negative effect of financial reorganization in 2008 is reported on EFF 2008 (p=0.07) and EFF 2009 (p=0.27). Contrarily, firms that use financial restructuring in 2009 were much more efficient and have an average efficiency score of 54%. The same result is observed where financial action positively, but insignificantly, affects the firm efficiency.
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Table 7: Specific restructuring actions and corresponding average firm efficiency in 2008 and 2009
Table 8: The relationship between specific restructuring action and firm efficiency in 2008 and 2009
Further to my research, Table 8 reports the effect on firm efficiency only for firms that used either operational or financial restructuring. I observed that firms that used operational restructuring in 2008 were more efficient comparing to firm that used financial restructuring in 2008. In contrast, financial restructuring in 2008 and 2009 seems to have a stronger impact on firm efficiency in 2009. However, these results are not significant, and therefore can not serve to explain which restructuring activities have greater impact on firm efficiency.
Additionally, Table 8 reports the results of a regression analysis, which examines the relation between specific operational or financial restructuring actions and firm efficiency in the distress year. Operational restructuring encompasses actions as employee layoffs, decrease of labour costs and sale of tangible assets. The reduction of labour force in 2008 positively relates to firm efficiency in 2008 and 2009, but the findings are not significant (p=0.26 and p=0.47, respectively). Cutback of costs per employee in 2008 also positively affected the firm efficiency in 2008 and 2009 (significant at the 9% and 11% level, respectively). The opposite is observed in 2009. Firms that cut labour costs were significantly less efficient (p=0.01). A significant positive effect of tangible assets sale to firm efficiency is observed in both 2008 and 2009. Furthermore, the same outcome is shown as significant, when in the same year tangible assets were sold and firm had a positive cash flow comparing to a year before.
2009
Average EFF EFF 2008 EFF 2009 EFF 2009
Operational restructuring 0.469 0.469 0.466
Financial Restructuring 0.466 0.452 0.543
Operaing and Financial Rest. 0.565 0.533 0.454
No Restructuring 0.465 0.470 0.598
2008
Regressand: EFF
Regressors Coefficient SE sig. Coefficient SE sig Coefficient SE sig.
Operational restructuring 0.012 0.03 0.65 -0.019 0.03 0.49 0.011 0.02 0.58
Employee layoff 0.030 0.03 0.26 0.020 0.03 0.47 -0.01 0.02 0.64
Cost per employee 0.030 0.02 0.09 0.034 0.02 0.11 -0,018 0.01 0.01
Asset Sale & Positive CF 0.129 0.04 0.00 0.108 0.44 0.02 0.033 0.05 0.48
Financial restructuring -0.037 0.02 0.07 -0.024 0.02 0.27 0.005 0.04 0.88
Debt Restructuring 0.052 0.02 0.01 0.055 0.02 0.01 -0.019 0.22 0.38
Leverage Decrease -0.063 0.027 0.02 -0.021 0.01 0.00 -0.036 0.03 0.21
Operational and Financial Rest. 0.598 0.18 0.00 0.070 0.02 0.00 -0.041 0.02 0.05
No Restructuring -0.037 0.02 0.09 -0.029 0.02 0.22 0.070 0.34 0.04
Operational or Financial 0.034 0.03 0.19 -0.011 0.03 0.70 -0.040 0.04 0.36
EFF 2008 EFF 2009 EFF 2009
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Financial restructuring comprises of debt restructuring and decrease of leverage. Debt restructuring enables a company to change its debts from long term to short term obligations. Firms that changed its debt from long term to short term in 2008, were significantly more efficient in 2008 and 2009. This trend deteriorated in 2009, but shows insignificant results. Firms that decreased their leverage structure in 2008 and 2009 reported worse firm efficiency in 2008 and 2009. However, whereas the results for 2008 are significant, the results for 2009 are not (p=0.21).
4.3. Discussion
According to the findings, firm efficiency is positively connected to the leverage ratio across all observed periods. This result is in line with Jensen and Meckling’s (1976) agency cost theory. Companies with more debt better exploited labour and assets to produce a “product”. Firms that efficiently used their disposable inputs have lower agency costs. My findings comply with Jensen (1989), who states that leverage plays the role of a control tool to reduce the agency costs created by the conflict of interest between managers and owners of the firm. Debt creation enables an obligation for a manager to effectively use disposable cash flow, because more leveraged firms have higher interest payments, what prevents managers from investing in non-profitable or too risky projects. Therefore I find the support for my Hypothesis 1 that highly-leveraged firms in time prior to the recession recorded better firm efficiency comparing to firms with lower amount of debt. Similarly, Margaritis and Psillaki (2010) found support for the Jensen and Meckling (1976) agency cost hypothesis that higher leverage is positively associated with improved firm efficiency.
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calculation, meaning that there is no company with negative value-added. Additionally, I did not include firms, which bankrupted in the observed time. The positive effect of leverage could have deteriorated if all the firms were considered.
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the debt liabilities. Leverage influences the probability of adopted restructuring action in time of the recession.
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provides the discipline to a firm to avoid long period of losses with no response and helps to preserve the firm’s going-concern value. I find a support for my Hypothesis 4 that firms, which use specific corporate restructuring actions, have better firm performance than firms which delay with restructuring or even do not take any actions. High leverage in time of the expansion can be seen as a safeguard of better firm performance when the economic condition deteriorates, because it triggers specific restructuring actions, which improve firm efficiency in time of the recession.
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5. Conclusion
The overall aim of my research was to examine the relation between a firm's capital structure prior to and during the recession, corporate restructuring actions and firm performance during the recession. My study comprises of firms, which operated in European automotive industry in the period from 2005 to 2009. My analysis is conducted using data envelopment analysis to obtain firm efficiency as a measure of firm performance. A worldwide recession shook the global economy to its foundations. Many studies exists that blame high debt values as the main cause for the financial crisis. I show that value-adding firms with a higher leverage ratio experienced improved efficiency, mainly due to frequent restructuring activity.
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My findings evidently show that capital structure importantly influences the reaction of a company, when economic conditions deteriorate. As a successful control tool, capital structure has to be wisely determined in order to serve its purpose. From the perspective of the agency cost theory, the shareholders need to bear in mind that leverage is a successful tool to reduce misunderstandings between owners and managers. In time of recession, when firms try to retain their competitive position, high leverage helps firms to efficiently use disposable inputs by considering several restructuring actions. High leverage prior to the recession is seen as a safeguard for better firm performance during the recession. Managers should be aware that restructuring actions should be considered frequently and especially when first signs of a recession become evident. Firms that lag or even do not consider any restructuring actions when a recession begins, can experience significant downturn of their performance. Rothenbücher and Schrottke (2009) claim that in a downturn, it is important to stay flexible and leave room for growth, so you can hit the ground running once the crisis ends.
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