Testing the Pecking Order Theory of Capital Structure in FTSE 350 Food Producers Firms in United Kingdom between 2001 and 2005

KeywordsCapital Structure FSTE 350 Food Sector Pecking Order Theory Trade-Off Theory United Kingdom

JEL Classification C13, C35, G32, L66

Full Article

1. Introduction

How do firms finance their operations? How should firms finance their operations? What factors influence these choices? How do these choices affect the rest of the economy? These are important long standing questions. At one time, the complexity of the problem was thought by many to be so great as to defy the development of reasonable theories according to Frank and Goyal (2009). Attempts to find solutions to these questions have led to two prominent and competing theories of capital structure known as the Trade-off theory and the Pecking Order theory (hereafter POT), in which the method of financing matters.

The trade-off theory is based on tax, bankruptcy and agency models. According to the trade-off theory each firm has a well-defined optimal capital structure, which balances the cost and benefits of debt financing. As pointed out by MM (1963), debt financing is more advantageous than equity because it reduces the expected tax liability thus increasing the after tax cash flow. And in the event of financial distress, a firm’s optimal capital structure should equate bankruptcy and debt-tax shield. The trade-off theory suggests that debt equity ratio is mean-reverting as the firm seeks to achieve the target ratio. There is a lot of support for the trade-off theory both from earlier and recent empirical research [see Taggart (1977), Jalilvand and Harris (1984), Miguel and Pindado (2001), Ozkan (2001), Bhaduri (2002), Loof (2004), Flannery and Rangan (2006), Marsh (1982) and Hovakimian et al. (2001)].

On the other hand, the pecking order theory (POT), states that firms follow a financing hierarchy preferring internal funds first, followed by external debt next and equity as a last resort. Contrary to the trade-off theory, it is a conventional wisdom that companies choose the least expensive method to finance their companies as this is in line with the pecking order theory. When it comes to new investments financing most companies will prefer using retained earnings, followed by debt and equity. On the other hand the trade-off model expects that there is the need to consider several costs and benefits in the decision of trade-off between dividend and leverage. According to Fama and French (2002) some of the predictors of trade-off model are taxes, free cash flow agency problems and bankruptcy costs.

Based on asymmetric information, a firm’s choice of financing uses a pecking order where internal finance is preferred to external finance, in which debt is liked to equity. According to Lumby and Jones (2011), the company should finance as much as possible through the use of retained earnings and where external finance is used because managers have identified positive NPV investments that cannot be financed with retained earnings, issue debt until debt capacity is reached and only then, if positive NPV projects still remain to be financed, issue equity. The pecking order theory forecasts that high-growth firms with large financing necessities end up with high debt ratios because of managers’ reluctance to issue equity. However,, the findings of Smith and Watts (1992) and Barclay, et al. (2001) contradict this prediction as they found out that high growth firms use less debt in their capital structure.

Corporate financing policy is central to the survival of any business, more especially those in the manufacturing industry. For example, in the food producer business, it is crucial for firms to use a proper mix of the financing sources available as most of the goods produce are easily perishable. Thus too much debt financing might not be good news in the event of slow sales. The primary aim of this study is to test the pecking order theory of FTSE 350 Food Producers Sector on their financing behaviour.

2. Literature Review

2.1. Capital Structure Theories

Firms’ financing policy requires managers to identify ways of funding new investments. The managers may exercise three main choices: use retained earnings, borrow through debt instruments, or issue new shares. Hence, the standard capital structure of a firm includes those three choices, which can also reflect firm ownership structure. The key purpose of the capital structure policy is to ensure that an appropriate mixture of debt and equity is used in financing the business. The mixture of debt and equity used to finance the assets of a firm is referred to as its capital structure. Several theories have been put forward on the subject of capital structure. These theories include the trade-off theory, pecking order theory, free cash flow/Agency theory and Market timing theory. However, for the purpose of this study, focus is on the two competing theories (trade-off and pecking order theories).

2.1.1. Trade-off Theory

The trade-off theory contends that each firm has a well- characterized optimal capital structure, which adjusts the advantages and costs of debt financing and that the firm moves towards it through time. The trade-off theory focuses on (a) the trade-off between taxes and bankruptcy, (b) agency conflicts and (c) stakeholders’ co-investments (Frank and Goyal 2003). The first branch (taxes x bankruptcy) compares the debt benefit of reduced tax burden with a higher vulnerability of the firm due to its higher financial leverage. That is firms should issue debt until the value of the tax shield on debt equals the expected cost of bankruptcy. The agency theory states that debt financing helps solve problems deriving from the firm excess cash flow as it commits the firm to debt interest payments. With the stakeholders’ co-investments, trade-off theory has it that financing with stock options is the best way to induce all stake holders to fight for the survival of the firm

The Trade-off theory of capital structure indicates that the decision of a company to choose how much debt and equity financing that is required is based on the balancing of the costs and benefits of each form of funding (Gurcharan 2010). According to Gurcharan (2010), there is an advantage to finance through debt (interest tax shield benefit) but this needs to include consideration of the costs of financial distress, including the bankruptcy costs of debt and non-bankruptcy costs. Therefore, the empirical relevance of the trade-off theory is still being questioned (Frank and Goyal, 2003). On the other hand, Miller (1977) and Graham (2003) argue that the tax savings obtained do appear large enough and certain, while the deadweight bankruptcy costs seem minor.

Myers (1984) recognizes that as firms’ borrowing increases, the cost of financial distress (example, bankruptcy costs, agency costs, transaction costs, etc.) also increases. He argues that at a certain point the costs of financial distress will exactly offset the interest tax shield generated by borrowing and at that point the value of the firm is maximized or the overall cost of capital is minimise. Thus, the existence of financial distress costs such as bankruptcy costs implies that an optimal capital structure exists and this occurs at the point where tax advantage is traded off against the likelihood of incurring those financial distress costs.

The trade-off  theory have some support because there are wide variations of gearing levels among firms that predict that "target debt ratio will vary from firm to firm" (Bradley et al., 1984). It also rationalises moderate borrowings. The pitfall to this theory however, is that it fails to explain the strong indirect correlation between profitability and financial leverage. Following from the analysis of this theory, one would expect that profitable firms would have a higher debt ratio. This is because higher profits mean more pounds for debt service and more taxable income to shield. Bradley et al.(1984) indicated that the most profitable firms borrow less, and the least profitable ones borrow more.

Early studies by Taggart (1977), Jalilvand and Harris (1984) provide evidence of mean reversion of leverage, which is consistent with the trade-off theory. While Miguel and Pindado (2001) and Fama and French (2002) reported mixed results, Ozkan (2001), Bhaduri (2002), Loof (2004) and Flannery and Rangan (2006) observed that leverage adjust partially to target leverage, hence supporting the trade-off theory prediction. Findings by Marsh (1982) and Hovakimian et al., (2001), show that a firm’s decision to issue new securities is determined by target capital structure.

2.1.2. Pecking Order Theory

Pecking order theory is one of the leading theories in corporate finance, as it predicts the structure of debt. It indicates that securities with lowest information costs must be issued first and higher information cost securities should be issued later. Frank and Fama (2003) suggested that it is better for companies to take advantage of short-term debt before thinking about long-term debt. In line with the pecking order theory is a fact that financing behaviour most of the time is driven by adverse selection costs. It can be inferred that the theory performs best with firms with severe adverse selection problems.

Myers (1984) indicated that firms follow a financing hierarchy determined by agency whiles information asymmetry and the signalling considerations were reported by (Myers and Majluf, 1984). That is, supposing there are three main funding sources available to firms: retained earnings, debt and equity. Retained earnings have no issue with adverse selection. Equity has serious adverse selection issues while debt has only a minor adverse selection issue. From an outside investor’s point of view, although both equity and debt have adverse selection premium, equity is riskier and has a larger premium. Outside investors demand higher rate of return on equity. From the insiders’ (managers) point of view retained earnings are a better source of funds than debt and debt is a better source than equity financing.  Thus, firms prefer internal funds above external funds and if retained earnings are inadequate, then debt is used. Only in extreme cases will firms use new equity financing.

Frank and Goyal (2003) tested the Pecking Order theory in the period 1971 - 1998. They found that, on average income within the business is not adequate to finance any investment, that external sources of funding are highly regarded, and, therefore, debt and equity are important sources of funding. On the issue of determinants of capital structure, Bancel and Mittoo (2004) mentioned that large firms do not take bankruptcy costs into much consideration, whilst high-growth firms consider common stock to be the lowest source of funds and use windows of opportunity to issue common stock.

Chen (2004) found that in the Chinese economy short-term finance is more considered and, therefore, less attention is paid to long term debt. A study by Hovakimian et al. (2004) also found that studies of corporate financing choices showed that the importance of stock returns was unrelated to target leverage, and was likely to be due to the Pecking Order theory. According to Rao et. al., (2007), unrewarding firms issue equity to counterbalance the excess leverage because of the accumulated losses. Along these lines, their review upheld the thought that organizations have an objective capital structure. However, preference for internal financing and the enticement to time the market by selling new equity when the share price is relatively high interfere with the tendency to maintain the firm’s debt ratio close to its target.

Since the purpose of this study is to test the pecking order theory of capital structure, the study examines the following empirical predictions of the pecking order theory:

Proposition 1: Investment is mostly internally financed. External finance is financed mainly through debt.

Proposition 2: New equity issues are only observed at high levels of debt.

Proposition 3: Leverage fluctuates over time with little tendency to revert back to target levels.

3. Methodology

Case study research designs or approaches can be founded on their capacity, attributes, or disciplinary point of view. One’s determination of a research design is determined by how well it permits full examination of a specific research question as indicated by Hancock and Algozzine (2006). Case studies concentrate on one (or only a couple) examples of a particular phenomenon with a view to providing an in-depth record of occasions, connections, encounters or procedures happening in that specific case as proposed by Denscombe (2007).

This study adopted the case study method but used a multiple case study approach but its focus was discovery led where the study described what was happening in FSTE 350 Food Sector and explored the key issues affecting the financing decisions and its pattern under the sector. Importantly this study was able to compare the similarities and differences between the individual constituent under the sector. A multiple case study approach focusing on a particular sector (Food Producer sector) is adopted for this study. The way in which companies finance their operations varies from industry to industry. Thus, by focusing attention on a particular sector within an industry, it enables the study to cover lots of ground on the subject.

The study was done retrospectively as ex post facto. Retrospective study investigates a phenomenon or issue that has occurred in the past. Such studies most often involve secondary data collection, based upon data available from previous studies or databases. The retrospective study was considered as the outcome of interest has already occurred at the time of this study’s initiation. Mitchell and Jolley (2013) explained ex post facto study as a research design in which the investigation starts after the facts have occurred without the interference of the researcher. Despite studying the facts that have already occurred, ex post facto research shares with experimental research design some of the basic logic of inquiry.

This study addressed one of the major limitations of case study research method which is credibility of generalisations made from findings due to its representativeness. Also validity and completeness is enhanced with this approach as a more representative sample was drawn from a small population. Six out of the seven companies under FSTE 350 Food Producers Sector was included in this study and credibility of the source of data for this study is not in doubt.

3.1. Sample

The sampling process adopted a discriminatory approach from the FTSE 350 UK Food Producer Sector since the focus of the study was on testing the pecking order theory of capital structure in a particular sector/industry. All the seven manufacturing companies under the sector were part of the population for the study. The sampling criteria consideration was that the company must be non-financial listed UK Domicile company as most financial companies are highly liquid. Also for ease of access to annual reports and accounts, all sampled companies have to be UK domiciled. It must be a FTSE 350 company since companies under this category in the food producer sector are the key players in the Food Producers Sector. Moreover, the company must has been actively trading throughout the period 2001 to 2005 so as to enable the study establish an accurate pattern of financing as well as how the relationship between net debt, financing deficit and net equity issue. Finally the company must not be involved in a takeover or merger during the period 2001 to 2005. Based on the above selection criteria and for the period considered in this study, seven companies qualified to be included in the population. Thus, the population consists of the following firms: Associated British Foods, Premier Foods, Cadbury Schweppes, Diary Crest, Tate & Lyle, Northern Foods and Unilever (UK). For the study to be statistically significant the sample size includes all firms in the population except for Premier Foods Plc as it was involve in the takeover of RHM during the period, which means all the companies in that FTSE 350 UK Food Producers Sector except one have been captured.

3.2. Data

The data for this study has been gathered from secondary sources. Secondary data required for this study is derived from the profit and loss accounts, balance sheet and cash flow statements of the various constituents of the UK FTSE 350 Food Producers Sector annual reports for the period 2001 to 2005 from the Financial Times All-share Index and Industry statistics, Fame database, Perfect analysis and DataStream.

The timeframe of 2001-2005 was chosen as it was during this period where a lot of mergers and acquisition were taken place in the FTSE 350 Food Sector. This was the period where five year high debt financing were recorded by some of the companies coupled with intense pressure from the grocery retailing giants like Tesco and ASDA  demanded that suppliers to reduce its operational cost to reduce its selling prices to better off their margins. This indeed forced some of the companies within the FTSE 350 Food Sector to initiated restructuring programmes.

Moreover a five year retrospective study of the financial situation of Northern Foods Plc. was conducted, one of the constituent of the FTSE 350 Food Producer Sector and there was the need to investigate its financing strategy as further study as an extension to the paper, so this particular study decided to take it up and investigate not only Northern Foods Plc but the whole of FTSE 350 Food Sector as a study using the same period, hence the ex post facto as a research design influenced the timeframe of the study.

3.3. Variables Description and Measurement

The first part of the regression analysis on the FTSE 350 Food producer sector companies focuses on the change in debt (ΔD) and its relationship with financing deficit (DEF). Also, change in debt and Equity dividend (DIV), investments (INV), change in working capital (ΔW) and internal cash flows (C).

(ΔD_it): is the change in debt/net debt issued for firm (i) at time t given as long term debt issuance minus long term debt reduction.

(DIV_it): Equity dividend paid in time t by firm (i)

(INV_it): net investments for firm (i) at time t (i.e. INV = capital expenditure + acquisitions and disposals)

(ΔW_it): change in working capital for firm (i) at time t [i.e. ΔW = change in operating working capital + changes in cash and cash equivalent + change in current debt]

(C_it): cash inflows of firm (i) at time t (i.e. cash inflow from operating activities - investments returns and servicing of finance – taxation)

(DEF_it): is the financing deficit for firm (i) at time t [i.e. DEF_it = DIV_it + INV_it + ΔW_it – C_it]

The second part of the regression analysis focuses on gearing (D_it) and its relationship with the variables is explained below. The analysis on this part focuses on the impact of firm-specific factors on total gearing. Thus, the following aggregate measure of gearing is adopted;

Total gearing (D_it) = total debt / total asset = TD/TA

Asset Tangibility (TAN_it): the ratio of tangible depreciated fixed assets (FA) to total assets (TA) According to Rajan and Zingales (1995), collateral value of assets or tangibility of assets held by a firm can have an influence on its capital structure. Tangible assets are likely to have an impact on the borrowing decisions of a firm because they are less subjected to information asymmetry.

Asset Tangibility = FA / TA

Profitability (PRF_it): a firm’s profitability is given as the ratio of its earnings before interest, tax and depreciation (EBITDA) to the book value of its total assets (TA). According to the pecking order theory (Myers, 1984), it is expected that investments would be internal finance if a firm is profitable. Thus more profitable firms are expected to hold less debt.

Profitability = EBITDA / TA

Market-to-book value ratio (MBV_it): it is normally used as proxy for company’s growth opportunities. In calculating the market-to-book ratio with the numerator as total assets (TA) minus the addition of the book value of equity (ECR) and the market value of equity (MV) divided by the total assets (TA) as the denominator. Companies with higher market-to-book ratios are indication that there must exist more growth opportunities in those companies. Myers (1997) indicated that a company’s ability to take advantage of growth opportunities when arise can be limited by the huge debt of the company. Therefore firms with high market-to-book ratios are expected to have good future growth opportunities and hence low leverage (Fama and French, 2002).

Market-to-book ratio = (TA – ECR + MV) / TA

Firm size (LS_it): there has been considerable consensus amongst past research regarding the measurement of size, which is either (i) the natural logarithm of total assets (e.g. Michaelas et al., 1999) or (ii) the natural logarithm of total sales (Ozkan, 2001). For the purpose of this study, the natural logarithm of total sales is used as a proxy for firm size.

Firm size = Ln (sales)

3.4. Empirical Models

The models used for the regression analysis are based on Frank and Goyal (2003) and Shyam-Sunder and Myers (1999) work on testing the pecking order theory of capital structure as well as the model of Rajan and Zingales (1995) work on determinants of capital structure.

The general regression models are:

Y_it =α + βX_it + ε_it

Y_it =α+ β₁X_it + β₂X_2it + …………..+β_nX_nit +ε_it

Thus, for the purpose of this study, the following regression equations were used.

ΔD_it = α + βDEF_it + ε_it   Equation 1

ΔD_it = α +β₁DIV_it + β₂INV_it + β₃ΔW_it – β₄C_it + ε_it    Equation 2

In testing the relationship between total gearing and determinants of capital structure, the equation below is used.

D_it = α + β_TANTAN_it + β_MBVMBV_it + β_LSLS_it + β_PRFPRF_it + ε_it      Equation 3

4. Results and Discussion

4.1. Pattern of Financing Decision

Following previous studies, the average of the firm-year data was found for each of the variables considered for this study. Whilst Table 1a shows the corporate cash flows for FTSE 350 UK Food Producer sector sampled companies, Table 1b shows corporate cash flows with investment lagged by one year (See Appendix A for individual company corporate cash flows and trend in financing pattern).

Table 1a.Aggregate Corporate cash flow of FTSE 350 UK Food Producer firms

Table 1b. Aggregate Corporate cash flow of FTSE UK 350 Food Producer firms when investments lagged by 1 year

Notes: *Investments are lagged by one year [i.e. investment reported in 2002 annual reports are entered under 2001 in Table 1b above; See Appendix B for computation of aggregate corporate cash flows and sources of data]

Tables 1a and 1b show corporate funds flow of the FTSE 350 UK Food producer sector companies for the period 2001 to 2005 with Table 1b showing cash flows with investments lagged by one year. The main reason for lagging investments by one year is that in practice companies raise funds for future investments presumably starting the following year.

On average, the sector has increased its cash dividend payout year on year (from £218.13m in 2001 to £286.4m in 2004) except for 2005 when it saw a drop in average cash dividend payout of approximately 68% to £92.12m comparative to the previous year. On the other hand, average investments increased sharply from £54.47m in 2001 to £604.63m in 2003. Although there was almost a 50% drop in investments expenditure in 2004 and 2005 compared to 2003, an investment expenditure of £229.3m and £335.3m was still recorded (see Table 1a). Generally the sectors working capital has improved significantly. Only in 2001 and 2003 did the companies on average increase their working capital by £36.53m and £42.08m respectively. The years 2002, 2004 and 2005 saw the sector make huge savings in working capital of £156.04m, £81.9m and £279.08m respectively.

Tables 1a and 1b show that despite the reduction in working capital expenditure, the companies on average performed better than in 2001 and 2003 when there was an increase in working capital expenditure. Performance wise the sample companies have been doing well as the tables have shown that the aggregate internal cash flows have increased year on year from £589.93m in 2001 to £765.38 in 2005. This result supports the research of Myers (1984) who prescribed that it is expected that investments would be internal finance if a firm is profitable. Thus, more profitable firms are expected to hold less debt.

The average corporate cash flows shown in the above tables match the Shyam-Sunder and Myers (1999) identity of financing deficit. From Table 1a, it is observed that on average the FTSE 350 UK Food producer sectors firms only recorded a shortage of funds of £173.09m in 2003 and a surplus of funds of £389.74m, £506.99m, £387.41m and £617.04m in 2001, 2002, 2004 and 2005, respectively. However, when aggregate investments lagged by one year, the FTSE 350 UK Food producer sector companies recorded a financial surplus for each of the years 2001 to 2005 (see Table 1b).

A very important message conveyed in Tables 1a and 1b is that on average the FTSE UK 350 Food Producer sector firms uses both internal and external (debt and equity) sources of finance. However, it can be seen from the tables that financing deficit is not matched pound-for-pound by a change in corporate debt. As a result corporate debt in the FTSE 350 UK  Food Producer Sector is not determine by financing deficit as the sector also uses equity as a source of external financing. POT has it that companies should only issue equity when and only when they reach their debt capacity thus the hypothesis new equity issues are only observed at high levels of debt. The information reported in the tables conveys a mixed message. For example, when aggregate net debt issues were highest (at £390.55m) in 2005, there was on average a net repurchase of equity worth £11.73m. However, when there was a net debt reduction in 2002, there were still net equity issues of £7.03m comparative to only £0.17m in 2003 when average net debt issued were lowest at £172.9m. The finding is in line with Lumby and Jones (2011), who indicated that a company should finance as much as possible through the use of retained earnings and where external finance is used it must be on positive NPV investments, a company must issue debt until debt capacity is reached and only then, if positive NPV projects still remain to be financed, issue equity. Barclay et al. (2001) suggest that it is not always true as they found out in their research that some high growth firms use less debt in their capital structure

On average the FTSE 350 UK Food producer sector firms made a substantial reduction in net debt issues of £276.68m and £223.17m in 2002 and 2004 respectively compared to the net debt issues of £219.43m in 2001, £172.9m in 2003 and £390.55m in 2005. The reduction in average net debt issues for 2002 and 2004 may be due to the corresponding improvement in internal cash flow and the reduction in working capital expenditure.

It is expected that recording a financial surplus will stop companies raising external funds from the debt or equity markets. The tables 1a and 1b show that despite the financial surplus recorded in 2001, 2002, 2004 and 2005, the FTSE 350 UK food producer companies still seek funding from the debt and equity market. Particularly striking is the fact that whilst there was a huge financial surplus of £617.04m in 2005, average net debt issues were a staggering £390.55m. From the tables, this could be attributed to the 12% increase in average total assets (from £7055.62m in 2004 to £7897.15m in 2005). Also whilst the sector manage to reduce its average net debt issues by £276.68m in 2002, it still had an average net equity issued of £7.03m On the other hand net equity issues have been declining over time during the period; that is from £14m in 2001 to an average repurchase of own shares of £11.73m in 2005.  

A major aspect of the POT is the importance of retained earnings relative to external financing. According to Myers (1984) most investments are finance by internal cash flow. During the period 2001 to 2005, FTSE 350 UK Food Producer Sector companies financed most of its investments using internal cash flows (see Table 1a & 1b). The POT argues that due to signalling, timing effect and adverse selection premium of debt and equity, debt should dominate as a source of external finance. Thus consistent with the report by Myers (1984), it is observed from Tables 1a & 1b that except for 2002 when there was average reduction of £276.68m in net debt issued and still an average net equity issued of £7.03m, the bulk of FTSE 350 UK Food Producer Sector firms’ external financing takes the form of debt.

Figure 1a. Year-on-year trend in financing pattern

Figure 1b. Year-on-year trend in financing pattern

Whilst Tables 1a and 1b only provide a snapshot of average corporate cash flows of the FTSE 350 UK Food Producer Sector firms in selected years, it is useful to consider the year-by-year trends in the relative use of debt and equity. Figures 1a and 1b show the changing roles of aggregate net debt and net equity relative to financing deficit scaled down by average total assets for the period 2001 to 2005.

As a result of the accounting cash flow identity, it is expected that net debt and net equity should track financing deficit. However, because of the signalling and adverse selection premium of equity, POT predicts that net debt issued should tracks financing deficit more closely than net equity issued. Over the period 2001 to 2005, it is observed from Figure1a that on average net debt tracks financing deficit more closely than net equity only from 2002 to 2004. Bearing in mind that firms raise funds for future investments (presumably starting the following year) and lagging investments by one year, the year-by-year trends as can be seen in Figure1b shows that net debt issued tracked financing deficit more closely than net equity issued only in 2002 and 2004. This result is in alignment with Gurcharan (2010), who indicated that there is an advantage to financing through debt (interest tax shield benefit), and this assertion was supported by Flannery and Rangan (2006) and MM (1963).

4.2. Results of the Empirical Analysis

The models adopted for the regression analyses are based on the model developed by Shyam-Sunder and Myers (1999) and modified by Frank and Goyal (2003). This model is represented by equation (1) and (2) in the methodology section and restated below. The association of financing deficit (DEF) and changes in debt/net debt issued (ΔD) described in the previous chapter is tested using data from FTSE 350 UK Food producer sector firms as follows:

ΔD_it = α + βDEF_it + ε_it Equation (1)

[Aggregate Model-Testing for relation between changes in net debt and financing deficit of FTSE 350 UK Food producer firms]

ΔD_it = α + β₁DIV_it + β₂INV_it + β₃ΔW_it – β₄C_it + εit  Equation (2)

[Disaggregate Model-Testing the relationship between change in debt and components of financing deficit]

In both the aggregate and disaggregate model, the dependent variable is net debt issued (ΔD_it) as proxy for change in debt by firm i at time t. Whilst the independent variable in the aggregate model is financing deficit (DEF_it); dividend paid (DIV_it), net investments (INV_it), change in working capital (ΔW_it) and Internal cash flow (C_it) are the independent variables in the disaggregate model.

4.2.1. Regression Analysis: Change in Debt (ΔD) and Financing Deficit (DEF)

The aggregate model (Equation 1) tests the claim of the pecking order theory that corporate debt is determined by financing deficit. The model is estimated using Ordinary Least Squares method. According to the POT where corporate debt matches financing deficit pound sterling-for-pound sterling (strong form POT) then the coefficient of DEF (β) should be equal to 1 when the intercept (α) is 0. However, debt capacity and other factors may force firms to issue some amount of equity. In such cases it is expected that β be less than, but close to, 1 (semi-strong form) and α not equal to zero.

When the explanatory variables are analysed in the aggregate form as shown in Table 2a, it is expected that the coefficient (β) of DEF is 1 for the strong form of POT and very close to 1 for the semi strong form. On the basis of the aggregate model, the regression results obtained for H₀: α =0 shows that (β) is -0.031 and the R² is 0.003 implying that when α is fixed at 0, the coefficient of DEF is not 1 as predicted by POT. The results obtained for H₀: α ≠ 0 shows that β is 0.143 with an R² of 0.022, when α is 0.013. The semi strong form of POT has it that as a result of some form of equity issue, when the intercept of Equation (1) (i.e. α) is not equal to zero, the coefficient of financing deficit (β) should be less than but close to 1. The regression results prove otherwise. The R² of 0.003 when α is fixed at 0 and 0.022 obtained when α is allowed to randomly determine its value as a result of the regression Eqn (1) indicates that 0.3% and 2.2% of corporate debt  of the FTSE 350 UK food producer sector firms considered in this study are determine by financing deficit.

Table 2b shows the results of the regression based on the aggregate model with average investments lagged by one year based on the assumption that firms raise funds for future investments (presumably starting the following year). A β of -0.310 and an R² of 0.230 was obtained for the fixed H₀: α=0. On the other hand, a β of -0.531 and an R² is 0.291 was obtained for the random H₀: α ≠ 0. Therefore, one can state that for fixed α =0 and random α ≠ 0 only 23% and 29% of corporate debt of FTSE 350 companies is determined by financing deficit when investments are lagged by one year.

For both H₀: α = 0 and H₀: α ≠ 0, even when investments are lagged by one year (see Table 2b), the coefficient (β) of the financing deficit and the R square are very low, suggesting that on the basis of the aggregate Frank and Goyal model (Equation 1), the regression result does not support the POT prediction that corporate debt is determined by the financing deficit.

Table 2a. Regression results for the aggregate FG Model

Table 2b. Regression result for the aggregate FG Model when investments are lagged by 1 year

Notes: The dependent variable Net debt issued as a proxy for Change in debt (ΔD); DEF = Financing deficit; N = number of observations; Standard errors are in brackets; * = coefficients of explanatory variables

4.2.2. Regression Analysis: Change in Debt (ΔD) and Components of Financing Deficit

Prior research on tests of POT stressed the importance of studying separately the impact that each of the components of financing deficit has on debt. This provides a much deeper analysis of the individual roles of the component parts of the financing deficit even though Frank and Goyal (2003) made it clear that disaggregating is not required to validate the POT. Equation 2 tests the relationship between change in debt (ΔD) and each of the explanatory variables; dividend paid, investments, change in working capital and internal cash flows. Table 3a show the result of the Ordinary least squares regression between change in debt and components of the financing deficit, the result of which is summarised in Table 3b.

Table 3a.Regression results for the disaggregate FG Model

Table 3b.Summary: Expected vs. Actual Signs obtained

Based on the POT predictions, a positive relationship is expected between dividend payments (DIV) and change in debt (ΔD). The negative signal obtained does not confirm such prediction, instead it supports the findings of Frank and Goyal (2003) which confirms STT claim that dividend is negatively related to debt.

Amongst the other variables that make up financing deficit, internal cash flow (C) is of significant importance. This variable is the major cause of conflicts between managers and other stakeholders in the firm (Jensen et al., 1992). However, POT argues that it is the best source of financing option implying that a negative relationship is expected between debt and internal cash flow. That is as a firms internal cash flow increase, it issues less debt. On the basis of the disaggregate model, the regression result does not support the pecking order theory prediction that increase in internal cash flows results in lower debt levels.

The pecking order theory has it that after controlling for internal cash flows, investments in fixed assets and working capital should be matched pound sterling-for-pound sterling by increase in debt issues. Therefore, a positive relationship is expected between investments (INV), change in working capital (ΔW) and change in debt (ΔD). The results obtained as per summary Table 3b confirms the POT predictions of a positive relationship on investments in both fixed assets and working capital, and change in debt.

Assuming that firms raise funds for future investments (presumably starting the following year) and lagging investments by one year and performing a regression run between change in debt (ΔD) and the components of financing deficit. The regression result based on the disaggregate model are shown in Table 4a. The results as summarise in Table 4b is somewhat mixed. Whilst the result for H₀: α = 0 shows a negative relationship between change in debt and dividend paid, the signal obtained for H₀: α ≠ 0 is positive supporting the POT prediction that dividend payments are positively related to change in debt. On the other hand, whilst a positive signal is obtained for internal cash flows when α is equal to zero, a negative signal is reported when α ≠ 0 (see Table 4b), thereby supporting the claim by POT that internal cash flows are negatively related to net debt issued (i.e. the more internal funds generated, the less debt required).

A positive relationship is expected between investments, change in working capital and net debt issued. On the basis of the disaggregate model, except for change in working capital (when α = 0), the regression results do not support the fact that change in debt is positively related to investments in fixed assets and change in working capital. Thus, it can be stated that when investments are lagged by one year, the pecking order theory and the static trade-off theory do not best explain the financing behaviour of FTSE 350 UK Food producer sector firms. Under both circumstances the R² obtained indicates that over 90% of change in debt of the sample companies could be explained using components of financing deficit as explanatory variables in a linear mode.

Table 4a. Regression results for the disaggregate FG Model when investments are lagged by 1 year

Table 4b. Summary: Expected vs. Actual Signs obtained

Notes: The dependent variable is ΔD = change in debt/net debt issued; DIV= dividend payments; INV = investments; ΔW = change in working capital; C = internal cash flow; * = coefficients of explanatory variables; Standard errors are in brackets; N= number of observations

4.2.3. Regression Analysis: Determinants of Capital Structure against Total Gearing

The primary purpose of this subsection is to determine whether or not asset tangibility, market-to-book value ratio, firm size and profitability are key determinants of total gearing for the FTSE 350 UK Food producer sector firms.

The average total gearing (D_it) for each of the years considered in this study has been between 32.18% and 33.78% (See Appendix C) implying that average total gearing for FTSE 350 UK Food produce firms has not change significantly over the period 2001 to 2005.

With regards to the determinants of capital structure of the sample firms, average asset tangibility for the period 2001 to 2005 is between 36.22% and 38.32%.  As can be seen in Appendix D1, Summary table, asset tangibility has drop from 38.32% in 2001 to 36.22% in 2005. On the other hand, aggregate market-to-book value ratio (MBV) has somewhat been fluctuating from 1.3411 in 2001 up to 1.4958 in 2002 and down in 2003 to 1.3179. 2004 recorded the highest market-to-book ratio of 1.6050 followed by a market-to-book value of 1.5138 in 2005.

Over the period 2001 to 2005 there has not been any significant change in the year-on-year average firm size. The lowest average firm size of 15.2018 was recorded in 2002 and the highest 15.2549 in 2005. Yearly average profitability ratio for the sample firms has not been very impressive. However, one can state from the summary table that it has been rising year on year from 12.45% in 2001 to 15.41% in 2004, after which it drop significantly to 13.46% in 2005.

The estimated Ordinary Least Square (OLS) regression model used is;

D_it = α + β_TANTAN_it + β_MBVMBV_it + β_LSLS_it + β_PRFPRF_it + ε_it    Equation 3

(Testing for relation between total gearing and firm specific factors)

Table 5a shows the result of the regression analysis between determinants of capital structure and total gearing as per the regression equation (3) when α is taken to be equal to zero and when α is not equal to zero. The dependent variable for the regression as shown in the OLS equation above is total gearing (D_it).

Table 5a. OLS regression results for relation between total gearing and determinants of capital structure

Notes: See Appendix C and D for data used in the regression; All figures are rounded to three decimal places; TAN = asset tangibility; MBV= Market to book ratio; LS = firm size; PRF. = profitability, standard errors are in brackets; N = number of observations; * coefficient of independent variables

Table 5a shows the result of the relationship between total gearing and firm specific factors both for when the intercept (α) of the regression equation (3) is zero and when it is not equal to zero. The regression results obtain for both instances are similar. A positive sign for the coefficient of asset tangibility was obtain thus favouring static trade-off theory (STT) and the argument by Nor et al. (2011), Titman and Wessels (1988), Harris and Raviv (1991). The regression run suggest that FTSE 350 UK Food producer companies to some extend use their assets as collateral to secure their debts.

In line with the POT, a positive relation is expected between market-to-book value ratio (MBV) and gearing. However, on the basis of the OLS regression model, MBV is negatively related to gearing as shown by the negative coefficient obtained. Although the result obtained for MBV does not support the prediction of POT, it is in line with prior studies (i.e.Titman and Wessels, (1988); Chung, (1993); Barclay and Smith (1996)), thus supporting the STT prediction that growth is negatively related to leverage (gearing).

In accordance with the prediction of the POT, a negative relationship between firm size and gearing is expected. On the basis of the regression analysis, the coefficient of the natural logarithm of sales is positive, thus favouring the STT. The results obtained agree with Michaelas et al. (1999) who pointed out that large firms are expected to have more debt than smaller firms as they are less likely to go bankrupt.

According to the POT, retained earnings are a firm’s best choice of source of finance. It is therefore expected that profitable firms would use less debt in financing their investments. The regression results obtain shows that average profitability of FTSE 350 UK Food producer sector firms are positively related to their average total gearing.  This implies that as a result of taxes, bankruptcy and agency costs, the FTSE 350 UK Food producer sector companies on average take on more debt, which is in line with the STT.

A summary of the expected signs of the coefficients of the determinants of capital structure considered in this study as predicted by POT and STT, and the signs of the coefficients actually obtained as a result of the regression run for the Rajan and Zingales (1995) model is shown in the table below.

Table 5b. RZ Model; Expected vs. obtained signs of coefficients of explanatory variables

As can be seen from the summary table 5b, none of the coefficients of the four explanatory variables considered has the expected signs according to the pecking order theory both for when the intercept (α) of equation (3) is zero and when it is not equal to zero. All the explanatory variable coefficients have signs that are consistent with the STT. The R² of 99.99% and 100% obtained for when α is zero and when α is not zero indicates that the variation in total gearing of FTSE 350 UK food producer sector firms can almost 100% be explained using tangibility, market-to-book ratio, firm size and profitability as explanatory variables in a linear model.

In summary, although there is some form of pecking order in the managers of FTSE 350 UK food producer sector firms’ choice of financing, their choices do not fully follow the pecking order theory of capital structure. The result of the empirical analysis also shows that FTSE 350 UK food producer sector firms do not follow POT. In the basic regression of financing deficit, POT was rejected in both the strong and semi strong form. The evidence obtained as a result of the regression of tangibility, growth opportunities, firm size and profitability against total gearing prove that POT does not best explain the financing behaviour of FTSE 350 Food producer sector firms.

5. Conclusion, Implications, Limitations and Further Study

The traditional view of the pecking order is that when external sources of finance are considered in funding investments, debt is preferred to equity. Hence, the prediction by the pecking order theory of capital structure that net debt tracks financing deficit more closely than net equity is not a common/normal trend. The pecking order theory of capital structure argues that a firm’s financing deficit is covered by debt and that equity is only issued as a last resort or in exceptional cases. Evidence shows that corporate debt of FTSE 350 UK food producer firms is not determined by their financing deficit.

Considering the components of financing deficit, the ones that are viewed differently by POT and trade-off theory are dividend and internal cash flow. The result obtained for both dividend and internal cash flow are not in line with POT instead they were totally favouring trade-off theory. The negative signal found for dividend payments supports the idea that dividend could replace debt in reducing agency conflicts. The signal obtained for internal cash flow is positive thus further discrediting the POT and strengthening the support for Static Trade-off Theory (STT). Hence, it can be concluded that corporate debt does not match financing deficit pound sterling-to-pound sterling implying that corporate debt is not determined by the financing deficit.

Asset tangibility and profitability are crucial when deciding between POT and trade-off theory of capital structure (Frank and Goyal, 2003; Fama and French 2002). The study tested the variables in the Rajan and Zingales model and obtained results that does not favour the POT but instead strongly supports the trade-off theory. The study found that the natural log of sales and the market to book value ratio did not behave as foreseen by POT instead the result strongly supports the trade-off theory.

As for asset tangibility which is viewed as a fundamental factor in validating either the POT or the STT by Frank and Goyal (2003), a positive signal was obtained. Also, a positive signal was obtained for profitability, a factor whose behaviour Fama and French (2002) argued should be seen as a cause for unconditionally discarding the STT. The signals for these two variables obtained in the study are congruent with the predictions of the STT and not that of the POT. The positive signal obtained for profitability clearly mirrors the UK economic environment in which these firms operate. It is because of low inflation rate; low borrowing rate and high corporation tax that these companies are liable to pay annually, thus forcing firms to borrow more so as to reduce their tax burdens. 

The main purpose of this study was to evaluate if the pecking order theory of capital structure best explains the financing behaviour of FTSE 350 UK food producer firms. Evidence obtained as a result of this study shows that the financing behaviour of FTSE 350 UK food producer firms is best explained by the trade-off theory and not the pecking order theory of capital structure.

The findings from this study have implications on financing decisions in the area of capital structure for managers, firms and governments:

- Managerial self-interest can affect the financing decision. For example, managers may invest in projects that increases firm size if they will derive some private utility from running a large business which might have a negative impact on shareholder value.

- It is well noted that debt financing can prevent managerial self-serving behaviour since cash flows generated by the assets of the firm cannot all be reinvested. Instead they need to be employed to service the debt. Debt can serve as a bonding device on the part of managers where they commit themselves not to overinvest.

- Firms have been provided with the factors that they must consider relevant in the capital structure decisions. Hence managers will understand the relationship between Trade-Off and Pecking Order Theory to manage their firms operations.

- Managers are recommended to profit from the suggestions of the Pecking Order Theory in decision making on their capital structure based on firms own preference. The firms would in the first place use the internally generated funds (and dividend) to finance their projects in order to avoid the problems caused by risky debts in investments and the information asymmetry between managers and securities markets.

- Governments must understand that firms can achieve much more when there is good governance and strengthening of the institutions which will invariably will have positive effects on business and industry.

The limitation to this study is that the sample size is small compared to prior studies in terms of the number of firms in the sample and time period for firm level data. Moreover, the study discriminates between companies and/or industry sector in that the data is restricted to FTSE 350 UK Food producer sector firms. However, focusing on a particular sector of an industry allows the research to conduct a complete and in-depth study.

Although this study follows the footsteps of many prior studies in the field of capital structure (i.e. testing the pecking order theory of capital structure), it has laid some ground works to explore the determinants of capital structure of FTSE 350 UK Food producer sector. One possible extension for future research is to extend the sample size to include FTSE 350 all share index firms and consider a much longer period for firm level data. Furthermore, a qualitative study can be conducted to explore what influences managers in their financing decisions and choices, whether in fact they have optimal capital structure in mind.

Appendices

Appendix A. Individual firm’s corporate cash flows and trends in financing pattern

TATE & LYLE PLC

Table 1A. Corporate cash flows-Tate & Lyle plc

Table 1B. Corporate Cash Flows of Tate & Lyle with Investment lagged by 1 year

Sources: Annual reports and accounts, Fame database, Perfect analysis & Data stream; *Investments is lagged by one year

ASSOCIATE BRITISH FOODS PLC

Table 1A. Corporate Cash Flow- Associate British Foods Plc

Table 1B. Associated British Foods Corporate cash flow with Investments lagged by 1year

Sources: Annual reports and accounts, Fame database, Data steam, Perfect Analysis, * Investments are lagged by one year.

NORTHERN FOODS PLC

Table 1A. Corporate Cash Flows: Northern Foods Plc

Table 1B. Northern Foods Plc Corporate cash Flows with Investments lagged by 1 year

Sources: Annual reports and Accounts, Fame database, Perfect analysis; *Investments lagged by one year

CADBURY SCHWEPPES PLC

Table 1A. Corporate Cash Flows: Cadbury Schweppes plc

Table 1B. Cadbury Schweppes Plc Corporate cash Flows with investment lagged by 1year

Sources: Annual reports and accounts, Fame database, Perfect analysis database.*Investments lagged by one year

DAIRY CREST PLC

Table 1A. Corporate Cash Flow: Diary Crest Plc

Table 1B. Dairy Crest Plc corporate cash flows with investment lagged by 1 year

Sources: Fame database, Annual reports and accounts and financial reviews, Perfect analysis database, *Investments lagged by one year

UNILEVER (UK) PLC

Table 1A. Corporate Cash Flow; Unilever (UK) Plc

Table 1B. Unilever (UK) Corporate cash flow with investments lagged by 1 year

Sources: Annual reports, Data stream database, Perfect Analysis, Fame Database, *Investments lagged by one year.

Appendix B. Computation of aggregate corporate cash flows

Table1. Cash dividends

Table 2a. Investments

Table 2b. Investments lagged by 1 year

Table 3. Change in working capital

Table 4. Internal Cash flow

Table 5.Net Debt Issued

Table 6. Net Equity Issued

Table 7. Aggregate Total Assets (Book Value)

Notes: The above data are from; Annual reports and accounts (2001-2005) of the companies in the sample, Fame data base, Perfect Analysis, Data stream data.

Appendix C. Total Gearing

Table 1A. Computation of total gearing

Notes:

1. Gearing = ratio of total debt to total assets
2. Data for computing total gearing is obtained from data stream, Fame database and Standard and Poors compustat
3. Total debt =Total of all long and short term debt
4. Total Assets= sum of tangible and intangible fixed assets plus investments and current assets

Table 1B. Average total gearing

Appendix D. Computation of determinants of capital structure

Table 1. Tate & Lyle PLC

Table 2. Associated British Foods PLC

Table 3. Northern Foods PLC

Table 4. Cadbury Schweppes PLC

Table 5. Dairy Crest PLC

Table 6. Unilever (UK) PLC

Notes:

1. Source of data: Data stream database, Fame database, Perfect Analyse database, The Pinsent Mansons Company Guide, Annual Reports and Accounts
2. MV = This is the overall value of a company, i.e. the price that one must pay to buy the entire company.
3. EBITDA =The earnings if the company before all interest expense, depreciation, amortisation and provision
4. TA =The total net tangible fixed assets after deduction of accumulated depreciation
5. ECR =Equity share capital and reserves of the company
6. TA= sum of tangible and intangible fixed assets plus investments and current assets

Appendix D1. Average determinants of capital structure

Table 1. Average Tangibility (TAN)

Table 2. Average Profitability (PRF)

Table 3. Average Firm size (LS)

Table 4. Average Market-to-book ratio (MBV)

Table 5. Summary table - average determinants of capital structure

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