The Effect of Inflation Uncertainty on the Capital Structure of Non-Financial Firms

Transcription

1 Pal. Jour. V.16, I.3, No , Copyright 2017 by Palma Journal, All Rights Reserved Available online at: The Effect of Inflation Uncertainty on the Capital Structure of Non-Financial Firms Reza Tehrani, Associate Professor, Faculty of Management, University of Tehran, Tehran, Iran Sara Najafzadeh Khoee Corresponding Author,Master of Financial Management, Faculty of Management, University of Tehran, Tehran, Iran Abstract The study of capital structure attempts to explain the mix of securities and financing sources used by corporations to finance real investments. Most of the research on capital structure has focused on the internal variables in order to describe firm specific characteristics influencing their preferences between debt and equity. Recent researches in this area has shown that macroeconomic condition has a significant effect on financing decisions. To our knowledge there is no study which has considered the effect of macroeconomic uncertainty on Iranian firms leverage. As inflation affects economies in various positive and negative ways, we tried to shed light on the effect of uncertainty over future inflation on the capital structure of non-financial firms listed in Tehran Stock Exchange. We used a sample of 186 manufacturing firms for the period from 2007 to 2014 with applying an EGARCH model to proxy for uncertainty. In this paper we used a fixed effect regression and the effect of inflation uncertainty on every firm in the sample was estimated separately. The results revealed that inflation uncertainty had a negative effect on the leverage of more than 50 percent of the firms in the sample, while others were positively affected by this type of uncertainty. Key words: Capital Structure, Inflation Uncertainty, ARCH, EGARCH, Panel Regression. Introduction Decades of intensive research in the field of capital structure and several theories in the finance literature trying to recognize new factors influencing on financing decisions has made capital structure as one of the main puzzles in finance. The importance of capital structure lies with the fact that it affects firms value. The aim of conventional corporate financial theory when making decisions is to maximize the value of the business or firm and all of corporate finance is built on three decisions including the investment decision, the financing decision, and the dividend decision. Any decision (investment, financial, or dividend) that increases the value of a business is considered a good one, whereas one that reduces firm value is considered a poor one [1]. Therefore considering the financing choice of a company as one of its major decisions which will have substantial effects on the cost of capital and consequently on its value is vital and of high importance. The debt equity decision is one of the most researched areas in finance and the capital structure determinants have been in the center of attention in the past decades. Over the years, research in capital structure has enhanced the overall perceiving of how firms make their financing decisions [2], [3], [4], [5], [6], [7], [8], [9]. However there is no universally accepted theory which can fully explain a firm preference in choosing financial resources [10]. The primary studies used to give consideration to the special firm characteristics. Based on these studies, there are almost similar agreements on the key internal factors affecting capital structure including profitability, firm size, asset structure, liquidity, growth opportunities, uniqueness, industry classification, earning volatility and stock return [10],[11], [12], [13], [14],while recent surveys have started to investigate external factors affecting debt-equity ratio which are mostly associated with Macroeconomic conditions. Frank and Goyal (2003) have come to conclusion that around 30 percent of differences in the capital structure inside the country can be explained by internal determinants, which posits that there are other factors than internal determinants influencing financing choices [15]. Hackbarth et al. (2006) revealed that macroeconomic conditions have considerable impacts Palma Journal

2 524 R.Tehrani and S.N.Khoee, on target capital structure [10]. Internal factors and their impacts can be managed by the firm, while macroeconomic factors cannot be controlled by managers and both types of determinants have significant effects on the corporate capital structure. Being aware of the level, direction and power of their impacts can help companies to make effective decisions according capital structure for the aim of financial stability and sustainable growth [16]. With considering the fact that external sources of financing are directly affected by the macroeconomic conditions while firm characteristics including probability of bankruptcy, profitability and capital investment are indirectly influenced by stages of life cycle via cost of capital, cash flows, leverage and the balance sheet components, it is implied that the target capital structure and its adjustments are both directly and indirectly affected by macroeconomic conditions and different stages of corporate life cycle [10]. Furthermore, a firm s financing choices might change as it makes the transition from a start-up firm to a mature firm to final decline. Typically, startup firms and firms in rapid expansion use debt sparingly; in some cases, they use no debt at all. As the growth eases and as cash flows from existing investments become larger and more predictable, we see firms beginning to use debt. Debt ratios typically peak when firms are in mature growth [1]. As we can see, global attention has been rising to consider other important variables which are necessary for managers prospects when making financing decisions, Inflation affects economies in various positive and negative ways and Iran is a country dealing with the issue of high inflation rate which will produce high inflation uncertainty so in this research we are trying to extend the literature on the effect of inflation uncertainty on the capital structure by using a panel data of 186 firms listed in Tehran stock exchange covering a period from 2007 to The rest of the paper is organized as follows; Section 2 discusses relevant literature. Section 3 describes the data and the research methodology used in this paper. Section 4 reports the empirical results and Section 5 summarizes and concludes the paper. Literature review One of corporate finance best-known theorem is written by the Modigliani-Miller theorem (1958). In their first model, they argued that in a frictionless world with no taxes, transaction costs and possibility of default, the value of a firm is unaffected by its leverage. However, they ultimately reversed this claim, explaining that leverage has a positive effect on the value of the firm and it is maximized when a firm is entirely financed with debt [3]. Miller and Modigliani were pioneers in moving capital structure analysis from an environment in which firms picked their debt ratios based on comparable firms and management preferences, to one that recognized the trade-offs. The trade-off theory of capital structure recognizes that target debt ratios may vary from firm to firm. This trade-off theory states, despite the fact that existing debt in the capital structure of firms creates tax shield and increases its value, risk increases as the firm adds debt to the capital structure. Providing tax shield and being a cheaper source of financing, make Debt beneficial for firms at low levels, But when large amounts of debt is taken on, the firms commence to be financially distressed by trying to meet interest payment obligations [17]. So according to this theory, capital structure decisions depend on benefits and costs of utilizing more debt [18]. Harkbarth et al. (2006) claimed that, if a firm determines its optimal capital structure by balancing the related benefits and costs of debt, then both benefits and costs should depend on macroeconomic conditions; the expected benefit of debt which is also used for the purpose of reducing the agency conflicts between managers and shareholders depends on whether there is an economic expansion or recession since it effects on the level of corporate cash flows. Further, expected costs of debt (bankruptcy costs and agency conflicts between creditors and shareholders) depend on probability of default and loss given default both of which should depend on the current state of the economy [15]. Myers and Majluf (1984) presented the pecking order theory which starts with asymmetric information indicating that managers know more about their companies prospects, risks, and values than do outside investors. Asymmetric information affects the choice between internal and external financing and between new issues of debt and equity securities. This leads to a pecking order, in which investment is financed first with internal funds, reinvested earnings primarily; then by new issues of debt; and finally with new issues of equity [19]. Myers and Majluf (1984) anticipated that leverage decreases with the increase of free cash flow [18]. Many studies have investigated the relation between capital structure and firm-level determinants and they have introduced almost a same set of factors. Mokhova &

3 Uncertainty on the Capital Structure of Non-Financial Firms 525 Zinecke (2014) have found that external determinants of capital structure play a substantial role in financial decision-making process and the knowledge about the power and direction of such influence supports managers to make effective and accurate financial decision for stable and successful development [10], [15], [20], [21], [22], [23], [26]. Mokhova & Zinecker (2014) have considered the effect of external factors on the capital structure. GDP is one of the most used external factors. As a rule, during the period of economic expansion, when interest rates are rising, banks are willing to increase loans to private sector, therefore, financial leverage should rise [16] but according to the pecking order theory, when product market goes up, it leads to more retained earnings therefore the use of debt will decrease [20]. Inflation rate is another external factor being considered in the researches. Inflation is expected to have a positive effect since it increases the true value of tax deductions on debt [22]; [23]. Camara (2012) has showed that inflation is negatively related to leverage since cost of borrowing will increase in the inflationary condition. Another variable which is suspicious to be related to leverage is exchange rate. The exchange rate sensitivity affects the firm value and its stock price. This would occur due to the adjustments of firms cash flows according to the fluctuations in foreign exchange rate. For instance the profit of an exporting firm is more likely to decrease based upon the appreciation of domestic currency and so is its value, therefore the firm ought to use external sources of financing. Since the stock price has been fallen, the issuance of new equity does not make sense and due to the reduction of profit, investors will not be interested in buying new shares, so borrowing would be a better choice, in this condition the amount of debt would increase. The macroeconomic environment has significant effects on the growth and financial performance of firms. The economic cycle for example has been discovered to affect profitability, leverage, cash flow and by means of that influence company failures. Bhattacharjee et al. (2009) have studied US and UK firm exits through bankruptcies and acquisitions and have discovered that both modes of exit depend on the macroeconomic environment, specifically, macroeconomic instability [24]. Baum et al. (2006) argued that higher uncertainty will obstruct managers ability to predict firm-specific information such as expected future cash flows. They showed that macroeconomic uncertainty signaling increased uncertainty hampers efficient use of resources. They also found that Firms experiencing rapid growth, firms that are financially constrained and capital-intensive firms are found to be quite sensitive to macroeconomic uncertainty. As we can see, macroeconomic condition seems to be an important factor for firms when deciding to overcome their financial needs.in this paper, we are interested to investigate the effect of inflation uncertainty on the capital structure. Data and methodology This paper is based on the evidence of firms listed in Tehran stock exchange and the sample contains 186 non-financial firms for the period All of the companies in the sample are calendar-year taxpayers and the debt to equity ratio which is considered as a proxy for capital structure, is positive. Availability of appropriate information was another selection requirement, therefore companies which had all required data for the period were selected. The required data of financial statements were obtained from official Tehran stock exchange database and the data of inflation including inflation rate was provided by central bank of Islamic Republic of Iran database. An EGARCH model was used to proxy for inflation rate uncertainty. Based on the literature this approach seems more appropriate comparing to other proxies which are derived from moving standard deviations of macroeconomic series or those that are based on the dispersion of forecasts [13]. We employed a panel data regression given as Eq. 1: Yit i X it Uit (1) Where i is the individual dimension and t is the time dimension. Y is the dependent variable which is a measure of capital structure. We have data of 186 firms for 8 years so our total observation is We have checked the stationary of inflation variable by using unit root test. The stationarity or otherwise of a series can strongly influence its behavior and properties and the use of non-stationary data can lead to spurious regressions. Stationary series can be defined as one with a constant mean, constant variance and constant autocovariances for each given lag which is the concept of weak satationarity. The early and

4 526 R.Tehrani and S.N.Khoee, pioneering work on testing for a unit root in time series was done by Dickey and Fuller [25]. Based on the Augmented Dickey-Fuller test, inflation rate had a unit root,therefore its first difference was utilized. Autocorrelation and partial autocorrelation functions were applied for modeling the inflation rate and the results showed AR (1) for inflation, details are shown in table 1. Table 1: Modeling the inflation rate Variable Coefficient Std. Error t-statistic Prob. C INF(-1) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat Prob(F-statistic) The results from using Autoregressive conditionally heteroscedastic (ARCH) model revealed that the variance of errors of inflation is not constant at the 95 percent confidence interval, see table 2. If the variance of the errors is not constant, this would be known as heteroscedasticity, if the errors are heteroscedastic, but assumed homoscedastic, an implication would be that standard error estimates could be wrong. It is unlikely in the context of financial time series that the variance of the errors will be constant over time, and hence it makes sense to consider a model that does not assume that the variance is constant, and which describes how the variance of the errors evolves [25]. Table 2: Heteroskedasticity Test: ARCH- inflation rate F-statistic Prob. F(1,19) Obs*R-squared Prob. Chi-Square(1) In order to calculate inflation uncertainty, we used an EGARCH model which was proposed by Nelson (1991) which is shown by Eq. 2: 2 2 u u t t (2) ln( t ) ln( t 1) 2 2 t 1 t 1 This model has several advantages over the pure GARCH specification. First, since the log (σ 2 t ) is 2 modelled, then even if the parameters are negative, σ t will be positive. There is thus no need to artificially impose non-negativity constraints on the model parameters. Second, asymmetries are allowed for under the EGARCH formulation [25]. The EGARCH model of inflation rate is shown in tables 3, respectively. The unit root test was also applied for the dependent variable and non-stationarity problem was not seen among them. Table 3: EGARCH model-inflation rate Variable Coefficient Std. Error z-statistic Prob. C AR(1) Variance Equation C(3) C(4) C(5) C(6) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter Durbin-Watson stat

5 Uncertainty on the Capital Structure of Non-Financial Firms 527 Empirical Results Hausman and Chaw tests were applied in order to see whether a fixed effect or a random effect model is appropriate. Based on these tests, a fixed effect model is preferred, see table 8 and 9. Table 4: Hausman test Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob Cross-section and random effect Table 5: Chaw test Effects Test Statistic d.f. Prob. Cross-section F (185,1295) Cross-section Chi-square The results of the fixed effect regression is presented in Table 10. It appeared that inflation uncertainty had a negative effect on the capital structure of 55 percent of the firms in the sample. The R-squared of the model is 84 percent which implies that 84 percent of variations in the dependent variable is explained by inflation uncertainty and the probability of F-statistic is zero which shows that the estimated model is significant. In explaining the negative effect of inflation uncertainty on corporate capital structure we can say that Inflation rate uncertainty would increase the firm s business risk by increasing the volatility of the firm s volume of sales, product and input prices. Therefore the volatility of the firm s operating income and its probability of bankruptcy will increase. In appointing the optimal capital structure, it is very important for the management to consider the size and the stability of the firm s cash flows relative to the fixed charges associated with the use of debt. Hence in a highly inflationary environment with heightened inflation uncertainty, a firm which is facing high business risk and uncertain cash flows and needs to raise funds for its investments, may choose to issue new equity and it will decide to keep some unused debt capacity for the future in order to maintain some flexibility. Otherwise, if the firm decides to borrow for its capital needs, it may be forced to issue new shares on unfavorable terms in the future [26]. Assaf (2014) found the same results as Hatzinikolaou et al, (2002), in his master thesis. He considered the effect of inflation uncertainty and discovered that Inflation uncertainty reduces leverage exogenously. It increases business risk, which refers to more volatile operating income, causing tax-shields to become more uncertain. Consequently, reduces the use of debt [27]. In explaining the positive effect of inflation uncertainty, this can be argued that inflation uncertainty increases inflation rate which will increase stockholders expected rate of return, in this case the price of shares will decrease, with increasing stockholders expected rate of return, WACC will rise so most of projects will have negative NPVs and they will not be implemented by firms hence it will have negative effect on GDP growth and this will have a negative effect on capital market so firms will prefer to finance their needs via money market [16]. Table 6: Fixed Effect Regression Variable Coefficient Prob. Variable Coefficient Prob. C _94--UNCINF _1--UNCINF _95--UNCINF _2--UNCINF _96--UNCINF _3--UNCINF _97--UNCINF _4--UNCINF _98--UNCINF _5--UNCINF _99--UNCINF _6--UNCINF _100--UNCINF _7--UNCINF _101--UNCINF _8--UNCINF _102--UNCINF _9--UNCINF _103--UNCINF _10--UNCINF _104--UNCINF _11--UNCINF _105--UNCINF _12--UNCINF _106--UNCINF _13--UNCINF _107--UNCINF _14--UNCINF _108--UNCINF _15--UNCINF _109--UNCINF

6 528 R.Tehrani and S.N.Khoee, _16--UNCINF _110--UNCINF _17--UNCINF _111--UNCINF _18--UNCINF _112--UNCINF _19--UNCINF _113--UNCINF _20--UNCINF _114--UNCINF _21--UNCINF _115--UNCINF _22--UNCINF _116--UNCINF _23--UNCINF _117--UNCINF _24--UNCINF _118--UNCINF _25--UNCINF _119--UNCINF _26--UNCINF _120--UNCINF _27--UNCINF _121--UNCINF _28--UNCINF _122--UNCINF _29--UNCINF _123--UNCINF _30--UNCINF _124--UNCINF _31--UNCINF _125--UNCINF _32--UNCINF _126--UNCINF _33--UNCINF _127--UNCINF _34--UNCINF _128--UNCINF _35--UNCINF _129--UNCINF _36--UNCINF _130--UNCINF _37--UNCINF _131--UNCINF _38--UNCINF _132--UNCINF _39--UNCINF _133--UNCINF _40--UNCINF _134--UNCINF _41--UNCINF _135--UNCINF _42--UNCINF _136--UNCINF _43--UNCINF _137--UNCINF _44--UNCINF _138--UNCINF _45--UNCINF _139--UNCINF _46--UNCINF _140--UNCINF _47--UNCINF _141--UNCINF _48--UNCINF _142--UNCINF _49--UNCINF _143--UNCINF _50--UNCINF _144--UNCINF _51--UNCINF _145--UNCINF _52--UNCINF _146--UNCINF _53--UNCINF _147--UNCINF _54--UNCINF _148--UNCINF _55--UNCINF _149--UNCINF _56--UNCINF _150--UNCINF _57--UNCINF _151--UNCINF _58--UNCINF _152--UNCINF _59--UNCINF _153--UNCINF _60--UNCINF _154--UNCINF _61--UNCINF _155--UNCINF _62--UNCINF _156--UNCINF _63--UNCINF _157--UNCINF _64--UNCINF _158--UNCINF _65--UNCINF _159--UNCINF _66--UNCINF _160--UNCINF _67--UNCINF _161--UNCINF _68--UNCINF _162--UNCINF _69--UNCINF _163--UNCINF _70--UNCINF _164--UNCINF _71--UNCINF _165--UNCINF _72--UNCINF _166--UNCINF _73--UNCINF _167--UNCINF _74--UNCINF _168--UNCINF _75--UNCINF _169--UNCINF _76--UNCINF _170--UNCINF _77--UNCINF _171--UNCINF _78--UNCINF _172--UNCINF

7 Uncertainty on the Capital Structure of Non-Financial Firms 529 _79--UNCINF _173--UNCINF _80--UNCINF _174--UNCINF _81--UNCINF _175--UNCINF _82--UNCINF _176--UNCINF _83--UNCINF _177--UNCINF _84--UNCINF _178--UNCINF _85--UNCINF _179--UNCINF _86--UNCINF _180--UNCINF _87--UNCINF _181--UNCINF _88--UNCINF _182--UNCINF _89--UNCINF _183--UNCINF _90--UNCINF _184--UNCINF _91--UNCINF _185--UNCINF _92--UNCINF _186--UNCINF _93--UNCINF Effects Specification Cross-section fixed (dummy variables) Weighted Statistics R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid F-statistic Durbin-Watson stat Prob(F-statistic) Conclusion Managers make their financial decisions according to the sources of financing based on both macroeconomic conditions and firm specifics characteristics. Most of the research on capital structure has focused on the internal variables in order to describe firm specific characteristics influencing their preferences between debt and equity. Recent researches in this area has proved that macroeconomic condition has a significant effect on financing decisions. To our knowledge there is no study which has considered the effect of macroeconomic uncertainty on Iranian firms leverage. As inflation affects economies in various positive and negative ways, we tried to shed light on the effect of uncertainty over future inflation on the capital structure of non-financial firms listed in Tehran Stock Exchange. We used a sample of 186 manufacturing firms for the period from 2007 to 2014 with applying an EGARCH model to proxy for uncertainty. In this paper we used a fixed effect regression and the effect of inflation uncertainty on every firm in the sample was estimated separately. The results revealed that inflation uncertainty had a negative effect on the leverage of 55 percent of the firms in the sample which can be implied that Higher inflation uncertainty will increase firms business risk and the volatility of their revenues and costs, in this case the probability of bankruptcy will rise, therefore firms will use less debt in their capital structure. In explaining the positive effect of inflation uncertainty, this can be argued that inflation uncertainty increases inflation rate which will increase stockholders expected rate of return, in this case the price of shares will decrease, with increasing stockholders expected rate of return, WACC will rise so most of projects will have negative NPVs and they will not be implemented by firms hence it will have negative effect on GDP growth and this will have a negative effect on capital market so firms will prefer to finance their needs via money market [16]. References Damodaran,A. (2010). Applied Corporate Finance (3rd Ed.). WILEY. Modigliani, F. & Miller, M. (1958).The cost of capital, corporation finance and the theory of investments. American Economic Review, 48, Modigliani, F. & Miller, M. H. (1963).Corporate income taxes and the cost of capital, American Economic Review, pp Jensen, M., & William Meckling. (1976). Theory of the firm: Managerial behavior, Agency costs and ownership structure, Journal of Financial Economics, 3, Myers, S. C. (1977). Determinants of corporate borrowing. Journal of Financial Economics, 5, Myers, S. C. & Majluf, N. (1984). Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics 13, Stulz, R. (1990). Managerial discretion and optimal financing policies. Journal of Financial Economics, 26, Ross, S. A. (1977). The determination of financial structure: The incentive-signaling approach. Bell Journal of Economics and Management Science, 8,

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