Effect of Macroeconomic and Market Variables on the Financial Distress of Listed Companies

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Effect of Macroeconomic and Market Variables on the Financial Distress of Listed Companies

Effect of Macroeconomic and Market Variables on the Financial Distress of Listed Companies: Evidences from Tehran Stock Exchange

Abstract

In this study, using an econometric model we investigate the impact of macroeconomic conditionsbesides the market conditions on the financial distress of listedcompanies. Our studied companies were pharmaceutical companies listed in Tehran Stock Exchange during 2005-2013. By using panel data analysis, our results showed that there is positive relationship between “retail/consumer price index”, “bank deposit interest rate”, “total bank credit”, and “rate of GDP growth” with financial distress.Also, we found a negative relationship between “real stock price index”, and “real rate of return”, with business failure.In this regard, we concluded that macroeconomic factors and market variables have significant impact on financial distress of listed companies.

Keywords: Economy, financial distress, macroeconomic conditions, stock companies, Tehran Stock Exchange

1. Introduction

Corporate failure or bankruptcy is one of the most important problems facing auditors, consultants, management and government policy makers(O’Leary 1998). This is an issue that will affect the economy of any country. Today, the number of failed firms is important for the economy of a country and is considered as an indicator of development and economic power (ZopounidisDimitras 1998). In the financial sphere, a firm is considered as financiallydistressedwhen having difficulty in meeting obligations to creditors.The chance of financial distress increases when a firm has high fixed costs,illiquidassets, or revenues that are sensitive to economic downturns. Liabilities of a company may be used for financing operations, but by doing so, firms are more at risk of experiencing financial distress;therefore, if the firm does not resolve financial distress, it leads to bankruptcy (Higgins 2007).Gordon (1971) defined financial distress as the decrease in the firm's profitability which increases the inability to repay the principal and interest on debts. Bankruptcy isoften used interchangeablywith financial distress.

“More firms enter financial distress as a result of poor management than as a result of economic distress;…In the early stages of financial distress, median firm operating income is measured on an unadjusted basis and after controlling other factors which significantly alter the increase in the firm performance” (Whitaker 1999). According to Jensen (1989), financial distress is a corrective action which improves firm performance. A company under financial distress can incur costs related to the situation, such as more expensivefinancing, opportunity costs of projects andless productive employees. The firm's cost of borrowing additional capital will usually increase, making it more difficult and expensive to raise the much needed funds. In an effort to satisfy short-term obligations, management might pass on profitable longer-term projects. Employees of a distressed firm usually havelower moraleand higher stress caused by the increased chance ofbankruptcy, which would force them out of their jobs. Such workers can be less productive when under such a burden. Newton (1998) divided the causes of financial distress and bankruptcy into two categories of intra-organizational and extra-organizational reasons. According to him, extra-organizational factors are: (a) the economic system properties, (b) the competition, (c) changes in business transactions, and improvements and transfers in public demands, (d) commercial fluctuations, (e) financing, and (d) unexpected events. On the other hand, intra-organizational factors are: (1) the excessive construction and development of credit (2) inefficient management, (3) insufficient capital, and (4) treason and fraud. The economic downturn, changes in interest rates, rising inflation, fluctuations in raw material prices and international economic conditions, government decisions, unwanted natural events and organization age phase are another reasons of financial distress and bankruptcy (Daraei Ghadikolaei2015). Altman(1971) used difference regression analysisintroduced macroeconomic and microeconomic factorsas the reasons for financial failure. Macroeconomic factor is a pertinent to a broad economy at the regional or national level and affects a large population rather than a few select individuals. Macroeconomic factors includeunemployment, inflation, savings and investment,economic activity, economic growth, banking facilities, and national monetary policy.Whilemacroeconomicsdeals with the economy as a whole,microeconomicsis concerned with the study of individual agents such as consumers and businesses and their economic decision-making. In developing countries such as Iran where macro-economic environment faces a state of instability in the adoption and implementation of economic policies, the role of macroeconomic factors in the firm performance can be as equal as microeconomic factors.

Financial distress of the companies is the subject of a great deal of study. Jostarndt Sautner (2008) empirically investigated the effect of financial distress on corporate ownership and control on German firms that suffered from repeated interest coverage shortfalls. They found a significant decrease in ownership concentration. Private investors gradually gave up their dominating role and thereby ceased to be an effective source of managerial control. By contrast, ownership representation by banks and outside investors almost doubled. Shareholdings by executive and non-executive directors also substantially increased but had no effect on managerial tenure. Li Liu (2009) conducted a study to find out the exact determinants of financial distresssof Chinese listed companies by using a panel data set containing information on the stock market under Binary Logit Model. They discovered that corporate governance, agency costs and ownership structure are important factors affecting the probability of financial distress. Shimizu (2011) in his study suggested that small banks enhance rate from the financial distress and reduce the bankruptcy ratio of small firms. Kordestani et al. (2011) provided a model to predict company’s financial distress on the basis of the operational, investment and financing components of its cash flow statement. They showed that there is significant difference in incidence rate of financial distress among the companies with different cash flow composition in one, two and three years before distress. McNamara et al. (2012) used both macroeconomic variables and firm specific variables in explaining corporate failure. The results suggested that including economic variables improve the explanation of failure by ten percent. The economic variables included in the analysis were one-year lag in change in GDP, a two-year lag in interest rates, a one-year lag in the share price index, and a one-year lag in corporate profits. Tykvová Borell (2012) examined the financial distress risks of European companies.Their results indicated that the private equity investors select companies which are less financially distressed than non-buyout companies. They also noted that when companies are backed by experienced private equity funds, their bankruptcy rates are even lower. Achim et al. (2012) developed a statistical model for prediction of bankruptcy risk namely Principal Component Analysis, and showed that the global financial crisis more influence the listed companies. Tinoco Wilson (2013) developed risk models for listed companies to predict financial distress and bankruptcy. The results showed the utility of combining accounting, market and macro-economic data in financial distress prediction models for listed companies.

In this study, given the above materials and considering precious studies, our purpose is to investigate the effects of the macro-economic factors including financial ratios, on financial distress of pharmaceutical listed companies in Iran subject to Article 141 of the Iranian AmendmentBill ofCommercial Code which says: “In the case of the loss of a minimum of half the company's capital, the board of directors is bound to call an extraordinary general meeting immediately, with a view to deciding whether the company shall be wound up or shall continue its operations. If the said general meeting turns down the winding- up of the company with observance of the regulations laid down in Article 6 of this Act, the company's capital will be decreased. If, contrary to the foregoing article, the board of directors have not called a general meeting or if the meeting is not convened in conformity with the regulations, any interested person may apple to the competent court for the winding-up of the company.”

2. Materials and Method

2.1. Macroeconomic factors

In this research,macroeconomic factors include: inflation, andeconomic growth. Inflation is the rate of change of prices for goods and services. It influences the interest rate on savings, mortgages and also affects the level of state pensions and benefits.Inflation is measured as an annual percentage increase. Economic growth is the increase in the inflation-adjusted market value of the goods and services produced by aneconomyover time. Human resources, increase of investment and population, and technological development are some of important factors affecting economic growth of a country. It is measured as the percent rate of increase in real gross domestic product (GDP).

2.1.1. Financial ratios

Retail/consumer price index (RCPI):Both the Consumer Prices Index (CPI) and the Retail Prices Index (RPI) measure inflation. RPI measure changes in average retail prices of a fixed basket of goods and services representing household consumption.Like CPI, RPI looks at the prices of items we spend money on, but it includes housing costs - such as council tax - and mortgage interest payments.RCPI can be calculated as following:

(1)

Where is consumer prices index in the period t, and is consumer prices index in the period t-1.

Bank deposit interest rate (DIR):Deposit interest rate is the rate paid by commercial or similar banks for demand, time, or savings deposits. The terms and conditions attached to these rates differ by country. The high rate of deposit interestfirstly cause investors to deposit in banks rather than to invest directly in stock, and secondly, since this rate has high correlation with the amount of bank credits, borrowing from banks becomes more difficult for the firms.

Total Bank credit (TBC):It is defined asthe amount of credit available to a company or individual from the banking system. It is the aggregate of the amount of fundsfinancial institutionsare willing to provide to an individual or organization. Its high amount means more and easier access to bank credits for the companies.This index reflects the macroeconomic and financial development in the industry.

Rate of GDP growth (RGDP): It showsthe rate of growth of the value of all final goods and services produced within a country in a given year.Economic growth does not necessarily mean economic growth of the private sector; for this reason, in this study, we considered economic growth of the industry instead of that of a country. Its high rate indicates favorable business environment for companies in the industry. Its statistics can be obtained from workshops census by the Statistics Center.RGDP can be calculated as following:

(2)

Where representsgross domestic product rate in the period t, and is gross domestic product rate in the period t-1.

2.2. Market variables

Realstock price index (RSPI):Stock price index(SPI), is a simple measure used to monitor the variation of the stockprice.to realize stock price index, nominal value of the stock price is divided by the CPI and then multiplied by 100. With high value of stock price index, itis expected to reduce the probability of financial distress of the company.

Real Rate Of Return (RET): It is measured as the percent rate of increase in RSPI(formula: nominal rate - inflation rate). It is expected to yield a high amount of negative impact on the probability of financial distress.

2.3. Research method

This research is an applied study in terms of goal, a field study in terms of data collection, a descriptive survey in terms of nature, and a cross–sectional (correlational) study in terms of time.It should be noted that his paper was extracted from the authors’ MSthesis. Our purpose is to investigate the relationship between the macroeconomic variables and financial distress in the listed companies.Our study samples are consisted of pharmaceutical companies listed on Tehran Stock Exchange during 2005-2013 those presented financial statements on an annual basis. We used library method (thesis, national and international papers) to collect the required data related to literature by visiting central libraries of the University of Tehran, and Sharif University of Technology. For gathering data related to study indicators, we used financial statements, and databases of studied companiesas well as Iran’s central bank and statistics center. After the extraction of the required data from the information systems, data were categorized and summarized and saved as afileinExcel, and then used to calculate the independent and dependent variables of the study. According to the research objectives and research questions, the model used in this is regression model (panel data) based on the classical principles of econometrics as shown below:

In the model, is dependent variable (financial distress). According to Article 141 of the Iranian AmendmentBill ofCommercial Code, with the loss of a minimum of half the capital, the company is considered as a failed corporate. Y value for such firms is considered as1, and for non-failed firmsit is zero.Toestimate the model, we used Eviews 8 Software.To analyze data we used statistical methods including panel data analysis, regression techniques, correlation and heteroskedasticity tests.

3. Results and Discussion

3.1. Statistics of research variables

Table 1 shows the descriptive statistics of the variables in the panel data regression model.

Table 1. Descriptive statistic of the studyvariables

Yit / RCPI / DIR / TBC / RGDP / PSPI / RET
Mean / 0.500 / 19.600 / 18.056 / 2473924.000 / 0.024 / 23944.990 / 0.052
Median / 0.500 / 18.400 / 17.500 / 2103916.000 / 0.041 / 12536.700 / 0.000
Max / 1.000 / 34.700 / 20.000 / 4292095.000 / 0.072 / 78398.100 / 2.229
Min / 0.000 / 10.800 / 16.000 / 832831.700 / -0.073 / 7966.500 / -2.332
SD / 0.500 / 8.518 / 1.608 / 1188047.000 / 0.045 / 21511.510 / 0.537

3.2. Panel data analysis

3.2.1. Unit root testing

Most of the economic theories express the long-term relationship among the variables in a level form. To ensure the existence of a long-term relationship among the variables in the model, the variables should be stationary. To test stationary of the variables, we usedLevin-Lin-Chu (2002)Test (LLC), because it is appropriate for small panelswith short time series. Also, LLC is more powerful than IM-Pesaran-Shin (IPS) test (Westerlund Breitung, 2009) . The results of testing panel unit roots showed that all variables arestationary (I(0))(see table 2), so H0 which says each time series contains a unit root is rejected and H1 which says each time series is stationary, is confirmed.

Table 2.Stationarity test of study variables using LLC method

Variable / Prob. / Statistic
RCPI / 0.0000 / -4.3138
DIR / 0.0002 / -3.5325
TBC / 0.0000 / -9.4663
RGDP / 0.0000 / -7.3702
PSPI / 0.0000 / -9.90403
RET / 0.0000 / -18.0640

3.2.2. Panel model estimation

Before testing our hypothesis, first it must be discussed whether the data are panel data or pooled data. To do this, F-Limer test was used where H0: There are equal intercepts, and H1: at least one of the intercepts is different with the others. H0 is based on pooled data method and H1 is based on panel data method if the calculated F is larger than critical F in the table, H0 is rejected and using panel data method is recommended, otherwise it is better to use pooled data.

F-Limer statistic was reported as 1.43 with a probability of zero; thereforewe should use panel data. Now to choose between fixed effects or random effects method for panel data estimation, we use Hausman test where H0: there is no correlation between individual effects and explanatory variables and estimation of generalized least squares is consistent. In H1, it is inconsistent. In other words, H0 shows consistency of the coefficients while H1 rejects this consistency. If H0 is rejected by doing Hausman test, the used method for estimation will be fixed effects method. The value of Hausman test was reported as 43.96 with zero probability which indicates the use of fixed effects method.After choosing the estimation model, now we estimate the panel data by using the generalized least squares (GLS) method whose results summary are presented intable 3.Lagrange multiplier (LR) test is an estimator for heteroscedasticity of variance and has chi-square distribution.

Table 3.Results of estimating panel data model

Variable / Coefficient / Z-statistic / Prob.
Constant / -1.122715 / - 6.46.900 / 0.0000
RCPI / 1.164827 / 5.925777 / 0.0000
DIR / 0.538353 / 3.285792 / 0.0000
TBC / -1.004262 / -6.004960 / 0.0000
RGDP / -1.318770 / -7.110569 / 0.0000
PSPI / -1.603373 / -7.406877 / 0.0000
RET / -2.034255 / -9.048067 / 0.0000
LR / 271.3269 / 0.0000
R2 / 0.6388
Total observations = 432

According to the results, the independent variables generally were able to explain the variations in the probability of financial distress in listed companies by 63%. This is show the relationship between financial distress and macroeconomic Factors. In addition, LR statistic with a value of 271.33 and zero probabilityindicates that all the coefficients of the variables cannot be simultaneously equal to zero. Moreover, all the estimated coefficients in the model are at a 99% confidence level. Table 4 presents marginal effects of variables.

Table 4.Results of the marginal effects of variables

Variable / Marginal effect
RCPI / 0.3790
DIR / 0.1752
TBC / -0.3268
RGDP / -0.4291
PSPI / -0.5217
RET / -0.6619

Based on the results, it can be said that there is a positive and significant relationship between RCPI and the probability of financial distressamonglisted companies at 99% confidence level. This result is not unexpected considering the increasing inflation expectations and the resulting increase in costs.In other words, the increased costs in the companies under investigation at least indicate that the probability of bankruptcy will also be higher. Results also showed that there is a positive relationship between bank deposit interest rate and the probability of bankruptcy such that the marginal effect of this variable in explaining the probability of bankruptcy of the listed companies is 17%. In addition, results indicated a negative and significant relationship between total bank credit and the probability of bankruptcy or financial distress, because the increase of bank credits means more and easier access to these facilities, and thus bettercrisis management and reduced risk of bankruptcy.Basedon the results in table 4, the increase of therate of GPD has a negative impact on the bankruptcy risk such that its marginal effect was -0.42 andindicates that duringthegrowthof aneconomy, the listed companies also benefit from this boom. Results revealed that there is a significant and negative relationship between the real stock price index and the probability of financial distress, because while there is an upward trend in stock index, in a high probability, stock price index of listed companies and their financial situation is positive and as a result, the probability offinancial distress is decreased. Finally, results reported a negative relationship between real rate of return and the probability of bankruptcy (see table 4), because with the higher returns, the likelihood of bankruptcy will drop.