Besides, being an essential issue in finance, corporate financial distress is also a cosmopolitan problem whose definition and stages are not exactly the same everywhere. From early studies and the theoretical framework associated with financial distress, Bahnson and Bartley (1992) generally define a financially distressed firm in terms of its inability to pay its debts, when they fall due for payment. Coming with a distinct point of view, while Gilbert, Menon, and Schwartz (1990) defined distress firms as firms that declared bankruptcy and firms that had negative cumulative earnings over three consecutive years, while, Whitaker (1999) characterize that a firm reaches a financial distress situation when its earnings before interests, taxes, and amortizations are smaller than its financial expenses.
This divergence in the definition is due to the variety of accounting procedures or rules in different countries or at different time spots as well as various events that sent firms into financial distress. The detection of company operating and financial difficulties is a subject which has always been particularly susceptible to financial ratio analysis (Beaver, 1966). However, since firms normally, operate within the framework of an economy, one can incontestably claimed that economic circumstances prevailing in the economy may also eventually describe, explain and predict the companies' financial health.
2.1 Theoretical Approach
Indeed, from the analysis of ample empirical research, it has been recognized that the rate of bankruptcy among firms increases sharply during economic recession (Mensah (1984). According to the literature, prior to corporate failures which are bound to bring enormous economic consequences, it is logically claimed that the firm's financial status is frequently in distress. Hence, a financially distressed firm acts as a prominent early warning for business bankruptcy prevention. This is the reason for which, financial distress is mainly used as proxy of failure's event in many previous studies.
It is hence, important to understand how macroeconomic variables influence the financial health of a company. For instance, suppose a firm incurs liabilities for its fixed operating cost in terms of foreign currency and following changes in market conditions, the local currency depreciates. As a result of which, the company will unable to cover its liabilities and goes bankrupt. In this case, the company failure was caused by two main factors. First, a firm factor which comes from the decision taken by the manager to take a loan in foreign currency and secondly, there is the macroeconomic factor emanating from the depreciation of the local currency. Hence, it can be found that a firm normally fails as a result of a combination of different factors.
An increase in the rate of inflation, which refers to changes in the average price level, is expected to cause an increase in the rate of corporate failures. One probable reason for this relationship is that, as the inflation rate is increasing, the purchasing power is decreasing. Hence, the ability of the consumers to buy goods or services that are supplied by the company is declining. As a result of which, it may give negative impact to the company's revenue as well as to the total turnover. Moreover, according to Mensah (1984) changes in price inflation influence companies in various ways: either by an increased in the cost of production or marketing (which cannot be avoided), or by generating higher prices which hence, lower the demand, or by protecting inefficiency by lowering competition.
Furthermore, unexpected inflation would lead to an erroneous output level, thereby, affecting the firm's profit due to misallocation of resources. In case actual inflation is lower than expected inflation at the time of entry into a nominal and fixed rate of debt or nominal wage contract, then it increases both the firm's real interest payments and the real wage (costs increases). Consequently, the company`s earnings are reduced and the probability of bankruptcy increases.
Expected inflation may also have a real effect on companies' profit such that Wadhwani (1986) noted that when expected inflation increases, a firm with a floating-interest nominal debt and no access to external capital, i.e. it cannot increase its nominal value of debt, would experience a negative cash-flow effect as its interest payments increase by more than the output price. This is because the nominal interest payments that the firm must pay include payment of principal. While, the nominal value of the firm's debt remains as it was before the price rise, the real value of the debt is lower after it.
Credit availability and market interest rate, both dependent, on the general economic climate do influence the company real activity. It is banks which enable the effective operation of credit-channel. The availability of credit can easily be measured by the money supply in the economy. It is the change in monetary policy that rises or lowers market interest rates tends which in turn; influence the external finance of firms. The credit-channel theory also affirms that the availability of credit is not comprehensible at a time of tightening monetary policy. Obviously, a rise in the real interest rate, which increases real interest payments, tends to reduce investment (especially if the borrowing costs of a company exceed its profits margins), spending and real economic activity as consumers will prefer to put their money in banks rather than consuming goods, thereby increasing the probability of liquidation. It can hence be deduced that, companies with relatively little debt will be least likely to fail in time of high interest.
Gross National Product(GNP) being an economic statistic of the total value of all final goods and services produced within a nation in a particular year, plus income earned by its citizens ,including income of those located abroad, is considered as a general indicator of a country's economic health. However, GDP (Gross Domestic Product) which excludes the income earned from foreign sources is found to be the most commonly used as proxy in numerous studies due to its accuracy and specificity. In fact, GDP is a more useful indicator as the income earned from abroad, being a huge sum is normally either reinvested for further overseas expansion or controlled by legislation be it host or home governments. Thus, the home country rarely benefits from its use. Increasing GDP, for instance, reflects the higher profitability of the firms in the economy which eventually lowers the rate of corporate failures. Thus, it is expected that the rate of companies being liquidated will decline in a period of prosperity such that, there is an inverse relationship between GDP and financial distress.
Economic theory suggests that there should be a strong link between economic activity and security prices, given that the stock price is the discounted present value of the firm's payout. If this payout is ultimately a function of the real activity of the firm, it implies that the performance of the firm is reflected through its stock price. This fact coincides with the Market Efficiency Hypothesis which states that the information of the companies is totally contained in the stock price. For instance, the performance of a company is normally shown in its financial results. If the company earns a profit for a particular period, the demand for shares will increase and so will its price. Likewise, in case the company shows poor performance, automatically the demand for that share will decrease as well as its price. Hence, a rise in share price indicates a good financial health of firms.
Profit which is, usually the most important performance indicator of firms in the long term,
is a measure of how much money a company makes. Thus, a profit is the revenue of the firm. As a result, company normally makes use of profits to meets its obligations. Eventually, high profitability means that the firm can service debt without risking financial distress.
The analysis, we made so far concentrated mainly on the theories and on the link of financial distress and macroeconomics variables. Throughout the years, different researchers made use of different macroeconomic variables as well as different methods to sharpen and provide evidence of their belief.
2.2 Empirical Evidence
Over the past decades, economics and finance researchers have shown consistent effort to investigate the causes of corporate failures. The first works conducted on companies' failure dated back to the 1960s. Initial studies tend to concentrate on analyzing company ratios in order to discriminate failed firms from non-failed firms.
Indeed, Beaver (1966) was the first researcher who was interested in the predictive power of the financial ratios in company failure prediction. He performed a univariate analysis on 30 selected financial ratios, and showed that corporate failure could be reliably predicted through selected financial ratios. Using a sample of 79 failed/non-failed firms and 30 financial ratios averaged over five years prior to failures, he claimed that cash-flow-to-total-debt ratio was the best single significant ratio in predicting failure. This ratio misclassified only 13 per cent of the sample for one year before bankruptcy and 22 per cent of the sample for five years before bankruptcy. He suggests that the ratio analysis is a useful tool for predicting failures at least five years before the actual failures. Subsequently, there have been relatively few studies using the univariate model for bankruptcy prediction, as researchers overwhelmingly used multivariate models instead, so as to determine the striking characteristics of companies which were potentially failing.
It is acknowledged that the first use of multivariate models and the discriminants analysis were first explored by Altman (1968), by way of the conception of the Z-score in view of improved Beaver's univariate analysis. He in fact provided support for the predictive power of multivariate discriminants analysis. He used a step-wise multiple discriminant Analysis (MDA) to develop a prediction model with a higher degree of accuracy by using a sample of 66 US manufacturing companies with 33 firms in each of the two (failure/non-failure) groups. . Five financial ratios used in his MDA model were working capital to total assets (A), retained earnings to total assets (B), earnings before interest and taxes to total assets (C), market value of equity to book value of total debt (D), and net sales to total assets (E) were found to be significant. The model gave a Z-score or discriminant score that would indicate a healthy or a likely bankrupt company. He found that all firms with an index of 2.99 or above were in the non-bankrupt group and those with an index of 1.81 or below were in the bankrupt group. The coefficients in the equation are calculated to minimize the Z-score from overlapping between the probable bankrupts and healthy companies. He ended up with a model in the following form Z = 1.2A + 1.4B + 3.3C + 0.6D + .999E. It should be noted that the model was extremely accurate in classifying 95% of the total sample correctly one year prior to failure (-1 year), but misclassification of failed firms increased significantly as the prediction time increased (28% at -2 years, 52% at -3 years, 71% at -4 years).
Since Johnson (1970) argued that significant results can be obtained only when financial ratios are used in conjunction with economic information as financial ratios exclude prominent information about alternative strategies and the economic conditions confronting management and investor, a second orientation has been noted based on the fact that besides the financial ratios, there are other variables bound to the economic environment whose relevance is incontestable in the explanation of the failure phenomenon. Moreover, in the paper titled, 'Predicting Corporate Financial Distress Using the Logit Model: the case of Malaysia', the researchers found that liquidity and profitability ratios maybe somehow deceiving since high ratios in isolation do not obviously entail that he company has sufficient money to pay its obligations. Another serious criticism of the use of financial ratios alone found in prior studies is that they are accrual accounting financial ratios that cannot reflect the ability of a firm to manage its future cash flows.
Following Johnson, Altman (1971) carried out an initial research trying to relate macroeconomic indicators such as changes in GDP, the stock exchange index and money supply aggregates to corporate failure by using US quarterly bankruptcies for 1947-1970. He finally, concluded that only three of these variables accounted to 19% of changes in corporate failure rate.
As a result, in her distinguished form of research, Rose and Giroux (1982) who analysed the relationship between 28 business cycle and corporate failure as indicators, conclude that economic conditions indeed do affect the failure process. Among all the economic variables used, the following 10 were as statistically significant: the Dow Jones industrials, the unemployment rate, the profits after tax/income originating in corporations, the corporate AAA rate, free reserves, the gross savings/GNP, the gross private domestic investment/GNP, and the change in total business investment, the output per hour and the retail sales/GNP.
In his research, Altman (1983) further, extended this narrow interpretation by examining the relationship between economic factors and bankruptcy first and then based on the findings, to construct a regression model. Among the indicators, five of them were found to be significant. Altman affirms that corporate failure and low or negative economic growth which was represented by real GNP and corporate profits are closely associated economic series. In addition, he observes increasing rate of failures during recessionary periods.
Taking further steps in capturing the influence of macroeconomic variables on aggregate company liquidations, Hudson (1986) identified profit and real interest rate as the crucial determinants of company liquidations on an annual basis from 1953 to 1981. Still in 1986, the analysis of Wadhwani who constructed a model to examine the effect of inflation on liquidation rates in the period 1964-1981, found that higher inflation leads to higher bankruptcy rate and as a consequence, leads to a depreciation of stock market prices.
Interestingly, while focusing on the effect of interest rates on company liquidations, Young (1995) argued that what matters is not real interest rates and inflation per se, but the extent to which ex-post inflation and real interest rates differ from their expected levels. He concluded that inflation hurts companies on the way up, due to cash-flow problems associated with high nominal interest rates, and on the way down, when a stronger than anticipated fall in inflation causes high real wages and real interest rates.
Another strand of related research concerns banking crises such that, Kaminsky and Reinhart (1996) analysed a sample of 20 crises, to finally report the ultimate importance of macroeconomic factors in a crisis. They document that output, the stock market, and the real exchange rate usually peak about a year before the onset of a banking crisis. On similar ground of study, after analysing a sample of developed and developing countries, during 1980 and 1994, Demirguc-Kunt and Detragiache (1997) find that low growth and high inflation are common associated with the probability of a banking crisis.
In addition in his research, Vlieghe (2001) indeed found that the debt/GDP ratio, the real interest rate, deviation of GDP from trend, and the real wage are long-run determinants of the liquidation rate. The birth of new companies, an index of property prices, and the nominal interest rate have significant short run effects.
Following the previous economic crisis, a new approach known as the baseline hazard functions which, incorporated macroeconomic variables was developed. The hazard function also known as, the instantaneous failure rate, is a measure of the tendency to fail over a very small time interval. Hillegeist et al. (2001) made use of the rate of recent defaults (RRD) and changes in interest rates (CIR) while later on, Nam, Kim, Park and Lee (2008) studied the foreign exchange rate and found that it serves better as a direct measure for the baseline hazard rate in bankruptcy prediction of a sample of 367 listed companies in the Korean Stock Exchange for the period 1991 - 2000.
On the other hand, Jia Liu (2004) made use of an error-correction model (ECM) to investigate the determinants of UK corporate failures by modelling the short-run and long-run behaviours of corporate failure rates in relation to macroeconomic phenomena over the period 1966-1999. The findings indicate that failure rates are associated with interest rates, credit, profits, price, and corporate birth rates both in the short run and in the long run. Of these macroeconomic variables, interest rate appears to be an important factor influencing failure rates which as a result can be used as a feasible policy instrument to reduce the incidence of corporate failures. This can be explained by the fact that an increased in average lending rate contributes towards higher cost of borrowing which indirectly affect the company's profitability. Moreover, while examining the link between financial distress and macroeconomic factors for a sample of UK manufacturing industry, Liou and Smith (2007) found that several macroeconomics variables such as interest rate, industrial production index, and producer price index are significant and related to the financial distress.
In the working paper, "Macroeconomic determinants of corporate failures in Malaysia" by Hamilton Ahmad, Siti Nurazira Mohd Daud (2008) among others have examined several macroeconomic variables that consist of credit liquidity condition, inflation, income (GDP), average lending rate and competition(represented by corporate birth rate) by using the Autoregressive Distributed Lag (ARDL) modeling approach. They have found that there is a long-run relationship between macroeconomic variables and corporate failures in Malaysia. Out of the three macroeconomics variables, the average lending rate and gross domestic product were found to be statistically significant at 10 percent critical levels with the expected signs, while the rate of inflation was significant at 5 percent. The result implies that any movement in the average lending rate, gross domestic product and the rate of inflation are found to be co integrated or co-moving with the changes in corporate failure rates. Gross domestic product (GDP) significantly influenced the corporate failure rates in a negative direction. The findings also demonstrate that an increase in the rate of inflation caused a rise in the corporate failures model.
Most studies on financial distress have been done in developed countries, with only a few being carried out in developing countries. The study of Zulkarnain (2009) tried to formulate a model to predict corporate financial distress and then applied the model to trace the potential failure Malaysian financially distressed firms due to the Asian Crisis in 1997. The data has been evaluated by Z score with a new model called, Distress-Grey area distress (Grey area non distress - Non distress). He, eventually, found 5 out of 64financial ratios significant to discriminate distress and non distress. The ratios were: total liabilities to total assets, assets turnover, inventory to total assets, sales inventory, and cash to total assets.
More recently, from the presentation of the paper titled, "Micro and macro determinants of financial distress" at the 15th International Business Research Conference, McNamara, R., Duncan, K., & Kelly, S. (2011) found that economic variables improve the explanation of failure by ten percent. It should be noted that, this research incorporated both macroeconomic variables, namely, 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 as well as firm specific variables in explaining corporate failure.
Synthesizing the studies mentioned above, it is still important to explore this topic further due to the limited literature on the dynamic of financial distress in the developing countries. It can also be concluded that in addition to the economic environment, the financial structure of the firm and its ability to deal with risk exposure are all equally important in shedding some light for the analysis since, macroeconomic and financial indictors complement each other.
