Commentary about London by William Blake free essay sample

London, which comprises of sixteen lines, isn't only a portrayal of William Blake’s origin yet in addition an itemized sonnet of how the economic wellbeing functions in London. The sonnet is a staggering and brief political investigation conveyed with energetic resentment. It is uncovering the perplexing associations between examples of proprietorship and the decision belief system, the manner in which every human connection are inevitably bound together inside a solitary ruinous society. The motivation behind why Blake composed it was on the grounds that he accepted that the human soul was being stifled by custom and legislative issues. His thought in the sonnet was that mankind could blossom if since quite a while ago settled foundations could be changed or expelled. Hence his sonnet â€Å"London† is progressive since it focuses on the need to address the wretchedness the speaker portrays. The individuals who are debased ought to be solid and healthy. On the other hand, Blake helps us in the sonnet to remember benefit, troopers, and royal residences, every one of them parts of abusive power. We will compose a custom paper test on Discourse about London by William Blake or on the other hand any comparable point explicitly for you Don't WasteYour Time Recruit WRITER Just 13.90/page Tunes of Experience, from which â€Å"London† was taken, was an assortment of sonnets on this essential subject. Blake distributed the work in 1794; the French Revolution was just five years of age at that point, with his own etchings. The poem’s opening shows the storyteller meandering the â€Å"charter’d† boulevards of London down to the â€Å"charter’d Thames†. The stacked word â€Å"charter’d† is utilized from a basic perspective, and Blake’s contemporary perusers would no uncertainty have gotten on it. The initial two lines of the principal refrain discusses how the decision class controls the road as well as the waterway that ought to be streaming unreservedly. The redundancy of the word â€Å"mark† is vehement; the Londoners are marked with noticeable indications of disorder and wretchedness. There is a scriptural sense at work here, as in the characteristic of the Beast from Revelations, or the sign of Cain, the dangerous â€Å"builder of the first city†. The unobtrusive move from â€Å"mark† utilized as an action word in line three to a thing in line four ties the storyteller to those he sees, indicating he is certifiably not an impartial spectator however one of the victims himself. The redundancy likewise shows the depression and tiredness that the Londoners appear to be experiencing a direct result of their abused lifestyle. In the second stanza of the sonnet, the shared trait of enduring was appeared in the reiteration of the word â€Å"every†. It additionally focused on the people’s sentiments of being detained and caught. The refrain is additionally an image of a general public in chains and the snugness of the sonnet uncovered the sentiments of capture. The word â€Å"ban† tells that they need opportunity of articulation. It uncovers how individuals couldn't voice their reactions or how the nation was being dominated. The â€Å"I† figure doesn’t show up till the finish of the stanza, as though he has been overpowered by the hints of human torment. The feeling of detainment is made completely plain in the expression â€Å"mind-forg’d manacles†. Allegorically, mental chains detaining through ideological acknowledgment of the norm. The not insignificant rundown of accusatory models gave a relentless force in the third section of the sonnet. The â€Å"Chimney-sweepers† speak to the desperate kids. The â€Å"Soldiers† speak to the anguish of the individuals who needed to serve in the military under troublesome conditions. The three explicit social sorts †the fireplace clear, the warrior and the prostitute †every single significant figure, a point clarified by the utilization of capitals, was utilized additionally for the delegate organizations. The tone of the creator as of now is distinct and accusatory. The kid clear was a notable figure of pity in Blake’s time. The word â€Å"appalls† here methods arraigns as opposed to the cutting edge utilization of disturbs. The congregation isn't shocked in a humane manner, yet is dreadful of the hazard the scopes speak to. On the last stanza of the sonnet, Blake recounted to an account of a little youngster out in the obscurity. Around then, young ladies needed to turn to prostitution in light of neediness. Blake composed that he could hear the youthful girl’s revile for what she must be gotten through. By striking at the family, the sonnet assaults the regenerative arrangement of society itself. The harlot’s revile accomplishes more than make the child cry; it decimates common lack of concern. The â€Å"plagues† means the goings of the rich and how their activities influence the lives of the whole guiltless included. The sonnet â€Å"London† gave a quite certain portrayal of the lifestyle in London at Blake’s timespan. The last thought of this sonnet is the case of a free society, with no chains, with no sort of ideological condition. The message is to be free yourself from the limitation of your own brain and the originations to have the option to discover opportunity.

Culture and Change Essay Example | Topics and Well Written Essays - 750 words - 1

Culture and Change - Essay Example A culture is comprised of various educational encounters that a representative carries with him/herself in a working environment. The entire way of thinking of culture turns out to be particularly essential to fathom when an inescapable need to bring or deal with an association wide change starts. In this manner, it tends to be said that culture and change are firmly related with regards to a hierarchical arrangement. Mullins (refered to in Venance, 2007) claims that those representatives who intentionally oppose changes in the authoritative culture and framework can really injure the normal execution standards of that association, since the significance of progress is significantly fundamental in today’s serious world. Apparent authoritative culture can be seen at Wal-bazaar which is perhaps the greatest company on the planet. Sam Walton, who is the author of this organization and is likewise called the ruler of client care, has reclassified the administrative culture which is too prominent to possibly be overlooked at Wal-shop today. Wal-Mart has been carefully following the strictly inferred administrative idea of hireling authority trying to answer the desires for their workers. (Johnson, 2010). Focusing on the desires and requests of the workers has consistently been viewed as significant for agreeing with the wants of the clients and expanding the efficiency level. Additionally, Wal-b azaar has constantly centered around keeping the costs low for prevailing upon the other significant organizations in the opposition. Easy to understand and simple to-identify with rules are made pretty much every other month and moves are immediately made, while regarding the requests of the hierarchical culture. Fundamentally, the bedrock of the Wal-Mart culture is primarily connected with components like religion, enthusiasm, an uncouth aggregate personality, present day science, objectivity, nature, steady battle, and low expenses. The amazing society existing in Wal-bazaar starts from three essential convictions, which are

In Various Regions Of The World The EFA Goals Are Frustrated By - 1

In Various Regions Of The World The EFA Goals Are Frustrated By - 1 In Various Regions Of The World The EFA Goals Are Frustrated By Social, Cultural And Economic â€" Essay Example > EDUCATION FOR ALL GOALSEducation For All (EFA) are standards set apart to govern education policies systems, and structures of 164 countries that agreed to take part. Indeed, they were intended to run between 2000 and 2015 culminating in 15 years. As a benchmarking tool, six goals were set to regulate and define a successful system by 2015 (Hutton 2014). These goals included: the expansion of early childhood and care education and achievement of universal primary education that would be free. Also, it provided guaranteed access to vocational and life skills to youth and adults, attaining 50% reduction illiteracy in adults by 2015. More goals included achieving gender parity and equality between male and female counterparts and further improving the quality of education given to children, adults, and youth (Sayed and Ahmed 2015). However, Nigeria has been experiencing a lot of challenges in meeting this goal despite a consistent increase in its per capita income up to 2014. In ranki ngs of specific targets, Nigeria has failed and has been viewed far from achieving any of the goals. Indeed, failure may be attributed to some challenges, which the country faces that include poverty, lack of sufficient funding from the government, corruption, high student to teacher ratio and child labour (Ametepee and Anastasiou 2015). Also, insecurity in the northern regions of the country, poor infrastructure and cultural barriers such as female hindrance from participating in education have hindered the country its EFA goals. In this study, the focus will lie majorly on goal two which is the attainment of free universal education, and goal six which discusses improving the quality of education offered. It will also address the frustrating factors to this goal and their impact. Nevertheless, the study will first examine the UNESCO contextual background. Also, it will review the Nigerian education system and how it has evolved in brief and how the neighbouring countries are far ing in the quest to achieve these goals. However, EFA study has been motivated by the need for education to be part of the core requirements of all human beings. It also aims at enhancing the growth of the education sector in Nigeria after the inception of the education for all goals, the challenges it has faced and the way forward to achieve these aims. In essence, it is vital for education to be integrated into one’s life since it enables people to improve their quality of life by increasing their creativeness. Also, adequate education improves individual bargaining power and eventually progress the economic performance of the nation. When an education system fails or is unable to meet the global standards or needs, necessary action must be put into place to ensure that the problem is corrected before it becomes a major issue. Nigeria, for example, seems to be facing a myriad of challenges and levels of illiteracy have been increasing rapidly. These problems have caused the fo rmer and if mitigated, the education sector in the country will thrive. United Nations under UNESCO (United Nations Education, Scientific and Cultural Organisation) initiated the EFA study. Its main aim was to provide efficient learning requirements to children, youth, and adults from all walks of life from both genders. These goals were created in correspondence to the Millennium Development Goals (MDGs) two and three which were concerned with universal primary education and gender parity (Roby, Erickson and Nagaishi 2016). The goals commenced in 2000 as a way of improving the educational sector that was ailing. Therefore, UNESCO was chosen to coordinate and oversee the member’s efforts in developing the education sector in their respective countries. In fact, through the global monitoring reports, UNESCO reports on the progress of the goals in various countries and provides solutions. In the recent reports, UNESCO has shown that majority countries have not achieved their target s entirely, but there is a steady rise towards its achievement. According to the Global Monitoring Reports by UNESCO, Nigeria is ranked 103, in the Education Development Index, out of 163 nations who signed up the EFA goals. On goal one, which involves expanding early childhood care education, 47% of countries, have already achieved the goal and 8% percent are adjacent to achieving the goal. However, 20% are very far from achieving the goal which includes Nigeria. On the second goal which is about attaining universal primary education, 52% percent have already reached it with 10 % percent close (UNESCO 2013). However, Nigeria and other nations make up 38 percent which has a long way to go. Goal three, which provides access to vocational and life skills, to be equitable has achieved poor performance in many nations with less than half of adolescents enroling in secondary schools, including Nigeria. The fourth goal which aims at decreasing adult illiteracy by 50% percent in 2015 has achieved 25% fulfilment with 32 percent being very far from attaining it. In Nigeria, for example, 51 percent of Nigerian adults are illiterate. On obtaining gender parity and equality which is the 5th goal, many countries, especially in the sub-Saharan region, are yet to achieve it. Specifically, Nigeria is yet to achieve both at the primary and secondary level with more males attending school than females. Female illiteracy is a result of early marriage and premature pregnancy. Further, there is also lack of teacher training on how to approach gender sensitive issues. The last goal addresses the quality of education and improvement. In fact, efficient education has not been achieved in majority countries. However, many states are still on track and will achieve the goals in due course.

THE EFFECT OF FINANCIAL DISTRESS ON OPERATING CASH FLOWS - Free Essay Example

This paper provides new evidence on the financial performance of Joint stock firms by emphasizing the role played by financial distress. The purpose of this paper is specify a model for early predication of financial distress that allows us to predict the specific nature of financial distress that can effect operating cash flow and which can lead the firm toward bankruptcy and to see the effect of financial distress on operating cash flows of companies listed on Karachi Stock Exchange. Financial distress is a situation when a firms assets value falls below some threshold. Firm starts to incur losses and it is not in a position to generate positive cash flows. A firm enters to financial distress before it goes bankrupt. We have studied 67 firms listed on Karachi Stock Exchange to see the effect on financial distress on their cash flows. Our sample includes financially distressed as well as financially health firms. We have incorporated financial data of consecutive four years (2003 to 2008) of 67 firms. In order to measure the financial distress we have used Modified Altman Z-Score as a proxy. Other independent variables, which have been used, are size of the firm, Working Capital, Working capital productivity and Operating Profit. By regressing these Five variables (Financial Distress, Working Capital, Size of Firm, Working capital productivity and Operating Profit) on Operating Cash Flows we have found that financial distress have a negative effect on corporate cash flows. However Size of Firm, Operating Profit and Working capital productivity have p ositive effect on Corporate Cash Flows. Working Capital has a negative effect on operating cash flows. We have estimated our model with the help of regression analysis. Our study is unique in a sense that there is a dearth of literature on financial distress with special reference to Pakistan. Keywords: Financial distress, Working capital, Working capital productivity, Bankruptcy, Altman Z-Score, Corporate Failure, Insolvency, Survival Analysis. Table of Contents 2 Abstract 2 Table of Contents 4 1. Introduction 5 2. Literature Review 8 3. Methodology 13 Data and Variables 13 Measurement of Variables 14 Operating Cash Flows (OCF) 14 Explanatory Variables 14 Financial Distress (FD) 14 Size of Firm (SZ) 15 Operating Profit (OP) 15 Working Capital (WC) 15 Working capital Productivity (WCP) 15 Hypotheses Testing 15 4. Empirical Framework 17 5. Results 17 Model Summary (b) 20 6. Discussion 22 Conclusion 23 Refererences 25 1. Introduction Financial Statements basically show the historical performance or record of the company at some previous point of time. By the time when financial statements are made public, changes are many economical areas such as market conditions, currency exchange rate and inflations can change the values of assets and liabilities. In this case there often exist discrepancies between book value of assets and their market values. In above case there might be companies that are healthy and many go through period of financial distress. In particular is the threat of not being able to meet debt obligations. The first Indication of financial distress is when firm does not have enough liquid assets (short-term assets) to cover (pay for) current liabilities (short-term liabilities) when this happen than firm ability to covering long-term liabilities is reduced resulting in creditors taking on more risk than the investment of loaning money to the firm is worth. When company is facing financi al distress, book value of company liabilities can become worth more than the market value of the same liabilities. If this happen, than firm is in danger of not meeting its obligations to creditors. In this case creditors may not be paid and in worst of financial distressed time, the creditors may receive nothing in interest or principal, if the firm files for bankruptcy. The importance of financial-decision making goals is to increase shareholders value and to keep them away from financial distress. The Predicting of financial distress is an early warning signal to keep investors from being loss. It has been more than 70 years, since Ramser Foster, and Fitzpatrich in 1931-1932, and 44 years, since Beaver (1966) but still they have not found the theory of financial distress ( Laclere M,2006). They were more statistical consideration then the intuitive models or fundamental causes of financial distress (Ooghe Prijcker, 2007; Balcean Ooghe, 2004). Since The Altmans model widely used among the investors, though it is not an intuitive model, once a firm is predicted having a financial distress next year, it has been treated as it has been financial distress currently (whtaker, 1999). This work aims at studying the effect of financial distress on operating cash flows of corporations. The interest in the area of financial distress has increased due to considerable number of corporate failures around the globe in recent years especially since the early 1990s. Notable failures include Global Crossing, Enron, Adelphia, Worldcom, HH Insurance, One Tel, and Ansert Airlines in 2001, and most recently FIN Corp in 2007. Financial distress is defined as a low cash flow state of a firm in which it incurs losses without being insolvent or financial distress is a term in Corporate Finance used to indicate a condition when promises to creditors of a company are broken or honored with difficulty. Financial distress is different from insolvency. Financially distressed companies have lower profitability, higher leverage, lower past excess returns and larger size compared to active companies. The failure or bankruptcy of financially distressed firms results in significant direct and indirect costs to many stakeholders; including shareholders, managers, employees, lenders and clients. For instance Shareholders lost nearly $11 billion when Enrons stock price, which hit a high of US$90 per share in mid-2000, plummeted to less than $1 by the end of November 2001. Failure of Australias second largest insurance company, HIH Insurance, in 2001 represents the 2nd largest corporate collapse in Australias history. The collapse of HIH entailed huge individual and social costs. The deficiency of the group was estimated to be $3.6 billion and $5.3 billion. The lineup of major corporate bankruptcies was capped by the mammoth filings of Conseco ($56.6 billion in liabilities), WorldCom ($ 46.0 billion), and Enron ($ 31.2 billion actually almost double this amo unt once you add in the enormous amount of off-balance liabilities making it the largest bankruptcy in the united states. Such costs may be avoided if financially distressed companies are identified well before failure. Then corrective measures can be taken to save the company from ominous bankruptcy. Much of the literary work on financial distress relates to failure prediction and survival analysis of firms. Some studies on financial distress have been made in the context of corporate risk management. Our study aims at studying the financial distress along with key performance indicators of the corporations to see how these indicators (profitability, Size of Firm, Working capital and Working capital productivity.) co-move with the financial distress. There is not sufficient literature on studying the effect of financial distress on corporate cash flows. Especially in Pakistan, the area has not been researched thoroughly. We estimate a linear model, which helps us in the measu rement of magnitude of effect of financial distress on the operating cash flows. Along with financial distress, we also measure the effect of size of firm, operating profits, working capital and working capital productivity on operating cash flows. We have included both financially distressed and financially healthy firms in our sample. Our findings provide evidence that financially distressed Pakistani firms face adverse cash flow problems. The remainder of this paper is organized as follows. Section 2 presents a review of literature in the area of financial distress. Section 3 describes Methodology and research design, i.e. data and variables used in the study. Section 4 describes the empirical framework (Model Description). Section 5 presents the results of the regression analysis. Section 6 Discussion and concludes the paper. 2. Literature Review The effect of financial distress on financial structure decisions is another conflicting point. According to the static trade-off theory, both the advantages of debt (tax shields) as well as its disadvantages (insolvency costs) have been traditionally considered in the capital structure literature. This trade-off between the benefits and costs of debt focuses on ex-ante insolvency costs, whose negative effect on leverage has been theoretically justified (Barnea et al., 1981) as well as empirically documented (Miguel Pindado, 2001). According to (Warner (1977), Altman (1984), Franks Touros (1989), Weiss (1990), Asquith, Gertner and Scharfstein (1994), Opler Titman (1994), Sharpe (1994), Denis Denis (1995), Gilson (1997) Financial distress has both direct and indirect costs. (Opler Titman (1994), (Shleifer Vishny (1992), Direct costs of distress, such as Litigation fees are relatively small. Indirect costs, such as loss of market share and inefficient asset sales are belie ved to be more important, but they are also much harder to quantify. The debate on financial distress started after the occurrence of corporate failures. Theorists and researchers emphasized on how to save a firm from being financially distressed. Opler Titman (1994) provide empirical evidence that financially distressed firms lose significant market share to their health competitors in industry downturns. Chevalier (1995) was of the view that financially distressed firm is likely to violate the debt covenants and these violations put heavy costs on the firm. Froot et al. (1993) established that financially distressed firms forego positive NPV projects. Researchers are of the view that a firm with a high leverage has an incentive to engage in hedging activities. The measurement of financial distress has also been debatable in the literary circles. Some researchers use leverage as a proxy for financial distress. Failure prediction models use firms distance to default as a prox y of the financial distress. Some models used accounting based measures of financial distress. Hill, Perry Andes(1996), Ward Foster(1997), DeYoung(2003), Nikitin(2003) and laitinen(2005) use only financial ratios as financial distress predictors; while Altman(1969), Ahrony, Jones and Swary(1980), Altman Brenner(1981), Broenstein Rose(1995) and Fama French(1995) used only market based covariance. Majority of researchers believe that financially distressed firms appear to exhibit lower profitability, lower historic excess returns and larger size than active companies. Beaver (1966) pioneered the development of model for corporate failure prediction. He found that the model can predict failed firms for at least five years before to failure. His model was based on financial ratios as single predictors of financial distress. Altman (1968) criticized the model and upheld that the model may give inconsistent and confusing classifications results for different ratios on the same fir m. Altman (1968) came up with his own model which can handle multiple financial ratios in predicting companys failure. In Altman (1968) study, five financial ratios include (1) working capital to total assets (2) retained earnings to total assets (3) earnings before interest and tax to total assets (4) market value of equity to par value to debt and (5) sales to total assets. His model found to be the best predictor of corporate bankruptcy. The model is very popular and is called Z Score model. The critics of this model say that it violates the assumption about the multivariate normal distribution of independent variables. Castagna Matolcsy (1981) pioneered the study of corporate financial distress and failure .In USA and Europeon countries, survival analysis techniques form the basis for a number of studies in financial distress research area. Cash flow is strongly related to financial distress. Henbry (1996) studied whether adding cash flow information will improve current ban k failure prediction models. Some researchers were of the view that combining market-driven variables with accounting ratios provide more accuracy to the financial distress models. Compartive studies have also been done in the area of financial distress. Rommer(2005) compared the financial distress predictors between French, Italian and Spanish firms using competing risk models. There are few research studies on financial distress in Asian context. For example, Honjo(2000) employs multiplicative hazards model for investigating business failure for new firms in Japanese manufacturing industry whereas Raj Rinastiti(2002) use Cox proportional hazards model to examine the failed banks in Asia during 1997 Asian crisis. Some of the prior corporate failure studies focus the analysis on specific industry sector. Chen and Lee (1993) focus the study on oil and gas industry. Similarly, Lee Urrutia(1996) have studied the property liability insurance industry. Researchers have establishe d that income capacity, operating efficiency and leverage are important factors in explaining corporate failure and financial distress.According to Hossari Rahman (2005), empirical investigation of corporate failure may be classified in to two categories; the studies that do not use financial data and those which use financial data which may be further classified in to those that use non ratio financial data and those that make use of financial ratios in modeling corporate collapse. The use of financial ratios to predict corporate failure has been well established since the original study of Beaver (1966). Most of the empirical research in this area has used financial ratios and have been successful in discriminating between failed and successful firms. However despite this success, financial ratio models have been criticized because of window dressing of figures on the part of the firm by use of creative accounting. Critics emphasize the use of market-based data along with fina ncial ratios. Many studies make use of market data for analyzing the financial distress of companies. Aharony, Jones and Swary (1980) find differences in the behavior of total and firm-specific variances in returns four years before formal bankruptcy is announced. Altman and Brenner (1981) suggest bankrupt firms experience deteriorating capital market returns for at least a year before to bankruptcy. Clark and Weinstein (1983) suggest that there is negative market return at least three years before to bankruptcy. Mossman et al. (1998), Shumway (2001) and Turetsky and McEwen (2001) also support that there is a relationship between market based variables and the likelihood of corporate financial distress. Company specific variables such as company age, size of the firm and squared size have also been used in the prediction of financial distress. Prior studies suggest that company age and size effect its endurance. The younger and smaller firms are more likely to fail than establ ished or bigger firms as they dont have sufficient experience in the business. Larger firms are expected to better manage and protect them from financial distress than smaller firms (Audretch Mahmood, 1995; Honjo, 2000). Small firms have a higher probability of entering financial distress because they are not resistant to the shocks they might encounter and the large firms have a high probability of entering financial distress because they might have inflexible organizations, problems with monitoring managers and employees and difficulties with providing efficient intra-firm communications. Researchers have also established that probability of financial distress is a decreasing function of firm size. Luoma Laitinen ( 1991) established that the symptoms of financial distress are observable from the deterioration of financial ratios or the effect of such ratios on corporate failure dont stay constant over time. Studies provide evidence that financial distress is not without costs . Financially distressed firms have to incur direct bankruptcy costs, higher contracting costs, the loss of tax shields and loss of valuable investment opportunities All the above studies provide us a solid base and give us idea regarding effect of financial and its components on operating cash flow. They also give us the results and conclusions of those researches already conducted on the same area for different countries and environment from different aspects. On basis of these researches this paper extends the previous research work done on financial distress. We have used modified Altman Z Score as a proxy for the financial distress. After including the financially distressed and financially healthy firms in our sample, we have seen the effect of financial distress on corporate cash flows. Prior to this work hardly any paper can be seen which studies the impact of financial distress on corporate cash flows, especially in Asian context. Our work adds to the literature in a sen se that it not only identifies the financially distressed firms but also measures the effect of financial distress on operating cash flows of the firms listed on Karachi Stock Exchange. Our work also contributes to the literature in establishing a fact that whether the model of financial distress developed by Altman is relevant in Pakistans Corporate Environment. 3. Methodology The purpose of this research is to contribute towards a very important aspect of financial management known as financial distress effects on operating cash flow with reference to Pakistan. Here we will see the relationship between financial distress effect on profitability of 64 Pakistani Joint stock firms listed on Karachi stock Exchange for a period of six years from 2003 2008. This section of the article discusses the firms and variables included in the study, the distribution patterns of data and applied statistical techniques regression analysis in investigating the relationship between financial distress and operating cash flow. Data and Variables Secondary data has been used in this study. The financial data of 67 companies listed on Karachi Stock Exchange has been compiled. The source of data is Statistics Department, State Bank of Pakistan. We have used financial data of 67 companies for four consecutive years i.e. from 2003 to 2008. We have selected 67 companies from different sectors such as Fuel and Energy, Cement, transport and communication, Engineering, Sugar, Chemical, Paper and Board and Miscellaneous sectors. Our sample consists of financially healthy as well as financially distressed companies. In this study we have operating cash flows as dependent variable and Financial Distress as independent variable. Along with financial distress we have used four other variables; firm size, operating profit working capital and working capital productivity. Measurement of Variables Operating Cash Flows (OCF) OCF has been arrived at by adding depreciation and current liabilities to the operating profit and deducting the accounts receivables there from have measured OCF. OCF is a dependent variable in this study. Explanatory Variables Financial Distress (FD), Size of Firm (SZ), Working Capital (WC), Working capital productivity (WCP) and Operating Profit are explanatory variables. Financial Distress (FD) In order to measure financial distress we have used modified Altman Z-Score model. It has been calculated as follows Altman Z Score= EBIT/Total Assets + Sales/Total Assets + 1.4*Retained Earnings/Total Assets + 1.2*Working Capital/Total Assets Where EBIT stands for earnings before income tax and interest. If Altman Z-Score is 3 or greater than 3, firm is said to be in good financial health. If Altman Z Score is greater than 2 but less than 3 firms has some risk of entering financial distress. And if firm has Altman Z Score of less than 2, it means that firm has entered financial distress and it may become bankrupt. Size of Firm (SZ) We have measured the size of firm (SZ) by taking the natural logarithm of the total sales of the firm. Operating Profit (OP) Operating profit means the profit associated with the core operations of the business. Working Capital (WC) Working Capital has been measured by deducting current liabilities from current assets. WC= Current Assets Current Liabilities Working capital Productivity (WCP) Working capital productivity is an expression of how effectively a company spends its available funds compared with sales or turnover, the working capital productivity figure helps to establish a clear relationship between its financial performance and process improvement. Higher will be the figure better would be working capital productivity. Working capital productivity = Sales à · (Current assets Current liabilities) Hypotheses Testing Since the aim of this study is to examine the relationship between financial distress and operating cash flow, the study makes a set of testable hypothesis {the Null Hypotheses H0 versus the Alternative ones H1}. Hypothesis 1 The first hypothesis of this study: H01: There is positive effect of financial distress on operating cash flow of Pakistani firms. H11: There is a negative effect of financial distress on operating cash flow of Pakistani firms. Hypothesis 2 The second hypothesis of the study is: H02: There is positive effect of operating profit on operating cash flow of Pakistani firms. H12: There is negative effect of operating profit on operating cash flow of Pakistani firms Hypothesis 3 The Third hypothesis of the study is: H03: There is positive effect of size of firms on operating cash flow of Pakistani firms. . H13: There is negative effect of size of firms on operating cash flow of Pakistani firms. Hypothesis 4 The Fourth hypothesis of the study is: H04: There is positive effect of working capital on operating cash flow of Pakistani firms. H14: There is negative effect of working capital on operating cash flow of Pakistani firms. Hypothesis 5 The Fourth hypothesis of the study is: H05: There is positive effect of working capital productivity on operating cash flow of Pakistani firms. H15: There is negative effect of working capital productivity on operating cash flow of Pakistani firms. 4. Empirical Framework Our estimated model, which shows the effect of financial distress on corporate cash flows, is as under: OCF = B B1FD + B2 SZ + B3 OP -B4 WC + B5WCP In this equation: OCF = Operating Cash Flows B= Constant Term or intercept of the equation B1= Slope of the variable financial distress (FD) FD= Financial Distress B2= Slope of the size variable SZ= Size of the firm B3= Slope of the operating profit variable OP= Operating Profit B4= Slope of the working capital WC= Working Capital B5= Slope of the working capital productivity WCP= Working capital productivity 5. Results The model shows that variable FD has a negative coefficient, which means that with the FD has a negative effect on the operating cash flows. Variable Size (SZ) has a positive coefficient which means that greater the size of the firm, the more cash flows for the firm from operations. Operating Profit (OP) has a positive coefficient, which means that OP has robust effect on Operating cash flows. Working capital has negative coefficient, which means that it is negatively related to cash flows from operations and working capital productivity (WCP) has a positive coefficient, which means Sales growing faster than the resources required to generate them is a clear sign of efficiency. B in this equation is intercept of the model or constant term. Let us see some descriptive statistics of our analysis. The table shows the mean values of OCF, FD, OP, SZ, WC and WCP. Descriptive Statistics Mean Std. Deviation N OCF 4525.2953 12646.70110 67 FD (Altman Z-Score) 1.926 1.5573 67 Firm Size 7.45587 2.162929 67 Working Capital 882.35 2587.491 67 Working Capital Productivity Operating Profit 6.75426 1348.82373 1.876545 5619.621546 67 67 Let us see the correlation matrix of the dependent and explanatory variables. The matrix shows that OCF is negatively related to FD while it is positively related to SZ, WC, and OP. It shows that FD is negatively related to OCF and OP while positively related to SZ and WC. Firm Size (SZ) is positively related to all variables. Similarly WC is negatively related to WCP and positively related to positive correlation with all other variables. Operating Profit (OP) has negative correlation with FD while positive correlations with OCF, SZ, WC and WCP .Working Capital Productivity (WCP) is negatively related to WC and positively related to all other variables. Correlations OCF FD(Altman Z-Score) Firm Size Working Capital Working Capital Productivity Operating Profit Pearson Correlation OCF 1.000 -.110 .443 .645 .387 .928 FD(Altman Z-Score) -.110 1.000 .174 .020 .225 -.044 Firm Size Working Capital Working Capital productivity Operating Profit .443 .421 .645 .928 .174 .225 .020 -.044 1.000 1.500 -.043 .309 .343 .348 1.000 .752 .174 -.100 2.50 .285 .309 1.032 .752 1.000 Sig. (1-tailed) OCF . .189 .000 .000 .000 .000 FD(Altman Z-Score) .189 . .079 .437 .000 .363 Firm Size .000 .079 . .002 .079 .005 Working Capital Working Capital Productivity .000 .000 .437 .072 .002 . .387. . .000 Operating Profit .000 .363 .005 .000 .005 . N OCF 67 67 67 67 67 67 FD(Altman Z-Score) 67 67 67 67 67 67 Firm Size 67 67 67 67 67 67 Working Capital Working Capital Productivity 67 67 67 67 67 67 67 67 67 67 67 67 Operating Profit 67 67 67 67 67 67 Variables Entered/Removed (b) Model Variables Entered Variables Removed Method 1 Operating Profit, FD(Altman Z-Score), Firm Size, Working Capital(a) Working Capital Productivity . Enter a. All requested variables entered. b. Dependent Variable: OCF Consider the Model Summary of our Estimated Regression Model. Model Summary (b) Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1 .954(a) .911 .905 3892.72617 2.145 a. Predictors: (Constant), Operating Profit, FD (Altman Z-Score), Firm Size, Working Capital (WC), Working Capital Productivity (WCP) b. Dependent Variable: OCF Coefficient of determination (R Square) or Model Fit is 0.911 which means that explanatory variables are capable of explaining 91% variations in the dependent variable i.e. Operating cash flows OCF. The ANOVA Table shows us the F-statistics. F-Statistics shows the overall strength of the model. F Value is 158.653 which is quite high. Hence we reject the null hypothesis that explanatory variables have positive effect on operating cash flows and we establish that Financial distress (FD) has a negative effect on operating cash flows (OCF). ANOVA shows that our model is quite good to estimate the effect of financial distress (FD), Size of the Firm, Operating Profit, Wor king Capital and Working Capital Productivity on Operating Cash Flows. ANOVA (b) Model Sum of Squares df Mean Square F Sig. 1 Regression 9616471554.991 4 2404117888.748 158.653 .000(a) Residual 939505654.596 62 15153317.010 Total 10555977209.586 66 a. Predictors: (Constant), Operating Profit, FD (Altman Z-Score), Firm Size, Working Capital, Working Capital Productivity b. Dependent Variable: OCF Consider the table which shows the t-values for our variables. The table shows that the size of the firm (SZ), operating profit and Working Capital Productivity (WCP) are statistically significant to affect the operating cash flows. If we ignore the sign FD is statistically significant to affect the corporate cash flows. Coefficients (a) Model Standardized Coefficients t Sig. Correlations Beta Zero-order Partial Part 1 (Constant) -3.051 .003 FD(Altman Z-Score) -.101 -2.605 .011 -.110 -.314 -.099 Firm Size .214 5.192 .000 .443 .550 .197 Working Capital Working Capital Productivity -.165 .245 -2.818 5.428 .006 .000 .645 .389 -.337 .500 -.107 .187 Operating Profit .982 16.916 .000 .928 .907 .641 a. Dependent Variable: OCF Coefficient Correlations (a) Model Operating Profit FD(Altman Z-Score) Firm Size Working Capital Working Capital Productivity 1 Correlations Operating Profit 1.000 .105 -.100 -.724 -.200 FD(Altman Z-Score) .105 1.000 -.187 -.046 -.185 Firm Size -.100 -.187 1.000 -.165 -.285 Working Capital Working Capital Productivity -.724 1.500 -.046 -.187 -.165 -0.45 1.000 -.058 -0.56 1.000 Co-variances Operating Profit .017 4.327 -3.154 -.027 -2.564 FD(Altman Z-Score) 4.327 98915.750 -14174.525 -4.175 -12178.252 Firm Size -3.154 -14174.525 58048.854 -11.340 58045.85 Working Capital Working Capital Productivity -.027 -3.254 -4.175 -12175.252 -11.340 4.327 .082 -.028 -4.585 .958 a. Dependent Variable: OCF Case wise Diagnostics (a) Case Number Std. Residual OCF Predicted Value Residual 56 3.892 11960.00 -3190.8577 15150.85766 62 4.706 27198.30 8880.1328 18318.16716 a. Dependent Variable: OCF Residuals Statistics (a) Minimum Maximum Mean Std. Deviation N Predicted Value -7234.8931 94892.6719 4525.2953 12070.79593 67 Residual -6178.19580 18318.16797 .00000 3772.92117 67 Std. Predicted Value -.974 7.486 .000 1.000 67 Std. Residual -1.587 4.706 .000 .969 67 a. Dependent Variable: OCF 6. Discussion Analysis on financial distress prediction model with modified Altman-Z Score results shows that our model is robust in explaining the variations in dependent variable i.e. Operating Cash Flows (OCF). Our estimated model shows that the variable Financial Distress (FD) is negatively related to corporate cash flows. However Firm Size (SZ) Operating Profit (OP) and Working Capital Productivity (WCP) are positively related to FD. In this study we found another negative relationship between Working Capital (WC) and operating cash flow. This study shows that financial distress negatively affects the operating cash flow of firm and if firm would be big in case of size than effect of financial distress on operating cash flow would not be as negative as this will be in case of small firm and positive effect of Working capital productivity and operating cash flow shows that how effectively a company spends its available funds compared with sales or turnover, the working capital productivity f igure helps to establish a clear relationship between its financial performance ,process improvement and operating cash flow. Negative effect of working capital on operating cash flow is obvious because it shows that capital not being put to work properly is being wasted, which is certainly not in investors best interests. Conclusion Our results show that our model is robust in explaining the variations in dependent variable i.e. Operating Cash Flows (OCF). We have used the financial data of 67 firms, half of which were facing financial distress. We measured the effect of Financial Distress (FD) on the Operating cash flows. Our estimated model shows that the variable Financial Distress (FD) is negatively related to corporate cash flows. However Firm Size (SZ) Operating Profit (OP) and Working Capital Productivity (WCP) are positively related to FD. The notion that large firms in Size have more probability of entering financial distress has not been substantiated by our study. Rather our study shows that the larger the size of the firm, the more the operating cash flows and company effectively spends its available funds compared with sales or turnover, the working capital productivity figure helps to establish a clear relationship between its financial performance and process improvement and therefore less chanc es of being financially distressed. Another important finding of the study is negative relationship between working capital (WC) and Operating Cash Flows (OCF). It means the more working capital we have, the less operating cash flows we have. Actually greater working capital means we have more funds tied up which have not been gainfully utilized in the business. This may be as a result of an error of estimating cash for business requirements on the part of the management. Huge working capital has its opportunity cost and that cost may be in the shape of less operating cash flows and less profitability. Our analysis strongly supports that higher operating profits result in higher operating cash flows for the firm; and this is true for small firms as well as for large firms in size. Summing up we can say that by using this model, on large data set we can obtain more generalize ability of the results. Refererences Altman E. (1968). Financial Ratios, Discriminant Analysis and the prediction of Corporate Bankruptcies. Journal of Finance, 23,589-609. Aharony, J., Jones, C. P. Swary, I. (1980).An analysis of risk and return Characteristics of corporate bankruptcy using capital market data.Journal of Finance, 35(4), 1001-1016. Altman, E.I. Brenner, M.(1981).Information effects and stock market responses to signs of firm deterioration. Journal of Financial and Quantitative Analysis, 16(1), 35-51. Audretsch, D.B. Mahmood, T. (1995). New Firm Survival: New Results using a hazard function. The review of Economics and Statistics, 77(1), 97-103. Beaver, W. H. (1966). Financial Ratios as predictor of failure, Empirical Research in Accounting: Selected Studies. Supplement to Vol. 4,71-111. Borenstein, S. Rose, N. L.(1995). Bankruptcy and pricing behavior in U.S. airline markets. The American Economic Review, 85(2) ,397-402. Castagna, A. D. Matolcsy, Z. P. (1981).The prediction o f Corporate Failure: Testing the Australian experience. Australian Journal of Management, 6(1) ,23-50. Chen, K. C. W. Lee, C. W. J. (1993).Financial ratios and corporate endurance: A case of the oil and gas industry. Contemporary Accounting Research, 9(2), 667-694. Clark, T. A. and Weinstein, M . I. (1983). The behavior of the common stock of bankrupt firms. Journal of Finance, 38(2),489-504. Chevalier, J., (1995).Capital Structure and Product Market Competition? An Empirical Evidence from Super Market Industry,Journal of Finance, 50,1112-1195. Froot, K. A., D. S. Scharfstein and J.C. Stein, (1993).Risk Management: Coordinating Corporate Investments and Financing Policies. Journal of Finance ,5,1629-1658. Opler, T. S. Titman, (1994). Financial Distress and Corporate Performance. Journal of Finance 49,1015-1040.

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