buy custom Virtual Classrooms essay

buy custom Virtual Classrooms essay A virtual classroom consists of education activities being conducted online and learning resources are also available which are free and easy to access. This means that students dont have to travel to school and have face to face lectures with the teachers but can access these lectures at the comfort of their homes. These classrooms have developed due to the advancement in technology and the schools adopting this technology with the aim increasing the number of students intake in these schools due to increased demand for education. It is proven that web based learning or rather use of virtual classrooms is an efficient method of learning, in which students who go through this system are as competent as the ones who attend the classes physically. Some people disagree with this claiming that students experience social isolation, where they cannot have fun with other students or share their personal experiences unlike the students who attend classes personally. They argue that education does not only entail reading of books but it also involves one developing well physically, mentally and socially. On the other hand schools are now able to register more students in their schools because not all of them have to attend the classes physically. This kind of learning saves the students time and cash, as opposed to the students who have to travel to and from the school. Also virtual schools save a lot of money because they dont have to employ some employees such as security officers and Janitors. The teachers are at a greater position to monitor and interact with the students because they can easily identify the students whove not been attending classes and the ones who need some more assistance in some fields of study. The greatest of all is that it makes the learning process easy because, one can access notes, exams and lectures easily online. Virtual classrooms have been of great help in expansion and improvement of the learning process because students can access learning materials and lectures easily. This has made it possible for more people to access good education at an affordable cost. Buy custom Virtual Classrooms essay

How to Sing Happy Birthday in Chinese

How to Sing Happy Birthday in Chinese The Happy Birthday Song has a strangely contested history. The tune was originally composed in the late 1800s by Patty and Mildred Hill, though the lyrics were not the same. In fact, the Hill sisters titled the song Good Morning To All. Somewhere along the way, the phrase happy birthday became associated with the melody. In 1935, the Summy Company registered a copyright for the Birthday Song. In 1988, Warner Music bought that copyright and has been making big bank ever since. Warner Music charged royalties for public performances of the Happy Birthday Song and appearances in film soundtracks. Only until 2016 did the popular song become public domain. In February 2016, a US federal judge closed a case ruling that Warner Music does not hold a valid copyright to the Happy Birthday Songs lyrics and melody. Now, the Birthday Song finally belongs to the public and is considered one of the most popular songs in the world. It has been translated into many languages, including Mandarin Chinese. Its an easy song to learn in Chinese since it is essentially just two phrases repeated over and over again.   Practice speaking the words to this song before singing them. This will ensure that you are learning the words with the proper tones. When singing in Mandarin Chinese, sometimes the tones are not clear given the melody of the song. Notes   Ã§ ¥  (zhà ¹) means wish or express good wishes. ç ¥ Ã¤ ½   (zhà ¹ nÇ ) means wishing you.   Ã¥ ¿ «Ã¦ ¨â€š (in traditional form) / Ã¥ ¿ «Ã¤ ¹  (simplified form) (kui là ¨) can be preceded by  other happy events  such as Christmas (è â€"è ªâ€¢Ã§ ¯â‚¬Ã¥ ¿ «Ã¦ ¨â€š / Ã¥Å" £Ã¨ ¯Å¾Ã¨Å â€šÃ¥ ¿ «Ã¤ ¹  / shà ¨ng dn jià © kui là ¨) or New Year (æâ€" °Ã¥ ¹ ´Ã¥ ¿ «Ã¦ ¨â€š / æâ€" °Ã¥ ¹ ´Ã¥ ¿ «Ã¤ ¹  / xÄ «n nin kui là ¨). Pinyin shÄ“ng rà ¬ kui là ¨zhà ¹ nÇ  shÄ“ng rà ¬ kui là ¨zhà ¹ nÇ  shÄ“ng rà ¬ kui là ¨zhà ¹ nÇ  shÄ“ng rà ¬ kui là ¨zhà ¹ nÇ  yÇ’ngyuÇŽn kui là ¨ Traditional Chinese Characters 生æâ€" ¥Ã¥ ¿ «Ã¦ ¨â€šÃ§ ¥ Ã¤ ½  Ã§â€Å¸Ã¦â€" ¥Ã¥ ¿ «Ã¦ ¨â€šÃ§ ¥ Ã¤ ½  Ã§â€Å¸Ã¦â€" ¥Ã¥ ¿ «Ã¦ ¨â€šÃ§ ¥ Ã¤ ½  Ã§â€Å¸Ã¦â€" ¥Ã¥ ¿ «Ã¦ ¨â€šÃ§ ¥ Ã¤ ½  Ã¦ ° ¸Ã©   Ã¥ ¿ «Ã¦ ¨â€š Simplified Characters 生æâ€" ¥Ã¥ ¿ «Ã¤ ¹ Ã§ ¥ Ã¤ ½  Ã§â€Å¸Ã¦â€" ¥Ã¥ ¿ «Ã¤ ¹ Ã§ ¥ Ã¤ ½  Ã§â€Å¸Ã¦â€" ¥Ã¥ ¿ «Ã¤ ¹ Ã§ ¥ Ã¤ ½  Ã§â€Å¸Ã¦â€" ¥Ã¥ ¿ «Ã¤ ¹ Ã§ ¥ Ã¤ ½  Ã¦ ° ¸Ã¨ ¿Å"Ã¥ ¿ «Ã¤ ¹  English Translation Happy BirthdayWish to you happy birthdayWish to you happy birthdayWish to you happy birthdayWish to you happiness forever Hear the Song The melody of the song is the same as the birthday song in English. You can hear the Chinese version sung to you by the crooning Mando pop-star Jay Chou.

Bank law Essay Example | Topics and Well Written Essays - 2000 words

Bank law - Essay Example The agent in possession of the said Nursing Home sold it and the proceeds were applied to reduction of the credit debt and no surplus accrued to benefit the other creditors and Narni. After the sale, no profit or income was derived by Narni. 2. Narni which runs the Carrum Nursing Home applied for overdraft facility with National Australia Bank. Pending formal approval of the application with limit of $65, 000.00, the Bank nevertheless honored the cheques drawn by Narni even though there were no funds to meet them since the account was regularly in debit. The bank refused to extend the overdraft facility to $100, 000.00 but supported Narni by honoring the cheques drawn despite lack of funds. The Court found that the "Bank and Narni conducted their business and arranged their affairs, from February 1989, on the basis that the approved overdraft of $65,000 was at best a nominal limit and that the Bank would tolerate surges well in excess of that limit in each monthly cycle. The bank ope rated and permitted the account to operate in a very flexible way so that the monthly surges far exceeded any such limit". The court also found that "Narni relied upon this attitude on the part of the Bank in the operation of its business, as the Bank officers knew". It was deduced from the facts that the Bank itself also enjoyed a benefit from this arrangement from the receipt of interest and other fees and by the retention of a satisfied customer. The Court found that it was a "term of this arrangement between the Bank and Narni that the Bank would not refuse to honour cheques drawn by it on the ground that the balance of the account exceeded the approved overdraft limit of $65,000." The correctly held that it was an implied term of the arrangement that the Bank could not terminate or vary it without giving the customer reasonable notice so as to allow time for it to arrange its affairs to comply. Furthermore, they must have regard to the fact that cheques, which had been previous ly drawn and delivered may have to be honoured under the pre?existing arrangement in place at the time they were drawn and delivered. The implication of such a term is an incident of the arrangement between the Bank and its customer because the Bank knew that Narni was dependent upon it. As aptly held by the court, " there was no warning of dishonor from the bank and this act was relied upon by Narni and giving rise to overdraft extension. Narni was dependent for its cash flow upon the accommodation of the bank in excess of the agreed limit given by the Bank." In the case of Joachimson v Swiss Bank Corporation [1921] 3 KB 110 CA, it was held that the following are considered implied terms: a). The bank will receive the customer’s deposits and collect his or her cheques; b). The bank will comply with written orders (i.e. cheques) issued by its customers assuming there is sufficient credit tin the account; c). The bank will repay the entire balance on the customers demand at th e account holding branch during banking hours -as was also held in Libyan Arab Foreign Bank v Bankers Trust [1989] AC 80 PC for the application for the terms in relation to UK banks; d). The bank will give reasonable notice before closing a customer’s account if it is in credit; e). the customer will take reasonable care when writing cheques (Topic 1, n.d.). Implied terms are extra terms read into contracts by the courts in order to give effect to statutory requirements and common law presumptions (Robinson, 2009). Implied

Historical Homes in Natchez Mississippi Essay Example | Topics and Well Written Essays - 1750 words

Historical Homes in Natchez Mississippi - Essay Example Natchez is one of Mississippi’s oldest cities and was founded in 1716. It is also famous as the southern terminus of the National Trace Parkway, located along the River Mississippi. Due to its strategic location, the city became famous in American history for the role it played in the development of the Old South West. Lorenz, Karl G. (2000). Natchez is the county seat (National Association of Counties. 2008) of and the largest and only incorporated city within Adams County, Mississippi, in the United States. According to a census taken in 2000, Natchez has a population of about 18, 464 people. According to archaeological findings, the original site of Natchez was the chief ceremonial village that was occupied by an Indian tribe since the 8th century. The society of Natchez was segregated according to matrilineal descent into nobles and commoners and their chief was called the â€Å"Great Sun.† At Natchez, the Grand Village of the Natchez Indians is well preserved as a great National Historic Landmark, and is maintained by the Mississippi Department of Archives and History. Natchez Mississippi is very famous for some of the most interesting historical landmarks in the world. Our study would also cover this aspect of investigating the different important historical landmarks and make a detailed study of each one of them. Some of these important landmarks include Natchez National Historical Park, Fort Rosalie and many other interesting landmarks. Natchez National Historical Park celebrates the rich and interesting cultural history of Natchez, Mississippi and gives us an interpretation of the pivotal role that the city exhibited in the settlement of the Old Southwest, the Cotton Kingdom and the Antebellum South. The Park comprised of three different units and Fort Rosalie is the location of an 18th Century fortification built by the French which was

Nazi Germanys discrimination against the Jews Essay Example for Free

Nazi Germanys discrimination against the Jews Essay As a result of anti-Semitism in Nazi Germany, a system of violent suppression and control emerged that ultimately took the lives of an estimated 6 million Jewish people Anti-Semitism is an opposition to, prejudice against, or intolerance of Semitic people, most commonly Jews. Anti-Semitism has existed throughout history, since Israels dispersion in 70 AD. In every land in which the Jews have lived, they have been threatened, violated and murdered, century after century. After Germanys defeat in World War I, many Germans found it hard to accept their defeat. These Germans connived a theory that the citizens at home had betrayed them, especially laying blame on Jews and Marxists in Germany for undermining the war effort (http://www.historyplace.com/worldwar2/riseofhitler/ends.htm). This is the main reason that led to the extreme discrimination and removal of basic rights of Jewish people in Germany during the 1930s and 1940s, however, there were many other reasons including Christianitys general hatred for Jewry. Jews were often the victims of Nazism. The first Jewish victims of the Nazi era were 8 innocent people who were killed in the streets on 1 January 1930 by Brownshirts. Soon after that, violence against Jews in the streets became common. Violence was an integral part of the Nazi programme Jews were molested in cafes and theatres, synagogue services were disrupted and anti-Jewish slogans became the daily calling card of Nazi thugs. (Gilbert,2001:31) One particular night of violence, known as Kristallnacht, is remembered with fear. During the night of November 9-10, 1938 thousands of windows were smashed out of Jewish businesses and homes, hundreds of synagogues were burnt to the ground, and more than ninety Jews were murdered. On March 9, 1933 the first Nazi concentration camp was opened at Dachau. On  April 1, a boycott of all Jewish shops was put in place. It only lasted a day, because of threats of a counter-boycott in the USA of all German made goods. However, the expulsion of all Jewish people from Germanys Universities and then the Burning of the Books quickly followed the one-day boycott. The Burning of the Books consisted of 20 000 books burned in a massive bonfire in front of the Berlin Opera House, and opposite the University of Berlin. The books that were destroyed were judged to be degenerate and intellectual filth by the Nazis, many being written by Jewish authors. Also during this time, Jewish scientists and intellectuals were dismissed from their positions, and Hitler was quoted as saying If the dismissal of Jewish scientists means the annihilation of contemporary German science, we shall do without science for a few years. In late 1939, the first ghettos were created in Poland. All Jews were forced to move into a designated area of a city or town, which was surrounded by brick walls topped with barbed wire, and guarded by armed men. SS General Heydrich ordered that the ghettos were to be located on railway junctions, or along a railway so that future measures may be accomplished more easily. Large numbers of people had to share small living quarters, and medical supplies and food were limited. The Jews could only bring into the ghettos what they could carry, and their luggage was searched and pillaged on their arrival. Life in the ghettos was hard, and death rates were high. Most of the deaths in the ghettos were by starvation or disease. In the two largest ghettos in Poland, Warsaw and Lodz, the death toll from starvation alone in the first twelve months after the creation of the ghettos reached approximately 42 000. In most of Western Poland, there were no ghettos. This was because General Heydrich had ordered Western Poland to be cleared completely of the Jews. Immediately after the Germans invaded a town, they rounded up all the Jewish people, made them dig large pits, then shot and buried them just outside the town. The ghettos were also referred to as concentration camps and slave labour camps. This was because while the Jews resided in the ghettos, they could be forced to work up to fourteen hours a day in some circumstances. Some were deported to separate concentration camps where they would work on farms in the country to maintain a food supply for the German war machine. Others who stayed in the ghettos worked for the Nazis in munitions factories making armaments, or for local businessmen who paid the government for the use of slave labour to work their factories. These Jews were mostly considered totally expendable, and were subject to minimal food rations, a lack of medical attention, and violent beatings. At least half a million Jews died as slave labourers. The extermination camps, or death camps were the sites for hundreds of mass murders. Men, women and children were deported from ghettos and concentration camps to these death camps and usually taken straight from the train to a gas chamber where they were gassed to death. A few hundred people were kept alive as slave labour to sort through the clothing and luggage of the victims. A small part of this labour force was known as the Death Jews. These Jews performed the task of removing bodies from the gas chambers and stripping them of anything of value. They then dragged the corpses to a crematorium where the naked bodies were burnt. Most of the labour forces were killed and replaced whenever a new group of deportees arrived. The most infamous death camp was Auschwitz, where mostly deportees from Western Europe and southwest Poland were taken. Lilli Kopecky, a deportee from Slovakia recalls arriving at Auschwitz: When we came to Auschwitz, we smelt the sweet smell. They said to us: There the people are gassed, three kilometers over there. We didnt believe it. (Gilbert,2001:77) More than a million Jews were murdered at Auschwitz alone. The Holocaust is probably the most infamous instance of anti-Semitism in History. The oppressive tactics of Nazi Germany took away all the rights of the Jews, and wiped out almost the entire race of Jewish people in Europe. If the Nazis had succeeded in what they came so close to doing, there would not be a trace of Jewry remaining in Europe today.

Causes and Effects of the French Revolution :: European Europe History

Causes and Effects of the French Revolution Revolution? The major cause of the French Revolution was the disputes between the different types of social classes in French society. The French Revolution of 1789-1799 was one of the most important events in the history of the world. The Revolution led to many changes in France, which at the time of the Revolution, was the most powerful state in Europe. The Revolution led to the development of new political forces such as democracy and nationalism. It questioned the authority of kings, priests, and nobles. The Revolution also gave new meanings and new ideas to the political ideas of the people. The French Revolution was spread over the ten year period between 1789 and 1799. The primary cause of the revolution was the disputes over the peoples' differing ideas of reform. Before the beginning of the Revolution, only moderate reforms were wanted by the people. An example of why they wanted this was because of king Louis XIV's actions. At the end of the seventeenth century, King Louis XIV's wars began decreasing the royal finances dramatically. This worsened during the eighteenth century. The use of the money by Louis XIV angered the people and they wanted a new system of government. The writings of the philosophes such as Voltaire and Diderot, were critical of the government. They said that not one official in power was corrupt, but that the whole system of government needed some change. Eventually, when the royal finances were expended in the 1780's, there began a time of greater criticism. This sparked the peasants notion of wanting change. Under the Old Regime in France, the king was the absolute monarch. Louis XIV had centralized power in the royal bureaucracy, the government departments which administered his policies. Together, Louis XIV and the bureaucracy worked to preserve royal authority and to maintain the social structure of the Old Regime. At this time in French history, the social classes played an important role in the lives of the people. The social structure of France was divided among three groups: the First Estate, the Second Estate, and the Third Estate. Each social group had a varied type of people within their structure, which presented the different views of the people. The First Estate was the Church. During the ancien regime, the church was equal in terms of its social, economic, and spiritual power. The First Estate owned nearly 10 per cent of all land in France.

Shakespeare’s Hamlet: A Conflicted Demonstration

Though Claudia also upset this order by murdering King Hamlet), for Hamlet to even consider killing Claudia, he crosses a moral taboo. Furthermore, when the ghost charges Hamlet to ‘Revenge his foul and most unnatural murder' and Hamlet accepts, replying ‘Haste me to Knott, that I with wings as swift/ As meditation or the thoughts of love/ May sweep to my revenge', he once again disregards the Christian value system that asserts Judgment and punishment to be only the right of God, and not of man.Hamlets only redeeming action, Is that after contemplating ‘To be, or not to be', he does not inevitably commit suicide: a death denied Christian burial. Secondly a sense of right and wrong can be derived from common sense, logic and the conscience. In this regard, Hamlet displays no moral integrity, as he firstly used Aphelia by displaying to her a faked ‘antic disposition' (ACTA, Sac. To which she was ‘so freighted' (ACTA, SSL) before allowing her to believe th at her love had been betrayed when he stated ‘I love you not' to her reply, ‘l was the more deceived' (Act, SSL After this, when given the opportunity to kill Polonium, ‘Now I might do it pat' he refrains because the victim ‘now a is a-praying' and the murder then would send him o heaven'. He shows no mercy, deciding to Walt till later when he is behaving In a way ‘That has no relish of salvation Inner choosing then to trip him that his heels may kick at heaven,] And that his soul may be damned and black,' As hell whereto It goes†¦ (ACTA, IS). It is possible however, that this example of postponing the revenge is an indication that Hamlet was perhaps reluctant, and did not truly wish to kill him. This indication of repressed guilt is also shown in ACTA Scenes where Hamlet states ‘†¦ I am myself indifferent honest, but yet I could accuse me of such things, that it ere better my mother had not borne me. I am very proud, revengeful, ambitio us, with more offences at my beck than I have thoughts to put them in, imagination to give them shape, or time to act them in'.Finally, a Judgment of moral integrity can take place when witnessing Hamlet's response to local laws. In this he varied. By Hamlet deciding to take Claudia' life In exchange for his fathers, he was following the pagan value systems of the era which accepted an ‘eye for an eye'. However, on discovering that Guilelessness and be struck off (ACTA, IS), he stole the commission, and illegally replaced it with a copy harming that Without debasement further, more, or less,] He should those bearers put to sudden death,] Not shriving time allowed'.Despite the action saving his life, Hamlet both broke a law, and ensured the death of those who once were his friends. Therefore, though it appears Hamlet believed he must extract his revenge, and at times showed unwillingness to do so, by this action and the behavior he used to carry it out Hamlet betrayed the relig ious rules, logic, common sense, conscience and law of the Elizabethan era, Hamlet displayed an at best conflicted, and at worst absent moral integrity.

Dividend Policy and Stock Price Behaviour in Indian Corporate Sector: a Panel Data Approach

Dividend Policy and Stock Price Behaviour in Indian Corporate Sector: A panel data approach Upananda Pani? Abstract: This paper attempts to explore the possible links between dividend policy and stock price behaviour in Indian corporate sector. A sample of 500 listed companies from BSE are examined for the years 1996-2006. Dividend policy has always been a source of controversy despite years of theoretical and empirical research both in developed countries and emerging economies. The present paper features a panel data approach to analyze the relationship between dividend-retention ratio and stock-price behaviour while controlling the variables like size and long-term debt-equity ratio of the firm. The sample is taken across six different industries namely electricity, food and beverage, mining, non-metallic, textile and service sector. The results are based on the fixed-effect model, as these perform statistically better than random effects and pooled OLS model. Results of the fixed-effect models indicate that dividend-retention ratio along with size and debtequity ratio plays a significant role in explaining variations in stock returns. The fixed effect models show the presence of firm level effect in explaining the possible links between dividend policy and stock price behaviour of the firm. In another words it exhibits the possibility of â€Å"clientele effect† effect in case of some industries. Therefore the model helps to understand the intricacies of dividend policy and stock-return behaviour in Indian corporate sector for the same period. Although the results are not robust enough as in the case of developed markets but shades some more interesting facets to the existing corporate finance literature on dividend policy in India. Kew Words: Dividened Policy, Stock Price, Corporate Finance, Fixed Effect Model JEL Code: G30, G35 Research Scholar, Indian Institute of Technology, Khragpur-721302. The author can be contacted [email  protected] ac. in ? 1 1. Introduction Dividend policy still remains an academic debate amid the clouding picture of its importance among the financial economists till today. There are few aspects of corporate financial policy where the gap between the academics and the practitioners is larger than that of the dividend policy. From Miller & Modigliani (1961)1, ,Gordon & Linter to Fama & French (2001)2 ,the research on the topic exhibits conflicting trends in dividend payments & firm value. The academic consensus shows that dividends really don’t matter very much for the market nor is relevant, when firms pay dividend as a signal to the investors. Both corporate officials and investment analysts, still continue to insist that a firm’s dividend policy matters a great deal for conveying the information to the stakeholders. One side of the argument on the basis of economic theory is, it doesn’t matter or is irrelevant. But the practitioners believe it as information content to the public, which reflects seriousness of the problem that is inherent in the reaction mechanisms of the market to the dividend policy announcements. I want to foreground an explanation before the practitioners, why, in the face of all this evidence of price increase in response to dividend announcements, otherwise sensible academics believe that a firm’s dividend policy really doesn’t make much difference. At the same time, I’11 argue that the dividends do matter for a firm. Dividend Policy & Share prices The dividend policy of a firm becomes the choice of financial strategy when investment decisions are taken as given. It is also imperative to know whether the firm will go for internal or external source of financing for its investment project. There are a number of factors affecting the dividend policy decisions of a firm such as investor’s preference, earnings, investment opportunities; annual vs. target capital structure, flotation costs, signaling, stability & Government policies and taxation. In the presence of asymmetric information, signaling is one of the crucial factors that influence the market. Dividends may convey information about the company, so it suggests the possibility of its influence 2 on the stock market. Paying large dividends reduces risk and thus influence stock price (Gordon, 1963) and is a proxy for the future earnings (Baskin, 1989) Baskin (1989) takes a slightly different approach and examines the influence of dividend policy on stock price volatility, as opposed to that on stock returns. He advances four basic models which relate dividends to stock price risk. He terms these as the duration effect, the rate of return effect, the arbitrage pricing effect and the informational effect. The difficulty in many empirical works examining the linkage between dividend policy and stock volatility or returns lies in the setting up of adequate control over the factors that influence both. For example, the accounting system generates information on several relationships that are considered by many to be measures of risk. Baskin (1989) suggests the use of the following control variables in testing the significance of the relationship between dividend yield and price volatility are operating earnings, the size of the firm, the level of debt, the payout ratio and the level of growth. So he had tried to explain the underlying linkage between dividend policies (dividend yield and dividend payout ratio) and stock price risk in his empirical work on USA. A number of theoretical mechanisms have been suggested that cause dividend yield and payout ratios to vary inversely with common stock volatility. As dividends can be cash dividends, stock dividends, stock splits & share repurchases, the question comes about the nature of the dividend & its impact on the share price and whether market is more volatile to high dividend yield share than normal share comes into the picture. There is a need to study the sensitivity of market to the nature of dividends. The linkage etween dividends & share price should be examined by controlling other factors which are responsible for affecting the dividend policy of a firm. Study of dividend policy and stock price in India As Indian stock market is one of the most volatile stock market in the world. As the no of private corporations are growing day by day, & financial markets becoming more developed, there need of the study of different policy implications by corporate sector. 3 There are a number of stu dies existing on the determinants of dividends3 behaviour in Indian context. All the studies have determined the dividend behaviour from the perspective of the factors influencing the dividend behaviour in the short run as well as in the long run4. But a very few literature captures the intricacies of market reaction to the dividend announcement by Indian corporate sector. The study by Reddy, Y S (2003) on dividend behavior of Indian corporate firms over the period 1990 – 2003 shows a conflicting picture of the dividend policy of firms across different industries. The study explores dividend trends for a large sample of stocks traded on the NSE and BSE, indicate that the percentage of companies paying dividends has declined from 60. 5 percent in 1990 to 32. 1 percent in 2003 and that only a few firms have consistently paid the same levels of dividends. Further, dividend-paying companies are more profitable, large in size and growth doesn't seem to deter Indian firms from paying higher dividends. Analysis of influence of changes in tax regime on dividend behavior shows that the tradeoff or tax-preference theory does not appear to hold true in the Indian context. This paper shows the contradictory results from the previous one. The limitations of these papers are they have taken only cash dividends for analyzing the determinant behaviour. The present paper is structured as follows as introduction. The subsequent section II follows the theoretical strands and section III highlights ed model for the purpose. The section IV denotes the data sources and variable construction. The section V shows empirical results and discussion. The last and final section displays the findings. II. Theoretical Strands and Literatures study The dividend irrelevance theory of Modigliani and Miller (1961) proposed the absence of any significant impact of the dividend policy on the value of shares because it’s impact is offset exactly by other means of financing and is thus irrelevant. This theory was formulated by assuming perfect market conditions, which didn’t take into account the imperfections like taxes, transaction cost or asymmetric information. Consequently, dividend policies have little impact on the market value of the firms. In a perfectly competitive market situation both the company, through its profit retention, and the 4 hareholders, through their dividends, might invest in the same assets, and hence, who’s making the investment does not matter for the economy as a whole. However, since the capital market is neither perfect nor complete the dividend irrelevance proposition needs to be applied carefully by focusing on effects of taxes, information content, agency cost and other relevant affecting variables. The Gordon model (1959) stock valuation model states the fair value of a stock should equal to the stock-dividend per share and the difference between the discount rate and the long-term dividend growth rate. The model assumes that the firm’s dividend will grow at a constant rate and that the discount rate stays the same for ever. The theory suggests if there will be an increase in dividend rate there will be simultaneously an increase in stock value of the firm. Fama (1998) is the advocate of modern corporate finance theory, which states that firms should be managed to create and maximize value. Here the value depicts the total price of a firm commands in the market that is the sum of the values of its equity and debt. Thus, the criteria and rules for correct financial decisions are oriented towards maximization of the total value of the firm. In theory, value maximization is appealing because it is associated with efficient allocation of resources, provided the capital market operates efficiently. That is, it rewards the most to firms that channel their resources to the best uses. Extensive empirical work on capital Market behaviour shows that the prices of corporate securities indeed respond to firms’ decisions in a way that appears to be consistent with expectations about the appreciation or depreciation of value in the market. The theory emphasizes the importance of corporate financing decisions on the value of the firm in the market. Thirumalvan & Sunita (2005) studied the impact of Share repurchases & Dividend announcements on Stock prices in the context of Indian Corporate sector during the period (2002-2004). They examined the signalling effect of Stock repurchases and Dividend announcements. The study examined abnormal returns across various repurchases level. They have taken the firms listed in the BSE Index for the purpose of 5 empirical investigation. The study covers the impact on stock prices five days prior and after the dividend announcement. The result exhibits the upward trend of share price movement after the dividend announcement. The crucial point of their findings is that positive signalling existed only for a day after the announcements. After which the extent of positivism of shares starts declining. Their finding shows that market reaction in the Indian context to events or announcements such as share repurchases and dividends generally fluctuate around day or two. The study can be cited as important for the present study. Sen and Ray (2003) have explained an interesting phenomenon regarding the key determinants of stock price in India. The study is based upon the stocks comprising the BSE index over a period 1988-2000. The empirical study revealed dividend pay-out is by far the single important factor affecting stock prices. The second factor comes earning per share which has very weak impact on the share prices. So the study explored one of the crucial factor dividend pay-out ratios having impact on Indian stock price. Black and Scholes (1974) in their study on the effects of dividend yield & dividend policy on common stock prices & returns They stated uninformed demand for dividends can result from dividend decisions which in turn derive from imperfections such as taxes, transaction costs and institutional investment constraints. Given the above background, the study makes an attempt to examine the effect of dividends and retention earnings on the stock price behaviour in Indian corporate sector in a partial macro economic framework. III. Proposed Derived Model In analyzing dividend and stock price behaviour, the most important point to begin with is an objective function representing a firm’s preference regarding dividend-retention mix instead of taking only dividend yield or payout ratio. Because the objective function is related to firm’s main motives & there has been a shift in it’s motives due to the dominance of joint stock corporations & the associated characteristics of separation of ownership & control. This shift can be characterized from the sole motive as maximization of rate of return on capital to other set of motives such as sales maximization, expansion of business. This set of motives contributing to an increase in the market value of the firm, also, is in consonance with the managing agency system of operation, which is a characteristics of Indian companies. Moreover, the separation of ownership & control also implies a difference in the objectives & preferences between firm’s management & its shareholders. From the shareholders side, their preferences depend upon mainly their income level & the degree of understanding of corporate stock –dealings & associated tax implications. Nevertheless, the behaviour of the shareholders may be generalized as that they prefer stable dividend rates & that the effect of taxes is only on the preference of the shareholders as the shareholders, who belong to the richer classes prefer low dividends and high retained earnings. The opposite is applicable in the case of middle income group of shareholders. On the other hand, the management behaviour can be relatively & conceptually distinguished between a ‘passive’ & an ‘active’ type5. The motives of passive management are similar to those of the shareholders & it efforts to ensure stable dividend. But firm also requires sufficient profit retentions to satisfy the firm’s long-term needs such as investment demand & liquidity needs etc. But the ‘active’ management aims at increasing the market value of the firm & the market price of shares as well. So while its credibility requires to emphasize on the shareholders preference, it’s general tendency would be to reduce dividends on the basis of different excuses like high tax rates on distributions, ‘tax shelter’ benefits. Given the vast diversity of stockholders, it is not surprising that, over time, stockholders tend to invest in firm’s whose dividend policies match their preferences. Stockholders in high tax brackets who do not need the cash flow from dividend payments tend to invest in those companies which either pay low or no dividends. By contrast, stock holders with low tax bracket will invest in companies with high dividends. This clustering of stock-holders in companies with dividend policies that match their preferences is called as clientele effect. So it suggests that firms get the investors they deserve since the dividend policy of a firm attracts 7 investors who like it. Second, it means that firms will have a difficult time changing an established dividend policy, even if it makes complete sense to do so. However in practice, it is reasonably assumed that managements are neither extremely ‘passive’ nor extremely ‘active’ and shareholders are neither rich nor badly dependent or dividend income alone but contain all the elements in different combinations. Thus, let’s consider a typical firm having a map of dividend preference curves, each indicating a specific level of utility obtained by alternative combinations of dividends & retentions. So the dividend preference function can be noted as: U = f (Dn, R) (3. 1) Where, Dn and R are the dividend and retention net of all taxes at all levels. The utility level can be seen as monotonically related to the motives of the management with respect to the shareholders preference. The shape of the utility curves might be a result of a process of accounting for their relative performances & the factors influencing such preferences as well. The second step is to represent the hypothesis that dividends affect stock prices or market value of the firm. The utility function can be represented as the function for optimizing the market value of the firm. The market value of the firm can be represented as Market value of the Firm = ? ? Dividends ? f ? Net profit , ? Re tained earnings ? ? ? (3. 2) The market value of the firm here is basically represented on the basis of Accounting Earning Analysis. Here the Net profit is derived from the current investment of the firm. The higher the net profit the higher will be the stock price. The market value of the firm also depends upon the ratio of Dividends to Retained Earnings because the profit is basically segregated into either dividend or retained earnings. If clientele effect is not present in the firm then higher dividends will lead to higher value of the share price whereas if the investors are rich then they will prefer lower dividend to retention. The 8 return on equity entirely depends on the net worth6 of a company. Equity return of a company depends upon dividends and retained earnings. If a company is going for dividends then the retained earning will be less, leading the firm to go for either newequity issues or External financing. If the flotation cost7 is high, the company will go for external financing which will be costlier for the firm than internal financing through equity. So the firm has to maximize the dividend to retained earnings ratio for any new investment aimed at firm’s growth. We can represent it through the following function; ? D? Pt = f ? Y , ? ? R? (3. 3) Where Y represents the net profit of the firm D represents ratio of dividends to retention earning of the firm. The ratio of R ividends to retained earnings acts as a proxy for future cash flow of the firm and share price, Pt , acts as the proxy for the absolute market value of the firm. While calculating the stock return on an equity share, we are basically interested to calculate the change in current price with respect it’s price in the previous period. So the equation (3. 3) can be represented as ? Pt ? ?P ? 0 ? ? ? ? = f ? Y , D ? , ? P R? ? ? ? 0 ? (3. 4) The eqn (3. 4) represents the change with respect to base price. We have assumed a CobbDouglas type of function represented as the following ? Pt ? ? Y ? ? D ? 2 ui ? ? = A? ? ? e ? P ? R ? P ? ? 0? ? ? ? 0? ?1 ? (3. 5) The equation (3. 5) can be expressed alternatively as 9 ?Y ? ?P? ?D? ln ? t ? = ln A + ? 1 ln ? ? + ? 2 ln? ? + ui ? P ? ?P ? ?R? ? 0? ? 0? (3. 6) We can write the above equation as ?Y ? ?D? ln Vit = ? i + ? 1 ln? ? + ? 2 ln? ? + uit ? P ? ?R? ? 0? (3. 7) Where ln A = ? i = 1†¦ N t = 1†¦ T, There may be potential links between size and volatility of stock returns of the firm. The size of the firm also exhibits crucial link between size and volatility. Small firms are likely to be less diversified in their activities and subject less investor’s scrutiny for the firm. But research is still confined to large listed companies. The Information on the stocks of smaller listed companies could conceivably be less informed and illiquid in nature. These firms are subject to greater price volatility as a result of above posed factors. So a control variable, long-run debt equity ratio is being added . When asymmetric information comes into the picture, there is also likely to be a link between borrowing & dividend policy. Baskin (1989) suggests that firms with a dispersed body of shareholders may be more disposed towards using dividend policy as a signaling device. The dividend policy may also be a function of size and there is a need to introduce size as a control variable. There is also a need of introducing control variables, which will reflect the corporate leverage. The earlier models have been aimed at capturing the effect of stock price and dividends but very few of them have tried to include the control variables such as debt-equity ratio and size of the firm. So in the present study, the focus is to fillup the limitations of the previous studies by using context-specific Panel-Data models including the control variables like leverage ratio and size of the firm. Through panel data estimation we can observe firm effect8 and time effect throughout the sample period. So now the eqn (3. 7) can be stated as ? Y ? ?D? ?D? ln Vit = ? i + ? 1 ln? ? + ? 2 ln? ? + ? 3 ( SZ ) + ? 4 ? ? +  µi + ? it ? P ? ?E? ?R? ? 0? (3. 8) Where V = value of the firm SZ = Ln (Total Assets) 10  µ i = firm specific component ? it = disturbance term IV. Analytical Framework We have already discussed the proposed model to be tested here to analyze the impact of dividends on stock returns. So in this section we will analyze the methodological issues over our proposed derived model. Simultaneously we will discuss other options available for the analysis. We will first analyze the results of different industry and then aggregate data over all the industry. The proposed model is here is ? Y ? ?D? ?D? Ln Vit = ? i + ? 1 ln? ? + ? 2 ln? ? + ? 3 ( SZ ) + ? 4 ? ? +  µi + ? it ? P ? ?R? ?E? ? 0? 4. 1 Where SZ = Ln (Total Assets)  µ i = Firm specific component ? it = Disturbance term Here the null Hypothesis is dividend or D/R ratio affects stock return i. e. H0: D/R affects Vit . We will test the results of the classical linear regression model and other tests. Then we will proceed to see if Panel data models improve the estimation. So we will propose different models before proceeding to fixed effect model. We will define four basic models to be tested before proceeding towards final estimation. 1. y it = ? + ? it (No group effect or xs) 2. y it = ? i + ? it (Group dummies only) 3. y it = ? + ? ?X it + ? it (Repressors only) 4. y it = ? i + ? ?X it + ? it (Xs and group effects) Model 1 on 2: H0: (no group effects on the mean of y) Model 1 on 3; H0: (no fit in the regression of y on xs) Model 1 on 4; H0: (no group effects or fit in regression) 11 Model 2 on 4; H0: (group effects but no fit in regression) Model 3 on 4; H0: (fit in regression but no group effects) We have tested the data set for applying the panel data models with the above five different hypothesis. The LR, F and LM Test along with the Hausman Specification test favors the use of fixed effect models for Food and Beverage, Mining Industry and Nonmetallic Industry whereas the diagnostic tests rejects the use of fixed effect models for Other services, Textile industry, and Mining industry. The Aggregate data is also not satisfying the qualifying criterion for applying Fixed effect models. V. Data Sources and Sample Design The study mainly relies on the Prowess database of the CMIE (centre for monitoring on Indian economy) in India in order to mitigate the above noted objectives. Since the present study aims at exploring the dividend and stock return volatility with the assumptions of â€Å"semi strong efficiency† in the stock market a sample of 500 companies from â€Å"A1† and â€Å"B1† group of shares is selected for the empirical analysis. All of them are spread across six different industries namely Electricity, Food and Beverage, Mining, Non-metallic, Textile and Service Sector. The first filtering criterion for selecting the stocks is their consistency with the dividend payment history for the study period 19962006. The second filtering criterion used for the selection is that the market-capitalization of these companies should be more than ten crores. The third filtering criterion is that the scrip must be traded continuously without any interruption during the above mentioned period. However, the study has conceptualized the dependent variable (i. e. market value of the firm) and the explanatory variables such as size of the firm, dividends to retain earning ratio, and debt to equity ratio. The stock return is considered as proxy for the market value of the firm (dependent variable) and for other subsequent variable, Ln (total assets of the firm) have taken as a proxy. 12 Sock Return: Market value of the firm which is the dependent variable of our interest is being represented by Stock Return . This can be calculated by taking closing share prices of each company. Stock returns should be calculated using the log return of the closing price of the stock, where the Closing price is defined as the last trade price of the stock. Vit = ln (Pt/Pt-1). Net profit Here the net profit is taken as the profit after taxes. Average book value of equity Profit after taxes is calculated as the difference between the profit before taxes and tax for the year. PBIT or Profit before interest and taxes is generally calculated as the sum of operating profit and non-operating surplus/ deficit. This represents a measure of profit which is not influence by financial leverage and the tax factor. Hence, it is pre-eminently suitable for inter-firm comparison. Hence it is assumed that higher Net profit of a firm leads to higher share prices as opposed to stock returns. It is denoted as Y in the study. P0 Dividend ? D? ? ? This can be calculated by adding together all the annual Re tained earnings ? R ? cash dividends paid to common shareholders & then dividing this summation by the total no of outstanding equity shares in each year. The average of all available years will be used. Retained earnings is calculated as the difference between profit before taxes and dividends and dividend by the total no of outstanding equity shares each year . Like Earnings, dividends act as proxy for the future profitability . Therefore this ratio is expected to have positive relationship with the stock return. Long term debt (Debt to Equity ratio) is calculated as the sum of each company’s debentures, mortgages & loans with a maturity greater than one year to total equity is to be calculated. The average over all the years will be used. 13 Size of the Firm (SIZE) The variable size should be constructed in such a way that it will reflect the value of the firm in real terms. Here the natural log of Total assets is being used as a proxy for size. VI. Empirical Estimation and Results Discussion The basic principles of fixed-effect model have already been discussed in the previous section. So in this section we attempt to estimate our proposed model. In this section we present the results in two sections. We present first the results of those industries that how the applicability of fixed effect models by our previous section of hypothesis testing. And those industries that don’t satisfy our criterion in another sections (table 4. 9). Here we test the other models and the significance of our target variables. The results from the regression analysis are discussed in two sub-sections. The first section is the result of the Table 8, which exclusively covers the regression result of one-way fixed effect model for Electricity, Food and Beverage and Non-Metallic Industry. The other section of the result from the Table 9,covers the regression from the other three industries that did not satisfy the filtering criterion of hypothesis for fixed effect model. These industries are other services, Textile and Mining. In the last section we discuss about the results of aggregate data. Electricity Industry:As we have already discussed in the previous chapter, we have taken one-way fixed effect model. The result for the electricity industry can be summarized as follows. Before estimating the final model, we have tested different combination of variables. The estimation of one way fixed firm effects multivariate regressions illustrate that controlling for the underlying time-invariant heterogeneity of firms has significant effect on results. The coefficient for PAT/P0 is 9. 32 which is significant at 5% level of significance. It explains 9. 32% variation in the model. The variable D/R is also exhibiting positive relationship with stock-returns. It implies higher the dividend paid 14 to the investor higher will be the return in the long-run. The co-efficient for D/R is 2. 48 which is significant at 1% level. This implies validity of the model through the dividends and retention. The coefficient of leverage ratio or D/E ratio is -1. 89% which is significant at 10% level. The negative sign of the coefficient implies the negative relationship between the stock return and D/E. As the leverage ratio will be higher then it will have a negative impact on the stock-return. The coefficient for another variable size is . 96 which is coming insignificant at any level of confidence. The standard error is also coming very high at 12. 54. The R2 for the model is 0. 44, which is explaining 44% variation for variation in the dependent variable stockreturn. The p value of F-test is significant at 1% level. The computed F-tests (Fixed firm effect versus pooled OLS) of the null hypothesis that all coefficients are jointly equal to zero are rejected. The one-way fixed effect model explains the relationship more clearly as it explains more than 50% level of variation of firm-specific component in the model. So the over all explanatory power of the model is high in the Electricity Industry. Food and Beverage Industry:- The computed F-test results favors the use of the fixed-effect model over the Pooled OLS is justifiable over the test of OLS vs. Fixed effect model. The Hausman statistics is also high suggesting the use of the fixed effect model over the random effect model. Before estimating the model with variables D/R, PAT/P0, D/E and SZ with Stock return, we have tried with different combination of independent variables with the stock-return. The Current model gave the high R2 and low standard errors. The coefficients for the variables D/R, PAT/P0, D/E and SZ are 3. 05, 11. 09,-1. 41, . 68 respectively. Here the variables D/R and PAT/P0 are significant at 1% and 5% level of significance. The coefficients for the control variable which is included to control the heteroscedasticity is significant for size of the firm which explains 68% variations in the stock-return is and the coefficient for the debt-equity ratio is -1. 41. The most important result is that the dividend retention ratio is positive and explains 11. 09% variation in stock return. The R2 is 0. 36, explaining 36% variation in the dependent 15 variable i. e. Stock return. The F-test for Pooled OLS Vs Fixed effect turns out to be significant and the null-hypothesis that all the co-efficients are zero is rejected here. Non-metallic industry:- The coefficients for the variables D/R, PAT/P0, D/E and SZ are . 024, 10. 58,0 -. 88 and 30. 5 respectively. The variables are significant at 5%, 1%, and 10 %( Sz. ) level of significance in T-test for testing the null-hypothesis that the means of the co- efficients are zero. The sign of the D/R remains positive here. It explains positive relationship with the stock-return. So the D/R ratio explains 11. 98% variation in the stock-return behaviour of the firms. It supports the null-hypothesis that D/R affects the stock prices. Another important observation is that the coefficient of size of the firm is 30. , which is quite high in comparison to the other industry. The variables are insignificant in other models like pooled OLS, so the F-test rejected the hypothesis that all co-efficients are jointly equal to zero. The R2 is coming with improved performance of 0. 46%, which is high in comparison with other two industries. After all Non-metallic industry is showing robust result with th e expected sign as proposed in methodology. Results from the Table 9:- We have presented another analysis for other services, Textile Industry and Mining industry because these industries are not satisfying the criterion for the fixed effect model. So the next best alternative is to test it with pooled OLS and Random effect model. We have done comparison with these three models for these industries. Other Services Industry:- If we compare the results of the fixed effect model and Random effect model here, then some interesting picture emerges. The co-efficients for the fixed firm effect model for the variables D/R, PAT/P0, D/E and SZ are coming 6. 37, . 33,-10. 54, 2. 61 respectively. Among the co-efficients D/R and D/E are significant at 10% level of 16 significance. D/R is surprisingly significant with a positive sign according to our prior expectation. We then compare the R2 value of two models, which is very low i. e. 0. 09 for fixed firm effect model and 0. 11 for the random effect model. Although R2 turns out to be very low the variable D/R and D/E ratio is exhibiting correct sign as per the hypothesis is concerned. The F-test for comparing the coefficients are equal to zero or not is becoming insignificant for the variables. This can be observed through the p-value which comes out 0. 9870. This is not significant at 1%, 5%and 10% level of significance. In the Random effect model the Coeff for the variables D/R, PAT/P0, D/E and SZ are 4. 9, 0. 53,-8. 09 and 13. 96 respectively. The R2 improves by two points to 0. 11 the target variable D/R ratio remain insignificant in the model. May be the cause for insignificant variables and low explanatory power of the model is due to improper specification which is affected by the industry characteristics. The firms in the Services industry generally went for less dividends and more retenti on in the study period. These are high growth firms which require more flow of money for the projects. So the investors got return through the capital gains here. Textile Industry:- If we observe the Coeff for the variables D/R, PAT/P0, D/E and SZ, the values are 5. 28, . 10, -1. 73,5. 95 and for the Random effect model the values are coming out 4. 83,. 17,-1. 30 and 0. 87 respectively. The results show some unexpected outcomes in the model. The signs of the Coeff are as per prior expectation but D/E ratio is out significant at 5% level in fixed firm effect model and other variables are remaining highly insignificant with R2, 0. 04 . In the Random effect model, the target variable D/R is significant at 5% level and PAT/P0, D/E ratio are significant at 10%, 1% level of significance respectively. The R2 for the random effect model has improved to 0. 13%. When we compare the result between two models, random effect model turns out to be more robust than the fixed effect model. 17 Mining Industry:- The values of the co-efficients for the variable D/R, PAT/P0, D/E and SZ, are 17. 07, 14. 75,-13. 77, 4. 09 and for the Random effect model the co-efficients are 16. 01, 10. 08,-6. 63 and 1. 66 respectively. In fixed effect model three Coeff. of PAT/P0, D/R and D/E ratio remain significant at 5%, 1%, and 10% respectively. The R2 for the fixed firm effect model remains at 0. 0 and for the random effect model it is 0. 14. We cannot judge the models by the R2 only because we have to check out the significance of the variables. So given these conditions, the fixed effect model is more appropriate in the Mining industry. Aggregate Industry Data:- As we have examined above the different industry wise data, only three Electricity, Food and Beverage and Non-metallic satisfy the tests for use of the fixed firm effect model whereas other three industries namely Textile, Mining and Other services do not satisfy the test criterion in favour of fixed effect model. Aggregate industry data doesn’t shows any robustness for using fixed-effect model over other possible models such as pooled OLS and Random Effect model. The results from fixed-effect models is having leverage over the random effect model results . The aggregate data of whole industries is affected by those industries, which are not satisfying the criterion for fixed effect model. The overall explanatory power of the Aggregate industry data are affected the fluctuations in other industries as the data set is characterized by different industry. So when we run the regression of one-way fixed effect model, the R2 is also exhibiting very low at 0. 12 only. The value of the Coeff of the variables D/R, PAT/P0, D/E and SZ are coming out 3. 10, . 34,-. 60, -. 15 respectively. If we observe the sign of the variables D/R, D/E and PAT/P0 remains as per prior expectation. Among the Coeff of variables, PAT/P0 and D/E come out significant at 1% and 5% level of significance. Whereas if we compare the result with random effect model, we will find that no variables are significant and the R2 turns out to be very low at 0. 08 18 only. The p-value of F-test is also coming very high at 0. 6, which is well above the 0. 01and 0. 05 level of significance. The use of the fixed effect model in aggregate data explained the variation of the independent variables more clearly than Random effect model and Pooled OLS model. VII. Conclusion We have tried to explore the relationship of dividends and stock return by using a simple Specification of stock r eturn as a function of net profit and dividend-retention ratio with two control variable such as size & debt-equity ratio of the firm. There was an attempt to test different structural tests before proceeding towards the final estimation through panel-data modeling. The exclusive tests of different model allow us to go for the use of panel-data modeling. As we have given six different industry classifications for the study, we have tested the proposed model for each industry separately with different combination of variables. The results display statistical significance and linearity when the industry classifications are given. The regression on aggregate data remains in significant. .However, the direction of relationship between the dependent variable is as per prior expectation. In other words dividend retention ratio is positively related with the stock-returns. In case of aggregate data which consists of all firms above from industry classifications, the regression lacks statistical significance, the null hypothesis that there is no relationship between the dependent variable and independent variable cannot be rejected. 19 When the fixed firm effect regression is applied on sample firms of classified industry category-wise, we observe some industry specific peculiarities. Firms of Electricity, Food and beverage and Non-Metallic Product show some robustness in the results of the regression. The signs of the coefficient and their value remain significant in the analysis. Other three industries, textile, mining and other services are exhibiting insignificant coefficients values and very low R2. This conflicting trend of these variables is also visible when we have tried Pooled OLS and Random effect model. When we relax the industry classification and with the same data set and variables, fixed effect model shows the regression is significant at 0. 05 level of significance as the p value of getting a higher or equal value than calculated f-value is 0. 0497, which is we can reject the null hypothesis that all coefficients are equal to zero. Another important result is the sign of the leverage ratio and the coefficient remain as per prior expectation. The negative sign of the debt-equity ratio implies the negative relationship between the stock-return and debt-equity ratio. As the firm will go for more debt, then its value is going to be affected by stock-return. Size of the firm remains consistently positive but in many cases it turns out to be insignif icant. So we can not generalize about the variable size. So we can conclude that dividends have impact on the stock-return in Indian corporate sector, which is industry specific. The study explores that the dividend paying companies are large, profitable and growth rate of the firm does not seems to dissuade the dividend payment. Although the regression is not showing high R2 but Net profit and Dividend and Retention Ratio remains significant in other services, mining and Textile industries. 20 Appendix Electricity Industry (Table 1) Models R2 H0 LRTest Chisqu. 114. 3 pvalue F-test FVal. 52. 06 pvalue LM-Test vs. Model-3 Haus. Spec. Fix vs. Ran. 1. Constant term only 2. Group effects only 3. X-variables only 4. X & group effect 5. Fit in Reg. but no Group effect. . 0000 M1 on 2 M1 on 3 M1 on 4 M2 on 4 M3 on 4 0. 001 0. 000 Chi 2 (1) 36. 21 p value; chi 2 =0. 000 0. 4245 123. 4 156. 6 0. 000 0. 000 113. 5 121. 9 0. 002 0. 010 1. 52 p ; chi 2 (1) 0. 2183 0. 2135 0. 63 141. 5 0. 100 128. 6 0. 000 0. 24 129. 5 0. 000 134. 7 0. 100 Note: – Large values of Hausman statistics argue in favour of the fixed effect model over the random effect model. 2. Large val ues of the LM statistics argue in favour of the one factor model (either Fixed or Random depends upon further Hausman Specification test) against the classical regression with no group effects. . A large value of the LM-statistics in the presence of a small Hausman statistics argues in favour of the random effect models. 4. If p ; 0. 10, then the test is significant at 90% confidence level, if p; 0. 05, then the test is significant at 95% level of confidence. If p; 0. 01, then the test is significant at 99% level of confidence. 5. The p-value of the LR test will be set to 1 if it is determined that your estimate is close enough to zero to be, in effect, zero for purposes of significance. Otherwise, the p-value displayed is set to one-half of the probability that a chi-square with 1 degree of freedom is greater than the calculated LR test statistic. 21 Food and Beverage Industry (Table 2) Models R2 H0 LRTest Chisqu. 113. 4 pvalue F-test FVal. 112. 9 pvalue LM-Test vs. Model-3 Haus. Spec. Fix vs. Ran. 1. Constant term only 2. Group effects only 3. X-variables only 0. 000 M1 on 2 M1 on 3 M1 on 4 M2 on 4 M3 on 4 0. 000 0. 000 Chi 2(1) 34. 21 2. 53 0. 32 134. 2 0. 000 132. 5 0. 000 p ; chi 2(1) p; chi 2=0. 000 0. 41 4. X & group effect 0. 53 103. 5 142. 8 0. 000 0. 000 126. 5 176. 5 0. 004 0. 3831 0. 001 5. Fit in Reg. ut no Group effect. 0. 24 121. 7 0. 002 183. 5 0. 000 Mining Industry (Table 3) Models R2 H0 LRTest Chisqu. 116. 070 pvalue F-test F-Val. pvalue LM-Test vs. Model-3 Haus. Spec. Fix vs. Ran. 1. Constant term only 2. Group effects only 3. X-variables only 4. X & group effect 0. 00 M1 on 2 M1 on 3 M1 on 4 M2 on 4 M3 on 4 0. 000 52. 084 0. 000 Chi 2(1) Chi 2 (1 ) 2. 02 p; chi2 (1) 0. 7318 0. 21 150. 894 0. 001 170. 23 0. 000 1. 21 p ; chi 2(1) 0. 32 161. 23 0. 003 232. 419 0. 000 0. 2721 0. 42 277. 186 0. 005 186. 03 0. 001 5. Fit in Reg. but no Group effect. 0. 15 172. 5 0. 000 58. 78 0. 000 22 Non-Metallic Industry (Table 4) Models R2 H0 LRTest Chisqu. 119. 070 pvalue F-test FVal. 21. 00 pvalue LM-Test vs. Model-3 Haus. Spec. Fix vs. Ran. 1. Constant term only 2. Group effects only 3. X-variables only 4. X & group effect 0. 00 M1 on 2 M1 on 3 M1 on 4 M2 on 4 0. 000 0. 000 chi2(1) = 3. 92 chi2(3) = 1. 23 Prob;chi2 = 0. 0013 0. 21 154. 894 0. 000 31. 01 0. 000 Prob ; chi2 = 0. 0477 0. 13 165. 23 0. 000 12. 02 0. 064 0. 25 267. 186 0. 000 49. 64 0. 000 5. Fit in Reg. but no Group effect. 0. 31 M3 on 4 172. 05 0. 214 64. 57 0. 741 Models R2 Other services Industry (Table 5) H0 LRpFTest value test ChiFsqu. Val. 0. 060 11. 00 on 2 pvalue LM-Test vs. Model-3 Haus. Spec. Fix vs. Ran. 1. Constant term only 2. Group effects only 3. Xvariables only 4. X & group effect 5. Fit in Reg. but no Group effect. 0. 01 M 1 109. 70 164. 89 0. 087 chi2(1) = 0. 30 chi2(4) = 1. 39 Prob;chi2 = 0. 8460 0. 24 M 1 on 3 0. 000 41. 01 0. 001 Prob ; chi2 = 0. 5812 175. 23 0. 000 52. 02 0. 020 0. 14 M1 on 4 217. 19 0. 000 79. 64 0. 000 0. 33 M 2 162. 05 on 4 M3 on 4 0. 000 95. 4 0. 000 23 Textile Industry (Table 6) Models R2 H0 LRTest Chisqu. 139. 070 pvalue F-test FVal. 71. 00 pvalue LM-Test vs. Model-3 Haus. Spec. Fix vs. Ran. 1. Constant term only 2. Group effects only 3. X-variables only 4. X & group effect 5. Fit in Reg. but no Group effect. 0. 03 M1 on 2 M1 on 3 M1 on 4 M2 on 4 M3 on 4 0. 000 0. 000 chi2(1) = 7. 75 Prob ; chi2 = 0. 0054 = 3. 50 0. 14 124. 894 0. 000 44. 00 0. 000 Prob;chi2 = 0. 4774 0. 21 195. 23 0. 000 22. 02 0. 000 167. 186 0. 000 152. 05 0. 000 69. 67 96. 8 0. 000 0. 001 0. 43 Aggregate Data (Table 7) Models R2 H0 LRTest Chisqu. 169. 70 pvalue F-test FVal. 31. 01 pvalue LM-Test vs. Model-3 Haus. Spec. Fix vs. Ran. 1. Constant term only 2. Group effects only 3. X-variables only 4. X & group effect 5. Fit in Reg. but no Group effect. 0. 02 M1 on 2 M1 on 3 M1 on 4 M2 on 4 M3 on 4 0. 000 0. 00 chi2(1) = 0. 01 chi2(4) = 1. 28 0. 11 184. 94 0. 000 51. 01 0. 000 Prob ; chi2 = 0. 9425 Prob;chi2 = 0. 8649 0. 21 145. 23 0. 000 62. 42 0. 000 0. 24 257. 186 0. 000 172. 95 89. 84 0. 000 24 Table 8 Results of Fixed-effect model Industry Variables Coeff. Fixed effect model S. E R2 F. V PAT/P0 Electricity Industry D/R D/E Size PAT/P0 Food & Beverage D/R D/E Size P AT/P0 Non-Metallic D/R D/E Size 9. 32** 12. 48* -1. 89*** . 96 3. 05* 11. 97** -1. 41* . 68 . 024** 10. 58* -. 88 30. 5** 5. 84 . 0794 4. 38 12. 54 1. 63 . 18 0. 71 1. 79 . 04 1. 74 2. 72 4. 70 0. 46 0. 36 0. 44 F(4,56)=11. 49 P;F= 0. 000 F(4,256) = 1. 26 0. 01 F(4,232) = 12. 21 Prob ; F = 0. 0000 Note:-1. Fixed effect model has no constant term. 2. *, **, *** represents 10%, 5% and 1% level of significance respectively 25 Table 9 Comparison of results of fixed effect model and Random effect model. Industry Variables C. F PAT/P0 D/R Other services D/E 6. 37 (12. 52) 0. 33*** (. 443) 0. 09 -10. 54*** (24. 56) 2. 61 (15. 52) 5. 28 (1. 83) 0. 10 (. 704) -1. 73** (1. 28) 5. 95 (2. 73) 17. 07** (10. 57) 14. 75* (27. 90) -13. 77*** (10. 79) 4. 09 (5. 80) 3. 10* (. 095) D/R Aggregate Data D/E . 34 (. 10) -. 60** (1. 89) -. 15 0. 10 0. 04 F. E R 2 R. E F F (4,182) = 0. 08 p;F = 0. 870 -8. 09*** (16. 69) 13. 96** (8. 43) 4. 83*** (1. 51) . 172** (. 667) -1. 30* (1. 066) . 87 (. 459) 16. 01** (8. 67) 10. 08*** (22. 26) -6. 63 (7. 39) 1. 66 (4. 91) -. 011 (. 0945) . 31 (. 1051) -1. 06 (1. 40) 0. 14 0. 13 C. F 4. 69 (9. 81) 0. 053 (. 426) 0. 11 R2 W W chi2(4 =2. 86 p;chi 0. 5819 Size PAT/P0 D/R Textile D/E Size PAT/P0 D/R Mining D/E Size PAT/P0 F (24,244) =0. 33 p;F =0. 990 Wald Chi 2(4)=10. 36 p;chi 2=0. 0348 F (4,46) =2. 00 p;F =0. 1097 Wald Chi 2 (4) =6. 35 p;chi 2 = 0. 1747 F (124,1232) = 16. 49 p;F 0. 76057 Wald Chi 2 (4) 0. 08 = 2. 31 p; chi2 0. 8745 0. 12 Size 1. 55 (1. 037) Note:- *, **, *** represents 10%, 5% and 1% level of significance respectively 26 References:Aharony, J. and I. Swary, 1981, â€Å"Quarterly Dividends and Earnings Announcements and Stockholders' Returns: An Empirical Analysis,† Journal of Finance, Vol 36, 1-12. Altman, E. I. , 1968, â€Å"Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy†, Journal of Finance, Vol 23, pp 589-609. Altman,E. I and V. Kishore, 1996, â€Å"The Default Experience of U. S. Bonds†, Working Paper, Salomon Center. Altman, E. I. , 1994, â€Å"Defaults and Returns on High Yield Bonds†, Working Paper, Salomon Center, New York University. Amihud, Y. B. Christensen and H. Mendelson,1992,†Further Evidence on the Risk-Return Relationship,† Working Paper, New York University. Asquith, P. and D. W. Mullins, Jr. , 1983, â€Å"The Impact of Initiating Dividend Payments on Shareholder Wealth,† Journal of Business, Vol 56, 77-96. Bailey, W. â€Å"Canada's Dual Class Shares: Further Evidence on the Market Value of Cash Dividends,† Journal of Finance, 1988, v43 (5), 1143-1160. DeAngelo, H. and E. M. Rice, 1983, â€Å"Antitakeover Charter Amendments and Stockholder Wealth†, Journal of Financial Economics, Vol 11, 329-360. DeAngelo, H. and L. DeAngelo, 1985, â€Å"Managerial Ownership of Voting Rights: A Study of Public Corporations with Dual Classes of Common Stock,† Journal of Financial Economics, Vol 14, 33-69. DeAngelo, H. , L. DeAngelo and E. M. Rice, 1984, â€Å"Going Private: The Effects of a Study in the Creation, Transfer and Destruction of Shareholder Value, Homewood, Ill. , Irfan, C. M. and Nishat, M. (2003),†Key fundamental factors and long run stock price changes in an emerging market- A case study of Karachi stock exchange†, Paper presented at PSDE conference, Islamabad. Jensen, M. C. nd Meckling, W. H. (1976) Theory of the firm: Managerial behaviour agency costs and capital structure, Journal of Financial Economics, (October) 305-60 Linter, J. , (1956), â€Å"Distributions of incomes of corporations among dividends, retained earnings and taxes†, American economic Review, 46 (1): 97-113. 27 Mendenhall, W. , and T. Sincich, (1989), A second Course in Business Sta tistics: Regression Analysis, Macmillan, London, New York. Miller, M. H. and Rock K. (1985) Dividend policy under asymmetric information, Journal of Finance, 40, September, 1031-51 Molodowsky, N. 1995, â€Å"A Theory of Price- Earnings Ratios†, Financial Analysis Journal, Jan. –Feb. 29-3. Nishat, M. (1992),†Share prices, dividend and retained earnings behaviour in Pakistan stock Market†, The Indian Economic Journal, Vol. 40 October-December, No. 2. Parkinson, Michael, â€Å"The Extreme Value Method for Estimating the Variance of the Rate of Return†, Journal of Business, Vol. 53, No. 1, University of Florida, (Jan. , 1980), pp. 61-65. Rappoport, (1986), â€Å"The affordable dividend approach to equity valuation†, Financial Analysis Journal, 42 (4): 52-58. Rozeff, M. S. 1982) Growth, beta and agency costs as determinant of dividend payout ratios, Journal of Financial Research, Fall, 249-59 Sharpe, W. , 1964, Capital asset prices: A theory of mar ket equilibrium†, The Journal of Finance, 19(1): 425-442. End Notes:1 Miller, Merton, and Modigliani, Franco, (1961) Dividend Policy, Growth, and Valuation of Shares, Journal of Business. 34. PP. 411-433. 2 Fama, Eugene F. & French, Kenneth R. , 2001. â€Å"Disappearing dividends: changing firm characteristics or lower propensity to pay? ,† Journal of Financial Economics, Elsevier, vol. 60(1), pages 3-43, April. 3 The term ‘dividends’, is defined inclusively under the Income Tax Acts, 1922 and 1961. The definition of Dividends includes distributions from accumulated profits wheather capitalised or not, which reduces the assets of a company or in the form of 28 debentures issue, distributions on liquidation or in the form of loan or advances to the extent such distributions are attributable to to accumulated profits. The definition for certain companies of closely held category, the definition is more inclusive 4 Sarma, JVM. (1990). â€Å"Taxation and corporate dividend behaviour in India†, Y V Reddy (2003). The trends of dividend Behaviour in Indian corporate sector. NSE working paper. 5 Sarma, J V M (1990) , Taxation and Corporate Dividend Behaviour in India, Harman Publishing House. 6 Net worth of a company refers to the difference between Total assets and Total debt of a company. 7 It refers to the cost of new-equity issues to be borne by the company, under the condition of imperfect market. 8 Firm effect refers to the effect of factors affecting the behaviour of an individual firm, if it is constant overtime. The time effect refers to the economic condition of particular time point : it varies over time. 29

Gary Barnett the Motivator essays

Gary Barnett the Motivator essays Gary Barnett changed Northwestern football when he arrived there in 1991. He put a mindset into the players and the school that they can overcome this and turn this program around. Gary brought enthusiasm to the team and made believers out of his players. He had calmness in the rough times giving the kids a reason not to panic if they just lost one game. In the 1995 season, Northwestern opened up the season beating Notre Dame at Notre Dame. Then the following they lost to a bad Miami (OH) team at home. That week Gary was distraught, but stayed calm and asked his team if they wanted to be the team that beat Notre Dame or the team that lost to Miami (OH). The reason he was such a good leader was because the kids believed in what Gary said. The team thought if they could trust him and have faith, they could do anything. Gary Barnett had many motivational techniques to get his players motivated. He thought you had to believe in yourself, to become successful. Gary made t-shirts that said Me to We. That was a way to tell his players that the only way they could win is if they believe in one another. One of his players wrote a paper on his motivational techniques. Northwestern has the lowest enrollment out of the whole Big Ten. They have an enrollment of only 7,500 kids. Where the University of Ohio State has about 31,000 kids. Gary didnt understand why kids didnt want to come, so it was his doing to change that. He did change that by telling his recruits that if you come to Northwestern that not only will you play football, but you will get a degree at a very good school. The kids realized that football doesnt last forever, but degree from Northwestern will be with you until the day you die. Darnell Autry and Tuscon Waterman decided to go to Northwestern for the education and not just to play football. They knew that with a degree from Northwestern they could get a job anywher ...

Thurgood Marshall, First Black Supreme Court Justice

Thurgood Marshall, First Black Supreme Court Justice Thurgood Marshall (July 2, 1908–January 24, 1993), the great-grandson of slaves, was the first African-American justice appointed to the United States Supreme Court, where he served from 1967 to 1991. Earlier in his career, Marshall was a pioneering civil rights attorney who successfully argued the landmark case Brown v. Board of Education, a major step in the fight to desegregate American schools. The 1954 Brown decision is considered one of the most significant civil rights victories of the 20th century. Fast Facts: Thurgood Marshall Known For: First African-American Supreme Court justice, landmark civil rights lawyerAlso Known As: Thoroughgood Marshall, Great DissenterBorn: July 2, 1908 in Baltimore, MarylandParents: William Canfield Marshall, Norma AricaDied: January 24, 1993 in Bethesda, MarylandEducation: Lincoln University, Pennsylvania  (BA), Howard University  (LLB)Published Works: Thurgood Marshall: His Speeches, Writings, Arguments, Opinions, and Reminiscences (The Library of Black America series) (2001)Awards and Honors: The Thurgood Marshall Award, established in 1992 by the American Bar Association, is presented annually to a recipient to recognize long-term contributions by members of the legal profession to the advancement of civil rights, civil liberties, and human rights in the United States, the ABA says. Marshall received the inaugural award in 1992.Spouse(s): Cecilia Suyat Marshall  (m. 1955–1993),  Vivian Burey Marshall (m. 1929–1955)Children: John W. Marshall,  Thurgoo d Marshall, Jr.Notable Quote: It is interesting to me that the very people...that would object to sending their white children to school with Negroes are eating food that has been prepared, served, and almost put in their mouths by the mothers of those children. Childhood Marshall (named Thoroughgood at birth) was born in Baltimore on Jan. 24, 1908, the second son of Norma and William Marshall. Norma was an elementary school teacher and William worked as a railroad porter. When Thurgood was 2 years old, the family moved to Harlem in New York City, where Norma earned an advanced teaching degree at Columbia University. The Marshalls returned to Baltimore in 1913 when Thurgood was 5. Thurgood and his brother Aubrey attended an elementary school for blacks only and their mother taught in one as well. William Marshall, who had never graduated from high school, worked as a waiter in a whites-only country club. By second grade, Marshall, weary of being teased about his unusual name and equally weary of writing it out, shortened it to â€Å"Thurgood.† In high school, Marshall earned decent grades but had a tendency to stir up trouble in the classroom. As punishment for some of his misdeeds, he was ordered to memorize portions of the U.S. Constitution. By the time he left high school, Marshall knew the entire document. Marshall always knew that he wanted to go to college but realized his parents couldnt afford to pay his tuition. Thus, he began saving money while he was in high school, working as a delivery boy and a waiter. In September 1925, Marshall entered Lincoln University, an African-American college in Philadelphia. He intended to study dentistry. College Years Marshall embraced college life. He became the star of the debate club and joined a fraternity; he was also very popular with young women. Yet Marshall found himself ever aware of the need to earn money. He worked two jobs and supplemented that income with his earnings from winning card games on campus. Armed with the defiant attitude that had gotten him into trouble in high school, Marshall was suspended twice for fraternity pranks. But Marshall was also capable of more serious endeavors, as when he helped to integrate a local movie theater. When Marshall and his friends attended a movie in downtown Philadelphia, they were ordered to sit in the balcony (the only place that blacks were allowed). The young men refused and sat in the main seating area. Despite being insulted by white patrons, they remained in their seats and watched the movie. From then on, they sat wherever they liked at the theater. By his second year at Lincoln, Marshall had decided he didnt want to become a dentist, planning instead to use his oratory gifts as a practicing attorney. (Marshall, who was 6-foot-2, later joked that his hands were probably too big for him to have become a dentist.) Marriage and Law School In his junior year, Marshall met Vivian Buster Burey, a student at the University of Pennsylvania. They fell in love and, despite Marshalls mothers objections- she felt they were too young and too poor- married in 1929 at the beginning of Marshalls senior year. After graduating from Lincoln in 1930, Marshall enrolled at Howard University Law School, a historically black college in Washington, D.C., where his brother Aubrey was attending medical school. Marshalls first choice had been the University of Maryland Law School, but he was refused admission because of his race. Norma Marshall pawned her wedding and engagement rings to help her younger son pay his tuition. Marshall and his wife lived with his parents in Baltimore to save money. Marshall commuted by train to Washington every day and worked three part-time jobs to make ends meet. Marshalls hard work paid off. He rose to the top of the class in his first year and won the plum job of an assistant in the law school library. There, he worked closely with the man who became his mentor, law school dean Charles Hamilton Houston. Houston, who resented the discrimination he had suffered as a soldier during World War I, had made it his mission to educate a new generation of African-American lawyers. He envisioned a group of attorneys who would use their law degrees to fight racial discrimination. Houston was convinced that the basis for that fight would be the U.S. Constitution itself. He made a profound impression upon Marshall. While working in the Howard law library, Marshall came into contact with several lawyers and activists from the NAACP. He joined the organization and became an active member. Marshall graduated first in his class in 1933 and passed the bar exam later that year. Working for the NAACP Marshall opened his own law practice in Baltimore in 1933 at the age of 25. He had few clients at first, and most of those cases involved minor charges, such as traffic tickets and petty thefts. It did not help that Marshall opened his practice in the midst of the Great Depression. Marshall became increasingly active in the local NAACP, recruiting new members for its Baltimore branch. Because he was well-educated, light-skinned, and dressed well, however, he sometimes found it difficult to find common ground with some African-Americans. Some felt Marshall had an appearance closer to that of a white man than to one of their own race. But Marshalls down-to-earth personality and easy communication style helped to win over many new members. Soon, Marshall began taking cases for the NAACP and was hired as part-time legal counsel in 1935. As his reputation grew, Marshall became known not only for his skill as a lawyer but also for his bawdy sense of humor and love of storytelling. In the late 1930s, Marshall represented African-American teachers in Maryland who were receiving only half the pay that white teachers earned. Marshall won equal-pay agreements in nine Maryland school boards and in 1939, convincing a federal court to declare unequal salaries for public school teachers unconstitutional. Marshall also had the satisfaction of working on a case, ​Murray v. Pearson, in which he helped a black man gain admission to the University of Maryland Law School in 1935. That same school had rejected Marshall only five years earlier. NAACP Chief Counsel In 1938, Marshall was named chief counsel to the NAACP in New York. Thrilled about having a steady income, he and Buster moved to Harlem, where Marshall had first gone with his parents as a young child. Marshall, whose new job required extensive travel and an immense workload, typically worked on discrimination cases in areas such as housing, labor, and travel accommodations. Marshall, in 1940, won the first of his Supreme Court victories in Chambers v. Florida, in which the Court overturned the convictions of four black men who had been beaten and coerced into confessing to a murder. For another case, Marshall was sent to Dallas to represent a black man who had been summoned for jury duty and who had been dismissed when court officers realized he was not white. Marshall met with Texas governor James Allred, whom he successfully persuaded that African-Americans had a right to serve on a jury. The governor went a step further, promising to provide Texas Rangers to protect those blacks who served on juries. Yet not every situation was so easily managed. Marshall had to take special precautions whenever he traveled, especially when working on controversial cases. He was protected by NAACP bodyguards and had to find safe housing- usually in private homes- wherever he went. Despite these security measures, Marshall often feared for his safety because of numerous threats. He was forced to use evasive tactics, such as wearing disguises and switching to different cars during trips. On one occasion, Marshall was taken into custody by a group of policemen while in a small Tennessee town working on a case. He was forced from his car and driven to an isolated area near a river, where an angry mob of white men awaited. Marshalls companion, another black attorney, followed the police car and refused to leave until Marshall was released. The police, perhaps because the witness was a prominent Nashville attorney, drove Marshall back to town. Separate but Not Equal Marshall continued to make significant gains in the battle for racial equality in the areas of both voting rights and education. He argued a case before the U.S. Supreme Court in 1944 (Smith v. Allwright), claiming that Texas Democratic Party rules unfairly denied blacks the right to vote in primaries. The Court agreed, ruling that all citizens, regardless of race, had the constitutional right to vote in primaries. In 1945, the NAACP made a momentous change in its strategy. Instead of working to enforce the separate but equal provision of the 1896 Plessy v. Ferguson decision, the NAACP strove to achieve equality in a different way. Since the notion of separate but equal facilities had never truly been accomplished in the past (public services for blacks were uniformly inferior to those for whites), the only solution would be to make all public facilities and services open to all races. Two important cases tried by Marshall between 1948 and 1950 contributed greatly to the eventual overturning of Plessy v. Ferguson. In each case (Sweatt v. Painter and McLaurin v. Oklahoma State Regents), the universities involved (the University of Texas and University of Oklahoma) failed to provide for black students an education equal to that provided for white students. Marshall successfully argued before the U.S. Supreme Court that the universities did not provide equal facilities for either student. The Court ordered both schools to admit black students into their mainstream programs. Overall, between 1940 and 1961, Marshall won 29 of the 32 cases he argued before the U.S. Supreme Court. Brown v. Board of Education In 1951, a court decision in Topeka, Kansas became the stimulus for Thurgood Marshalls most significant case. Oliver Brown of Topeka had sued that citys Board of Education, claiming that his daughter was forced to travel a long distance from her home just to attend a segregated school. Brown wanted his daughter to attend the school nearest their home- a school designated for whites only. The U.S. District Court of Kansas disagreed, asserting that the African-American school offered an education equal in quality to the white schools of Topeka. Marshall headed the appeal of the Brown case, which he combined with four other similar cases and filed as Brown v. Board of Education. The case came before the U.S. Supreme Court in December 1952. Marshall made it clear in his opening statements to the Supreme Court that what he sought was not merely a resolution for the five individual cases; his goal was to end racial segregation in schools. He argued that segregation caused blacks to feel innately inferior. The opposing lawyer argued that integration would harm white children. The debate went on for three days. The Court adjourned on Dec. 11, 1952, and did not convene on Brown again until June 1953. But the justices did not render a decision; instead, they requested that the attorneys supply more information. Their main question: Did the attorneys believe that the 14th Amendment, which addresses citizenship rights, prohibited segregation in schools? Marshall and his team went to work to prove that it did. After hearing the case again in December 1953, the Court did not come to a decision until May 17, 1954. Chief Justice Earl Warren announced that the Court had come to the unanimous decision that segregation in the public schools violated the equal protection clause of the 14th Amendment. Marshall was ecstatic; he always believed he would win, but was surprised that there were no dissenting votes. The Brown decision did not result in overnight desegregation of southern schools. While some school boards did begin making plans for desegregating schools, few southern school districts were in a hurry to adopt the new standards. Loss and Remarriage In November 1954, Marshall received devastating news about Buster. His 44-year-old wife had been ill for months but had been misdiagnosed as having the flu or pleurisy. In fact, she had incurable cancer. However, when she found out, she inexplicably kept her diagnosis a secret from her husband. When Marshall learned how ill Buster was, he set all work aside and took care of his wife for nine weeks before she died in February 1955. The couple had been married for 25 years. Because Buster had suffered several miscarriages, they had never had the family they so desired. Marshall mourned but did not remain single for long. In December 1955, Marshall married Cecilia Cissy Suyat, a secretary at the NAACP. He was 47, and his new wife was 19 years his junior. They went on to have two sons, Thurgood, Jr. and John. Work for the Federal Government In September 1961, Marshall was rewarded for his years of legal work when President John F. Kennedy appointed him a judge on the U.S. Circuit Court of Appeals. Although he hated to leave the NAACP, Marshall accepted the nomination. It took nearly a year for him to be approved by the Senate, many of whose members still resented his involvement in school desegregation. In 1965, President Lyndon Johnson named Marshall to the post of solicitor general of the United States. In this role, Marshall was responsible for representing the government when it was being sued by a corporation or an individual. In his two years as solicitor general, Marshall won 14 of the 19 cases he argued. Supreme Court Justice On June 13, 1967, President Johnson announced Thurgood Marshall as the nominee for Supreme Court Justice to fill the vacancy created by Justice Tom C. Clarks departure. Some southern senators- notably Strom Thurmond- fought Marshalls confirmation, but Marshall was confirmed and then sworn in on Oct. 2, 1967. At the age of 59, Marshall became the first African-American to serve on the U.S. Supreme Court. Marshall took a liberal stance in most of the Courts rulings. He consistently voted against any form of censorship and was strongly opposed to the death penalty. In the 1973 Roe v. Wade case, Marshall voted with the majority to uphold a womans right to choose to have an abortion. Marshall was also in favor of affirmative action. As more conservative justices were appointed to the Court during the Republican administrations of presidents Ronald Reagan, Richard Nixon, and Gerald Ford, Marshall found himself increasingly in the minority, often as the lone voice of dissent. He became known as The Great Dissenter. In 1980, the University of Maryland honored Marshall by naming its new law library after him. Still bitter about how the university had rejected him 50 years earlier, Marshall refused to attend the dedication. Retirement and Death Marshall resisted the idea of retirement, but by the early 1990s, his health was failing and he had problems with both his hearing and vision. On June 27, 1991, Marshall submitted his letter of resignation to President George H. W. Bush. Marshall was replaced by Justice Clarence Thomas. Marshall died of heart failure on Jan. 24, 1993, at age 84; he was buried at Arlington National Cemetery. Marshall was posthumously awarded the Presidential Medal of Freedom by President Bill Clinton in November 1993. Sources Cassie, Ron. â€Å"The Legacy of Thurgood Marshall.†Ã‚  Baltimore Magazine, 25 Jan. 2019.Crowther, Linnea. â€Å"Thurgood Marshall: 20 Facts.†Ã‚  Legacy.com, 31 Jan. 2017.â€Å"Past Recipients Keynote Speakers.†Ã‚  American Bar Association.â€Å"Thurgood Marshalls Unique Supreme Court Legacy.†Ã‚  National Constitution Center – Constitutioncenter.org.

I'm sending you two articles could you please use them only, extract Essay

I'm sending you two articles could you please use them only, extract the info and write about Non Lipid Cardiovascular Risk Factors and Flow basis Markers - Essay Example While the classical view of IHD has been the accumulation of plasma lipids and other sedimentary substances (plaques) on arterial walls, diminishing the lumens by large percentages till serious impediment to blood flow occurs that lead to the pathological condition. There are also other factors that progressively weaken and rupture arterial walls and also seriously affect blood flow (Libby, 2006). The principal predictive potential to assess degrees of progression towards cardiovascular disease is assaying the levels of these risk factors in the blood. These factors are consequently called biomarkers and since they generally affect blood flow to the heart they are also called flow basis biomarkers. This paper is assessing the predictive values of some non-lipid biomarkers. Biomarkers capable of predicting cardiovascular risk are generally categorised into eight groups - 'inflammatory markers, markers for plaque erosion and thrombosis, lipid-associated markers, markers of endothelial dysfunction, myocardial injury or dysfunction markers, oxidative stress, metabolic markers and markers of neovascularisation' (Cooke, 2006). Common lipid biomarkers are low density lipoprotein (LDL) and high density lipoprotein (HDL) cholesterol including oxidised LDL cholesterol, small dense LDL cholesterol, lipoprotein and lipoprotein-associated phosphol

Two State Comparison Finance of Higher Education Research Paper

Two State Comparison Finance of Higher Education - Research Paper Example About two-thirds of states allocate funds for education usually comprising from 10 to 12 percent of the state budget (NCSL 2010). In this work, I compared the Arkansas and Tennessee in their financing of higher education for possible lessons. Formula for state support to higher education. According to ADHE (2010, p. 3), A.C.A â€Å"establishes the process and key components for formula development for funding public institutions of higher education† that the State of Arkansas adopted. Based on ADHE (2010, p. 3), the content of the formula is the principle of providing â€Å"fair and equitable state support to all postsecondary students across the state, regardless of the state institution attended† while recognizing level requirements, equipment needs, unique missions, growth, economies of scale, and other factors. In contrast, compared to Arkansas’ equity-based formula, the formula adopted by the State of Tennessee for funding higher education is outcome and per formance-based. The TSBE (2011, p. 4) pointed this out very clearly when it emphasized a â€Å"productivity and efficiency through an outcomes-based funding formula† for higher education. The TSBE (2011 p. 5) reported that the outcomes based funding was approved for implementation since AY 2011-12 while the performance funding standard was approved for implementation since AY 2010-11. Institutional winners. ... Evaluating Tennessee’s progress on performance or outcome-based for higher education, however, may be too early because Tennessee has just begun their new policy. If outcomes and performance correlate with the income class of the student population, the likely winners in Tennessee will be the institutions catering to students from the rich. Conditions associated with state support for higher education. It follows from our discussion that the condition that should be associated for the state’s continuing support for higher education in Arkansas is that education should be extended especially to those disadvantaged by family income. However, there is no data available in the documents reviewed by this work suggesting that such a condition was imposed on the schools receiving state support in Arkansas. It also follows that the condition that should be associated for the state’s continuing support for higher education in Tennessee is improvement in educational perfor mance. However, similar to Arkansas, there is no data available in the documents reviewed by this work that such a condition was imposed in the schools for higher education in Tennessee. Trend on state support for higher education in the last five years. According to the CSEP (2009c), the ten-year budget change in the appropriation of state tax funds for the operating budget of higher education in Arkansas has been a positive 54.3%; the two-year change was 9.3%; the five-year change was 28.6% although the one year change was a negative 0.4%. Given the two-year change in state spending for higher education at 9.3%, the percentage change for Arkansas State spending for community college spending rose by only 9.0% between 2007 and 2009 (CESP 2009c). Nevertheless, based on