All-Electrical Aircraft Example

All All All-Electrical Aircraft al Affiliation Introduction To begin with, Sharon Weinberger highlights in the prologue in An All-Electric Aircraft? That those weighed down by hiked summer travelling expenses should cheer up and get ready for an exciting and aspiring breakthrough in upcoming aviation charges. This new anticipation is birthed by breaking news that scientist have presented a grand plan of coming up with an airplane that is 100% electric powered and fully equipped with superconducting engines. This is paradoxical. A new invention in aviation would instantaneously hike the aviation charges other than drastically reduce them as this prologue affirms. Weinberger points out the Scientist claims that superconductors are the pre-eminent option when selecting aviation constructing materials since they have been proved to retain 100% energy. According to Martins, on New research on superconductivity, superconductors have been affirmed to retain almost 100% energy since none of the ener gy dispensed with them is lost. This proves that the scientist claims hold water (Martins, 2007). Also, following Weinberg assertion that the grand plan of coming up with an electric airplane cannot be met by the contemporaneous technology based on the grand weight of the available magnets is questionable. Weinberg never considers other factors outside the scope of this assertion and also never points out additional claims to back up the proclaimed assertions. It is unusual to either credit or discredit the contemporary technology based on a single factor, whether real or false. Also, Sharon Weinberger points out that the upcoming aircrafts would be more serene and tranquil for having no in build driving engines. However, this claim contends with Taylor assertion in The Internal-Engine in Theory and Practice that the aviation turbulence and noise could result from other vast causes such as engine friction against other components or even combustion vibrations (Taylor, 1985). Rupa Ha ria highlights in the prologue of Is the Future of Aviation in Electric Aircraft? The chronological breakthroughs in aviation industry tracing them from 1903 Wright Brothers invention. Rupa then suggests the probability of advancement in aviation which may include a rebirth of an electric airplane. This is a systematic approach that is universal, aspiring and more convincing as compared to Weinberger approach. Rupa gives precise, bold standpoints why she feels that the anticipated invention will take over the aviation industry. She quotes that the electric airplanes are environmental friendly since no fuel ignition is involved. She also quotes the serene aura of the aircrafts for having battery driven engines that have drastically low noise rates. Rupa points out that the aviation charges are likely to drop drastically since the new aircrafts will utilize a cheaper fuel compared to the contemporaneous utilized fuel sources. Rupa winds up this article by asserting that embracing the anticipated electric airplanes will banish utilization of petroleum fuel, create an environmental friendly aura and save on fundamental resources such as aviation travel charges and time. It is without doubt that Rupa, through her brief scrutiny on the anticipated innovation in aviation, has presented her standpoint ideas in a logical, witty and concise approach which leaves the reader both intrigued and awakened.ReferencesMartins, B. P. (2007). New research on superconductivity. New York: Nova Science.Taylor, C. F. (1985). The internal-combustion engine in theory and practice. Cambridge, Mass: M.I.T. Press.An All-Electric Aircraft? (Webpage Timeline)wired.com/2007/06/an-all-electric/Is the Future of Aviation in Electric Aircraft? (Webpage Timeline)http://aviationweek.com/blog/future-aviation-electric-aircraft

Battle of the Crater in the Civil War

Battle of the Crater in the Civil War The Battle of the Crater occurred July 30, 1864, during the American Civil War (1861-1865) and was an attempt by Union forces to break the siege of Petersburg. In March 1864, President Abraham Lincoln elevated Ulysses S. Grant to lieutenant general and gave him overall command of Union forces. In this new role, Grant decided to turn over operational control of the western armies to Major General William T. Sherman and moved his headquarters east to travel with Major General George G. Meades Army of the Potomac. The Overland Campaign For the spring campaign, Grant intended to strike General Robert E. Lees Army of Northern Virginia from three directions. First, Meade was to ford the Rapidan River east of the Confederate position at Orange Court House, before turning west to engage the enemy. Further south, Major General Benjamin Butler was to move up the Peninsula from Fort Monroe and menace Richmond, while to the west Major General Franz Sigel destroyed the resources of the Shenandoah Valley. Commencing operations in early May 1864, Grant and Meade encountered Lee south of the Rapidan and fought the bloody Battle of the Wilderness (May 5-7). Stalemated after three days of fighting, Grant disengaged and moved around Lees right. Pursuing, Lees men renewed the fighting on May 8 at Spotsylvania Court House (May 8-21). Two weeks of costly saw another stalemate emerge and Grant again slipped south. After a brief encounter at North Anna (May 23-26), Union forces were halted at Cold Harbor in early June. To Petersburg Rather than force the issue at Cold Harbor, Grant withdrew east then moved south towards the James River. Crossing over a large pontoon bridge, the Army of the Potomac targeted the vital city of Petersburg. Situated south of Richmond, Petersburg was a strategic crossroads and rail hub which supplied the Confederate capital and Lees army. Its loss would make would Richmond indefensible (Map). Aware of Petersburgs significance, Butler, whose forces were at Bermuda Hundred, unsuccessfully attacked the city on June 9. These efforts were halted by Confederate forces under General P.G.T. Beauregard. First Attacks On June 14, with the Army of the Potomac nearing Petersburg, Grant ordered Butler to send Major General William F. Baldy Smiths XVIII Corps to attack the city. Crossing the river, Smiths assault was delayed through the day on the 15th, but finally moved forward that evening. Though he made some gains, he halted his men due to darkness. Across the lines, Beauregard, whose request for reinforcements had been ignored by Lee, stripped his defenses at Bermuda Hundred to reinforce Petersburg. Unaware of this, Butler remained in place rather than threatening Richmond. Despite shifting troops, Beauregard was badly outnumbered as Grants troops began arriving on the field. Attacking late in the day with the XVIII, II, and IX Corps, Grants men gradually pushed the Confederates back. Fighting resumed on 17th with the Confederates doggedly defending and preventing a Union breakthrough. As the fighting continued, Beauregards engineers commenced constructing a new line of fortifications closer the city and Lee began marching to the fighting. Union assaults on June 18 gained some ground but were halted at the new line with heavy losses. Unable to advance, Meade ordered his troops to dig in opposite the Confederates. The Siege Begins Having been halted by the Confederate defenses, Grant devised operations for severing the three open railroads leading into Petersburg. While he worked on these plans, elements of the Army of the Potomac manned the earthworks that had sprung up around Petersburgs east side. Among these was the 48th Pennsylvania Volunteer Infantry, a member of Major General Ambrose Burnsides IX Corps. Composed largely of former coal miners, the men of the 48th devised their own plan for breaking through the Confederate lines. Armies Commanders Union Lieutenant General Ulysses S. GrantMajor General Ambrose BurnsideIX Corps Confederate General Robert E. LeeMajor General William Mahone A Bold Idea Observing that the closest Confederate fortification, Elliotts Salient, was a mere 400 feet from their position, the men of the 48th conjectured that a mine could be run from their lines under the enemy earthworks. Once complete, this mine could be packed with enough explosives to open a hole in the Confederate lines. This idea was seized upon by their commanding officer Lieutenant Colonel Henry Pleasants. A mining engineer by trade, Pleasants approached Burnside with the plan arguing that the explosion would take the Confederates by surprise and would allow Union troops to rush in to take the city. Eager to restore his reputation after his defeat at the Battle of Fredericksburg, Burnside agreed to present it to Grant and Meade. Though both men were skeptical about its chances for success, they approved it with the thought that it would keep the men busy during the siege. On June 25, Pleasants men, working with improvised tools, began digging the mine shaft. Digging continuously, the shaft reached 511 feet by July 17. During this time, the Confederates became suspicious when they heard the faint sound of digging. Sinking countermines, they came close to locating the 48ths shaft. The Union Plan Having stretched the shaft under Elliotts Salient, the miners began digging a 75-foot lateral tunnel that paralleled the earthworks above. Completed on July 23, the mine was filled with 8,000 pounds of black powder four days later. As the miners were working, Burnside had been developing his attack plan. Selecting Brigadier General Edward Ferreros division of United States Colored Troops to lead the assault, Burnside had them drilled in the use of ladders and instructed them to move along the sides of the crater to secure the breach in the Confederate lines. With Ferraros men holding the gap, Burnsides other divisions would cross to exploit the opening and take the city. To support the assault, Union guns along the line were ordered to open fire following the explosion and a large demonstration was made against Richmond to draw off enemy troops. This latter action worked particularly well as there were only 18,000 Confederate troops in Petersburg when the attack began. Upon learning that Burnside intended to lead with his black troops, Meade intervened fearing that if the attack failed he would be blamed for the needless death of these soldiers. Last Minute Changes Meade informed Burnside on July 29, the day before the attack, that he would not permit Ferreros men to spearhead the assault. With little time remaining, Burnside had his remaining division commanders draw straws. As a result, the ill-prepared division of Brigadier General James H. Ledlie was given the task. At 3:15 AM on July 30, Pleasants lit the fuse to the mine. After an hour of waiting without any explosion, two volunteers entered the mine to find problem. Finding that the fuse had gone out, they re-lit it and fled the mine. A Union Failure At 4:45 AM, the charge detonated killing at least 278 Confederate soldiers and creating a crater 170 feet long, 60-80 feet wide, and 30 feet deep. As the dust settled, Ledlies attack was delayed by the need to remove obstructions and debris. Finally moving forward, Ledlies men, who had not been briefed on the plan, charged down into the crater rather than around it. Initially using the crater for cover, they soon found themselves trapped and unable advance. Rallying, Confederate forces in the area moved along the rim of the crater and opened fire on the Union troops below. Seeing the attack failing, Burnside pushed Ferreros division in to the fray. Joining the confusion in the crater, Ferreros men endured heavy fire from the Confederates above. Despite the disaster in the crater, some Union troops succeeded in moving along the right edge of the crater and entered the Confederate works. Ordered by Lee to contain the situation, the division of Major General William Mahone launched a counterattack around 8:00 AM. Moving forward, they drove Union forces back to the crater after bitter fighting. Gaining the slopes of crater, Mahones men compelled the Union troops below to flee back to their own lines. By 1:00 PM, most of the fighting had concluded. Aftermath The disaster at the Battle of the Crater cost the Union around 3,793 killed, wounded, and captured, while the Confederates incurred around 1,500. While Pleasants was commended for his idea, the resulting attack had failed and the armies remained stalemated at Petersburg for another eight months. In the wake of the attack, Ledlie (who may have been drunk at the time) was removed from command and dismissed from the service. On August 14, Grant also relieved Burnside and sent him on leave. He would not receive another command during the war. Grant later testified that though he supported Meades decision to withdraw Ferreros division, he believed that if the black troops had been permitted to lead the attack, the battle would have resulted in a victory.

Corporate finance Essay Example | Topics and Well Written Essays - 1250 words

Corporate finance - Essay Example 1. The argument of the purchasing manger that there would be savings of $96000 over a period of eight years holds no grounds. First of all it is not clear whether manager is arguing the saving in absolute terms (net cash flow) or in terms of profits. The manger has calculated the savings of $96000 as under: The calculations of purchasing manager are absolutely wrong, as he is taking total cost of manufacturing of the present in- house activity and comparing it with only cost of purchasing the component from Amalgament Components. Manufacturing costs and purchasing price are altogether incomparable costs. He has altogether ignored the many expenses required to be added to the cost of purchases to make it comparable to manufacturing cost, like depreciation on Scanner of $8000, freight inward, assembling cost of the product, salaries of administrative and selling staff and many other assembling, administrative, selling expenses, and even the taxation outflows. 2. The suggestion of selling the machinery is absolutely illogical. The machinery was purchased only one year back for $45000 and selling only for $5000 is no good suggestion, considering the fact that the firm would suffer a loss to the tune of $35000 after taking into account capital allowance for two years. If at all machinery is to sold, it should be done at a time when the proposal of buying the component actually start bringing profits, as the machinery has got few alternative uses as per production manager. 3. The argument about only 60% use for current 4 years of warehouse holds grounds when $50000 is planned to be spent on extension of warehousing facilities after the fourth year, particularly when a capital allowance can be claimed @ 4%. The matter needs serious consideration while evaluating the buying option. 1. The argument of production manager that present machinery holds 8 years of useful life, and also machinery could be used for alternative purposes as well are valuable arguments from

On Either one of the Prison Epistles or one of the Pastoral Epistles Research Paper

On Either one of the Prison Epistles or one of the Pastoral Epistles and on one of the General Epistles - Research Paper Example Lastly, it discusses one important lesson learned from each letter and the impact of the lesson learned to someone’s life. Epistle means a literary letter which was planned to be published and read by the general public. The Prison Epistles are the letters that can be found in the New Testament of the Holy Bible. One of the Prison Epistles written by Paul during his imprisonment in Rome is the Prison Epistle to the Philippians. According to the New International Version Holy Bible (1984), Paul had been mobbed in Jerusalem, arrested there, and transferred to Caesarea, and finally, when he requested to the Roman imperial court that a decision or judgment to be changed and appealed as a Roman citizen, he had been removed to Rome for trial. When the Philippians heard this situation, they prepared to stand by him, raised some money for him to use in his trial and sent Epaphroditus, a member of the church in Philippi in Macedonia, to wait on Paul, to devote one’s services to Paul, and to stay with him until his problem were solved. So Epaphroditus went with the gift given by the church and for the purpose of telling Paul about the interest and excitement of the church to know some news about his situation and the result of his trial before the Roman imperial court. Paul took this chance and this occasion to write to the Philippians with three reasons namely: (1) to thank them for their gift and thank them for their fellowship in the gospel, (2) to tell and comfort them about his situation in Rome and about his trial, telling them that the effect of his imprisonment has turned out for the advancement of the gospel, and lastly (3) especially to encourage them and strengthen them in the hope and joy that was theirs in Jesus Christ. He also wrote that he is going to send Timothy soon, that he may know of their condition and send Epaphroditus back to them because Epaphroditus longs for all of them and that he has the feeling of great worry or unhappiness bec ause the church heard that he is ill but God has been so merciful to him. He told them that he is more excited to send Epaphroditus back to them so that they may be glad that Paul might have less worry or fear. The other purpose of the letter was to stop the Judaizers from encouraging the Philippian Christians to submit to circumcision and the last purpose why Paul wrote to them was to encourage the Philippian believers to stop the misunderstanding among them especially the two women involved namely, Euodia and Syntyche that they need to agree with each other as sisters in the Lord or be united. He also asked his faithful partner to help these two women for they have worked hard with him to spread the gospel. The key characteristics of the letter were (1) the Epistle is a letter and not a long and serious piece of writing on a particular job. It is just a simple letter to personal friends which has no theological discussions, no fixed outline and no formal development, (2) it is a l etter of love, Paul’s message has nothing but praise or the Philippians and prayer that their love may be rich, (3) it is a letter of joy, despite being imprisoned, he is still full of joy. After reading the book of Philippians, 20 times that Paul uses the words joy, rejoice, peace, content, and thanksgiving. It is a

Duke Heart Failure Program Case Study Example | Topics and Well Written Essays - 500 words

Duke Heart Failure Program - Case Study Example What are the financial results of the CHF disease management program? Hint: Examine revenue and cost impacts for the Hospital (inpatient and outpatient) and Physicians perspective. According to the American Heart Association, the annual direct cost was estimated to be $ 22.2 billion to treat the CHF patients, in addition to $ 2.1 billion in the loss of productivity. The costs of the hospital were about 60 percent of the direct costs of CHF. Hospital readmission rates were about 2 percent with in 2 days, 20 percent with in 1 month, and 50 percent for 6 month time. The only one largest expense for Medicare was CHF and it was also the basic cause of admission in emergency room among the Medicare population. Non-compliance of diet and medication resulting in readmission was about 33 percent to 64 percent whereas 35 percent of readmissions were related to inadequate discharge planning or follow- up. 3.

Stock Market Performance and Economic Relationship

Stock Market Performance and Economic Relationship Abstract: Whether national economy is affecting the stock market or other way round? A lot of studies have done on the past what are relationship of these variables. In my work I have used cointegration and Granger Causality method to find out the relationship between the stock index price and Economic growth indicator GDP. Introduction The debate of whether stock market is associated with economic growth or the stock market can be served as the economic indicator to predict future. According to many economists stock market can be a reason for the future recession if there is a huge decrease in the stock price or vice versa. However, there are evidence of controversial issue about the ability of prediction from the stock market is not reliable if there is a situation like 1987 stock market crashed followed by the economic recession and 1997 financial crises. (Stock market and economic growth in Malaysia: causality test). The aim of the study is to find the relation between the stock market performance and the real economic activity in case of four countries The UK, The USA, Malaysia and Japan. With my limited knowledge I have tried to find out the role of financial development in stimulating economic growth. A lot of economists have different view about stock market development and the economic growth. If we focus on some related literature published on this topic one question arises: Is economic development is affected by stock market development? Even though there are lots of debate on some are saying that stock market can help the economy but the effect of stock market in the economy especially in the economy is very little. Ross Levine suggested in his paper published in 1998 that recent evidence suggested stock market can really give a boom to economic growth. (REFERENCE) It is not really possible to measure the growth by simply looking at the ups and down in the stock market indicator and by looking at the rates of growth in GDP. A lot of things can cause in the growth of stock market like changes in the banking system, foreign participation in the in the financial market may participate strongly. Apparently it seems that these developments can cause development of stock market followed by the good economic growth. But to check the accuracy one required to follow an appropriate method which would meaningfully measure whether stock price is really effecting the economic growth or not? In my work I have tried to find out the co integrating relationship between Stock price and GDP and tried to check if there is a long run and short run relationship between the stock price and GDP. The method used for the studies is Engle Granger co integration method. To do this I have used ADF (Augmented Dickey Fuller Test) to check for the stationary behaviour of the variables and then I have performed the Engle Granger Engle Granger co integration method followed by residual based error correction model. To check for the short run relationship I have used 2nd stage Engle Granger co integration method. To check the causal effect of the four countries stock market and economic growth I used Granger Causality Method. In this paper I have reviewed some studies of scholars which I have discussed on the literature review part. This paper contains five parts Part two is about the literature based on the past wok of scholars. Part Three discussed about the Data. Part four is about the methodology, Results are discussed on part five and part six is all about the summary and conclusion of the whole study. In my work I have founded there is no long run relationship between stock market and economic growth in all four countries. In addition there is no causal relation between stock index yield and the national economy growth rate. The empirical results of the thesis concludes that the possibility of seemingly abnormal relationship between the stock index and national economy of these for countries. Literature Review: Stock market contributes to economic growth in different ways either directly or indirectly. The functions of stock market are savings mobilization, Liquidity creation, and Risk diversification, keep control on disintermediation, information gaining and enhanced incentive for corporate control. The relationship between stock market and economic growth has become an issue of extensive analysis. There is always a question whether the stock market directly influence economic growth. A lot of research and results shows that there is a strong relationship between stock market and economic growth. Evidence on whether financial development causes growth help to reconcile these views. If we go back to the study of Schumpeter (1912) his studies emphasizes the positive influence on the development of a countrys financial sector on the level and the potential risk of losses caused by the adverse selection and moral hazard or transaction costs are argued by him how necessary the rate of growth argues that financial sectors provides of reallocating capital to minimize the potential losses. Empirical evidence from king and Levine (1983) show that the level of financial intermediation is good predictor of long run rates of growth, capital accumulation and productivity. Enhanced liquidity of financial market leads to financial development and investors can easily diversify their risk by creating their portfolio in different investments with higher investment. Another study from Levine and Zervos (1996) using the data of 24 countries found that a strong positive correlation between stock market development and economic growth. Their expanded study on 49 countries from 1976-1993, they used Stock Market liquidity, Economic growth rate, Capital Accumulating rate and output Growth Rate. They found that all the variables are positively correlated with each other. Demiurgic and Maksimovic (1996) have found positive causal effects of financial development on economic growth in line with the ‘supply leading hypothesis. According to his studies countries with better financial system has a smooth functioning stock market tend to grow much faster as they have access to much needed funds for financially constrained economic enterprises by the large efficient banks. Related research was done for the past three decades focusing on the role of financial development in stimulating economic growth they never considered about the stock market. An empirical study by Ming Men and Rui on Stock market index and economic growth in China suggest that possible reason of apparent abnormal relationship between the stock Index and national economy in china. Apparent abnormal relationship may be because of the following reason inconsistency of Chinese GDP with the structure of its stock market, role played by private sector in growth of GDP and disequilibrium of finance structure etc. The study was done using the cointegration method and Granger causality test, the overall finding of the study is Chinese finance market is not playing an important role in economic development. (Men M 2006 China paper). An article by Indrani Chakraborti based on the case of India presented in a seminar in kolkata in October, 2006 provides some information about the existence of long run stable relationship between stosk market capitalization, bank credit and growth rate of real GDP. She used the concept of the granger causality after using both the Engle-Granger and Johansen technique. In her study she found GDP is co-integrated with financial depth, Volatility in the stock market and GDP growth is co integrated with all the findings the paper explain that the in an overall sense, economic growth is the reson for financial development in India.(Chakraboty Indrani). Few writers from Malaysia found that stock market does help to predict future economy. Stock market is associated with economic growth play as a source for new private capital. Causal relationship between the stock market and economic growth which was done by using the formal test for causality by C.J. Granger and yearly Malaysia data for the period 1977-2006. The result from the study explain that future prediction is possible by stock market. A study focused on the relationship between stock market performance and real economic activity in Turkey. The study shows existence of a long run relationship between real economic activity and stock prices†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ Result from the study pointed out that economic activity increases after a shock in stock prices and then declines in Turkish market from the second quarter and a unitary (Turkish paper) An international time series analysis from 1980-1990 by By RAGHURAM G. RAJAN AND LUIGI ZINGALES shows some evidence of the relation between stock market and economic growth. This paper describes whether economic growth is facilitated by financial development. He found that financial development has strong effect on economic growth. (Rajan and Zingales, 1998) The study of Ross LEVINE AND SARA ZERVOS on finding out the long run relationship between stock market and bank suggest a positive effect both the variables has positive effect on economic growth. International integration and volatility is not properly effected by capital stock market. And private save saving rates are not at all affected by these financial indicators. The study was done on 47 countries data using cross sectional analysis. In theory the conventional literature on growth was not sufficient enough to look for the connection between financial development and economic growth and the reason is they were focused on the steady state level of capital stock per workerof productivity. And they were not really concentrated on the rate of growth. Actually the main concern was legitimated to exogenous technical progress. (Levine and Zervos 1998) Belgium Stock market study with economic development shows the positive long run relationship between both the variables. In case of Belgium the evidences are quiet strong that Economic growth is caused by the development of the stock market. It is more focused between the period 1873 and 1935; basically this period is considered as the period of rapid industrialization in Belgium. The importance of the stock market in Belgium is more pronounced after liberalization of the stock market in 1867-1873. The time varying nature of the link between stock market development and economic growth is explained by the institutional change in the stock exchange. They also tried to find out the relationship to the universal banking system. Before 1873 the economic growth was based on the banking system and after 1873 stock market took the place. (Stock Market Development and economic growth in Belgium, Stijin Van Nieuwerburg, Ludo Cuyvers, Frans Buelens July 5, 2005) Senior economist of the World Banks Policy research department Ross Levine has discussed about Stock market in his paper Stock Markets: A Spur to economic growth on the impact of development. Less risky investments are possible in liquid equity market and it attracts the savers to acquire an asset, equity. As, they can sell it quickly when they need access to their savings, and if they want to alter their portfolio. Though many long term investment is required for the profitable investment. But reluctance of the investors towards long term investment as they dont have the access to their savings easily. Permanent access to capital is raised by the companies through equity issues as they are facilitating longer term, more profitable investments and prospect of long term economic growth is enhanced as liquid market improves the allocation of capital. The empirical evidence from the study strongly suggests that greater stock markets create more liquidity or at least continue economic gr owth. (Levine. R A spur to economic Growth) A lot of research has established that future economic growth is influenced by countrys financial growth, stock market index returns are another factor of economic growth. The researcher focused to extend their study; they tie together these two strings and started analyzing the relationship between banking industry, stock returns and future economic growth. Research was done on 18 developed and 18 emerging markets and the results are positive and noteworthy relationship between future GDP and stock returns. Few important features can also be predicted such as bank-accounting-disclosure standards, banking crises, insider trading law enforcement and government ownership of banks. (Bank stock returns and economic growth q Rebel A. Cole a, Fariborz Moshirian b,*, Qiongbing Wu c a Department of Finance, DePaul University, Chicago, IL 60604, USA b School of Banking and Finance, The University of New South Wales, Sydney, NSW 2052, Australia c Newcastle raduate School of Business, The University of Newcastle, Newcastle, NSW 2300, Australia Received 29 September 2006; accepted 26 July 2007Available online 21 September 2007) Another paper was focused on the linkages between financial development and economic growth using TYDL model for the empirical exercises by Purna Chandra Padhan suggests that both stock price and economic activity are integrated of order one and Johansen-Juselias Coin-integration tests for this study found one co integrating vector exists. It is proved by the spurious relation rule in this study the existence of at least one direction of causality. He described that bi-directional causality between stock price and economic growth meaning that economic activity can be enhanced by well developed stock exchange and vice-versa. ( Title:  The nexus between stock market and economic activity: an empirical analysis for India Author(s): Purna Chandra Padhan Journal: International Journal of Social Economics Year: 2007 Volume: 34 Issue: 10  Page: 741 – 753 DOI: 10.1108/03068290710816874 Publisher: Emerald Group Publishing Limited) Chee Keong Choong (Universiti Tunku Abdul Rahman Malaysia) Zulkornain Yusop (Universiti Putra Malaysia) Siong Hook Law (Universiti Putra Malaysia) Venus Liew Khim Sen (Universiti Putra Malaysia) Date of creation: 23 Jul 2003 Tried to find out the importance of the causal relationship of Financial development and economic growth. The findings of their study usin autoregressive Distributed lag (ARDL) describes about the positive long run impact on economic growth Granger causality also suggest same results. A study by Randall Filler(2000) using 70 countries data over the period 1985-1997 proves that there is a very little relationship between economic growth and stock market especially in developing countries and currency appreciation has occurred. From the result of the study we can see that an important role may be played by the stock market in an economy, and these are not essential for economic growth. However, another study on Iran by N. Shahnoushi, A.G Daneshvar, E Shori and M. Motalebi 2008 Financial development is not considered as an effective factor to the economic growth. The study was focused on the causal relationship between the financial development and economic growth. Time series data used for the study from the period 1961-2004. Granger causality shows there is no co integrating relationship between financial development and economic growth in Iran only the economical growth leads to financial development. Establishing link between savings and investment is very much important and financial market provides that. Transient or lasting growth is the ultimate affect of the financial market. Economic growth can be influenced by financial market by improving the productivity of the capital, Investment to firms can be channelled and greater capital accumulation by increasing savings. To ensure the stability of the financial market potential regulation is important due to asymmetric information, especially at the time of financial liberalization. (Economic Development and Financial Market Tosson Nabil Deabes Moderm Academy for technology aand computer sciences; MAM November 2004 Economic Development Financial Market Working Paper No. 2 ) Data: The empirical analysis was carried out using the quarterly data for The UK, The USA, Japan and Malaysia. The data were collected from the DataStream for the period 1993I to 2008III. Economic growth is measured as the growth rate of gross domestic product (GDP) of each country with the help of stock prices SP. For the software processing I used Eviews 6.0 for the planned regression in order to get the results. The empirical analysis is done from the quarterly data from the stock market indices and the and the GDP between the first quarter of 1993 and the fourth quarter of 2008. All the data has been extracted from the data stream and expressed in US$. The data for Japan share price is from Tokyo Stock Exchange. Malaysias Share price is form Kuala Lumpur Composite Index, UKs is from UK FT all share price index and USA share price is taken from the DOW Jones industrial share price index. The nature of the Data is series used for the time series regression. List of Variables: UGDP UK GDP USP UK Share price LUGDP Log of UK GDP LUSP Log of UK Share price USGDP USA GDP USSP USA (DOW Jones) Share price LUSGDP Log of USA GDP LUSSP Log of USA Share price MGDP Malaysia GDP MSP Malaysia Share price LMGDP Log of Malaysia GDP LMSP Log of Malaysia Share price JGDP Japan GDP JSP Japan Share Price LJGDP Log of Japan GDP LJSP Log of Japan Share price Methodology: Cointegration long term common stochastic trend between non stationary time series. If non-stationary series x and yare both integrated of same order and there is a linear combination of them that is stationary, they are called co integrated series. A common stochastic trend is shared in Cointegration. It follows that these two series will not drift apart too much, meaning that even they may deviate from each other in the short-term, they will revert to the long-run equilibrium. This fact makes cointegration a very powerful approach for the long-term analyses. Meanwhile, cointegration does not imply high correlation; two series can be co integrated and yet have very low correlations. Cointegration tests allow us to determine whether financial variables of different national markets move together over the long run, while providing for the possibility of short-run divergence. The first step in the analysis is to test each index series for the presence of unit roots, which shows whether the series are nonstationary. All the series must be nonstationarity and integrated of the same order. To do this, we apply both the Augmented Dickey-Fuller (ADF) test. Once the stationarity requirements are met, we proceed Granger bivariate cointegration (1987) procedure. 30 International Research Journal of Finance and Economics Issue 24 (2009) Series Stationary Test: In this study I have used Augmented Dickey Fuller Test (ADF) to test the stationary of variables. The unit root test is usually used to confirm stationary of a series. The ADF is test for unit root where I have checked the Unit root and strong negative numbers of unit root is being rejected by the null hypothesis (level of significance). In this study I have used Augmented Dickey Fuller Test (ADF) to check whether the series is stationary or not. ADF test is based on the estimate of the following regression: is in this case variable of interest = , is the differencing operator, t is the time trend and is the random component of zero mean and constant variance. The parameters to be estimated are { } Null and alternative hypothesis of unit root test are: , () () Here with the test we can find the estimates of are equal to zero or not. Y is said to be stationary if the cumulative distribution of the ADF statistics by showing that if the calculated ratio of the coefficient is less than the critical value according to Fuller (1976). If we accept the Ho the sequence is predicted to be having unit root and if Ho is rejected then we can say that the series doesnt have unit root. This proves that the series is stationary. The co–integration test can only be performed if both the sequences are all integrated of order I (1). Cointegration Test: Engle and Granger (1987) first established the cointegration method. It is a method of measuring long term diversification based on data. Linear combination of two non stationary series shows that they are integrated in order one I(1) that is stationary. And this is a co integrated series. Cointegration Long term common random trend between non stationary time series. The linear combination of both the non stationary series can be stationary if both the variables are integrated in same order. Cointegration is a very powerful approach in the long term analysis because a common stochastic trend is shared in cointegration that mean two series will not drift separately too much. They might deviate from each other but in the long run but eventually the will revert back in the long run. If there is very low correlation between the series still the series can be co-integrated as high correlation is not implied in cointegration. The reason for choosing the method as it will allow us to check the move between the variable in the long run even there might be a divergence in the short run. The first step in the analysis is check each index series whether the series for the presence of unit root which shows whether the series is non stationary. The method that I followed to do this is Augmented Dickey Fuller Test (ADF). I proceed the Granger cointegration technique 1987 when the stationary requirements are met. According to Engle and Granger (1987) to check for cointegration if both the variables and are integrated with order one the proposed method for cointegration residual-based test for cointegration (Engle-Granger method). So from the above method we can find the equation By regressing with And after that and is denoted as the estimated regression coefficient vectors. After that I saved the residual from the above equation. Then, = – is representing the estimated residual vector. If the residual is integrated with order zero that means the series for the residual is stationary, and and are then co integrated and vice versa. I have checked it by performing Augmented Dickey fuller test on the residual series on level value with intercept only of each country. An in this situation (1, -) is called co-integrating vector if the series is stationary. Therefore is a co integrating equation, so, from it we can say that there is long run relationship between and. Granger causality test: Granger causality test is applied if the relationship is lagged between the two variables to determine the direction of relation in statistical term. It gives information about the short term relationship between the variables. In terms of conceptual definition causality is consist of different ideas, this concept produce a relation between caused and results were agreed upon. Aristo defines that there exist a link between causes and results and without causes these results are impossible. And this is strong relationship. Some economists believe that the idea of causality is the mix of both theoretical and explanation and statistical concept. The frontline operational definition of causality is given by some economist, but Granger is the one who provided the information to understand it correctly and completely. Granger causality approach (1969), lets think the variable y is Economic Growth (GDP) and x is Stock price index, if it is possible to predict the past values of y and x than from the lagged values of y alone. X is said to be granger caused by and y is helping in predicting it. in case of a simple bivariate model, causality can be tested between stock market growth and economic growth. Granger causality run on the basis of the following bivariate regressions of the form: (1) (2) Where GDP denotes economic growth and SP denotes the stock price index and they explain the changes in growth. Variables are expressed in logarithm form. The distribution of and are uncorrelated by assumption. From the equation one it can be said that current GDP is related to lagged values of itself and as well as that of SP. And equation 2 postulates same kind of behaviour for SP. Both the equations can be obtained by ordinary least squares (OLS). The f statistics are the Wald statistics for the joint hypothesis: and F test is carried out for the null hypothesis of no Granger causality. The formula of f statistic is Lagged term is defined here by m; number of parameter is defined as k. Test result for Unit Root: Augmented Dickey Fuller Model (ADF) is used to test the stationary of each variable. Null and alternative hypothesis describes about the investigation of unit root. If the null is accepted and alternative is rejected then the variable non stationary behaviour and vice versa is stationary. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test Japan t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -2.653258 -3.522887     -2.901779 -2.588280   -2.693600   -4.088713   -3.472558 -3.163450 1st Difference -9.053185 -3.524233   -2.902358 -2.588587 -9.003482   -4.090602   -3.473447 -3.163967 Share Price Level   -2.116137 -3.522887     -2.901779 -2.588280   -2.203273   -4.088713   -3.472558 -3.163450 1st Difference   -6.899295 -3.524233   -2.902358 -2.588587   -6.844396   -4.090602   -3.473447 -3.163967 Table 01: Unit root test for stationary Japan If we have a look on the unit root test for the variables GDP and Share price to find out the stationary behaviour the Augmented Dickey Fuller Test with intercept and with intercept and trend in level and first difference. The t statistic value with trend is -2.653258 which is higher than the critical values in 1%, 5% and 10% critical value. The same applies with intercept and trend as the t statistic value -2.693600 is higher than the critical value in all the level of critical value. So from the nature of stationary behaviour we can say in level GDP shows nonstationary behaviour. And the first difference LnGDP is integrated with order one. In case of LnSP the results with intercept and with intercept trend in level are -2.116137 and -2.203273 which is higher than the critical values shows non stationary behaviour as they are higher than the critical value. The unit root test for the variables at first difference shows stationary as the t statistic value is than the critical value i n all level and they are integrated in order one. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test Malaysia t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -1.195020 -3.522887     -2.901779 -2.588280 -1.933335   -4.088713   -3.472558 -3.163450 1st Difference -5.951843 -3.524233   -2.902358 -2.588587 -5.923595   -4.090602   -3.473447 -3.163967 Share Price Level   -1.900406 -3.522887     -2.901779 -2.588280   -1.891183   -4.088713   -3.472558 -3.163450 1st Difference   -7.842122 -3.524233   -2.902358 -2.588587   -7.779757   -4.090602   -3.473447 -3.163967 The unit root test result for LMGDP and LMSP values presented in natural logarithm. And the level values with intercept and with intercept and trend for LMGDP is -1.195020 and -1.93335 respectively. The values are higher than the critical value means the series has non stationary behaviour. On the other hand the 1st difference values with intercept and with intercept and trend are -5.951843 and -5.923595 respectively. The 1st difference values are integrated with order one. And in the same way I did the ADF test to check for Stationary behaviour of LMSP in level and first difference with intercept and trend. The values in level are -1.900406 and -1.891183 with intercept and trend us higher than the critical value and the series is not integrated with order one. The first difference t statistic values are -7.842122 and -7.779757 with intercept and with intercept and trend respectively are less than the critical value in both the case implies that the series is integrated with order on e. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test UK t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -0.690866 -3.522887     -2.901779 -2.588280 -2.377333   -4.088713   -3.472558 -3.163450 1st Difference -7.474388 -3.524233   -2.902358 -2.588587 -7.439027   -4.090602   -3.473447 -3.163967 Share Price Level -1.711599 -3.522887     -2.901779 -2.588280 -1.261546   -4.088713   -3.472558 -3.163450 1st Difference -7.254574 -3.524233   -2.902358 -2.588587 -7.391821   -4.090602   -3.473447 -3.163967 The results from Augmented Dickey Fuller test (ADF) for UK GDP in level with intercept and with intercept and trend is –0.690866 and -2.377333 respectively. Both the values in level are higher than the critical value and are integrated in order 0 shows non stationary behaviour. The t statistic values in 1st difference with intercept and with intercept and trend are -7.474388 and -7.439207 respectively. Which suggest that the critical values are less than the critical values in 1%, 5% and 10% level. So from the above hypothesis it can be said that it series is integrated with order one. When I performed the unit root test using the same method the series in level with intercept and with intercept and trend the values in are -1.711599 and -1.261546 respectively. The values are higher than the critical values implies that they are not integrated in order one shows non stationary behaviour. However, the 1st difference value of log natural share price is -7.254573 and -7.391821 wit h intercept and with intercept and trend respectively. So from the result we can say that the series is integrated in order one in both the cases with intercept and with intercept and trend. So the series in first difference is stationary. Variables level/1st D Stock Market Performance and Economic Relationship Stock Market Performance and Economic Relationship Abstract: Whether national economy is affecting the stock market or other way round? A lot of studies have done on the past what are relationship of these variables. In my work I have used cointegration and Granger Causality method to find out the relationship between the stock index price and Economic growth indicator GDP. Introduction The debate of whether stock market is associated with economic growth or the stock market can be served as the economic indicator to predict future. According to many economists stock market can be a reason for the future recession if there is a huge decrease in the stock price or vice versa. However, there are evidence of controversial issue about the ability of prediction from the stock market is not reliable if there is a situation like 1987 stock market crashed followed by the economic recession and 1997 financial crises. (Stock market and economic growth in Malaysia: causality test). The aim of the study is to find the relation between the stock market performance and the real economic activity in case of four countries The UK, The USA, Malaysia and Japan. With my limited knowledge I have tried to find out the role of financial development in stimulating economic growth. A lot of economists have different view about stock market development and the economic growth. If we focus on some related literature published on this topic one question arises: Is economic development is affected by stock market development? Even though there are lots of debate on some are saying that stock market can help the economy but the effect of stock market in the economy especially in the economy is very little. Ross Levine suggested in his paper published in 1998 that recent evidence suggested stock market can really give a boom to economic growth. (REFERENCE) It is not really possible to measure the growth by simply looking at the ups and down in the stock market indicator and by looking at the rates of growth in GDP. A lot of things can cause in the growth of stock market like changes in the banking system, foreign participation in the in the financial market may participate strongly. Apparently it seems that these developments can cause development of stock market followed by the good economic growth. But to check the accuracy one required to follow an appropriate method which would meaningfully measure whether stock price is really effecting the economic growth or not? In my work I have tried to find out the co integrating relationship between Stock price and GDP and tried to check if there is a long run and short run relationship between the stock price and GDP. The method used for the studies is Engle Granger co integration method. To do this I have used ADF (Augmented Dickey Fuller Test) to check for the stationary behaviour of the variables and then I have performed the Engle Granger Engle Granger co integration method followed by residual based error correction model. To check for the short run relationship I have used 2nd stage Engle Granger co integration method. To check the causal effect of the four countries stock market and economic growth I used Granger Causality Method. In this paper I have reviewed some studies of scholars which I have discussed on the literature review part. This paper contains five parts Part two is about the literature based on the past wok of scholars. Part Three discussed about the Data. Part four is about the methodology, Results are discussed on part five and part six is all about the summary and conclusion of the whole study. In my work I have founded there is no long run relationship between stock market and economic growth in all four countries. In addition there is no causal relation between stock index yield and the national economy growth rate. The empirical results of the thesis concludes that the possibility of seemingly abnormal relationship between the stock index and national economy of these for countries. Literature Review: Stock market contributes to economic growth in different ways either directly or indirectly. The functions of stock market are savings mobilization, Liquidity creation, and Risk diversification, keep control on disintermediation, information gaining and enhanced incentive for corporate control. The relationship between stock market and economic growth has become an issue of extensive analysis. There is always a question whether the stock market directly influence economic growth. A lot of research and results shows that there is a strong relationship between stock market and economic growth. Evidence on whether financial development causes growth help to reconcile these views. If we go back to the study of Schumpeter (1912) his studies emphasizes the positive influence on the development of a countrys financial sector on the level and the potential risk of losses caused by the adverse selection and moral hazard or transaction costs are argued by him how necessary the rate of growth argues that financial sectors provides of reallocating capital to minimize the potential losses. Empirical evidence from king and Levine (1983) show that the level of financial intermediation is good predictor of long run rates of growth, capital accumulation and productivity. Enhanced liquidity of financial market leads to financial development and investors can easily diversify their risk by creating their portfolio in different investments with higher investment. Another study from Levine and Zervos (1996) using the data of 24 countries found that a strong positive correlation between stock market development and economic growth. Their expanded study on 49 countries from 1976-1993, they used Stock Market liquidity, Economic growth rate, Capital Accumulating rate and output Growth Rate. They found that all the variables are positively correlated with each other. Demiurgic and Maksimovic (1996) have found positive causal effects of financial development on economic growth in line with the ‘supply leading hypothesis. According to his studies countries with better financial system has a smooth functioning stock market tend to grow much faster as they have access to much needed funds for financially constrained economic enterprises by the large efficient banks. Related research was done for the past three decades focusing on the role of financial development in stimulating economic growth they never considered about the stock market. An empirical study by Ming Men and Rui on Stock market index and economic growth in China suggest that possible reason of apparent abnormal relationship between the stock Index and national economy in china. Apparent abnormal relationship may be because of the following reason inconsistency of Chinese GDP with the structure of its stock market, role played by private sector in growth of GDP and disequilibrium of finance structure etc. The study was done using the cointegration method and Granger causality test, the overall finding of the study is Chinese finance market is not playing an important role in economic development. (Men M 2006 China paper). An article by Indrani Chakraborti based on the case of India presented in a seminar in kolkata in October, 2006 provides some information about the existence of long run stable relationship between stosk market capitalization, bank credit and growth rate of real GDP. She used the concept of the granger causality after using both the Engle-Granger and Johansen technique. In her study she found GDP is co-integrated with financial depth, Volatility in the stock market and GDP growth is co integrated with all the findings the paper explain that the in an overall sense, economic growth is the reson for financial development in India.(Chakraboty Indrani). Few writers from Malaysia found that stock market does help to predict future economy. Stock market is associated with economic growth play as a source for new private capital. Causal relationship between the stock market and economic growth which was done by using the formal test for causality by C.J. Granger and yearly Malaysia data for the period 1977-2006. The result from the study explain that future prediction is possible by stock market. A study focused on the relationship between stock market performance and real economic activity in Turkey. The study shows existence of a long run relationship between real economic activity and stock prices†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ Result from the study pointed out that economic activity increases after a shock in stock prices and then declines in Turkish market from the second quarter and a unitary (Turkish paper) An international time series analysis from 1980-1990 by By RAGHURAM G. RAJAN AND LUIGI ZINGALES shows some evidence of the relation between stock market and economic growth. This paper describes whether economic growth is facilitated by financial development. He found that financial development has strong effect on economic growth. (Rajan and Zingales, 1998) The study of Ross LEVINE AND SARA ZERVOS on finding out the long run relationship between stock market and bank suggest a positive effect both the variables has positive effect on economic growth. International integration and volatility is not properly effected by capital stock market. And private save saving rates are not at all affected by these financial indicators. The study was done on 47 countries data using cross sectional analysis. In theory the conventional literature on growth was not sufficient enough to look for the connection between financial development and economic growth and the reason is they were focused on the steady state level of capital stock per workerof productivity. And they were not really concentrated on the rate of growth. Actually the main concern was legitimated to exogenous technical progress. (Levine and Zervos 1998) Belgium Stock market study with economic development shows the positive long run relationship between both the variables. In case of Belgium the evidences are quiet strong that Economic growth is caused by the development of the stock market. It is more focused between the period 1873 and 1935; basically this period is considered as the period of rapid industrialization in Belgium. The importance of the stock market in Belgium is more pronounced after liberalization of the stock market in 1867-1873. The time varying nature of the link between stock market development and economic growth is explained by the institutional change in the stock exchange. They also tried to find out the relationship to the universal banking system. Before 1873 the economic growth was based on the banking system and after 1873 stock market took the place. (Stock Market Development and economic growth in Belgium, Stijin Van Nieuwerburg, Ludo Cuyvers, Frans Buelens July 5, 2005) Senior economist of the World Banks Policy research department Ross Levine has discussed about Stock market in his paper Stock Markets: A Spur to economic growth on the impact of development. Less risky investments are possible in liquid equity market and it attracts the savers to acquire an asset, equity. As, they can sell it quickly when they need access to their savings, and if they want to alter their portfolio. Though many long term investment is required for the profitable investment. But reluctance of the investors towards long term investment as they dont have the access to their savings easily. Permanent access to capital is raised by the companies through equity issues as they are facilitating longer term, more profitable investments and prospect of long term economic growth is enhanced as liquid market improves the allocation of capital. The empirical evidence from the study strongly suggests that greater stock markets create more liquidity or at least continue economic gr owth. (Levine. R A spur to economic Growth) A lot of research has established that future economic growth is influenced by countrys financial growth, stock market index returns are another factor of economic growth. The researcher focused to extend their study; they tie together these two strings and started analyzing the relationship between banking industry, stock returns and future economic growth. Research was done on 18 developed and 18 emerging markets and the results are positive and noteworthy relationship between future GDP and stock returns. Few important features can also be predicted such as bank-accounting-disclosure standards, banking crises, insider trading law enforcement and government ownership of banks. (Bank stock returns and economic growth q Rebel A. Cole a, Fariborz Moshirian b,*, Qiongbing Wu c a Department of Finance, DePaul University, Chicago, IL 60604, USA b School of Banking and Finance, The University of New South Wales, Sydney, NSW 2052, Australia c Newcastle raduate School of Business, The University of Newcastle, Newcastle, NSW 2300, Australia Received 29 September 2006; accepted 26 July 2007Available online 21 September 2007) Another paper was focused on the linkages between financial development and economic growth using TYDL model for the empirical exercises by Purna Chandra Padhan suggests that both stock price and economic activity are integrated of order one and Johansen-Juselias Coin-integration tests for this study found one co integrating vector exists. It is proved by the spurious relation rule in this study the existence of at least one direction of causality. He described that bi-directional causality between stock price and economic growth meaning that economic activity can be enhanced by well developed stock exchange and vice-versa. ( Title:  The nexus between stock market and economic activity: an empirical analysis for India Author(s): Purna Chandra Padhan Journal: International Journal of Social Economics Year: 2007 Volume: 34 Issue: 10  Page: 741 – 753 DOI: 10.1108/03068290710816874 Publisher: Emerald Group Publishing Limited) Chee Keong Choong (Universiti Tunku Abdul Rahman Malaysia) Zulkornain Yusop (Universiti Putra Malaysia) Siong Hook Law (Universiti Putra Malaysia) Venus Liew Khim Sen (Universiti Putra Malaysia) Date of creation: 23 Jul 2003 Tried to find out the importance of the causal relationship of Financial development and economic growth. The findings of their study usin autoregressive Distributed lag (ARDL) describes about the positive long run impact on economic growth Granger causality also suggest same results. A study by Randall Filler(2000) using 70 countries data over the period 1985-1997 proves that there is a very little relationship between economic growth and stock market especially in developing countries and currency appreciation has occurred. From the result of the study we can see that an important role may be played by the stock market in an economy, and these are not essential for economic growth. However, another study on Iran by N. Shahnoushi, A.G Daneshvar, E Shori and M. Motalebi 2008 Financial development is not considered as an effective factor to the economic growth. The study was focused on the causal relationship between the financial development and economic growth. Time series data used for the study from the period 1961-2004. Granger causality shows there is no co integrating relationship between financial development and economic growth in Iran only the economical growth leads to financial development. Establishing link between savings and investment is very much important and financial market provides that. Transient or lasting growth is the ultimate affect of the financial market. Economic growth can be influenced by financial market by improving the productivity of the capital, Investment to firms can be channelled and greater capital accumulation by increasing savings. To ensure the stability of the financial market potential regulation is important due to asymmetric information, especially at the time of financial liberalization. (Economic Development and Financial Market Tosson Nabil Deabes Moderm Academy for technology aand computer sciences; MAM November 2004 Economic Development Financial Market Working Paper No. 2 ) Data: The empirical analysis was carried out using the quarterly data for The UK, The USA, Japan and Malaysia. The data were collected from the DataStream for the period 1993I to 2008III. Economic growth is measured as the growth rate of gross domestic product (GDP) of each country with the help of stock prices SP. For the software processing I used Eviews 6.0 for the planned regression in order to get the results. The empirical analysis is done from the quarterly data from the stock market indices and the and the GDP between the first quarter of 1993 and the fourth quarter of 2008. All the data has been extracted from the data stream and expressed in US$. The data for Japan share price is from Tokyo Stock Exchange. Malaysias Share price is form Kuala Lumpur Composite Index, UKs is from UK FT all share price index and USA share price is taken from the DOW Jones industrial share price index. The nature of the Data is series used for the time series regression. List of Variables: UGDP UK GDP USP UK Share price LUGDP Log of UK GDP LUSP Log of UK Share price USGDP USA GDP USSP USA (DOW Jones) Share price LUSGDP Log of USA GDP LUSSP Log of USA Share price MGDP Malaysia GDP MSP Malaysia Share price LMGDP Log of Malaysia GDP LMSP Log of Malaysia Share price JGDP Japan GDP JSP Japan Share Price LJGDP Log of Japan GDP LJSP Log of Japan Share price Methodology: Cointegration long term common stochastic trend between non stationary time series. If non-stationary series x and yare both integrated of same order and there is a linear combination of them that is stationary, they are called co integrated series. A common stochastic trend is shared in Cointegration. It follows that these two series will not drift apart too much, meaning that even they may deviate from each other in the short-term, they will revert to the long-run equilibrium. This fact makes cointegration a very powerful approach for the long-term analyses. Meanwhile, cointegration does not imply high correlation; two series can be co integrated and yet have very low correlations. Cointegration tests allow us to determine whether financial variables of different national markets move together over the long run, while providing for the possibility of short-run divergence. The first step in the analysis is to test each index series for the presence of unit roots, which shows whether the series are nonstationary. All the series must be nonstationarity and integrated of the same order. To do this, we apply both the Augmented Dickey-Fuller (ADF) test. Once the stationarity requirements are met, we proceed Granger bivariate cointegration (1987) procedure. 30 International Research Journal of Finance and Economics Issue 24 (2009) Series Stationary Test: In this study I have used Augmented Dickey Fuller Test (ADF) to test the stationary of variables. The unit root test is usually used to confirm stationary of a series. The ADF is test for unit root where I have checked the Unit root and strong negative numbers of unit root is being rejected by the null hypothesis (level of significance). In this study I have used Augmented Dickey Fuller Test (ADF) to check whether the series is stationary or not. ADF test is based on the estimate of the following regression: is in this case variable of interest = , is the differencing operator, t is the time trend and is the random component of zero mean and constant variance. The parameters to be estimated are { } Null and alternative hypothesis of unit root test are: , () () Here with the test we can find the estimates of are equal to zero or not. Y is said to be stationary if the cumulative distribution of the ADF statistics by showing that if the calculated ratio of the coefficient is less than the critical value according to Fuller (1976). If we accept the Ho the sequence is predicted to be having unit root and if Ho is rejected then we can say that the series doesnt have unit root. This proves that the series is stationary. The co–integration test can only be performed if both the sequences are all integrated of order I (1). Cointegration Test: Engle and Granger (1987) first established the cointegration method. It is a method of measuring long term diversification based on data. Linear combination of two non stationary series shows that they are integrated in order one I(1) that is stationary. And this is a co integrated series. Cointegration Long term common random trend between non stationary time series. The linear combination of both the non stationary series can be stationary if both the variables are integrated in same order. Cointegration is a very powerful approach in the long term analysis because a common stochastic trend is shared in cointegration that mean two series will not drift separately too much. They might deviate from each other but in the long run but eventually the will revert back in the long run. If there is very low correlation between the series still the series can be co-integrated as high correlation is not implied in cointegration. The reason for choosing the method as it will allow us to check the move between the variable in the long run even there might be a divergence in the short run. The first step in the analysis is check each index series whether the series for the presence of unit root which shows whether the series is non stationary. The method that I followed to do this is Augmented Dickey Fuller Test (ADF). I proceed the Granger cointegration technique 1987 when the stationary requirements are met. According to Engle and Granger (1987) to check for cointegration if both the variables and are integrated with order one the proposed method for cointegration residual-based test for cointegration (Engle-Granger method). So from the above method we can find the equation By regressing with And after that and is denoted as the estimated regression coefficient vectors. After that I saved the residual from the above equation. Then, = – is representing the estimated residual vector. If the residual is integrated with order zero that means the series for the residual is stationary, and and are then co integrated and vice versa. I have checked it by performing Augmented Dickey fuller test on the residual series on level value with intercept only of each country. An in this situation (1, -) is called co-integrating vector if the series is stationary. Therefore is a co integrating equation, so, from it we can say that there is long run relationship between and. Granger causality test: Granger causality test is applied if the relationship is lagged between the two variables to determine the direction of relation in statistical term. It gives information about the short term relationship between the variables. In terms of conceptual definition causality is consist of different ideas, this concept produce a relation between caused and results were agreed upon. Aristo defines that there exist a link between causes and results and without causes these results are impossible. And this is strong relationship. Some economists believe that the idea of causality is the mix of both theoretical and explanation and statistical concept. The frontline operational definition of causality is given by some economist, but Granger is the one who provided the information to understand it correctly and completely. Granger causality approach (1969), lets think the variable y is Economic Growth (GDP) and x is Stock price index, if it is possible to predict the past values of y and x than from the lagged values of y alone. X is said to be granger caused by and y is helping in predicting it. in case of a simple bivariate model, causality can be tested between stock market growth and economic growth. Granger causality run on the basis of the following bivariate regressions of the form: (1) (2) Where GDP denotes economic growth and SP denotes the stock price index and they explain the changes in growth. Variables are expressed in logarithm form. The distribution of and are uncorrelated by assumption. From the equation one it can be said that current GDP is related to lagged values of itself and as well as that of SP. And equation 2 postulates same kind of behaviour for SP. Both the equations can be obtained by ordinary least squares (OLS). The f statistics are the Wald statistics for the joint hypothesis: and F test is carried out for the null hypothesis of no Granger causality. The formula of f statistic is Lagged term is defined here by m; number of parameter is defined as k. Test result for Unit Root: Augmented Dickey Fuller Model (ADF) is used to test the stationary of each variable. Null and alternative hypothesis describes about the investigation of unit root. If the null is accepted and alternative is rejected then the variable non stationary behaviour and vice versa is stationary. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test Japan t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -2.653258 -3.522887     -2.901779 -2.588280   -2.693600   -4.088713   -3.472558 -3.163450 1st Difference -9.053185 -3.524233   -2.902358 -2.588587 -9.003482   -4.090602   -3.473447 -3.163967 Share Price Level   -2.116137 -3.522887     -2.901779 -2.588280   -2.203273   -4.088713   -3.472558 -3.163450 1st Difference   -6.899295 -3.524233   -2.902358 -2.588587   -6.844396   -4.090602   -3.473447 -3.163967 Table 01: Unit root test for stationary Japan If we have a look on the unit root test for the variables GDP and Share price to find out the stationary behaviour the Augmented Dickey Fuller Test with intercept and with intercept and trend in level and first difference. The t statistic value with trend is -2.653258 which is higher than the critical values in 1%, 5% and 10% critical value. The same applies with intercept and trend as the t statistic value -2.693600 is higher than the critical value in all the level of critical value. So from the nature of stationary behaviour we can say in level GDP shows nonstationary behaviour. And the first difference LnGDP is integrated with order one. In case of LnSP the results with intercept and with intercept trend in level are -2.116137 and -2.203273 which is higher than the critical values shows non stationary behaviour as they are higher than the critical value. The unit root test for the variables at first difference shows stationary as the t statistic value is than the critical value i n all level and they are integrated in order one. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test Malaysia t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -1.195020 -3.522887     -2.901779 -2.588280 -1.933335   -4.088713   -3.472558 -3.163450 1st Difference -5.951843 -3.524233   -2.902358 -2.588587 -5.923595   -4.090602   -3.473447 -3.163967 Share Price Level   -1.900406 -3.522887     -2.901779 -2.588280   -1.891183   -4.088713   -3.472558 -3.163450 1st Difference   -7.842122 -3.524233   -2.902358 -2.588587   -7.779757   -4.090602   -3.473447 -3.163967 The unit root test result for LMGDP and LMSP values presented in natural logarithm. And the level values with intercept and with intercept and trend for LMGDP is -1.195020 and -1.93335 respectively. The values are higher than the critical value means the series has non stationary behaviour. On the other hand the 1st difference values with intercept and with intercept and trend are -5.951843 and -5.923595 respectively. The 1st difference values are integrated with order one. And in the same way I did the ADF test to check for Stationary behaviour of LMSP in level and first difference with intercept and trend. The values in level are -1.900406 and -1.891183 with intercept and trend us higher than the critical value and the series is not integrated with order one. The first difference t statistic values are -7.842122 and -7.779757 with intercept and with intercept and trend respectively are less than the critical value in both the case implies that the series is integrated with order on e. Variables level/1st Difference Augmented Dickey Fuller Statistic(ADF) test UK t statistic value With Trend t statistic value With trend and Intercept 1% 5% 10% 1% 5% 10% GDP Level -0.690866 -3.522887     -2.901779 -2.588280 -2.377333   -4.088713   -3.472558 -3.163450 1st Difference -7.474388 -3.524233   -2.902358 -2.588587 -7.439027   -4.090602   -3.473447 -3.163967 Share Price Level -1.711599 -3.522887     -2.901779 -2.588280 -1.261546   -4.088713   -3.472558 -3.163450 1st Difference -7.254574 -3.524233   -2.902358 -2.588587 -7.391821   -4.090602   -3.473447 -3.163967 The results from Augmented Dickey Fuller test (ADF) for UK GDP in level with intercept and with intercept and trend is –0.690866 and -2.377333 respectively. Both the values in level are higher than the critical value and are integrated in order 0 shows non stationary behaviour. The t statistic values in 1st difference with intercept and with intercept and trend are -7.474388 and -7.439207 respectively. Which suggest that the critical values are less than the critical values in 1%, 5% and 10% level. So from the above hypothesis it can be said that it series is integrated with order one. When I performed the unit root test using the same method the series in level with intercept and with intercept and trend the values in are -1.711599 and -1.261546 respectively. The values are higher than the critical values implies that they are not integrated in order one shows non stationary behaviour. However, the 1st difference value of log natural share price is -7.254573 and -7.391821 wit h intercept and with intercept and trend respectively. So from the result we can say that the series is integrated in order one in both the cases with intercept and with intercept and trend. So the series in first difference is stationary. Variables level/1st D

Prisoners Normative Reintegration into Society Essay -- Social Issues,

Normative reintegration into society and the resocialization of released prisoners has long been a prominent problem in society. With recidivism rates in the United States upwards of 69% it is quite clear that released prisoners are having difficulty readjusting and returning to normative lives in society (Bureau of Justice Statistics, 2008). Prison aims to serve retribution, incapacitate, deter, and rehabilitate offenders, but much of the research on recidivism rates criticize the idea that â€Å"prison works† (Dhami, 2006). However, it seems with so many prisoners returning to prison within a year of being released, the prison system is not providing inmates with the rehabilitation and therapy needed to function once they return to society. In the past many studies have shown that inmates who take place in vocational and therapy based programs are more successful with reintegration into everyday life upon their release. Additionally, there have been numerous studies that h ave shown the healing and therapeutic abilities of animals when used in programs with deviant, sick, or mentally ill individual(Deaton, 2006) (Dell, 2011) (Field, 1951). So it would seem that the combination of vocational programs with the use of animals would be the next logical step in prison programs. While animal therapy programs are relatively new in the justice system, there are quite a few currently in use in prisons around the United States (Furst, 2006). The proposed study would be exploratory in nature and seeks to answer the following question; are prisoners that complete animal therapy programs while incarcerated more successful with normative reintegration into society when released? The researcher proposes that inmates who complete animal th... ...olees who experience homelessness are far more likely to return to prison than parolees that have a place to live (Visher, 2003). The emotional health, well being, and social comfort of a parolee is very important to reintegration into society as well. Many parolees have a difficult time controlling anger, relating to people, adapting to new situations, and maintaining friendships and family relationships. Programs with animals teach prisoners social and emotional skills that may help ease the transition for a parolee into society upon release. According to a study done on an animal therapy program in Virginia women’s correctional facility, in the last three years the prisoners that completed the program have a 0% recidivism rate and 100% employment rate, which is a far cry from the statistics of prisoners who did not participate in like programs (Deaton, 2005).