Griggs v. Duke Power Company Research Paper Example | Topics and Well Written Essays - 1000 words

Griggs v. Duke Power Company - Research Paper Example This is because neither possessing a high school education nor passing the tests was a necessity for successful performance on the jobs in question. In the suit, they argued that the practices were illegal since a higher proportion of the African Americans did not have high school educations. On its part, the company put forward the argument that the requirements were based on its judgment and that they would generally improve the general quality of the workforce, and that the company had no discriminatory intent in instituting these requirements. Further, the company argued that its lack of discriminatory intent was demonstrated by its efforts to assist uneducated employees by financing two thirds of the tuition cost for high school education, (Rue & Byars, 2008). The ruling meant that the Duke Power Company could not use the two tests as the criteria for transferring incumbent employees from an outside job to an inside job. Based on the Title VII of the Civil Rights Act of 1964, businesses, including the Duke Power Company, should adhere to the several key provisions stipulated by Section 703. These provisions outline unlawful employment practices for businesses and companies. It is an unlawful practice for any employer to refuse or fail to hire or discharge any person, or otherwise to discriminate against any person with respect to his terms, privileges, compensation, or terms of employment, based on the person’s color, sex, race, religion, or national origin. It is also unlawful to segregate, limit, or classify employees or applicants for employment in any manner that would tend to deprive or deprive any person of employment opportunities, or affect his position as an employee adversely, due to the person’s color, sex, religi on, race, or national origin, (Rue & Byars, 2008).According to Rue & Byars (2008), it is also unlawful for an employment agency to refuse or fail to refer for employment, or otherwise discriminate against any person based on his or her color or race, or to refer or classify for employment any person based on his color, race, sex, or religion.  

, BUSINESS COMMUNICATIONS (CM1010-07E) Essay Example | Topics and Well Written Essays - 250 words

, BUSINESS COMMUNICATIONS (CM1010-07E) - Essay Example A clear heading and numbering system should be used; usually no more than three levels are preferred in order to maintain simplicity. The abstract is best written in the present tense and gives an overall summary of the entire report; the introduction is best written in the future tense and lets the reader know what they are going to read; the body is then written in the present telling the reader what they are reading, and the conclusion is best written in the past telling the reader what they have read. The style and tone of the report is important and it must be written with its intended audience in mind. If the intended reader is not apt in the specific topic area then the style and tone, together with the language must be kept more simpler than if the reader was well conversed or an expert in the area. Verbosity does not say more; it is better to write simply, clearly and to the point with correct grammar and transitional

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

Tragedy Through Misreading in William Shakespeares King Lear Essay

Tragedy Through Misreading in William Shakespeare's King Lear Shakespeare’s tragedy, King Lear, portrays many important misconceptions which result in a long sequence of tragic events. The foundation of the story revolves around two characters, King Lear and Gloucester, and concentrates on their common flaw, the inability to read truth in other characters. For example, the king condemns his own daughter after he clearly misreads the truth behind her â€Å"dower,†(1.1.107) or honesty. Later, Gloucester passes judgment on his son Edgar based on a letter in which he â€Å"shall not need spectacles†(1.2.35) to read. While these two characters continue to misread people’s words, advisors around them repeatedly give hints to their misinterpretations, which pave the road for possible reconciliation. The realization of their mistakes, however, occurs after tragedy is inevitable. Gloucester and Lear, create their eventual downfalls due to their inability to read deceit. Though these characters share the same tragic flaw, the means by which they make their errors is completely different. Gloucester remains a poor reader because he is quick to believe his sense of sight. When his illegitimate son, Edmund, reveals a deceitful letter designed to incriminate Edgar, Gloucester is quick to believe him. â€Å"Abominable villain†(1.2.74) he cries out before he even examines the letter with his reading glasses. Edmund’s trickery is conducted cleverly, but Gloucester’s lack of disbelief is unexplainable. Even though Gloucester is a fundamentally good man he tends to have a pessimistic view on his situation, as well as the rest of the world. Gloucester displays his inability to read and comprehend reality once more when he begins to read the skies. â€Å"... ...able to regain his ability to see but it is during the last act of the play in which the circumstances are completely out of his control. These characters both die because they are pushed way past the limits of human fortitude and competence. When Lear tells Gloucester â€Å"A man may see how this world /goes with no eyes† (4.6.146-47) he displays both of their misfortunes, but it is too late to prevent ultimate tragedy. Shakespeare proposes that their tragic saga is a mere game to the heavens. â€Å"As flies to wanton boys, are we to th’ gods,/They kill us for their sport† (4.1.37-38). This line generalizes the overall simplicity behind the tragedy of King Lear. Even though Gloucester and Lear made terrible, fatal errors the reader feels at the end as if it is intended to be their destiny. Work Cited Shakespeare, William. King Lear . New York: Oxford UP, 1994.

A Study On Customer Attitude Towards Online Shopping

Abstract:The technological development with respect to internet has given a new dimension to marketing. Online customers are increasing and the virtual marketers realize the importance of customer oriented approach. This online facility benefits the users to gain in depth information about the product and to compare and evaluate the products offered by various suppliers. To conduct an empirical investigation a survey was conducted to collect data and was analyzed and interpreted using SPSS.A questionnaire was developed based on the objective of the study. The factors facilitating online shopping were measured on a five point Likert Scale. It was very clear from the study that security was the main concern and the users also mentioned about the absence of physical handling of the products in online shopping. At the same time many users felt that it was very convenient and cost effective.IntroductionOnline shopping has been growing because of the technological advancement, convenience, better purchasing capacity and the availability of different search engines and easier payment modes. The availability of the quality of the information, various brands and products enable the customers to make a choice from a wider market. Customers come across different types of risks in online shopping and they may not opt for internet marketing.With the advent of the internet , online shopping has gained immense popularity . The ease and convenience of shopping from anywhere in the world without having a physical visit to any shopping mall, has made online shopping or e-shopping an indispensable facility for many people.Internet marketing tools such as e-mail marketing, blogs, face book,  twitter, MMS, SMS and webisodes ( webisodes are created to enable the customers to visit the sites repeatedly and thus converting them into brand loyal customers) make it easier for the marketers to reach to their customers. They also combine the various marketing activities such as advertis ing, online campaigns and other public relations to create product awareness.In a constantly changing world of today, where past is replaced by dynamic present and the dynamic present is replaced by more challenging future, the old ways of doing things is no longer valid thus a new technology brings with it not only the potential for success but also a good design , its value to its users, ultimate use and acceptability. The current situation of shopping is changing due to globalization, technical innovations and market saturation.The intensity of competition increases due to new products and services as well as the entrance of competitors from other industries. The continuously growing educational standards and the opportunity to gather information induce enormous changes in customer behavior.Consumer attitude towards e-shopping is s a new strategic marketing and the information available influences customer attitude positively. The advent of web technology constitutes a new medium of commerce which puts the customer in a position to directly and quickly interact with the web services.The empirical study will find whether online shopping will gain importance and its use will accelerate at a faster rate in the coming years. Thus the study concludes that the online shopping is more cost effective and less time consuming. The study also confirms that there is a willingness and readiness on the part of the users to go ahead with such technological sophistications or improvements.However in certain respects the users felt online payments system lacks in security and it caters to the needs of the educated mass and felt that it may not be of any use where the physical  handling of the product becomes important. A few users felt that shopping means a family affair and a few felt that they enjoy their shopping with friends. In such cases e-shopping may not be too interesting under certain field of marketing. This study covers the key areas related to internet market ing and the customers attitude towards shopping using internet.Literature ReviewThe researcher has made an attempt to present the reviews of available studies which consists of articles and other research papers in the related areas. The study revealed the customers’ perceptions and characteristics that influences customers attitudes toward online shopping. An earlier study conducted by Ghose (1998) predicted that the internet may be an important channel for marketing. Another study has revealed that the fear of security system in online shopping due to credit card fraud has been one of the major reasons for customers avoiding online shopping. (Ratnasingham 1998).A study by Palumbo and Herbig (1998) suggested that in coming years internet may offer cost effective and sophisticated tools for online advertising, sales promotion and placing orders and communicating with their customers all over the world. The study of Walters and Lancaster (1999) revealed that the internet offer s direct links with customers and suppliers and facilitates transactions processes and information transfer at a faster pace.Jayawardhena and Foley (2000) identified that convenience, site design and financial security are the dominant factors in customers assessment of e-satisfaction. A study by Torre and Moxon ( 2001), concluded that many companies have adopted internet for conducting business transactions and sharing business information with their customers. The study made by Thomas S.H. Teo (2001) revealed the linkage between the use variables such as age, gender,income, education and internet usage established the relationship of internet usage with respect to surfing , mailing, chatting and messaging.A study by Ranganatham and Ganapathy(2002) revealed that the safety, security and privacy of  websites have a greater impact on the intention of the customers do go for online transactions. The most important reason for internet users to avoid online shopping is its security. K een et al (2002) found that demographic factors such as age, gender, education and income has a significant effect on the attitude of the consumers towards online shopping and also revealed that educated internet users are more comfortable to go for online shopping. Benedict et al 2004 found from their study that the need to touch, feel, smell or ability to try a product influences customers decision whether or not to shop online. One of the main reasons for which customers hesitate to shop online is that online shoppers are unable to touch the real products in order to evaluate the quality.Different types of online buyers have different evaluations of website design and website reliability but similar perception of website security (Shegill and Chen 2005) . Nearly 70% of web users use internet for sending and receiving emails, surfing, chatting and messaging . India was ranked fourth after US, China and Japan in terms of internet users by Computer Industry Almanac in 2005. A study by Collier and Bienstock (2006 ) identified product delivery as an important factor that influences online customers satisfaction and future purchase intention.Online purchase intentions and influences of personal attitudes were similar for males and females. (Yu-Bin Chiu, Chieu-Peng Lin Taiwan and Ling Lang Tang ) Customers showed interest in products like cars, computers, mobiles apparel and also services such as ticketing, health management and tourism management. Approximately 10 percent of the world’s population use online shopping has been shown in Online Consumer Opinion Survey of AC Neilsen. Ebay Pay Pal has been established as pay sources for various online purchase that includes air , rail and movie tickets , electronic items and apparels Taylor Nelson Sofres refers in the Third Annual Global E-commerce report that e-shopping in India includes a variety of products such as  books, apparels and electronic items.Factors including competitive cost, better customer se rvice and other demographic considerations have helped the marketing industry to soar to greater heights. The development of information technology and the growth of the communication network has opened new horizons in the world of marketing . This has enabled the customer to enter into a new technological development called e-tailing. This e-shopping enables the customer to benefit from the pool of information , product comparison, cost effectiveness and various other offers from its suppliers and thus making a better choice of product.Research MethodologyA pilot study was conducted among fifteen people consisting of neighbors, students and colleagues to evaluate how well the questionnaire was framed and understood.Sampling DesignThe sample has been taken only from the IT industry and the education sector since they have the prior knowledge about internet browsing. A sample size of 240 was considered for the study. Respondents were selected by purposive and convenience sampling met hod for the study. The study uses exploratory research design and analyses the primary data to show customer attitude towards online shoppingThe primary data has been collected through a self administered and structured questionnaire. Questionnaires were given to different age group of people ranging between the age group of 25 to 50. The questions were framed in view of the main factors like Security, Reliability, Quality and Loyalty. The variables were measured against a five point Likert scale.Following the literature review Questionnaires were developed based on the literature to determine the behavioral pattern while purchasing  online. The questions were designed and presented in two different parts. Part I comprised of the respondents’ personal background such as age, gender, educational qualification , occupation and income per month. Part II enabled the respondents to furnish the factors that influenced them to buy the product online.The questionnaire was developed based on the observations of the researcher, review of the literature and consultations with the people on the same area of interest. The variables used in the study is also based on the review of the literature and the researches done by other researchers. The research objectives of the studyTo analyze the customer behavior pattern in on line shopping To understand the relevance of online shopping for retail products and services. To understand the views of the respondents about the retail and service industryStatistical AnalyticsData in this study were analyzed using Statistical Package for Social Sciences (Version 19.0) and Amos (Version 19). Factor analysis is used to identify the load variables to the factors such as Security, Reliability, Quality and Loyalty. Further these factors are analyzed to identify the inter relationship among the factor using the path analysis.Data Analysis Frequency table of demographic profiles Table – 1 AGE Age GroupMale Female 25 – 3 04838 30 – 353930 35 – 403217 40 – 451908 45 – 500603 Total14496Table -2 EDUCATIONAL QUALIFICATION EducationMale Female UG7342 PG4124 PROFESSIONALS2116 RESEARCH ERS0914 TOTAL14496Table -3 HOUSEHOLD INCOME PER MONTH IncomeMale Female Less than 10,0002416 10,001 – 20,0004237 20,001 – 30,0004825 30,001 – 40,0001813 40,001 & above1205 Total14496Table -4 FREQUENCY OF USERS Frequency of usersMale Female Daily3728 Alternate days5134 Once in a week3823 Occasionally1811 TOTAL14496Table -5 ONLINE SHOPPING EXPERIENCE AND SATISFACTION Satisfied with online shoppingMaleFemale Yes10258 No 4238 Total14496From the Tables 1 – 5 the following inferences were observed. Out of the 240 respondents men accounted for 60% and women accounted for 40% of the total respondents . Out of the 240 respondents the age group between 25 – 30 years represents 36% of the respondents and the age group between 30 – 35 represents 28% of the total  re spondents Out of 240 respondents, household income per month of Rs 10,001 – Rs 20,000 represent 33% of the respondents and income of Rs20,001 – 30,000 represents 30.4% of the total respondents.Out of 240 respondents holding Post graduate and above degrees represents 52% of the respondents and professional degree holders represent 15% and researcher scholars include 9% of the total respondents. Around 87.5% of the males use online services at least once a week while 88% of the females are online service once a weeks. About 71% males experienced satisfaction in online shopping while 60% females experienced satisfaction in online shopping.Hypothesis testing: The following are the findings of the hypothesis testing using chi-square through SPSS. Result 1: There is association between age and online shoppingResult 2: There is association between monthly family income and online shoppingResult 3: There is association between frequency of internet use and online shoppingResul t 4: Educational qualification and online shopping are relatedAround 82 % of the respondents felt that internet shopping was available 24Ãâ€"7 and it could be done from any place. They also expressed the convenience of home delivery at a cheaper price. A few respondents felt t hat it enabled them to engage themselves in other activities while shopping since extensive information was available online in different fields. However around 78% respondents felt t hat the payment gateway is not secure and they were under constant insecurity of their credit card information being hacked.They also said that it lacks the physical touch of the product and thus they were unable to judge the quality of the product. A few respondents felt that the absence of social interaction made online shopping a less interesting way of shopping. A few elders felt that  they didn’t have a credit card to use the internet shopping. One should accept the fact that though e- shopping is slowly increasing in India it doesn’t keep pace with the increase in global marketing.Many Indian customers do not use internet market due to their fear factor and the apprehension about the quality of the goods that they may receive. With increase of the secured payment gateways and the use of SSL ( Secure Socket Layers) which enables a safe transfer of private documents via internet may allow the e-marketing industry to flourish in the coming years.2.3 Factor AnalysisThe following table shows the various variables that were considered in the study. Table – 6Q1I trust the brand of the product Q2Novelty and innovation in the product Q3Delivery of the product is shipped to a wrong destination Q4My credit or debit card information can be misused Q5Product delivered on time Q6Shipping cost and FOB are clear Q7On line transaction is interrupted due to virus transmission Q8Product quality cannot be judged without physical touch Q9Extensive information about the product Q10Payment process is not safe Q11After sales services are not maintained Q12Goods delivered in good condition Q13Online customer satisfaction Q14Product packaging Q15Lack of knowledge about the stock in hand Q16Wider range of product line Q17Duplication of transaction due to network failures Q18Home delivery Q19Price list and discount offer are clear Q20Availability 24Ãâ€"7Table -7 KMO and Bartlett's TestKaiser-Meyer-Olkin Measure of Sampling Adequacy..837 Bartlett's Test of SphericityApprox. Chi-Square3709.515 df190 Sig..000The KMO measure of sampling shows that 84% infers that the sampling procedure is good and this leads to factor analysis.Table 8 Extraction Method – Principal Component AnalysisQ210.894964 Q110.883193 Q1010.826436 Q1310.813798 Q1210.807486 Q1410.798794 Q1810.788084 Q1910.766677 Q910.751079 Q1110.74923 Q1610.726154 Q1710.69611 Q810.670899 Q1510.657976 Q510.649796 Q2010.573682 Q410.560741 Q610.478726 Q310.439737 Q710.434629From the scree plot we confirm that the four factors S ecurity (F1), Reliability (F2), Quality (F3), Loyalty (F4) can be formed.Table – 9Component 1234 Q11.772 Q8.755 Q12.753 Q5.744 Q17.685 Q10.666 Q4.661 Q7.656 Q15.639 Q3.607 Q6 .830 Q20 .787 Q9 .779 Q16 .582 Q19 .568 Q13 .876 Q18 .814 Q14 .789 Q2 .930 Q1 .924 Table – 10Rotated Component Matrix(a)Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 8 iterations.Table -11 Transformation MatrixComponent1234 1.795.494.342.085 2-.420.404.198.789 3-.097-.450.887-.044 4.427-.625-.241.608 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.Path Analysis diagram is drawn and from the diagram it indicates that the variables are factored as follws.This diagram shows that in Factor 1 Security the following variables are identified. Q17Duplication of transaction due to network failures Q10Payment process is not safe Q4My credit or debit card information can be misus ed Q7On line transaction is interrupted due to virus transmission Q15Lack of knowledge about the stock in hand Q3Delivery of the product is shipped to a wrong destination Q11After sales services are not maintained Q8Product quality cannot be judged without physical touch Q12Goods delivered in good condition Q5Product delivered on timeThe following variables are identified by Factor2Q16Wider range of product line Q19Price list and discount offer are clear Q6Shipping cost and FOB are clear Q20Availability 24Ãâ€"7 Q9Extensive information about the productThe following variables are identified by Factor 3Q13Online customer satisfaction Q14Product packaging Q18Home deliveryThe following variables are identified by Factor 4Q1I trust the brand of the product Q2Novelty and innovation in the productScope for further Research and Suggestion Several types of viral marketing can be studied with relevance to viral marketing for retail products in India. This study is restricted to Chennai and i t can be further extended to other metropolitan cities as a comparative study for future research.ConclusionThe study revealed that the customer were more willing to use internet for the services rather than the products. Most of them were content with rail booking through online however a few felt that booking air tickets were little more expensive since the travel agents were able to give better competitive ticket fare. The study also revealed that internet is less time consuming and more cost effective. Many were of the opinion that while travelling to new places they were very comfortable to find the details of places, accommodation and food.They were also able to make a better choice by comparison the prices offered and the kind of the service provided. Even though in many hospitals online booking was available many felt that it was easier to call and fix up and appointment rather than doing it thro online. However they felt that many foreigners take up the treatment by using t he internet. People were also keen on placing orders for health care products like Amway. Another factor that influenced the buyers was the physical touch of the product.Though there may be a larger range of products to select from, the n on disclosure of all the information about the product may pose a threat to the web users. Moreover the browsing speed, connectivity , power shut down and other technical problem may further crb the growth of internet marketing. The most important factor that prevents the growth of the online marketing is the safety and security .The fear of their debit/credit card being misused and the lack of information posted in their respective web sites post a major threat for the customers. A The online transactions doesn’t allow for a social network or a pleasant family outing and in practice the expectations of the customers is to shop with friends and family and such an expectation may not be fulfilled in online shopping.SuggestionsBrands should mo nitor the cyberspace for unauthorized use of their brand names. The companies should have policies and procedures that enable them to remove the web sites that violate the copyright laws. They should also educate their customers about the risks of buying from unauthorized sources and should have a consortium to report suspicious goods and sellers.

Amputation Mishap

Amputation Mishap The Neighborhood News reports of a medical error at The Neighborhood Hospital. The report states a 62 year-old male patient underwent surgery to have his leg amputated only to discover the wrong leg was amputated during surgery. The newspaper article states the mishap is negligence. In the following paragraphs, negligence, gross negligence, and malpractice are discussed and determine if the newspaper’s statement of negligence is correct. Ethical principles in nursing and nursing documentation regarding such issues are also discussed. Negligence and malpractice fall under the tort laws definition.According to Guido (2010), â€Å"Torts are civil wrongs, not based on contracts, but on personal transgressions in that the responsible person performed an action incorrectly or omitted a necessary action† (p. 92). Tort laws are based on fault and in a health-care setting, tort laws are the most common. To determine if the above scenario results in negligence, gross negligence, or medical malpractice, one must understand the definition of each. According to Guido (2010), negligence is a general term and â€Å"equates with carelessness, a deviation from the standard of care that a reasonable person would use in a particular set of circumstances† (p. 2). According to Judson and Harrison (2006), four key elements (four D’s), must be present to prove negligence (p. 101): 1. Duty: The person charged has a duty to provide care to the patient. Neighborhood Hospital and staff have a duty to provide a standard of care that a reasonable person would use in a particular set of circumstances. 2. Dereliction: The person charged breaches the duty of care to the patient. The operating room team failed to identify the correct leg for amputation prior to proceeding with the operation; therefore a breach of duty has occurred. 3.Direct cause: The breach of duty is a direct cause of injury to the patient. The wrong leg is amputated as a direct result of failure to identify the correct leg for amputation. As a direct result, the patient will become a double amputee once the correct leg is amputated. 4. Damages: A recognizable injury to the patient is present. In this case, the wrong leg was amputated deeming a recognizable injury. Using the above criteria, negligence is present in this case scenario. Gross negligence occurs when medical practitioners perform an intentional act regardless of the negative, anticipated consequences.In this scenario, the patient must prove the medical staff at Neighborhood Hospital intentionally amputated the wrong leg. The medical staff at Neighborhood Hospital did not intentionally amputate the wrong leg, therefore ruling out gross negligence. According to Guido (2010), medical malpractice is â€Å"the failure of a professional person to act in accordance with the prevailing professional standards or failure to foresee consequences that a professional person, having the necessary skills and education, should foresee† (p. 93). Guido further states the difference between negligence and malpractice is licensure.If the act is by a non-professional person, it is negligence. If the act is by a professional person, it is malpractice. Six elements must be present to prove malpractice (Guido, 2010, p. 93): 1. Duty owed to the patient Neighborhood Hospital and staff have a duty to provide a standard of care that a reasonable person would use in a particular set of circumstances. 2. Breach of the duty owed to the patient. The operating room team failed to identify the correct leg for amputation prior to proceeding with the operation; therefore a breach of duty has occurred. 3. Foreseeability.The omission of identifying the correct leg for amputation prior to surgery. 4. Causation: breach of duty owed caused injury. The wrong leg is amputated as a direct result of failure to identify the correct leg for amputation. As a direct result, the patient will become a double ampute e once the correct leg is amputated. 5. Injury. In this case, the wrong leg was amputated deeming a recognizable injury. 6. Damages. The amputated leg cannot be replaced; therefore the patient is entitled to compensatory damages regarding pain and suffering, permanent disability, disfigurement, emotional damages as well as financial loss and medical expenses.In this scenario, all six elements to prove malpractice are present. The negligence is by licensed personnel in a hospital setting. Using the definitions and criteria above, the newspaper incorrectly defines the mishap as negligence. The correct term to use in this case is professional negligence or malpractice. Nursing documentation should be reflective of the patient’s hospital stay. This includes identifying and addressing patient needs, assessments, problems, limitations, and responses to nursing interventions.According to Guido (2010), â€Å"Documentation must show continuity of care, interventions that were impleme nted, and patient responses to the therapies implemented. Nurses’ notes are to be concise, clear, timely, and complete† (p. 197). Guido (2010) lists the following guidelines for nurses to use to ensure documentation is complete and accurate (p. 197-209): 1. Make an entry for every observation. If documentation is absent, it can be assumed an observation did not take place. 2. Follow-up as needed. Evaluation and observations require follow up to ensure appropriate patient responses and optimal outcomes. . Read nurses notes prior to giving care. Reading nurses notes enable the nurse to know and understand patient diagnosis, response to treatment, and steps necessary to carry out the plan of care. 4. Always make an entry (even if it is late). Document immediately after the observation to reduce the risk of losing valuable information. A late entry is acceptable although risks omitting valuable information. Never document an event before it happens. 5. Use clear and objecti ve language. Document using clear, objective, and definite terms to describe the observation.Vague terms lead to misinterpretation. 6. Be realistic and factual. It is important to document factual observations and assessments exactly as they happen. It is also recommended to document a realistic picture of the patient, especially if the patient is noncompliant with the plan of care. 7. Chart only one’s own observations. Charting observations of others is not accurate observations and can cause credibility of the nurse in question. 8. Chart all patient education 9. Correct chart errors. 10. Identify oneself after every entry. 11. Use standardized checklists or flow sheets. 2. Leave no room for liability. According to Guido (2010), â€Å"Understanding one’s ethics and values is the first step in understanding the ethics and values of others and in assuring the delivery of appropriate nursing care† (p. 4). Nurses and other healthcare providers face ethical issues d aily. Together, law and ethics guide nursing practice to provide safe, effective care keeping patients free from harm. â€Å"Ethics are concerned with standards of behavior and the concept of right and wrong, over and above that which is legal in a given situation† (Judson & Harrison, 2006, p. ). In addition, understanding law and ethics in nursing practice keeps nurses at their professional best and decreases the risk of legal litigation, such as the scenario described by the Neighborhood News. â€Å"Though malpractice is rare in the lives of individual healthcare professionals, the number of malpractice suits is on the rise† (Larson & Elliott, 2010, p. 153). The nursing profession has more professional responsibility and accountability than any other time in the history of nursing.According to Weld and Garmon Bibb (2009), â€Å"nurses must confront the fact that they now owe a higher duty of care to their patients, and by extension, are more exposed to civil claims for negligence than ever before† (p. 2). Understanding ethical principles in nursing, importance of nursing documentation and how it relates to medical malpractice and negligence is imperative. References: Guido, G. W. (2010). Legal & Ethical Issues in Nursing (5th ed. ). University of Phoenix eBook Collection database. Judson, K. , & Harrison, C. (2006). Law & Ethics for Medical Careers (5th ed. ). University of Phoenix eBook Collection database.Larson, K. , & Elliott, R. (2010, March-April). The Emotional Impact of Malpractice. Nephrology Nursing Journal, 37(2), 153-156. Ebscohost. com. Prideaux, A. (2011). Issues in Nursing Documentation and Record Keeping Practice. British Journal of Nursing, 20(22), 1450-1454. Ebscohost. com The Neighborhood- Pearson Health Science. The Neighborhood News. Retrieved October 1, 2012, from http://pearsonneighborhood. ecollege. com/re/DotNextLaunch. asp? courseid=3609454 Weld, K. K. , & Garmon Bibb, S. C. (2009, January-March). Concept Analys is: Malpractice and Modern-Day Nursing Practice. Nursing Forum, 44(1), 2-10. Ebscohost. com.

How to Make Invisible Ink With Baking Soda

How to Make Invisible Ink With Baking Soda Follow these easy instructions to make non-toxic invisible ink, in just a few minutes, using baking soda (sodium bicarbonate). The advantages of using baking soda are that its safe (even for kids), simple to use, and readily available. Invisible Ink Ingredients Baking sodaPaperWaterLight bulb (heat source)Paintbrush or swabMeasuring cupPurple grape juice (optional) Make and Use the Ink Mix equal parts water and baking soda.Use a cotton swab, toothpick, or paintbrush to write a message onto white paper, using the baking soda solution as ink.Allow the ink to dry.One way to read the message is to hold the paper up to a heat source, such as a light bulb. You can also heat the paper by ironing it. The baking soda will cause the writing in the paper to turn brown.Another method to read the message is to paint over the paper with purple grape juice. The message will appear in a different color. The grape juice acts as a pH indicator that changes color when it reacts with the sodium bicarbonate of baking soda, which is a base. Tips for Success If you are using the heating method, avoid igniting the paper; dont use a halogen bulb.Baking soda and grape juice react with each other in an acid-base reaction, producing a color change in the paper.The baking soda mixture can also be used more diluted, with one part baking soda to two parts water.Grape juice concentrate results in a more visible color change than regular grape juice. How It Works Writing a secret message in baking soda solution slightly disrupts the cellulose fibers in paper, damaging the surface. When heat is applied, the shorter, exposed ends of the fibers darken and burn before the undamaged sections of paper. If you apply too much heat, theres a risk of igniting the paper. For this reason, its best to use either the grape juice chemical reaction or else apply a gentle, controllable heat source.

Poverty in America essays

Poverty in America essays Poverty in the United States is getting worse each day and not enough is getting done about it. There are people who want to help the poor, but no one knows exactly how to help them. Those who are against poverty agree that something needs to be done, but they do not know how to go about getting things done. A primary reason for people not taking action is because of lack of information that is provided about issues on poverty. There is no limited amount of information about poverty. People only need to know where to go to obtain such information. Issues about poverty is not stressed enough by the media to keep America informed on what the country is going through with this problem. Poverty in America is being blamed on the system and the individual affected. The system is to blame because of social programs like welfare and social security on give a minimal amount of money to aid the poor. The Trickle Down approach which was introduced by the Reagan and Bush Administrators, was installed with the belief that by issuing a tax cut amongst the upper class would give more money into the economy that would eventually reach the lower class. A second program issued was the Interventionist approach, which was an action made on behalf of the federal government to help educate and employ the poor in order to help them attain a job career. Unfortunately, these social programs was not able to keep up with the inflation rates and the constant want of material goods by the poor, created by the need to fit in with the middle and upper classes (Burton, 1992). As individuals, poverty is being blamed because of the lifestyles that families live in today. It is said that because of the lack of support in poor families, individuals raised in poverty are likely to fail as adults (Bradbury, 2001). Education can take a toll on how much support poor families receive. With the lack of education, and intelligence, individua...