What Legacy Did Alexander the Great Leave Behind - 933 Words

Alexander the Great’s actions and decisions have significantly impacted upon the world during his time, ultimately leaving behind a legacy that can be affiliated with the westernization of the globe. He helped bring the western civilization, which included the scientific and liberal thinking of the Greeks to much of the rest of the world. He introduced a study of science for science’s sake to the nations and he is also considered as one of the most successful military commanders in history, for by the time of his death he had conquered most of the world known as Ancient Greece. However, his greatest achievement – which is to this day debated by scholars all over the globe – is his role in cultural diffusion. Contemporary scholars have†¦show more content†¦Alexander never wasted time. He always arrived before his enemies expected. His men followed him for more than 21,000 miles because they believed he had their best interests in mind. They always counted on him to lead them to victory after victory and he never failed. On the basis of military conquest, contemporary historians and especially those writing in Roman times who measured success by the number of human bodies left on the battlefield deemed him ‘great’. Professor Wright explains, â€Å"In the history of our European civilization four names stand out from all other: Alexander, Julius Caesar, Charles the Great, Napoleon. All four were so superior to the ordinary level of human capacity that they can hardly be judged by common standards. †¦ Alexander, both in his works and in his character, is entitled to the first place. †¦ He was the fine flower of Greek civilization †¦ the effects of his conquests in widening the horizon of men’s minds can only be compared with the discovery of America.† Before Alexander the world was a mesh of comparatively isolated and insular empires. 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The Sampling and Data Collection Procedures used in market research - Free Essay Example

Sample details Pages: 16 Words: 4696 Downloads: 3 Date added: 2017/06/26 Category Finance Essay Type Narrative essay Did you like this example? This study is based on 60 monthly observations from April 2005 to March 2010 inclusive. The period was chosen to provide enough observations to obtain reliable parameter estimates. The totality of the data was obtained from Yahoo Finance, Bank of England, and Office for National Statistics. Don’t waste time! Our writers will create an original "The Sampling and Data Collection Procedures used in market research" essay for you Create order Despite that historical Stock data is available on daily, weekly and monthly basis; monthly data was obtained because historical data for some other independent variables like inflation and money supply were only available monthly. FTSE100 Index was selected amongst the London Stock Exchange (LSE) FTSE group as it represents the share index of the 100 most highly capitalized UK companies and constitute about 80% of the market capitalisation of the entire LSE thus it is likely to lead to more robust estimates. For the selected macroeconomic variables, Interest rate data was obtained from Bank of Englands Monetary Policy Statistics, and Money supply data were sourced from Bank of England Publications: Bankstats (Monetary Financial Statistics). UK representative of Inflation rate, Consumer Price Index (CPI) data were obtained from Office for National Statistics (ONS). CPI for all items based on monthly percentage change was used. Data for Inflation rate, Money supply and Interest rate are measured by rates of change rather than absolute values as this facilitates comparison with stock returns. 3.2 Measure of Variables 3.2.1 Stock Return (SR) Dependent Variable LSE FTSE 100 Index Monthly Close Stock data adjusted for dividends and splits were downloaded from Yahoo Finance. From the monthly adjusted close data, the monthly stock return was calculated as follows: SR = log (Qt/Qt-1) 1 Where Qt is adjusted close price of t time, and Qt-1 = adjusted close price of t-1 time. Stock return was used as dependent variable to determine how the three macroeconomic variables (Inflation rate, Interest rate and Money supply) affect it. 3.2.2 Money Supply Independent Variable There is an abundance of literature which treats deposit modeling from a macroeconomic point of view. By money supply we mean the total stock of monetary media of exchange available to a society for use in connection with the economic activity of the country Ahuja (2004). According to the standard concept of money supply, it is composed of two elements (1) currency with the public and (2) demand deposit with the public. Central banks introduced monetary aggregates to monitor the money supply in the economy and the different monetary aggregates are M0, M1, M2, M3, M4 and MZM as defined below: M0 The physical currency (coins and bank notes) and the accounts of Central Bank exchangeable into physical currency; M1 M0 plus the amount in the demand accounts (checking accounts, current accounts, etc) M2 M1 plus the amount in savings account, money market accounts and small certificate of deposit accounts (CDs under $100,000). M is called the quasi-money, i.e the deposits wi thout maturity that could without any risk and quasi instantly be converted in cash; M3 M2 plus large CDs, repurchase agreements and currency deposit (Eurodollars in the US). In some countries, M3 takes into account all the ultra liquid and risky investments easy to sell into the market: institutional money funds, short term investment funds, term deposits, etc. M4 M3 plus medium term treasury bonds. In UK, M4 is defined as M3 plus private sector holdings of building society shares and deposits and sterling certificates of deposits. MZM represents the Money Zero Maturity i.e all the deposits without any maturity. In the US, MZM is M less small-demonian. Money Supply is the amount of money in an economy at a given time. The simplest definition is the actual amount of bank notes and coins in circulation. There are various variations on the above listed types and the exact definition of money supply varies from country to country. In the UK, there are only two Money S upply measures: M0 and M4. The exact definitions are revised from time to time by the Bank of England. M0 represents notes and coins in circulation with the public plus UK private sectors non-interest bearing sterling sight deposits with banks in the UK; plus UK private sectors interest-bearing retail sterling deposits with banks in the UK and is referred to as the wide monetary base, or narrow money. M4 represents UK private sectors holdings of: Sterling notes and coins; plus Sterling deposits with banks in the UK; plus Building society shares, deposits, and sterling certificates of deposit and is referred to as broad money or simply the money supply. Seasonally adjusted and non-seasonally adjusted broad money supply M4 are published monthly by Bank of England in its Quarterly Bulletin (BEQB). Thus the seasonally adjusted broad money aggregate M4 is a measure of the quantity of UK money supply and will be used in this study as one of the independent variables. Monthly seas onally adjusted growth rate data (percentage) were obtained from Bank of England, Bankstats (Monetary Financial Statistics) Tables Growth rates of M4 monthly seasonally adjusted data (Table A2.1.1). 3.2.3 Interest Rate Independent Variable Mankiw (2000) defines interest rate as, the market price at which resources are transferred between the present and the future. He further adds that interest rate is the return of saving and the cost of borrowing. A rise in interest rate could influence investors decision to switch from the stock market to the money market. Reduced interest rates also encourage demand for cash mainly for speculative purposes. Thus, the lower the yield on bonds and debt instruments, the higher the stock returns and the higher the yield on bonds and debt instruments, the lower the stock returns. The interest rate used in this study is the official bank rate that Bank of England charges banks for secured overnight lending as most bank lending rates are tied to the official bank rate. Data were obtained from Bank of England, Statistical Interactive Database Official Bank Rate history. In the UK, changes to the official bank rate are based on recommendations made by the Monetary Policy Committ ee and subsequently enacted by the Governor, Bank of England. Changes in interest rates are thereafter announced after a decision has been made following the Thursday meeting of the Monetary Policy Committee. Such change becomes effective after the announcement thus, there were instances where interest rates are changed within the month. To harmonize the monthly data for interest rates, data were adjusted where there is a change within a month by calculating the number of days based on the old rate and number of days based on the new rate. Results for the two rates are thereafter added to arrive at the interest rate for the month and used as an independent variable in this study. 3.2.4 Inflation Rate Independent Variable Inflation is a rise in the general level of prices of goods and services in an economy over a period of time. Inflation rate is the measure of price inflation. Inflation rate affects investors attitude and decisions on where to invest funds. Where inflation rate is high, real income would decline; investors will sell their assets which includes stocks and shares to improve their purchasing power as each currency buys fewer goods and services. However, where inflation rate is low, real income increases and investors will buy assets with their strong purchasing power. High inflation rate and hyperinflation can be caused by excessive growth of the money supply. High inflation rates negatively affect stock returns while low inflation rate boost stock returns. Inflation rate data was obtained from Office for National Statistics, Consumer Price Index monthly percentage change data. 3.3 Models Models used in this study are: The Unit root test Granger Causality test Multiple Regression analysis test. 3.3.1 Unit Root Test It is important to check whether a time series variable is stationary or non-stationary for the following reasons: To avoid spurious regressions. Where two variables are trending over time, a regression of one on the other could lead to a high R2 even when the two are totally unrelated. To avoid misleading results as the stationarity or non-stationarity of a series could influence its behavoiur and properties strongly. Also, where variables in the regression model are not stationary, standard analysis assumptions will not hold, thus the hypothesis test of the regression parameters would be invalid. As different unit root test can be employed, the Augmented Dickey-Fuller test was employed in this study. The objective of the test is to test the hypothesis H0: ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´ = 0 (Unit Root) H1: ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´ ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€šÃ‚   0 Where ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´ = p 1 The Dickey-Fuller unit root test was based on the following regression forms: ÃÆ'  ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  Yt = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´Yt-1 + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼t ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚  Ãƒ ¢Ã¢â€š ¬Ã¢â€ž ¢ Yt is a random walk (without constant and trend) ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  Yt = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´Yt-1 + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼t ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚  Ãƒ ¢Ã¢â€š ¬Ã¢â€ž ¢ Yt is a random walk with drift (with constant) ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  Yt = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²T + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´Yt-1 + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼t ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚  Ãƒ ¢Ã¢â€š ¬Ã¢â€ž ¢ Yt is a random walk with drift around a stochastic trend (with constant and trend) The Augmented Dickey-Fuller unit root test was based on the following regression forms: ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  Yt = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²T + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´Yt-1 + yi ÃÆ'Ã… ½Ãƒâ€šÃ‚ £ÃƒÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  Y t-1 + ÃÆ'Ã… ½Ãƒâ€šÃ‚ µt Where ÃÆ'Ã… ½Ãƒâ€šÃ‚ µt is a pure white noise error term ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚   Y t-1 = (Y t-1 Y t-2), ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  Y t-2 = (Y t-2 Y t-3) etc To test if ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´ = 0, Decision rule: Where t ÃÆ'†¹Ãƒâ€ Ã¢â‚¬â„¢ Augumented Dickey-Fuller critical value ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚  Ãƒ ¢Ã¢â€š ¬Ã¢â€ž ¢ do not reject null hypothesis, i.e. unit root exists. Where t ÃÆ'†¹Ãƒ ¢Ã¢â€š ¬Ã… ¡ Augumented Dickey-Fuller critical value ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚  Ãƒ ¢Ã¢â€š ¬Ã¢â€ž ¢ reject null hypothesis, i.e. unit root does not exists. To transform data from non-stationary to stationary, the Difference-Stationary Process (DSP) was used. The regression equation is: ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  (ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  Yt) = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ´ÃƒÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒ ¢Ã¢â€š ¬Ã‚  Yt-1 + ÃÆ'Ã… ½Ãƒâ€šÃ‚ µt Differencing was applied to render the series stationery. The use of 1st difference or 2nd difference generated the stationarity. 3.3.2 Granger Causality Test Despite that multiple regression analysis deal with the dependence of one variable on other variables, it does not imply causality. Granger causality test is implemented to identify how much one factor is significant in forecasting the other one. Granger (1969) discussed the important problem of apparent instantaneous causality and suggested that the problem often arises due to slowness in recording information or non usage of sufficiently wide class of possible causal variables. Thus, the results are not coefficients of the real dependence or indicators of the actual causality; rather it is just a sign of existing linear interdependency of one factor on another. The hypothesis is to hold only if one factor follows the other and the initial is a potential reason for the follower. Granger (1969) proposed a time-series data based approach to determine causality. In this study, Granger causality test was conducted to examine the direction of causality between Inflation rate, Intere st rate, Money supply and Stock returns. For example, does Inflation rate granger-cause Stock returns (INFR ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚  Ãƒ ¢Ã¢â€š ¬Ã¢â€ž ¢ SR) or does Stock return granger-cause Inflation rate (SR ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚  Ãƒ ¢Ã¢â€š ¬Ã¢â€ž ¢ INFR) with the arrow indicating the direction of causality. In a simple Granger-causality test, there are two variables and their lags. As required by the Granger test, each variable was first transformed to achieve stationarity and then lagged. Based on the above illustration, the following two equations can be specified where it is assumed that the disturbances ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼1t and ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼2t are uncorrelated: (INFR)t = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ± + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²i(INFR)t-1 + Tj(SR)t-j + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼1t (SR)t = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¸ + Øi(SR)t-1 + ÃÆ' Ãƒâ€¹Ã¢â‚¬  j(INFR)t-j + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ¼2t Subsequently, four different hypotheses can be formulated: Unidirectional causality from SR to INFR. Here, INFR i ncreases the prediction of SR but not vice versa i.e. Tj ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€šÃ‚   0 and ÃÆ' Ãƒâ€¹Ã¢â‚¬  j = 0. Unidirectional causality from INFR to SR. Here, SR increases the prediction of INFR but not vice versa. Thus, Tj = 0 and ÃÆ' Ãƒâ€¹Ã¢â‚¬  j ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€šÃ‚   0. Bilateral or Feedback causality. Here, the sets of SR and INFR coefficients are statistically significantly different from zero in both regressions i.e. an increase in SR increases the prediction of INFR and vice versa. Thus, Tj ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€šÃ‚   0 and ÃÆ' Ãƒâ€¹Ã¢â‚¬  j = 0. Independence. Here, the sets of SR and INFR coefficients are not statistically significant in both the regressions i.e. an increase in SR increases the prediction of INFR and vice versa. Thus, there are no granger causalit in any direction i.e. Tj = 0 and ÃÆ' Ãƒâ€¹Ã¢â‚¬  j = 0. Granger causality was tested using EViews Pairwise Granger Causality Test. A common difficulty in perfor ming Granger-causality test is the lag length as results are not independent from the chosen lag structure. Since Granger causality test is very sensitive to the number of lags, lag 2 and lag 10 was used along with the conventional 5 percent level of significance value to confirm that lagged terms are important in the causality test, and also because I did not use Akaike or Schwarz information criterion to select the lagged terms. 3.3.3 Multiple Regression Analysis test Regression analysis test is a statistical analysis utilized for the investigation of relationships between variables i.e. it is used to ascertain the causal effect of one variable on another variable. In this study, correlation and multiple regression analysis was used to predict the direction of change and estimate the quantitative effect of the causal variables on the variable that they influence. Thus, the study investigated the relationship between Inflation rate, Interest rate, Money supply, and Stock returns by examining the relationship between the dependent and explanatory variables using regression analysis. Regression analysis helps to understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. The method to be performed is outlined below: Estimated regression model Response variable and regression coefficient Estimating the coefficient of multiple determination 3.3.3.1 Estimated Regression Model Three explanatory variables: Money supply (X1); Interest rate (X2); and Inflation rate (X3), were investigated for their relationship with a response variable FTSE 100 Index returns (Y) model. According to Studenmund (2006), the multivariate regression model with K independent variable is represented as detailed below: Yi = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²0 + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²1X1i + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²2X2i + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²3X3i ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦. ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²KXKi + i Where i goes from 1 to N and indicates the observation number. ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²0 indicates the constant term ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² indicates the coefficient of the function. X1i indicates the ith observation of independent variable X1. X2i indicates the ith observation of another independent variable X2 X3i indicates the ith observation of another independent variable X3 i indicates the error term. The coefficient ÃÆ'Ã… ½Ãƒâ€š  ²1 measures the impact on Y of a one-unit increase in X1, holding constant X2, X3, ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦.. and XK but not holding constant any relevant variables that might have been omitted from the equation. Multivariate regression coefficient indicates that a change in the dependent variable associated with a one-unit increase in the independent variable in question holding constant the other independent variables in the equation. In this study, where there are three independent variables -money supply, interest rate and inflation rate, the above equation will be written as follows: SR = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²0 + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²1MS + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²2INTR + ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²3INFR + i Where, SR = Monthly percentage change in adjusted close in the FTSE 100 Index MS = Monthly seasonally adjusted M4 INTR = Monthly Bank of England Base rate. INFR = Monthly CPI rate. With ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²0 as the constant term, where MS, INTR and INFR = 0, then SR = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²0. Since Beta is the coefficient of the function, it therefore predicts the variance in SR from MS, INTR and INFR. Thus a negative beta coefficient indicates that MS, INTR and INFR affect SR negatively and a unit increase in MS, INTR and INFR will decrease SR by the coefficient amount. Also, a positive beta coefficient indicates that MS, INTR and INFR affect SR positively and a unit decrease in MS, INTR and INFR will increase SR by the coefficient amount. p-value was used to measure how reliable MS, INTR and INFR can predict SR. Were the p-value is greater than 0.05, it implies no statistical significant relationship with SR. 3.3.3.2 Testing the response variable and Regression Coefficients I used student t-test to examine if explanatory variables are significant predictor of the response variable. The t-statistics is given as: Where is given as: Sb = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²iÃÆ'â„ ¢Ãƒâ€šÃ‚ ­ is the hypothesised value, K is the number of parameters and n is the number of sample observation. Then we set the hypothesis: H0: ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²iÃÆ'â„ ¢Ãƒâ€šÃ‚ ­= 0 H1: ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²iÃÆ'â„ ¢Ãƒâ€šÃ‚ ­ÃƒÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€šÃ‚   0 If the hypothesised value is ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²iÃÆ'â„ ¢Ãƒâ€šÃ‚ ­= 0, then the testing amounts to deciding if the explanatory variables are a significant predictor of the response variable. However, in testing the overall significance of the regression we set the hypothesis: H0: ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²1 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²2 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²3 = 0 H0: ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²1 ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€šÃ‚   ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²2 ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€šÃ‚   ÃÆ'Ã… ½Ãƒâ€šÃ‚ ²3 ÃÆ' ¢Ãƒ ¢Ã¢â€š ¬Ã‚ °Ãƒâ€šÃ‚   0 This t est aims at finding out whether the explanatory variables do actually have any significant influence on the response variable. The easiest way to reach a decision is by means of p-values. A p-value less than 5% suggests that the estimated model is significant. 3.3.3.3 Estimating coefficient of multiple determination The coefficient of multiple determination (denoted by R2), in the four variable-model shows the percentage of the total variation of the response variable, Y that is explained by changes in the explanatory variables,X1, X2 and X3. Therefore: R2Y.X1X2X3 = ÃÆ'Ã… ½Ãƒâ€šÃ‚ £( The value of lies between 0 and 1. The higher the greater the percentage of the variation of response variable (the better the goodness of fit) explained by the regression plane (Koutsoyiannis 2003). At this point, we need to note that our model has not been check for the assumptions about the random variable and the explanatory variables. Therefore, I did not check if our data has presence of seasonality, serially correlated, heteroscedasticity, multicollinearity and autocorrelation. Chapter 4 Empirical Results and Analysis 4.1 The Unit Root Augmented Dickey Fuller unit root stationarity test are presented below: Table 1 Unit Root and Stationarity Test for FTSE 100 at level Null Hypothesis: FTSE100 has a unit root Exogenous: Constant, Linear Trend Lag Length: 3 (Automatic based on SIC, MAXLAG=10) t-Statistic   Ãƒâ€šÃ‚  Prob.* Augmented Dickey-Fuller test statistical -1.921036   0.6304 Test critical values: 1% level -4.130526 5% level -3.492149 10% level -3.174802 The computed Augmented Dickey-Fuller test-statistic (-1.921036) is greater than the critical values (-4.130526, -3.492149 and -3.174802 at 1%, 5% and 10% significant level respectively). I cannot conclude to reject H0. This implies that FTSE 100 has a unit root problem and the series is a non-stationery series i.e. not stationery at level. This position requires further testing at 1st level. Table 2 Unit Root and Stationarity Test for FTSE 100 at 1st Difference Null Hypothesis: D(FTSE100) has a unit root Exogenous: Constant, Linear Trend Lag Length: 2 (Automatic based on SIC, MAXLAG=10) t-Statistic   Ãƒâ€šÃ‚  Prob.* Augmented Dickey-Fuller test statistic -10.51879   0.0000 Test critical values: 1% level -4.130526 5% level -3.492149 10% level -3.174802 The computed Augmented Dickey-Fuller test-statistic (-10.51879) is smaller than the critical values (-4.130526, -3.492149 and -3.174802 at 1%, 5% and 10% 1st significant level respectively). Thus, I can reject H0. This implies that FTSE 100 does not have a unit root problem and the FTSE 100 series is a stationery series at 1%, 5% and 10% 1st significant level i.e. stationery at 1st difference Table 3 Unit Root and Stationarity Test for Inflation at level Null Hypothesis: INFLATIONRATE has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic based on SIC, MAXLAG=10) t-Statistic   Ãƒâ€šÃ‚  Prob.* Augmented Dickey-Fuller test statistic -8.527799   0.0000 Test critical values: 1% level -4.121303 5% level -3.487845 10% level -3.172314 The computed Augmented Dickey-Fuller test-statistic (-8.527799) is smaller than the absolute critical values (-4.121303, -3.487845 and -3.172314 at 1%, 5% and 10% significant level respectively). Therefore, I can reject H0. This implies that INFLATIONRATE does not have a unit root problem and the series is a stationery series at 1%, 5% and 10% significant level i.e. stationery at level. Table 4 Unit Root and Stationarity Test for Interest rate at level Null Hypothesis: INTERESTRATE has a unit root Exogenous: Constant, Linear Trend Lag Length: 1 (Automatic based on SIC, MAXLAG=10) t-Statistic   Ãƒâ€šÃ‚  Prob.* Augmented Dickey-Fuller test statistic -1.936709   0.6226 Test critical values: 1% level -4.124265 5% level -3.489228 10% level -3.173114 Computed Augmented Dickey-Fuller test-statistic (-1.936709) is greater than the critical values (-4.124265, -3.489228 and -3.173114 at 1%, 5% and 10% significant level respectively). Thus, I cannot conclude to reject H0. This implies that INTERESTRATE 100 has a unit root problem and the series is a non-stationery series at level i.e. not stationery at level. This result requires further testing at 1st level. Table 5 Unit Root and Stationarity Test for Interest rate at 1st Difference Null Hypothesis: D(INTERESTRATE) has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic based on SIC, MAXLAG=10) t-Statistic   Ãƒâ€šÃ‚  Prob.* Augmented Dickey-Fuller test statistic -2.960972   0.1520 Test critical values: 1% level -4.124265 5% level -3.489228 10% level -3.173114 Computed Augmented Dickey-Fuller test-statistic (-2.96092) is greater than the critical values (-4.124265, -3.489228 and -3.173114 at 1%, 5% and 10% significant level respectively). This implies that (D)INTERESTRATE 100 has a unit root problem and the series is a non-stationery series at 1st level i.e. not stationery at 1st level. Again, I cannot conclude to reject H0 at this point as the result requires further testing at 2nd difference. Table 6 Unit Root and Stationarity Test for Interest rate at 2nd Difference Null Hypothesis: D(INTERESTRATE,2) has a unit root Exogenous: Constant, Linear Trend Lag Length: 1 (Automatic based on SIC, MAXLAG=10) t-Statistic   Ãƒâ€šÃ‚  Prob.* Augmented Dickey-Fuller test statistic -6.816662   0.0000 Test critical values: 1% level -4.130526 5% level -3.492149 10% level -3.174802 At 2nd level, the computed Augmented Dickey-Fuller test-statistic (-6.816662) is smaller than the absolute critical values (-4.130526, -3.492149 and -3.174802 at 1%, 5% and 10% significant level respectively). Therefore, I can reject H0. This implies that DINTERESTRATE2 does not have a unit root problem and the series is stationery at 1%, 5% and 10% 2nd significant level. Thus the 2nd-difference of INTERESTRATE becomes stationery. Table 7 Unit Root and Stationarity Test for Money Supply at level Null Hypothesis: MONEYSUPPLY has a unit root Exogenous: Constant, Linear Trend Lag Length: 0 (Automatic based on SIC, MAXLAG=10) t-Statistic   Ãƒâ€šÃ‚  Prob.* Augmented Dickey-Fuller test statistic -5.787052   0.0001 Test critical values: 1% level -4.121303 5% level -3.487845 10% level -3.172314 Computed Augmented Dickey-Fuller test-statistic (-5.787052) is smaller than the absolute critical values (-4.121303, -3.487845 and -3.172314 at 1%, 5% and 10% significant level respectively). Therefore, I can reject H0. This implies that MONEYSUPPLY does not have a unit root problem and the series is a stationery series at 1%, 5% and 10% significant level i.e. stationery at level. Unit root test conducted on the four variables: Stock Returns; Interest Rate; Inflation Rate; and Money Supply were reliable as they all passed the Durbin-Watson test. The Durbin-Watson statistics were quite significant to reject the autocorrelation at 1.933634 for FTSE100 (1st difference); 1.935061 for Interest Rate (2nd difference); 1.984945 for Inflation Rate; and 1.978578 for Money Supply. 4.2 Granger Causality Augmented Dickey-Fuller test has been calculated as Granger causality requires that the series should be covariance stationary. .Granger Causality test was computed using EViews for lagged 2 terms at 5% level of significance with the following results. Table 8 Pairwise Granger Causality Test between FTSE100 DINTERESTRATE Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  DINTERESTRATE does not Granger Cause DFTSE100   55   4.84185 0.0120   DFTSE100 does not Granger Cause DINTERESTRATE   5.29129 0.0082 At lagged term 2, I will accept the null hypothesis that Interest rate does not granger-cause FTSE100 and that FTSE100 does not granger-cause Interest rate as the p-values are both below 0.05. However, the fact that Interest rate does not granger-cause FTSE100 does not imply that FTSE100 is independent of Interest rate and vice versa as granger causality refers to the ability of Interest rate to forecast FTSE100. Table 9 Pairwise Granger Causality Test between FTSE100 INFLATIONRATE Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  INFLATIONRATE does not Granger Cause DFTSE100   56   1.40244 0.2553   DFTSE100 does not Granger Cause INFLATIONRATE   0.32788 0.7220 The p-values above 0.05 suggest that Inflation rate granger-cause FTSE100 and vice versa. Thus I reject the null hypothesis H0. Table 10 Pairwise Granger Causality Test between FTSE100 MONEYSUPPLY Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  MONEYSUPPLY does not Granger Cause DFTSE100   56   0.59881 0.5533   DFTSE100 does not Granger Cause MONEYSUPPLY   1.99209 0.1469 Similar to the results in Table 9 above, I reject the null hypothesis H0 because the p-values are higher than 0.05 in both regressions. Money supply does granger-cause FTSE100 and FTSE100 does granger cause Money Supply. Table 11 Pairwise Granger Causality Test between DINTERESTRATE INFLATIONRATE Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  INFLATIONRATE does not Granger Cause DINTERESTRATE   55   3.78624 0.0294   DINTERESTRATE does not Granger Cause INFLATIONRATE   2.31506 0.1093 Table 11 postulates that Inflation rate does not granger-cause interest rate but Interest rate does granger-cause Inflation rate. P-value of 0.0294 is less than 0.05 (accept the null hypothesis) while p-value of 0.1093 is higher than 0.05 (reject the null hypothesis). Table 12 Pairwise Granger Causality Test between DINTERESTRATE MONEYSUPPLY Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  MONEYSUPPLY does not Granger Cause DINTERESTRATE   55   1.52566 0.2274   DINTERESTRATE does not Granger Cause MONEYSUPPLY   0.47661 0.6237 Money supply does granger-cause interest rate and Interest rate does granger cause Money supply. The null hypothesis is rejected in the two regressions because the p-value in the two instances are more than 5% level of significance. Table 13 Pairwise Granger Causality Test between MONEYSUPPLY INFLATIONRATE Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  MONEYSUPPLY does not Granger Cause INFLATIONRATE   58   1.04867 0.3576   INFLATIONRATE does not Granger Cause MONEYSUPPLY   0.25617 0.7750 Similar to the result in Table 12 above, since the p-values are higher than the 5% level of significance, the null hypothesis H0 is rejected in the two situations. Thus, Money Supply granger-cause Inflation rate and vice versa. Granger causality test carried out with lag 10 produced a different result as illustrated in Table 14. 4.4 REGRESSION TABLE 15 CORRELATION USING EVIEWS FTSE100 INTERESTRATE INFLATIONRATE MONEYSUPPLY DFTSE100   1.000000 INTERESTRATE -0.233544   1.000000 INFLATIONRATE   0.172117 -0.002656   1.000000 MONEYSUPPLY -0.316644   0.400237 -0.278901   1.000000 Correlation matrix amongst FTSE 100, Inflation rate, Interest rate and Money supply are listed in Table 12 above. The result shows that there is negative correlation between FTSE 100 and the macroeconomic variables Money supply and Interest rate. However, there is a positive correlation between FTSE 100 Index and Inflation rate. Also, among the macroeconomic variables, there is negative relationship between Interest rate Inflation rate, and Inflation rate Money supply. These are in line with what is generally explained in economic theory. As inflation increases the market reacts negatively (Varian, 2003). There is a positive correlation between Interest rate and Money supply. Results were further analysed using Excel and similar results were obtained In all macroeconomic variables, the pair-wise correlation was very low which suggest that there are no collinearity problems. With above result, there is need to verify the existence of multi collinearity by running the regression. Table 15: Regression results without testing for stationarity and unit root in Excel SUMMARY OUTPUT Regression Statistics Multiple R 0.352636386 R Square 0.124352421 Adjusted R Square 0.077442729 Standard Error 0.043224995 Observations 60 ANOVA  Df SS MS F Significance F Regression 3 0.014858768 0.004952923 2.650889742 0.057519925 Residual 56 0.104630409 0.0018684   Total 59 0.119489177     Coefficients Standard Error t Stat P-value Intercept 0.027716505 0.014080199 1.968473987 0.05397107 MS -0.017252571 0.010733585 -1.607344751 0.11360312 INTR -0.003263929 0.00317997 -1.026402297 0.30911525 INFR 0.012988814 0.015847688 0.819603093 0.41591714 From Table 15 above, Inflation rate affects Stock return positively as shown by ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² coefficient 0.01298. This further indicates that one unit increase of Inflation rate would cause Stock return to increase by 0.01298 units. However, Money Supply and Interest rate affects Stock return negatively with ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² coefficient of -0.01725 and -0.00326 respectively. This also indicates that a unit increase in Money supply and Interest rate would result to reduction in Stock returns by 0.01725 and 0.00326 units respectively. The statistical significance of Money supply, Interest rate and Inflation rate on Stock return is 0.11, 0.31 and 0.42 r espectively. Since the p-values are more than 0.05, it is a sign of low significance. R2 of 0.124 represents the prediction level of variance in Stock returns by Money Supply, Interest rate and Inflation rate. This also implies that only 12% of stock returns are predicted by combination of the three macroeconomic variables and other macroeconomic variables not covered in this study predicts stock return by 88%. Table 16: Regression results after testing for stationarity and unit root in EViews Dependent Variable: DFTSE100 Method: Least Squares Date: 08/23/10 Time: 16:16 Sample (adjusted): 4 60 Included observations: 57 after adjustments Coefficient Std. Error t-Statistic Prob.  Ãƒâ€š CONSTANT -0.024102 0.026751 -0.900944 0.3717 DINTERESTRATE -0.126212 0.049943 -2.527110 0.0145 INFLATIONRATE 0.014430 0.037484 0.384960 0.7018 MONEYSUPPLY 0.023353 0.021515 1.085388 0.2827 R-squared 0.162273   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Mean dependent var 0.000545 Adjusted R-squared 0.114854   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  S.D. dependent var 0.096607 S.E. of regression 0.090890   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Akaike info criterion -1.890737 Sum squared resid 0.437835   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Schwarz criterion -1.747365 Log likelihood 57.88599   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Hannan-Quinn criter. -1.835017 F-stat istic 3.422132   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Durbin-Watson stat 3.065866 Prob(F-statistic) 0.023644 Results from Table 16 above, where data was tested for unit root and stationarity, differs from what obtains in Table 15. Inflation rate and Money supply affects Stock return positively as shown by ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² coefficient 0.0144 and 0.0233 respectively. This implies that one unit increase of Inflation rate and Money supply would cause Stock return to increase by 0.0144 and 0.0233 units respectively. However, only Interest rate affects Stock return negatively with ÃÆ'Ã… ½Ãƒâ€šÃ‚ ² coefficient of -0.1262. Thus, a unit increase in Interest rate would result to reduction in Stock returns by 0.01262 units. The statistical significance of Interest rate, Inflation rate and Money supply on Stock return is 0.01, 0.70 and 0.28 respectively. Since the p-values for Interest rate on Stock return is 0.01, which is less than 0.05, it implies that Interest rate predi cts effect on Stock return. Statistical significance of Inflation rate and Money supply is more than 0.05 and indicates a sign of low significance. R2 of 0.162 represents the prediction level of variance in Stock returns by Money Supply, Interest rate and Inflation rate. This implies that only 16% of stock returns are predicted by combination of the three macroeconomic variables and other macroeconomic variables not covered in this study predicts stock return by 84%.

The Strategic Plan for Ninestiles School Free Essays

string(83) " are widely accepted and have become theoretic counsel for school ‘s scheme\." Development planning is the mechanism for a school to specify its strategic and operational betterment activities. Strategy, as a long-run purpose, sets the way for school and the nucleus moral intent. However a good scheme is non sufficient by itself but requires a sound short-run operational program. We will write a custom essay sample on The Strategic Plan for Ninestiles School or any similar topic only for you Order Now Davies, B. J, A ; Ellison, L. ( 2005 ) emphasise that the strategic â€Å" program provides a consistent manner of interpreting the nucleus moral intent of the school and its values into action, influenced by a hereafters position and vision. † With the coming of local direction of schools, parental pick, and the publication of school scrutiny conference tabular arraies, it is apparent that a school needs to advance and market itself to avoid a autumn in axial rotations. One of the challenges which the school sets itself, hence, is to develop a system which recognizes and wagess pupil accomplishment in order to better the school. This model scheme is produced for Ninestiles as a school betterment program. In this program I will roll up and analyze the information and information from Ofsted, public presentation tabular arraies, and the school web site and school profile to sketch the strategic program. In add-on, I will urge operational actions and planning procedures. More significantly, through doing the appropriate links between the literature reappraisal and the instance survey of school effectivity and betterment, I will bring forth an appropriate program to back up and advance whole-school and student success for farther instruction and life outside of school. Literature reappraisal Schools, as educational Centres, ne’er fail to pull attending from people, society and authoritiess since the eighteenth century. Consequently, every school has to alter to face challenges. However, school effectivity and school betterment have become the focal point of instruction systems in the modern universe. With development of economic system and society, schools can non shut their Gatess and leave the issues of outside universe in order to last and turn in turn toing the complicated alteration challenges in to the twenty-first century, which makes establishments more porous and permeable ( Elkind, 1993 ) . Schools hence need to do witting to face with alterations come from inside and outside of school. Fullan, Cuttress, and Kilcher ( 2005 ) outlined eight key alterations forces that all leaders would hold to understand, overcome and undertake in schools. They are: â€Å" ( 1 ) prosecuting peoples moral intents, ( 2 ) edifice capacity, ( 3 ) understanding the alteration procedure, ( 4 ) development civilizations for acquisition, ( 5 ) developing civilizations of rating, ( 6 ) concentrating on leading for alteration, ( 7 ) furthering coherency devising, and ( 8 ) cultivating tri-level development. † The eight alterations forces are non isolated and incorporate on an purpose of instruction in school. As an purpose of instruction, the moral intent is the greatest driver of alteration. â€Å" moral intent in educational alteration is an orientation of school ‘s spirit, that means to better society through to develop educational systems and so to raise quality of all citizen. Fullan ( 2005 ) stated that concentrating on leading is the most powerful lesson of alteration. It is non controversial, Collins ( 2001 ) and Mintzberg ( 2004 ) agreed with Fullan ( 2005 ) and pointed out that successful school need a effectual leading. â€Å" Secondary scheme for school betterment † ( The pilot school and pilot local governments, Defs and primary and secondary scheme, 2006 ) provides an overview of the indispensable elements of the secondary intensifying support programme, it as a counsel, makes sense for schools development. The cardinal subjects: Constructing leading capacity Bettering the conditions for larning Bettering the quality of instruction and acquisition Using informations intelligently Supplying an engaging and appropriate course of study Establishing a acquisition community ( The pilot school and pilot local governments, Defs and primary and secondary scheme, 2006, p? ) However, if Ninestiles School will turn to each of the subjects, the primary status is that there must be an equal leading and direction and acquisition conditions within the school. A good suggestion made by â€Å" Secondary scheme for school betterment 2006 † that is that a successful leaders should cognize as followed: how to get the better of opposition to anything new, grab chances and avoid jeopardy That large springs are associated with large wagess and that incrental chage will take them nowhere That the cardinal challenge is to alter people ‘s behaviors and that they can merely make that by act uponing their feeling every bit good as their thought How to take alteration every bit good as manage it Leadership in school should â€Å" turn to the position quo through set uping a sense of urgency, making a guiding group, developing a vision and scheme and pass oning both of them efficaciously † . In short, leading should be able to happen out new ways and attacks of working through warrant of short-run wins and consolidating advancement in order to ease more alteration. Rationale is that leading must guarantee that the nucleus activities of instruction and acquisition are cardinal to duty and answerability of the school ( The pilot school and pilot local governments, Defs and primary and secondary scheme, 2006 ) As a general driver, developing civilization of larning supply a set of schemes for people larning from each other. Change cognition requires furthering coherency devising in order to increase peoples corporate power to drive the system running frontward swimmingly. Dufour, Eaker, and Dufour ( 2005 ) stressed the necessity and power of professional acquisition communities while Fullan ( 2005 ) identified beyond one school and Pfeffer and Sutton ( 2000 ) commend that turning information in to actionable cognition is a societal procedure Black, Harrison, Lee, Marshall, and Wiliam 2003 and Fullam ( 2005 ) emphasised one of the highest-yield schemes for educational alteration late developed is assessment for larning. Fullan ( 2005 ) claim that schools need to alter persons, every bit good as demand to alter contexts, cultivating tri-level development provide more learning in context ( at school degree, territory degree and province level,2006 ) . Barber ( 2005 ) provinces same point of view that eight drivers are keys to make effectual and permanent alteration. These drivers are widely accepted and have become theoretic counsel for school ‘s scheme. You read "The Strategic Plan for Ninestiles School" in category "Essay examples" The first serious treatments and analyses of School effectivity emerged in the 1960s out of concern for equality of educational chance. In the beginning, surveies stressed societal background and heredity as the strongest influences. However, Wrigley ( 2004 ) and MacGilchrist et Al ( 2005 ) have listed failings of the school effectiveness tradition: â€Å" ( 1 ) excessively narrow a position of accomplishment ; ( 2 ) over trust on quantifiable results ; ( 3 ) force per unit area of answerability through testing, conference tabular arraies and review and can falsify the course of study, instruction and acquisition ; ( 4 ) identified characteristics of effectual schools may non be easy movable. In fact, these issues are non particular phenomenon, how to avoid these disadvantages has become more and more educationalists ‘ consideration. In contrast to school effectivity, during the past 30 old ages at that place has been a parallel thrust for school betterment used to accomplish organizational alteration through ab initio unsystematic attempts. Hopkins and Reynolds ( 2001 ) suggested that three elements should be taken into history when sing the development of school betterment: a ‘bottom-up ‘ attack to self-evaluation and betterment planning with teacher ownership ; greater focal point on student results through links with school effectivity community and going progressively ‘top-down ‘ through strategic authorities intercession. In short, betterment demands change. Expediently, bottom-up self-evaluation is a fast and direct feedback for monitoring and following up betterment program, top-down authorities intercession is a drive force to oversee and press that schools must concentrate on instruction and acquisition. Hargreaves and Shirley ( 2009.p5 ) analysed that three ways of alteration have gone earlier as followed: First manner of province support and professional freedom, of invention but besides incompatibility. Second manner of market competition and educational standardization in which professional liberty is lost. Third manner that tries to voyage between and beyond the market and the province and balance professional liberty with answerability. Entering the fast, flexible and vulnerable new universe of the twenty-first century, we have to face dramatically new jobs and challenges. It is realized that the old three ways of educational alteration have non matched the new alterations and development, A â€Å" 4th manner † of educational alteration has been identified, based on the best of the old ways of the yesteryear without withdrawing to or reinventing the worst of them ( Hargreaves and Shirley,2009 ) . They asserted that â€Å" it is non a manner to retain bossy control over narrowly defined ends and marks. The 4th manner, instead, is a democratic and professional way to betterment that builds from the underside, tips from the top and provides support and force per unit area from the sides. † Sing context of Ninestiles School, the 4th manner provide some inspiration: Leadership is the cardinal function for development of a school Every instructor should set duty before answerability. Michael Fullan ( 2009 ) points out that school alteration depends on what instructors do and believe. As a moral intent, instructors should set duty before answerability – it is every bit simple and every bit complex as this. Parents should be more to the full engaged. Students as active spouses in their ain development are most of import. Back land Ninestiles school is a 6th foundation school and it is a larger than most secondary schools in Birmingham. It serves 1471 pupils ( 11-18 old ages old ) in the Acocks Green country of Birmingham but besides attracts pupils from other countries of the metropolis. Just over a half pupils are White British ; somewhat over 10 % are from Asiatic Pakistani backgrounds and similar proportions are of Asiatic Indian heritage. A particular unit attached to the school has 45 pupils with address and linguistic communication of community troubles. ( Ninestiles website 2011 ) Ninestiles has been a specialist school for engineering for 15 old ages and has had applied larning position since 2007. Ninelstiles school is committed to a course of study which aims to supply a acquisition environment in which all pupils irrespective of gender, ability, societal or cultural background, are encouraged to accomplish to their full potency, all the pupils have been exposed to a assortment if instruction and learning manners experience of cardinal accomplishments. School ‘s mission is to fix all-around citizens who are able to play a full portion in the life in the community. By prosecuting aims with vision, Ninestiles seeks to prosecute the head, elevate the spirit, and excite the best attempt of all who are associated with the school. What does Ofsted state? Ninestiles School was to the full praised by Ofsted in 2009 and was judged as outstanding overall. Inspectors reported that Ninestiles â€Å" has made many alterations in order to to the full run into the demands of all pupils and get the better of any barriers to larning † ( Ofsted 2009 p.4 ) . Outstanding facets of the school include: Students ‘ accomplishment, as the school is extremely effectual at actuating pupils who have made limited advancement in the yesteryear. It is barely surprising that the huge bulk of parents are satisfied to the school. Teaching and acquisition, because of consistent manner in which instructors plan lessons in the visible radiation of pupil ‘s mark. Leadership and direction, as the cardinal precedences are to the point and based on the sound rating and school has been originative in developing high quality leaders at all degrees in the school. Student ‘s personal development and wellbeing as they appreciate in mature manner about their school and class as brilliant function theoretical accounts for younger pupils. Other effectual facets of the school were noted by Ofsted as follows: The course of study is effectual in run intoing the demands of all pupils. The course of study is a major factor in guaranting first-class behavior and high degrees of motive amongst all groups of pupils. Work-based accomplishments, including teamwork and endeavor, work-related acquisition chances prepare pupils outstandingly good for employment or the following phase in the instruction. In add-on, pupils have chances to try a broad scope of classs. These classs is strong work-related dimension. Consequently, the Information and communicating engineering is used really good and extensively. The attention, support, aid and counsel are highly effectual to lend to the pupils ‘ outstanding personal development. Students are safe in the school and parents and pupils value a really good relationship with grownups. The rapid passage to an all-age tutorial system was handled really good. Governors are really effectual because they play a cardinal function in guaranting that many new developments are carefully considered prior to execution. Governors insist that best value rules are applied to all that the school does. Ninestiles in the Performance tabular arraies? Harmonizing the Ofsted study in the last four old ages, there has been a fluctuation in GCSE consequences. Fortunately, there was a important rise in 2010 from 51 % to 64 % 5+A*-C including English and Maths. However, the public presentation of pupils at GCSE needs to be kept stable and if possible farther improved. More significantly ; from the tabular array as follows, it can be seen that compared with national and metropolis figures its GCSE public presentation is now higher. Here we should pay attending to CVA, in 2009, CVA suggested advancement in line with outlook at 997.1, but in 2010, the CVA raised dramatically to 1031. This suggests that in 2010 students made advancement well beyond outlook. Comparison with national and metropolis figures Year school National criterion Birmingham norm Ninestiles school 2009 50 % GCSE 1000CVA 48 % GCSE 1000CVA 51 % GCSE 997.1CVA 2010 53 % GCSE 1000CVA 55 % GCSE 1000CVA 64 % GCSE 1031CVA Beginning informations: DfE School and college public presentation tabular arraies. Ninestiles ‘ ain position of its effectivity Ninestiles is efficaciously structured to react to the demands of twenty-first Century instruction. The school twenty-four hours has been carefully designed with modern larning demands in head. The wide and balanced course of study is antiphonal to single demands and the altering national context. All squads have a structured remit and an consciousness of the portion they play in making the vision. About Curriculum statement Ninestiles School is committed to supplying a learning environment in which all pupils are encouraged to accomplish to their full potency. Students are assessed on twenty-first century accomplishments like teamwork and communicating. The pupils, their parents and instructor are all involved to take the degree or class in which pupils would wish to take. Ninestiles takes great pride in supplying chances for their pupils either at the academic or vocational development as it is believed that doing the appropriate links to the existent universe will non merely enrich their apprehension of the curriculum country but will besides get down to fix them for farther instruction and life outside of school. The school twenty-four hours has been carefully designed with modern larning demands in head. Reality Baste Leaning ( RBL ) is mandatory for all pupils. This type of larning focal points on existent universe scenarios and pupils learn by replying jobs About work-related acquisition Ninestiles school has taking border position of work-related acquisition. It has been a specialist school for engineering for 13 old ages and has had applied larning position since 2007. Work-related acquisition is defined by school as any planned activity that uses work as a context for larning ( OFSTED 2009 ) . By supplying pupils with the chances and context in order to develop their work-related accomplishments, cognition and understanding. Such construct is based on logic of specialisation and it involves work-related acquisition within the classs for all students at cardinal phase 4. It occurs across the course of study when different topics and classs are offered to pupils. ninestile ‘s mission is to fix all-around citizens who are able to play a full portion in the life in the community. As a typical engineering school school ‘s schemes reflect our aspirations and we seek an appreciate the counsel and encouragement in transporting out these aspirations aims. Every pupil in the school has been exposed to a assortment of learning and larning manners, experience and work out existent universe jobs and leaves school with extended experience of cardinal accomplishments. Our aspirations are targeted non towards rankings but instead towards accomplishing a topographic point where take great pride in supplying chances for their pupils either at the academic or vocational development as it is believed that doing the appropriate links to the existent universe will non merely enrich their apprehension of the curriculum country but will besides get down to fix them for farther instruction and life outside of school. Key precedences for betterment Fortunately, Ninestiles School has made many alterations positively, but we can non shy away from confronting its failings. Harmonizing to the review judgement reported by Ofsted in 2009, there are six facets that should be improved and strengthened: For the group ( 16-19 ) whose public presentation reached comparatively lower class than others group, most facets review concerned with were at grade 2 or 3. The in-between director working in ( 16-19 ) group should be adjusted and consolidated to to better tutoring and mentoring systems and heighten top-down bureaucratism, prescription and counsel. Finical support. Headteacher, with regulating organic structure and all staffs, analyses budget to guarantee school development program precedences with appropriate budget allotment. The school budget needs to be flexibly used to back up a push for betterment. ( Fullan, M. , Barber, ( 2009 ) Use the award system. The award strategy provide encouragement and acknowledgment for attempt and accomplishment. A survey conducted by Harris.L ( 1996 ) showed that the better the kids performed in all these old countries ( classwork, prep, attending, promptness, behaviour ) the more successful would both learning and larning become. Another must be emphasized is in footings of personal development and wellbeing for school overall, pupils had truly bad attending ( at class 3 ) and healthy life style ( at class 2 ) . Comparison with other similar school ( table 2 ) School Attendance Ninestiles In 2009 Ninestiles In 2010 Birmingham In 2010 England In 2010 % of half yearss missed 8.2 % 8.5 % 6.8 % 6.9 % Unauthorised absence 2.3 % 1.6 % 1.4 % Persistent absence 9.1 % 8.5 % 4.4 % 4.6 % Figure from OFSTED From table 2, it can be shown that pressing job of Ninestiles school is hapless attending, there are two steps that should be suggested, one is parent meeting and calling.The 4th manner recommend parents should be more to the full engaged. The school should present first twenty-four hours of absence naming place for all absentees and consult students and parents over wagess and countenance. Parents meetings should be held with all parents monthly and there should be hebdomadal updates by phone. In this instance, each pupils received monthly advancement cheque. Others is to set up award system. The 4th manner stressed the pupil as active spouse in their ain development is of all time the most of import. Award system efficaciously build pupils assurance for their farther survey. It is traditional and really effectual for pupil public presentation including category work, prep, attending, promptness, behavior and public presentation at GCSE. The 3rd facet should be highlighted is for leading, review pointed the school ‘s self-evaluation and community coherence did non exercise every bit good as outlook â€Å" leading should acquire the vision right to increase urgency and construct the guiding squad. The schools white paper ( 2010 ) emphasized school should better top-down bureaucratism and â€Å" bottom-up † support. It is good circle for self-evaluation † . The policy has non been to the full updated to run into all current demands. The school policy and patterns should be shared and public in the school web site. There is a statement in the school prospectus which linked to development program marks. Policy and pattern are reviewed and updated every term in visible radiation of altering profile. This is besides a good manner for all ( pupils, instructors, parents and society ) to measure our school. The monitoring and rating of instruction and acquisition has non ever identified rapidly enough the advancement made by different groups of pupils All the grounds from different instruction system around the universe shows that the most of import factor in finding how good kids do is the quality of instructor and instruction. High quality instructor is cardinal fact of successful school. The school alteration depends on what instructors do and believe ( Fullan ( 2000 ) . As a moral intent, instructors should set the duty before answerability. Raising entry demands and more preparation in or out-school is suggested by white paper. The school should guarantee all staffs must be in topographic point in order to better pupils ‘ public presentation. Specifically, the school needs to set up a particular group for the monitoring and rating of instruction and acquisition in order to react quickly to any fluctuations in advancement and proctor more efficaciously the advancement that different groups of pupils make in lessons. This group is to supervise more efficaciously the advancement that different groups of pupils make in lessons, peculiarly in Years 7 and 8 ( Ofsted 2009 ) . pupils public presentation at GCSE need to maintain stable and promote and school ‘s CVA should be Consolidated. Teachers are clear about their instruction ends that attempt on the school ‘s highest-priority ends in ways most likely to better pupils ‘ public presentation of academic. In the instance, instructors create a strategic program for bettering the quality of instruction and do adept usage of bing learning stuffs in order to give more clip to patterns that enrich and clear up the content. To develop instructors harmonizing to program and do certain their cognition and learning stills maintaining updated to fit the demands of societal and single ‘s development. Precisely, School betterment group need run intoing with instructors to place and research the issue that are involved in placing students in old ages 9 and 10. this conference should be based on informations gathered earlier in the school from logbooks and treatment with pupil deputies. Furthermore, there should be voluntary after-school or lunchtime lesson provided by staff and an excess session, affecting strong links with external bureaus is based on test techniques, is organized What issues/weaknesses have been identified? Precedences for Improvement Proposed Actions Success Criteria For the age group ( 16-19 ) whose public presentation reached comparatively lower Ofsted class than other groups in this school. For this group, most appraisals reached merely grades 2 or 3 Improve quality of instruction and acquisition Adjust in-between leading working in this group. Raise pupil aspirations through links with concern and higher instruction For this group, mark of most appraisals should make above classs 2 Students had truly hapless attending ( at class 3 with 8.5 % absence ) , Improve attainment Work with parents to advance good attending, recognizing links to attainment the attending to make 95 % relentless absence to be reduced to 5 % at grade 2. The school ‘s self-evaluation and community coherence were non effectual every bit good as outlook. the policy has non been to the full updated to run into all current demands. Monitoring and rating of instruction and larning have non been ever identified rapidly plenty Strengthen leading Build betterment group Monitor and track advancement more strictly school betterment groups become progressively influential in driving up criterion Student ‘s public presentation at GCSE needs to be kept stable and promoted. Provide encouragement and acknowledgment for attempt and accomplishment. Establish â€Å" good acquisition â€Å" civilization in school. It will be anticipate to 70 % 5+A*- including English and Mathematicss by 2012 Decision In recent old ages criterions have risen steadily in our school, the most of import thing is that a school is able to prolong this advancement or non when it confront with disputing circumstance sometime. It is shown above that Ninestiles School has won a well-deserved repute for its current effectivity and betterment from society and Ofsted while Ninestiles school has taking border position of work-related acquisition. the school assets, direction and societal supports all have been ready for Ninestiles to take obstructions for acquisition and made many alterations In order to run into all pupils ‘ demands. However, there are still many challenges that school has to face with. Ninestiles school can provides thoughtful and far-sighted strategic leading that create the environments that makes good learning pay off and larning efficaciously to back up and track our all aim. There has been an highly clear vision that reaches into every corner of this school. However, the most common position of scheme is to put the way of school ( Davies, B. Davies, J. A ; Ellison, L. 2005 ) . It consists of some short-time purpose, that is: First, school should beef up leading that should acquire the vision right to increase urgency and construct the guiding squad. Second, The school should set up evidence-based attack to bettering instruction and acquisition and better consistence in feedback and marker. Third, school should set in topographic point enhanced tutoring and mentoring systems to guarantee that all pupils are supported harmonizing to their demands. Finally, the school demands to put our appraisal system to guarantee that our enterprise on path and supervise our school as a whole is accomplishing the short term ends and long term aspirations. Pursuit of excellence, as counsel, sets an ambitious docket of aspirations by specific schemes and programs, which call for us to settle down to work in much land for one ‘s ain responsibility and concentrate on coordination, steadiness, clearcutness, pertinence and existent consequence. Our school needs to guarantee that all pupils and instructors can be to the full equipped to do a difference in the planning period. In another words, the school should be already to be after the following stage of its development because of â€Å" no best, but better â€Å" How to cite The Strategic Plan for Ninestiles School, Essay examples