Individual Assignment Process Improvement Plan Essay Example for Free

Individual Assignment Process Improvement Plan Essay Individual Assignment: Process Improvement Plan  · Complete the Statistical Process Control for the process identified in Week One.  · Write a 1,050 words (maximum) explanation of the control limits including the calculations and data used to determine them.  · Discuss the effect of any seasonal factors using the process performance data collected each week.  · Discuss the confidence intervals and their usefulness based on the number of data points. General Questions General General Questions Complete the Statistical Process Control for the process identified in Week One. Write a paper of no more than 1,050 words in which you explanation of the control limits, including the calculations and data used to determine them. (I expect everyone to use the data that they have collected and create a control chart for your process. I want to see your calculations for the upper and lower control limits as well as the raw data). Discuss the effect of any seasonal factors using the process performance data collected each week. Discuss the confidence intervals and their usefulness based on the number of data points. Format your paper consistent with APA guidelines. When choosing your major, think about the kind of job you want, but think about the person you are. If you are someone who doesnt want to get up before noon, for example, you might not want to choose a major where the job possibilities require you to work early in the morning. In this file OPS 571 Week 5 Individual Assignment Process Improvement Plan you can find overview of the Statistical process control (SPC) Individual Assignment: Process Improvement Plan  · Complete the Statistical Process Control f Complete course guide available here https://bitly.com/12CiLPG When choosing your major, think about the kind of job you want, but think about the person you are. If you are someone who doesnt want to get up before noon, for example, you might not want to choose a major where the job possibilities require you to work early in the morning. General Questions General General Questions Complete the Statistical Process Control for the process identified in Week One. Write a paper of no more than 1,050 words in which you explanation of the control limits, including the calculations and data used to determine them. (I expect everyone to use the data that they have collected and create a control chart for your process. I want to see your calculations for the upper and lower control limits as well as the raw data). Discuss the effect of any seasonal factors using the process performance data collected each week. Discuss the confidence intervals and their usefulness based on the number of data points. Format your paper consistent with APA guidelines.

Hr Provision Essay Example for Free

Hr Provision Essay Provision function: is a consecutive process of human resources planning, job analysis, recruitment, selection, placement and incorporation. HR Planning The ongoing process of systematic planning is to achieve optimum use of an organizations most valuable asset its human resources. The objective of HR planning is to ensure the best fit between employees and jobs, while avoiding manpower shortages or surpluses. Sands Corporation would have to look at the three key elements of the HR planning process, which are: forecasting labour demand, analyzing present labour supply, and balancing projected labour demand and supply. Proper human resource planning will enable Sands HR department to plan recruitment, selection, training and career development . The HR plan needs to be flexible enough to meet short-term staffing challenges, while adapting to changing conditions in the business and environment over the longer term. Job Analysis and Design Job analysis is the process by which HR systematically investigate the task, duties and responsibilities of the jobs within an organisation. For human resource to be effective, Sands HR must be aware of the essentials that amount to each position. That is there should be a process whereby the substance, demands and responsibilities of a job are determined. Therefore two sets of information should originate from job analysis. First, Job Description which is the document that identifies and defines: a job in terms of duties, responsibilities, tasks and supervisory relationships. Second, Job Specification which is a written statement which emphasises the characteristics required from the incumbent to perform the job successfully, which should include skills, abilities and knowledge . Recruitment and selection the process of acquiring applicants who are available and qualified to fill the positions and choosing from a group of applicants the individual best suited for a particular position. Recruitment usually comes about as a result of HR planning and vacant positions that have to be filled. The staffing personnel, should use the job analysis as the point of departure, and follow steps such as recruitment planning, recruitment action (how, where and when), the type of recruiting source, screening and selecting . HR manager and the staffing personnel should through the recruiting process, consider the legal aspects as well, such as the labour Relation Act, No. 66 of 1995, the Basic Conditions of Employment Act, No. 75 of 1997 and the Employment Equity Act, no. 55 of 1998. Placement this is the process by which the staffing specialist will place a new appointed employee in an organisation, or transfer existing employees are transferred to new posts. Placement is important because of the heterogeneity of the labour groups. The staffing personnel should make sure that there is â€Å"FIT† between the job itself and the new job incumbent, so that there would be high productivity and a lower turn over from the new incumbent. It should be clear that placement is a combination of the employers’ requirement to fill a position successfully and the employee’s motivation to reach the top. Incorporation The specialist in training and development should attend and make sure that the new employee settles into the new position. The employee should be provided with the information regarding the organisation and its culture through orientation, must also be given specific information about the position and the department should be given through induction. The new employee must be made to feel part of the new work group as soon as possible. The training personnel need to explain the organisations policies, rules and regulations to the new employee as well as counter negative influences by fellow workers.

Study on Monetary Policy and the Stock Market

Study on Monetary Policy and the Stock Market Monetary policy is the regulation of the interest rate and money supply of a country by its Central Bank or Federal Reserve in other to achieve the major economic goals which include price stability, full employment, economic growth etc.  Ã‚   The stock market on the other hand is often considered a primary indicator of a countrys economic strength and development as it is a major source of savings and income for most individuals. History has shown that the economy of any country reacts strongly to movements in stock prices and is replete with examples in which large swings in stock, housing and exchange rate markets coincided with prolonged booms and busts (Cecchetti, Genberg, Lipsky and Wadhwani, 2000). Recent happenings even confirm this as the latest economic recession was preceded by a crash in the stock market. As a result of the relationship between the stock market and the economy, it is very important to the Central bank that the stock market performs well as bad performance can seriously disrupt the economy. This is because the stock market serves as a primary source of income and retirement savings to many and movements in stock prices can have a major effect on the economy as it influences real activities such as consumption, investments, savings etc While some economists say that monetary policy decisions depend on stock price movements, some others believe that stock price movements depend on monetary policy decisions. In this paper, we analyze both sides of the coin by looking at how stock markets react to monetary policy and how monetary policy reacts to movements in stock markets. This research work is aimed at finding out which granger causes which using the Granger Causality test. We will also analyze the relationship between both interest rates and monetary policy and that between money supply and monetary policy. In section II, a thorough review of the relevant literature of the topic is carried out as we try to understand more about the relationship between monetary policy and the stock market and the effects of both components (money supply and interest rates) of monetary policy 0n the stock market. In the next section, we describe the variables and data set used in the study and the empirical model is developed. Results are presented and discussed in the next section. We conclude the paper in section V and suggestions for further studies are pointed out and policy implications are considered. REVIEW OF RELEVANT LITERATURE Monetary policy is one of the most effective tools a Central Bank has at its disposal (Maskay, 2007) and is used to achieve the macroeconomic goals set by the government. This is done by regulating the two components of monetary policy which are interest rates and money supply to maintain balance in the economy. The stock market is an important indicator of the wellbeing of the economy as stock prices reflect whether the economy is doing well or not. Movements in stock prices have a significant impact on the macroeconomy and are therefore likely to be an important factor in the determination of monetary policy (Rigobon and Sack, 2001). The stock market is a financial market where equities are bought and sold either as an IPO (Initial Public Offer) in the primary market or exchange of existing shares between interested parties in the secondary market. Although stocks are claims on real assets and researchers have found considerable evidence that monetary policy can affect real stock p rices in the short run (e.g Bernanke and Kuttner, 2005), monetary neutrality implies that monetary policy should not affect real stock prices in the long run (Bordo, Dueker and Wheelock, 2007). To understand the relationship between monetary policy and the stock market, we must first understand what monetary policy is. Lamont, Polk and Saa-Requejo (2001), Perez-Quiros and Timmerman (2000) among others use change in market interest rates or official rates as their measures of monetary policy. This measure of monetary policy, however, coincides with changes in business cycle conditions and other relevant economic variables. Christiano, Eichenbaum and Evans (1994) extracted monetary policy as the orthogonalized innovations from VAR models proposed by Campbell (1991) and Campbell and Ammer (1993). Research methodology based on this has shown that the response of US stocks returns to monetary policy shocks based on federal fun rates show that returns of large firms react less strongly than those of small firms (Thorbecke, 1997), that the overall policy for stock returns is quite low ( Patelis, 1997) and that international stock markets react to both to changes in their local mon etary policies and that of the United states ( Conover, Jensen and Johnson ( 1999). Monetary policy shocks that are extracted from structural VAR models or from changes in interest rates using monthly or quarterly data are likely to subject to the endogeneity problem i.e they are unlikely to be purely exogenous ( Ehrmann and Fratzscher, 2004). Another VAR-based method was used by Goto ad Valkanov (2000) to focus on the covariance between inflation and stock returns while Boyd, Jagan and Hu (2001) considered the linkages between policy and stock prices. Their analysis did not focus directly on monetary policy; rather it focused on markets response to employment news (Bernanke and Kuttner, 2005). In their own research paper, Ehrmann and Fratzscher (2004) find that SP 500 shows a strong effect of monetary policy on equity returns, that the effect of monetary policy is stronger in an environment of increased market uncertainty, that that negative surprises ( i.e monetary policy has tightened less and loosened more than expected) has larger effects on the stock market than positive surprises, that small firms are react more to policy shocks than large firms, that firms with low cash flows are affected more by US monetary shocks and that firms with poor ratings are more prone to monetary policy shocks than those with good ratings. They find that firms react more strongly when no change had been expected, when there is a directional change in the monetary policy stance and during periods of high market uncertainty. There has also been cross-sectional dimensions of the effect of monetary policy on the stock markets in literature though few. Hayo and Uhlenbruck (2000), Dedola and Lippi (2000), Peersman and Smets ( 2002), Ganley and Salmon (1997) etc are some economists who have analyzed this and overall, their findings show that the stock prices of firms in cyclical industries, capital-intensive industries and industries that are relatively open to trade are affected more strongly by monetary policy shocks (Ehrmann and Fratzscher, 2004). According to Bernanke and Kuttner (2005), changes in monetary policy are transmitted through the stock market via changes in the values of private portfolios (â‚ ¬Ã…“wealth effectâ‚ ¬?), changes in the cost of capital and by other mechanisms. In their paper, they analyzed the stock markets response to policy actions both in the aggregate and at the level of industrys portfolios and they also tried to understand the reasons for the stock markets response. Their findings show that monetary policy is, for the most part, not directly attributable to policys effects on the real interest rate instead it seems to come either through its effects on expected future excess returns or expected future dividends. While economists commonly associate restrictive/expansive monetary policy with higher/lower levels of economic activity, financial economists discuss various reasons why changes in the discount rate affect stock returns. (Durham, 2000) Changes in the discount rate affect the expectations of corporate profitability ( Waud, 1970) and discrete policy rate changes influence forecasts of market determined interest rates and the equity cost of capital ( Durham, 2000). Modigliani (1971), suggests that a decrease in interest rates boosts stock prices and therefore financial wealth and lifetime resources, which in turn raises consumption through the welfare effect. Mishkin (1977) on the other hand suggests that lower interest rates increase stock prices and therefore decrease the likelihood of financial distress, leading to increased consumer durable expenditure as consumer liquidity concerns abate (Durham, 2000). Tobins q is the equity market value of a firm divided by its book value. It can also be defined as the ratio of the market value of a firms existing shares to the replacement cost of the firms physical assets. Higher stock prices reduce the yield on stocks and reduce the cost of financing investment spending through equity issuance (Bosworth, 1975). Tobins q explains on e of the mechanisms through which movements in stock prices can affect the economy: the wealth channel. The other channels of monetary policy transmission include; the interest rate channel and the exchange rate channel. The wealth channel has the investment effect, wealth effects and balance sheet effects (www.oenb.at/en). Bernanke and Blinder (1992) and Kashyap, Stein and Wilcox (1993) show that a tightening of monetary policy has a very strong impact on firms that highly depend on banks loans to financing their investments as banks reduce their overall supply of credit. Deteriorating market conditions affect firms by also weakening their balance sheets as the present value of collateral falls with rising interest rates and that this effect can be stronger for some firms than for others (Bernanke and Gertler 1989, Kiyotaki and Moore 1997). These two arguments are based on information asymmetries as firms for which more information is publicly available may find it easier to collect loans when credit conditions become tighter (Gertler and Hubbard 1988, Gertler and Gilchrist 1994).Stock returns of small firms generally respond more to monetary policy than those of large firms ( Thorbecke 1997, Perez-Quiros and Timmermmann 2000). Some economists (Sprinkle (1964), Homa and Jaffee (1971), Hamburger and Kochin (1972)) in the early 1970,s alleged that past data on money supply could be used to predict future stock returns. These finding where not in line with the efficient market hypothesis which states that all available information should be reflected in current prices (Fama, 1970) meaning that anticipated information should not have any effect on current stock prices. Most economists believe that stock prices react differently to the anticipated and unanticipated effects of monetary policy ( Maskay, 2007). The Keynesian economists argue that there is a negative relationship between stock prices and money supply whereas real activity theorists argue that the relationship between the two variables is positive (Sellin, 2001). The Keynesian economists believe that a change in money supply or interest rates will affect stock prices only if the change in the money supply alters expectations about future monetary policy while the real activity economists argue that increase in money supply means that money demand is increasing in anticipation of increase in economic activity (Maskay, 2007). Another factor discussed by Sellin (2001) is the risk premium hypothesis proposed by Cornell i.e higher money supply indicates higher money demand and higher money demand suggests increased risk which leads investors to demand higher risk premiums for holding stocks making them less attractive. The real activity and risk premium hypothesis is combined by Bernanke and Kuttner (2005) who argue that the price of a stock is a function of the present value of future returns and the perceived risk in holding the stock. While advocates of the efficient market hypothesis hold that all available information is included in the price of a stock, the opponents argue otherwise and that stock prices can also be affected by unanticipated changes in money (Corrado and Jordan, 2005). The effect of anticipated and unanticipated changes in money supply on stock prices was analyzed by Sorensen (1982) who found out that unanticipated changes in money supply have a larger impact on the stock market than anticipated changes. Bernanke and Kuttner (2005) on the other hand analyze the impact of announced and unannounced changes in the federal funds rate and find that the stock market reacts more to unannounced changes than to announced changes in the federal funds rate which is also in line with the efficient market hypothesis. Studies by Husain and Mahmood (1999) have opposing results. They analyze the relationship between the money supply and changes (long run and short run) in stock market prices and find that chan ges in money supply causes changes in stock prices both in the short run and long run implying that the efficient market hypothesis does not always hold. Maskay(2007) analyzes the relationship between money supply and stock prices. He also seperates money supply into anticipated and unanticipated components and adds consumer confidence, real GDP and unemployment rate as control variables. The result from his analysis shows that there is a positive relationship between changes in the money supply and the stock prices thereby supporting the real activity the theorists. The result from his analysis on the effect of anticipated and unanticipated change in the money supply on stock market prices shows that anticipated changes in money supply matters more than unanticipated changes. This supports the critics of the efficient market hypothesis. According to Cecchetti, et al. (2000), macroeconomic performance can be improved if the central bank increases the short-term nominal interest rate in response to temporary â‚ ¬Ã…“bubble shocksâ‚ ¬? that raise the stock price index above the value implied by economic fundamentals. On the other hand, Bernanke and Gertler (2001) assumed in their research that the Central Bank cannot tell whether an increase in stock prices is driven by a bubble shock or a fundamental shock. This study will analyze both exogenous and endogenous components of the relationship between monetary policy and the stock market i.e the effect of monetary policy on the stock market and the the effect if any of the stock market on monetary policy decisions. This particular analysis will be done using the federal funds rate as a representative of monetary policy. We also follow the methodology used by Maskay (2007) closely as we try to find the effect of money supply on the stock market. Although Maskay used M2 as a measure of money supply, this study will separate money supply into M1 and M2 and analyze their relationship with the stock prices. Following from the theory and review of literature, this paper is aimed at answering the following questions: How do movements in the stock market affect monetary policy decisions on federal funds rates? How does monetary policy affect stock market prices? Do stock market prices react differently to the M1 and M2 components of money supply? RESEARCH METHODOLOGY The effect of stock market prices on monetary policy. In this section, I test for the relationship between monetary policy and stock prices using the Taylor rule. The Taylor rule is a monetary policy rule that stipulates how much the central bank would or should change the nominal interest rate in response to the divergence of actual inflation rates from target inflation rates and of actual GDP from potential GDP. The rule is written as; it = r*t + ÃŽÂ ² (à Ã¢â€š ¬ tâ‚ ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t) +ÃŽÂ ³ (yt Ã…Â ·t)â‚ ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦.. (1) Where; it = target short-term nominal interest rate. r*t = assumed equilibrium real interest rate. à Ã¢â€š ¬t = the observed rate of inflation. à Ã¢â€š ¬*t = the desired rate of inflation. yt = the logarithm of real GDP. Ã…Â ·t = the potential output. But, to analyze the behavior of monetary policy, the following regression equation is estimated; it = ÃŽÂ ± + ÃŽÂ ²Et(à Ã¢â€š ¬ t+iâ‚ ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t+i) +ÃŽÂ ³Et (yt+i+ Ã…Â ·t+i)+ÃŽÂ µt â‚ ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦..(2) Where: Et = the expected value conditional to information available at the time. A good conduct of monetary policy should have ÃŽÂ ² and ÃŽÂ ± each equal to 0.5 as suggested by John Taylor. To conduct our study, we use the following equation; it = ÃŽÂ ± + ÃŽÂ ²Et(à Ã¢â€š ¬ t+iâ‚ ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t+i) +ÃŽÂ ³Et (yt+i+ Ã…Â ·t+i)+ˆ‘Π´k à Ã¢â‚¬ ¦t-k + ÃŽÂ µt ..(3) Because the monetary authorities target variables other than inflation and output deviations from the target (asset prices in this case) thereby making equation (2) mis-specified. A standard Taylor rule is well specified when the monetary authorities target only inflation and output deviations from the target. The addition to this variable is the lagged change in asset prices which is added in order to determine the relationship between monetary policy and stock prices. The data for the CPI (Consumer Price Index), real GDP (Gross Domestic Product) and the federal funds rate are obtained from the IMF Washington website while the data for SP 500 Index are obtained from the Federal Reserve Economic Data (FRED) of the Federal Reserve Bank of St Louis website; www.federalreserve.gov. The effect of monetary policy on stock market prices. In this section, we test whether movements in stock prices are sometimes dependent on monetary policy. This test is carried out by regressing the actual change in federal funds rates upon the SP 500 index. We us the following simple model for this purpose: SP500 = ÃŽÂ ²1 + ÃŽÂ ²2*actual change in federal funs rate + ÃŽÂ ²3*real GDP + ÃŽÂ ²4* unemployment rate. Real GDP and Unemployment rate are added as control variables. The data for real GDP is obtained from IMF, Washington while the data for unemployment rates in obtained from www.federalreserves.gov. We add GDP because it is an important determinant of the stock prices as most industries react to changes in the economy and do well as the economy does well and vice versa i.e they are procyclical in nature. When the GDP is low, the stock prices generally tend to be low, as the companys performance would be worse than before. A direct, positive relationship is expected between stock prices and the GDP. Unemployment rate is also used as a control variable in this model because it is one of the major factors that determines the demand for stocks thereby either driving the stock prices up or down. When the unemployment rate is high, demand for stock reduces as less people can afford to buy them and this subsequently drives down stock prices and vice versa. The unemployment rate is also a proxy for for overall aggregate demand in the economy ( Maskay, 2007) and when it is low, aggregate demand is high. We expect an inverse relationship between the unemployment rates and stock prices. The effect of M1 and M2 components of money supply on stock prices. In this section, we test the relationship between monetary policy and stock prices from the money supply angle of monetary policy. We use the M1 and M2 components of money supply for this analysis. This is done by first testing the relationship between the percentage change in M1 and the stock prices and then testing the relationship between M2 and the stock market. The simple empirical model used for this test is; SP500 = ÃŽÂ ²1 + ÃŽÂ ²2*%ˆâ€  M1 + ÃŽÂ ²3*Real GDP + ÃŽÂ ²4*Unemployment rateâ‚ ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦.. (1) SP500 = ÃŽÂ ² 1+ ÃŽÂ ²2*%ˆâ€  M2 + ÃŽÂ ²*3Real GDP + ÃŽÂ ²4*Unemployment rateâ‚ ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦Ã¢â€š ¬Ã‚ ¦.. (2) Unemployment rate and real GDP are also used here as control variables for the same reasons given above. The data on percentage change in M1 and M2 were obtained from Federal Reserve Economic Data from the website of the Federal Reserve Bank of St. Louis. We were able to get the monthly data of M1 and M2 and then got the quarterly averages to produce the quarterly data. DATA DESCRIPTION In this section, we define and describe the various data used in this study. We used quarterly data from 1990 to 2009. The variables used in this analysis include; The Federal Funds Rate; The federal funds rate is a monetary policy tool used by the Central Bank/Federal reserve of the country to regulate the economy. Economists believe it has an inverse relationship with stock prices as because when there is an upward movement in stock prices above the desirable level, the federal reserve increases (contractionary) the federal funds rate . This leads to a decrease in the amount of money demanded by individuals thereby causing a lower demand for stocks and pushing down stock prices. We obtained data on the federal funds rate from the website of the federal reserve bank of Louisiana. 2. The Consumer Price Index; A consumer price index (CPI) is an index that estimates the average price of consumer goods and services purchased by households. It is used in our study to calculate inflation. We do this using the eviews software (100 ÃÆ'— (cpi â‚ ¬Ã¢â‚¬Å" cpi ( -4)). We obtained the quarterly data on CPI from the website of the International Monetary fund in washington. The CPI has an inverse relationship with monetary policy actions. 3. Real Gross Domestic Product (Real GDP); This can be defined as a measure which adjusts for inflation and reflects the value of all goods and services produced in a given year, expressed in base year prices. Real GDP provides a more accurate figure as it accounts for changes in the price level. The quarterly data on Real GDP is obtained from the website of the International Monetary Fund, Washington. 4. SP 500; It is a capital weighted index of the prices of 500 large-cap common stocks actively traded in the United States. It is believed to have an inverse relationship with monetary policy as an expansionary (interest rate reduction) monetary policy leads to an upward movement of the sp500 index. The quarterly data for the sp500 is obtained from the federal reserve bank of Louisiana. 5. Unemployment Rate; The unemployment rate is used as one of the control variables. It is an important indicator of the wellbeing of an economy. The lower the unemployment rate, the higher the aggregate demand for stock thereby pushing up stock prices. The quarterly data on unemployment rate is obtained from the website of the Federal Reserve Bank of Louisiana. We get the quarterly data by finding quarterly averages from the monthly data provided. 6. Monetary aggregates â‚ ¬Ã¢â‚¬Å" M1 and M2; M1 is a monetary aggregate and it includes the transaction deposits of banks and cash in circulation and all other money equivalents that are easily convertible into cash while includes M1 plus short-term deposits in banks and 24-hour money market funds. Money supply has a positive relationship with stock prices because the higher the money supply, the higher the demand for stock which eventually increases stock prices. We split money supply into M1 and M2 to find out if they have the same relationship with stock prices. The quarterly data on percentage change in monetary aggregates is obtained from the website of the federal reserve bank of Louisiana. We also had to calculate the quarterly averages of the monthly data given. DATA ANALYSIS Model 1: The Taylor rule it = r*t + ÃŽÂ ² (à Ã¢â€š ¬ tâ‚ ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t) +ÃŽÂ ³ (yt â‚ ¬Ã¢â‚¬Å" Ã…Â ·t)+ ÃŽÂ µt Dependent Variable: FED_FUNDS_RATE Method: Least Squares Date: 07/05/10 Time: 20:19 Sample(adjusted): 1991:1 2009:4 Included observations: 76 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. C 3.615513 1.220783 2.961634 0.0041 INFLATION 0.684264 0.156212 4.380348 0.0000 OUTPUT_GAP -1.42E-06 9.83E-07 -1.442803 0.1534 R-squared 0.249642 Mean dependent var 3.860658 Adjusted R-squared 0.229085 S.D. dependent var 1.686064 S.E. of regression 1.480394 Akaike info criterion 3.661167 Sum squared resid 159.9844 Schwarz criterion 3.753170 Log likelihood -136.1244 F-statistic 12.14348 Durbin-Watson stat 0.181830 Prob(F-statistic) 0.000028 The estimation results are; it =3.62 + 0.68(à Ã¢â€š ¬ tâ‚ ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t) â‚ ¬Ã¢â‚¬Å" 1.42 (yt â‚ ¬Ã¢â‚¬Å" Ã…Â ·t) The coefficient associated to inflation is positive, 0.68, but is statistically significant with a p-value of 0.00. The coefficient associated with the output gap is negative (-1.42) and statistically significant. The estimated stabilizing rate of interest (c) is positive (3.61) and statistically significant. An R-squared of 0.25 means that we are only able to explain about 25% of the variability in the interest rate. The augmented taylor rule model: it = ÃŽÂ ± + ÃŽÂ ²Et(à Ã¢â€š ¬ t+iâ‚ ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t+i) +ÃŽÂ ³Et (yt+i+ Ã…Â ·t+i)+ˆ‘Π´1 à Ã¢â‚¬ ¦t-1 + ÃŽÂ µt one lag Dependent Variable: FED_FUNDS_RATE Method: Least Squares Date: 07/05/10 Time: 21:30 Sample(adjusted): 1991:3 2009:4 Included observations: 74 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. C 8.298961 1.280893 6.479044 0.0000 INFLATION_F 0.548999 0.181198 3.029825 0.0034 OUTPUT_GAP_F -9.10E-06 1.51E-06 -6.041926 0.0000 S(-1) 4.24E-05 7.35E-06 5.775767 0.0000 R-squared 0.442430 Mean dependent var 3.809595 Adjusted R-squared 0.418534 S.D. dependent var 1.678852 S.E. of regression 1.280190 Akaike info criterion 3.384432 Sum squared resid 114.7220 Schwarz criterion 3.508976 Log likelihood -121.2240 F-statistic 18.51494 Durbin-Watson stat 0.214690 Prob(F-statistic) 0.000000 Interpretation: The estimated regression is; it = 8.30 + 0.55Et(à Ã¢â€š ¬ t+iâ‚ ¬Ã¢â‚¬Å" à Ã¢â€š ¬*t+i) -9.10Et (yt+i+ Ã…Â ·t+i)+4.24ˆ‘à Ã¢â‚¬ ¦t-k The coefficient associated to expected inflation is positive (0.55) but is statistically significant because it has a p-value of 0f 0.003, the coefficient associated with expected output gap is negative (-9.10) and is statistically significant (p-value = 0.000). The coefficient associated with the change in asset prices (lagged by 1 for better estimation) which is denoted by S (-1) is negative and it is statistically significant therefore we reject the null hypothesis. The measure of goodness of fit (R-square) is 0.44 meaning that we are able to explain about 44% of the variability in the interest rate Our model consistently overestimates the actual interest rate and the residuals do not seem to be independently and identically distributed. We therefore conduct some tests which include: 1. The Jacque-Bera test: This is a statistic that measures the difference of the skewness and kurtosis of the series with those from a normal distribution. By simply looking at the histogram, we can see that the distribution is roughly normal and the jarque-bera statistic of 0.58 shows that it is not statistically significant and we should accept the null hypothesis. The white test: This is used to test whether the errors are heteroskedastic or not. In the presence of heteroskedasticity, OLS estimates are consistent but efficient. White Heteroskedasticity Test: F-statistic 3.846209 Probability 0.000621 Obs*R-squared 25.97528 Probability 0.002062 Test Equation: Dependent Variable: RESID^2 Method: Least Squares Date: 07/06/10 Time: 00:41 Sample: 1991:3 2009:4 Included observations: 74 Variable Coefficient Std. Error t-Statistic Prob. C -35.28961 24.46199 -1.442630 0.1540 INFLATION_F -5.419657 3.008210 -1.801622 0.0763 INFLATION_F^2 0.307231 0.200286 1.533961 0.1300 INFLATION_F*OUTPUT_GAP_F 5.95E-06 2.83E-06 2.105586 0.0392 INFLATION_F*S(-1) -2.78E-05 1.73E-05 -1.603361 0.1138 OUTPUT_GAP_F 9.90E-05 5.34E-05 1.852558 0.0686 OUTPUT_GAP_F^2 -6.19E-11 2.74E-11 -2.257288 0.0274 OUTPUT_GAP_F*S(-1) 3.35E-10 1.43E-10 2.337290 0.0226 S(-1) -0.000309 0.000140 -2.205282 0.0310 S(-1)^2 -7.97E-11 5.33E-10 -0.149679 0.8815 R-squared 0.351017 Mean dependent var 1.550298 Adjusted R-squared 0.259754 S.D. dependent var 1.968439 S.E. of regression 1.693596 Akaike info criterion 4.016674 Sum squared resid 183.5692 Schwarz criterion 4.328034 Log likelihood -138.6169 F-statistic 3.846209 Durbin-Watson stat 0.580160 Prob(F-statistic) 0.000621 According to the two test statistics involved in the regression result, we can say that the distribution is statistically significant so we can reject null hypothesis. The Durbin-Watson test: This is used to test for serial correlation. Autocorrelated residuals means that OLS is no longer best, linear, unbiased estimators and that the standard errors computed using the OLS formula are not correct. The Durbin-Watson statistic of 0.214690 shows that there is positive serial correlation as DW Model 2: SP500 = ÃŽÂ ²1 + ÃŽÂ ²2 federal funds rate + ÃŽÂ ²3real GDP + ÃŽÂ ²4unemployment rate. The aim of this model is to determine if the federal funds rate has any impact on the stock market. Real GDP and unemployment rate are used as control variables for reasons given in the research methodology. Dependent Variable: SP500 Method: Least Squares Date: 07/06/10 Time: 01:38 Sample: 1990:1 2009:4 Included observations: 80 Variable Coefficient Std. Error t-Statistic Prob. C -115.7008 222.2313 -0.520632 0.6041 FED_FUNDS_RATE 0.990301 12.96436 0.076386 0.9393 REAL_GDP01 0.159538 0.010327 15.44916 0.0000 UNEMPLOYMENT_RATE -119.5674 17.42177 -6.863101 0.0000 R-squared 0.872734 Mean dependent var 924.0339 Adjusted R-squared 0.867710 S.D. dependent var 378.2205 S.E. of regression 137.5651 Akaike info criterion 12.73478 Sum squared resid 1438237. Schwarz criterion 12.85388 Log likelihood -505.3912 F-statistic 173.7244 Durbin-Watson stat 0.350064 Prob(F-statistic) 0.000000 Interpretation: The estimated regression is: sp500 =-115.78 + 0.99*actual change in federal funds rate + 0.16*real GDP â‚ ¬Ã¢â‚¬Å" 119.57* unemployment rate. The coefficient associated with the federal funds rate is negative and is not statistically significant. The coefficient associated with the real GDP is positive and is statistically significant while the coefficient associate

Alan Turing :: essays research papers

Biography: Alan Mathison Turing   Ã‚  Ã‚  Ã‚  Ã‚  Alan Mathison Turing was surrounded by enigma, not only did he break many cryptic codes but he also lived a mysterious life. Turing was born on June 23, 1912 in Paddington, London to Julius Mathison and Ethel Sara Turing. Turing’s father, Julius, was an officer in the British administration in India when he decided that his son would be raised in England.   Ã‚  Ã‚  Ã‚  Ã‚  Turing had an older brother named John, who also had a childhood determined by the demands of the class and the exile in India of his parents. Alan and his older brother lived among various English foster homes while they were children until 1926, when their father retired from India. While raised in foster homes, Alan was not encouraged nor shown any support, yet through his own curiosity and imagination he found a deep underlying passion for science, primarily in chemistry experiments. Later he went on to other areas of science.   Ã‚  Ã‚  Ã‚  Ã‚  Alan became more and more enthralled with science, and his mother worried that he would not be accepted to Sherbourne, an English public school, because he was so much of a scientific specialist. But in 1926, Alan was granted admittance to the public school. However, after a short while the Headmaster reported to his mother that if Alan was solely a scientific specialist, that he was wasting his time. Many other teachers also felt the same was as the Headmaster.   Ã‚  Ã‚  Ã‚  Ã‚  In 1928, Turing became interested in relativity, and it was at this time that Alan met Christopher Morcom, and everything changed for him. And it was Morcom’s death that prompted Turing to get further involved and motivated to do what Morcom could not. Turing questioned how the human mind was embodied in matter, and whether this matter was released after death. This led him to study twentieth century physics where Alan began to question whether quantum mechanical theory affected the state and his questions of mind and matter.   Ã‚  Ã‚  Ã‚  Ã‚  In 1931, Turing won an entrance to King’s college in Cambridge on scholarship. It was here that Turing was able to express his ideas freely. In 1932 Turing read Con Neumann’s work on the logical foundations of Quantum Mechanics. It was also here at Cambridge that Turing’s homosexuality became a big part of his identity. Turing went on to receive his degree in 1934 followed by a M.A. degree from King’s college in 1935, and a Smith prize in 1936 for his work on probability theory.

Essay --

Imagine you are in the beginning 17th century England, you are starting to feel as if you disagree with the Kings ideals which are very different from your own. You would like to be able to express your beliefs and also live somewhere that has prosperity and a great future for you and your family. The only problem is that your beliefs and ideals aren’t supported where you live and you feel isolated and are looking for somewhere new to be free. In today’s societies we have so many beliefs and very different ways of thinking that we differ greatly from others. We are accepted by others with the same beliefs and also have the freedom to express whichever belief we have. This wasn’t so easy to achieve. Someone somewhere had to do something, sacrifice their life, challenge the norm, in order to have the freedom to choose that we have today. In the United States of America we can; for the most part; say and do as we please. We can follow any religion or no religion as we please. If we don’t agree with our President or policies we have a voice. This foundation was laid on our Ancestors pre say that made a voyage, fought famine, died by diseases and conflicts among the natives of the land to find a land where you can be free of a Kings rule and start their own rules and ways of life. With the new World the possibilities are endless because you can start over a new life and civilization. I New England colonies of British America were located in New Hampshire, Vermont,   Maine, Massachusetts, Connecticut, and Rhode Island. these all later on being part of the 13 colonies  including the middle and southern colonies. The founders of these New England colonies had  different goals from the Jamestown settlers. They left England for all differe... ...t they grew rye, corn, pumpkins, squash, beans, peas, carrots and turnips instead. They  also owned sheep, pigs, chickens, and cows. This was a largely farm centered life. Although a huge improvement from a feudal society. The early 1600’s were very crucial to the new colonies. Many waves of settlers were making their way across the Atlantic risking their lives, catching various disease, leaving their family, starting a new life with their families, risking exile from the mother land. All this in order for no longer having any religious persecution or a better life per say. These settlers wanted something outside of the mother country and to explore a new world. This had to be exciting and freighting. Many risks were taken but well worth it. They were the first crusaders in a lot of the freedoms we have today. Without them we wouldn’t have the America we have today.

Affirmative Action Essay -- essays papers

Affirmative Action Affirmation Action In Today Society: Myths and Facts As America nears the end of the twentieth century, we still face many lingering problems that stand unresolved. One of the most pressing and difficult problems is that of human relations, or to many, the trigger word race relations. For over 225 years America has been trying to fulfill the promise of the founders of this nation that â€Å"All Men Are Created Equal†, yet we still see institutionalized injustices and discrimination. Therefore, this paper attempts to look at one controversial issue that was implemented to correct previous human relation injustices of our nations. This issue is Affirmative Action. To examine affirmation action, this paper looks at the origin of affirmative action programs, U.S. Supreme Court affirmative action debate, employment and affirmative action, and finally myths and facts about affirmative action. I hope that through this paper these issues can be presented to gain a better understanding of affirmative action in today’s society. Affirmative action is a policy assigned to increase representation of women and minorities in business, educational institutions and government. It origin lies in the legislation that came out of the civil right movement of the 1960’s. The Civil Right Act of 1964 was passed, which forbids discrimination unions, employment agencies, and business employing more than 25 employees. However, the tasks for enforcement of this law had been immense and extremely difficult. In an endeavor to redress the systematic discriminations of the past, especially against blacks, remedial programs often called "affirmative action" were undertaken by educational institutions, unions, and governments. These programs required a percentage of minorities – group (racial minority and women) representation goal and a timetable for accomplishment of that goal. The basic premise was to level to playing ground for minorities. Almost, immediately from its inception affirmative action program has been controversy. The process of minority goals and percentages created a powerful† â€Å"white backlash†. Critics charge that the ratios are not goals but quotas and that affirmative action programs really call for reverse discrimination (discrimination against white males). Resolution of this conflict is difficult. While it is true that some minority group ... ... doors by themselves. In a perfect world program such, as Affirmative Actions would not be needed. Personnel decisions would be basis upon each individual’s abilities and qualifications, without regards to gender or ethnic group. However, we are far from a perfect world. As long as we have prejudices, hatred, and discrimination in society, programs of Affirmative Action will be necessary. Bibliography: Coleman, James William, and Cressey, Donald R. Social Problem. 5th ed. Harper Collins College Publishers. New York. 1993. 188-190 Levenson, Alec R., and Williams, Darrell L. Interracial America: Opposing View, â€Å" Affirmative Action Combat Unintentional Racism†, Greenhaven Press Inc., San Diego, 1996, 154-158 Bender, David and Leone, Bruno. Work: Opposing Viewpoints, â€Å"Affirmative Action Promotes Equality†, Greenhaven Press Inc., San Diego, 168-176 Collier’s Encyclopedia. CD-ROM. Sierra Home, 1998 Reflective in Race Relation, Online, www. Elibrary.com, 18 Feb. 1999 Coleman, Jonathan. Long Way To Go: Black & White In America, Atlantic Monthly Press, New York, 1997 Carter, Stephen L., Reflections of an Affirmative Action Baby, Basic Books, New York,

Directional Imbalances in Supply Chain

Imbalance is a concept that suggests a lack of stability, and in relation to supply chain it is one type of instability that if occurs would have substantial costs on organizations. It is a mismatch that happens along the same corridor causing large numbers of empty containers to be shipped back to the source. That means â€Å"large surplus of containers at one side and a deficit of containers on another. †1 Studies show that â€Å"the situation is the worst in the corridor between Asia and USA, there is almost three times more maritime freight going from Asia to USA that the other way around. 1 This phenomenon has several outcomes, from forgone revenue to the change of prices to the competition between modes of transport. On the other hand there are several factors that affect it. Seasonal variations for instance, that comes about due to the lack of demand for certain seasonal goods. Let’s take oil transport as an example; the oil tankers are specifically made for the transport of oil. These containers cannot be refilled with any other type of good. The shipping industry regarding containerized goods has to deal with several types of cargo which makes it easier to deal with imbalances by creating solutions and routes to outcome this imbalance. It is a different thing with oil shipping as it is imported from oil rich countries to industrial countries who consume oil. That means that the oil containers goes one way full and comes back empty. Shipment companies have to cope with these imbalances by looking at the situation as a whole. The solution comes from the fact that they deal with several ports and more than one industry of goods. Adjusting prices is one strategy, making exports from a surplus port less costly than imports to the same port and vice versa. Another is creating collapsible shipping container. This ingenious idea developed by a Dutch shipping container manufacturer, Cargoshell. It is an â€Å"energy-saving solution to empty shipping container. † 2 Its benefits outgrow the financial aspect as â€Å"CO2 emission is reduced drastically as each is made of a composite material that weighs 25% less than standard shipping containers. 2 In the late 1960’s, shipping giant Sealand responded with the introduction of a round the world liner service which was not very successful. The collapsible containers, although as they may seem to solve a lot of this problem, has not yet been introduced commercially and they render some issues with transport and handling aspects. This means that it is inevitable to have some ships leave ports empty and it is just the concern of reducing that number as much as possible that matters.