...FEMA and Federalism Deanne Norgaard POL 120 - American National Government May 26, 2014 Season Hoard FEMA and Federalism The Federal Emergency Management Agency (FEMA) is a federal program designed to respond to natural emergencies and disasters all over our country. Its initial catalyst is a governor’s declaration of a disaster area. So when recent tornadoes touched down and cut a path of destruction through Illinois, particularly in the towns of Washington and Gifford, the governor made his declaration and FEMA was expected to spring into action. Upon examination however, FEMA ruled that despite seven fatalities and millions of dollars of damage, the area did not qualify for assistance. Both the Illinois governor and U.S. Senators were stunned and the state was left to respond to the emergency themselves. What is this federal policy and is it better than just having each state respond to its own issues? The qualifications to receive FEMA assistance are determined by the following: the amount and type of damage (major damage and number of homes destroyed); impact on the infrastructure of affected areas or critical facilities; imminent threats to public health and safety; impacts to essential government services and functions; unique capability of Federal government; dispersion or concentration of damage; level of insurance coverage in place for homeowners and public facilities; available assistance from other (Federal, state, local, voluntary organizations); and...
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...as the second largest pharmacy chain, in the United States, with more than 7,600 stores, and is the second largest US pharmacy based on total prescription revenue. II. Purpose To determine if there are excess returns on CVS’ stock. III. Time period of data Monthly Fama/French Benchmark Return(SMB, HML, Rm-Rf), Monthly risk-free rate and Monthly price of CVS from Oct 2005 to Oct 2015. IV. Test of the correlation The correlation matrix for the excess return variables (SMB, HML, Rcvs-Rf, Rm-Rf) | Rm-Rf | SMB | HML | Rcvs-Rf | Rm-Rf | 1 | | | | SMB | 0.394264 | 1 | | | HML | 0.424707 | 0.305891 | 1 | | Rcvs-Rf | 0.597283 | 0.305935 | 0.197747 | 1 | Analysis: V. Serial correlation tests Method: Durbin-Watson statistic Procedure: first, we use the formula DW=t=2Tεt-εt-12t=1Tεt2 to calculate the DW value. It is 2.2161. It is higher than 2.0 so we use (4-DW=1.7839) to compare with the criteria. Then we find that the critical values dl and du for 121 observations when there is one independent variable are 1.65 and 1.69. Because the DW statistic of 1.7839 for the regression is higher than du, we can’t reject the null hypothesis of no serial correlation. Conclusion: There is no serial correlation on the CAPM model. VI. CAPM model: Rcvs-Rf=α+β(Rm-Rf) 1. Model The Rcvs-Rf represents the excess returns on CVS. The Rm-Rf represents the excess return on market. The α represents the potential value addition of a fund manager. The...
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...(December 2012) In statistics, the Durbin–Watson statistic is a test statistic used to detect the presence of autocorrelation (a relationship between values separated from each other by a given time lag) in the residuals (prediction errors) from a regression analysis. It is named after James Durbin and Geoffrey Watson. The small sample distribution of this ratio was derived by John von Neumann (von Neumann, 1941). Durbin and Watson (1950, 1951) applied this statistic to the residuals from least squares regressions, and developed bounds tests for the null hypothesis that the errors are serially uncorrelated against the alternative that they follow a first order autoregressive process. Later, John Denis Sargan and Alok Bhargava developed several von Neumann–Durbin–Watson type test statistics for the null hypothesis that the errors on a regression model follow a process with a unit root against the alternative hypothesis that the errors follow a stationary first order autoregression (Sargan and Bhargava, 1983). Note that the distribution of this test statistic does not depend on the estimated regression coefficients and the variance of the errors.[1] Contents [hide] 1 Computing and interpreting the Durbin–Watson statistic 2 Durbin h-statistic 3 Durbin–Watson test for panel data 4 Implementations in statistics packages 5 See also 6 Notes 7 References 8 External links Computing and interpreting the Durbin–Watson statistic[edit] If et is the...
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...work has continued to grace the homes of many over the years. Much of her writing was influenced by the events of her life and her experiences. Her career as a writer started at a young age and continued to grow until the end of her life. Alcott wrote a variety of pieces and for a wide audience. She was a multitalented woman whose writing was one of few steady aspects of her life. Louisa May Alcott was a talented writer who led an interesting life. Louisa May Alcott was born on November 29, 1832 (Durbin). She was born in Germantown, Pennsylvania to Amos Bronson Alcott and Abigail May Alcott (Durbin). Louisa was one of four daughters born to the Alcotts. She had an older sister, named Anna, and two younger sisters, named Lizzie and May (Durbin). The Alcotts moved somewhat frequently throughout Louisa’s life, and many of their moves were due to her father’s job or other familial needs. They first moved to Boston for her father’s career as an educator and then to Concord (Durbin). Louisa May Alcott received the beginnings of her education in Boston and Concord, although she never received any formal education. Most of Alcott’s learning came from her father who was an “idealistic philosopher” and teacher (Louisa May Alcott). “Her father believed strongly in the values of high moral principles, self-reliance, reading, and philosophical discussion”, and he taught many of these things to his daughters (Louisa May Alcott). When the Alcotts were living in Concord, Louisa met some...
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...S.E. of regression | 0.261342 | Akaike info criterion | 0.191731 | Sum squared resid | 5.122486 | Schwarz criterion | 0.282374 | Log likelihood | -4.477517 | Hannan-Quinn criter. | 0.228017 | F-statistic | 19.10538 | Durbin-Watson stat | 1.628379 | Prob(F-statistic) | 0.000000 | | | | | | | | | | | | | | | | | | | Dependent Variable: SUM | | | Method: Least Squares | | | Date: 04/10/13 Time: 16:46 | | | Sample (adjusted): 1 56 | | | Included observations: 56 after adjustments | | | | | | | | | | | | Variable | Coefficient | Std. Error | t-Statistic | Prob. | | | | | | | | | | | PERIOD | 0.161968 | 0.069930 | 2.316123 | 0.0245 | SERVICEEMP | 0.011298 | 0.002568 | 4.399456 | 0.0001 | C | -0.342361 | 0.145535 | -2.352436 | 0.0224 | | | | | | | | | | | R-squared | 0.392183 | Mean dependent var | 0.391715 | Adjusted R-squared | 0.369246 | S.D. dependent var | 0.313554 | S.E. of regression | 0.249024 | Akaike info criterion | 0.109550 | Sum squared resid | 3.286693 | Schwarz criterion | 0.218051 | Log likelihood | -0.067402 | Hannan-Quinn criter. | 0.151616 | F-statistic | 17.09863 | Durbin-Watson stat |...
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...to address global issue specifically extreme poverty is to provide access to clean water and sanitation to the poor. Furthermore, access to clean water and sanitation will protect people from diseases such as Ebola and Cholera. United States, which the key global leader in funding for water and sanitation programs, participates in an investment project to end poverty. By increasing funding for water and sanitation programs, United States believe that they can help people to stay healthy and decrease the chance of having Ebola and Cholera diseases. In addition, by expanding interest in critical water and sanitation programs, the United States can keep on exhibiting its leadership abroad. Website : http://www.cnn.com/2015/04/16/opinions/durbin-wentz-water-key-solving-poverty/index.html The article "Why water is key to beating poverty" was published in a website named CNN on April 16, 2015. According to Wikipedia, "The Cable News Network (CNN) is an American basic cable and satellite television channel that is owned by the Turner Broadcasting System division of Time Warner." In addition, CNN was the first all-news television channel in the United States. CNN.com relies heavily on global news that features the latest multimedia...
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...ECONOMETRIC ANALYSIS. INDEX: - Introduction..................................................................................3 -Background....................................................................................8 -Empirical Analysis.........................................................................9 -Conclusion.....................................................................................31 -Bibliography..................................................................................31 * INTRODUCTION: For many years it has tried to explain and predict economic phenomena. In the present work we destructive her to perform an econometric study of the function of the number of travelers who occupy tourist accommodation in Andalusia. The data required for such analysis have been collected from the database of the Institute of statistics and cartography of Andalusia, for easy access through the official website (http://www.juntadeandalucia.es/institutodeestadisticaycartografia/index.html). The National Statistical Institute(NSI) sends every month to the Institute of statistics of Andalusia provisional results which offers survey during the previous month in the eight Andalusian provinces. The survey is exhaustive in all provinces, except in some categories where sampling procedures are performed. The estimates are published disaggregated by categories up to the level that allows the maintenance of statistical confidentiality. The highest...
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...Section 1: Interpersonal Skills for Leaders Studies show that many leaders’ failures are attributable to interpersonal skills such as building relationships, leading teams, developing a positive work environment, effective communication and inspiring trust (Eblin, 2011). These skills become even more important when the basic element of the business is the person. It is evident that leaders must master these skill sets to be successful as a leader in their industry. RELATIONSHIP MANAGEMENT: Interpersonal Competencies Must Haves As a part of the four key factors in emotional intelligence, relationship management involves the “soft” or personal side of management that has a direct impact on the aspects of the business (Durbin, 2010). “Interpersonal skills are goal-directed behaviors used in face-to-face interactions, which are effective in bringing about a desired state of affairs” (Hayes, 1991, p14). Following is a closer look at three critical interpersonal competencies that a successful leader must have. Communication Skills Listening – Nichols and Stephens (1957) estimate that 45 percent of all communication is spent listening while far less is spent speaking. Communication is essential to the success leaders and the most influential portion is listening but listening is more than just hearing. Listening is the active engagement of communication to search for complete understand of the meaning of another’s message (Hayes, 1991). To be a superior listener one must...
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...Part III: Debit Card The debit cards have been out in the market since 1960s. They helped to change the way that people used money and bank accounts. Debit cards are frequently used to pay for purchasing at stores or other locations all over the world. They are also worked by debiting money from owners’ checking accounts. For many people in the United States, debit cards have taken the place of cash and checks. However, debit cards are still a relatively new banking tool. The debit card rules has been changed over time since debit cards were out in the market. There are two main changes that attract people’s attention in recent two years. Electronic Fund Transfer Act: New Overdraft Rules According to Board of Governors of the Federal Reserve System, new rules give debit card users additional options regarding overdrafts. An overdraft usually occurs when a debit card user make a purchase but don’t have enough money in the accounts to pay for it. Banks will cover the costs when card users become overdrawn by charging a fee (Board of Governors of the Federal Reserve System [BGFRS], 2010). Banks used to automatically enroll customers in standard overdraft practices. Banks will cover customers’ transaction for a flat fee around $20 to $30 every time customers overdraw their accounts. Banks also offer an overdraft protection plan that provides a link to users’ saving accounts to cover transactions by charge less expensive fees than standard overdraft practices (BGFRS, 2010). The...
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...FILE='\\soliscom.uu.nl \uu\Users\3530647 \1\Capm spss.sav '. DATASET NAME DataSet1 WINDOW=FRONT. NEW FILE. DATASET NAME DataSet2 WINDOW=FRONT. REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS CI(95) R ANOVA /CRITERIA =PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT mcdonaldrp /METHOD=ENTER sp500rp /RESIDUALS DURBIN /SAVE RESID. Regression [DataSet2] Descriptive Statistics Mean Std. Deviation N mcdonaldrp -,0017 ,01145 502 sp500rp -,0027 ,00840 502 Correlations mcdonaldrp Pearson Correlation sp500rp 1,000 ,495 ,495 1,000 . ,000 mcdonaldrp sp500rp Sig. (1-tailed) mcdonaldrp sp500rp ,000 . mcdonaldrp 502 502 sp500rp N 502 502 Variables Entered/Removeda Model 1 Variables Entered Variables Removed b sp500rp Method . Enter a. Dependent Variable: mcdonaldrp b. All requested variables entered. Page 1 b. All requested variables entered. Model Summaryb R Model 1 Adjusted R Square R Square a ,495 ,245 Std. Error of the Estimate ,243 Durbin-Watson ,00996 2,049 a. Predictors: (Constant), sp500rp b. Dependent Variable: mcdonaldrp ANOVAa Sum of Squares Model 1 df Mean Square Regression ,016 1 ,016 Residual ,050 500 ,066 Sig. ,000b ,000 Total F 501 162,223 a. Dependent Variable: mcdonaldrp b. Predictors: (Constant)...
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... | | Sample (adjusted): 1/04/2005 11/02/2010 | | Included observations: 1449 after adjustments | | | | | | | | | | | | Coefficient | Std. Error | t-Statistic | Prob. | | | | | | | | | | | LOG_RETURNS(-1) | -0.944031 | 0.026247 | -35.96681 | 0.0000 | C | 0.000692 | 0.000484 | 1.429639 | 0.1530 | | | | | | | | | | | R-squared | 0.472016 | Mean dependent var | 1.64E-07 | Adjusted R-squared | 0.471651 | S.D. dependent var | 0.025333 | S.E. of regression | 0.018414 | Akaike info criterion | -5.150009 | Sum squared resid | 0.490653 | Schwarz criterion | -5.142723 | Log likelihood | 3733.181 | Hannan-Quinn criter. | -5.147290 | F-statistic | 1293.611 | Durbin-Watson stat | 1.996888 | Prob(F-statistic) | 0.000000 | | | | | | | | | | | | | | PHILLIP Peron test for Log return series Null Hypothesis: LOG_RETURNS has a unit root | | Exogenous: Constant | | | Bandwidth: 11...
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...address included) that Sophia received in March 2013. Karl announced that he planned to claim both Ryan and Isabella as dependents on his own tax return. Ryan (age 19 in December 2012) graduated from high school on May 6, 2012, and plans to start college in 2014. He earned $8,000 in 2012 and $17,000 in 2013. Isabella’s income is negligible and originates from nontaxable sources (e.g., Social Security benefits and interest on municipal bonds). For tax years 2012, Sophia filed her Federal income tax return as married filing separated and claimed no exemptions for dependents. She has not yet filed for 2013. Being somewhat perplexed with her situation, she comes to you for advice in early March 2014. Memo - Issue Sophia Durbin is a part of a household that she provides over half the support for her son, Ryan, and mother-in-law, Isabella. Sophia’s husband, Karl left abruptly in March 2012. For tax year 2012, Sophia received notification in March 2013 via post card from Karl that he planned to claim Ryan and Isabella as dependents. Sophia filed Federal income tax return under married filing separately and did not claim any exemptions for dependents. Isabella receives income from nontaxable sources, social security and municipal bonds. (The textbook does not clearly state when this started, it’s assumed it covers both 2012 and 2013 tax years.) Ryan graduated high school May 6, 2012 and will be attending college starting in 2014. He turned 19 in December...
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...Modelación de mecanismos de transmisión monetaria en México Período 1998-‐2012 Descripción de las series de tiempo usadas • Se usaron los datos obtenidos de las bases del Banco de México y del INEGI tomando como referencia el período de 1998-‐2012 en formato trimestral debido a que la referencia con menos información (tasa de interés) solamente abarcaba esos períodos Modelos utilizados Se realizaron comparaciones entre los modelos fabricados mediante el criterio de Mínimos Cuadrados Ordinarios (MCO) y vectores auto-‐regresivos (Modelos VAR) para evaluar el grado de efectividad de cada uno de ellos en su capacidad para predecir el comportamiento de las distintas variables. Modelo MCO Y= aX + b Modelo VAR ������������ = ������������ + ������1������������ − 1 + ������2������������ − 2 + ⋯ + ������������������������ − ������ en donde Yt , Yt-‐1,..,Yt-‐p representa una variable que depende de sí misma...
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...| | Date: 05/03/11 Time: 10:25 | | | Sample: 1952 1982 | | | Included observations: 29 | | | | | | | | | | | | | Variable | Coefficient | Std. Error | t-Statistic | Prob. | | | | | | | | | | | C | -1.074148 | 0.236263 | -4.546402 | 0.0001 | T | -0.023862 | 0.013049 | -1.828664 | 0.0785 | | | | | | | | | | | R-squared | 0.110203 | Mean dependent var | -1.455117 | Adjusted R-squared | 0.077248 | S.D. dependent var | 0.624716 | S.E. of regression | 0.600102 | Akaike info criterion | 1.883038 | Sum squared resid | 9.723306 | Schwarz criterion | 1.977334 | Log likelihood | -25.30405 | Hannan-Quinn criter. | 1.912570 | F-statistic | 3.344012 | Durbin-Watson stat | 2.469136 | Prob(F-statistic) | 0.078518 | | | | | | | | | | | | | | | | | | | | | | | | Signifikansnivået vurderes på bakgrunn av dette: “Alle forklaringsvariablene er signifikante fordi p-verdiene deres er mindre enn signifikansnivået på 5%” Beholder hvis p-verdien er under signifikansnivået. Alternativ 2: price c t Dependent Variable: PRICE | | | Method: Least Squares | | | Date: 05/03/11 Time: 10:27 | | | Sample: 1952 1982 | | | Included observations: 29 | | | | | | | | | | | | | Variable | Coefficient | Std. Error | t-Statistic | Prob. | | | | | | | | | | | C | 0.418624 | 0.076877 | 5.445350 | 0.0000 | T | -0.008360 | 0.004246...
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...Probability, Statistics, and Forecasting OPRE 433 Fall 2013 Regression Report Xie Gehui (gxx24@case.edu) Dec 2, 2013 I. Introduction The data set given contains more than one independent variable, so the target of our regression analysis is to build an appropriate multiple regression model. To realize this target, we have to build a multiple linear regression model to test the regression assumptions: model appropriateness, constant variance, independence, and normality. Certainly we need to modify the data set or the model itself to satisfy these assumptions, and at last get the model acceptable. In the original data set that we are going to deal with in this report, there are 20,640 observations of 8 explanatory variables labeled X1, X2, X3, X4, X5, X6, X7, X8 and 1 dependent variable labeled Y. All of the 9 variables are continuous. II. Method of analysis To check the model appropriateness assumption, we need to make sure the functional form is correct. The residual plot will show the pattern suggesting the form of an appropriate model. To check the validity of the constant variance assumption, we need to examine residual plots. A residual plot with a horizontal band appearance suggests that the spread of the error terms around 0 is not changing much as the horizontal plot value increases. Such a plot tells us that the constant variance assumption approximately holds. To check the independence assumption, we need to detect if any positive autocorrelation...
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