Analysis Of Gdp Determinants Statistics Economics Essay

Analysis Of Gdp Determinants Statistics Economics Essay The aim of our report is to identify the factors which affects GDP for any country. In our report we are analyzing such factors in relation to Indias GDP. The report will be dealing with regression analysis, hypothesis testing, mean, median, mode etc of such factors which are independent variables and their affect on GDP which is a dependent variable. 2. Introduction: The report revolves around an exploratory study. It includes analyzing the statistical data of Indias GDP and other factors like Employment to population ratio, FDI, population for the past 20 years. Our aim is to identify the dependence of above mentioned factors on GDP of India and results of the regression analysis. Here we take GDP as the dependent variable and other three factors as the independent variables. Before getting into analysis we look into the substitute measures of each variable used in the report for analyzing regression, hypothesis testing and calculating the mean and median values. GDP Lending Interest Rates FDI Population Employment to population ratio 2.1) GDP: GDP forms the dependent variable of our research study. GDP is an indicator of overall economic welfare of a country. It is the sum total of the final goods and services produced within the borders of the nation. In other words, summing up the consumption, government expenditure, investments and net exports results in the GDP growth rate of a country. It is considered to be a very important element as it helps in estimating the health of countrys economy. Calculating the GDP is not an easy task because of which they are left to be calculated by the economists. GDP growth rate of an economy is dependent on various factors like FDI, population to employment ratio, lending interest rate, population etc. Governments closely watch out the GDP as it measures the economic performance of the country. If GDP rises it means the economy has grown and vice versa. GDP is criticized on various grounds like it does not talks about the spending power, distribution of income or well being of countrys inhabitant. Formula of calculating GDP: GDP=C+I+G+(X-M) Where, C=consumption I=investment G=government expenditure (X-M) =Net Exports The independent variables (Population, Lending Interest rates, FDI, Employment to population ratio etc ) that we are using in the research analysis affect each of these above mentioned components. The data related to GDP has been shown in the appendix 9.1 2.2 ) Employment to population ratio: It is taken as an independent variable in our study. We attempt to measure the impact of this ratio on GDP growth in India. Employment to population ratio basically means the ratio of the total working age of the labor force employed over total population. Following formula is used in calculating the ratio: Employment to population ratio= Employed Persons/ Total non-institutionalized civilian population *100 This ratio does not bear underrating problems relating to unemployed persons and other discouraged workers that enter or exit the labor force. The data of employment ratio is shown in appendix 9.1 2.3) FDI: Foreign direct investment is an independent variable in our research report. We try finding out the impact of FDI on GDP growth rate. In simple words it is an investment made by one company in a given country in another company based or set up in another country. FDI has been a major source of managerial skills, technology, capital and access to market desired for sustained economic development and growth in the recent past. All the Countries are involved in inviting more and more of foreign direct investment to come and invest in their country resulting in rapid economic growth. FDI is considered to be an important factor in facilitating growth, however, it will result in growth only if the inflows are carefully managed and invested. The related data is included in the appendix 9.1 for the past 20 years . All the inferences related to FDI has been drawn on the basis of such data. 2.4) Population: The growth of population has always been a debating issue. There is no conclusion as to it is negative or positive for growth of an economy. Population and economic growth are interrelated to each other in a way that, population increases due to high economic growth leading to early marriages and hiking birth rates and checking on the mortality rates by providing healthy environment to the citizens. Higher population also depresses economic growth through diminishing returns. (Becker, Glaeser, and Murphy 1999, p. 145) In our study we attempt to study the impact of population on economic growth which is expressed as the real GDP per capita. The data regarding population for past 20 years has been included in the appendix 9.1. All the analysis related to it has been done on the basis of such data and various results has been drawn on such basis. 2.5) Lending Interest Rate: Lending Interest rate is the amount of interest charged by a lender from a borrower in case of loan being offered. A countrys real GDP and interest rates are interlinked in a variety of means. They have a direct relationship, i.e., high lending rate results in high growth for the economy. The dependence of GDP on Lending Interest Rate can be studied in the analysis of the study. The related data regarding interest rate is included in appendix 9.1 3. Tools used for research study: The statistical tools used in our research study with the objective of finding the dependence of GDP on various independent variables like, Population, Lending interest rates, FDI, Employment to population ratio are Regression Analysis, Mean, Median, Mode, Hypothesis Testing Steps involved in analysis: Our first step was to scrutinize and identify the factors responsible for GDP growth of a nation. Next, we tried locating data of the identified factors for the past 20 years. Than we tried finding relationship of various factors with the GDP of a nation. The data was than constructed and summarised in a proper manner to conduct regression analysis. SPSS software was used to conduct the regression analysis and hypothesis testing. All the data and factors collected are using the secondary sources, i.e., Internet and Journals. 4. Data Description: N i.e. the number of observations for our research is 20. There are two types of data: Qualitative Quantitative Qualitative data deals with categorical measurement and is not measured in terms of numeric values. For our study the qualitative factors can be like Market Risk, Business Confidence etc, which affects the GDP but due to their qualitative nature we overlooked them of the study. Quantitative data deals with the numerical measurement of the database. Relating to our study, the quantitative data factors are Population, GDP, Lending interest rates, FDI etc. We have limited our research taking in account only the quantitative data. Data can also be time series or cross sectional: Cross sectional data is the data for a given point of time analyzing the differences among the subjects. Whereas time series data is concerned with the data over a spread time course In our report we are using time-series data, for 20 years i.e. from 1991 to 2010. Regression Analysis: Regression Analysis means scrutinizing the relationship between a dependent and independent variable. After conducting an analysis, regression statistics is helpful in identifying the dependent variable when the independent variables are unknown. Dependent Variable- GDP growth of India Independent variable- FDI, Employment to Population ratio and Real Interest Rate The regression equation is: Y=b1X1+b2X2+.+E In the above equation- Y= dependent variable X1, X2 =independent variables b1, b2 =coefficients describing effect of independent variables on the dependent variables E=error term In our study, the equation looks like, GDP=b1F1+b2F2+b3F3++bnfn Where, F1 to Fn= independent variable factors Hypothesis testing: Hypothesis testing is the test of significance wherein we identify the likelihood that an assumption is true, and at what likelihood we would hold the assumption as true. The assumption made is referred as the Null hypothesis and is denoted by H0 and an alternate hypothesis is defined known as an Alternative Hypothesis and is denoted by Ha. The rationale behind this test is to hold null hypothesis to be true and then performing the study on the argument in question. Once the hypothesis is defined and data is collected and constructed, following steps of hypothesis are followed: A critical region of size alpha is determined using the sample distribution of the test statistics Using the sample data, identify the values of test statistics The last step is confirming that the value of test statistics falls under the critical region defined; if no, we accept the null in favour of the alternative hypothesis and if yes, we reject the null hypothesis. 5). Variables considered as independent in hypothesis and doing regression analysis In doing the analysis of various factors affecting GDP growth some of the factors which is been considered as the variables are FDI, Employment ratio, Population and Lending interest rate as they impact directly in the growth of GDP for any country. The factors are denoted by r and following relation between the factors as stated above and the regression can be explained under 5.1) Population (H1) Although increase in population has a negative impact on the economy of any country. However, such increase allows availability of labor at cheap rates which attracts the companies or firms to make more investment in the form of Foreign direct investment or FIIs that helps to give upward thrust in GDP. 5.2) Foreign Direct Investment(H2) It can be argued on the grounds of proven facts that Foreign Direct Investment has a positive relation for boosting the economic growth of any country which results in increasing the GDP of the country. FDI allows the money to come in the economy which creates opportunities to increase growth of the economy. 5.3) Employment Ratio(H3) It also affects the economy which indeed affects GDP growth as with the increase in the employment more expenditure will have to be incurred which in turn affect countrys GDP 5.4) Lending Interest Rate(H4) If the interest rate increases it will lead to less money circulation in the economy. The banks and financial institutions of the country will not able to lend money as the people will not be willing to accept because the increase in interest rate will attract more interest expense and hence will resist to it. This will result in decrease in the consumption which will bend the GDP down and secondly money circulation will also reduce which result in the fall in GDP growth. Hence the whole discussion can be summarized in the following manner-: H1- Increase in population lead to increased GDP. Hence it has a positive relation H2- Increase in FDI Increases GDP. It also has a positive relation H3- Increase in employment leads to increase in GDP. It shows positive relation H4- Increase in Interest rate leads to fall in GDP. It has a negative relation 6). Regression results 6.1) Employment Regression (Appendix 9.3.1) In this regression model, Employment ratio is an independent variable and on X-axis. GDP is a dependent variable and on y-axis. After doing data analysis of this model, we conclude that the regression equation for this is: Here, is an intercept which is 1.736 is a slope of this equation which is -2.958 Estimated value If employment ratio is increase by 1, there is decrease in GDP by 2.958. There is negative linear relationship between GDP and employment ratio. Now if we talk about correlation between these two variable which is R. = +à ¢Ã‹â€ Ã… ¡(.720) = +.849 In this + sign shows that correlation is positive and is .849 Now is .72 which shows that 72 % variance in GDP is explained by employment ratio. Now if we talk about this model whether it is good or bad, we have to check two condition. should be high In this is high. Hypothesis test: : ÃŽÂ ² = 0 (no linear relationship between X and Y) : ÃŽÂ ² à ¢Ã¢â‚¬ °Ã‚   0 (linear relationship between X and Y) This is conclude by t statistics Now, = -6.80 Standard error à ¢Ã‹â€ Ã¢â‚¬â„¢value is .000 and we assume ÃŽÂ ± is .05 which is greater than p-value. Hence we reject . So we conclude that it is a good regression model. 6.2) FDI Regression (Appendix 9.3.2) In this regression model, FDI is an independent variable and on X-axis. GDP is a dependent variable and on y-axis. After doing data analysis of this model, we conclude that the regression equation for this is: Here, is an intercept which is 3.894 is a slope of this equation which is 0.029 Estimated value If FDI is increase by 1, there is increase in GDP by . There is positive linear relationship between GDP and FDI as the slope is positive. Now if we talk about correlation between these two variable which is R. = +à ¢Ã‹â€ Ã… ¡(.782) = +.884 In this + sign shows that correlation is positive and is .884 Now is .78 which shows that 78 % variance in GDP is explained by FDI. Now if we talk about this model whether it is good or bad, we have to check two condition. should be high In this is high. Hypothesis test: : ÃŽÂ ² = 0 (no linear relationship between X and Y) : ÃŽÂ ² à ¢Ã¢â‚¬ °Ã‚   0 (linear relationship between X and Y) This is conclude by t statistics Now, = 8.025 Standard error à ¢Ã‹â€ Ã¢â‚¬â„¢value is .000 and we assume ÃŽÂ ± is .05 which is greater than p-value. Hence we reject . So we conclude that it is a good regression model. 6.3) Lending interest rate (Appendix 9. 3.3) In this regression model, Lending interest rate is an independent variable and on X-axis. GDP is a dependent variable and on y-axis. After doing data analysis of this model, we conclude that the regression equation for this is: Here, is an intercept which is 2.088 is a slope of this equation which is -1.066 Estimated value If lending interest rate increases by 1, there is decrease in GDP by 1.066. There is negative linear relationship between GDP and lending interest rate as the slope is negative. Now if we talk about correlation between these two variable which is R. = +à ¢Ã‹â€ Ã… ¡(.466) = +.683 In this + sign shows that correlation is positive and is .849 Now is .46 which shows that 46 % variance in GDP is explained by employment ratio. Now if we talk about this model whether it is good or bad, we have check two condition. should be high In this is high. Hypothesis test: : ÃŽÂ ² = 0 (no linear relationship between X and Y) : ÃŽÂ ² à ¢Ã¢â‚¬ °Ã‚   0 (linear relationship between X and Y) This is conclude by t statistics Now, = -3.964 Standard error à ¢Ã‹â€ Ã¢â‚¬â„¢value is .001 and we assume ÃŽÂ ± is .05 which is greater than p-value. Hence we reject . So we conclude that it is a good regression model. 6.4) Population Regression (Appendix 9.3.4) In this regression model, Population is an independent variable and on X-axis. GDP is a dependent variable and on y-axis. After doing data analysis of this model, we conclude that the regression equation for this is: Here, is an intercept which is 3.894 is a slope of this equation which is 0.029 Estimated value If population is increase by 1, there is increase in GDP by 3.60 There is strong positive linear relationship between GDP and POPULATION as the slope is positive. Now if we talk about correlation between these two variable which is R. = +à ¢Ã‹â€ Ã… ¡(.819) = +.905 In this + sign shows that correlation is positive and is .905 Now is .81 which shows that 81 % variance in GDP is explained by population. Now if we talk about this model whether it is good or bad, we have to check two condition. should be high In this is high. Hypothesis test: : ÃŽÂ ² = 0 (no linear relationship between X and Y) : ÃŽÂ ² à ¢Ã¢â‚¬ °Ã‚   0 (linear relationship between X and Y) This is conclude by t statistics Now, = 9.031 Standard error à ¢Ã‹â€ Ã¢â‚¬â„¢value is .000 and we assume ÃŽÂ ± is .05 which is greater than p-value. Hence we reject . So we conclude that it is a good regression model. 7) Conclusion The effect of factors like employment ratio, foreign direct investment, lending interest rate and population on GDP of India are considered as important variables which we have tried to explain with the help of regression analysis and hypothesis testing. By considering the data of past 20 years we have also calculated its mean, median, mode, Variance, standard deviation (appendix 2). We have one dependent variable that is GDP and four independent variables which are FDI, employment ratio, population, and interest rate. According to multiple regressions, the equation for the model is: Where x1, x2, x3, x4 are the independent variable, estimated value E(y) is expected by these variable. In our report, we have taken separate simple regression models Regression analysis cannot interpret as a procedure for establishing a cause and effect relationship between variables. It can only show that how much these variables are related or associated with each other. Regression equation tells us about mean value of y for given value of x. According to Hypothesis test, all four regression model is good model and it estimates the mean value for these independent variables with less errors. The models also shows the relationship between GDP and these independent variables and their effect on GDP. If value of these independent variables is increase by 1, we conclude how much it affects the estimated value of GDP. Estimated value of GDP is increases by 3.60 if there is one unit increase in population Estimated value of GDP is increased by .029 if there is one unit increase in FDI Estimated value of GDP is decreased by 2.958 if there is one unit increase in employment ratio Estimated value of GDP is decreased by 1.066 if there is one unit increase in interest rate Hence it can be concluded that all factors affects GDP and we cant estimate GDP if we dont have particular value of these independent variable. 8) Bibliography References Amosweb.com (2012) AmosWEB is Economics: Encyclonomic WEB*pedia. [online] Available at: http://www.amosweb.com/cgi-bin/awb_nav.pl?s=wpdc=dspk=employment-population+ratio [Accessed: 29 Nov 2012]. Anderson, D. and Sweeney, D. (2011) Statistics for Business and Economics. 11th ed. New Delhi: Cengage Learning India Private Limited. Databank.worldbank.org (2012) World Databank. [online] Available at: http://databank.worldbank.org/ddp/home.do [Accessed: 29 Nov 2012]. Investopedia.com (2012) Real Interest Rate Definition | Investopedia. [online] Available at: http://www.investopedia.com/terms/r/realinterestrate.asp#axzz2DS1wJc9k [Accessed: 29 Nov 2012]. Scribd.com (2012) GDP. [online] Available at: http://www.scribd.com/doc/81376677/GDP [Accessed: 29 Nov 2012]. Scribd.com (2001) FACTORS INFLUENCING THE GDP OF INDIA. [online] Available at: http://www.scribd.com/doc/84520340/FACTORS-INFLUENCING-THE-GDP-OF-INDIA [Accessed: 29 Nov 2012]. Unknown. (2012) [online] Available at: http://web.williams.edu/go/math/sjmiller/public_html/BrownClasses/162/Handouts/StatsTests04.pdf [Accessed: 29 Nov 2012].

Booker T. Washingtons Up from Slavery Essay -- Up from Slavery

The book, Up From Slavery, written by Booker Taliaferro Washington, profoundly touched me when I read it. Washington overcame many obstacles throughout his life. He became perhaps the most prominent black leader of his time. Booker T. Washington belived that African Americans could gain equality by improving their economic situation through education rather than by demanding equal rights. Washington’s life story was told during the mid to late 1800’s into the early 1900’s, in the time when the Emancipation Proclamation had gone into effect. The Emancipation Proclamation was one major event in history that forever changed our country. All slaves were free and had to go find a new place to live and a new place to work. When the slaves were first freed there was alot ofhostile feelings from the whites towards the newly freed slaves. To blacks living within post- Reconstruction South, Washington offered industrial education as the means of escape from sharecropping and allowed blacks to become self-employed, while owning their own land, or small business. Booker over came the obstacles of the free black man by educating himself and other blacks to become â€Å"equal† to whites. Until the start of World War I African Americans had a difficult time. His speaking tours and private persuasion tried to equalize public educational opportunities and to reduce racial violence. There were many gains earned after the Civil War seemed lost by the time of World War I because racial violence and lynching reached an all time high. However, both the National Association for the Advancement of Colored People (NAACP) and the National Urban League (NUL) were founded by blacks and whites during this time. Both of these major civil rights organizations make efforts on the part of blacks and their white allies to insure that the United States provides "freedom and justice to all". The year of Washington's death marked the beginning of the Great Migration from the rural South to the urban North. He is known as one of the best civil rights leaders for the African American people in the late 1800’s and early 1900’s. Booker began his life as a slave for the Burroughs family. He was born in Franklin Co., Virginia around the year 1858 or 1859, he was not sure exactly when he was born because there was never any paper work kept on slaves. His mo... ...to be equally educated. His speeches not only attracted the black people but also, northern and southern white people. Booker worked hard for all that he achieved during his life time. People all over were followers of Booker T. Washington. One example of how much these followers appreciated Washington is through raising money for a trip to Europe. Not just anyone went to Europe in those days. The trip showed how much the people appreciated Booker’s efforts for civil rights and education of blacks. They sent him and his wife away for three months of strictly relaxation. I believe that this is a very inspirational book giving the message â€Å"you can do anything if you put your mind to it†. Booker shows his reader this through all the things he does in his life time. This book was a very enjoyable book to read. I would highly recommend all people to read Up From Slavery to see the impact Booker T. Washington had on the African American civil rights that are present in the United States today. I believe that Up From Slavery showed how blacks improved their economic situation through gaining education. Bibliography: Up From Slavery by Booker T. Washington

On the Importance of the Educational Experience Essay

In Democracy and Education Dewey presents his views regarding the three functions of education. He gives the main function of education, these being: (1) Education should simplify and order the factors of the dispositions it wants to develop, (2) Education should purify and idealize existing social customs, and (3) Education should create a wider and better balanced environment which will influence the young (Dewey 37). He notes that these stand as a requirement for enabling the development of a progressive and democratic society wherein he defines a progressive society as one in which â€Å"individual variations are considered precious†¦ (thereby) allowing for intellectual freedom and the play of diverse gifts and interests in its educational measure† (Dewey 451). Dewey’s views thereby relate the importance of the experience within educational institutions to that of ensuring democracy within a particular community. Since the foundations of democracy are that of liberty and equality, Dewey places emphasis on the necessity of ensuring that intellectual freedom may be practiced within the context of an institution that allows diversity. Within educational systems, an example of this can be seen in the practice of coeducation. As opposed to this view, however, Link Byfield, in his article â€Å"If Girls Can Succeed Only at the Expense of Boys, Maybe We Need Segregated Schools† claims that the implementation of coeducational systems leads to the development of sexism within the system which proves detrimental to the non-privileged sex. In line with this, the tasks of this paper are the following: (1) It seeks to present the views presented by Byfield in his article above and (2) It aims to present an analysis of his argument in line with how coeducation has helped in the presentation of more views in the different subjects within the educational institution and how these views enable the expansion of the educational process. Byfield (2008) argues that increase in the scores of high school girls in the School Achievement Indicators Program (SAIP) in Canada shows that there is ‘regress’ in the educational system. The bases for his claim are the following. He claims that low proficiency of high school boys in language skills and low number of high school boys who have graduated within the time-frame of the survey. He thereby opposes the view presented by the SAIP that school systems within favor the members of both sexes. The bases for SAIP’s conclusion are the following views. First, â€Å"high school girls on average are matching boys in the technology related subjects of math and science, and are far ahead in language skills† and second the ratio of the number of graduates shows that more girls are graduating as opposed to boys. In line with this, Byfield notes, given that a change in the system [from male-oriented to female-oriented] led to the ‘regress’ in the educational achievement of male students, the author argues that it is necessary to segregate students in terms of sex. The basis for his claim is the view that sexism continues to be practiced within educational institutions. He notes that this is apparent in the shift of power from the boys to the girls. He says, â€Å"Now girls seem to run everything†¦ the boys’ just tune out†. In addition to this, he says that the adaptation of a segregated system will allow the individual to be socialized in a natural environment which will allow him to be prepared for the ‘real life’. He further argues that this will not â€Å"offend the ‘social imperative’† in the sense that it will create a society â€Å"driven by misunderstanding, ignorance, selfishness, and distrust†, on the other hand, such a setting will free the individual from an environment characterized by â€Å"moshpits of vulgarity where youth is free to run itself according to the values it has absorbed from MachMusic and 12 years of automatic passing and parent-free sex instruction†.

Anger Is A Common Emotion Of The World - 2013 Words

Anger is a very common emotion in the world. It’s extremely difficult to always be calm and never experience difficult emotions. Anger can be a small issue such as road rage to a more harsh feeling like warfare. Anger is known as one of the seven deadly sins of the world. It’s also one sin that pretty much everyone has experienced at least once in their lifetime. The nature of anger is a very complicated subject. Questions often occur asking why is anger such a easy emotion to feel? What can cause a person to feel rage or frustration? What can we do to take steps to avoid anger from controlling our lives? Some people may say that counseling can help. While others believe that some souls are beyond the point of no return. In today’s world those seeking to control their emotions often visit a local church of a counselor. Psychologists often try to theorize what can be done to heal these emotions and try to make sense out of them. Many years ago two particular philo sophers took all of their knowledge and formed thesis’s on what they felt anger meant to them. These two philosophers were Aristotle and Seneca. Aristotle is known for his work in the nature of humans. Seneca wrote essays on various topics one of which was anger. Each philosopher breaks down their theories of anger and gives a better explanation of why violence occurs and if there is a way to stop it from spiraling. Using this thesis can help to explore the topics of the minds of criminals and the subject of domesticShow MoreRelatedJealousy By William Shakespeare s Proverbs 844 Words   |  4 Pagesis an emotion that often makes each of us act and react in a bad way. Some pout, some stomp the ground and shake their fist and still others yell and scream. Some people do all of these things at the same time. Revenge is an act, based on an emotion. But is it formed from the same emotion as jealousy? 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