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2022代写写手Quantitative Methods essay 作业需求

By August 21, 2022essay代写

2022代写写手Quantitative Methods essay 作业需求

2022代写写手Quantitative Methods essay 作业需求

Cardiff Business School Quantitative Methods: 2009/2010.Project for the Quantitative Methods

The deadline for the submission of this project is the Friday 19th of March 2010.This project accounts for 50% of your grade on Quantitative Methods. The remaining 50% is accounted for by the examination. You must submit a complete project for assessment.Project Presentation Guidelines:1. Your project should be word-processed, well-organised and bound or stapled.Your answer (project work) should be concise and focussed.2. Relevant econometric results must be typed and reported in Tables. Eviews output should be saved in a CD. DONOT APPEND EVIEWS OUTPUT to the hardcopyof your project. The project must not be made bulky by appending the Eviews output.3. The maximum word limit is 1500 words, excluding the Tables. The hardcopy of the project (including Tables, Text and References) MUST NOTEXCEED 13 pages in total. Excessive length will be penalized.4. A CD containing an electronic version of your exact project report (MS Word document) and Eviews results (output) should also be submitted. It should clearly be labelled by your name and student number, for example, “Sarah_Smith.doc,Student No: 0123456”.

Plagiarism warningIf plagiarism is suspected, your project will receive close scrutiny. Electronic versions of your work will also be examined. All projects found to contain identical text will receive a mark of zero.NOTE:The total mark for this project is 100%. The mark for each question is clearly shown.It is important that you answer all the questions given below. Your work must be clearly presented and concisely explained. This should include, where appropriate, explanationand interpretation of the following:The Essay is provided by UK Assignment• Methods and models employed,• Formulation of the null and alternative hypotheses, • Hypothesis tests,• Inference drawn, and• Explanation of economic intuition of the relationship(s) estimated.Data file:Data set for this project is provided in an Eviews file “project-2010.wf1”. Download this data. This file contains data on:gdp = real GDP (Output) of a country, say a Sample Country.ks = real physical capital stockemp = labour force employedbr = stock of Domestic knowledge (R&D) (i.e., total stock of domestic technology)sf = stock of foreign knowledge (i.e., total knowledge stock of Sample country’s trading partners)All variables are in natural logarithms. Data sample is 1960 to 2008. Data frequency is annual.Question 1. Tabulate descriptive statistics (mean, median, maximum, minimum and standard deviation) of the dataset and describe them. Plot all five series and comment ontheir time pofile. (Marks 5).Question 2. Estimate the following production function by OLS Estimator:t 0 1 t 2 t 3 t 4 t t q =α +βks +β emp +β br +β sf +e (1).Where q = gdp and rest of the variables are also as defined above. Also compute (i) the second and the third order Breusch-Godfrey LM tests of residual serial correlation, (ii) Breush-Pagan test of hetroscedasticity, (iii) White’s test of heteroscedasticity and (iv) RESET test of functional form. Comment on the overall (OLS) results of above production function as well as the diagnostic tests computed in (i) – (iv). Marks (15).Question 3. Does the model (1) suffer from residual serial correlation and heteroscedasticity? If so, first address the problem of auto-correlation by estimating either an AR(1) or an AR(2) specification of the above model (equation (1)). Please note in Eviews, estimating AR(1) and AR(2) specifications are straightforward and they are equivalent to the Cochrane-Orcutt corrections for the residual autocorrelation. Your final specification (model), whether AR(1) or AR(2), must be based on the requirement that the model passes the second order residual serial correlation. Report the results andrelevant tests of your preferred specification and interpret the results. Test if your model still shows the heteroscedasticity and report the results. You must comment on all the results. (Marks 15).Question 4. Conduct CHOW test of structural break treating 1990 as the date of break.Report and interpret the CHOW test result. (Marks 5).Question 5. Conduct unit root (DF/ADF) tests on each of the variables of equation (1) above. You must conduct unit root tests sequentially and report all the results in a Table.The Essay is provided by UK Assignment http://www.ukassignment.orgUsing these results, explain clearly whether the variables in equation (1) are I(0), I(1) or I(2). (Marks 15).Question 6. Specify and concisely explain the two steps of Engle-Granger co-integration test. Following this method, estimate, test and report if equation (1) forms a cointegrating relationship. Interpret the co-integrating parameters. Plot the error correction term (ECT) and comment. (Marks 10)Question 7. Briefly discuss the differences between Engle-Granger and the DynamicOLS (DOLS) estimators of a co-integrating relationship. Specify and estimate a firstorder DOLS co-integrating regression of equation (1) and report the results. Test for thesecond order residual autocorrelation on this DOLS and assess whether you need to optfor a DGLS (Dynamic GLS) estimator. Depending on the residual serial correlations,estimate a suitable (either AR(1) or AR(2)) DGLS co-integrating regression such thatyour preferred (final) specification passes residual autocorrelation tests. Conductsignificance tests on co-integrating parameters through Wald test and interpret the results.Plot the ECT (error correction term) derived from the DGLS model of your choice andcomment. (Marks 15).Question 8. Compare and contrast the co-integration results obtained from the Engle-Granger approach and your preferred DGLS model. Explain with illustration the conceptof an error-correction model. (Marks 10).Question 9. Specify two regression equations for Granger causality tests between outputgrowth and domestic R&D growth in a multivariate framework using all the variables ofequation (1). Conduct short run and long run Granger causality tests and report andinterpret the results. (Marks 10).The End.


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