Growth in Developing Countries: A Panel Cointegration Approach Zequn (Charlie) Li December 19‚ 2014 Economics 385 St. Olaf College Abstract Many factors influence the economic growth process. Especially‚ the inflow of foreign direct investment (FDI) has been found to play a crucial role in the economic growth of receiving countries. This paper examines determinants of economic growth in developing countries from 1991 to 2010. Using panel cointegration approach‚ with panel data across thirty
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Within the realm of Artificial Intelligence there are several secs which are responsible for making up that which is A.I. Normally when an individual thinks of Artificial Intelligence a few things come to mind such as the HAL 9000 system‚ known as “the inimitable star of the classic Kubrick and Clarke film ‘2001: A Space Odyssey’”(Picard 2001)‚ others will think of the movie “Blade Runner”‚ this film featured an alternate future where a group of individuals were responsible for tracking down cyborg
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This paper re-examines the causal relationship between stock prices and macro variables like consumption expenditure‚ investment spending‚ and economic activity (measured by GDP) in Pakistan. Using annual data from 1959-60 to 1998-99 and applying cointegration and error correction analysis‚ the paper indicates the presence of long-run relationship between stock prices and macro variables. Regarding the cause and effect relationship‚ the analysis indicates a one-way causation from macro variables to stock
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from http://www.frbkc.org/PUBLICAT/EconRev/EconRevArchive/1992/3Q92hakk.pdf Kocaeli‚ S.‚ & Durmus‚ C. (2004). The Validity of Purchasing Power Parity. Retrieved from http://smye2009.org/file-002_KOC.pdf Ramirez‚ M‚ & Khan‚ Shahryar. (1999). A cointegration analysis of purchasing power parity: 1973-96 . Manuscript submitted for publication‚ Retrieved from http://www.iaes.org/journal/iaer/aug_99/ramirez/
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bibliography‚ which includes the full reference for all articles‚ books and other sources you have cited in the body of the text. The bibliography (and any footnotes) need not be included in the word count. EViews output should NOT be pasted directly into the project. You should present your EViews equation estimation output as it would be in published academic papers. (Look at some papers – sometimes output is in Tables‚ sometimes as estimated equations with s.e.s/t stats/p-values in brackets under
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Regression with Time Series Data Week 10 Main features of Time series Data Observations have temporal ordering Variables may have serial correlation‚ trends and seasonality Time series data are not a random sample because the observations in time series are collected from the same objects at different points in time For time series data‚ because MLR2 does not hold‚ the inference tools are valid under a set of strong assumptions (TS1-6) for finite samples While TS3-6 are often too restrictive
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I nternational eview of anagement and usiness esearch ol. 1 ssue.1 Attaining Customer Loyalty! The Role of Consumer Attitude and Consumer Behavior MOHAMMAD MAJID MEHMOOD BAGRAM Assistant Professor Allama Iqbal Open University‚ Islamabad Pakistan Email: bagram@hotmail.com Tel: +92-3335188677 SHAHZAD KHAN Lecturer City University of Science & Information Technology‚ Peshawar Pakistan Email: shahzadkhan.lecturer@gmail.com Tel: +92-3339405596 Abstract All over the
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J. and Lütkepohl‚ H. (1996)‚ “Making Wald Tests Work for Cointegrated VAR Systems”‚ Econometric Reviews‚ Vol.15‚ pp. 369-386. Dun’s Review (1980)‚ “Bring Back the Gold Standard”‚ Vol. 115‚ No.2‚ pp.58-67. Engle‚ R.‚ & Granger‚ C. W. (1987). “Cointegration and Error Correction: Representation‚ Estimation and Testing”. Econometrica‚ Vol.55‚ pp.251-276. Ensers‚ Walter (1995)‚ Applied Econometrics Time Series‚ John Wiley and Sons‚ Singapore. Gaur‚ A. and Bansal‚ M. (2010)‚ “A Comparative Study of Gold
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Please write down your fitted regression model. 6. Is Trend correlated with USPI? Set up the hypothesis testing at 5% significance level. 7. What percentage of variation in USPI is explained by this model? Why? 8. Based on your Eview model‚ report your forecast of USPI for the period of 1999.08-2000.07. Report RMSE. Use Chapter 4 Powerpoint question 4.3 to answer the following questions: 9. Report the Eveiw output for regression model USPIt = (USTBR)t + t based on the
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(MOP) and relative productivity (PROD) to get it. Using quarterly data from 1980Q1 to 2012Q4‚ the empirical analysis commences by checking the stationarity of the variables that turn out to be all stationary at first difference. Then‚ using the cointegration test and the Vector-Error Correction Model of the Moroccan Dirham exchange rate as function of the indicated macroeconomic fundamentals‚ the regression shows that the main fluctuations of the real effective exchange rate are due to trade openness
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