Analysis of economic data
Analysis of Economic Data teaches methods of data analysis to students whose primary interest is not in econometrics, statistics or mathematics. It shows students how to apply econometric techniques in the context of real-world empirical problems. It adopts a largely non-mathematical approach relying on verbal and graphical intuition and covers most of the tools used in modern econometrics research e.g. correlation, regression and extensions for time-series methods. It contains extensive use of real data examples and involves readers in hands-on computer work. The new edition includes new material on the mathematical background required by students and, for those readers unfamiliar with this background, a brief explanation of the relevant mathematics. Topics covered include: the equation of a straight line, the summation operator, and logarithms. The author also includes a much greater discussion of data transformations such as growth rates and index numbers. More material will also be added on data sources, largely focusing on internet data sources. Gary Koop has a very high international profile in the field of econometrics and is well known for his books and numerous journal publications. The second edition provides stronger coverage of the relevant introductory mathematics, including: the equation of a straight line, the summation operator, and logarithms. This will make the book more accessible for those students who have limited mathematical skills. Greater discussion is also provided of data transformations such as growth rate and index numbers. Index numbers are becoming increasingly important and are frequently used in economics courses. More material will also be provided on data sources, especially internet data sources which are becoming extremely important as a means of gathering data. Some students have difficulty with the collection of data and the inclusion of this material will help those students.
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Basic data handling
An introduction to simple regression
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ADL model AT-plot autocorrelation bananas calculate causality ceteris paribus coefficients cointegration common confidence interval correlation countries critical value data set deforestation dependent variable deterministic trend discussion distributed lag model dummy variables econometrics economic economists empirical equation equilibrium Exercise explanatory power explanatory variables Figure forecasting formula GDP per capita Granger cause house price hypothesis testing implies indicate instance intercept interest rates interpret intuition labeled lag length level of significance long run multiplier macroeconomic marginal effect measure multicollinearity multiple regression nonstationary Note number of bathrooms number of bedrooms observations obtain OLS estimates omitted variables bias output P-value personal income plot population density price inflation real GDP regres regression line regression model relationship residuals root test run a regression safety training series data series variables simple regression software packages spreadsheet stationary stock price Table tend test statistic trend behavior unit root volatility wage inflation zero