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The Nature of Econometrics Tools of Using Econometrics
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Historical Origin of the Term “Regression” Regression is a main tool of econometrics It was firstly introduced by Francis Galton (1886) in his famous paper called: Family Likeness in Stature (Proceedings of Royal Society, London, Vol 40, pp. 42-72). Where he tried to found out that the average height of children born of parents of a given height tended to move or “regress” toward the average height in the population as a whole.
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The Modern Interpretation of Regression Regression analysis is concerned with the study of the dependence of one variable, the dependent variable, on one or more other variables, the explanatory variables.
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Example XXXXXXXXXXXX XXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXX XXXXXXXXXXXXXXXXXX Son’s Height (İnches) 75 70 65 60 » 60 65 70 75Father’s Height (inches) Galton’s Study: Hypothetical Distribution of Sons’ Heights (Dependent variable) Corresponding to given Heights of Fathers (Independent Variables) Regression Line
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Hypothetical and Classical Phillips Curve (1970-2004) + - 0 Inflation (%) Unemployment Rate (%) 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 Regression Line
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Statistical vs Deterministic Relationships Regression analysis is concerned with what is known as the statistical dependence among variables. Statistical relationships deal with random or stochastic variables that have probability distributions. Stochastic: comes from Greek word “stokhos” meaning “a bull’s eye”. For example, the outcome of throwing darts on a dart board is a stochastic process, that is, a process fraught with misses.
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Regression vs Causation Y = 0 + 1 X + ε t Since Y depends on X, it does not necessarily imply causation. However, there are tools to measure causation among variables via regression models.
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Regression vs Correlation In regression analysis, there are one dependent variable and one or more independent variables In correlation analysis there are two variables and both are independent. The correlation coefficient measures the strength or degree of linear association between two variables.
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Terminology and Notation Y Dependent Variable Explained Variable Predictand Regressand Response Endogeneous X Explanatory Variable Independent Variable Predictor Regressor Stimulus or control variable Exogeneous
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Types of Regression Analyses Simple Regression Analysis: Two-variable regression analysis which has one dependent and one independent variable. Multiple Regression Analysis: Regression analysis which studies the dependence of one variable on more than one independent or explanatory variables.
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The Nature and Source of Data for Econometric Analysis Types of Data Time Series Data Cross Sectional Data Panel or Pooled Data
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Sources of Data International Sources or Websites www.worldbank.org Worldbank Development Indicators www.imf.org International Financial Statistics
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