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Unformatted text preview: Dougherty: Introduction to Econometrics 3e Study Guide Chapter 1 Simple regression analysis Overview This chapter introduces the least squares criterion of goodness of fit and demonstrates, first through examples and then in the general case, how it may be used to develop expressions for the coefficients that quantify the relationship when a dependent variable is assumed to be determined by one explanatory variable. The chapter continues by showing how the coefficients should be interpreted when the variables are measured in natural units, and it concludes by introducing R 2 , a second criterion of goodness of fit, and showing how it is related to the least squares criterion and the correlation between the fitted and actual values of the dependent variable. Further material Definition of crosssectional, time series, and panel data Data sets may be of three types: crosssectional data, time series data, and panel data. Crosssectional data sets are generated at one moment in time and the observations generally relate to households, individuals, enterprises, or geographical areas. It is usually very desirable that the sample should be drawn from a welldefined population using a statistically respectable sampling scheme, so that one may generalize from the results. For example, the Consumer Expenditure Survey data set, whose observations relate to households, employs a sampling scheme that makes it nationally representative of the United States. Time series data sets consist of repeated observations on a set of variables over an interval of time. Generally the interval between the observations is fixed, often being a year, a quarter, or a month, but in some cases, such as analysis using stock market prices, the frequency may be much greater. An example is the Demand Functions data set, used for examples and exercises in Chapters 11–13 of the text. It consists of 45 annual observations over the period 1959–2003 on aggregate expenditure on different categories of consumer expenditure, the prices of the categories, and aggregate disposable income. Panel data sets have both crosssectional and time series dimensions, being repeated observations over an interval of time on the same crosssection sample. The National Longitudinal Survey of Youth is an example. The 6,000 males and females in the core sample were first interviewed in 1979. From then until 1994 they were reinterviewed every year, and since 1994 every two years. The EAEF data sets derived from it and used as examples and exercises in the first part of the text are effectively crosssectional data sets because the earnings data relate to only one year, 2002, and the other characteristics, such as educational attainment, are mostly fixed....
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 Spring '10
 öcal
 Econometrics

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