Econometrics For Dummies
Econometrics can prove challenging for many students unfamiliar with the terms and concepts discussed in a typical econometrics course. Econometrics For Dummies eliminates that confusion with easy-to-understand explanations of important topics in the study of economics.
Econometrics For Dummies
Download File: https://www.google.com/url?q=https%3A%2F%2Fmiimms.com%2F2udtc4&sa=D&sntz=1&usg=AOvVaw2jM9vxHF6nOKYJeiEdQL5v
Econometrics For Dummies breaks down this complex subject and provides you with an easy-to-follow course supplement to further refine your understanding of how econometrics works and how it can be applied in real-world situations.
To accurately perform these tasks, you need econometric model-building skills, quality data, and appropriate estimation strategies. And both economic and statistical assumptions are important when using econometrics to estimate models.
Fortunately, one of the primary contributions of econometrics is the development of techniques to address such problems or other complications with the data that make standard model estimation difficult or unreliable.
Econometrics for Dummies is an ideal companion for anintroductory course in econometrics. The book is written for people thatwant to learn how to use econometrics in their research and complementsthe discussion of theory with advice about how to move from data andeconomic theory to estimation. All the computational examples and outputin the book use Stata. The book assumes some previous knowledge ofstatistics and economics but does offer a comprehensive review of thebasic concepts needed to understand the concepts in the text.
Econometrics for Dummies presents theoretical econometric resultsand provides an intuitive interpretation of them. The book is a goodreference for those wanting to get an insight into basic econometric conceptsencountered in an introductory econometrics course.
Dummy variables may be extended to more complex cases. For example, seasonal effects may be captured by creating dummy variables for each of the seasons: D1=1 if the observation is for summer, and equals zero otherwise; D2=1 if and only if autumn, otherwise equals zero; D3=1 if and only if winter, otherwise equals zero; and D4=1 if and only if spring, otherwise equals zero. In the panel data fixed effects estimator dummies are created for each of the units in cross-sectional data (e.g. firms or countries) or periods in a pooled time-series. However in such regressions either the constant term has to be removed, or one of the dummies removed making this the base category against which the others are assessed, for the following reason:
where newvar is the name of a matrix to contain the seasonal dummies, nobs is the number of observations andnseas is the number of periods in the seasonal cycle (4 for quarterly data and 12 for monthly data).
Warning: The SEAS function on the MATRIX command places a 1 in the first observation of the firstcolumn. Therefore, if the quarterly data starts in quarter 3 thenthe first column of the matrix of seasonal dummies will be the dummyvariable for quarter 3.
This example is discussed in Section 15.10 of Gujarati [1995, pp. 517-519].The data set is quarterly seasonally unadjusted data on profits and sales for U.S. manufacturing corporations. The SHAZAM commands (filename: PROFITS.SHA) below create a matrix QD that contains 4 columns of seasonal dummies. The dummy variables for quarters 2, 3 and 4 are placed in the variables QD2, QD3 and QD4.
The next SHAZAM commands show model estimation with 4 quarterlyseasonal dummy variables. The OLS regression includes the matrix of seasonal dummies QD in the list of explanatoryvariables. (SHAZAM will interpret the columns of the matrix as 4 separateexplanatory variables). The NOCONSTANT option is used on the OLScommand to specify that the intercept is to be excluded.
The qualitative independent variable models are estimated through (i) intercept dummy model, (ii) slope dummy model, (iii) intercept and slope dummy model, and (iv) interaction between dummies. An extension to multiple categories, seasonal effects and regime effects are estimated and tested in this topic. 041b061a72
