By Philip Hans Franses

ISBN-10: 0511042728

ISBN-13: 9780511042720

ISBN-10: 0521520908

ISBN-13: 9780521520904

ISBN-10: 0521817692

ISBN-13: 9780521817691

This ebook is a perfect creation for starting scholars of econometrics that assumes purely simple familiarity with matrix algebra and calculus. It gains useful questions which might be replied utilizing econometric equipment and versions. concentrating on a constrained variety of the main simple and customary equipment, the booklet experiences the fundamentals of econometrics ahead of concluding with a couple of contemporary empirical case reports. the amount is an intuitive representation of what econometricians do while confronted with functional questions.

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**Additional resources for A Concise Introduction to Econometrics: An Intuitive Guide**

**Example text**

This is perhaps not so much of a problem, as there are various ways to see which variables are redundant. In some textbooks this is called model selection, although perhaps the phrase variable selection is better. The second case of omitted variables can be worse as one has overlooked something – that is, the model is lacking components which would have added explanatory value to the model. It sounds like a doctor who misses out a sign of some disease or a plumber who diagnoses a leak at the wrong spot.

As will be discussed in chapter 3, there are various approaches to estimating parameters, but here it suffices to mention just a basic one. 17) where it can be assumed (although it is not exactly necessary) that εi ∼ N(0, σ 2 ). 18) A simple idea would now be that the best match (or fit) between yi and βˆ 1 +βˆ 2 xi would correspond to the case where σˆ 2 is smallest. Hence, one might look for estimators for β 1 29 A Concise Introduction to Econometrics and β 2 for which the residual terms εˆ i have the smallest variance σˆ 2 .

A second source of economic data concerns repeated crosssections, meaning that one observes the behavior of individuals over time. When these are the same individuals, the resulting data are called panel data. Examples of panel data are household panels who document all purchases in each week, or panels of countries for which certain economic characteristics are observed, or panels of firms for which financial variables have been measured over a number of years. One reason why one might consider panel data is that there may be some common properties across the individuals over time, such that there is no need to consider n independent regression models.

### A Concise Introduction to Econometrics: An Intuitive Guide by Philip Hans Franses

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