Download Econometrics by Example by Damodar Gujarati PDF

By Damodar Gujarati

Damodar Gujarati is the writer of bestselling econometrics textbooks used around the globe. In his newest e-book, Econometrics by way of instance, Gujarati offers a different learning-by-doing method of the examine of econometrics. instead of counting on advanced theoretical discussions and intricate arithmetic, this ebook explains econometrics from a realistic viewpoint, with each one bankruptcy anchored in a single or prolonged real-life examples. the elemental thought underlying every one subject is roofed and an appendix is incorporated at the easy statistical innovations that underlie the fabric, making Econometrics by way of instance an preferably versatile and self-contained studying source for college students learning econometrics for the 1st time.

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Extra resources for Econometrics by Example

Sample text

All one has to do is "Google" a topic and it is amazing how many sources one finds. The quality of data The fact that we can find data in several places does not mean it is good data. One must check carefully the quality of the agency that collects the data, for very often the data contain errors of measurement, errors of omission or errors of rounding and so on. Sometime the data are available only at a highly aggregated level, which may not tell us much about the individual entities included in the aggregate.

It might seem that this R2 value is rather low, but keep in mind that we have 1,289 observations with varying values of the regressand and regressors. In such a diverse setting the R2 values are typically low, and they are often low when individual-level data are analyzed. This part also gives the adjusted R2 value, which is slightly lower than the unadjusted R2 values, as noted before. Since we are not comparing our wage model with any other model, the adjusted R2 is not of particular importance.

All we can say is what a person with the given (X) characteristics might earn. This is the essence of forecasting. Forecasting is generally used in the context of time series analysis. In Chapter 16 we will explore this topic more fully with illustrative examples. 10 The road ahead Now that we have presented the basics of the CLRM, where do we go from here? The answer follows. 2 is based on the assumptions of the CLRM. The question that naturally arises is: how do we know that this model satisfies the assumptions of the CLRM?

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