Anon

265

ChAPter

13

Model estimation

a

fter reading this chapter you will understand:

■ (^) The concept of estimation and estimators.
■ (^) The properties of estimators.
■ (^) The least-squares estimation method.
■ (^) How to apply the least-squares method.
■ (^) The use of ordinary least squares, weighted least squares, and general-
ized least squares.
■ (^) The maximum likelihood estimation method.
■ (^) How to apply the maximum likelihood method.
■ (^) The instrumental variables approach to estimation.
■ (^) The method of moments and its generalizations.
■ (^) How to apply the method of moments.
In the previous chapters of this book, we have described the most com-
monly used financial econometric techniques. However, with the exception
of our discussion of the simple linear regression in Chapter 2, we purposely
did not focus on methods for estimating parameters of the model. As we
mentioned in the preface, we did not do so because most users of financial
econometric techniques utilize commercial software where the vendor uti-
lizes the latest estimation techniques. Nevertheless, it is still important to
understand the various estimation methods that can be applied to specific
models. In this chapter, we discuss these methods. We begin by discussing
the concept of estimation and the concept of sampling distributions.

Statistical Estimation and Testing

All of the financial econometric models that we have described in this book
have parameters that must be estimated. Statistical estimation is a set of
criteria and methodologies for determining the best estimates of parameters.