by Lund University
This is NEKN31, Advanced Econometrics for students at Lund University
All the mathematics that we need to get started. Most of this will be known to you. We begin by reviewing matrix algebra and functions of several variables. We then look at some multivariable calculus. In particular, how to differentiate a function with respect to a vector. We apply these derivatives to linear functions and quadratic forms.
This chapter is about the linear regression model
All the probability theory that we need for this course
The final chapter of this course is an introduction to statistics. The basic idea of statistics is to make inference about a population given a sample drawn from this population. We begin by translating the population/sample concepts into a framework consistent with formal probability theory in section one. Section two looks at some important distributions that we often end up using in statistics. Section three looks at the simplest problems in statistics, making inference about the mean and the variance. We then move on to a more general study of statistics, introducing estimators and their small-sample properties. The following section is devoted to the more important, but also more difficult, large-sample properties of estimators. The final section will generalize what we have done so far in this chapter by looking at several estimators collected in a vector.
The statistics of the linear regression model, small samples
The statistics of the linear regression model, large samples
Some additional material on the linear regression model. This chapter is based on chapter 3 of Verbeek. Most of this is likely known from before. See Lecture 6 Part 2.
Endogeneity and instrumental variables
Method of moments and GMM
Models with limited dependent variables
Univariate time series
Time series models