Introductory econometrics Chapter 1. ppt

Welcome to Econometrics Introduction

Why study Econometrics? An empirical analysis uses data to test a theory or to estimate a relationship A formal model can be tested Theory may be ambiguous as to the effect of some policy change – can use econometrics to evaluate the program

Steps in Empirical Analysis Careful formulation of the question of  interest Economic Model or Informal Economic Intuition or Reasoning Turn an Economic Model into an Econometric Model State Hypothesis of Interest Data Estimation Testing of Hypothesis

Types of Data – Cross Sectional Cross-sectional data is a random sample Each observation is a new individual, firm, etc. with information at a point in time If the data is not a random sample, we have a sample-selection problem

Types of Data – Cross Sectional

Types of Data – Cross Sectional

Types of Data – Time Series Time series data has a separate observation for each time period – e.g. stock prices Since not a random sample, different problems to consider Trends and seasonality will be important

Types of Data – Time Series

Types of Data – Pooled Crosssections and Panel Can pool random cross sections and treat similar to a normal cross section – known as pooled cross-sections data. Will just need to account for time differences. Can follow the same random individual observations over time – known as panel data

Types of Data – Pooled Crosssections

Types of Data – Panel

The Question of Causality Simply establishing a relationship between variables is rarely sufficient Want to the effect to be considered causal

If we’ve truly controlled for enough other  variables, then the estimated ceteris paribus effect can often be considered to be causal Can be difficult to establish causality

Example: Returns to Education A model of human capital investment implies getting more education should lead to higher earnings In the simplest case, this implies an equation like

 Earnings    0   1education  u

Example: (continued) The estimate of   1, is the return to education, but can it be considered causal? While the error term, u, includes other factors affecting earnings, want to control for as much as possible Some things are still unobserved, which can be problematic