1. 1 Econometrics (NA1031) Lecture 1 Introduction

2. 2 ”How much” type questions oBy how much a unit change in income affects consumption? oBy how much should the central Bank raise interest rates to prevent inflation? oBy how much can the price of football tickets be increased and still fill the stadium? Econometrics is about how we can use economic, business or social science theory and data, along with tools from statistics, to answer “how much” type questions; i.e. estimate important parameters which are unknown.

3. 3 The econometric model We are interested in studying the average or systematic behavior over many individuals or many firms. Not a single individual or a single firm. An econometric model representing the sales of Honda accords is q d = f(p,p s, p c,i) + e Where f(p,p s,p c,i) is the systematic part and e is a random and unpredictable part.

4. 4 The econometric model Specification of the systematic part How are the variables related? Assumptions about the nature of the random part (error term)

5. 5 Data Controlled experiment (“pure sciences”): explaining mass, Y : pressure, X2, held constant when varying temperature, X3, and vice versa. Uncontrolled experiment (econometrics) explaining consumption, Y : price, X2, and income, X3, vary at the same time. Economic data Cross section, Time series, Panel

6. 6 Statistical inference Infer or learn something about the real world by analyzing a sample of data Estimating economic parameters Predicting economic outcomes Testing economic hypothesis

7. 7 Review of statistical concepts (Read the text and the complementary material for a detailed exposition)

8. 8 Random variables What is meant by a random variable? May be discrete or continuous Have probability (density and distribution) functions We can ask (and answer) questions like what is the probability of X taking a certain value (if discrete) or lying in an interval. Have expected (mean) values Have variances

9. 9 Random variables May be related to (depend on) other random variables (or not) Covariance Correlation Linear association Is not causation

10. 10 Stata There is a short introduction to Stata document on the course webpage on Fronter. It is very brief and intends to get you started and not to be comprehensive. You can download the data files that we are going to practice from http://users.du.se/~rem/ or from course webpage (see the map Data sets). http://users.du.se/~rem/

11. 11 Getting started with Stata Start the software Click on Windows icon and programs and click on the icon StataSE-64 (Or Windows Start, Computer, Common (\\bob), Stata 14, click on the icon StataSE-64 (short cut))\\bob Get familiar with the different windows You can use menu and dialog boxes but in our sessions we are going to run commands or use do-files. By typing update all possible new functions will be installed. Stata is case sensitive

12. 12 Do-files We are going to mostly use do-files when we work with Stata. Do-files are text files in which a set of commands are written. These can be executed without having to type the commands with the keyboard or using dialog boxes. mkdir C:\PE cd C:\PE copy http://users.du.se/~rem/chap01_15.do chap01_15.do doedit chap01_15.do

13. 13 Assignment use http://users.du.se/~rem/cps4_small, clear Look at the distribution (descriptive statistics and/or histograms) of some variables that you find interesting. Also pick some variables in the dataset that you expect may be correlated to each other. Then check the actual correlation.