Applied Econometrics Second edition Dimitrios Asteriou and Stephen G. Hall
What is Econometrics? The Stages of Econometric Work INTRODUCTION What is Econometrics? The Stages of Econometric Work
What is Econometrics? Econometrics means measurement (metrics in greek) in economics. The importance of applied work in economics is increasing constantly. Theory suggests that X affects Y but is this true or not? This is the work of the applied econometrician.
What is Econometrics? Examples of problems that may be tackled by an Econometrician Modelling long-term relationships among prices and interest rates. Examining the effect of inflation in unemployment rates Examining the effect of disposable income on consumption
What is Econometrics? Examples of problems that may be tackled by an Econometrician (continued) Determining the factors that affect GDP per capita growth Testing the validity of the CAPM and APT theories Forecasting the correlation among the returns and the stock indices of two countries.
The Stages of Applied Econometric Analysis Economic Theory Econometric Model Data Model Estimation Specification Testing and Diagnostics Is the Model Adequate? No Yes Test any hypothesis Use for Predictions and Policy Making
The Structure of Economic Data There are three different types of economic data TIME SERIES CROSS SECTIONAL PANEL DATA
The Structure of Economic Data Time Series Data Examples: GDP, Unemployment, Inflation, Stock Prices, etc Vectors or Columns (like in a spreadsheet) Frequencies: Yearly, Bi-annually, Quarterly, Monthly, Weekly, Daily, Hourly. Lots of different values for different time periods for one country, state, city, market.
The Structure of Economic Data Cross-Sectional Data Examples: GDP, Unemployment, Inflation, Stock Prices, etc. Vectors or Rows (like in a spreadsheet) Frequencies: Yearly, Bi-annually, Quarterly, Monthly, Weekly, Daily, Hourly. Lots of different values for different countries, states, cities, markets, but for one time period only.
The Structure of Economic Data Panel Data A combination of time series and cross-sectional data. Examples: GDP, Unemployment, Inflation, Stock Prices, etc. Matrices (columns and rows to make an n times m matrix) Frequencies: Yearly, Bi-annually, Quarterly, Monthly, Weekly, Daily, Hourly. Lots of different values for different countries, states, cities, markets, and for different time periods.
The Structure of Economic Data - Notation Time series: Yt, t=1990, 1991, …, 2012 Cross-Sectional: Yi, i=1, 2, 3, …, 40 Panel Data: Yit, i and t defined as above. It is common to denote each observation by the letter t and the total number of observations by T for time series data, and to denote each observation by the letter i and the total number of observations by N for cross-sectional data.
The Structure of Economic Data – Quantitative vs Qualitative The data may be quantitative and qualitative. Quantitative (e.g. GDP per capita, exchange rates, stock prices, unemployment rates) Qualitative (e.g. Day of the week, gender, level of education)