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EE325 Introductory Econometrics1 Welcome to EE325 Introductory Econometrics Introduction Why study Econometrics? What is Econometrics? Methodology of Econometrics.

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Presentation on theme: "EE325 Introductory Econometrics1 Welcome to EE325 Introductory Econometrics Introduction Why study Econometrics? What is Econometrics? Methodology of Econometrics."— Presentation transcript:

1 EE325 Introductory Econometrics1 Welcome to EE325 Introductory Econometrics Introduction Why study Econometrics? What is Econometrics? Methodology of Econometrics

2 EE325 Introductory Econometrics2 Course Goals To provide students an understanding of why econometrics is necessary and a working ability with basic econometric tools such that: Students can apply basic econometric tools to estimation, inference, and forecasting in the context of real world economic problems Students understand how to process information from a sample of economic data Students can read critically the results and conclusions Students have a foundation for further study of advance econometrics.

3 EE325 Introductory Econometrics3 Why study Econometrics A gap exists between what you have learned as an economics student and what economists actually do Most economists engage in economic analysis (empirical: use economic data to estimate economic relationships, test economic hypotheses, and predict economic outcome) Studying Econometrics fills this gap

4 EE325 Introductory Econometrics4 What is Econometrics? “ Econometric is based upon the development of statistical methods for estimating economic relationship, testing economic theories, and evaluating and implementing government and business policy” (wooldridge p. 1) Econometrics is concerned with using data to test a theory or to estimate a relationship— empirical economic analysis.

5 EE325 Introductory Econometrics5 What is Econometrics? The study of Econometrics: Estimation of economic relationship Testing of hypotheses about economic theory Forecasting

6 EE325 Introductory Econometrics6 What is Econometrics? Econometrics has evolved as a separate discipline from statistics because - Rare in economics (and many other areas without labs!) to have experimental data. Econometrics focuses on the problems inherent collecting and analyzing nonexperimental, or observational, data - Economists have developed new techniques to deal with the complexities of economic data and to test the predictions of economic theories

7 EE325 Introductory Econometrics7 Methodology of Econometrics Steps in Empirical Economic Analysis 1. Formulation of the question of interest, statement of theory or hypothesis 2. Formulating a model (based on economic theory, past experience or intuition, other studies): -specification of the mathematical model of theory -specification of the statistical, or econometric model

8 EE325 Introductory Econometrics8 Methodology of Econometrics 3. Obtaining the data 4. Estimation of the parameters of the econometric model 5. Hypothesis testing 6. Forecasting or prediction 7. Policy decision

9 EE325 Introductory Econometrics9 Types of Data – Cross Sectional Cross-sectional data: Data collected over sample units in a particular time period Consists of a sample of individuals, households, firms, cities, states, countries, or a variety of other units, taken at a given point in time. for example: income by province in Thailand during 2006. (How many observation do we have?) Often obtained by random sampling from the underlying population

10 EE325 Introductory Econometrics10 Types of Data – Time Series Time series data: data collected over discrete intervals of time (observations on variable(s) over time) Time series data has a separate observation for each time period – e.g. annual gross domestic product of Thailand from 1980-2005 Since not a random sample, different problems to consider Trends and seasonality will be important

11 EE325 Introductory Econometrics11 Types of Data – Pooled cross sections & Panel Can pool random cross sections and treat similar to a normal cross section – known as pooled cross section data. Will just need to account for time differences. Can follow the same random individual observations over time – known as panel data or longitudinal data. (consists of time series for each cross-sectional member in the data set)


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