Lecture 1. Introduction to Econometrics

Сентябрь 11, 2022

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Lecture 1. Introduction to Econometrics

Содержание

2. The Subject of Econometrics Econometrics is the application of statistical methods to the quantification and critical
3. The Aims and Approaches of the Course The aims of the course are: - To develop
4. Methodology of Econometrics: 1. Statement of Theory or Hypothesis 2.Specification of Mathematical Model 3. Specification of
5. Economic Relationships and Models Considered in the Course Demand and Supply functions; Earnings functions; Production functions;
6. Econometric Analysis of ICEF Students UoL Exams Results Elements of Econometrics, 2012-2014 The model specification for
7. The Questions on the Model to be answered in the Course Is the model specification reliable?
8. Time Series Example: Price of Oil (Brent) and RuR/USD Exchange Rate (01/09/14-31/08/15) The relationship is available
9. Reading Main Textbook: Dougherty, Christopher. Introduction to Econometrics. Oxford University Press, 2011, 2006 (4th or 3rd
10. Main Electronic Resources: ICEF Information System: http://icef-info.hse.ru University of London site: http://www.londoninternational.ac.uk/community/students VLE Student Portal: http://my.londonexternal.ac.uk/london/portal
11. Statistical Glossary for Econometrics: Descriptive statistics: Mean, variance, standard deviation, covariance, correlation Random variables, Probability distributions:
12. Example: Plim rules Plim rule 1 plim (X + Y) = plim X + plim Y
13. Notation in the course (examples) Greek letters – true values, latin (or greek with hats) -
14. Types of Data and of Regression Model Data: cross-sections, time series, panel data. Model A: cross-sectional
15. Some issues which are important in applied analysis Correct specification (functional form, regressors availability) Endogeneity Sample
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The Subject of Econometrics
Econometrics is the application of statistical methods to

the quantification and critical assessment of hypothetical economic relationships using data.
The Art of Econometrician: Finding the set of assumptions which are sufficiently specific and realistic in order to take the best possible advantage from the data available. (E.Malinvaud).

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The Aims and Approaches of the Course
The aims of the

course are:
- To develop an understanding of the use of regression analysis for quantifying economic relationships and testing economic theories.
- To equip for reading and evaluation of empirical papers in professional journals.
To provide practical experience of using econometric software to fit economic models (Econometric Views will be used).

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Methodology of Econometrics:
1. Statement of Theory or Hypothesis
2.Specification of Mathematical Model
3.

Specification of Econometric Model
4. Obtaining the Data
5. Estimation of the Parameters
6. Hypothesis Testing
7. Forecasting or Prediction
8. Using the Model for Control or Policy Purposes

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Economic Relationships and Models Considered in the Course
Demand and Supply functions;
Earnings

functions;
Production functions;
Cost functions;
Economic growth models;
Educational attainment functions;
Consumption functions;
Investment functions;
Macroeconomic equilibrium models;
Academic success functions.

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Econometric Analysis of ICEF Students UoL Exams Results
Elements of Econometrics,

2012-2014
The model specification for 2012:
EOE_UOL = 4.01 + 0.51 EOE_ICEF + 0.38 MACMIC_UOL + e
(1.01) (6.96) (4.09)
(t-statistics are in parentheses; R2 = 0.76; 92 observations in the sample).
The model specification for 2013:
EOE_UOL = 7.79 + 0.44 EOE_ICEF + 0.56 MACMIC_UOL + e
(2.31) (7.16) (5.80)
(t-statistics are in parentheses; R2 = 0.70; 132 observations in the sample).
The model specification for 2014:
EOE_UOL = 6.36 + 0.35 EOE_ICEF + 0.59 MACMIC_UOL + e
(1.51) (3.52) (5.68)
(t-statistics are in parentheses; R2 = 0.61; 114 observations in the sample).
EOE_UOL – UoL exam grade in Econometrics,
EOE_ICEF – the average of ICEF Econometrics exams grades in October, December and March,
MACMIC_UOL – the average of UoL grades in Micro- and Macroeconomics.

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The Questions on the Model to be answered in the

Course

Is the model specification reliable? How to interpret it?
How to interpret the explanatory variables? Why and how do they influence the UoL grades?
Does the model stay the same year by year? How to test this?
Are there other factors missing, which ones, and how does this influence the outcome?
Are there other links between the model variables? Does it influence the conclusions?
Can we use the model for predictions?

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Time Series Example: Price of Oil (Brent) and RuR/USD Exchange

Rate (01/09/14-31/08/15)
The relationship is available but there are questions to answer:
Were there other factors to be included in the model?
What was the time structure of the relationship (lags, trends, autocorrelations, etc)?
Was the reaction the same or changed in time?
Could the behaviour of the series in time (e.g. stationarity) influence the conclusions?

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Reading
Main Textbook:
Dougherty, Christopher. Introduction to Econometrics. Oxford University Press, 2011,

2006 (4th or 3rd edition). Russian translation: Доугерти Кр. Введение в эконометрику. Изд.3. М., ИНФРА-М, 2009.
Student resources for the book (Data sets, slides, Study Guide): VLE
Additional Textbooks:
Gujarati D.N. Basic Econometrics.
Wooldridge J.M. Introductory Econometrics. A modern approach.
Study Guides:
Dougherty, Christopher. Elements of econometrics. Study Guide. University of London. 2014.
ICEF materials: Lecture Notes, Slides, Class Notes, Exam Materials (ICEF Information System).
Other reading: see the Course Syllabus, ICEF.

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Main Electronic Resources:
ICEF Information System: http://icef-info.hse.ru
University of London site: http://www.londoninternational.ac.uk/community/students
VLE

Student Portal: http://my.londonexternal.ac.uk/london/portal Course EC2020 Elements of econometrics
Oxford University Press: www.oup.com/uk/orc/bin/9780199567089
http://crow.academy.ru/econometrics - many useful materials
ICEF Computer Classes (desktops): «Хрестоматия по Эконометрике»

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Statistical Glossary for Econometrics:
Descriptive statistics: Mean, variance, standard deviation, covariance,

correlation
Random variables, Probability distributions: Discrete and Continuous, Uniform, Normal, t-, F-, χ2 - distributions. Expected value, population variance and covariance. Independence.
Sampling : Population, sample. Sample selection.
Estimation: Estimator, estimate. Unbiasedness (expected value), consistency (probability limit), efficiency. Central limit theorem.
Statistical Inference: Hypothesis testing. Significance tests, significance levels. Power of a test, Type I and Type II errors. t-tests, F-tests. Confidence intervals. P-values. One-sided and two-sided tests.
Data types: Cross-section, time series, panel.
Rules: variance, covariance and probability limit rules.

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Example: Plim rules
Plim rule 1 plim (X + Y) = plim

X + plim Y
Plim rule 2 plim bX = b plim X
Plim rule 3 if b is a constant, plim b = b
Plim rule 4 plim Z = (plim X)(plim Y)
Plim rule 5
Plim rule 6 plim f(X) = f(plim X)

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Notation in the course (examples)
Greek letters – true values, latin (or

greek with hats) - estimators
var(X) = σx2 – population variance of X
Var(X)= - sample variance
Sx2 = - unbiased estimator of
population variance

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Types of Data and of Regression Model
Data: cross-sections, time series,

panel data.
Model A: cross-sectional data with nonstochastic regressors. Their values in the observations are fixed and do not have random components.
Model B: cross-sectional data with stochastic regressors. The regressors’ values are drawn randomly and independently from defined populations.
Model C: time series data. The regressors’ values may exhibit persistence over time
Regressions with panel data will be treated as an extension of Model B.

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Some issues which are important in applied analysis
Correct specification (functional form,

regressors availability)
Endogeneity
Sample selection
Sample size
Multicollinearity
Nonstationary Time Series
Unobserved Heterogeneity

Lecture 1. Introduction to Econometrics

Содержание

The Subject of EconometricsEconometrics is the application of statistical methods to

The Aims and Approaches of the CourseThe aims of the

Methodology of Econometrics:1. Statement of Theory or Hypothesis2.Specification of Mathematical Model3.

Economic Relationships and Models Considered in the CourseDemand and Supply functions;Earnings

Econometric Analysis of ICEF Students UoL Exams ResultsElements of Econometrics,

The Questions on the Model to be answered in the

Time Series Example: Price of Oil (Brent) and RuR/USD Exchange

ReadingMain Textbook: Dougherty, Christopher. Introduction to Econometrics. Oxford University Press, 2011,

Main Electronic Resources: ICEF Information System: http://icef-info.hse.ru University of London site: http://www.londoninternational.ac.uk/community/studentsVLE

Statistical Glossary for Econometrics:Descriptive statistics: Mean, variance, standard deviation, covariance,

Example: Plim rules Plim rule 1 plim (X + Y) = plim

Notation in the course (examples)Greek letters – true values, latin (or

Types of Data and of Regression Model Data: cross-sections, time series,

Some issues which are important in applied analysis Correct specification (functional form,

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