Introduction
Advanced Econometrics - HEC Lausanne
Christophe Hurlin
University of Orléans
October 2013
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
1 / 27
Instructor
Christophe Hurlin
Contact
christophe.hurlin@univ-orleans.fr
Teaching assistant
Sara Cavalli
Personal website
https://hec.unil.ch/docs/index.php/churlin/cours/512/session_1461
Personal website
http://www.univ-orleans.fr/deg/masters/ESA/CH/churlin_E.htm
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
What is econometrics? Not an easy question!
Main objective of this course is to de…ne this term!
Econometrics can be de…ned as the statistical analysis of economic
(…nancial) phenomena.
"Econometrics is the quantitative analysis of actual economic
phenomena based on the concurrent development of theory and
observation, related by appropriate methods of inference", P. A.
Samuelson, T. C. Koopmans, and J. R. N. Stone (1954)
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Econometrics is fundamentally based on four elements:
1
A sample of data
2
An econometric model
3
An estimation method
4
Some inference methods
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Question: Why using a sample?
Let us assume that we want to study a characteristic / property x
of the individuals of a population.
The individuals (unit) of the population are not necessarily some
persons: it can be …rms, assets, countries, time index etc..
The characteristic x may be quantitative (salary, weight, total asset,
GDP etc.) or qualitative (social status, genre etc.)
The characteristic x may be stochastic or deterministic (weight,
size etc..).
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
In the case of a population of
two individuals, inference,
econometrics, etc (and this
course.).. are useless.
Let us imagine that Adam
weighs 80 kg and Eve 50 kg...
Adam and Eve, Titian (1490-1576)
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Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
When the population is large
or in…nite, sampling is the
only mean to study the weight
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Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
De…nition (Population)
A population can be de…ned as including all people or items with the
characteristic one wishes to understand.
1
In most of cases, it is impossible to observe the entire statistical
population, due to cost constraints, time constraints, constraints of
geographical accessibility.
2
A researcher would instead observe a statistical sample from the
population in order to attempt to learn something about the
population as a whole.
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
In most of cases, the sample is random:
De…nition (Probability sampling)
A probability sampling is a sampling method in which every unit in the
population has a chance (greater than zero) of being selected in the
sample.
Consequence: a sample is a collection of random variables even the
characteristic x is deterministic.
sample: fX1 , X2 , ..., XN g
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Example (random sample)
Let us consider a population of four persons and denote by e
x the weight
(assumed to be non stochastic) of the individual with:
e
xA = 80 e
xB = 50 e
xC = 40 e
xD = 90
Consider a random sample of N = 2 individuals denoted by
8
9
<
=
X1
, X2
|{z}
:
;
Weight of the …rst indi. selected in the sample
So we can obtain a realisation
fx1 , x2 g = f50, 80g or fx1 , x2 g = f90, 40g or fx1 , x2 g = f90, 90g etc.
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Fact
Whatever the assumption made on the characteristic X (deterministic or
stochastic) the result of the probability sampling is a random sample, i.e.
a collection of random variables X1 , X2 , .., XN .
Fact
Given the sampling probability method used, we can assume that these
random variables are independent and identically distributed (i.i.d.).
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Fact
In general, in economics and …nance, only one realisation of the sample
is available: this is your data set!
fx1 , x2 , .., xN g
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Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
The challenge of econometrics and mathematical statistic is to draw
conclusions about a population (or the true DGP) after observing only one
realisation fx1 , ..xN g of a random sample (your data set..).
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
In econometrics, data come from one of the two sources: experiments and
non experimental observations
1
Experimental data are based on (randomized controlled)
experiments designed to evaluate a treatment or policy or to
investigate a causal e¤ect.
2
Data obtained outside an experimental setting are called
observational data (issued from survey, administrative records etc...)
All of this lecture is devoted to methods for handling real-world
observational data
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Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Whether the data is experimental or observational, data sets can be mainly
distinguished in three types:
1
Cross-sectional data
2
Time series data
3
Panel data
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Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Cross-sectional data:
Data for di¤erent entities: workers, households, …rms, cities,
countries, and so forth.
No time dimension (even if date of data collection varies somewhat
across units, it is ignored).
Order of data does not matter!
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Time series data:
Data for a single entity (person, …rm, country) collected at multiple
time periods. Repeated observations of the same variables (GDP,
prices).
Order of data is important!
Observations are typically not independent over time;
In this case the notion of population corresponds to the Data
Generating Process (DGP).
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Panel data or longitudinal data:
Data for multiple entities (individuals, …rms, countries) in which
outcomes and characteristics of each entity are observed at multiple
points in time.
Combine cross-sectional and time series issues.
Present several advantages with respect to cross-sectional and time
series data (depending on the question of interest!).
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Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
De…nition (Econometric model)
An econometric model speci…es the statistical relationship that is believed
to hold between the various economic quantities pertaining to a particular
economic phenomenon under study.
An econometric model can be derived from a deterministic economic
model by allowing for uncertainty, or from an economic model which
itself is stochastic.
However, it is also possible to use econometric models that are not
tied to any speci…c economic theory.
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
We can distinguish:
1
Parametric model: the relationship (joint probability distribution)
between the dependent variable /vector Y and the explicative
variables X is fully characterised by a set of parameters θ
Y = f (X ; θ ) + ε
where link function f (.) is assumed to be known.
2
Non parametric and semi-parametric models: the link function
can not be described using a …nite number of parameters. The link
function is assumed to be unknown and has to be estimated.
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
The general approach of econometrics is the following:
1
Step 1: Model speci…cation
2
Step 2: Estimation of the parameters
3
Step 3: Validation
1
2
3
4
4
Signi…cance tests;
Speci…cation tests;
Backtesting (forecasting performances);
Etc.
Step 4: Use of the model (forecasting, feedback on the building of
the model, etc.)
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Objectives of the course
The objective of this course are mainly related to the steps 2 (Estimation)
and 3 (Validation)
More speci…cally:
1
To provide a global understanding of modern econometric methods;
2
To give a critical assessment of the presented methods;
3
To constitute an introduction and a basis for the more speci…c
econometric courses of the Masters.
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
References
Amemiya T. (1985), Advanced Econometrics. Harvard University Press.
Greene W. (2007), Econometric Analysis, sixth edition, Pearson - Prentice
Hil (recommended)
Johnson J., Econometric Methods, 3rd edition, MacGraw-Hill
Pelgrin, F. (2010), Lecture notes Advanced Econometrics, HEC Lausanne (a
special thank)
Ruud P., (2000) An introduction to Classical Econometric Theory, Oxford
University Press.
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Advanced Econometrics - HEC Lausanne
October 2013
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Introduction
Course outline
Chapter 1: Estimation theory
Chapter 2: Maximum Likelihood Estimation (MLE)
Chapter 3: The multiple linear regression model: the Ordinary Least
Squares (OLS) estimator
Chapter 4: Inference and statistical hypothesis testing
Chapter 5: The Generalized Least Squares (GLS) estimator
Chapter 6: Endogeneity, error-in-variables and the Instrumental Variables
(IV) estimator
Chapter 7: The Generalized Method of Moments (GMM)
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
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End of the general introduction
Christophe Hurlin (University of Orléans)
Christophe Hurlin (University of Orléans)
Advanced Econometrics - HEC Lausanne
October 2013
25 / 27
Course rules
Your grade will be determined based on the following criteria:
Final Exam (F) (compulsory)
Mid-term (MT) (optional)
Retake exam (RE) (compulsory if necessary).
Two cases:
1
Without retake exam, the …nal grade is given by:
GRADE = 0.7 F + 0.3 max(MT , F )
2
With a retake exam, the …nal grade is given by
GRADE = 1 RE
In other words, if you need to redo the exam, then the grade will be simply
based on the make-up exam grade - the mid-term exam no longer counts.
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Advanced Econometrics - HEC Lausanne
October 2013
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Course rules
1
The …nal exam and the retake exams cover the entire course
(including the exercises). The mid-term exam covers the parts
indicated by the instructor.
2
All exams (mid-term, …nal, and retake exams) are closed book.
3
All type of calculator is authorized for all the exam.
4
The duration of the …nal exam and the retake exam is 180 minutes.
The midterm is 120 minutes.
5
Careful and clear justi…cation of your answers will be rewarded. The
solution approach has to be clear to the grader. In particular,
(numerical) results without analytical derivations receive no grade.
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Advanced Econometrics - HEC Lausanne
October 2013
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