C1.Introduction to Eco No Metrics
Transcript of C1.Introduction to Eco No Metrics
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Introduction
to
Econometrics
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What is econometrics? Econometrics is a set of research tools employed in various
economic fields (accounting, finance, marketing and
management) and also in history, political science, and
sociology.
Econometrics means economic measurement> from the
Greek words: eikonomia economy andmetren measure.
It plays a special role in the training of the economists by:
quantifying the economic reality
bridging the gap between economic theory and the real
world.
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Econometrics may be defined as the social science that applies
the tools ofeconomic theory,mathematicsandstatistics for
estimating economic relationships, testing the validity of
economic theories and validating the government policies.
Example.
The Central Bank rises the discount rate by 3%economic theory suggests this will influence the interest rates of
the commercial banks, the credits, the investments, the inflation
but how much?Only econometrics can answer this question by combining
economic theory, statistical data and mathematical tools!
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Why study econometrics?
Economic theory makes statements about how important
variables are related to one another, but:
does not provide the necessary measure of strength of the
relationship or
the magnitudes involved (how much a change in one
variable affects another).
Example
The law of demand: a reduction in price of a commodity isexpected to increase the quantity demanded of that
commodity (but how much?).
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Economic model vs econometric model
An economic model is a set of assumptions that aproximately
describes the behaviour of an economy.
An econometric model gives:
the form of the algebraic relationships among the economicvariables involved and
a specification of the errors (due to the factors omitted from
the model)
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1.Quantity demanded, qd, for an individual commodity (Ford cars):
qd = f( p, pc, ps, i )
p = price of the car; pc = price of complements (like gasoline);
ps = price of substitutes (other similar cars); i = income
demand
2. Quantity supplied, qs (beef):
qs = f( p, pc, pf, ps )
p = price of beef; pc = price of complements ;
ps = price of substitutes (pork); pf = price of inputs (e.g. corn)
supply
The economic model(describes the way in which economic variables are interrelated).
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The econometric model
qd = f( p, pc, ps, i ) + e
The random error accounts for the many factors that affectsales and miss from this model; it is a noise component thatobscures our understanding of the relationships.
Assuming quantity demanded is a linear function of prices, theeconometric model of the demand for Ford cars is :
qd = 1+ 2p+ 3pc+ 4p
s+ 5i + e,
where i are unknown parameters to be estimated usinga sample of economic data.
The systematic part(the average behavior)
Therandomerror(theunpredictablepart)
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Limits of econometrics
any econometric model can capture only a part of thereal economic world => a simplified image of the reality;
qualitative variables (like motivation, satisfaction,
management) are difficult to incorporate in aneconometric model;
imperfect identification of the contribution of each factor
of influence (because factors interact and influences aredifficult to separate);
forecasting based on past trends is uncertain.
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1 2 2
2
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1 2
dependent
(endogeneous)
variable explanatory (exogeneous) variable
parameters
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1 2
1 1
2 2 2
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God created the econometricians to makeGod created the econometricians to make
weather forecasts look good .weather forecasts look good .
The value of the explanatory variable (Yd) is known
Estimated values of the parameters
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Economic Empirical Study
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Economic Empirical Study
(anatomy of econometric modeling)
Economic Theory; Past Experience, studies
Formulating a model: Cause - effect C = f(Y) ==>Ct = 1 + 2Y + et
Gathering data: Statistics monthly, quarterly, yearly data
Estimating the model: Simple OLS method or other advances
Testing the hypothesis:H0:2>0,
positive relationship or not If not true
Interpreting the results:
Forecasting Policy implication and decisions
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Types of econometric models
1. Considering the number of influence factors simple models are based on the assumption of a single
decisive factor of influence X, all the others havingrandom or fixed effects captured by the error term e.
y = f(x)+e
multiple models: use two or more factors of influence;better but more complicated => the number of factorshave to be limited.
y = f(x1,x
2,...,x
p)+e
2. Considering the form of the relationship betweenthe dependent variable y and the factors ofinfluence linear models
non-linear models: exponential, parabolic, etc.
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Types of econometric models (contd)
3. Considering the time factor- static models: the factors influence the dependentvariable y over the same period of time:
y = f(x1t,...,xjt,...,xkt) + et
- dynamic models include the time variable: the time variable is one of the factorsy = f(xt,t) + et
autoregressive models: the lagged dependent variablebecomes a factor of influence itself
y = f(xt,yt-k) + et lagged models: the factor x influences y over several
periods of time:
y = f(xt,xt-1,... xt-k) + et
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Types of econometric models (contd)
4. Considering the number of equations
- models having a single equation
- multiple equation models: consist of a system of
equations
-> structural form:
dependent (endogenous) variabiles
independent (exogenous) variabiles
===
nmnmnnnnn
mmnn
mmnn
UXcXcXcYYbYb
UXcXcXcYbYYb
UXcXcXcYbYbYb
......
......
......
22112211
2222212122121
112121111212111
niYi ,, 1
mjXj ,, 1