DYNAMIC ECONOMETRIC
MODELS
Dr. C. Ertuna
DEFINITION
In Dynamic Econometric Models time plays a
central role. Past (lagged) values of dependent
or independent variables are introduced in the
model to describe the underlying process.
Dr. C. Ertuna
TYPES of DYNAMIC MODELS
In general there are three types of dynamic models:
a) Distributed Lag Models: Models that include
lagged values of independent variables.
i.
ii.
The Koyck Transformation
The Almond Transformation
b) Autoregressive Models: Models that include
lagged values of dependent variables.
i.
ii.
The Partial Adjustment Model
The Adaptive Expectations Model
c) Autoregressive Distributed Lag Models:
Dr. C. Ertuna
REASONS for LAGGED VALUES
1. Habit (Psychological inertia)
2. Transition / Time to Adjust
3.Technical or Technological Reasons causing
delay in change.
4.Institutional Reasons (such as contracts)
Dr. C. Ertuna
USE of DISTRIBUTED LAG MODELS
1. Impact of Advertising (over several periods)
on (current) Sales
2. Impact of Safety Training on Accidents.
3.Impact of Marketing Mix on Market Share.
4.Impact of Air Pollution on Mortality Rate.
Dr. C. Ertuna
DISTRIBUTED LAG MODELS and
NUMBER of LAGS
Too many lags may cause multicollinearity and
lost of degrees of freedom. In general there are
two approaches to overcome those problems:
a) Koyck Transformation
b) Almond Transformation
Dr. C. Ertuna
Koyck Transformation
• Koyck assumes geometric decline and same sign in βs.
Following Asteriou and Hall (page 206-207) we can
convert infinite distributed lag model with
geometrically declining βs into following form:
• 𝑌𝑡 = 𝛼 1 − 𝜆 + 𝛽0 𝑋𝑡 + 𝜆𝑌𝑡−1 + 𝑣𝑡
where,
λ = speed of decline (adjustment coefficient)
β0 = immediate effect
β0
= long_run effect
1−λ
vt = ut − λut−1
Dr. C. Ertuna
DISTRIBUTED LAG MODELS and
OLS REGRESSION
To estimate Distributed Lag Models OLS
Regression can be used.
The results are BLUE as long as the residuals do
not exhibit autocorrelation.
Dr. C. Ertuna
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