1. DYNAMIC ECONOMETRIC MODELS
Dr. C. Ertuna

2. 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

3. TYPES of DYNAMIC MODELS
In general there are three types of dynamic models:
Distributed Lag Models: Models that include lagged values of independent variables.
The Koyck Transformation
The Almond Transformation
Autoregressive Models: Models that include lagged values of dependent variables.
The Partial Adjustment Model
The Adaptive Expectations Model
Autoregressive Distributed Lag Models:
Dr. C. Ertuna

4. REASONS for LAGGED VALUES
Habit (Psychological inertia)
Transition / Time to Adjust
Technical or Technological Reasons causing delay in change.
Institutional Reasons (such as contracts)
Dr. C. Ertuna

5. USE of DISTRIBUTED LAG MODELS
Impact of Advertising (over several periods) on (current) Sales
Impact of Safety Training on Accidents.
Impact of Marketing Mix on Market Share.
Impact of Air Pollution on Mortality Rate.
Dr. C. Ertuna

6. 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:
Koyck Transformation
Almond Transformation
Dr. C. Ertuna

7. Koyck Transformation
Koyck assumes geometric decline and same sign in βs. Following Asteriou and Hall (page ) we can convert infinite distributed lag model with geometrically declining βs into following form:
𝑌 𝑡 = 𝛼 1−𝜆 + 𝛽 0 𝑋 𝑡 + 𝜆 𝑌 𝑡−1 + 𝑣 𝑡
where,
λ=speed of decline (adjustment coefficient)
β 0 =immediate effect
β 0 1−λ =long_run effect
v t = u t − λ u t−1
Dr. C. Ertuna

8. 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

9. END