within-transformation
eliminating alpha by sustracting from each variable for each unit the mean over time
Time series analysis
= time-ordered set of values of a variable x which was measured at several points in time
–> time-series on one/more variable/-s
Procedure of Time series
Formulation adn Estimation of time series model
- basic principle
time series decomposition
why does SPSS drop one dummy?
-
if all would be included, there would be perfect collinearity
–> the last dummy is captured by the constant, so all others refer to this dummy
–> if alpha exists: if there is noa lpha, we can include all dummys
Forecast error
the difference between the actual or real and the predicted or forecast value of a time series
–> the bigger k = the mor einto the future i look, the higher the forecasting error
Projection interval
Area in which the unknown value will lie with a certain probability
With 95% confidence are the values for YT+k within the predicted value 1 and value 2 in the period T+k
Panel data
= contain for the same observation units data for several points in time
disadv
Mannheim Innovation Panel
- why do they bother to do the calls for non-respondents?
- if there is a reason why companies are not responding, the results might be baised
Pooled regression
what does within-transformation do?
fixed effects disappear
fixed effects: individual heterogeneity
Hausman test
to assess whether to use fixed or random effects estimation
–> tests if the unobserved effects alphai are independent of the explanatory variables xj
Adv of FE model
the influences of all atributes that are constant over time are considered, irrespectve of whether or not they are observed
Herfindahl index
measure of concentration/ fragmentation
–> large H : large fragmentation (Monopol)
variable time in time series analysis
time can be seen as proceeding completely steadily and unaffected of any other events