Time series data means data has been collected over time such as from 1980 to 2009 while cross section data means data has been collected at a particular point of time. Such as, 400 managers perception in a particular time such as year 1980.
When we run the regression line, the residual of the model may be serially correlated (which is not desirable) if the data or variable is time series type. Normally heteroscadasticity does not arise when the data is time series type.
But when we run the regression line, the residual of the model may be heteroscedastic (which is not desirable)if the data is cross section type. Normally serial correlation or auto-correlation does not appear when the data is cross section type.
1 comment:
Respected Sir sayed.
your website is really helpful for the students of eviews.you have done really a good job. i have a problem. in my model i have a restriction that sum of the coeffients of two varaibles is equal to one. how can i incorporate this. please explain i would be very thankful to you.
waiting for your reply
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