Dynare forums

Hi All,

I am estimating a medium scale DSGE model for a developing country with data limitations. The original model variables are expressed in per capital terms. I have some issues in observing per capita data for output, consumption, investment, government expenditure etc.
1. both population and employed population data is not available on quarterly frequency.
2. Many papers have used employed population or labour force to calculate per capita values. But even to do an interpolation of annual data, I can't get consistent annual data on this due to different area coverage in labour surveys at different years due to the civil war.

Given these facts I am left with 2 options.

1. use aggregate numbers as observables ( as in the original paper Medina and Soto (2007))
2. use an interpolated overall population series to calculate the per capita observables.

Can anyone suggest me the best option for me to get a better result?

Thank you.
Sujee

It depends on the size of population growth and your sample length. If there is significant population growth, I would be hesitant to use aggregate data. Given that population is typically a slow-moving series with not much business cycle frequency, smoothing or interpolation should work. See also my Guide to Observation Equations on my homepage on the population series in the US that has also its own issues.