Timeline for Convert annual data to quarterly frequency
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 8, 2013 at 9:37 | comment | added | Nick Cox | This answer is a totally sensible statistical answer in my view to the question as originally posed. What was not well explained until the answer by @Analyst is that you must have data in some other variable on quarterly variations for this to be possible. Even then the method is, and can only be, a stretch. (This activity is standard is certain parts of economics.) | |
| May 7, 2013 at 1:03 | comment | added | Peter Ellis | It won't just be seasonally adjusted, it will also have the quarterly randomness removed (which is surely precisely what is needed if you are fitting a quarterly model). So it will be equivalent to a trend series from a decomposition. | |
| Apr 11, 2013 at 21:51 | comment | added | mr.rox | Yes, but seasonality will have to be removed anyway before running a regression. my disaggregated data might not have the same properties as that of original quarterly data, but it will be a seasonally adjusted version of the original quarterly data. | |
| Apr 9, 2013 at 20:16 | comment | added | Peter Ellis | My point is that it isn't possible to disaggregate annual to quarterly. That is, there is no possible way to recreate the first of my two plots if all you have is the data for the second. Anyway, good luck with your analysis. | |
| Apr 9, 2013 at 14:43 | comment | added | mr.rox | Dear @Peter Ellis, I am actually disaggregating annual to quarterly. Many thanks for your time! | |
| Apr 6, 2013 at 23:41 | comment | added | Peter Ellis | Well, you can do what in effect the second plot does by interpolating lines between each point and call that "quarterly" data but it still isn't really quarterly data - it has no resemblance to the top plot. So if you put it into a model that expects real quarterly data you will get a misleading result. I think you would be better off taking your other variables' quarterly data and aggregating it to annual. This is a more honest approach to the limitations of the actual data you are unfortunately stuck with. | |
| Apr 6, 2013 at 23:30 | comment | added | mr.rox | Many thanks Peter Ellis, I have used this method before, I will just disaggregate the annual data into four quarterly values, the last value will be the same figure as in the annual figure for the year. When you plot the resulting quarterly series, it will overlap the annual figures preserving the original information. I know eviews has option to use cubic splines to do this job, but I am not sure how safe it is to apply it in an empirical research article. | |
| Apr 6, 2013 at 21:42 | history | answered | Peter Ellis | CC BY-SA 3.0 |