I am looking at CPI datasets for developing countries which have gaps in them.
For each country I have two time-series with annual averages for years 2000-2013: i) General/Overall CPI and ii) Food CPI. I'm also assuming that Food CPI must have some relationship with the General/Overall CPI since the Food category has its own weight in the General CPI.
Now, I have two types of cases, some such as: http://imgur.com/a/9z7o8#1 where gaps are between values. I'm assuming I can interpolate here, if so, how would I go forward with this? I also have to deal with more complicated cases such as: http://imgur.com/a/9z7o8#0, any suggestions in this case? Would a simple extrapolation even make sense here?
An option for my first case that I read (on BLS) is taking the geometric mean of the year immediately before and after of the missing value. Other people have suggested I should predict the missing values by a simple regression model of the CPI on the GDP deflator for that year (which I do have).
Also, in some cases, gaps in annual averages exist because the monthly data needed to calculate these averages is incomplete. So say I only have 2006 data for Russia for months Jan-June, then the annual average data point is missing in the data series. I assume I can just take a simple average of the available months and impute that for 2006?
Thanks in advance