Form a monthly series from a quarterly series

Question

Assume that we have quarterly GDP change data like the following:

         Country
1999Q3   0.01
1999Q4   0.01
2000Q1   0.02
2000Q2   0.00
2000Q3  -0.01
<         


        

Answer 1

Convert to zoo with "yearmon" class index assuming the values are at the ends of the quarters. Then perform the rolling mean giving z.mu. Now merge that with a zero width zoo object containing all the months and use na.spline to fill in the missing values (or use na.locf or na.approx for different forms of interpolation). Optionally use fortify.zoo to convert back to a data.frame.

library(zoo)

z <- zoo(coredata(DF), as.yearmon(as.yearqtr(rownames(DF)), frac = 1))
z.mu <- rollmeanr(z, 2, partial = TRUE)
ym <- seq(floor(start(z.mu)), floor(end(z.mu)) + 11/12, 1/12)
z.ym <- na.spline(merge(z.mu, zoo(, ym)))

fortify.zoo(z.ym)

giving:

      Index      Country
1  Jan 1999 -0.065000000
2  Feb 1999 -0.052222222
3  Mar 1999 -0.040555556
4  Apr 1999 -0.030000000
5  May 1999 -0.020555556
6  Jun 1999 -0.012222222
7  Jul 1999 -0.005000000
8  Aug 1999  0.001111111
9  Sep 1999  0.006111111
10 Oct 1999  0.010000000
11 Nov 1999  0.012777778
12 Dec 1999  0.014444444
13 Jan 2000  0.015000000
14 Feb 2000  0.014444444
15 Mar 2000  0.012777778
16 Apr 2000  0.010000000
17 May 2000  0.006111111
18 Jun 2000  0.001111111
19 Jul 2000 -0.005000000
20 Aug 2000 -0.012222222
21 Sep 2000 -0.020555556
22 Oct 2000 -0.030000000
23 Nov 2000 -0.040555556
24 Dec 2000 -0.052222222

Note: The input DF in reproducible form used is:

Lines <- "         Country
1999Q3   0.01
1999Q4   0.01
2000Q1   0.02
2000Q2   0.00
2000Q3  -0.01"

DF <- read.table(text = Lines)

Update: Originally question asked to move last value forward but was changed to ask for spline interpolation so answer has been changed accordingly. Also changed to start in Jan and end in Dec and now assume data is for quarter end.