st: RE: Calculating Moving Averages with Missing Values

["Nick Cox" <n.j.cox@durham.ac.uk>]

Consider this output 

. set obs 10
obs was 0, now 10

. gen t = _n

. gen y = _n

. tsset t
        time variable:  t, 1 to 10
                delta:  1 unit

. tssmooth ma y3 = y, w(1 1 1)
The smoother applied was
     (1/3)*[x(t-1) + 1*x(t) + x(t+1)]; x(t)= y

. tssmooth ma y5 = y, w(2 1 2)
The smoother applied was
     (1/5)*[x(t-2) + x(t-1) + 1*x(t) + x(t+1) + x(t+2)]; x(t)= y

. l

     +---------------------+
     |  t    y    y3    y5 |
     |---------------------|
  1. |  1    1   1.5     2 |
  2. |  2    2     2   2.5 |
  3. |  3    3     3     3 |
  4. |  4    4     4     4 |
  5. |  5    5     5     5 |
     |---------------------|
  6. |  6    6     6     6 |
  7. |  7    7     7     7 |
  8. |  8    8     8     8 |
  9. |  9    9     9   8.5 |
 10. | 10   10   9.5     9 |
     +---------------------+

-tssmooth ma- fills as best it can at the ends of series (which is _not_
the same as treating missings as 0s, as otherwise the results above
would not be obtained). 

Jeff can override the results of -tssmooth- if he doesn't want that. 

replace y3 = . if missing(L1.y, F1.y) 
replace y5 = . if missing(L1.y, L2.y, F1.y, F2.y) 

For example, L1.y is missing at the beginning of a series y and F1.y at
the end. This works with panel data too. 

A user-written alternative to -tssmooth- is the -egen- function
-filter()- from -egenmore-. 

Alternatively, please spell out whatever way of dealing with ends you
prefer. 

Nick 
n.j.cox@durham.ac.uk 

J.M.Chwieroth@lse.ac.uk

When I use the tssmooth function to create 2 or 5 year moving averages,
Stata calculates these moving averages until the end of the time-series
rather than stopping 1 year (in the case of the 2 year moving average)
or 4 years (in the case of the 5 year moving average) before the end of
the time-series? It thus counts forward missing values as zero.    Would
you know a possible strategy to fix  this problem?


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