Hi Sergio, you can adjust the coarsening rather than using the defaults in CEM.  more coarse bins will generate more observations.  you want to make the choices based on the substance of the variables, and which ones are more important to match finely on

Gary
--
Gary King - Albert J. Weatherhead III University Professor - Director, IQSS - Harvard University
GaryKing.org - King@Harvard.edu - @KingGary - 617-500-7570 - Assistant: 617-495-9271

On Wed, Apr 5, 2017 at 10:04 AM, Sergio Salis <Sergio.Salis@natcen.ac.uk> wrote:

Hi all,

 

I’m considering using the cem Stata programme to evaluate the impact of a welfare-to-work programme in the UK. However, I have never used cem before so I am trying to understand some basic issues before proceeding with the estimation.

 

The first thing I’d be interested in understanding is: How does one handle situations where after running cem the number of matched strata (and units within them) are very small?

 

Applying the cem algorithm to data from a previous impact evaluation I get:

 

Number of strata: 8883

Number of matched strata: 132

 

             0     1

      All                            8208  1584

  Matched                     179   141

Unmatched               8029  1443

 

If I calculate the ATT using cem matched data I get an impact estimate which is positive (around 5ppts; based on 320 obs only) while using psmatch2 on all data (i.e. not only those in cem matched strata; around 8,237 obs are used) with kernel weights I get an estimate of around -5.7ppts. This means I reach opposite conclusions about the impact of the programme of interest using cem and psmatch2.

 

I understand the cem-based estimates are based on better matched data (i.e. produce less biased estimates) compared to my psmatch2 estimate with kernel weights) but this comes at the expense of external validity: inference on the initial population is made based on a very small subset of data (estimates based on cem are not statistically significant while my original estimate was highly significant). Any advice about how one can handle situations of this type?

 

Many thanks,

Sergio

 

 


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