For our replication project, Justin Grimmer and I have been exploring missing data problems. We were given a data set by the authors that was stripped of most identifiable information. Alas, it retains only those variables necessary for the authors' OLS regressions, even though it has a rich data history: it was produced by merging 1990 Census data with a detailed 1986 survey of municipalities. The authors omitted any unique variable that would let us link back to the original databases, a copy of which we have in our possession. To identify the missing data points (the unit of analysis is municipalities), we are trying to link the data table they used in their regressions with the 1986 raw data or the 1990 Census. Lacking a unique identifier, we have been unable to get an exact match, but we have been trying to link on the following variables: -Log of 1990 Census population--rounded to either 2 or 3 decimal pts. (The problem here is that increasing precision captures rounding errors between the two data sets, while decreasing precision leads to too many false matches when we merge.) Because the authors rounded the log of population to 3 (or so) decimal points, we get rounding errors if we just try to exponentiate. -Census region -A variety of dummy variables for various survey responses. These have been only somewhat useful since they are not a unique identifier. -We think that the states are listed in alphabetical order in their data table (based on the sequencing of regions) but we aren't sure how to use this fact. Linking on any combination of these produces either too few identifiable matches or too many. We've been using the merge() function in R. It seems to work okay but it is not good at identify what's causing mismatches. We have gotten close to linking the 1990 Census data with the 1986 survey, but this only gets us to their first step; it doesn't let us work backward to match with their table. Has anyone on the list dealt with such a problem in the past? Any suggestions are greatly appreciated. We're considering going back to the authors, but we suspect they may not have what we need. Thanks, Clayton and Justin _______________________________________________ gov2001-l mailing list gov2001-l(a)lists.fas.harvard.edu http://lists.fas.harvard.edu/mailman/listinfo/gov2001-l