Professor King and other ei practitioners: I am hoping for some clarification and/or advice. My polisci colleague and I study political movements and elections in Ecuador. We have analyzed some of the results of the 2002 elections there, primarily the votes for President in the first and second rounds. We are particularly interested in the voting differences between indigenous peoples (hereafter Indians) and others (mestizos, blanco-mestizos, etc.). I won't go into the methodological problems of estimating ethnicity here. We have the data at the parish level (the closest thing to a precinct) and have looked at the relationship between %Indian and % voting for Presidential Candidate G, who was in an alliance with an indigenous-led political movement. The hypothesis is simple: a larger % of Indians should vote for candidate G than should non-Indians. For the 943 parishes we first ran the "Goodman regression" and find that the estimate for the proportion of Indians casting their vote for candidate G is .465 and for non-Indians it is .163. Then, using the ezi program we run the regular or first-stage ei and the "Aggregate Quantities of Interest" are .463 for Indians and .164 for non-Indians. These results, and others, are very close between the "no-intercept" OLS regression and ei. So, it seems we have two results: 1) a much higher proportion of Indians voted for candidate G than did non-Indians and, 2) there is not an "ecological fallacy" or aggregation problem with that conclusion. The thing is, we have a very important "control" variable - region. There are very strong regional differences in Ecuador in voting patterns. There are three regions: Coast, Sierra, and Oriente (jungle). The third is not very important since only 3% of the population lives there. Candidate G is a Sierra (and Oriente) candidate and he did not receive a lot of support on the Coast (especially in the first round). This confounds the ethnic differences because Indians live overwhelmingly in the Sierra, not on the coast. I have read numerous other articles using ei, including those going on to a "second-stage" and the exchange between Herron and Shotts and Adolph and King. But we are not interested in analyzing the variance in the ei estimates of the proportion of Indians voting for candidate G across the parishes, which is the equivalent of what the other researchers have been doing. If the ecological inference issue has been resolved, i.e., a higher % of Indians really did vote for candidate G than did non-Indians, would it not be appropriate to just return to simple OLS regression if I want to explain variance in votes for candidate G across parishes, with %Indian and two dummy variables representing the Coast and Oriente regions of Ecuador? This is to resolve the question of whether a higher proportion of Indians voted for candidate G in the Sierra than did non-Indians, which is the case. By the way, we also estimated this by "regular" ei by just using the parishes in the Sierra, which once again produced estimates very close to the Goodman regression. SO, I JUST WANT TO KNOW WHETHER USING OLS REGRESSION WITH OUR ORIGINAL DEPENDENT VARIABLE, THE %INDIAN PREDICTOR AND A COUPLE OF CONTROL VARIABLES IS AN ACCEPTABLE APPROACH. (By the way, in the OLS regressions we do weight the cases by size of parish). I appreciate any comments, Scott H. Beck, Professor Department of Sociology and Anthropology East Tennessee State University Johnson City, TN 37614 Tel.: 423-439-6648 Email: r30scott(a)etsu.edu