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bdecon / econ_data

Python 3 examples of using economic data APIs and working with economic microdata. Includes bd CPS.
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bd CPS: create longitudinal weights #136

Open bdecon opened 5 years ago

bdecon commented 5 years ago

Think about how to weight matched observations.

From IPUMS:

Weighting Linked Datasets

The Bureau of Labor Statistics delivers cross-sectional weights, but they provide only limited longitudinal weights (PANLWT for linking adjacent months for gross flows analysis). IPUMS-CPS has generated longitudinal weights for several different types of links. These weights are based on the cross-sectional weights and arrived at by iterative proportional fitting (ipf) or raking. For example, we create new weights for the set of people who link from time 1 to time 2 based on the population counts of the people who were eligible to link from time 1 to time 2. The eligible counts are based on the intersections at time 1 of

STATEFIP, AGE, and SEX
HISPAN, AGE, and SEX
RACE, AGE, and SEX
bdecon commented 5 years ago

Related to problem described in #155