@article {10.34196/ijm.00248,
article_type = {journal},
title = {Pooling Incomplete Data Sets},
author = {Klevmarken, Anders},
volume = 15,
number = 1,
year = 2022,
month = {apr},
pub_date = {2022-04-30},
pages = {31-42},
citation = {IJM 2022;15(1):31-42},
doi = {10.34196/ijm.00248},
url = {https://doi.org/10.34196/ijm.00248},
abstract = {Data needed in micro studies are not always available from just a single source. In such cases it might be possible to combine two or more independent samples. The problem studied in this paper is to estimate a linear function between \textit{y} and \textit{x} from one sample of y-observations and another of x-observations. This is feasible if there are common variables \textit{z} which can be used to predict \textit{x}. A two-stage least squares estimator is propounded, which, for the model considered, is also an ML estimator. Simulation experiments show that it has a good relative efficiency and virtually no small sample bias.},
journal = {IJM},
issn = {1747-5864},
publisher = {International Journal of Microsimulation},
}