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Evaluating Social Policy by Experimental and Nonexperimental Methods
Author(s) -
Bratberg Espen,
Grasdal Astrid,
Risa Alf Erling
Publication year - 2002
Publication title -
scandinavian journal of economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.725
H-Index - 64
eISSN - 1467-9442
pISSN - 0347-0520
DOI - 10.1111/1467-9442.00276
Subject(s) - estimator , propensity score matching , matching (statistics) , selection (genetic algorithm) , average treatment effect , econometrics , sample (material) , selection bias , context (archaeology) , economics , difference in differences , computer science , statistics , mathematics , machine learning , geography , chemistry , chromatography , archaeology
Although it is important to establish causal relationships in social policy evaluation, the effects are difficult to observe due to sample selection. To evaluate the performance of estimators designed to handle sample selection bias, we analyse data from a Norwegian rehabilitation project with a randomised experimental design. The data permit us to compare the performance of different nonexperimental estimators with the experimental results. In our case study we find that nonexperimental evaluation based on sample selection estimators with selection terms that fail to meet conventional levels of statistical significance is highly unreliable. The difference in difference estimator and propensity score matching estimators perform better in our context. JEL classification : C 51; J 24; H 43; I 12