Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/236252
Authors: 
Jayachandran, Seema
Biradavolu, Monica
Cooper, Jan
Year of Publication: 
2021
Series/Report no.: 
IZA Discussion Papers No. 14221
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
We propose a new method to design a short survey measure of a complex concept such as women's agency. The approach combines mixed-methods data collection and machine learning. We select the best survey questions based on how strongly correlated they are with a "gold standard" measure of the concept derived from qualitative interviews. In our application, we measure agency for 209 women in Haryana, India, first, through a semi-structured interview and, second, through a large set of close-ended questions. We use qualitative coding methods to score each woman's agency based on the interview, which we treat as her true agency. To identify the close-ended questions most predictive of the "truth," we apply statistical algorithms that build on LASSO and random forest but constrain how many variables are selected for the model (five in our case). The resulting five-question index is as strongly correlated with the coded qualitative interview as is an index that uses all of the candidate questions. This approach of selecting survey questions based on their statistical correspondence to coded qualitative interviews could be used to design short survey modules for many other latent constructs.
Subjects: 
women's empowerment
survey design
feature selection
psychometrics
JEL: 
C83
D13
J16
O12
Document Type: 
Working Paper

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