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Replication Data for: How Much Does the Cardinal Treatment of Ordinal Variables Matter? An Empirical Investigation

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication Data for: How Much Does the Cardinal Treatment of Ordinal Variables Matter? An Empirical Investigation
 
Identifier https://doi.org/10.7910/DVN/VWURHG
 
Creator Bloem, Jeffrey
 
Publisher Harvard Dataverse
 
Description Many researchers use an ordinal scale to quantitatively measure and analyze concepts. Theoretically valid empirical estimates are robust in sign to any monotonic increasing transformation of the ordinal scale. This presents challenges for the point-identification of important parameters of interest. I develop a partial identification method for testing the robustness of empirical estimates to a range of plausible monotonic increasing transformations of the ordinal scale. This method allows for the calculation of plausible bounds around effect estimates. I illustrate this method by re-visiting analysis by Nunn and Wantchekon (2011) on the slave trade and trust in sub-Saharan Africa. Supplemental illustrations examine results from (i) Aghion et al. (2016) on creative destruction and subjective well-being and (ii) Bond and Lang (2013) on the fragility of the black-white
test score gap.
 
Subject Social Sciences
 
Contributor Code Ocean