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Estimating responsiveness scores using rscore


  • Giovanni Cerulli

    () (National Research Council of Italy)


rscore computes unit-specific responsiveness scores using an iter- ated random-coefficient regression approach. The model fit by rscore considers a regression of a response variable y, that is, outcome, on a series of factors (or re- gressors) x, that is, varlist, by assuming a different reaction (or “responsiveness”) of each unit to each factor contained in x. rscore allows for i) ranking units according to the obtained level of the responsiveness score; ii) detecting more in- fluential factors in driving unit performance; and iii) studying the distribution (heterogeneity) of factors’ responsiveness scores across units. Also, rscore offers useful graphical representation of results. We provide two illustrative applications of the model: the first is on a cross-section, and the second is on a longitudinal dataset.

Suggested Citation

  • Giovanni Cerulli, 2017. "Estimating responsiveness scores using rscore," Stata Journal, StataCorp LP, vol. 17(2), pages 422-441, June.
  • Handle: RePEc:tsj:stataj:v:17:y:2017:i:2:p:422-441

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    Cited by:

    1. Giovanni Cerulli & Maria Ventura & Christopher F Baum, 2018. "The Economic Determinants of Crime: an Approach through Responsiveness Scores," Boston College Working Papers in Economics 948, Boston College Department of Economics.


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