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rscore: a Stata module to compute responsiveness scores

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  • Giovanni Cerulli

    (Research Institute on Sustainable Economic Growth, Rome)

Abstract

This paper presents rscore, a Stata module to compute unit responsiveness scores using a iterated random coefficient regression (RCR). The basic econometrics of this model can be found in Wooldridge (2002, pp. 638-642). The model estimated by rscore starts from a classical regression of Y, the target variable, on a series of factors X (the regressors), by assuming a different reaction (or responsiveness) of each unit to each factor contained in X. This is done by using a random coefficient regression (RCR), an approach in which the usual regression coefficients vary across units. The application of such an approach can convey new and interesting analytical findings compared to the traditional regression approach. In particular, by measuring a unit-specific regression coefficient for each regressor this model allows for: (i) ranking units according to the level of the responsiveness score obtained; (ii) detecting factors that are more influential in driving unit performance; (iii) studying, more in general, the distribution (variety) of the factors’ responsiveness scores across units. The knowledge of these idiosyncratic scores can be also exploited to test the presence of increasing, constant, or decreasing returns of Y to X in a straightforward and graphically easy-to-read way.

Suggested Citation

  • Giovanni Cerulli, 2015. "rscore: a Stata module to compute responsiveness scores," United Kingdom Stata Users' Group Meetings 2015 02, Stata Users Group.
  • Handle: RePEc:boc:usug15:02
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