Goodrich on "Bringing Rank-Minimization Back In" 

 Please join us tomorrow, September 16th when we are excited to have Ben Goodrich (Government/Social Policy) presenting "Bringing Rank-Minimization Back In: An Estimator of the Number of Inputs to a Data-Generating Process," for which Ben has provided the following abstract: 

 
This paper derives and implements an algorithm to infer the number of inputs to a data-generating process from the outputs. Previous working dating back to the 1930s proves that this inference can be made in theory, but the practical difficulties have been too daunting to overcome. These obstacles can be avoided by looking at the problem from a different perspective, utilizing some insights from the study of economic inequality, and relying on modern computer technology.

 Now that there is a computational algorithm that can estimate the number of variables that generated observed outcomes, the scope for applications is quite large. Examples are given showing its use for evaluating the reliability of measures of theoretical concepts, empirically testing formal models, verifying whether there is an omitted variable in a regression, checking whether proposed explanatory variables are measured without error, evaluating the completeness of multiple imputation models for missing data, and facilitating the construction of matched pairs in randomized experiments. The algorithm is used to test the main hypothesis in 
Esping-Andersen (1990), which has been influential in the political economy literature, namely that various welfare-state outcomes are a function of only three underlying variables. 
  

 The Applied Statistics workshop meets each Wednesday in room K-354, CGIS-Knafel (1737 Cambridge St). We start at 12 noon with a light lunch, with presentations beginning around 12:15 and we usually wrap up around 1:30 pm.  

 We hope you can make it.