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Using Stata for a memory-saving fixed-effects estimation of the three-way error-components model


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  • Thomas Cornelissen

    (Leibniz Universität Hannover)


Researchers trying to estimate tens or hundreds of thousands of fixed effects for two or more groups (workers and firms; pupils, teachers and schools; etc.) in datasets with high numbers of observations are often limited by the size of computer memory available. Such a model is commonly estimated by sweeping out one of the effects by the fixed-effects transformation (time-demeaning) and by including the remaining effects as dummy variables. If K is the number of fixed effects to be included as dummy variables, and N is the number of observations, then the design matrix is of dimension N x K (neglecting any remaining right-hand-side regressors). The time-demeaned dummies have to be stored as “float” variables consuming 8 bytes per cell in Stata. For example, with 2 million observations (N) and 10 thousand fixed effects (K), the memory requirement would be 160 gigabytes. This paper describes how the memory requirement can be reduced to store only a K x K matrix, which in the given example reduces the memory requirement to below 1 gigabyte. The paper also describes the Stata program felsdvreg.ado, which implements the method in Mata. Besides implementing the memory-saving estimation method, the program also takes care of checking the identification of the effects and provides useful summary statistics.

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Bibliographic Info

Paper provided by Stata Users Group in its series German Stata Users' Group Meetings 2008 with number 07.

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Date of creation: 03 Jul 2008
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Handle: RePEc:boc:dsug08:07

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Cited by:
  1. Christian Volpe Martincus & Jerónimo Carballo, 2010. "Is Export Promotion Effective in Developing Countries? Firm-Level Evidence on the Intensive and Extensive Margins of Exports," IDB Publications 36763, Inter-American Development Bank.
  2. Hackl, Franz & Kügler, Agnes & Winter-Ebmer, Rudolf, 2011. "Reputation and Certification in Online Shops," Economics Series 279, Institute for Advanced Studies.
  3. Nils Braakmann, 2008. "Crime does pay (at least when it’s violent)!– On the compensating wage differentials of high regional crime levels," Working Paper Series in Economics 91, University of Lüneburg, Institute of Economics.


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