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Solving Finite Mixture Models: Efficient Computation in Economics Under Serial and Parallel Execution

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Abstract

Many economic models are completed by finding a parameter vector θ that optimizes a function f(θ), a task that can only be accomplished by iterating from a starting vector θ0. Use of a generic iterative optimizer to carry out this task can waste enormous amounts of computation when applied to a class of problems defined here as finite mixture models. The finite mixture class is large and important in economics and eliminating wasted computations requires only limited changes to standard code. Further, the approach described here greatly increases gains from parallel execution and opens possibilities for re-writing objective functions to make further efficiency gains.

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Authors and Affiliations

  1. Department of Economics, Dunning Hall, Queen’s University, Kingston, Ontario, Canada, K7L 3N6

    Christopher Ferrall

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  1. Christopher Ferrall
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Correspondence to Christopher Ferrall.

Additional information

Documented code that implements the algorithm described is available from the author for objectives written in C and other languages. It runs in both serial and parallel mode using the MPI library.

JEL Classification: C61; C63; D58

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Ferrall, C. Solving Finite Mixture Models: Efficient Computation in Economics Under Serial and Parallel Execution. Comput Econ 25, 343–379 (2005). https://doi.org/10.1007/s10614-005-6413-3

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  • DOI: https://doi.org/10.1007/s10614-005-6413-3

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