Coleman, Charles (2016): A SAS® Macro for the Generalized RAS Algorithm.
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Abstract
The problem of constraining matrices of mixed sign to controls of possibly mixed sign arises in inputoutput matrices in economics and net migration in demography. The recently developed Generalized RAS (GRAS) algorithm is presented to solve these problems. The GRAS algorithm produces a unique solution that minimizes an entropylike function. The algorithm is applied to a wellknown example and compared to the solution originally obtained using a generalization of the AkersSiegel procedure.
Item Type:  MPRA Paper 

Original Title:  A SAS® Macro for the Generalized RAS Algorithm 
Language:  English 
Keywords:  matrix scaling; matrix raking; matrix balancing; mixed signs; GRAS; SAS; plusminus problem; migration; GRAS 
Subjects:  C  Mathematical and Quantitative Methods > C0  General > C02  Mathematical Methods C  Mathematical and Quantitative Methods > C6  Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C67  InputOutput Models C  Mathematical and Quantitative Methods > C8  Data Collection and Data Estimation Methodology ; Computer Programs > C88  Other Computer Software D  Microeconomics > D5  General Equilibrium and Disequilibrium > D57  InputOutput Tables and Analysis J  Labor and Demographic Economics > J1  Demographic Economics > J19  Other R  Urban, Rural, Regional, Real Estate, and Transportation Economics > R1  General Regional Economics > R15  Econometric and InputOutput Models ; Other Models 
Item ID:  77842 
Depositing User:  Dr. Charles Coleman 
Date Deposited:  23 Mar 2017 18:11 
Last Modified:  28 Sep 2019 03:47 
References:  Akers, D.S., and Siegel, J.S. (1965). “National Census Survival Rates, by Color and Sex, for 1950–1960.” Current Population Reports, series P23, no. 15. Washington, D.C.: U.S. Bureau of the Census. Bregman, L.M. (1967). Proof of the Convergence of Sheleikhovskii’s Method for a Problem with Transportation Constraints. USSR Computational Mathematics and Mathematical Physics, 1(1): 191–204. Fagan, J. and Greenberg, B. (1984), Making Tables Additive in the Presence of Zeroes, in Proceedings of the Joint Statistical Meetings, Survey Research and Methodology Section. http://www.amstat.org/sections/srms/Proceedings/papers/1984_038.pdf, Accessed February 15, 2016. Junius T. and Oosterhaven J. (2003). The Solution of Updating or Regionalizing a Matrix with both Positive and Negative Entries. Economic Systems Research, 15(1), 8796. Lenzen M., Gallego, B., and Wood, R. (2009). Matrix Balancing under Conflicting Information. Economic Systems Research, 21(1), 23–440. Lenzen M., Moran, D.D., Geschke A., and Kanemoto, K. (2014). A NonSignPreserving RAS Variant. Economic Systems Research, 26(2), 197208 Schneider, M.H. and Zenios, S.A. (1990). A Comparative Study of Algorithms for Matrix Balancing. Operations Research, 38(3), 439455. Shryock, H.S., Siegel, J.S., and Associates (1973). The Methods and Materials of Demography (2nd Printing, revised). Washington, D.C.: U.S. Government Printing Office. Temurshoev U., Miller, R. E., and Bouwmeester, M. C. (2013). A Note on the GRAS Method. Economic Systems Research, 25(3), 361–367. 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/77842 
Available Versions of this Item

A SAS® Macro for the Generalized RAS Algorithm. (deposited 20 Mar 2017 16:58)

A SAS® Macro for the Generalized RAS Algorithm. (deposited 22 Mar 2017 03:41)
 A SAS® Macro for the Generalized RAS Algorithm. (deposited 23 Mar 2017 18:11) [Currently Displayed]

A SAS® Macro for the Generalized RAS Algorithm. (deposited 22 Mar 2017 03:41)