Keywords: restricted least squares, nonparametric regression, monotonicity and concavity constraints, cost and profit functions, quadratic programming
Reference: P. A. Ruud, "Least Squares Estimation Subject to Monotonicity and Concavity Constraints," Invited Symposium on Computationally Intensive Methods In Econometrics, 1995.
Description: This entry contains Matlab programs for computing the least squares, nonparametric, fit of cost functions using data on factor demands, factor prices, and output levels. Both factor demands and outputs may be multi-dimensional.
The algorithm is a specialized quadratic programming method based on applying Gauss-Seidel to the dual program. The Gauss-Seidel steps include projection onto the cone of constraints that require each observation to be the least cost factor demands for that output level and input prices and a projection that imposes all monotonicity constraints. In addition, when the active constraints are stationary over two iterations, the program attempts to jump to a final solution.
The computational example included is the re-estimation of the cost function for electricity utilities from the Christensen-Greene study (JPE, 84(4), 1976, 655-676).
The attached technical paper used these programs for the calculations: P. A. Ruud, "Least Squares Estimation Subject to Monotonicity and Concavity Constraints," Invited Symposium on Computationally Intensive Methods In Econometrics, 1995.
Platforms: Matlab
Support: Please contact the author with questions or suggestions at ruud@econ.Berkeley.EDU.
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Archive file: ruud895.zip
3837 Aug 17 09:24 CG.out 6336 Jul 31 10:57 Christensen.dat 6543 Aug 17 09:17 Estimation.m 2202 Aug 17 09:37 abstract.txt 1873 Aug 17 09:11 active.m 3636 Jul 31 12:30 avgcost.m 521 Jul 31 10:48 feq.m 527 Jul 31 10:48 fle.m 517 Jul 31 10:48 flt.m 1553 Jul 31 11:00 intpolfactor_p.m 2591 Jul 31 14:57 install.txt 744 Jul 31 10:55 load_Christensen.m 4376 Aug 17 09:01 project.m 8011 Aug 17 09:22 results_cg.mat 204594 Aug 17 10:27 tokyo1.ps
Test problem replicated by David Revelt, 18 August 1995. No errors reported. Test was run on Sun SPARCstation IPX running SunOS 4.1.3, using Matlab ver. 4.2A.
Archived by Grace Katagiri, 25 August 1995.