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Two-Stage Budgeting: A Difficult Problem

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  • Norman, A
  • Chou, J.
  • Chowdhury, M.
  • Dalal, A.
  • Fortson, M.
  • Jindal, M.
  • Payne, K.
  • Rajan, M.

Abstract

Utility maximization with a weakly separable utility function requires a consumer create an optimal budget for each separable subgroup. We show that computational complexity of optimal budgeting is the maximum of an exponential in the number of alternatives and a quadratic in the number of budget increments. From a budget survey of undergraduates we show that an undergraduate procedural consumer can obtain a budget estimate from the experience of previous students and can monitor the flow of funds and can make adjustments at a minuscule fraction of the calculations needed for optimal budgeting. Copyright 2001 by Kluwer Academic Publishers

Suggested Citation

  • Norman, A & Chou, J. & Chowdhury, M. & Dalal, A. & Fortson, M. & Jindal, M. & Payne, K. & Rajan, M., 2001. "Two-Stage Budgeting: A Difficult Problem," Computational Economics, Springer;Society for Computational Economics, vol. 18(3), pages 259-271, December.
    • Handle: RePEc:kap:compec:v:18:y:2001:i:3:p:259-71
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    1. repec:ebl:ecbull:v:6:y:2008:i:30:p:1-12 is not listed on IDEAS
    2. Wang, Zheng-Xin & Zheng, Hong-Hao & Pei, Ling-Ling & Jin, Tong, 2017. "Decomposition of the factors influencing export fluctuation in China's new energy industry based on a constant market share model," Energy Policy, Elsevier, vol. 109(C), pages 22-35.
    3. Tetsuya Saito, 2008. "An Expository Note on Alchian-Allen Theorem When Sub-Utility Functions are Homogeneous of Degree n > 0 with Two-Stage Budgeting," Economics Bulletin, AccessEcon, vol. 6(30), pages 1-12.
    4. A. Norman & M. Aberty & K. Brehm & M. Drake & S. Gour & C. Govil & B. Gu & J. Hart & G. Kadiri & J. Ke & S. Keyburn & M. Kulkarni & N. Mehta & A. Robertson & J. Sanghai & V. Shah & J. Schieck & Y. Siv, 2008. "Can Consumer Software Selection Code for Digital Cameras Improve Consumer Performance?," Computational Economics, Springer;Society for Computational Economics, vol. 31(4), pages 363-380, May.

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