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Censored QUAIDS estimation with quaidsce

Author

Listed:
  • Juan Carlos Caro

    (University of Luxembourg)

  • Grace Melo

    (Texas A&M University)

  • José Alberto Molina

    (Departamento de Análisis Económico, Universidad de Zaragoza)

  • Juan Carlos Salgado

    (Instituto Nacional de Salúd Pública, México)

Abstract
Censoring, or zero expenditures, in the dependent variables of demand systems can lead to inconsistent parameter and elasticity estimates. Poi (2012) introduced the Stata command quaids to estimate quadratic almost-ideal demand systems, or QUAIDS (Banks, Bundell and Lewbel, 1997), although without the possibility to address censoring. In this paper, we introduce the command quaidsce to consistently estimate the QUAIDS in the presence of zero observations, using the two-step procedure proposed by Shonkwiler and Yen (1999). The new command also allows for estimating expenditure and price elasticities with standard errors, using post-estimation tools.

Suggested Citation

  • Juan Carlos Caro & Grace Melo & José Alberto Molina & Juan Carlos Salgado, 2021. "Censored QUAIDS estimation with quaidsce," Boston College Working Papers in Economics 1045, Boston College Department of Economics.
    • Handle: RePEc:boc:bocoec:1045
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    References listed on IDEAS

    as
    1. Blundell, Richard & Robin, Jean Marc, 1999. "Estimation in Large and Disaggregated Demand Systems: An Estimator for Conditionally Linear Systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 209-232, May-June.
    2. Crawford, Ian & Laisney, Francois & Preston, Ian, 2003. "Estimation of household demand systems with theoretically compatible Engel curves and unit value specifications," Journal of Econometrics, Elsevier, vol. 114(2), pages 221-241, June.
    3. J. Scott Shonkwiler & Steven T. Yen, 1999. "Two-Step Estimation of a Censored System of Equations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 972-982.
    4. Steven T. Yen & Biing-Hwan Lin & David M. Smallwood, 2003. "Quasi- and Simulated-Likelihood Approaches to Censored Demand Systems: Food Consumption by Food Stamp Recipients in the United States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 458-478.
    5. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    6. Brian P. Poi, 2012. "Easy demand-system estimation with quaids," Stata Journal, StataCorp LP, vol. 12(3), pages 433-446, September.
    7. Capacci, Sara & Mazzocchi, Mario, 2011. "Five-a-day, a price to pay: An evaluation of the UK program impact accounting for market forces," Journal of Health Economics, Elsevier, vol. 30(1), pages 87-98, January.
    8. Amemiya, Takeshi, 1974. "Multivariate Regression and Simultaneous Equation Models when the Dependent Variables Are Truncated Normal," Econometrica, Econometric Society, vol. 42(6), pages 999-1012, November.
    9. Jean-Marc Robin, 1999. "[Econometrics of systems of demand] [Econométrie des systèmes de demande]," Post-Print hal-02688894, HAL.
    10. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
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    Cited by:

    1. Semet, Raphaël, 2024. "Coordinating social equity and emissions: Challenges in carbon tax policy," Energy Policy, Elsevier, vol. 185(C).

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    More about this item

    Keywords

    Censoring; Stata; QUAIDS; quaidsce;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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