IDEAS home Printed from https://ideas.repec.org/p/ags/aaea08/6534.html
   My bibliography  Save this paper

Censored Quantile Regression and Purchases of Ice Cream

Author

Listed:
  • Gustavsen, Geir Waehler
  • Jolliffe, Dean
  • Rickertsen, Kyrre

Abstract

The effects on purchases of ice cream of increasing the value added tax (VAT) for less healthy foods and removing the VAT for healthy foods are estimated. The effects on high- and low-purchasing households are estimated by using quantile regressions. Many households did not purchase ice cream and censored quantile regressions are estimated by a recently developed algorithm, which is simple, robust, and performs well near the censoring point. High-purchasing households will reduce their annual per capita purchases with 1.8 kilograms corresponding to an annual reduction of more than half a kilogram of body weight.

Suggested Citation

  • Gustavsen, Geir Waehler & Jolliffe, Dean & Rickertsen, Kyrre, 2008. "Censored Quantile Regression and Purchases of Ice Cream," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6534, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea08:6534
    DOI: 10.22004/ag.econ.6534
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/6534/files/463214.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.6534?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Stewart, Hayden & Blisard, Noel & Jolliffe, Dean, 2003. "Do Income Constraints Inhibit Spending on Fruits and Vegetables Among Low-Income Households?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(3), pages 1-16, December.
    2. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    3. Buchinsky, Moshe, 1994. "Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression," Econometrica, Econometric Society, vol. 62(2), pages 405-458, March.
    4. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    5. Fred Kuchler & Abebayehu Tegene & J. Michael Harris, 2005. "Taxing Snack Foods: Manipulating Diet Quality or Financing Information Programs?," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 27(1), pages 4-20.
    6. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    7. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521608275.
    8. Fred Kuchler & Abebayehu Tegene & J. Michael Harris, 2005. "Taxing Snack Foods: Manipulating Diet Quality or Financing Information Programs?," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 27(1), pages 4-20.
    9. John L. Park & Oral Capps, 1997. "Demand for Prepared Meals by U.S. Households," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 814-824.
    10. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    11. Bilias, Yannis & Chen, Songnian & Ying, Zhiliang, 2000. "Simple resampling methods for censored regression quantiles," Journal of Econometrics, Elsevier, vol. 99(2), pages 373-386, December.
    12. Geir Wæhler Gustavsen & Kyrre Rickertsen, 2006. "A Censored Quantile Regression Analysis of Vegetable Demand: The Effects of Changes in Prices and Total Expenditure," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 54(4), pages 631-645, December.
    13. Thomas L. Cox & Michael K. Wohlgenant, 1986. "Prices and Quality Effects in Cross-Sectional Demand Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(4), pages 908-919.
    14. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
    15. Hong H. & Chernozhukov V., 2002. "Three-Step Censored Quantile Regression and Extramarital Affairs," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 872-882, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pradhan, Jaya Prakash, 2011. "Regional heterogeneity and firms’ innovation: the role of regional factors in industrial R&D in India," MPRA Paper 28096, University Library of Munich, Germany.
    2. Pradhan, Jaya Prakash, 2010. "R&D strategy of small and medium enterprises in India: Trends and determinants," MPRA Paper 20951, University Library of Munich, Germany.
    3. Gustavsen, Geir Wæhler & Rickertsen, Kyrre, 2013. "Adjusting VAT rates to promote healthier diets in Norway: A censored quantile regression approach," Food Policy, Elsevier, vol. 42(C), pages 88-95.
    4. Achim Schmillen & Joachim Möller, 2009. "Determinants of Lifetime Unemployment - A Micro Data Analysis with Censored Quantile Regressions," Working Papers 275, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
    5. Gaurav Nayyar, 2009. "The Demand for Services in India. A Mirror Image of Engel's Law for Food?," Economics Series Working Papers 451, University of Oxford, Department of Economics.
    6. Schmillen, Achim & Möller, Joachim, 2012. "Distribution and determinants of lifetime unemployment," Labour Economics, Elsevier, vol. 19(1), pages 33-47.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gustavsen, Geir Wæhler & Rickertsen, Kyrre, 2013. "Adjusting VAT rates to promote healthier diets in Norway: A censored quantile regression approach," Food Policy, Elsevier, vol. 42(C), pages 88-95.
    2. Geir Wæhler Gustavsen & Kyrre Rickertsen, 2009. "The effects of taxes on purchases of sugar-sweetened carbonated soft drinks: a quantile regression approach," Applied Economics, Taylor & Francis Journals, vol. 43(6), pages 707-716.
    3. Kim, Mo Se & Lee, Byung Sung & Lee, Hye Seon & Lee, Seung Ho & Lee, Junseok & Kim, Wonse, 2020. "Robust estimation of outage costs in South Korea using a machine learning technique: Bayesian Tobit quantile regression," Applied Energy, Elsevier, vol. 278(C).
    4. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    5. Gustavsen, Geir Waehler & Rickertsen, Kyrre, 2004. "For Whom Reduced Prices Count: A Censored Quantile Regression Analysis Of Vegetable Demand," 2004 Annual meeting, August 1-4, Denver, CO 20172, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Gustavsen, Geir Waehler, 2005. "Public Policies and the Demand for Carbonated Soft Drinks: A Censored Quantile Regression Approach," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24737, European Association of Agricultural Economists.
    7. Joachim Wagner, 2014. "Exports, foreign direct investments and productivity: are services firms different?," The Service Industries Journal, Taylor & Francis Journals, vol. 34(1), pages 24-37, January.
    8. Halkos, George E., 2011. "Nonparametric modelling of biodiversity: Determinants of threatened species," Journal of Policy Modeling, Elsevier, vol. 33(4), pages 618-635, July.
    9. Bernd Fitzenberger & Ralf Wilke, 2006. "Using quantile regression for duration analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 105-120, March.
    10. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
    11. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2020. "Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes," De Economist, Springer, vol. 168(4), pages 519-540, December.
    12. Pitselis, Georgios, 2020. "Multi-stage nested classification credibility quantile regression model," Insurance: Mathematics and Economics, Elsevier, vol. 92(C), pages 162-176.
    13. Halkos, George, 2010. "Modelling biodiversity," MPRA Paper 39075, University Library of Munich, Germany.
    14. Joachim Wagner, 2016. "From Estimation Results to Stylized Facts: Twelve Recommendations for Empirical Research in International Activities of Heterogeneous Firms," World Scientific Book Chapters, in: Microeconometrics of International Trade, chapter 15, pages 479-514, World Scientific Publishing Co. Pte. Ltd..
    15. Genya Kobayashi & Hideo Kozumi, 2012. "Bayesian analysis of quantile regression for censored dynamic panel data," Computational Statistics, Springer, vol. 27(2), pages 359-380, June.
    16. Madhavan-Nambiar, Padmanand & Florkowski, Wojciech & Chinnan, Manjeet & Ressurrecion, Anna, 2014. "Factors Driving Fruit and Vegetable Expenditures and Consumption Frequency in Lesser Developed Country: an Analysis of Urban Households from the Republic of Uganda," 2014 Annual Meeting, February 1-4, 2014, Dallas, Texas 162414, Southern Agricultural Economics Association.
    17. Lin, Guixian & He, Xuming & Portnoy, Stephen, 2012. "Quantile regression with doubly censored data," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 797-812.
    18. Machado, José A.F. & Santos Silva, J.M.C. & Wei, Kehai, 2016. "Quantiles, corners, and the extensive margin of trade," European Economic Review, Elsevier, vol. 89(C), pages 73-84.
    19. Pitselis, Georgios, 2017. "Risk measures in a quantile regression credibility framework with Fama/French data applications," Insurance: Mathematics and Economics, Elsevier, vol. 74(C), pages 122-134.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea08:6534. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.