IDEAS home Printed from https://ideas.repec.org/a/wly/japmet/v8y1993i4p383-395.html
   My bibliography  Save this article

A count‐amount model with endogenous recording of observations

Author

Listed:
  • B. M. S. Van Praag
  • E. M. Vermeulen

Abstract

This paper discusses some of the problems which are encountered if an event Ỹ is only recorded if its value satisfies a recording criterion A. It follows that we get an incorrect idea of the frequency of the events and of its true distribution. In order to solve these problems, an econometric model has been constructed by means of which consistent estimation of the true parameters is possible. The model is estimated on consumer purchases, where the number of purchases is assumed to be NEGBIN‐distributed and the purchase amounts obey a lognormal distribution. Purchases are only recorded if their value exceeds Dfl. 10. It is shown that ignoring the recording condition will result in biased estimates and invalid predictions. Apart from this, the model is, among others, relevant for insurance problems, marketing surveys and criminological and epidemiological phenomena.

Suggested Citation

  • B. M. S. Van Praag & E. M. Vermeulen, 1993. "A count‐amount model with endogenous recording of observations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 383-395, October.
    • Handle: RePEc:wly:japmet:v:8:y:1993:i:4:p:383-395
    DOI: 10.1002/jae.3950080406
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/jae.3950080406
    Download Restriction: no
    File URL: https://libkey.io/10.1002/jae.3950080406?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. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    3. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    4. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    5. Morrison, Donald G & Schmittlein, David C, 1988. "Generalizing the NBD Model for Customer Purchases: What Are the Implications and Is It Worth the Effort? Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 165-166, April.
    6. Alessie, Rob & Gradus, Raymond H J M & Melenberg, Bertrand, 1990. "The Problem of Not Observing Small Expenditures in a Consumer Expenditure Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 151-166, April-Jun.
    7. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    8. Morrison, Donald G & Schmittlein, David C, 1988. "Generalizing the NBD Model for Customer Purchases: What Are the Implications and Is It Worth the Effort?," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 145-159, April.
    Full references (including those not matched with items on IDEAS)

    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. Bockenholt, Ulf, 1998. "Mixed INAR(1) Poisson regression models: Analyzing heterogeneity and serial dependencies in longitudinal count data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 317-338, November.
    2. Dionne, Georges, 1998. "La mesure empirique des problèmes d’information," L'Actualité Economique, Société Canadienne de Science Economique, vol. 74(4), pages 585-606, décembre.
    3. Gouriéroux, Christian & Monfort, Alain, 1997. "Modèles de comptage semi-paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 73(1), pages 525-550, mars-juin.
    4. Dionne, Georges & Vanasse, Charles, 1997. "Une évaluation empirique de la nouvelle tarification de l’assurance automobile (1992) au Québec," L'Actualité Economique, Société Canadienne de Science Economique, vol. 73(1), pages 47-80, mars-juin.
    5. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
    6. Dionne, Georges & Gagne, Robert & Gagnon, Francois & Vanasse, Charles, 1997. "Debt, moral hazard and airline safety An empirical evidence," Journal of Econometrics, Elsevier, vol. 79(2), pages 379-402, August.
    7. Baptista, Rui & Swann, Peter, 1998. "Do firms in clusters innovate more?," Research Policy, Elsevier, vol. 27(5), pages 525-540, September.
    8. Georges Dionne & Olfa Ghali, 2005. "The (1992) Bonus‐Malus System in Tunisia: An Empirical Evaluation," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 72(4), pages 609-633, December.
    9. Michael R. Baye & J. Rupert J. Gatti & Paul Kattuman & John Morgan, 2009. "Clicks, Discontinuities, and Firm Demand Online," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 18(4), pages 935-975, December.
    10. Konstantinos Drakos & Andreas Gofas, 2006. "In Search Of The Average Transnational Terrorist Attack Venue," Defence and Peace Economics, Taylor & Francis Journals, vol. 17(2), pages 73-93.
    11. Bauer, Thomas K. & Million, Andreas & Rotte, Ralph & Zimmermann, Klaus F., 1998. "Immigration Labor and Workplace Safety," IZA Discussion Papers 16, Institute of Labor Economics (IZA).
    12. Frank T. Rothaermel & Andrew M. Hess, 2007. "Building Dynamic Capabilities: Innovation Driven by Individual-, Firm-, and Network-Level Effects," Organization Science, INFORMS, vol. 18(6), pages 898-921, December.
    13. Rothaermel, Frank T. & Thursby, Marie, 2007. "The nanotech versus the biotech revolution: Sources of productivity in incumbent firm research," Research Policy, Elsevier, vol. 36(6), pages 832-849, July.
    14. Mello, Marco & Moscelli, Giuseppe, 2022. "Voting, contagion and the trade-off between public health and political rights: Quasi-experimental evidence from the Italian 2020 polls," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 1025-1052.
    15. Greene, William, 2008. "Functional forms for the negative binomial model for count data," Economics Letters, Elsevier, vol. 99(3), pages 585-590, June.
    16. Dionne, Georges, 2012. "The empirical measure of information problems with emphasis on insurance fraud and dynamic data," Working Papers 12-10, HEC Montreal, Canada Research Chair in Risk Management.
    17. Dionne, G., 2000. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud," Ecole des Hautes Etudes Commerciales de Montreal- 00-04, Ecole des Hautes Etudes Commerciales de Montreal-Chaire de gestion des risques..
    18. M. Wedel & W. S. Desarbo & J. R. Bult & V. Ramaswamy, 1993. "A latent class poisson regression model for heterogeneous count data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 397-411, October.
    19. Baye, Michael & GATTI, RUPERT J & Kattuman, Paul & Morgan, John, 2004. "Estimating Firm-Level Demand at a Price Comparison Site: Accounting for Shoppers and the Number of Competitors," Competition Policy Center, Working Paper Series qt923692d1, Competition Policy Center, Institute for Business and Economic Research, UC Berkeley.
    20. Dohse, Dirk & Schertler, Andrea, 2003. "Explaining the regional distribution of new economy firms: a count data analysis," Kiel Working Papers 1193, Kiel Institute for the World Economy (IfW Kiel).

    More about this item

    Statistics

    Access and download statistics

    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:wly:japmet:v:8:y:1993:i:4:p:383-395. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0883-7252/ .

    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.