IDEAS home Printed from https://ideas.repec.org/a/wly/hlthec/v17y2008i1p41-54.html
   My bibliography  Save this article

Care‐giver advice as a preventive measure for drinking during pregnancy: zeros, categorical outcome responses, and endogeneity

Author

Listed:
  • Joseph V. Terza
  • Donald S. Kenkel
  • Tsui‐Fang Lin
  • Shinichi Sakata

Abstract

We conduct an empirical investigation of the impact of prenatal care‐giver advice on alcohol consumption by pregnant women. In the design of the model and estimator, we pay particular attention to three aspects of the data. First, a large proportion of pregnant women do not drink at all. To accommodate this aspect of the sample we base the essential formulation of the model on the modified version of the two‐part approach of Duan et al. (Journal of Business and Economic Statistics 1983; 1: 115–126.) suggested by Mullahy (Journal of Health Economics 1998; 17: 247–281.). Second, in the survey that we analyze (the 1988 National Maternal and Infant Health Survey – NMIHS), respondents were only required to report their consumption up to a specified range of values (e.g. 1–2 drinks per week, 2–5 drinks per week, and so on). For this reason, the model is cast in the grouped regression framework of Stewart (Review of Economic Studies 1983; 50: 141–149.). Third, the binary physician advice variable is likely to be endogenous and the econometric specification explicitly accounts for this possibility. To summarize the results, we find that failing to account for endogeneity leads to the counterintuitive conclusion that advice has a positive and statistically significant influence on drinking during pregnancy. When the model is extended to allow for potential endogeneity, we find that advice has a negative and statistically significant impact. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Joseph V. Terza & Donald S. Kenkel & Tsui‐Fang Lin & Shinichi Sakata, 2008. "Care‐giver advice as a preventive measure for drinking during pregnancy: zeros, categorical outcome responses, and endogeneity," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 41-54, January.
    • Handle: RePEc:wly:hlthec:v:17:y:2008:i:1:p:41-54
    DOI: 10.1002/hec.1232
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/hec.1232
    Download Restriction: no
    File URL: https://libkey.io/10.1002/hec.1232?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. Mark B. Stewart, 1983. "On Least Squares Estimation when the Dependent Variable is Grouped," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 50(4), pages 737-753.
    2. Mullahy, John, 1998. "Much ado about two: reconsidering retransformation and the two-part model in health econometrics," Journal of Health Economics, Elsevier, vol. 17(3), pages 247-281, June.
    3. John Mullahy, 1998. "Much Ado About Two: Reconsidering Retransformation and the Two-Part Model in Health Economics," NBER Technical Working Papers 0228, National Bureau of Economic Research, Inc.
    4. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
    5. Kenkel, Donald S, 1991. "Health Behavior, Health Knowledge, and Schooling," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 287-305, April.
    6. Ippolito, Pauline M & Mathios, Alan D, 1995. "Information and Advertising: The Case of Fat Consumption in the United States," American Economic Review, American Economic Association, vol. 85(2), pages 91-95, May.
    7. Viscusi, W Kip, 1990. "Do Smokers Underestimate Risks?," Journal of Political Economy, University of Chicago Press, vol. 98(6), pages 1253-1269, December.
    8. Donald S. Kenkel & Joseph V. Terza, 2001. "The effect of physician advice on alcohol consumption: count regression with an endogenous treatment effect," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 165-184.
    9. Duan, Naihua, et al, 1983. "A Comparison of Alternative Models for the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 115-126, April.
    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. AZUMAH, Shaibu Baanni & MAHAMA, Abass & DONKOH, Samuel A., 2020. "Modelling The Determinants Of Adoption Of Multiple Climate Change Coping And Adaptation Strategies. A Micro Analysis Of Smallholder Farmers In Northern Ghana," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 23(1), March.
    2. Helge Liebert & Beatrice Mäder, 2018. "Physician Density and Infant Mortality: A Semiparametric Analysis of the Returns to Health Care Provision," CESifo Working Paper Series 7209, CESifo.
    3. Massimiliano Bratti & Alfonso Miranda, 2011. "Endogenous treatment effects for count data models with endogenous participation or sample selection," Health Economics, John Wiley & Sons, Ltd., vol. 20(9), pages 1090-1109, September.
    4. Maria Chiara Di Guardo & Kathryn Rudie Harrigan & Elona Marku, 2019. "M&A and diversification strategies: what effect on quality of inventive activity?," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 23(3), pages 669-692, September.
    5. Liebert, H. & Mäder, B., 2016. "Marginal effects of physician coverage on infant and disease mortality," Health, Econometrics and Data Group (HEDG) Working Papers 16/17, HEDG, c/o Department of Economics, University of York.
    6. Liebert, Helge & Mäder, Beatrice, 2016. "The impact of regional health care coverage on infant mortality and disease incidence," Economics Working Paper Series 1620, University of St. Gallen, School of Economics and Political Science.
    7. Bratti, M. & Miranda, A, 2010. "Endogenous Treatment Effects for Count Data Models with Sample Selection or Endogenous Participation," Health, Econometrics and Data Group (HEDG) Working Papers 10/19, HEDG, c/o Department of Economics, University of York.
    8. Helge Liebert & Beatrice Mäder, 2022. "Physicians and the Production of Health: Returns to Health Care During the Mortality Transition," CESifo Working Paper Series 9699, CESifo.
    9. Giulia Bettin & Riccardo Lucchetti, 2012. "Interval regression models with endogenous explanatory variables," Empirical Economics, Springer, vol. 43(2), pages 475-498, October.
    10. Monica Puoma LAMBON-QUAYEFIO & Nkechi S. OWOO, 2021. "Investigating the Long-Term Effects of Child Labor on Household Poverty and Food Insecurity in Ghana," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 87(4), pages 561-587, December.

    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. Donald S. Kenkel & Joseph V. Terza, 2001. "The effect of physician advice on alcohol consumption: count regression with an endogenous treatment effect," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 165-184.
    2. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    3. Silva João M. C. Santos & Tenreyro Silvana & Windmeijer Frank, 2015. "Testing Competing Models for Non-negative Data with Many Zeros," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 1-18, January.
    4. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
    5. Shuofen Hsu & Chaohsin Lin & Yaling Yang, 2008. "Integrating Neural Networks for Risk‐Adjustment Models," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(3), pages 617-642, September.
    6. Carole Roan Gresenz & Jeanette A. Rogowski & Jose Escarce, 2004. "Healthcare Markets, the Safety Net and Access to Care Among the Uninsured," NBER Working Papers 10799, National Bureau of Economic Research, Inc.
    7. Partha Deb & Murat K. Munkin & Pravin K. Trivedi, 2006. "Bayesian analysis of the two‐part model with endogeneity: application to health care expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1081-1099, November.
    8. Giampiero Marra & Matteo Fasiolo & Rosalba Radice & Rainer Winkelmann, 2023. "A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health," Health Economics, John Wiley & Sons, Ltd., vol. 32(6), pages 1305-1322, June.
    9. Liu, Lei & Strawderman, Robert L. & Cowen, Mark E. & Shih, Ya-Chen T., 2010. "A flexible two-part random effects model for correlated medical costs," Journal of Health Economics, Elsevier, vol. 29(1), pages 110-123, January.
    10. Vecino-Ortiz, Andrés Ignacio, 2008. "Determinants of demand for antenatal care in Colombia," Health Policy, Elsevier, vol. 86(2-3), pages 363-372, May.
    11. Massimiliano Bratti & Alfonso Miranda, 2010. "Endogenous Treatment Effects for Count Data Models with Sample Selection or Endogenous Participation," DoQSS Working Papers 10-05, Quantitative Social Science - UCL Social Research Institute, University College London, revised 10 Dec 2010.
    12. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2015. "The influence of obesity and overweight on medical costs: a panel data perspective," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(2), pages 161-173, March.
    13. Jay Dev Dubey, 2021. "Measuring Income Elasticity of Healthcare-Seeking Behavior in India: A Conditional Quantile Regression Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 767-793, December.
    14. Amanda Kowalski, 2016. "Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 107-117, January.
    15. van Doorslaer, Eddy & Wagstaff, Adam & van der Burg, Hattem & Christiansen, Terkel & De Graeve, Diana & Duchesne, Inge & Gerdtham, Ulf-G & Gerfin, Michael & Geurts, Jose & Gross, Lorna, 2000. "Equity in the delivery of health care in Europe and the US," Journal of Health Economics, Elsevier, vol. 19(5), pages 553-583, September.
    16. C. GEAY & M. KOUBI & G. de LAGASNERIE, 2015. "Evolution of outpatient healthcare expenditure, a dynamic micro-simulation using the Destinie model," Documents de Travail de l'Insee - INSEE Working Papers g2015-15, Institut National de la Statistique et des Etudes Economiques.
    17. Heres-Del-Valle, David & Niemeier, Deb, 2011. "CO2 emissions: Are land-use changes enough for California to reduce VMT? Specification of a two-part model with instrumental variables," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 150-161, January.
    18. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
    19. Galina Besstremyannaya, 2012. "Estimating income equity in social health insurance system," Working Papers w0172, New Economic School (NES).
    20. Catalina Amuedo-Dorantes & Susan Pozo, 2011. "New evidence on the role of remittances on healthcare expenditures by Mexican households," Review of Economics of the Household, Springer, vol. 9(1), pages 69-98, March.

    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:hlthec:v:17:y:2008:i:1:p:41-54. 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://www3.interscience.wiley.com/cgi-bin/jhome/5749 .

    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.