IDEAS home Printed from https://ideas.repec.org/a/eee/ehbiol/v13y2014icp34-45.html
   My bibliography  Save this article

How effective are public health departments at preventing mortality?

Author

Listed:
  • Brown, Timothy Tyler

Abstract

This study estimates the causal impact of variation in the expenditures of California county departments of public health on all-cause mortality rates and the associated value of lives saved. Since the activities of county departments of public health are likely to affect mortality rates with a lag, Koyck distributed lag models are estimated using the Lewbel instrumental variables estimator. The findings show that an additional $10 per capita of public health expenditures reduces all-cause mortality by 9.1 deaths per 100,000. At current funding levels, the long-run annual number of lives saved by the presence of county departments of public health in California is estimated to be approximately 27,000 (26,937 lives, 95% confidence interval: [11,963, 41,911]). The annual value of these lives is estimated to be worth $212.8 billion using inflation-adjusted standard U.S. government estimates of the value of a statistical life ($7.9 million).

Suggested Citation

  • Brown, Timothy Tyler, 2014. "How effective are public health departments at preventing mortality?," Economics & Human Biology, Elsevier, vol. 13(C), pages 34-45.
  • Handle: RePEc:eee:ehbiol:v:13:y:2014:i:c:p:34-45
    DOI: 10.1016/j.ehb.2013.10.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1570677X13000920
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ehb.2013.10.001?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. James Thornton, 2002. "Estimating a health production function for the US: some new evidence," Applied Economics, Taylor & Francis Journals, vol. 34(1), pages 59-62.
    2. Huang, Ho-Chuan (River) & Lin, Yi-Chen & Yeh, Chih-Chuan, 2009. "Joint determinations of inequality and growth," Economics Letters, Elsevier, vol. 103(3), pages 163-166, June.
    3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    4. Maurice J. G. Bun & Frank Windmeijer, 2010. "The weak instrument problem of the system GMM estimator in dynamic panel data models," Econometrics Journal, Royal Economic Society, vol. 13(1), pages 95-126, February.
    5. Bun, Maurice J. G. & Kiviet, Jan F., 2003. "On the diminishing returns of higher-order terms in asymptotic expansions of bias," Economics Letters, Elsevier, vol. 79(2), pages 145-152, May.
    6. Grossman, Michael, 2006. "Education and Nonmarket Outcomes," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 10, pages 577-633, Elsevier.
    7. Denny, Kevin & Oppedisano, Veruska, 2013. "The surprising effect of larger class sizes: Evidence using two identification strategies," Labour Economics, Elsevier, vol. 23(C), pages 57-65.
    8. Grembowski, David & Bekemeier, Betty & Conrad, Douglas & Kreuter, William, 2010. "Are local health department expenditures related to racial disparities in mortality?," Social Science & Medicine, Elsevier, vol. 71(12), pages 2057-2065, December.
    9. Tai-Hsin Huang & Zixiong Xie, 2013. "Population and economic growth: a simultaneous equation perspective," Applied Economics, Taylor & Francis Journals, vol. 45(27), pages 3820-3826, September.
    10. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    11. Matthew Lang, 2013. "The Impact Of Mental Health Insurance Laws On State Suicide Rates," Health Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 73-88, January.
    12. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    13. Douglas L. Miller & Marianne E. Page & Ann Huff Stevens & Mateusz Filipski, 2009. "Why Are Recessions Good for Your Health?," American Economic Review, American Economic Association, vol. 99(2), pages 122-127, May.
    14. Lichtenberg, Frank R., 2004. "Sources of U.S. longevity increase, 1960-2001," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(3), pages 369-389, July.
    15. N/A, 2009. "On the Recession," Local Economy, London South Bank University, vol. 24(3), pages 253-253, May.
    16. James Thornton, 2011. "Does more medical care improve population health? New evidence for an old controversy," Applied Economics, Taylor & Francis Journals, vol. 43(24), pages 3325-3336.
    17. David Stifel & Harold Alderman, 2006. "The "Glass of Milk" Subsidy Program and Malnutrition in Peru," The World Bank Economic Review, World Bank, vol. 20(3), pages 421-448.
    18. Christiane Schroeter & Sven Anders & Andrea Carlson, 2013. "The Economics of Health and Vitamin Consumption," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 35(1), pages 125-149.
    19. Joseph J. Sabia, 2007. "Early Adolescent Sex and Diminished School Attachment: Selection or Spillovers?," Southern Economic Journal, John Wiley & Sons, vol. 74(1), pages 239-268, July.
    20. Thomas J. Kniesner & W. Kip Viscusi & Christopher Woock & James P. Ziliak, 2012. "The Value of a Statistical Life: Evidence from Panel Data," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 74-87, February.
    21. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    22. M. Shahe Emran & Forhad Shilpi, 2012. "The extent of the market and stages of agricultural specialization," Canadian Journal of Economics, Canadian Economics Association, vol. 45(3), pages 1125-1153, August.
    23. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    24. Singh, G.K. & Siahpush, M., 2001. "All-cause and cause-specific mortality of immigrants and native born in the United States," American Journal of Public Health, American Public Health Association, vol. 91(3), pages 392-399.
    25. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    26. W. Viscusi, 2008. "How to value a life," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 32(4), pages 311-323, October.
    27. Andreas Drichoutis & Rodolfo Nayga & Panagiotis Lazaridis, 2012. "Food away from home expenditures and obesity among older Europeans: are there gender differences?," Empirical Economics, Springer, vol. 42(3), pages 1051-1078, June.
    28. Bruno, Giovanni S.F., 2005. "Approximating the bias of the LSDV estimator for dynamic unbalanced panel data models," Economics Letters, Elsevier, vol. 87(3), pages 361-366, June.
    29. Andrews,Donald W. K. & Stock,James H. (ed.), 2005. "Identification and Inference for Econometric Models," Cambridge Books, Cambridge University Press, number 9780521844413, September.
    30. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    31. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    32. Grossman, Michael, 2000. "The human capital model," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 7, pages 347-408, Elsevier.
    33. Joseph J. Sabia, 2007. "Reading, Writing, And Sex: The Effect Of Losing Virginity On Academic Performance," Economic Inquiry, Western Economic Association International, vol. 45(4), pages 647-670, October.
    34. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    35. Joseph J. Sabia, 2007. "The Effect of Body Weight on Adolescent Academic Performance," Southern Economic Journal, John Wiley & Sons, vol. 73(4), pages 871-900, April.
    36. Schroeter, Christiane & Anders, Sven M. & Carlson, Andrea & Rickard, Bradley J., 2010. "The Economics of Health Behavior and Vitamin Consumption," 115th Joint EAAE/AAEA Seminar, September 15-17, 2010, Freising-Weihenstephan, Germany 116391, European Association of Agricultural Economists.
    37. Erwin, P.C. & Greene, S.B. & Mays, G.P. & Ricketts, T.C. & Davis, M.V., 2011. "The association of changes in local health department resources with changes in state-level health outcomes," American Journal of Public Health, American Public Health Association, vol. 101(4), pages 609-615.
    38. Samuel Bazzi & Michael A. Clemens, 2013. "Blunt Instruments: Avoiding Common Pitfalls in Identifying the Causes of Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 152-186, April.
    39. Steven A. Block, 2007. "Maternal nutrition knowledge versus schooling as determinants of child micronutrient status," Oxford Economic Papers, Oxford University Press, vol. 59(2), pages 330-353, April.
    40. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    41. Alberto Palloni & Elizabeth Arias, 2004. "Paradox lost: Explaining the hispanic adult mortality advantage," Demography, Springer;Population Association of America (PAA), vol. 41(3), pages 385-415, August.
    42. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    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. Seuring, Till & Goryakin, Yevgeniy & Suhrcke, Marc, 2015. "The impact of diabetes on employment in Mexico," Economics & Human Biology, Elsevier, vol. 18(C), pages 85-100.
    2. Timothy Tyler Brown & Vishnu Murthy, 2020. "Do public health activities pay for themselves? The effect of county‐level public health expenditures on county‐level public assistance medical care benefits in California," Health Economics, John Wiley & Sons, Ltd., vol. 29(10), pages 1220-1230, October.
    3. Steven F. Koch & Evelyn Thsehla, 2022. "The impact of diabetes on labour market outcomes," Development Southern Africa, Taylor & Francis Journals, vol. 39(3), pages 424-456, May.
    4. Fortin, Bernard & Ragued, Safa, 2017. "Does temporary interruption in postsecondary education induce a wage penalty? Evidence from Canada," Economics of Education Review, Elsevier, vol. 58(C), pages 108-122.
    5. Ammi, Mehdi & Arpin, Emmanuelle & Dedewanou, F. Antoine & Allin, Sara, 2024. "Do expenditures on public health reduce preventable mortality in the long run? Evidence from the Canadian provinces," Social Science & Medicine, Elsevier, vol. 345(C).
    6. Waziri, Salisu Ibrahim & Mohamed Nor, Norashidah & Law, Siong Hook & Hassan, Azman, 2018. "Access to Safe Drinking Water, Good Sanitation, Occurrence of Under-Five Mortality and Standard of Living in Developing Countries: System GMM Approach," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 52(2), pages 279-289.
    7. Jie Liu & Ziqiang Han & Justin Veuthey & Ben Ma, 2020. "How investment in public health has impacted the prevalence of tuberculosis in China: A study of provincial variations between 2005 and 2015," International Journal of Health Planning and Management, Wiley Blackwell, vol. 35(6), pages 1546-1558, November.
    8. Piekalkiewicz, Marcin, 2016. "Money, Social Capital and Materialism. Evidence from Happiness Data," EconStor Preprints 130185, ZBW - Leibniz Information Centre for Economics.
    9. Craig Arthur Gallet, 2017. "The Impact of Public Health Spending on California STD Rates," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 23(2), pages 149-159, May.
    10. Seuring, Till & Serneels, Pieter & Suhrcke, Marc, 2019. "The impact of diabetes on labour market outcomes in Mexico: A panel data and biomarker analysis," Social Science & Medicine, Elsevier, vol. 233(C), pages 252-261.
    11. Yoon, Jangho & Luck, Jeff, 2016. "Intersystem return on investment in public mental health: Positive externality of public mental health expenditure for the jail system in the U.S," Social Science & Medicine, Elsevier, vol. 170(C), pages 133-142.
    12. Carrieri, V.; Jones, A.M.;, 2017. "Intergenerational transmission of nicotine within families: have e-cigarettes had an impact?," Health, Econometrics and Data Group (HEDG) Working Papers 17/03, HEDG, c/o Department of Economics, University of York.
    13. Stephen Martin & James Lomas & Karl Claxton, 2019. "Is an ounce of prevention worth a pound of cure? Estimates of the impact of English public health grant on mortality and morbidity," Working Papers 166cherp, Centre for Health Economics, University of York.

    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. Roberto Dell'Anno & Adalgiso Amendola, 2015. "Social Exclusion and Economic Growth: An Empirical Investigation in European Economies," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 61(2), pages 274-301, June.
    2. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 70628, University Library of Munich, Germany.
    3. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    4. Alexander Chudik & M. Hashem Pesaran, 2017. "A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels," CESifo Working Paper Series 6688, CESifo.
    5. Biørn, Erik, 2012. "The Measurement Error Problem in Dynamic Panel Data Analysis: Modeling and GMM Estimation," Memorandum 02/2012, Oslo University, Department of Economics.
    6. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute.
    7. Robert Baumann & Victor A. Matheson, 2013. "Estimating economic impact using ex post econometric analysis: cautionary tales," Chapters, in: Plácido Rodríguez & Stefan Késenne & Jaume García (ed.), The Econometrics of Sport, chapter 10, pages 169-188, Edward Elgar Publishing.
    8. Martínez-Zarzoso, Inmaculada & Maruotti, Antonello, 2011. "The impact of urbanization on CO2 emissions: Evidence from developing countries," Ecological Economics, Elsevier, vol. 70(7), pages 1344-1353, May.
    9. Jochimsen, Beate & Thomasius, Sebastian, 2014. "The perfect finance minister: Whom to appoint as finance minister to balance the budget," European Journal of Political Economy, Elsevier, vol. 34(C), pages 390-408.
    10. Yannis Psycharis & Stavroula Iliopoulou & Maria Zoi & Panagiotis Pantazis, 2021. "Beyond the socio‐economic use of fiscal transfers: The role of political factors in Greek intergovernmental grant allocations," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 982-1008, June.
    11. Biørn, Erik & Han, Xuehui, 2012. "Panel Data Dynamics and Measurement Errors: GMM Bias, IV Validity and Model Fit – A Monte Carlo Study," Memorandum 27/2012, Oslo University, Department of Economics.
    12. Alexander Chudik & M. Hashem Pesaran, 2017. "An Augmented Anderson-Hsiao Estimator for Dynamic Short-T Panels," Globalization Institute Working Papers 327, Federal Reserve Bank of Dallas, revised 27 Mar 2021.
    13. Huang, Yongfu, 2010. "Political Institutions and Financial Development: An Empirical Study," World Development, Elsevier, vol. 38(12), pages 1667-1677, December.
    14. Ricardo Barradas, 2023. "Why Has Labor Productivity Slowed Down in the Era of Financialization?: Insights from the Post-Keynesians for the European Union Countries," Review of Radical Political Economics, Union for Radical Political Economics, vol. 55(3), pages 390-422, September.
    15. Bakhat, Mohcine & Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2017. "Elasticities of transport fuels at times of economic crisis: An empirical analysis for Spain," Energy Economics, Elsevier, vol. 68(S1), pages 66-80.
    16. Yongfu Huang, 2005. "Will political liberalisation bring about financial development?," Bristol Economics Discussion Papers 05/578, School of Economics, University of Bristol, UK.
    17. Dang, Viet Anh & Kim, Minjoo & Shin, Yongcheol, 2015. "In search of robust methods for dynamic panel data models in empirical corporate finance," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 84-98.
    18. Garriga, Ana Carolina & Rodriguez, Cesar M., 2023. "Central bank independence and inflation volatility in developing countries," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1320-1341.
    19. Erik Biørn, 2015. "Panel data dynamics with mis-measured variables: modeling and GMM estimation," Empirical Economics, Springer, vol. 48(2), pages 517-535, March.
    20. DELL'ANNO, Roberto & VILLA, Stefania, 2012. "Growth in Transition Countries: Big Bang versus Gradualism," CELPE Discussion Papers 122, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.

    More about this item

    Keywords

    Public health expenditures; All-cause mortality; Lewbel instrumental variables; Dynamic panel models; California;
    All these keywords.

    JEL classification:

    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    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:eee:ehbiol:v:13:y:2014:i:c:p:34-45. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622964 .

    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.