IDEAS home Printed from https://ideas.repec.org/a/rfa/aefjnl/v4y2017i4p145-159.html
   My bibliography  Save this article

Effects of Food Assistance Programs, Demographic Characteristics, and Living Environments on Children¡¯s Food Insecurity

Author

Listed:
  • Zhiming Qiu
  • Chanjin Chung

Abstract

The objective of this study is to examine impacts of food assistance programs, demographic characteristics, and socioeconomic status of households on children¡¯s food insecurity in U.S. Annual cross-sectional and pseudo-panel analyses with fixed effect regressions are conducted in this study using probit and truncated regressions. The simultaneous equation procedure is applied to address the endogeneity problem caused by the reverse influence of food insecurity on participation of food programs. Results show that some government-sponsored food programs are effective in alleviating the children¡¯s food insecurity problem, and demographic characteristics and living environments are important factors in determining the status of children¡¯s food insecurity. Our results also manifest the importance of considering the endogeneity problem of food program variables in evaluating the effectiveness of food programs.

Suggested Citation

  • Zhiming Qiu & Chanjin Chung, 2017. "Effects of Food Assistance Programs, Demographic Characteristics, and Living Environments on Children¡¯s Food Insecurity," Applied Economics and Finance, Redfame publishing, vol. 4(4), pages 145-159, July.
    • Handle: RePEc:rfa:aefjnl:v:4:y:2017:i:4:p:145-159
    as

    Download full text from publisher

    File URL: http://redfame.com/journal/index.php/aef/article/view/2507/2644
    Download Restriction: no
    File URL: http://redfame.com/journal/index.php/aef/article/view/2507
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richard Blundell & Martin Browning & Costas Meghir, 1994. "Consumer Demand and the Life-Cycle Allocation of Household Expenditures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(1), pages 57-80.
    2. Mª Dolores Collado, 1998. "Estimating binary choice models from cohort data," Investigaciones Economicas, Fundación SEPI, vol. 22(2), pages 259-276, May.
    3. Verbeek, Marno & Nijman, Theo, 1992. "Can Cohort Data Be Treated as Genuine Panel Data?," Empirical Economics, Springer, vol. 17(1), pages 9-23.
    4. Bishop, John A & Formby, John P & Zeager, Lester A, 1996. "The Impact of Food Stamps on US Poverty in the 1980s: A Marginal Dominance Analysis," Economica, London School of Economics and Political Science, vol. 63(250), pages 141-162, Suppl..
    5. Sonya Kostova Huffman & Helen H. Jensen, 2008. "Food Assistance Programs and Outcomes in the Context of Welfare Reform," Social Science Quarterly, Southwestern Social Science Association, vol. 89(1), pages 95-115, March.
    6. Baker, Judy L. & Grosh, Margaret E., 1994. "Poverty reduction through geographic targeting: How well does it work?," World Development, Elsevier, vol. 22(7), pages 983-995, July.
    7. Christian A. Gregory & Alisha Coleman-Jensen, 2013. "Do High Food Prices Increase Food Insecurity in the United States?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 35(4), pages 679-707.
    8. Albert J. Reed & J. William Levedahl, 2010. "Food Stamps and the Market Demand for Food," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1392-1400.
    9. Alaimo, K. & Olson, C.M. & Frongillo E.A., Jr. & Briefel, R.R., 2001. "Food insufficiency, family income, and health in US preschool and school-aged children," American Journal of Public Health, American Public Health Association, vol. 91(5), pages 781-786.
    10. Rachel Dunifon & Lori Kowaleski-Jones, 2001. "Associations Between Participation in the National School Lunch Program, Food Insecurity, and Child Well-Being," JCPR Working Papers 249, Northwestern University/University of Chicago Joint Center for Poverty Research.
    11. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    12. Coleman-Jensen, Alisha & Nord, Mark & Singh, Anita, 2013. "Household Food Security in the United States in 2012," Economic Research Report 262219, United States Department of Agriculture, Economic Research Service.
    13. Bernard, Jean-Thomas & Bolduc, Denis & Yameogo, Nadège-Désirée, 2011. "A pseudo-panel data model of household electricity demand," Resource and Energy Economics, Elsevier, vol. 33(1), pages 315-325, January.
    14. Mallar, Charles D, 1977. "The Estimation of Simultaneous Probability Models," Econometrica, Econometric Society, vol. 45(7), pages 1717-1722, October.
    15. Ribar, David C. & Hamrick, Karen S., 2003. "Dynamics Of Poverty And Food Sufficiency," Food Assistance and Nutrition Research Reports 33851, United States Department of Agriculture, Economic Research Service.
    16. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Can cohort data be treated as genuine panel data?," Other publications TiSEM d4eada8f-b91c-4fe7-a58c-7, Tilburg University, School of Economics and Management.
    17. Caroline Ratcliffe & Signe-Mary McKernan & Sisi Zhang, 2011. "How Much Does the Supplemental Nutrition Assistance Program Reduce Food Insecurity?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(4), pages 1082-1098.
    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. Rumman Khan, 2018. "Assessing cohort aggregation to minimise bias in pseudo-panels," Discussion Papers 2018-01, University of Nottingham, CREDIT.
    2. Verbeek, Marno & Vella, Francis, 2005. "Estimating dynamic models from repeated cross-sections," Journal of Econometrics, Elsevier, vol. 127(1), pages 83-102, July.
    3. Sarah Bridges & Simona Mateut, 2009. "Attitudes towards immigration in Europe," Working Papers 2009008, The University of Sheffield, Department of Economics, revised May 2009.
    4. Chi-Hong (Patrick) Tsai & Corinne Mulley & Geoffrey Clifton, 2014. "A Review of Pseudo Panel Data Approach in Estimating Short-run and Long-run Public Transport Demand Elasticities," Transport Reviews, Taylor & Francis Journals, vol. 34(1), pages 102-121, January.
    5. repec:mpr:mprres:8084 is not listed on IDEAS
    6. Yancy Vaillant & Esteban Lafuente & Manoj Chandra Bayon, 2019. "Early internationalization patterns and export market persistence: a pseudo-panel data analysis," Small Business Economics, Springer, vol. 53(3), pages 669-686, October.
    7. Charles Ackah, & Oliver Morrissey, & Simon Appleton, 2007. "Who Gains from Trade Protection in Ghana? A Household-Level Analysis," Discussion Papers 07/02, University of Nottingham, CREDIT.
    8. Antonio Cutanda & José M. Labeaga & Juan A. Sanchis-Llopis, 2020. "Aggregation biases in empirical Euler consumption equations: evidence from Spanish data," Empirical Economics, Springer, vol. 58(3), pages 957-977, March.
    9. Kanang Amos Akims & Perez Ayieko Onono & Dianah Mukwate Ngui, . "Trade Liberalization and Productivity in the Nigerian Manufacturing Sector," Journal of Economic and Sustainable Growth 3, Office Of The Chief Economist, Development Bank of Nigeria.
    10. Mª Dolores Collado, 1998. "Estimating binary choice models from cohort data," Investigaciones Economicas, Fundación SEPI, vol. 22(2), pages 259-276, May.
    11. Dolores Collado, M., 1997. "Estimating dynamic models from time series of independent cross-sections," Journal of Econometrics, Elsevier, vol. 82(1), pages 37-62.
    12. Rumman Khan, 2021. "Assessing Sampling Error in Pseudo‐Panel Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 742-769, June.
    13. Wilson, Norbert L. W. & Zheng, Yuqing & Burney, Shaheer & Kaiser, Harry M., 2016. "Do Grocery Food Sales Taxes Cause Food Insecurity?," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235324, Agricultural and Applied Economics Association.
    14. David Aristei & Luca Pieroni, 2010. "Habits, Complementarities and Heterogeneity in Alcohol and Tobacco Demand: A Multivariate Dynamic Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 428-457, August.
    15. Inkmann, Joachim & Klotz, Stefan & Pohlmeier, Winfried, 1998. "Growing into Work - Pseudo Panel Data Evidence on Labor Market Entrance in Germany," ZEW Discussion Papers 98-47, ZEW - Leibniz Centre for European Economic Research.
    16. James Mabli, "undated". "SNAP Participation and Urban and Rural Food Security," Mathematica Policy Research Reports 99ba5f92f8434d3084c34a7d9, Mathematica Policy Research.
    17. Bernard, Jean-Thomas & Bolduc, Denis & Yameogo, Nadège-Désirée, 2011. "A pseudo-panel data model of household electricity demand," Resource and Energy Economics, Elsevier, vol. 33(1), pages 315-325, January.
    18. Kasraian, Dena & Maat, Kees & van Wee, Bert, 2018. "Urban developments and daily travel distances: Fixed, random and hybrid effects models using a Dutch pseudo-panel over three decades," Journal of Transport Geography, Elsevier, vol. 72(C), pages 228-236.
    19. Katsushi S. Imai & Takahiro Sato, 2014. "Recent Changes in Micro-Level Determinants of Fertility in India: Evidence from National Family Health Survey Data," Oxford Development Studies, Taylor & Francis Journals, vol. 42(1), pages 65-85, March.
    20. Friedrich Breyer & Normann Lorenz & Thomas Niebel, 2015. "Health care expenditures and longevity: is there a Eubie Blake effect?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(1), pages 95-112, January.
    21. Hong Liu & Wei Tan, 2009. "The Effect of Anti-Smoking Media Campaign on Smoking Behavior: The California Experience," Annals of Economics and Finance, Society for AEF, vol. 10(1), pages 29-47, May.

    More about this item

    Keywords

    food program; food insecurity; living environment; demographic characteristics; pseudo panel data; simultaneous equation procedure;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:rfa:aefjnl:v:4:y:2017:i:4:p:145-159. 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: Redfame publishing (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.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.