IDEAS home Printed from https://ideas.repec.org/p/ags/aaea09/49272.html
   My bibliography  Save this paper

The Last of the American Ag Economists

Author

Listed:
  • Epperson, James E.

Abstract

It has become more and more difficult to recruit prospective American Ph.D. students in Agricultural and Applied Economics. The purpose of this study was to determine the extent of the problem, to ascertain why with respect to location and other important factors, and hopefully deduce recruiting solutions. Results indicate that the paramount factors in a profile of those willing to pay the price in terms of sacrifice and effort to obtain a Ph.D. encompass willingness to accept a relatively low starting salary with a Ph.D., likely to be a Foreign National, prone to be in a Midwestern university, and willing to relocate globally. Generally, the Ph.D. starting salary would have to increase dramatically to change the minds of graduate students not intending to pursue a Ph.D. including most American graduate students. A change in public policy appears to be the only real solution.

Suggested Citation

  • Epperson, James E., 2009. "The Last of the American Ag Economists," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49272, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea09:49272
    DOI: 10.22004/ag.econ.49272
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/49272/files/Ph.D.%20Paper%204.29.09.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.49272?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Estrella, Arturo, 1998. "A New Measure of Fit for Equations with Dichotomous Dependent Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 198-205, 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. Jiao, Yang & Qi, Li & Chen, Zhuo, 2023. "Academic profile of Chinese economists: Productivity, pay, time use, gender differences, and impacts of COVID-19," China Economic Review, Elsevier, vol. 81(C).

    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. Esther Fernández Galar & Javier Gómez Biscarri, 2003. "Revisiting the Ability of Interest Rate Spreads to Predict Recessions: Evidence for a," Faculty Working Papers 04/03, School of Economics and Business Administration, University of Navarra.
    2. Franck Sédillot, 2001. "La pente des taux contient-elle de l'information sur l'activité économique future ?," Economie & Prévision, La Documentation Française, vol. 147(1), pages 141-157.
    3. Christelis, Dimitris & Jappelli, Tullio & Padula, Mario, 2010. "Cognitive abilities and portfolio choice," European Economic Review, Elsevier, vol. 54(1), pages 18-38, January.
    4. Karl Taylor & Robert McNabb, 2007. "Business Cycles and the Role of Confidence: Evidence for Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(2), pages 185-208, April.
    5. Ahmed, Jameel & Straetmans, Stefan, 2015. "Predicting exchange rate cycles utilizing risk factors," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 112-130.
    6. Qi, Min, 2001. "Predicting US recessions with leading indicators via neural network models," International Journal of Forecasting, Elsevier, vol. 17(3), pages 383-401.
    7. Alexey Mikhaylov, 2019. "Oil and Gas Budget Revenues in Russia after Crisis in 2015," International Journal of Energy Economics and Policy, Econjournals, vol. 9(2), pages 375-380.
    8. Tillmann, Peter, 2007. "Inflation regimes in the US term structure of interest rates," Economic Modelling, Elsevier, vol. 24(2), pages 203-223, March.
    9. Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
    10. Zhihong Chen & Azhar Iqbal & Huiwen Lai, 2011. "Forecasting the probability of US recessions: a Probit and dynamic factor modelling approach," Canadian Journal of Economics, Canadian Economics Association, vol. 44(2), pages 651-672, May.
    11. A. Montini, 1999. "I consumi alimentari delle famiglie italiane: un modello per le decisioni di consumo extradomestico utilizzando i microdati di spesa familiare," Working Papers 364, Dipartimento Scienze Economiche, Universita' di Bologna.
    12. Richard H. Clarida & Lucio Sarno & Mark P. Taylor & Giorgio Valente, 2006. "The Role of Asymmetries and Regime Shifts in the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1193-1224, May.
    13. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    14. Michael LaCour-Little & Michael Marschoun & Clark L. Maxam, 2002. "Improving Parametric Mortgage Prepayment Models with Non-parametric Kernel Regression," Journal of Real Estate Research, American Real Estate Society, vol. 24(3), pages 299-328.
    15. repec:spo:wpmain:info:hdl:2441/6407 is not listed on IDEAS
    16. Christophe Blot & Grégory Levieuge, 2008. "Are MCIs Good Indicators of Economic Activity ? Evidence from the G7 Countries," Working Papers hal-00973056, HAL.
    17. Harri Pönkä, 2018. "Sentiment and sign predictability of stock returns," Economics Bulletin, AccessEcon, vol. 38(3), pages 1676-1684.
    18. Heikki Kauppi, 2008. "Yield-Curve Based Probit Models for Forecasting U.S. Recessions: Stability and Dynamics," Discussion Papers 31, Aboa Centre for Economics.
    19. Haase, Felix & Neuenkirch, Matthias, 2023. "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
    20. Bronwyn H. Hall & Albert N. Link & John T. Scott, 2003. "Universities as Research Partners," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 485-491, May.
    21. Liu, Jingzhen & Kemp, Alexander, 2019. "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, vol. 81(C), pages 672-686.

    More about this item

    Keywords

    Labor and Human Capital;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:aaea09:49272. 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.