IDEAS home Printed from https://ideas.repec.org/a/sae/jocore/v25y1981i2p259-288.html
   My bibliography  Save this article

Arms Race Modeling

Author

Listed:
  • Stephen J. Majeski

    (Department of Political Science Syracuse University)

  • David L. Jones

    (Department of Political Science University of Illinois)

Abstract

The Richardson model has been employed frequently in the study of arm races, but seldom with empirically satisfactory results. For each of twelve pairs of arms expenditure series which are commonly proposed as arms races, we consider two potential sources for the failure of Richardson modeling efforts. First, they may not constitute arms races. Second, for those which do, the Richardson model specification may not be adequate. The methodology which enables us to explore these issues is "statistical causality analysis," as recently promulgated in time series research. Using this methodology, we find that arms expenditures are independent in a majority of the twelve cases examined. For those cases where interdependence is found, those which exhibit arms competition, the traditional Richardson model specification is not empirically supported. Finally, we provide a specific methodology for improved model specification derived from a general distributed lag model for any proposed arms race.

Suggested Citation

  • Stephen J. Majeski & David L. Jones, 1981. "Arms Race Modeling," Journal of Conflict Resolution, Peace Science Society (International), vol. 25(2), pages 259-288, June.
    • Handle: RePEc:sae:jocore:v:25:y:1981:i:2:p:259-288
    DOI: 10.1177/002200278102500203
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/002200278102500203
    Download Restriction: no
    File URL: https://libkey.io/10.1177/002200278102500203?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. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    2. Feige, Edgar L & Pearce, Douglas K, 1976. "Economically Rational Expectations: Are Innovations in the Rate of Inflation Independent of Innovations in Measures of Monetary and Fiscal Policy?," Journal of Political Economy, University of Chicago Press, vol. 84(3), pages 499-522, June.
    3. Davis, Otto A. & Dempster, M. A. H. & Wildavsky, Aaron, 1966. "A Theory of the Budgetary Process," American Political Science Review, Cambridge University Press, vol. 60(3), pages 529-547, September.
    4. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    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. Hasan Sahin & Onur Ozsoy, 2008. "Arms Race Between Greece And Turkey: A Markov Switching Approach," Defence and Peace Economics, Taylor & Francis Journals, vol. 19(3), pages 209-216.
    2. Christos Kollias, 1997. "Defence spending and growth in turkey 1954-1993: A causal analysis," Defence and Peace Economics, Taylor & Francis Journals, vol. 8(2), pages 189-204.

    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. Xiaojie Xu, 2017. "The rolling causal structure between the Chinese stock index and futures," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(4), pages 491-509, November.
    2. Mishkin, Frederic S, 1982. "Does Anticipated Monetary Policy Matter? An Econometric Investigation," Journal of Political Economy, University of Chicago Press, vol. 90(1), pages 22-51, February.
    3. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    4. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, vol. 42(C), pages 152-160.
    5. Zapata, Hector O. & Gil, Jose M., 1999. "Cointegration and causality in international agricultural economics research," Agricultural Economics, Blackwell, vol. 20(1), pages 1-9, January.
    6. Francisco F. R. Ramos, 1996. "Forecasting market shares using VAR and BVAR models: A comparison of their forecasting performance," Econometrics 9601003, University Library of Munich, Germany.
    7. Pardey, Philip G. & Craig, Barbara J., 1987. "Dynamics Of The Agricultural Research And Output Relationship," Staff Papers 13515, University of Minnesota, Department of Applied Economics.
    8. Phipps, Tim, 1982. "Farmland Prices and the Return to Land: An Application of Causality Testing," 1982 Annual Meeting, August 1-4, Logan, Utah 279162, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Richard A. Ashley & Kwok Ping Tsang, 2014. "Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach," Econometrics, MDPI, vol. 2(1), pages 1-20, March.
    10. Langley, Suchada Vichitakul, 1982. "The formation of price expectations: a case study of the soybean market," ISU General Staff Papers 198201010800009358, Iowa State University, Department of Economics.
    11. Krishna, Kala & Ozyildirim, Ataman & Swanson, Norman R., 2003. "Trade, investment and growth: nexus, analysis and prognosis," Journal of Development Economics, Elsevier, vol. 70(2), pages 479-499, April.
    12. McCrorie, J. Roderick & Chambers, Marcus J., 2006. "Granger causality and the sampling of economic processes," Journal of Econometrics, Elsevier, vol. 132(2), pages 311-336, June.
    13. Steven M. Shugan, 2007. "—Causality, Unintended Consequences and Deducing Shared Causes," Marketing Science, INFORMS, vol. 26(6), pages 731-741, 11-12.
    14. Bajo-Rubio, Oscar & Sosvilla-Rivero, Simon & Fernandez-Rodriguez, Fernando, 2001. "Asymmetry in the EMS: New evidence based on non-linear forecasts," European Economic Review, Elsevier, vol. 45(3), pages 451-473, March.
    15. Tae-Hwy Lee & Weiping Yang, 2012. "Money–Income Granger-Causality in Quantiles," Advances in Econometrics, in: 30th Anniversary Edition, pages 385-409, Emerald Group Publishing Limited.
    16. Hu, Beibei & Ding, Yang & Dong, Xianlei & Bu, Yi & Ding, Ying, 2021. "On the relationship between download and citation counts: An introduction of Granger-causality inference," Journal of Informetrics, Elsevier, vol. 15(2).
    17. Al Awad, Mouawiya & Goodwin, Barry K., 1998. "Dynamic linkages among real interest rates in international capital markets," Journal of International Money and Finance, Elsevier, vol. 17(6), pages 881-907, December.
    18. Hendry, David F. & Mizon, Grayham E., 2001. "Reformulating empirical macro-econometric modelling," Discussion Paper Series In Economics And Econometrics 0104, Economics Division, School of Social Sciences, University of Southampton.
    19. Wang, Zijun & Yang, Jian & Li, Qi, 2007. "Interest rate linkages in the Eurocurrency market: Contemporaneous and out-of-sample Granger causality tests," Journal of International Money and Finance, Elsevier, vol. 26(1), pages 86-103, February.
    20. Bwo‐Nung Huang & Chin‐Wei Yang, 2004. "Industrial output and stock price revisited: an application of the multivariate indirect causality model," Manchester School, University of Manchester, vol. 72(3), pages 347-362, June.

    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:sae:jocore:v:25:y:1981:i:2:p:259-288. 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: SAGE Publications (email available below). General contact details of provider: http://pss.la.psu.edu/ .

    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.