Skip to main content
Article
Licensed
Unlicensed Requires Authentication

Political Cycles in Military Deployment

  • EMAIL logo , and
Published/Copyright: September 4, 2017

Abstract

The determinants of military deployment have been extensively discussed in the literature. Empirical studies indicate that, next to the international security arena, also domestic socio-economic variables play an important role. For example, wealth and size of the supplying nation tend to positively influence the number of military troops being deployed. The present study contributes to this literature by focusing on a set of political variables, i.e. the effect of upcoming elections as well as the composition of government. For a cross-sectional time-series of 34 democratic countries, covering the period from 1990 until 2014, we run a linear (fixed effects) panel regression model correcting for a first order autoregressive disturbance term as well as linear dynamic models with diverse corrections. When studying deployment at country level, we find a negative and significant impact of elections on the number of troops deployed, meaning that a country deploys fewer troops close to elections. As for government composition, we observe that rather central administrations deploy substantially fewer troops than right- or left-wing governments.

JEL Classification: F51; D74; F53

A Appendix

Table 3:

Overview of all UN and non-UN missions and locations included in the dataset (alphabetical order).

MissionLocationMissionLocation
UN missions
 BINUBBurundiONUMOZMozambique
 BONUCACentral African RepublicONUSALEl Salvador
 IPTFBosnia and HerzegovinaUNAMAAfghanistan
 LBBItalyUNAMETTimor-Leste
 MICAHHaitiUNAMIIraq
 MINUCIIvory CoastUNAMICCambodia
 MINUGUAGuatemalaUNAMIDSudan
 MINURCACentral African RepublicUNMIHHaiti
 MINURCATChadUNMIKSerbia
 MINURSOWestern SaharaUNMILLiberia
 MINUSCACentral African RepublicUNMINNepal
 MINUSMAMaliUNMISSudan
 MINUSTAHHaitiUNMISETTimor-Leste
 MIPONUHHaitiUNMISSSouth Sudan
 MONUAAngolaUNMITTimor-Leste
 MONUCDR CongoUNMOGIPPakistan
 MONUSCODR CongoUNMOPCroatia
 ONUBBurundiUNMOTTajikistan
 ONUCAHondurasUNOAAngola
 ONUCIIvory CoastUNOCIIvory Coast
 UNAMIRRuandaUNOMILLiberia
 UNAMSILSierra LeoneUNOMSILSierra Leone
 UNAVEMAngolaUNOMURUganda
 UNCROCroatiaUNOSOMSomalia
 UNDOFSyrian Arab RepublicUNOTILTimor-Leste
 UNFICYPCyprusUNPFCroatia
 UNFORCroatiaUNPREDEPMacedonia
 UNIFILLebanonUNPROFORCroatia
 UNIIMOGIranUNPSGCroatia
 UNIKOMIraqUNSMIHHaiti
 UNIOSILSierra LeoneUNSMISSyrian Arab Republic
 UNISFASudanUNTACCambodia
 UNMAAngolaUNTAESCroatia
 UNMEEEritreaUNTAETTimor-Leste
 UNMIBHBosnia and HerzegovinaUNTMIHHaiti
 UNOMIGGeorgiaUNTSOIsrael
Non-UN missions
 AFORAlbaniaKVMKosovo
 AMISIIEthiopiaLicorneCôte d’Ivoire
 AMISONSomaliaMFOEgypt
 AMMIndonesiaMIATMMalta
 ArgusAfghanistanMICOPAXCentral African Republic
 ASTUTETimor-LesteMinsk ConferenceArmenia and Azerbaijan
 Augural (AMIS)SudanMNF-Iraq/US Forces IraqIraq
 BoaliCentral African RepublicNATOMacedonia and Kyrgyzstan
 BougainvillePapua New GuineaNATO COMMZ-WAlbania
 BPSTKenyaNATO HQ TiranaAlbania
 BronzeBosnia-HerzegovinaNew DawnIraq
 CJTFDjibuti and KuwaitNNSCS Korea
 CMACCambodiaNorthern WatchTurkey
 CSCEFormer YugoslaviaNTM-IIraq
 Deliberate ForgeItalyOEFAfghanistan, Kuweit, Kyrgyzstan, Kenya, Horn of Africa, Gulf, US, Pakistan
 Dent FlightItalyOp AccordionUnited Arab Emirates
 DIATMMoroccoOp AlbaAlbania
 DIEAlbaniaOp Amber FoxMacedonia, FYR
 ECMMFormer YugoslaviaOp BarkhaneChad, Mali and Niger
 EEKosovoOp ConcordiaMacedonia, FYR
 EECCroatiaOp GritlockSierra Leone
 EpervierChadOp ImpactKuwait and Iraq
 EU Military StaffUS, New YorkOp JaguarJamaica
 EUFORBosnia-HerzegovinaOp New DawnIraq
 EUFOR (RCA)Central African RepublicOp OkraUnited Arab Emirates
 EUFOR IBosnia-Herz and ItalyOp SangarisCentral African Republic
 EUFOR IIBosnia/CroatiaOp United AssistanceLiberia
 EUFOR II/KFORItalyOSCEGeorgia, Montenegro, Albania, Bosnia-Herzegovina, Bosnia, Serbia and Moldova
 EUFOR RD CongoDR Congo and GabonOSCE Higher Level PlanningVienna
 EUFOR Tchad/RCAChad and Central African RepublicPeace Support (Iraq)Iraq and Kuweit
 EUMMAlbania, Serbia, Bosnia-HerzOSCE Minsk ConferenceArmenia and Azerbaijan
 EUMM/EUPMMacedonia and BosniaProteusJerusalem
 EUPM (Proxima)Macedonia, FYRProvide ComfortTurkey
 EUPOLAfghanistanProvide PromiseFormer Yugoslavia
 EUPOL KinshasaCongo, DRRAMSI (Op Anode)Solomon Islands
 EUTMUgandaServalMali
 SHAPEBelgiumSFOR (Air C)Croatia, Bosnia, Hungary and Italy
 HRSaKuwaitSFOR Air Element (Op Joint Guard)Bosnia-Herzegovina, Croatia, Hungary, Italy, France, Germany, UK
 IFORBosnia, Croatia, HungarySFOR IIBosnia
 IFOR Air CompItalySFOR II/KFORItaly
 IMATT (Sculpture)Sierra LeoneSouthern WatchSaudi Arabia, Bahrain, Iraq and Kuweit
 Iraqi FreedomKuwaitSupport HopeRwanda
 ISAF (OEF)AfghanistanTamourJordan
 ISFTimor-LesteTask Force Tampa or Foundation (US CENTCOM)US and Bahrain
 Joint GuarantorKosovoTIPH (2)Palestinian Autonomous Areas of Gaza and Jericho
 Joint GuardianYugoslaviaTIPHZHebron
 KFOR(Former) YugoslaviaUnknownIraq, Rwanda, Tajikistan, (former) Yugoslavia, Kosovo, Kuweit, Sierra Leone, Macedonia, Kyrgyzstan, Uzbekistan
 KFOR (Joint Enterprise)Serbia (Kosovo) and MacedoniaUXOLLaos
 KFOR ISerbia and Montenegro and Macedonia
  1. aHumanitarian reconstruction support.

B Appendix

The first model allowing for an autoregressive disturbance term is run under fixed effects following the results of a simple Hausman test. The Baltagi Wu Lbi statistic is calculated to check for potential autocorrelation issues. It is just above the critical value of 2. In general, higher values than 2 could indicate an underestimation of significance levels. Both the second (Arellano and Bond) and third (Blundell and Bond) estimation are evaluated by testing for potential serial correlation in the transformed errors and for the validity of the over-identifying conditions.[8] The former indeed reveals slight issues, suggesting that the Windmeijer correction is be more appropriate. The Sargan post-estimation test for the latter indeed seems to confirm more consistent estimates.

References

Achen, C. (2001). Why lagged dependent variables can suppress the explanatory power of the other independent variables. Accessed 31 May 2017 Available online: https://www.princeton.edu/csdp/events/Achen121201/achen.pdf.Search in Google Scholar

Andersson, A. (2002). United Nations intervention by united democracies? State commitment to UN interventions 1991–99. Cooperation and Conflict, 37(4), 363–386.10.1177/001083602762574469Search in Google Scholar

Arellano, M. & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297.10.2307/2297968Search in Google Scholar

Bellamy, A. J. & Williams, P. D. (2013). Introductio. Alex, J. & Paul D. Williams (Eds.), Providing peacekeepers (pp. 1–22). Oxford: Oxford University Press.10.1093/acprof:oso/9780199672820.001.0001Search in Google Scholar

Blundell, R. & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87, 115–143.10.1016/S0304-4076(98)00009-8Search in Google Scholar

Bove, V., Efthyvoulou, G. & Navas, A. (2016). Political cycles in public expenditure: Butter vs guns. Journal of Comparative Economics. in press. DOI: 10.1016/j.jce.2016.03.004.Search in Google Scholar

Bove, V. & Elia, L. (2011). Supplying peace: Participation in and troop contribution to peacekeeping missions. Journal of Peace Research, 48(6), 699–714.10.1177/0022343311418265Search in Google Scholar

Choi, S.-W. (2013). What determines US humanitarian intervention? Conflict Management and Peace Science, 30(2), 121–139.10.1177/0738894212473916Search in Google Scholar

Du Bois, C., Buts, C. & Raes, S. (2015). Post-Somalia syndrome: Does it exist? Peace Economics, Peace Science and Public Policy, 21(4), 515–522.10.1515/peps-2015-0025Search in Google Scholar

Dubois, E. (2016). Political business cycles 40 years after Nordhaus. Public Choice, 166(1), 235–259.10.1007/s11127-016-0313-zSearch in Google Scholar

Eichenberg, R. C. & Stoll, R. (2003). Representing defense: Democratic control of the defense budget in the US and Western Europe. Journal of Conflict Resolution, 47(4), 399–422.10.1177/0022002703254477Search in Google Scholar

Gaibulloev, K., Sandler, T. & Shimizu, H. (2009). Demands for UN and non-UN peacekeeping. Nonvoluntary versus voluntary contributions to a public good. Journal of Conflict Resolution, 53(6), 827–852.10.1177/0022002709338509Search in Google Scholar

Gaibulloev, K., Georg, J. Sandler, T. & Shimizu, H. (2015). Personnel contributions to UN and non-UN peacekeeping missions. A public goods approach. Journal of Peace Research, 52(6), 727–742. 10.1177/0022343315579245Search in Google Scholar

International Institute for Strategic Studies, 1990–2014. The Military Balance.Search in Google Scholar

Karagol, E. T. & Turhan, A. (2008). External debt, defense expenditures and political business cycles in Turkey. Defence and Peace Economics, 19(3), 217–224.10.1080/10242690801972170Search in Google Scholar

Kauder, B. & Potrafke, N. (2016). The growth in military expenditure in Germany 1951–2011: Did parties matter? Defence and Peace Economics, 27(4), 503–519.10.1080/10242694.2015.1050276Search in Google Scholar

Klaus, A., Isler, C., Knöpfel, L., Weisstanner, D. & Engler, S. (2016). Comparative political data set 1960–2014. Bern: Institute of Political Science, University of Berne.Search in Google Scholar

Rogoff, K. (1990). Equilibrium Political Budget Cycles. American Economic Review, 80(1), 21–36.10.3386/w2428Search in Google Scholar

Sandler, T. (1990–2012). Database deployment. University of Texas at Dallas.Search in Google Scholar

StataCorp. (2015). Stata user’s guide (Release 14). Texas: StataPress.Search in Google Scholar

Stojek, S. M. & Tir, J. (2014). The supply side of United Nations peacekeeping operations: Trade ties and United Nations-led deployments to civil war states. European Journal of International Relations, 21(2), 352–376.10.1177/1354066114532665Search in Google Scholar

Uzonyi, G. (2015). Refugee flows and state contributions to post-Cold War UN peacekeeping missions. Journal of Peace Research, 52(6), 743–757.10.1177/0022343315574353Search in Google Scholar

Whitten, G. D. & Williams, L. K. (2011). Buttery guns and welfare hawks: The politics of defense spending in advanced industrial democracies. American Journal of Political Science, 55(1), 117–134.10.1111/j.1540-5907.2010.00479.xSearch in Google Scholar

Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics, 126(1), 25–51.10.1016/j.jeconom.2004.02.005Search in Google Scholar

Published Online: 2017-9-4

©2017 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 22.4.2026 from https://www.degruyterbrill.com/document/doi/10.1515/peps-2017-0025/html
Scroll to top button