1. Soft Modelling of Military Expenditures, Inequality and Profits
Ali Cevat Taşıran
Middle East Technical University, North Cyprus Campus
Adem Yavuz Elveren
Fitchburg State University, MA
January 6, 2017
Chicago

2. Milex Inequality Growth Kuznets Dunne & Uye (2010)
Study
Period
# of Countries
Method
Ali (2007)
160
2SLS
Ali (2012)
MENA
countries
Kentor et al. (2012) 82
GLS
Lin & Ali (2009) 58
Panel Granger
Töngür & Elveren (2015) 37
GMM
Töngür et al. (2015)
130
Dunne & Uye (2010)
i) negative and ambiguous effects are more common
ii) recent studies: negative effect
iii) positive effect is more pronounced in the case of developed countries
Milex
Political regimes, development, and conflict
Ali (2007)
Higher political & social instability
Ali (2007; 2012); Lin & Ali (2009); Kentor at al. (2012)
Töngür & Elveren (2015); Töngür, Hsu & Elveren (2015)
AD increasesbenefits poor relatively more
Pay is higher in military industries; guns-butter
less-skilled labor and skilled R&D personnel
Literature Survey: Dunne & Uye (2010) inter alia
Higher employment and output
Misallocation of resources
Inequality
Growth
Töngür & Elveren (2016) growth=f(milex, inequality)
Augmented Solow growth model,
82 countries,
Higher Shigher I; large sunk costs; higher work effort
Poor invest less in H; instabilityuncertinity & less investment
Kuznets

3. Milex Inequality Profit Elveren & Hsu (2016) 24 OECD countries
A panel autoregressive distributed lag model
for the whole period
in the post-1980 era
weak evidence: for arms-exporting countries, non-arms-exporter countries
Milex
Political regimes, development, and conflict
Ali (2007)
Higher political & social instability
Ali (2007; 2012); Lin & Ali (2009); Kentor at al. (2012)
Töngür & Elveren (2015); Töngür, Hsu & Elveren (2015)
AD increasesbenefits poor relatively more
Pay is higher in military industries; guns-butter
less-skilled labor and skilled R&D personnel
Increasing demand, increasing labor productivity, bringing about int. trade dominance
Crowding out, reducing productivity via “unreproductive” goods, increasing OCC by expanding a capital intensive sector
Elveren & Hsu (2016)
Inequality
Profit
Might be (+) in SR but (-) in LR, Vasudevan (2015)
Palley (2002), Dutt (2006), and Carvalho and Rezai (2016): high AD was maintained by “debt-fueled consumption”
Edward N. Wolf (2015) inter alia

4. Method Why Partial Least Squares Path Modelling (PLS-PM)?
Different theoriesDifferent conceptualizations different measurements of the variables incorrect types of empirical distribution functions of the Threevariate
No consistent empirical distribution specifications of Military Expenditures, Inequalities and Profits.
Problem is complex, theoretical knowledge is scarce/complex, and no information about distributions of the dependent variables
So, PLS modelling is the most appropriate technique in this context, as it uses Least-Squares oriented but distribution-free methods.

5. Data The analysis covers 21 countries for the years from 1988 to 2008
Argentina, Australia, Brazil, Canada, Chile, China, France, Germany, India, Indonesia, Italy, Japan, Korea, Mexico, Netherlands, Russia, Spain, Sweden, Turkey, UK, US
423 observations and 125 variables

6. Data Set
Source
World Income Distribution
COW
Nordhaus et al. (2012)
William Nordhaus, John R. Oneal and Bruce Russett (2012). The Effects of the International Security Environment on National Military Expenditures: A Multicountry Study. International Organization, 66, pp doi: / S
size of informal economy
Marxian profit rate
UTIP-UNIDO manufacturing Theil pay inequality index
UTIP-EHII inequality index
SIPRI
World Development Indicators
US Department of State’s Bureau of Verification and Compliance
Center for Systemic Peace, Major Episodes of Political Violence, (War List)
Uppsala Conflict Data Program
Penn World Tables

7. Results-no heterogeneity

8. Results-with unobserved heterogeneity Response-Based Unit Segmentation (REBUS)

9. Results Korea Australia Netherlands Spain Sweden Turkey Canada France
Italy

10. Results
Netherland UK US
Canada
France Germany
Japan

11. Results
Mexico
Turkey
Brazil
Chile
Argentina

12. Results
China
India
Indonesia

13. Results
1) Milex has larger negative effect on profits when overall profit rates are higher.
2) Milex has positive effect on profits when Milex is smaller.
3) Higher Milex increases income inequality in countries with very large or very small military expenditures.
4) When inequality is low, higher Milex leads to both lower income inequality and profits.
5) When inequality is high, higher Milex leads to both higher income inequality and profits.

14. THANK YOU!