1. Dual concepts of Yin-Yang, Animal Spirits, and network
trajectory phases of innovation in capturing the selected
environments of macroeconomics both in developing and
developed countries
Vignes Gopal Krishna
Department of Economics
Faculty of Economics and Administration
University of Malaya
50603 Kuala Lumpur
Email address : vignesgopal@yahoo.com

2. Outline
a) Introduction
b) Theoretical Guide
c) Methodology and Data
d) Results and Findings
e) Conclusion
f) References

3. Introduction
• Transitional thoughts from mono to multi dimension.
• Contradictory power between traditional and
assimilated realities.
• Current world speaks out more on the partial
equilibrium than full equilibrium
• Mono mode versus combined mode (Pragmatic
Approach)

4. Theoretical Guide
• Duo states versus Multi-states of Animal
Spirits
* Flexibility versus Rigidity of thoughts
* “Partial win” versus “Full win”
* Integration versus Dis-integration
* Real complexity & Evolutionary economics
* Passive versus active mode

5. Methodology and Data
• Specification of selected variables
a) Adolescents fertility rate(AFR),
b) infant mortality rate (IMR),
c) Total fertility rate (TFR),
d) Annual growth rate (AGR),
e) Real gross domestic product (RG),
f) Rural population (Rural population),
g) Cereal yield (CY),
h) CO emissions per capita (COPP),

6. • i) inflation rate (IR),
• J) Fossil Fuel energy consumption (%)(FFEC),
• K) Labour force participation rate (LFPR)
• l) Female labour force participation rate
(FLFPR)
• m)Male labour force participation rate (MLFPR

7. • 126 countries (2010 & 2011) – World
Development Indicators
• Classification of countries based on the four
stages of development – Global
Competitiveness Report 2012-2013
• Selection of variables – Global Risk Report

8. Countries FDC
Albania 0
Armenia 0
Bangladesh 1
Benin 1
Bosnia and Herzegovina 0
Bulgaria 0
Burkina Faso 1
Burundi 1
Cambodia 1
Cameroon 1
Cape Verde 0
Chad 1
China 0
Colombia 1
Costa Rica 0
Cote d'Ivoire 0
Dominican Republic 0
Ecuador 0
El Salvador 0
Ethiopia 1
Gambia, The 1
Georgia 0
Ghana 1
Kenya 1
Kyrgyz Republic 1
Lesotho 1
Liberia 1
Macedonia, FYR 0
Madagascar 1
Malawi 1
Malaysia 1
Mali 1
Mauritania 0
Mauritius 1
Moldova 0
Montenegro 0
Morocco 1
Mozambique 0
Namibia 1
Nepal 1
Nicaragua 1
Nigeria 1
Pakistan 0
Panama 0
Paraguay 0
Peru 0
Romania 1
Rwanda 1
Senegal 0
Serbia 1

9. Sierra Leone 0
South Africa 0
Suriname 0
Swaziland 1
Tajikistan 1
Tanzania 0
Thailand 0
Timor-Leste 1
Uganda 0
Ukraine 1
Vietnam 1
Yemen, Rep. 1
Zambia 1
Zimbabwe 1

10. Argentina 1
Australia 0
Austria 0
Bahrain 1
Barbados 1
Belgium 0
Brazil 1
Canada 0
Chile 1
Croatia 1
Cyprus 0
Czech Republic 0
Denmark 0
Estonia 1
Finland 0
France 0
Germany 0
Greece 0
Hong Kong SAR,
China 0
Hungary 1
Iceland 0
Ireland 0
Israel 0
Italy 0
Japan 0
Kazakhstan 1
Korea, Rep. 0
Latvia 1
Lebanon 1
Lithuania 1
Luxembourg 0
Malaysia 1
Malta 0
Mexico 1
Netherlands 0
New Zealand 0
Norway 0
Oman 1
Poland 1
Portugal 0
Puerto Rico 0
Russian Federation 1
Seychelles 1
Singapore 0
Slovak Republic 0
Slovenia 0
Spain 0
Sweden 0
Switzerland 0
Trinidad and Tobago 0
Turkey 1
United Arab Emirates 1
United Kingdom 0
United States 0
Uruguay 0

11. Results and Findings

12. Table 2: Levene’s Two-tailed t-test Scores by the types of classifications (Stages of Factor and Efficiency
driven)- FDC = 1, FDC = 0 (Stage of Efficiency driven)
FDC N Mean Standard
Deviation
Standard error T-test
AFR 0 33 61.77 36.62 6.38
1 39 72.33 42.70 6.84 -1.13
IMR 0 33 29.58 26.28 4.58
1 39 47.34 25.07 4.01 -
2.92***
TFR 0 32 2.35 1.72 0.30
1 39 3.51 1.95 0.31 -
2.66***
AGR 0 30 4.50 3.00 0.55
1 39 4.74 4.02 0.64 -0.28
RG 0 30 86186000000000 449021000000000 81979600000000
1 39 30326000000000 116103000000000 18591400000000 0.67
RP 0 33 33605442.59 116922000.00 20353465.61
Note: ***, ** and * refer to statistical significance at 1%, 5% and 10% respectively;
Source: Computed using SPSS 19.0 for Windows package.

13. 1 39 37656166.78 136044000.00 21784487.34 -0.14
CY 0 33 2737.19 1321.65 230.07
1 39 2320.45 1704.37 272.92 1.17
COPP 0 33 2.45 2.43 0.42
1 39 1.12 1.76 0.28 2.62**
IR 0 33 7.01 4.15 0.72
1 39 8.47 6.63 1.06 -1.14
FFEC 0 33 52.46 33.65 5.86
1 39 33.16 34.72 5.56 2.39**
LFPR 0 32 63.73 11.26 1.99
1 39 68.52 11.29 1.81 -1.78*
LFPRF 0 32 51.69 16.02 2.83
1 39 59.89 16.93 2.71 -2.09**
LFPRM 0 32 76.10 10.27 1.81
1 39 61.77 36.62 6.38 -0.60
Note: ***, ** and * refer to statistical significance at 1%, 5% and 10% respectively;
Source: Computed using SPSS 19.0 for Windows package.

14. Table 3: Levene’s Two-tailed t-test Scores by the types of classifications (Stages of transitional and innovation driven)-
TSC = 1, TSC = 0 (Stage of Innovation driven)
TSC N Mean Standard
Deviation
Standard error T-test
AFR 0 35 13.65 12.73 2.15
1 19 28.48 20.50 4.70 -2.87
***
IMR 0 35 4.02 3.93 0.66
1 20 9.40 5.33 1.19 -3.94***
AGR 0 34 1.55 2.47 0.42
1 18 5.05 2.35 0.55 -5.02***
RG 0 34 47971000000000 202229000000000 34682000000000
1 18 11273000000000 25724300000000 6063270000000 1.04
RP 0 35 5378813.38 10160850.19 1717497.15
1 20 7950872.27 11429124.94 2555630.03 -0.84
CY 0 35 4617.45 2359.76 398.87
1 20 3839.64 3948.57 882.93 0.80
COPP 0 35 9.26 6.17 1.04
1 20 8.21 5.91 1.32 0.62*
Note: ***, ** and * refer to statistical significance at 1%, 5% and 10% respectively;
Source: Computed using SPSS 19.0 for Windows package.

15. IR 0 35 3.15 1.57 0.27
1 20 4.49 2.89 0.65 -1.92
FFEC 0 35 73.78 23.25 3.93
1 19 81.68 23.65 5.43 -1.18
LFPR 0 35 60.87 5.90 1.00
1 19 61.09 8.43 1.94 -0.10
LFPRF 0 35 53.38 7.41 1.25
1 19 46.98 11.90 2.73 2.13**
LFPRM 0 35 68.75 5.26 0.89
1 19 73.29 8.89 2.04 -2.04*
Note: ***, ** and * refer to statistical significance at 1%, 5% and 10% respectively;
Source: Computed using SPSS 19.0 for Windows package.

16. CONTINUOUS FLOW OF NETWORK TRAJECTORY PHASES OF
INNOVATION (CFNTPI)
Origination and
development
Creative Accumulation
(Mark 2)
Information power
Participating Institutions
Number of actors
Behavioural economics
Timing/Duration
Diffusion
Creative Destruction
(Mark 1)
Retention
Adaptation
Adoption
Information power
Participating Institutions
Number of actors
Sources : Author, Schumpeter (1934), Akerlof and Shiller (2009), Dopfer et al(2004), and Dopfer (2012).

17. Conclusion
• Stages of pre-diffusion and post-diffusion that have captured the power of
asymmetric information, participating institutions and the number of actors are
crucial in maintaining the increasing pace of sustainability from the modes of
partial and full capacity through the timing and behavioural aspects of economics
• Contradictory power and the power of relation will determine the pace of patching
up and catching up.
• Combined version of the analytical approach is an important tool to capture the
overall complexity of economics.
• The discussions on the issues of interest will control the contradictory power in the
dual mixture on the patterns of positive and evolutionary.

18. References
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• Dopfer, K. (2012).The origins of meso economics Schumpeter's legacy and
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