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Are There Any Optimal Strategies for Nations?

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An Economic Inquiry into the Nonlinear Behaviors of Nations

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Abstract

In previous chapters, we have found that environmental challenges and external threats—as long as they are predictable or manageable—may become the driving forces contributing—directly or indirectly—to the eventual success of nations. On the other hand, however, various historical events have shown that they could also result in disastrous consequences in both democratic and authoritative states. In this chapter, using a highly simplified model and data from various nations, we observe that while domestic instability always tends to retard long-run economic growth, the influences of external threats on macroeconomic performance are quite complicated, sometimes showing a nonlinear pattern. Specifically, the estimated results show that external threats tend to encourage long-run economic growth in politically stable and economically open nations and to retard long-run economic growth in politically unstable and economically closed nations.

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Notes

  1. 1.

    In Chinese, “Han” is a different character from that used for the like-sounding “Han” (or ethnic Chinese) in Chinese. However, it is written in the same way as the character “Korea” (Han), even though the Republic of Korea (ROK) has nothing to do with the state of Han.

  2. 2.

    Cited from Sima et al. (2007, 102). The figures within brackets are added by author.

  3. 3.

    Cited from http://www.chu.cam.ac.uk/archives/collections/churchill_papers/biography/ (accessed 2015-12-28).

  4. 4.

    The former Union of Soviet Socialist Republics (USSR) once posted an estimated number of 700,000 soldiers on its side of the China–USSR boundary, at a time when 1 million soldiers from the People’s Liberation Army in China stood on the other side (Guo 2012, 91).

  5. 5.

    Cited from ADST (2013).

  6. 6.

    The “Pannemaker” in the lower right refers to Adolphe François Pannemaker, one of Doré’s assistants in turning his art into a full-fledged engraving, and a reasonably notable engraver in his own right.

  7. 7.

    According to the International Military Tribunal for the Far East (IMTFE 1948, 1012, 1015) and Wakabayashi (2008, 362), during this massacre, Japanese soldiers killed between 40,000 and 300,000 Chinese people and raped at least 20,000 women and girls.

  8. 8.

    See Vogel (2011) for an excellent biographical description of Deng Xiaoping during the post-Mao era.

  9. 9.

    See Zhai (2000, 54–5, 135). Note that the Chinese military claims to have caused 38 % of American air losses in the war. China claimed that its military and economic aid to North Vietnam totaled US$20 billion (c. US $143 billion adjusted for inflation in 2015) during the Vietnam War (Womack 2006, 167, 176).

  10. 10.

    Cited from French (March 1, 2005).

  11. 11.

    Cited from Fogel (1994, 385).

  12. 12.

    The data on the number of cases of boundary and territorial disputes, and on military expenditure as a percentage of GDP are from Guo (2007) and the World Bank Database (available at http://data.worldbank.org/), respectively.

  13. 13.

    Based on the data presented in the Appendix.

  14. 14.

    The data on the following variables (except those that are stated otherwise) are for 2010 and from the World Bank Database (available at http://data.worldbank.org/).

  15. 15.

    Selected literature relating to theoretical and empirical analyses of the determinants of short-run economic growth would include Barro (1991, 1997, 2003), Moral-Benito (2007), and Ciccone and Jarociński (2008).

  16. 16.

    Due to space limitations, we have not reported the details about the VIF test here.

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Author information

Authors and Affiliations

  1. Peking University, Beijing, China

    Rongxing Guo

Authors
  1. Rongxing Guo
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Appendix: Instability and Threat Scores, by Country

Appendix: Instability and Threat Scores, by Country

Country

Domestic instability (DI)

DI threshold (DI*)a

External threat (ET)

Afghanistan

7.8

1.7

1.1

Albania

6.2

5.4

1.8

Algeria

6.6

6.4

2.5

Angola

7.6

10.3

2.9

Armenia

5.8

3.5

2.9

Australia

3.6

3.2

1.6

Austria

3.6

8.5

1.3

Azerbaijan

5.2

9.1

3.7

Bahrain

5.5

11.6

2.3

Bangladesh

7.5

2.7

1.5

Belarus

4.8

8.9

1.6

Belgium

4.0

12.7

1.1

Belize

6.2

9.7

1.5

Benin

5.9

4.0

2.3

Bhutan

5.3

7.1

0.7

Bolivia

7.7

6.9

1.8

Bosnia and Herzegovina

7.5

5.1

2.0

Botswana

4.7

6.4

2.0

Brazil

5.4

1.8

2.5

Bulgaria

6.0

9.0

1.5

Burkina Faso

6.9

3.2

1.2

Burundi

6.9

1.5

3.5

Cambodia

8.0

9.0

1.8

Cameroon

6.9

2.9

3.0

Canada

2.8

4.9

1.9

Central African Republic

7.8

2.0

1.5

Chad

8.5

6.1

5.0

Chile

5.1

6.4

2.5

China

4.8

4.4

4.9

Colombia

7.0

2.7

3.8

Congo, Dem. Rep.

8.2

7.3

2.6

Congo, Rep.

6.3

14.2

1.5

Costa Rica

3.5

6.4

0.7

Cote d’Ivoire

7.8

8.4

0.9

Croatia

6.1

6.3

2.2

Cuba

4.2

3.8

2.3

Cyprus

4.1

8.0

2.4

Czech Republic

3.7

11.0

1.1

Denmark

2.2

8.3

3.3

Dominican Republic

7.6

3.7

0.4

Ecuador

7.7

4.7

2.2

Egypt, Arab Rep.

5.4

3.6

1.6

El Salvador

5.2

4.3

1.5

Equatorial Guinea

6.1

15.8

1.5

Eritrea

6.7

0.8

1.1

Estonia

6.7

12.5

1.4

Ethiopia

5.1

NA

2.3

Finland

3.2

6.5

1.2

France

5.3

4.3

3.0

Gabon

5.1

9.6

0.9

Gambia, The

6.7

4.0

0.3

Georgia

6.3

5.8

2.7

Germany

3.8

7.1

1.6

Ghana

5.9

4.9

0.6

Greece

6.3

3.7

2.4

Guatemala

6.6

4.3

1.1

Guinea

7.5

4.7

0.7

Guinea-Bissau

7.5

3.3

1.6

Guyana

6.7

8.6

2.1

Haiti

7.8

2.6

0.7

Honduras

6.8

7.6

2.7

Hong Kong SAR, China

4.0

36.6

0.0

Hungary

6.1

13.7

1.4

Iceland

5.3

9.0

0.9

India

4.5

3.7

3.2

Indonesia

6.8

4.1

0.8

Iran, Islamic Rep.

6.2

4.2

4.6

Iraq

7.9

6.6

2.8

Ireland

4.6

17.2

1.2

Israel

5.5

5.8

5.3

Italy

5.0

4.2

1.4

Jamaica

6.0

5.2

0.5

Japan

3.8

2.5

1.8

Jordan

5.4

8.0

3.4

Kazakhstan

4.8

7.4

3.9

Kenya

7.5

3.5

1.8

Korea, Rep.

5.1

8.2

2.7

Kuwait

5.5

11.1

2.6

Kyrgyz Republic

7.1

8.6

3.9

Lao PDR

5.1

5.9

0.5

Latvia

6.7

9.0

1.5

Lebanon

7.0

6.1

3.3

Lesotho

7.0

7.4

1.9

Liberia

7.4

7.3

0.8

Libya

4.3

10.9

1.5

Lithuania

6.1

10.9

3.0

Luxembourg

3.6

29.8

0.3

Macedonia, FYR

6.6

6.6

1.6

Madagascar

7.1

4.2

0.8

Malawi

5.7

4.9

1.4

Malaysia

6.5

14.5

3.8

Mali

7.0

3.6

0.9

Malta

4.7

14.7

0.4

Mauritania

6.9

8.5

0.3

Mauritius

3.5

8.8

1.4

Mexico

6.1

5.0

0.8

Moldova

7.5

6.5

0.6

Mongolia

6.1

7.8

0.5

Morocco

5.6

5.4

2.8

Mozambique

5.7

5.0

0.6

Namibia

5.8

8.0

2.9

Nepal

7.5

1.6

1.8

Netherlands, The

4.0

12.0

2.0

New Zealand

3.6

5.1

0.8

Nicaragua

5.9

6.4

1.5

Niger

7.5

3.7

1.9

Nigeria

7.0

4.2

1.5

Norway

1.2

6.6

1.3

Oman

3.9

9.5

6.1

Pakistan

7.8

2.3

2.4

Panama

7.1

11.8

0.3

Papua New Guinea

6.9

NA

0.3

Paraguay

6.4

9.2

1.5

Peru

7.0

4.4

2.0

Philippines, The

6.8

5.8

3.2

Poland

4.5

6.7

1.0

Portugal

4.8

5.0

1.6

Qatar

4.1

10.4

1.3

Romania

6.4

5.4

1.5

Russian Federation, The

6.5

4.9

7.3

Rwanda

4.9

2.0

2.0

Sao Tome and Principe

4.3

NA

0.3

Saudi Arabia

6.1

8.3

5.8

Senegal

7.5

4.2

0.9

Serbia

6.4

5.5

2.1

Seychelles

4.1

15.6

1.2

Sierra Leone

7.2

2.8

1.0

Singapore

4.7

33.2

2.4

Slovak Republic

5.5

12.8

1.2

Slovenia

3.8

10.7

1.8

South Africa

7.0

4.8

1.5

Spain

5.5

4.3

1.4

Sri Lanka

7.3

3.3

1.6

Sudan

8.0

3.3

1.5

Swaziland

4.7

9.8

2.1

Sweden

3.2

7.7

0.7

Switzerland

3.4

10.7

0.4

Taiwan

4.3

6.7

NA

Tajikistan

7.1

2.6

3.5

Tanzania

5.9

3.1

2.2

Thailand

7.0

11.0

2.1

Timor-Leste

7.3

1.6

2.0

Togo

5.3

6.7

1.9

Trinidad and Tobago

4.7

9.6

0.4

Tunisia

4.6

8.4

0.8

Turkey

6.8

3.5

2.6

Turkmenistan

6.2

13.0

2.8

Uganda

6.5

2.9

3.1

Ukraine

7.6

8.5

2.8

United Arab Emirates, The

4.1

13.1

4.8

United Kingdom, The

4.6

4.8

3.9

United States, The

5.3

2.1

4.8

Uruguay

5.2

4.4

2.0

Uzbekistan

6.3

5.3

2.0

Venezuela, RB

7.3

4.8

2.6

Vietnam

4.3

12.0

4.3

Yemen, Rep.

6.1

NA

3.6

Zambia

7.8

6.2

2.9

Zimbabwe

8.8

6.1

0.6

  1. Notes: aIf a country’s actual DI score is smaller than its threshold, then the ET score implies a positive contribution to the country’s economic prosperity; and if a country’s actual DI score is larger than its threshold, then the ET score implies a negative contribution to its economic prosperity. “NA” denotes that the threshold is not available since the country is not included in the regression.
  2. Sources: (1) The DI scores are from the EIU (2009). (2) The ET scores are calculated by author. (3) The threshold (DI*) scores are calculated by author according to Eq. (5.1) and the World Bank Database

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Guo, R. (2017). Are There Any Optimal Strategies for Nations?. In: An Economic Inquiry into the Nonlinear Behaviors of Nations. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-48772-4_5

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