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立 政 治 大 學
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立 政 治 大 學
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Chapter 3
Panel Data Analysis (I) : Foreign Aid
Reflecting on our understanding of China and South Korea’s foreign aid systems described in the above chapters, we are going to examine our “question” with regards to the relationships between the two countries’ foreign aid policies and other economic factors possibly affecting them.
3.1 Data sets
Diagram 3 summarizes how we collected and organized the data sets relating to this research. Details are explained later on.
Diagram 3: Summary of data collection sources
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According to the database of the World Bank, other governmental sources, there are 53 countries which have economic indicators including population, GDP, GDP per capita, trade volume, energy production etc. However, data of some African countries have been missing due to poor governance or other unknown reasons. Given the limitations of data availability, we have to narrow down the scope of the countries to the 41 countries86 which provide consistent and reliable data sets. Detailed data of 41 African countries are shown in Appendix 1.
3.1.2 The donor countries’ foreign aid
Under the assumption that the amount of foreign aid of these two countries has reflected their foreign aid policies, we have collected the two countries’ aid volume.
To obtain the amount of Korean foreign aid, we make use of database of OECD-DAC.87 The database of OECD-DAC has efficiently accumulated aid figures of membership countries including South Korea in time series.
In the case of Chinese foreign aid, we rely on some literature such as the works of Garner (2007)88 and Davies (2008)89 which have been collected through research on
86 In alphabetical order, the 41 countries are Algeria, Angola, Botswana, Burundi, Cameroon, Cape Verde, Central Africa Rep., Congo DR, Congo Rep.,Cote d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Senegal, Sierra Leone, South Africa, Sudan, Tanzania, Togo, Tuinisia, Uganda, and Zambia.
87 Sourece: http://stats.oecd.org/index.aspx (accessed on Jan 7, 2011)
88 Garner (2007), op cit.
89 Davies (2008), op cit., 66-68.
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media reports revealing Chinese foreign aid statistics as mentioned in Chapter 1. Even though some official statistics labeled as Foreign Economic Cooperation (对外经济 合作) can be observed, according to definitions of the figures90, these statistics cover very broad economic activities including overseas projects funded by foreign countries as well as foreign aid.91 In light of this, we start analyzing Chinese aid based on the literature sources mentioned above.
3.1.3 Economic factors affecting the aid
Concerning economic factors affecting the volume of foreign aid, we have selected GDP, GDP per capita, population, trade volume between the donor and the recipient country, FDI from the donor country, and energy production. We now assume that population implies size of the countries which may be linked to political influences in the continent, while GDP of recipient countries corresponds to their economic size.
GDP per capita is an indicator to show the income level of the African countries.
Trade volume between aid partners and FDI from the donor countries reflects economic closeness between the countries. Production of recipient countries’ energy resources shows the importance from the perspective of energy security from the donor countries.
90 中国贸易外经统计年鉴 2008，国家统计局贸易外经统计司 编，中国统计出版社，801.
According to this yearbook, These activities include (1) overseas civil engineering construction projects by foreign investors (2) overseas projects financed by the Chinese government through its foreign aid programs (3) construction projects of Chinese diplomatic missions, trade offices and other institutions stationed abroad, and so on.
91 Chinese Foreign Economic Cooperation by recipient country is shown in the fourth column of Appendix 1. Even though these figures do not exactly reflect the exact foreign aid size, they are actually the only detailed official figures that could be obtained from the Chinese authorities. So, for comparison purposes, we are going to handle its statistical output in Chapter 4 separately.
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Regarding data sources, we make use of World Bank’s database to obtain data sets of population, GDP, and GDP per capita. The bank owns a wide variety of consistent time series economic indicators including these variables. Here, GDP of the African countries is calculated at the current market prices92 in million US dollars, while GDP per capita comes from the GDP divided by population of the recipient country.
FDI from China and South Korea to African countries and trade volume between the donor and its partner are gathered from the statistical yearbook of the donor countries.93 With regards to supply of core natural resources, we obtain these data sets from the database of the Energy Information Agency (EIA) as they provide relatively reliable and consistent time series data. The metrics we utilize in our study include total primary energy production comprised of petroleum (crude oil and natural gas plant liquids), dry natural gas, and coal, and the net generation of nuclear, hydroelectric, and non-hydroelectric renewable electricity.94
Based on the data collection methods explained above, we compile the complete data set. A summary of our statistical table is as shown in Table 5. The average amount of Chinese aid to a given recipient country is 107.49 million USD with a maximum
92 The criteria of current market prices is useful as long as consumer prices do not fluctuate drastically.
According to EIU database, consumer prices of sub-Saharan Africa from 2003 to 2006 were 8.4%, 4.9%, 7.7%, 5.1% respectively. Since 2003, the consumer prices have been relatively stablized. For example, the consumer prices of year 2001 was 40.5% and that of 2002 was -13.6%. Source:
http://secure.alacra.com/cgi-bin/alacraswitchISAPI.dll (accessed on June 1, 2011)
93 Chinese data come from China‘s Commercial Yearbook（中国商务年鉴）and China Statistical Yearbook (中国统计年鉴) (e.g. http://www.stats.gov.cn:82/tjsj/ndsj/2008/indexch.htm)，while Korean statistics from Overseas Direct Investment Yearbook and the website of Korean statistical information service ( http://www.kosis.kr/).
94 Source: http://www.eia.gov/cfapps/ipdbproject/docs/IPMNotes.html#t1 (accessed on May 27, 2011)
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value of 4,200 million USD, while the corresponding figures of Chinese Foreign Economic Cooperation 95 are 282.92 million USD and 9,614 million USD respectively. Korean aid averages out to 1.23 million USD while its maximum amount to an individual African country is 35.02 million USD. Other relevant indicators such as population, GDP, GDP per capita, bilateral trade, FDI inflow, and total energy production are shown below.
Table 5: Summary of Statistics for 41 African countries from 2003 to 2006
Item
Average 107.49 282.92 1.23 20,241,092 21,329,840,504 1,628 799,021 268,671 7,757 2,318 0.79512 Standard Deviation 488.03 1,049.94 4.68 26,949,923.56 41,219,688,154 2,337 1,660,539.86 562,799.48 20,284.13 11,458.04 1.82166 Maximum 4,200 9,614 35.02 144,719,953 257,729,745,476 15,355 11,827,481 3,260,641 146,700 123,297 7.74823 Minimum 0.00 0.00 0.00 462,440 235,922,971 86 2,596 12 -8,510 0 0.00000