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Chapter 7. Scope and Limit of Research with Data Analysis
Summarizing Data of Latin America
China’s rapid economic growth and its millions of people being removed from poverty were quite impressive. It had surpassed Japan to become the world’s second largest economy several years after it joined the World Trade Organization (WTO). In Latin America, China has also broken many records economically. For instance, China has surpassed the United States as a top destination for exports of South American countries (especially Argentina, Brazil, Chile, and Peru). [11] Furthermore, Chinese policy banks like China Eximbank and China Development Bank had become the largest public lenders to Latin American governments. China had as well launched bilateral free trade agreements (FTAs) with Chile (2006), Peru (2010), and Costa Rica (2011). [12] Being WTO-plus, these three countries defied that China’s true intention was something against international norms.
The escalation of trade and investment between China and Latin America had generally started form 2002. (See Figure 1) On the other hand, the magnitude and nature of China’s growing trade and investment ties differed considerably across countries and sub-regions within Latin America. Due to China’s huge demand for copper, iron ore, oil, and soybeans, all of which were abundant to varying degrees in the South American countries, prices of these commodities reached historical highs after 2003. (see Table 1) As a result, all these countries had benefited from trade and solid growth for more than a decade and all have built up sizeable foreign exchange reserves.
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Figure 1. Latin American and Caribbean Trade with China, as a share of LAC GDP
Source: China-Latin America Economic Bulletin 2019
Chart 4. Commodity Price Data for Selected Products, 2000-2019 (annual prices in US$)
Year
Crude oil,
average Fish meal Soybeans
Soybean oil Beef
Iron ore,
cfr spot Copper ($/bbl) ($/mt) ($/mt) ($/mt) ($/kg) ($/dmtu) ($/mt) 2000 28.23 407.88 211.83 338.14 1.93 28.79 1813.47
2001 24.35 465.32 195.83 353.24 2.11 30.03 1578.29
2002 24.93 638.83 212.67 461.71 2.11 29.31 1559.48
2003 28.90 640.34 264.00 558.59 2.13 31.95 1779.14
2004 37.73 648.58 306.50 618.23 2.67 37.90 2865.88
2005 53.39 676.59 274.69 544.59 2.73 65.00 3678.88
2006 64.29 755.35 268.65 599.34 2.65 69.33 6722.13
2007 71.12 1166.49 383.10 886.06 2.70 122.99 7118.23
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2008 96.99 1203.53 521.87 1260.81 3.24 155.99 6955.88
2009 61.76 1191.10 423.62 853.07 2.73 79.98 5149.74
2010 79.04 1138.96 447.10 1000.86 3.42 145.86 7534.78
2011 104.01 1442.06 537.52 1297.66 4.08 167.75 8828.19
2012 105.01 1527.77 595.51 1225.60 4.21 128.50 7962.35
2013 104.08 1750.82 551.39 1055.39 4.13 135.36 7332.10
2014 96.24 1680.65 484.86 905.97 5.05 96.95 6863.40
2015 50.75 1554.19 392.12 755.63 4.56 55.85 5510.46
2016 42.81 1490.64 405.45 814.99 4.06 58.42 4867.90
2017 52.81 1366.97 393.38 850.40 4.39 71.76 6169.94
2018 68.35 1525.17 394.30 788.32 4.20 69.75 6529.80
2019 61.41 1448.35 368.35 764.76 4.76 93.85 6010.15
Source: World Bank Commodity Market (Pink Sheet) http://www.worldbank.org/en/research/commodity-markets
On the contrary, Mexico and Central America didn’t benefit from the process so much. Lack of the commodities that China had voraciously bought up from the South American countries, they also had to defend themselves from the flood of Chinese manufactured imports with the exception of Costa Rica. It aroused the reactions and attitudes akin to those of the 1950s, when most of the region embraced protectionism.
Why do we always argue about tariffs and protectionism? Just as Joseph Stiglitz stated in his work People, Power, and Profits, trade agreements do matter, but more for the pattern of trade than for the deficit of trade. [13] For example, if a country, say, Mexico imposed a 25 percent tariff on China, it would import less products from China and more from Vietnam. Since comparable Vietnamese products were more expensive than those made in China (if they were not, the Mexicans would already
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have been importing products from Vietnam), the cost of products in Mexico would increase. The standard of living in Mexico would, in turn, decrease. In other words, the world had created efficient global supply chains, it was difficult and not
economically smart to shift away from it. Being counteraction of globalization, deglobalization was to blame by some, but there were also others being pessimistic about globalization. Advocates of globalization emphasized how exports create jobs, but they failed to mention the number of jobs destroyed by imports. If trade was roughly balanced, and if imports were more labor-intensive, then overall, trade destroyed jobs, resulting in unemployment and inequality.
In the cases of China-Latin America trade, there were two biggest concerns: unequal exchange and “resource curse”. Firstly, the debates about unequal exchange focused on the chronic price swings and negative terms of trade for commodity exporters in Latin America during the early post-World War II period and became a pillar of the dependency school’s emphasis on the international system as the perpetuator of underdevelopment. The earlier experience with this pattern of trade inspired policies of the well-known import-substitution industrialization. However, the good news was that for all but Mexico the terms of trade during the China boom (2003-2013) were highly favorable. The downside of this story is that, although forward linkages in terms of manufactured exports had clearly improved in Latin America, backward linkages to the domestic market were still too weak. For the relatively less successful policies for promoting science, technological adaptation, advanced education, and research, there were also intermediate goods (e.g. cell phones) imported from China that Latin American producers were not competitive enough to produce on their own.
That is to say, Latin American countries were perhaps more pressed than ever before to climb the value-added production ladder and to articulate a longer-term vision for a growth model based on efficiency.
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In addition, the “resource curse”, or “Dutch disease” arguments were also in place.
Compared to the U.S., the interest rates in Latin American countries have been much higher since 2000. It caused massive capital inflows to these countries combined with the commodity price boom, the accumulation of unprecedented levels of foreign exchange reserves. One consequence was the considerable overvaluation of the Latin American currencies (until the wave of depreciations triggered by the abrupt
devaluation of the Chinese yuan in 2015). However, the Global Financial Crisis revealed the substantial macroeconomic, financial sector, and trade reforms had been undertaken by Latin American countries over the past two decades. The example of Brazil showed that, although Brazil is still a formidable industrial exporter, Brazilian manufacturing had taken an extra hit from the resource curse during the 2000s. The more powerful industrial groups in Sao Paulo have blamed this trend on Chinese manufactured exports to Brazil, and hence the Brazilian government’s move to apply protectionist measures against China.
To sum up the aforementioned assumptions and evidences, I visualized the selected data of Gini coefficient (2017, World Bank) for measuring income inequality and data of China’s outward FDI to Latin American countries (FDI stock, 2012, Yellow Book of Latin America and the Caribbean by Social Sciences Academic Press, China).
Because I assumed the capital flows were more important to make the income inequality changed than the goods of the trade. I got the scatter plot below:
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Figure 2. Correlation between Income Inequality and China’s Outward FDI to Latin America
I also used the data of the income inequality in several main trade partners with China in Latin America during the China Boom (2003-2013).
Figure 3. Changes of Income Inequality During the China Boom in Latin America
According to these scatter plots, there is an insignificant positive correlation between the income inequality and the Chinese FDI stock in these Latin American countries.
On the other hand, the income inequality had decreased in a much larger degree. In other words, the trade between China and Latin American countries did help Latin American countries accumulate the capital, but the improved income inequality
0
0 200 400 600 800 1000 1200 1400 1600
Gini Coefficient (%)
China's Outward FDI Flows to Latin American Countries (US$ million)
Correaltion between Income Inequality and China's Outward FDI to Latin America
40 45 50 55 60
2002 2004 2006 2008 2010 2012 2014 2016
Gini Coefficient (%)
Year
Changes of Income Inequality During the
China Boom in Latin America
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seemed to have little to do with these economic ties.
Perhaps we have to look into the main types of products of the China-Latin America trade in 2015 as well:
Chart 5. Main Products of China-Latin American Trade
LA Exports to China LA Imports from China
1. Soybeans and other oilseeds 19.2% 1. Telecommunications equipment 9.7%
2. Iron ore and concentrates 16.8% 2. Data processing machine 3.8%
3. Crude Petroleum 11.8% 3. Optical instruments, apparatus 3.3%
4. Copper 11.4% 4. Ships, boats, floating structures 3.3%
5. Copper ores, concentrates 10% 5. Other electrical equipment 2.3%
Source: UN Comtrade
According to the percentage data, so far there is still certain pattern in the China-Latin America trade because a large part of exports to China still depends on the raw
material and major agricultural products which were controlled by the owners of the mining and the landlords in Latin America. The imported products are on the other hand the ones that the Latin American producers not competitive enough with Chinese counterparts. Those are the ones with higher-values. Thus, this kind of trade would not improve the development of industries and unequal distribution of wealth in the region.
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