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ABSTRACT
This paper quantifies drain from the global South through unequal exchange since 1960. According to our primary method, which relies on exchange-rate differentials, we find that in the most recent year of data the global North (‘advanced economies’) appropriated from the South commodities worth $2.2 trillion in Northern prices — enough to end extreme poverty 15 times over. Over the whole period, drain from the South totalled $62 trillion (constant 2011 dollars), or $152 trillion when accounting for lost growth. Appropriation through unequal exchange represents up to 7% of Northern GDP and 9% of Southern GDP. We also test several alternative methods, for comparison: we quantify unequal exchange in terms of wage differentials instead of exchange-rate differentials, and report drain in global average prices as well as Northern prices. Regardless of the method, we find that the intensity of exploitation and the scale of unequal exchange increased significantly during the structural adjustment period of the 1980s and 1990s. This study affirms that drain from the South remains a significant feature of the world economy in the post-colonial era; rich countries continue to rely on imperial forms of appropriation to sustain their high levels of income and consumption.
Disclosure Statement
No potential conflict of interest was reported by the author(s).
Notes
1 We calculated this figure using data from Köhler Citation2003, p. 384.
2 The ratio of GDP, PPP to GDP, MER (i.e. ERDI) is equivalent to the inverse of the price level (Köhler and Tausch Citation2002, p. 96 - 97). As such, we calculate each country’s ERDI by finding the inverse of the price level of their GDPe (denoted as PL_DA in PWT9.1). Since PWT’s GDP, PPP data is rendered in 2011 prices, ERD indices calculated as the inverse of PL_DA indicate how much higher a country’s prices would be if they were at parity with the US in 2011. This does not mean that we estimate the Northern value of Southern exports by inflating the export figures to 2011 prices. Since we multiply the market price of exports by the ratio of the peripheral ERDI to the core ERDI, the Northern value of exports is always measured at the Northern price level in the relevant year.
3 We calculated the poverty gap in 2017 with data from the World Bank (Citation2021).
4 To exclude China from the price distortion factor we sum the Northern value of all exports from peripheral countries other than China, and then divide that figure by the market price of the same exports.
5 PWT9.1 does not contain data on GDP, MER (constant 2011 dollars). We therefore calculated GDP, MER by dividing each country’s GDP in constant 2011 local currency units (the q_gdp variable), by their 2011 exchange rate (XR_2). The q_gdp and XR_2 variables are in the ‘National Accounts data’ file on the PWT website. For GDP, PPP we used RGDPe.
6 One limitation of these time series is that the availability of data changes over time. For instance, with the exception of 1961, we do not have export data for China until 1978. Since these and other export flows are left out of our calculations, we may underestimate unequal exchange in the early years. Nevertheless, the trends we have discussed here can be observed for countries that have data for the entire series.
7 and include per capita figures calculated with population data from the World Bank (Citation2020). When calculating total population, we excluded countries without unequal exchange data.
8 For instance, we assume that if the South’s 1961 losses ($29.7 billion) were invested in Southern development in 1962, they would have grown at the South’s 1962 growth rate (6%), yielding a total of $31 billion at year’s end. In 1963, the South would then be able to re-invest this $31 billion plus the scale of value transfer in 1962 ($25 billion), with this entire sum growing by the 1963 growth rate (7%). Our calculations here include years of negative returns. For instance, in 1961 the South’s growth rate was −0.5%. As such, we assume that, if the South had invested their 1960 losses ($23 billion) in 1961, they would have lost $115 million. These growth rates are calculated with the RGDPe variable from PWT9.1.
9 Another reason records higher estimates in the 1960s and early-1970s is that we calculated as the sum of all country-level peripheral losses. By contrast, we calculated by multiplying aggregate exports by d1. This means only includes exports from countries with corresponding ERDI data, whereas includes all available export data. This is not, however, the primary cause of the discrepancy.
10 We filtered the ILO data by economic activity: ‘Aggregate Total,’ by sex: ‘Total,’ and by currency: ‘US dollars.’ This ensures that, as much as possible, we are comparing average wages across all economic activities and both sexes, in US dollars.
11 Ecuador’s ERDI is calculated as the ratio of the US price level (PL_DA) to Ecuador’s price level (PL_DA).
Additional information
Notes on contributors
Jason Hickel
Jason Hickel is an economic anthropologist and a Fellow of the Royal Society of Arts. He writes on global inequality, international development and ecological economics.
Dylan Sullivan
Dylan Sullivan is a graduate student in the Department of Political Economy at the University of Sydney. His work focuses on global inequality, colonial history, environmental justice, and the economics of socialist planning.
Huzaifa Zoomkawala
Huzaifa Zoomkawala is an independent scholar, data analyst and poet based in Karachi. His work focuses on feminist and anti-colonial approaches to contemporary social issues.