Cross-Country Comparisons of Wealth

This continues a sequence of posts on how objective looking statistics conceal hidden values, because a positivist approach prohibits open expression and discussion of value judgments. Previous posts in the sequence are: Lies, Damned Lies, and Statistics, Subjectivity Concealed in Index Numbers, and The Values of a Market Society.

Countries compete with each other on the GDP numbers, without any awareness of the values which are embodied in such competitions. Such comparisons are fraught with many difficulties. We illustrate the difficulties which arise when we try to compare GDP across nations. To being with, let us examine the GDP data measured in Local Currency Units (LCU) for the countries India, Pakistan, Malaysia, Bangladesh, China and Irland from the World Development Indicator (WDI) data set of the World Bank[1] which is presented in Table 1. Firstly, look at the column for the year 1970.  The largest GDP is the one for Malaysia which is 13.10 trillion MYR. On the other hand, Irland has the smallest GDP which is 2.26 billion IEP. On this basis, can one say that in 1970 Malaysia had the largest wealth and Irland had the smallest wealth? Well obviously not, because the numbers are not comparable since they are measured in LCU. The currency units are not comparable across countries. We must learn how to translate one local currency unit into another, in order to be able to compare countries according to GDP .

Country LCU 1970 1980 1990 2000 2010
India Trillion INR 0.48 1.50 5.86 21.70 78.00
Pakistan Trillion PKR 0.05 0.24 0.86 3.83 14.80
Malaysia Trillion MYR 13.10 54.30 119.00 356.00 795.00
Bangladesh Trillion BNT 0.04 0.28 1.00 2.37 6.94
China Trillian CNY 0.23 0.46 1.87 9.92 40.20
Irland Billion IEP 2.26 13.00 36.70 106.00 156.00

Data is take from the World Bank WDI data set.

At first glance, this does not seem like a difficult problem. Why not use the exchange rate between the two currencies? Deeper thinking about this reveals great difficulties. First, the exchange rate is determined by international trade, exports, imports, balance of payments, and Central Bank policies. For these reasons, it can fluctuate substantially. These fluctuations do not relate to the domestic wealth of the countries. For example, going from 2018 to 2019, the dollar appreciated strongly against the rupee going from PKR 100/USD to PKR 150/USD. Measured in dollar terms, the GNP of Pakistan declined by a rather large amount. However, while this change made imports expensive, it boosted exports, and strengthened import substituting industries in the domestic economy. It makes no sense to consider this change as a reduction in the domestic wealth of Pakistan, because resources within Pakistan were not affected by the change in the exchange rates. Yet, unless we standardize the wealth by using common units of measurement, by converting to dollars, how can we compare the wealth of Pakistan with the wealth of any other country?

To compare wealth across countries, we cannot use the LCU – local currency units – because these are arbitrary and unrelated to each other. Yet, any common unit of measurement we use introduces arbitrary subjective biases into the picture, while giving an appearance of objectivity. Different types of benchmarks can be used to convert an LCU into a common unit for cross-country comparisons. However, we can use this arbitrariness to get any desired conclusions, since there are no objective methods to make such comparisons. To illustrate this, we consider a graph of the Chinese GDP from xxxx to xxxx based on WDI data. The top curve in Figure 1 is Chinese GDP in trillions of Yuan. The other curves are conversions to Dollars, gold and Indian Rupees. As can be seen from the Figure 1, each curve shows a different pattern of growth in Chinese GDP.



Which of these four curves represent the objective “true” picture of the growth of the Chinese economy? None of the numbers (not even the LCU picture, as we will show later) is objective truth. In fact, objective truth does not exist in this situation, and the subjective choices we make create the facts via manufactured numbers. If the subjectivity and arbitrariness is openly acknowledged, these numbers may be of some use for different purposes. The real-world context and goals must be specified and the statistical analysis must be adapted to suit the real world purpose. Again this shows the impossibility of separating the statistical analysis from the real-world context. The appearance of objectivity created by numbers allows experts to deceive the public. Someone who wants to portray the growth of China in a bad light could use the Dollar based curve, which shows the least growth. Someone who uses gold valuation of Yen could argue that the GDP of China has gone down in terms of its gold value in the recent past. Those who are not aware of the arbitrary choices made in creating such comparison could easily be decieved by this modern rhetoric based on apparently objective numbers.

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