Dear Editor,
Among other evils, tribal politics has damaged our very psyche in a peculiar way: intellectuals have become know-it-all, pompous, and arrogant. Humility has become an extremely scarce commodity in Guyana. The recent UG Student Society-sponsored “debate” between Elson Low (EL) and Joel Bhagwandin (JB) offers a fine example of what I mean. Both discussants claim victory, but their letters do not offer much in the way of substance. JB’s letter (SN, July 12) contains lots of data and is in need of some clarification, which is the purpose of this essay.
JB’s missive is marked by logical misjumps, logical non sequitur if you will, that strains both logic and comprehension. The essence of his arguments is that the PNC destroyed Guyana’s economy, while the PPP fixed and grew it. The latter is a half-truth: the PPP fully adopted the Economic Recovery Program (ERP) negotiated with the IMF by the Hoyte Government. Just as important, the PPP fully implemented the ERP at record speed, faster than most countries usually do. Were it not for the ERP, debt relief, the generosity of major donors, remittances, the existing output capacity, the “animal spirt” of private enterprise, and the “base effect,” Guyana could not have doubled its real GDP from 1992 to 2014. The “base effect” refers to a low base so that an absolute increase translates into a higher percentage rise compared to a larger base.
From 1992 to 1997, non-oil output grew by an average of 7.3 percent, a performance not repeated ever since. Over the entire 23-year that JB considered (1992-2014), real GDP grew by 3.6 percent and not 4.0 percent. The country’s external debt stock fell from 512.2 percent of GDP to 76.1 percent, and not from 900 percent to 40 percent. The plunge was more the result of the ERP than the efforts of the PPP: it would have happened under the PNC if it had won the 1992 election and implemented the ERP fully and quickly.
JB complained that EL spoke about poverty but referenced “an old report that states Guyana’s poverty level is 43%.” The problem is that JB failed to produce a more updated datapoint. Instead, he waffles incoherently about “Guyana’s labour force participation rate of 49% … Effectively, I sought to illustrate the correlation between the non-participation of half of the working age population in the labour force―to the perceived level of poverty.” Yet he did not say what the correlation coefficient is, which is the single datapoint that conveys an idea to which the two variables – labour-force participation rate and poverty – move in the same direction: “co-move” in the language of statistics.
To justify his “correlation” assertion, JB resorted to the total number of households (HH) in Guyana, about 250,000. The presumed idea is that in each HH “one person is the breadwinner.” So what if one or two persons is/are the breadwinner in an HH – what’s the point? Is it that the poverty rate should be lower than 43 percent? There is something economists call the “working poor,” people whose wages do not allow them to live above the poverty line. Given the low wage rate in both the public and private sectors, the high rate of inflation and the astronomically high prices of imported food items in grocery stores (as much as 2 to 2.5 times higher than the US), it is not unreasonable to conjecture that Guyana’s poverty rate remains high, probably close to 43 percent.
As an aside, correlation is not causation. The Pearson’s correlation coefficient tells whether there is an association between two variables, whether the two variables move in the same direction. That is correlation, and correlation is not causation; the latter is necessary to establish a causal relationship. When economists at the University of Oxford in London were developing advanced time series techniques in the 1960s, they looked at the plot of all manner of variables. They noticed, for example, that rainfall in Africa was associated with – moved in the same direction – marriages in London, which is ridiculous. Does rainfall in Africa cause the number and rates of marriages in London to go up? Absolutely not! This is an example of what came to be known as “spurious correlation,” which refers to a high correlation coefficient between of two variables that is in fact due to a third factor.
Other data (see JB’s eight bullet points) supplied by JB baffles me. He wrote that real GDP rose from US$200M to US$4B. According to World Bank’s data (supplied by the Government of Guyana), Guyana’s real GDP was US$2.04B in 1992 and not US$200M. That’s a huge data high-jump! JB says that net international reserves increased from US$15M to US$652; according to WB data, the figures are US$188.08M and US$667.93M, respectively.
But absolute numbers mean nothing in an economy that grew by 3.6 percent from 1992 to 2014, a surge in food imports as a percent of merchandize imports from 6.9 percent to 14.7 percent, and a rise in population from 739,000 to 744,600, an increase of just 0.8 percent.
From an economic standpoint, absolute numbers do not mean much. The message from an absolute number/variable can only be deciphered if it is related to an appropriate economic datapoint/variable. In this case, the importance of total international reserves is usually gauged by the number of months of imports they can buy. In 1992, Guyana had sufficient reserves to buy 3.3 months of imports, a figure that rose to 3.6 months in 2014, representing a meagre increase of 0.3 months. Such a poor statistic is nothing to cheerlead about. JB threw another number into the mix: the official exchange rate, which was “stable at G$208.5/US$1.” Stability suggests little variation, but the exchange rate moved from G$125/US$1 in 1992 to G$206.5/US$1 in 2014. That is not stability, unless he is referring to the last three years or so.
The rate of inflation, according to JB, fell from 89.7 percent to 1.2 percent. Earlier in his letter, he did not take kindly to his “opponent” questioning the “credibility of the [Bureau of Statistic] report,” which shows a labour force participation rate of 49 percent. Why would he accept an inflation rate of 1.2 percent from 1992 to 2014 as credible? The Consumer Price Index (CPI) is done only for Georgetown, and not the entire country. Further, given the surge of imported food, the extraordinarily large price differential between Guyana and North America, the astronomical increase in the price of food produced locally, and the rise of internal transportation cost, how can inflation be so extraordinarily low? Why does JB not question the credibility of Guyana’s inflation rate? Inflation is one indicator of macro-economic stability – could it be a fiddled number?
Finally, I was not at the debate and the presentations and discussions were probably more comprehensive and substantial than what was captured in the letters, which is why I am not criticizing either debater; my goal is to help readers interpret JB’s data in economic terms. It is crucially important for those who have a big microphone to be wary of the data Guyana produces. At least since the early 1980s, the IMF, WB, IDB, USAID, various UN organizations and donors, and academics, such as Clive Thomas and this writer, have been questioning the credibility of the data and suggested ways to generate timely and quality data.
Unlike other countries, Guyana does not revise national data, which suggests that the country has discovered a way to generate incredibly accurate data. That cannot be true, and it is unacceptable. It is difficult to avoid the conclusion that Guyana’s data is massaged, which is compounded by the tendency of some to distort or misreport the data. Perhaps that’s why some writers do not supply their data sources.
Sincerely,
Ramesh Gampat
