American Economic Data: The problems
This paper investigates the provision and accuracy of official national income accounting data for 37 countries in North and South America.
The main factor determining the quality of national income statistics across the Americas is the capacity and resources devoted to national statistics offices which depends on the resources available to them to follow international best practice.
There is a global standard set by the United Nations for measuring national income, but poorer countries generally report lower quality statistics because of the reduced resources available to national statistical offices to implement best practice and together with the paucity of comprehensive household and business surveys available.
Given the differences in per capita income across North and South America some differences in the quality of economic statistics are inevitable. Argentina produces, arguably, the most unreliable economic data as a result of political interference and in consequence the World Bank omits estimates from its database. Chile, which became an OECD member in 2010 stands out as a producer of the most reliable economic data and can be compared favourably with the USA and many European countries.
In addition to this general problem, the most significant data issues found across the Americas are:
Real growth in the activity of an economy is estimated by comparing GDP at current and at constant prices. Constant price estimates use the price relatives of a particular year, known as a base year or benchmark year, to weight the volume components of production. But since the structure of production and relative prices over time are dynamic the pattern of relative prices and the industries surveyed in the base year become less relevant over time. Even when the economic data produced by national statistical offices are published regularly serious distortions arise from the use of outdated base years. This biases estimates of the relative size of economies and the speed at which they are growing in real terms. This means that the estimates of GDP used in country rankings are likely to be seriously inaccurate with the degree of bias for each country being dependent on the length of time since the last base year was employed/updated by the national statistics office.
The time elapsed between current estimates of GDP and the base year is of crucial importance to the accuracy of national income data. According to Jerven (2013) failures to regularly update a base year in which the structure and relative prices of an economy are monitored can lead to serious bias in the estimation of GDP. He refers to the case of Ghana when estimated GDP was uplifted by 60% overnight as a result of an update in the base year from 1993 to 2006. In 2014, the Nigerian National Bureau of Statistics released new estimates of GDP showing a rise of 59.5% after the economy’s base year was updated from 1990 to 2010. One of the reasons for these large uplifts is that better estimates of some economic activities such as telecommunications, tourism and financial services were made by statisticians while some previously unrecorded activities from the informal sector were included.
Table 1 shows the results of a sample of recent rebasing exercises for 18 American countries. A scatter graph of this data shows that there is a strong positive relationship between the numbers of years since the last rebasing exercise and the size of GDP uplift (See Figure 1).
Table 1: Results of Rebasing in the Americas
Figure 1: The Americas: % GDP Uplift and Years since last Rebasing
Reassessing GDP in the Americas
In this section we report on an exercise to estimate what the size of the Americas GDP might be if most countries updated their base years to 2014. When this exercise was carried out for Africa it was estimated that GDP might be currently underestimated by about 30% . Given the inadequate resources allocated to national income accounting in most African countries a rebasing exercise, often carried out with external technical and financial support, usually does far more than the updating relative price weights. Some sectors of the economy are measured more accurately using better survey methods, while some economic activities are monitored that were not previously monitored such as mobile telephony. This explains the 60% uplift experienced by Ghana.
Some indication of the impact of rebasing in an American country can be estimated by considering the case of Chile where working papers by the Bank of Chile provide a detailed analysis of the four most recent rebasing exercises: 1986, 1996, 2003 and 2008. The impact of frequent rebasing in Chile suggests that most American countries might not expect an uplift of estimated GDP on the scale experienced by Ghana. Nevertheless, some of the poorer countries in the Americas have not rebased for some time so it is expected that more significant uplifts in GDP estimates would result since they lack the statistical probity and efficiency of Chile. This means that there could be a reassessment of the size of economic activities in areas such as financial services, communications and tourism as was the case with the Ghana uplift referred to above.
The methodology we use to estimate what would happen if countries all rebased up to 2014 is crude, but simple and involves applying an estimated constant cumulative annual rate of growth to the years between the last reported base year and 2013. The longer the period between 2014 and the last base year and the higher the assumed cumulative growth rate, the higher the uplift that would be expected from rebasing. Analysing the existing economic data shows that aggregate GDP in the Americas may be underestimated and could be around 2.6% higher.
Two assumptions were necessary to carry this exercise out.
Inconsistent Base Year Data: Unlike African and some Asian countries, information on base years from the World Bank, IMF and UN databases were largely consistent for the Americas. The reported base years from the three international sources are shown by country in Table 2. Given the differences in reported base years, the source(s) generally used to calculate how many years the latest base year was out of date was highlighted in bold.
Table 2: Reported Base Years by Source
Cumulative annual rate: The assumed annual rate that would act as a proxy by replicating over time the effect of the uplift created in one year by rebasing GDP was 1.6% for American countries. This was based on an econometric model using data from the sample of 18 GDP national rebasing exercises shown in Table 1 and Figure 1.
Results: In 2014, the sample of 36 American countries had a combined GDP of US$28.5 trillion measured in PPP international dollars at 2011 relative prices. Applying the assumed uplift estimate produces a revised figure for aggregate GDP of US$29.2 trillion, an average uplift of 5.3%, but this is misleading since it includes Canada, Chile, Colombia, Dominican Republic, Guatemala, Nicaragua and the U.S. (0% uplift) as these countries have adopted chaining which is in effect rebasing every year. This simple methodology produces a wide variation in uplift estimates for the economies that have not rebased for some time from a high of 64.2% in Puerto Rico to 9.6% for Mexico.
The country uplifts and estimated GDP before and after the applied uplift figures are shown in Table 3, showing each country ranked by current GDP and rebased GDP.
Table 3: Rebased* GDP data and % Uplift
These standards are not mandatory and the adoption by a country of a standard such as SNA 1993 does not imply that all of the recommendations are implemented. The near general use of SNA 1993 means that, apart from the individual discrepancies across countries mentioned above, economic statistics across the Americas are broadly comparable in terms of the definitions used and accounting methodologies applied. However, the United Nations Statistical Commission formally adopted SNA 2008 in 2009 and some of the recommendations of the new standard have been implemented by some countries. Significant differences between SNA 1993 and SNA 2008 include the treatment of government accounts, capital expenditure, intellectual property and the measurement of the informal sector and illegal activities, areas which are particularly important in emerging markets. The longer it takes other American countries to adopt this standard the less reliable will be economic comparisons between themselves and the developed world. In recognition of this problem the United Nations Statistical Commission facilitated a workshop in September 2013 in Rio de Janeiro attended by 11 of the countries investigated here in order to identify and remove the political, institutional and resource problems facing American countries in adopting the new standard.
Table 4: Accounting Standards by Country
4.The Shadow Economy Problem
All economies have many unrecorded economic transactions which bias downwards official estimates of GDP, employment and income per head. The SNA 1993 national income accounting standard recognised the importance of the informal economy particularly in developing economies defining it as belonging to the household sector, but there was no explicit methodological recommendation as to how to measure its size. Chile decided to make an attempt to measure the size of the non-observed economy prior to its update of the benchmark year from 2003 to 2008 using recommendations from Eurostat in order to estimate underground activity, producers not obliged to register with the authorities and producers not registered and underreporting. The total value added in the non-observed economy calculated by this limited project was estimated to be between 2.84% and 4.41% of GDP [IMF, (2011)].
The SNA 2008 standard goes a lot further in defining the informal sector and in placing the onus of measurement on national statistical offices adopting the standard to include estimates within the framework of national income accounting. The SNA 2008 standard recommends a number of methods of estimating the informal economy, although at present without a set of full regular surveys researchers rely on the work of Freidrich Schneider a leading expert on the size and importance of shadow or grey economic activity across the world. In his latest estimates for 2007 which covers 27 of the countries investigated in this analysis, Table 2 shows that the relative size of the shadow economies across the Americas ranged from 8.4% of GDP in the US to 63.5% in Bolivia with an average value (mean) of 36.2%. However, the average value is misleading since if the US applied SNA 2008 effectively to adjust GDP up by 8.4% the result in 2013 would have been an additional US$1.4 trillion, while Bolivia estimating its larger percentage shadow economy at 63.5% of GDP would only generate an additional US$41.5 billion.
Table 5: The Shadow Economy % of National Income
5. The Problem of Political Manipulation
One example of political intervention in the production of statistics has been witnessed in Argentina. A feature of recent economic history in the Americas. In 2007, the Argentine administration decided to interfere with the calculation of the official Consumer Price Inflation Index (CPI) estimated by the National Statistics Institute (INDEC) and a few months later, the wholesale price index (WPI) was also modified, as well as the official Household and Employment, Manufacturing Survey. This has had a positive upwards bias on GDP and there have been accumulating gaps between the official estimation of inflation and alternative ones, Cavallo (2012).
Argentine GDP are estimated using volume index indicators and a base year of 1993, not by deflating the value of production or value added at current prices by chaining. The extent to which the political intervention has biased GDP upwards has been recorded by Coremberg (2013) who applied the standard SNA 1993 methodology to the main basic series that constitute GDP in Argentina to produce a reproduced ARKLEMS series from 1993 to 2012 to compare against official GDP. The main result of this procedure was a series that replicates almost exactly the official Argentine GDP growth from 1993 to 2007. After that year, however, an important gap appears. This gap increases over time as is shown in Figure 2.
As most of the Latin American countries and those in the Caribbean use the same, albeit outdated, national accounting methodology SNA1993, ranking countries using GDP estimates is relatively sound, but comparing them with OECD countries such as the US, Canada, Mexico and Chile will cause problems as SNA 2008 is progressively adopted. The information already available on estimates of the size of the shadow economy economies (See Table 5) suggests that significant additional upward revisions might be expected when many South and Central American countries adopt SNA 2008 themselves since the new standard requires greater efforts to be devoted to measuring informal and illicit activities.
Second, the long overdue rebasing of most countries in the Americas means that GDP is underestimated and that the rankings of some countries by GDP size may have to be reassessed. However, the data presented in Table 3 shows much still needs to be done by statistical offices in Latin American and the Caribbean in updating their base years. Accurate and transparent statistics are essential indicators of economic potential and if the poorer economies in the Americas wish to continue to attract rising investment interest, the issue of data quality needs to be urgently addressed.
The lack of reliable recent economic data is being addressed by World Economics which produces monthly surveys (Sales Managers Indexes) of business conditions across Latin America, in Mexico for the US and for the Americas, which includes Canada. Indicators of the speed and direction of economic activity are available for these areas. In addition to a headline figure the Sales Managers Indexes (SMIs) also monitor Business Confidence, Market Growth, Sales Growth, Prices Charged and Staffing Levels in separate diffusion indexes. The SMI are published monthly providing data relating to the current month and are available on the World Economics (www.worldeconomics.com) website.
Cavallo, Alberto (2012). Online vs Official Price Indexes: Measuring Argentina′s Inflation - Journal of Monetary Economics. December 2012
Coremberg, A (2014), Measuring Argentina’s GDP: Myths and Facts, World Economics, (2014). http://www.worldeconomics.com/Papers/Measuring%20Argentinas%20GDP%20Myths%20And%20Facts_01f3d684-522d-4555-859b-399bce100061.paper
Jerven, M. (2013) Poor Numbers: How we are misled by African Development Statistics and what to do about it, Cornell.
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Luxembourg, Alvisse Parc Hotel 12‐13 June.
IMF (2011), Chile: Report on National Accounts Mission, Statistics Department, July.
Schneider, F and Williams, C. C., (2013) The Shadow Economy, Institute of Economic Affairs, Hobart Paper 172.
World Economics, (2014) Sales Managers’ Index: Latin America
World Economics, (2014) Sales Managers’ Index: Mexico http://www.worldeconomics.com/SMI/Mexico-SalesManagersIndex.efp
World Economics, (2014) Sales Managers’ Index: US http://www.worldeconomics.com/SMI/SalesManagersIndex.efp
 Few countries were excluded as there was no base year information available: Curacao, Sint Maarten (Dutch part) and St. Martin (French part). Aruba, Bermuda, Puerto Rico, Turks and Caicos Islands, and Virgin Islands (U.S.) were also excluded as no GDP PPP data was available for the 2014 year.
 No estimate was available for the following countries: Antigua and Barbuda, Aruba, Barbados, Bermuda, Cayman Islands, Cuba, Curacao, Dominica, Grenada, Puerto Rico, Sint Maarten (Dutch part), St. Kitts and Nevis, St. Lucia, St. Martin (French part), St. Vincent and the Grenadines, Turks and Caicos Islands, and Virgin Islands (U.S.).
 Since 2007 many consultants and experts have been fined by the government; the Argentinean justice system has quashed penalties only recently after more than four years of trials and judicial conflicts.
 Specifically Argentina KLEMS where KLEMS (K-capital, L-labor, E-energy, M-materials, and S-purchased services) refers to broad categories of intermediate inputs that are consumed by industries in their production of goods and services.
 The database is available at: http://arklemsenglish.wordpress.com/database/