The data series available on MOxLAD draw mostly from the studies and statistical abstracts of the Economic Commission for Latin America, but also rely on Mitchell's International Historical Statistics, International Monetary Fund's International Financial Statistics, the World Bank's World Development Indicators and a variety of national sources. In all cases the source used has been included with the series, as well as additional information if the procedures used are different from the norm.
We have attempted to cover all 20 countries in the region, although it is not possible for some series.
The original database covered only the 20th century, but the MOxLAD now covers up to 2010. The data will be progressively extended back to 1870 in cases where information is available.
Information about the procedures followed in constructing the database is presented below.
All comparative analyses, particularly when extended over many countries and many years, encounter methodological problems such as the reliability, consistency, and comparability of the data series.
The reliability of statistical data depends to a large extent on the quality of the source material, but also on the quality of data adjustments and methods, which cannot always be vouched for. This is particularly true for source material dating from the earlier part of the century. Even if the reliability of data can be established, changes in the statistical concepts and methods employed in the data collection and dissemination process methods within countries are not always fully accounted for in the source material.
This may be due to:
differences in data coverage due to the inclusion or exclusion of certain components (e.g., enrolment in public and/or private schools). Consequently, despite best efforts to ensure full disclosure, series may not always be strictly consistent or comparable for the region—let alone for one country—and may result in misleading international comparisons of long-run statistics.
With the publication (and subsequent revision) of the United Nations System of National Accounts and the International Monetary Fund Balance of Payments Manual, national and international data collection and dissemination practices have become increasingly standardised. For data preceding the mid-century, regional comparisons may require the supposition that the margin of discrepancy in the data reported by original sources is more or less comparable for each country, making these statistics reasonable, albeit imperfect, indicators.
The researchers involved in the recompilation of the data presented in MOxLAD have made every effort to ensure meaningful intercountry comparison. This has involved the inclusion of data series and the selection of data sources in conformance with a conceptual framework with emphasis on consistency in statistical concepts over time, data coverage for the broadest range of countries and time series, and intercountry comparability. These issues have required that adjustments be made to the original data, particularly the series for GDP and life expectancy.
The data series included in MOxLAD are defined as follows:
Population: Midyear estimates of total residents from census data, with interpolations between census years; expressed in thousands.
Urban Population: Midyear population of areas defined as urban in each country; expressed in thousands. Please note that the definitions tend to vary between countries and over time, as the process of urbanisation occurs. Figures are calculated from their share of total population reported in the original data sources.
Life expectancy: The estimates of life expectancy were produced by Barbara and Shane Hunt for the Thorp volume with data from the Centro Latinoamericano de Demografía (CELADE) (1996), Arriaga (1968), and Palloni (1990). CELADE's estimates are the official estimates of the respective member countries because they are produced in cooperation with member governments. They are also reproduced by the United Nations and other international agencies. CELADE's estimates refer to a 5-year period, beginning with 1950-55. To get year-specific estimates, the figures of adjacent life tables were averaged; as a result, the earliest year-specific CELADE estimate refers to 1955.
The main source of data for figures for 1950 and earlier years is Arriaga (1968). Arriaga's method inferred mortality rates from the survival of cohorts from one census to the next. Consequently the method was not applicable in cases where immigration was substantial. Thus Arriaga did not attempt estimates for Argentina, Uruguay, and Cuba. For lack of census data, neither did he attempt estimates before 1950 for Haiti and Ecuador. Arriaga's estimates refer to specific years, are generally estimated for each year that begins a new decade, and extend through either 1950 or 1960, which overlaps with the earliest CELADE estimates. Table 1 below shows the correspondence between the two sources for 1960.
Life Expectancy, 1960: Comparisons between Arriaga (1968) and CELADE (1996)
(1) Figure is from UN DY (1951).
(2) Figure refers to 1950. CELADE estimate is derived from linear extrapolation of figures for 1955 and 1960.
Table 1 shows that the match is quite good: what discrepancy exists appears to be largely systematic (i.e., the Arriaga estimates are slightly higher). A 2% discrepancy was considered insignificant. In such cases, which cover 10 of the 20 Latin American republics, the Arriaga figure was tacked on to the CELADE series without adjustment. In two other cases (Cuba, Uruguay), Arriaga made no estimates, and in one (Haiti) Arriaga had an estimate for 1950 only. In that case, the estimate diverged significantly from that of a linear projection of CELADE figures for 1955 and 1960, and the latter estimate was used.
There were, however, seven cases of discrepancy. In six of the cases where the Arriaga figures for 1960 exceeded those of CELADE, the discrepancy ranged from 12% for Honduras to 4% for Nicaragua and Venezuela. In these cases, the CELADE figure was considered to be the more reliable for 1960, and Arriaga's earlier estimates were adjusted accordingly. However, it was considered inappropriate to apply a downward adjustment to the earliest Arriaga estimate for each country, since the already low values of those early estimates were seen as the most noteworthy result of the statistical exercise. Because this result should not be exaggerated by a downward adjustment coming from discrepancies arising many years later in 1960, the downward adjustment applied to Arriaga's estimates was based on a sliding, linear scale, ranging from the actual discrepancy in 1960 to zero in the earliest year for which Arriaga had an estimate in each given country. This discrepancy in the case of Paraguay is, however, sui generis, both with respect to magnitude and direction, as will be discussed further below.
Alberto Palloni's (see Palloni 1990) more recent estimates for some countries and some time periods rely on vital statistics data, adjusted to allow for incomplete reporting. Palloni's estimates fill in several of the gaps in Arriaga's work. These estimates provide comparisons with those of CELADE (1996) for four different five-year periods. If it is assumed that a discrepancy of 3% or less indicates general agreement between the two sources, then 71% (54 of 76) of the comparisons are in agreement. In general, discrepancies greater than 3% do not persist from one time period to the next in the given country. Thus, they appear accidental and not reflective of an underlying bias in one or the other series. Some of the largest discrepancies are, however, quite persistent. They refer to Bolivia, Brazil, Colombia, and Paraguay, and are set forth in further detail in Table 2 below.
Life Expectancy, 1950-1985: Comparisons between Palloni and CELADE for Selected Countries
For Bolivia and Colombia, discrepancies arise only in the early years, but they are substantial. Palloni's estimates show life expectancies that are between two and a half and five years less than those of CELADE. For Brazil, Palloni's figures are consistently lower than those of CELADE, right through to the latest period. Without further knowledge of the different sources and methods used in the estimates, the CELADE estimates were preferred because its figures are official and in better agreement with those of Arriaga, as well as because it has greater coverage.
These arguments could not be applied to the discrepancy in the case of Paraguay because the CELADE figures, whilst official and complete, do not seem credible. CELADE's life expectancy figure for Paraguay in 1950-55 was 62.6 years, a figure equal to that of Argentina and exceeded in Latin America only by Uruguay. This would indicate a significantly greater length of life and superior health conditions than could be found in countries such as Chile, Costa Rica, and Venezuela, all of which had significantly longer life expectancy than Paraguay in later years. In consequence, Palloni's figures for Paraguay were used from 1950-55 through 1980-85; CELADE estimates were used only for interpolation and for extrapolation since 1980-85.
For the period before 1950, two alternative sources are available: Arriaga (1968) and Palloni (1990). The advantage of Palloni is that it is the more recent and, to some extent, builds on Arriaga's earlier work. Arriaga's advantage is that his estimates refer to the decennial years used in this study. Also, his work is more complete; Palloni offers estimates for only three points in time: 1900-05, 1930-35, and 1940-45. For these reasons, the Arriaga estimates were preferred, and Palloni's estimates used to fill in existing gaps and as a check on Arriaga. The devices for checking were the ratios shown in Table 3, which compares figures for those countries and points of time where both authors offer estimates.
Life Expectancy, 1900-1950: Comparisons between Palloni and CELADE (Ratio of Palloni estimate divided by Arriaga estimate)
Table 3 shows that the correspondence is fair in 1940-45, better for 1930-35, and quite good for 1900-05. More specifically, 7 of the 16 comparisons for 1940-45 diverged by more than 5%, 4 of 14 for 1930-35, and only 1 of 7 for 1900-05. The one country with more than a 5% discrepancy in 1900-05 was Costa Rica, with a 10% gap between estimates of Arriaga and Palloni. In addition, Palloni's 1900-05 figure for Colombia is 8% higher than Arriaga's earliest figure, which refers to 1910. It should also be noted that Palloni's 1930-35 figure for the Dominican Republic is 19% above Arriaga's earliest figure, which refers to 1930.
This suggests that while the century-long trends in increase of life expectancy were very little affected by choice of source, the timing and magnitude of the acceleration of improvement around mid-century were affected by choice of source. Thus in the case of Brazil, using Palloni as a source would show an increase in life expectancy of only some 6 years from the early 1940s to the early 1960s, whereas using Arriaga would show an increase of 19 years over approximately the same period. In the case of Bolivia, however, the story was reversed. Palloni estimates an extremely low life expectancy--only 28 years--as late as 1940-45, and then a very rapid rise in the 20 years following, presumably the result of improved health conditions following the Bolivian Revolution. In both the Bolivian and Brazilian cases one source is not intrinsically more plausible than the other, but Arriaga's estimates were preferred in part for source uniformity.
There were, however, instances where Palloni includes data not available in Arriaga (or in the U.N. Demographic Yearbook, in the case of Argentina). In the case of Argentina 1900-05, Palloni's figure of 40.3 was used, along with the UN figure for 1915, for constructing estimates for 1910 and 1900. In the case of Cuba 1900-1950, Palloni's figures from 1900-05 to 1950-55 were used to interpolate estimates for 1900 through 1950. This series fit well enough with the CELADE series that begins in 1955 that no linking adjustments were attempted. In the cases of Honduras 1900-05 and Panama 1900-05, it was decided not to rely on the Palloni figures to fill the gaps in Arriaga's estimates for these countries and periods without more information on Palloni's estimation methodology. Both estimates seem dubious, Honduras 1900-05 because it is identical to Honduras 1930-35, and Panama 1900-05 because it is only slightly lower than Panama 1930-35—this despite the fact that mortality rates in Panamanian cities dropped sharply at the time of the building of the Panama Canal.
Illiteracy rate: In theory, the illiteracy rate is the percentage of the population of or above a certain age (usually 15) who cannot read and write a simple statement about everyday life. In practice, however, the illiteracy rate can sometimes refer to the percentage of the population of or above a certain age with less than two years of primary school enrolment, or can be self-defined. The reported figures come from census data, with interpolations between census years. The illiteracy rates reported in some earlier censuses are not for population age 15 and over. These rates were adjusted for groups aged 15 and over by applying the illiteracy rates from specific associated groups in later censuses (see the notes below the chart displaying results).
Public Spending on Education: Current operating expenditures in education, including wages and salaries and excluding capital investments in buildings and equipment; expressed as a percent of gross domestic product.
Primary, Secondary, and Tertiary School Enrolment: Gross enrolment in primary, secondary, and tertiary levels of education regardless of age; expressed in thousands. Secondary school generally includes vocational and teacher training. Users should be aware that enrolment data may not be very precise due to lack of uniformity of definition of enrolment, (e.g., pupils in attendance on a particular day, in regular attendance, or on the register), reorganisation of school systems, differences in the period constituting the school year between countries and over time, and the inclusion or exclusion of private school enrolment. Users are advised to consult the country notes and cautioned that these may not always fully account for changes in data coverage.
Economically Active Population (EAP): The number of employed and unemployed persons. Reported figures come from census data with interpolations between census years; expressed in thousands. The number in brackets preceding the (+) sign (e.g., [C 14+]) refers to the lower age limit of those persons considered to be economically active; the higher end is usually assumed to be 65 years. Figures are calculated from their share in total population reported in the original data sources.
EAP in Manufacturing: The number of employed and unemployed persons in the manufacturing industry; expressed in thousands. Figures are calculated from their share in total EAP reported in the original data sources.
EAP in Agriculture: The number of employed and unemployed persons in agriculture; expressed in thousands. Figures are calculated from their share in total EAP reported in the original data sources.
Electricity Output: Gross output of electricity, including electricity consumed in power stations and transmissions losses; expressed in million gigaWatt hours. Figures generally include electricity generated by hydropower (hydroelectric power plants), coal, crude oil and petroleum products, natural gas, and nuclear power plants, as well as geothermal, solar, wind, and tide and wave energy, and combustible renewables and waste.
Cement Production: Manufacturing production of hydraulic cements used for construction-purposes, including aluminous, metallurgic, natural, and Portland cement; expressed in thousand metric tonnes.
Beer Production: Manufacturing production of beer; expressed in thousand hectolitres. Figures include all types of beer except home-brewed beer.
Roads: Route length of line open at the end of each year; expressed in kilometres. Figures generally include narrow gauge line and exclude mountain railways. Purely industrial lines, (i.e., closed to public traffic), are not generally included, although the distinction cannot always be made for some countries, (e.g., Central American countries).
Railways: Extensión de líneas abiertas al fin de cada año, expresado en kilómetros. Incluye líneas de medida estrecha y generalmente excluye líneas ferroviarias en las montañas. Líneas puramente industriales (es decir, cerradas al uso público) generalmente no están incluidas aunque la distinción para algunos países (p.ej., países en América Central) no siempre se puede hacer.
Telephones: Number of telephones in use; expressed in thousand lines. For later years, may include cellular subscribers. Users are advised to consult the country notes for changes in data coverage.
Passenger Cars and Commercial Vehicles: Official estimates at year-end; expressed in thousands. Passenger cars are defined as cars seating fewer than eight persons, and include jeeps and station wagons but exclude special-purpose vehicles. Figures for commercial vehicles include buses and taxis but exclude trailers and farm tractors.
Exports: Total value of merchandise exports valued FOB (free on board); expressed in million US dollars. The FOB valuation comprises the price of goods at the border of exporting country and includes the value of the commodity, all outlays on transport to the shipping point, and all requisite fees for loading. Reported trade figures are generally of ‘special’ rather than ‘general’ trade, i.e. they refer only to commodities that have been produced within the country. Domestically produced exports plus re-exports of products originally imported for domestic consumption are included, while goods shipped to and from free-trade zones are not included. Users are advised to refer to original sources for more detailed references to the nature of the statistics used.
Index of Unit Value of Exports: The fixed-weight index of price of exports, generally constructed using the Laspeyres formula. Series with different base years are linked by ratio splicing at the first annual overlap; linked series are then shifted to a common base period (1970=100). These series differ from export price indices, which are compiled from survey data for prices at the wholesale level or from direct pricing (i.e., directly from the exporter); the latter are generally considered preferable to unit value indices because of biases introduced by the aggregation of commodity classification categories with no meaningful unit of quantity (e.g., categories related to machine tools, capital equipment, and certain consumer goods).
Index of Export Quantum: The fixed-price index of the quantity of exports, generally constructed using the Laspeyres formula. Series with different base years are linked by ratio splicing at the first annual overlap; linked series are shifted to common base period (1970=100).
Imports: Total value of import goods valued CIF (cost, insurance, and freight); expressed in million US dollars. The CIF valuation comprises the price of goods at the border of the importing country, and includes the component elements of FOB valuation, as well as the cost of insurance and the cost of international transport. Reported trade figures are generally of ‘special’ rather than ‘general’ trade, i.e., they refer only to commodities that are intended for internal use.
Index of Import Quantum: The fixed-price index of the quantity of imports, generally constructed using the Laspeyres formula. Series with different base years are linked by ratio splicing at the first annual overlap; linked series are shifted to common base period (1970=100).
Index of Unit Value of Imports: The fixed-weight index of price of imports, generally constructed using the Laspeyres formula. Series with different base years are linked by ratio splicing at the first annual overlap; linked series are shifted to a common base period (1970=100). These series differ from import price indices, which are compiled from survey data for prices at the wholesale level or from direct pricing (i.e., directly from the importer); the latter are generally considered preferable to unit value indices because of biases introduced by the aggregation of commodity classification categories with no meaningful unit of quantity (e.g., categories related to machine tools, capital equipment, and certain consumer goods).
Consumer Imports: These refer to miscellaneous manufactured articles (section 8 of the Standard International Trade Classification (SITC) Rev. 3); expressed as a percent of Imports.
Intermediate Imports: Incluye combustibles y lubricantes, expresadas como porcentaje de las importaciones.
Fuel Imports: These refer to mineral fuels, lubricants and related materials; (section 3 of the Standard Trade Classification (SITC) Rev. 3); expressed as a percent of Intermediate Imports.
Capital Imports: These refer to machines, transport, and equipment imports (section 7 of the Standard International Trade Classification (SITC) Rev. 3); expressed as a percent of Imports.
Index of US Inverse Net Barter Terms of Trade: Included as a proxy for world terms of trade (index of world export prices relative to world import prices) faced by Latin America. This index is obtained by dividing the price index of non-manufactured imports (to 1970, and general imports thereafter) by the price index of exports at a constant base year (1970=100).
Central Government Revenue: Total ordinary revenue exclusive of loan receipts; expressed in million local currency units. Depending on data availability, for some countries and time periods, figures are for current (tax and nontax) revenue excluding capital revenue and grants. Users are advised to consult the country notes for changes in data coverage.
Customs Tax Revenue: Customs tax revenue; expressed in million local currency units. Depending on data availability, for some countries and time periods, figures may include all or certain components of taxes on international trade, (e.g., import duties, exchange taxes, and other taxes on international trade and transactions). Users are advised to consult the country notes for changes in data coverage.
Income Tax Revenue: Tax on income, profit and capital gains; expressed in million local currency units, may include property tax for some countries and time periods. Users are advised to consult the country notes for changes in data coverage.
Taxes on Domestic Goods and Services: Expressed in million local currency units. Depending on data availability, for some countries and time periods the figures represent Value-Added Tax or excise taxes only. Users are advised to consult the country notes for changes in data coverage.
Central Government Expenditure: Includes all types of central government budgetary expenditure excluding debt redemption; expressed in million local currency units. Depending on data availability, for some countries and time periods, figures may include extra-budgetary expenditures, or entail budget estimates. Users are advised to consult the country notes for changes in data coverage.
Several National Accounts variables for which it has been possible to obtain wide coverage are presented.
Six of these are related to total GDP. Five of them are a homogenous set of series that have been constructed based on ECLAC estimates with a 1970 base year:
In addition, a GDP at constant 1990 PPP prices is presented in order to allow broad international comparisons.
The following series complete the national accounts section.
GDP at current prices 1970 local currency units: Current GDP (1970 LCU/ECLAC)
The primary source for GDP series is ECLAC. These series are based on ECLAC (1978), which provides GDP estimates based on factor costs at current prices. This source includes all of Latin America except Cuba. The start date for the series vary from country to country depending on the availability of data, but the end date for all of them is 1976. In some cases we have corrected a series, obtaining different annual variations, but maintaining the base level in 1970.
Backward-projection: In a few cases it has been possible to gain access to other sources in order to obtain GDP series at current prices for periods prior to the start dates of the respective ECLAC series. In these cases the two series have been spliced together, using the annual variations of the new source.
Projection: The permanent updating of national accounts leads to new estimates, with new base years, which in turn lead to revisions in the levels as well as the annual variations of the series. The method used here is to reconstruct the annual variations using the most recently available estimates. For example, a current price GDP estimate for 2010, with base year 2005, can show a change of 10% from 2005 to 2006, while a previously available estimate, with base year 1995, shows a 7% change. Similarly, the 2005 base year estimate can be 10% higher than the 1995 base year estimate. In accordance with the method used here, the annual variations in the most recently available series (10% for 2006/2005 in this case) is used, but the levels that arise from the original 1970 base year are maintained, even at current prices.
GDP at 1970 constant prices, 1970 local currency units: Real GDP (1970 prices)
The primary source for GDP series is the ECLAC. These series are based on ECLAC (1978), which provides GDP estimates based on factor costs at current prices. This source includes all of Latin America except Cuba. The start date for the series vary from country to country depending on the availability of data, but the end date for all of them is 1976.
Backward-projection: The aforementioned series have been extended back in time using estimates of GDP by volume or comparable historical statistical compendiums. Because these series are more widely available than those for current prices, greater coverage is achieved.
Projection. In the majority of cases, GDP estimates for after 1976 have been constructed by applying a GDP index in constant market prices (normally with a later base year).
GDP at 1970 purchasing power parity dollars: “PPP GDP (1970 US$)”
In order to compare GDP for different countries it is common to convert their level of production to a common unit of measure. This is usually done using the exchange rate or purchasing power parity (PPP). PPP is generally preferred because: (1) in low-income countries, where labor is much cheaper, the exchange rate tends to over-estimate the value of non-tradable services; (2) the exchange rate can reflect intervention in currency or capital markets; and (3) the reliability of the exchange rate can be affected by the volatility of capital movements (see Maddison, 2001, p. 162).
The most commonly used sources for PPP conversion have been Heston and Summers (1991) and subsequent revisions, as well as the UN and OECD International Comparison Program (ICP), although this last source only covers 7 Latin American countries. MOxLAD employs the 1970 PPP conversion factors reported by ECLAC (1978) and uses them to project the GDP at constant prices series. The PPP rates are estimated based on a basket of goods that reflects regional consumption patterns in Latin America during the 1960s (see United Nations, 1968) and that were updated by ECLAC in 1970. The ECLAC PPP rates were chosen in order to maintain the consistency of the database, since the GDP at constant prices series reported by MOxLAD are also from ECLAC. This source has the additional advantage of covering all countries in the region, except for Cuba (see also GDP at 1990 purchasing power parity dollars).
Implicit GDP deflator, 1970 local currency units (1970 = 100): “GDP Deflator (1970=100)”
The primary source for the implicit GDP deflator is ECLAC (1978).
Backward-projection: In a few cases it has been possible to gain access to other sources in order to obtain an implicit GDP deflator at current prices for periods prior to the start dates of the respective ECLAC series. In these cases the two series have been spliced together using the annual variations of the new source but maintaining 1970 as the base-year in which the index equals 100.
Projection: The permanent updating of national accounts leads to new estimates, with new base years, which in turn lead to revisions in the levels as well as the annual variations of the GDP series as well as their implicit deflators. The method used here has been to reconstruct the annual variations with the most recently available estimates. For example, a current price GDP estimate for 2010, with base year 2005, can show a change of 8% from 2005 to 2006, while a previously available estimate, with base year 1995, shows a 4% change. In accordance with the method used here, the annual variations in the most recently available series (8% in this example) is used, but the levels that arise from the original 1970 base year are maintained. In addition, this deflator doesn’t take into account changes en currency units over time. In the 1970s and 1980s, inflation rates were very high in many countries and currency units were often changed. This series is constructed as if the currency unit of 1970 had never changed. The implicit GDP deflator using monetary unit current in each year is presented below.
Implicit GDP deflator, current year local currency units (1970 = 100): “GDP deflator (1970=100, different LCU)”
The primary source for the implicit GDP deflator is ECLAC (1978).
Backward-projection. In a few cases it has been possible to gain access to other sources in order to obtain an implicit GDP deflator at current prices for periods prior to the start dates of the respective ECLAC series. In these cases the two series have been spliced together using the annual variations of the new source but maintaining 1970 as the base-year in which the index equals 100.
Projection: The permanent updating of national accounts leads to new estimates, with new base years, which in turn lead to revisions in the levels as well as the annual variations of the GDP series as well as their implicit deflators. The method used here has been to reconstruct the annual variations with the most recently available estimates. For example, a current price GDP estimate for 2010, with base year 2005, can show a change of 8% from 2005 to 2006, while a previously available estimate, with base year 1995, shows a 4% change. In accordance with the method used here, the annual variations in the most recently available series (8% in this example) is used, but the levels that arise from the original 1970 base year are maintained.
This series takes into account changes in monetary unit, i.e., the index is calculated in the monetary unit current in each year. This means that a series that has an value of 11500.0 in one year can have a value of 12.0 the next year, if the monetary unit is divided by 1000; for example, if 1000 pesos are converted to 1 new peso.
This set of procedures for the GDP series with base year 1970 gives more weight to comparability between countries and change over time than to consistency in levels for any one country. We would like to emphasize that these series should not be used as a substitute for the original sources when studying individual countries.
GDP at 1970 purchasing power parity dollars: “PPP GDP (1990 US$)”
The 1970 ECLAC estimates have the advantage of being part of a larger set of internally consistent estimates. However, this set of estimates is restricted only to Latin America and is not comparable to other estimates with greater international coverage. Because of this, an alternative measure of PPP GDP is presented. This measure is proposed by A. Maddison (2010) and uses 1990 as a base-year in order to facilitate international comparisons.
These two sources not only present different levels with respect to countries outside of Latin America, but also present differences between Latin American countries. Table 4 compares the PPP GDP per capita at constant prices, calculated for 1990 with that results from projecting the ECLAC series and the figures that arise from Maddison for the same year. As can be seen, Maddison’s estimates place the unweighted average for Latin America at 21.8% of the US level, while the ECLAC estimates place it at just 11.7% of the US level. The differences between the two sources in the relative positions of different Latin American countries are also significant. For example, according to the ECLAC, the average of the rest of Latin America with respect to Argentina was 49%, while according to Maddison it was 79%.
Official PPP estimates for Cuba do not exist (see Pérez-López, 1991). Consequently, the ratio between the 1980 PPP rate for Cuba and the average 1980 PPP rate for Argentina, Brazil, Chile, Colombia, México and Venezuela from Brundenius and Zimbalist (1989, pp. 53, 58) and the average rate from ECLAC (1978, p. 8) is used to estimate the 1970 PPP rate for Cuba.
GDP per capita in PPP dollars, 1990. Relative to the US and Argentina
|Country||According to CEPAL (dollars de 1970)||Maddison (dólares de 1990)||According to CEPAL (dollars de 1970)||Maddison (dollars de 1990)|
Agriculture value-added: Expressed in local currency at 1970 constant prices. Reports the output of the sector net of intermediate inputs and includes the cultivation of crops, livestock production, hunting, forestry and fishing. The depreciation of reproducible assets and depletion/degradation of natural resources are not deducted; expressed in million constant local currency units at 1970 prices. The series was extended to 2000 by applying the real rate of growth of the series at different base years to the series in 1970 prices. As in the case of GDP, the growth rates of the most recently available series have been used, but have been applied maintaining the 1970 base year fixed.
Manufacturing value-added: Expressed in local currency units at 1970 constant prices. Reports the output of the sector net of intermediate inputs; the depreciation of reproducible assets or depletion/degradation of natural resources are not deducted. The series was extended to 2000 by applying the real rate of growth of the series at different base years to the series in 1970 prices. Depending on data availability, for some countries and time periods, figures may include mining and quarrying; users are advised to consult the country notes for data coverage. As in the case of GDP, the growth rates of the most recently available series have been used, but have been applied maintaining the 1970 base year fixed.
Gross Domestic Fixed Investment: Also known as gross fixed capital formation, figures include land improvements, plant, machinery, and equipment purchases, and the construction of infrastructure, (e.g., roads, railways, schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings); expressed as a percent of Gross Domestic Product.
Gross National Savings: Gross domestic savings plus net income and net current transfers from abroad; expressed as a percent of GDP. By convention, this series is calculated as a residual, as there is no direct source of data.
Foreign Direct Investment: Net inflows (from balance of payments), includes equity capital, reinvested earnings, and other capital associated with inter-company transactions between affiliated enterprises but excludes capital flows for exceptional financing, (e.g., debt-for-equity swaps); expressed in million US dollars. For earlier years, data are for US FDI only; users are advised to consult the country notes for data coverage.
External Debt: Comprises total debt, (including the sum of public, publicly guaranteed, and private non-guaranteed long-term external debt, use of IMF credit, and short-term debt), owed to non-residents repayable in foreign currency, goods, or services; expressed in million US dollars. Short-term external debt includes all debt having an original maturity of one year or less and interest in arrears on long-term debt. Users are advised the consult the country notes for data coverage.
Nominal Exchange Rate in 1970 Local Currency Units: 1970 Local currency units per US dollar. This series ignores changes currency units and is therefore compatible with the GDP at current prices series and the implicit GDP deflator. Unless otherwise noted, the figures are market prices and refer to the yearly average (see notes for each country in each table of results).
Consumer Price Index: Reflects the annual changes in the cost to the average consumer of acquiring a fixed basket of goods and services. The Laspeyres formula is generally used to construct the index. Series with different base years are linked by ratio splicing at the first annual overlap, linked series are shifted to a common base period (1970=100). Users are advised to consult the country notes for data coverage, and strongly recommended to refer to original sources for specific information regarding the year to which the weights refer, and other country-specific details on the construction of component indices.
US Producer Price Index: Included as a proxy measure for the average change over time in selling prices received by world producers of goods and services. The United States wholesale price index (WPI) was renamed the producer price index (PPI) in 1978, reflecting the theoretical model of the output price index underlying the PPI, see Archibald (1977). The change from WPI to PPI did not affect the index methodology.
Specific Commodity Price Indices: Shows the fixed-weight index of the spot or transaction prices of commodities sold in world markets at a common base period (1970=100); Manufactures refers to the index of unit value of manufactures exports from the G-5 countries to developing countries.
Weighted Commodity Price Indices: Shows the US dollar index of prices of internationally traded primary commodities at a common base year (1970=100) weighted by: the values of world exports of each commodity (excluding petroleum) in 1977-1979 (Commodity Prices I); the value share of developing countries' export of each commodity (excluding petroleum) in 1981 (Commodity Prices II); the value shares of commodities (excluding petroleum) in world trade of the respective year (Commodity Prices III); the value shares of commodities (including petroleum) in world trade of the respective year (Commodity Prices IV). Please see Grilli and Yang (1988) and Ocampo and Parra (2003) on methodology.
Weighted Commodity Price Indices by Category: Shows the US dollar index of internationally traded commodity prices for food, non-food, and metals exports at a common base year (1970=100) weighted by the values of world exports of each sub-group in 1977-1979. Please see Grilli and Yang (1988) and Ocampo and Parra (2003) on methodology.
The Montevideo-Oxford Latin American Economic History Data Base, 'MOxLAD', is a partnership between the Economic and Social History Programme (PHES), of the Universidad de la República, Montevideo, and the Latin American Centre and the Department of International Development, Oxford University. The objective of the partnership is to expand and update the database previously known as OxLAD, and develop related activities. The database contains statistical series for a wide range of economic and social indicators covering twenty countries in the region for the twentieth century up to today. Its purpose is to provide economic and social historians worldwide with a systematic collection of available statistical information in a single on-line source. The data presented in MOxLAD have been collected with a view toward providing comprehensive coverage while ensuring as much consistency and inter-country comparability as possible in the definition, coverage, and valuation of the series. The initial goal was systematic coverage of the twentieth century, but this is now being expanded, both backwards and forwards.
The MOxLAD team has been carrying out a process of systematic revision and updating of the database, with particular focus on the national accounts series. However, we are conscious of the fact that many of the series can be further improved based on current research being conducted in the region. Therefore, we trust that by making MOxLAD available to the public we can promote discussion between the producers and users of this information, further enriching the process of revision and updating. We hope that MOxLAD can create a space for scholars to meet, debate and collaborate. In order to foster this, we have created mechanisms for submitting questions, comments and criticisms, as well as public forums for debating about sources and procedures.
The original database derived from a project on the economic history of twentieth century Latin America, funded by the Inter-American Development Bank, which resulted in the study published as Thorp, R,. Progress, Poverty and Exclusion: an Economic History of Latin America in the Twentieth Century (Washington D.C.: Inter-American Development Bank 1998). The material appeared as the statistical appendix to Thorp 1998 and was compiled by Pablo Astorga under the direction of Valpy Fitzgerald and Rosemary Thorp. The data base was corrected, updated and expanded during 2002-3 by Ame Bergès under the guidance of Valpy Fitzgerald. This was made possible by a grant from the Hewlett Foundation.
The MOxLAD is currently managed by Luis Bértola (PHES), who coordinates the Executive Committee, also composed of Valpy FitzGerald (Department of International Development), José Antonio Ocampo (Columbia University) and Diego Sánchez-Ancochea (Latin American Centre). The working team at Montevideo is also made up of Jorge Álvarez, Reto Bertoni, María Camou, Gastón Díaz, Cecilia Lara, Silvana Maubrigades y María José Rey.
The International Advisory Committee is so far composed of Rosemary Thorp (Chair), Pablo Astorga, Victor Bulmer-Thomas, Enrique Cárdenas, John Coatsworth, Renato Colistete, Carlos Contreras, Roberto Cortés Conde, José Díaz Bahamonde, Daniel Díaz Fuentes, Pablo Gerchunoff, André Hoffman, Shane Hunt, Juan Carlos Moreno-Brid, Héctor Pérez Brignoli, José Alejandro Peres Cajías, Leandro Prados de la Escosura, Ricardo Salvatore, Richard Salvucci, Bruno Seminario, Xavier Taffunel, Antonio Tena and César Yáñez.
The present expansion is being funded by the Economic and Social History Programme of the Universidad de la República, Montevideo (project “Latin American Development in Comparative Perspective”, GUINCHE-group granted by CSIC) and the Data Bank of the Faculty of Social Sciences of the Universidad de la República. It is also supported by grants from Oxford University (Latin American Centre and the Department of International Development) and the Banco de la República Oriental del Uruguay.