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THE THREE FACES
OF THE INTERNATIONAL
COMPARISON PROJECT
Irving B. Kravis
FILhE
CUSY
he system of international income and purchasing power comparisons produced by the United Nations International Comparison Project (icP)is improvingour perceptionsof the world economy in three major ways.' The most direct and widely known revelations, of course, are the true size of countries' average incomes and the
differences between them. The non-icP method commonly used-the
conversion of income in own-currency to a numeraire currency by the
use of the exchange rate-exaggerates the dispersion of per capita incomes by systematicallyunderstating those of poorer countries.
What has attracted less attention is the insight the icp study brings to
comparative national price levels. Until now the vast literature on prices
and exchange rates has been confined to comparative movementsof the
price levels of different countries over time. This approach requires
adopting some base period when price levels are assumed to be in
equilibrium. There has been no way of measuringthe differencesin the
levelsof prices for GDP at a givenperiod. The icP fillsthis gap. It enables
us to observe, for example, that Germany's price level was 130 percent
of the U.S. level in 1980 and 76 percent of it in 1984, not just that
German prices declinedby more than 40 percent relative to U.S.prices.
The icp's third and still less noticed contribution is the opportunity to
compare the relativequantities and pricesof the goods that make up the
Theauthoris gratefulto LaszloDrechsler,
AlanHeston,andRobertE. Lipseyfor their
helpfulcommentson an earlier draft of this paper,but none of them is responsiblefor the
viewsexpressedhere. DavidRobinsondid the statisticalwork and Nancy Bonsallprepared
the manuscript.
3
of different countries. Take, for example, the share of spending on
producers' durable goods. For most countries, the share expressed in
own-currency is available from the national accounts. Without the Icp
comparisons, however, one cannot tell to what extent a country's spending share is higher than another's because it absorbs larger quantities of
producers' durable goods and to what extent it is merely because their
prices are higher.
All three of these new insights arise because purchasing power parities
(PPPs)replace the exchange rate as the means of converting GDP and its
components to a common currency. The exchange rate has great importance and many uses, but it is not a reliable indicator of the purchasing
power of a currency. For example, the average German mark (DM)/U.S.
dollar exchange rate in 1984 was DM 2.85 but it took only DM 2.17 to
buy the bundle of GDP that $1 would buy. The German GDP per capita
was DM 24,186; the U.S. was $11,363. Converted at the exchange rate
of DM 2.85, the German figure was only 75 percent of the U.S. GDP per
capita. The correct ratio was in fact 98 percent, based on the relative
purchasing power of the two currencies.
One purpose of this paper is to elaborate on these three faces of the
icp. Another is to place these results in the context of the history of
international income comparisons, the methods used to obtain them, and
the problems of maintaining and developing the system of comparisons.
GDPS
A Little
History
4
The story of real income comparisons goes back to Gregory King
(1936). He found that in 1688 per capita incomes in England and Holland were about the same, but almost a fourth lower in France. Nearly
three centuries later, the United Kingdom and the Netherlands are still
very close; France is roughly 10 percent higher. Since King's work, some
other estimates have been made. But until the last few decades, major,
well-organized efforts were rare. The most ambitious was an investigation of the real wages and welfare of industrial workers in about 200
towns and cities of Belgium, France, Germany, the United Kingdom, and
the United States carried out by the British Board of Trade and published in five reports between 1908 and 1911. Data were collected in the
field on money wages in certain ubiquitous trades; price comparisons
were made for foods, fuel, and rents; and descriptions of workers' welfare (such as the extent of overcrowding) were provided. At the risk of
pressing the data beyond what they can support, it may be said that
weekly real wages in October 1905 were about 60 percent higher in the
United States than in England, while in the other three countries they
were some 30 percent below the English level (Kravis 1984). Another
landmark study of a very different character was Colin Clark's comparisons of real income in his Conditions of Economic Progress (1940).
Using a remarkable range of secondary sources, Clark compared the
Research Observer 1, no. 1 Uanuary 1986)
purchasing power of thirty currencies for consumption goods with a
y
1929 reference date and more than a dozen with a 1946 reference date.
Two advances in statistics and technology paved the way for the next
stages of international comparisons. The first was the development of
national accounts; the other was the computer. The first widened the
focus from wages and wage earners to all types of income and income
recipients and provided a statistical framework of concepts (for example,
GDP) and accounting rules. The computer made it possible to compare
many more countries in a completely even-handed and consistent way
(KHS 1982, p. 71). In particular, researchers could satisfy the requirement
that the index numbers for income should be "base-country invariant"that is, the quantitative relationships among countries should be independent of the choice of the numeraire country. Another important
requirement is that the index numbers should be transitive: that is, Ij.b +
Ik/b should equal Ij,, when each index is computed directly and where I is
an index of quantities or prices, and j, k, and b, are countries.
The first study based on national accounts was the Gilbert and Kravis
(1954) comparison for four western European countries and the United States, sponsored by the Organisation for European Economic Cooperation (OEEC). In several important respects, this study established the
broad approach adopted in later work, including not only the Gilbert
and Associates (1958) extension to four more western European countries but also the icp. All worked with a breakdown of GDP in terms of
final expenditures for functional categories (such as food and clothing)
instead of trying to compare the output of the GDP originating in each
industry. All also used the relationship that prevails for a given good for
any pair of countries: the price ratio between the countries times the
quantity ratio equals the expenditure ratio.
These basic principles were applied to work on Latin America (Braithwaite 1968; Salazar-Carrillo 1973) and eastern Europe. However, many
other studies were made during the 1950s and 1960s, mainly involving
pairs of countries. Almost all were based on secondary data sources and
differed in scope, method, timing, and quality. The result was a patchwork that fell far short of a cohesive picture of world incomes (KKHS
1975, pp. 2-3).
In 1968 the United Nations Statistical Office (UNSO)felt the time was
ripe to meet head on the major source of incomparability that prompted
these scattered efforts-the deviation of exchange rates from purchasing
power parities. The UNSO had already promoted international comparability of national accounts by sponsoring the development of a standarized system of national accounts (United Nations 1968). With help from
the Ford Foundation, the icP was organized. Half of its small central
staff came from UNSO,the rest from the University of Pennsylvania. The
ICP's first effort, phase 1, covered seven countries with a 1967 reference
date and ten countries for 1970. Phase II extended the comparisons
Irving B. Kravis
to
5
sixteen countries with 1970 and 1973 data. Phase III included thirty-four
countries with a 1975 reference date. The basic methodology was established in phase I, but was improved and extended in the later phases.
In phase IV, the icp was taken over by the UNSO. This phase included
about sixty countries with a 1980 reference date. Much of the work was
done by regional groups of countries, with much less coordination in the
selection of specifications and in methods of quality matching.
How It
Is Done
The heart of international income comparisons is making price, rather
than quantity, comparisons. For most kinds of goods, it is easier to
obtain a representative sample of country-to-country price ratios than
quantity ratios, and the sampling variability of price ratios tends to be
smaller. If aggregation problems are ignored, the approach may be simply described as deriving a quantity (real income) comparison by dividing a price ratio into an expenditure ratio:
Qb
Eb
Pb
where j and b are countries; Q's are physical quantities, E's are expenditures (for GDP or its appropriate components), and the P's are prices, the
E's and P's being in own-currencies. (P/Pb is the purchasing power
parity.)
The tasks involved are:
* Dividing
GDP into categories for which expenditure data and price
comparisons can be obtained
* Selecting and pricing a sample of specifications for each expenditure
category
* Aggregating the price relatives at the category level
* Aggregating the categories to form price and quantity indexes for
GDP and its subaggregates.
The methods used by the European Community in its parallel series of
comparisons through which its member countries participated in the ICP
were broadly similar, but involved greater detail in classifying expenditures and different ways of matching qualities in price comparisons
(SOEC 1983, pp. 22f).
The way these tasks have been performed in the iCP may be summarized briefly, with particular attention to those elements that affect the
quality of the results. Final expenditures on GDP are subdivided into
about 150 detailed categories, following closely the United Nations
(1968) recommendations. The degree of disaggregation depended primarily on the availability of expenditure data in various countries. The
classification employed is mainly a functional one: household consumption, capital formation, and government consumption are differentiated
and then subdivided-for example, food and then beef within consump-
6
Research Observer 1, no. 1 (January 1986)
tion. Some effort is made to select classifications that have homogeneous
international price relationships for their products.
*The next step is to make price comparisons for each detailed category,
with a few exceptions (such as number of teachers and of government employees) for which quantity comparisons are more feasible.
This phase of the work has the greatest influence on the quality of the
income comparison. The sample of specifications for each category must
be representative of price formation influences in each country, and the
items actually priced in the different countries must be equivalent in
quality. To insure such equivalence, the icp arranged international exchanges of samples, on-the-spot inspection of goods in shops by visiting
price experts, plus the advice of merchants, manufacturers, and engineers. Once specifications were established, the country's statistical authorities provided the national average price for each. In phase III the
thirty-four participating countries each priced an average of nearly 400
consumer goods, 38 construction specifications, and nearly 100 producer
durable goods.
This approach ran into a major aggregation problem because the
countries varied widely in their consumption habits. This variety made it
impossible to price a standard list of specifications in all countries and
still retain the principle that only representative items be compared.
Thus, for most detailed categories, few if any countries reported prices
for the full list of items. Methods were devised for deriving transitive,
base-country invariant index numbers from incomplete sets of prices for
the detailed categories. The missing prices in country A were inferred
from the price relationships found in other countries between them and
other items for which prices were available in country A (Summers
1973).
The formula for aggregating across the categories valued the quantities of goods in each country's GDP at world average prices. Added
together, these values yield the desired real income comparisons for
GDP or its subaggregates. The formula, which was suggested by Robert
Geary and amplified by S. Khamis, involves deriving the price comparisons and the average world prices simultaneously in two subsets of
equations (KHS 1982, p. 90). Although there has been a lively academic
discussion of aggregation methods, it seems unlikely that equally plausible methods would produce significantly different results (KHS 1982, pp.
95f).
In the first three phases of the icp, the methods described above were
applied uniformly to all countries, regardless of their location or political affiliation. In phase III, for example, the Geary-Khamis formula was
used to calculate "world" average prices, taking into account the price
structures of all thirty-four countries. Malawi and the United States were
treated alike-although each was assigned a "supercountry" weight,
based on the importance of that type of country in the world, not just
Irving
B. Kravis
7
the country per se (KHS 1982, p. 79). A single set of prices-a common
measuring rod-was therefore used to value the product of every country or supercountry.
The same is not true of the phase IV results, because the exercise has
been regionalized. For example, comparisons among fifteen participating
African countries were carried out using average African prices to value
each country's components of GDP. At a second stage this method was
applied to several "core" countries from each region to produce interregional comparisons. The regional GDP totals obtained from the second
stage were applied pro rata to the countries within the region in the
proportions of real GDP produced by the first stage. The regional groupings included two sets of countries in Europe (the European Communities, or EC, and one led by Austria), Africa, Asia, and Latin America.
In addition, the EC insisted that the relative per capita GDPS of its
member countries obtained in exclusively EC calculations be kept fixed in
the worldwide comparisons of the UNSO (and also in the OECD comparisons for its member countries). As a result, a common measuring rod
was no longer used for comparisons between countries in different regions. The EC's average prices were used to value and compare the GDPS
of its member countries, and world prices were used to determine the
total GDP of the EC. This meant that a different set of prices was used to
value the quantities in, say, a Germany/Norway comparison than in a
Germany/United States comparison, and both are different from the EC
average prices that produced the internal EC comparison of, say, Germany and France.
A valid argument for having regional estimates is that the sample of
specifications compared in price and the weights used in aggregation will
be closer to those of the countries being compared when the comparison
is limited to a region. For internal policy purposes within the EC, comparisons involving only EC members are preferable. But the EC's fixity
rule requires that the worldwide comparisons may not present alternative results for EC member countries based on the application of world
average prices. The aim is to avoid undermining the confidence that
policymakers would have in the estimates were there alternative sets of
indexes available.
However, the fixity rule imposes a high price on worldwide uses and
users. Fixed regional results cannot be embodied in the worldwide indexes so as both to preserve the GDP relationships among countries in a
region and to have the sum of the region's quantities for each category
equal to the sum established by the interregional comparison. It is
impossible to produce a table characterized by "matrix consistency" like
the one below, that is, with all the rows adding up correctly for each
column, each row showing the proper quantitative relationship between
the country columns, and the regional and world versions differing by a
fixed multiple.
8
Research Observer 1, no. 1 (January 1986)
Country A
150
30
20
200
Consumption
Investment
Government
GDP
International units
Country B
200
15
35
250
Region
350
45
55
450
All in all, the case for taking a world view in phase V, now being
planned with a 1985 reference date, is compelling. The UNSO would
produce "universal" comparisons, leaving it to regional bodies to produce purely regional estimates where there is a practical need for them.
The results of phase IV are available for some of the regional groupings. But the worldwide comparisons being prepared by the UNSO are not
completed at the time of writing. In this article, we have linked the
European (Ward 1985) and African (SOEC 1985a) comparisons for 1980
and extrapolated Asian and Latin American benchmark comparisons
from 1975 phase III results to 1980. These procedures give only rough
interim estimates, but they serve to illustrate the icp findings.
To prepare table 1, the forty-nine countries for which such estimates
could be made were listed in ascending order of real per capita income
and divided into seven income classes, each with seven countries. The
table shows the simple averages of the real (Ppp-converted) per capita
Real Income
Comparisons
Table 1. Per Capita GDP Converted to Dollars by PPPsand by
Exchange Rates, Averages for Countries Grouped by Income
Class, 1980
Average GDP per capita
converted by
Exchange rate
PPP
Exchange rate
deviation index
(U.S. = 100)
(1)
(2)
(3)
4.8
8.7
15.6
26.1
46.5
76.5
93.6
2.3
5.4
9.1
16.2
37.3
86.2
109.1
2.1
2.0
1.8
1.7
1.3
0.9
0.9
1
2
3
4
5
6
7
Income class
7.0 or less
7.0-9.9
10.0-21.9
22.0-34.9
35.0-59.9
60.0-84.9
85.0 or more
Note: Forty-nine countries were arrayed according to their PPP-converted per capita GDP in
1980 (from low to high) and divided evenly into the seven income classes. Only OECD countries
(including Canada, Japan, and the United States) are found in classes 6 and 7, but a few OECD
countries are found in classes 4 and 5. Classes 1 to 5 comprise mainly developing countries:
fifteen African, ten Asian, and five Latin American and Caribbean countries.
Sources: See tables 2-4.
Irving B. Kravis
9
Table 2. Real and Nominal
1983
GDP Per
1980
GDP per capita
(U.S. = 100)
converted by
Country
Portugal
Yugoslavia
Greece
Ireland
Spain
Italy
United Kingdom
Austria
Finland
Netherlands
Belgium
France
Denmark
Germany
Luxembourg
Norway
Capita, European Countries, 1980 and
1983 GDP per capita
(U.S. = 100)
converted by
Exchange rate
deviation index
1980
1983
PPPs
(1)
Exchange rates
(2)
PPs
(3)
Exchange rates
(4)
(1) (2)
(5)
(3) - (4)
(6)
34.4
35.6
43.8
51.1
55.7
69.1
73.1
75.2
77.9
82.2
84.7
86.0
85.8
88.7
93.8
98.9
21.8
27.7
36.4
48.4
49.5
61.3
82.8
89.7
81.5
104.5
106.2
106.5
113.0
115.5
111.1
123.3
35.1
n.a.
40.9
52.2
56.5
67.4
75.8
76.8
82.0
79.2
84.7
87.3
89.1
88.7
88.2
102.5
14.7
n.a.
24.2
36.7
29.7
44.4
57.9
63.5
68.4
65.9
59.6
67.9
78.8
76.2
62.5
95.3
1.58
1.29
1.20
1.06
1.13
1.13
0.88
0.84
0.96
0.79
0.80
0.81
0.76
0.77
0.84
0.80
2.39
n.a.
1.69
1.42
1.90
1.52
1.31
1.21
1.20
1.20
1.42
1.29
1.13
1.16
1.41
1.08
n:a. Not available.
Sources: Ward (1985), except Yugoslavia (UN 1984).
(column 1) and the nominal (exchange-rate-converted)
per capita
(column 2). The ratio of the real to the nominal per capita GDPS set
out in column 3 has been called the exchange rate deviation index
(ERDI); it provides a gauge of the extent to which the exchange rate,
valuable though it is for many purposes, fails as a measure of purchasing
power. It can be seen that the lower a country's real GDP per capita, the
higher its ERDI tends to be. This generalization also ocurred in earlier
phases of the ICP. In phase III, for example, the ERDI averaged 2.6 for
eight countries with 1975 real per capita GDPS of 15 percent or less of the
U.S. level, but it was unity for nine countries with real incomes from 60
to 90 percent of the U.S. level (KHS 1982, p. 22). Thus, the dispersion of
real per capita incomes is smaller than that of nominal per capita
incomes; the coefficients of variation for the underlying 1980 benchmark
observations in columns 1 and 2 are 84 percent and 108 percent respectively.
The larger number of countries included in phase IV makes possible a
closer examination of the relationships between real and nominal per
capita GDP. Column 5 in table 2 shows the 1980 ERDI for sixteen European economies. As in table 1, the lowest-income countries have the
highest ERDIs. In 1980, the average ERDI for the five countries with the
GDP
GDP
10
ResearchObserver1, no. 1 (January1986)
lowest real incomes was 1.25; for the next five it was 0.91; for the
remaining six it was 0.80. Among the more industrialized countries of
western Europe, however, the relationship between the ERDI and real GDP
per capita is much more tenuous. For the countries in the lower half of
the table (rows 7 to 16), the negative association between per capita
income and the ERDIS is very weak despite a wide spread of per capita
incomes (Norway's is 35 percent greater than the United Kingdom's).
The underlying reason for this weak relationship may be seen by considering the ERDI in terms of its reciprocal-that is, the price level:
ERDI
Own-currency GDP . PPP
Own-currency GDP - Exchange rate
Exchange rate
ppp
In terms of the earlier illustration, a Pppof DM 2.17 to the dollar and an
exchange rate of DM 2.85 to the dollar means that German prices are on
average 76 percent of the U.S. level. Since the price levels of western
Table 3. Real and Nominal GDP Per Capita, African
Countries, 1980
1980 GDP per capita
(average for
15 countries = 100)
converted by
Country
Ethiopia
Mali
Tanzania
Malawi
Madagascar
Kenya
Senegal
Zambia
Nigeria
Zimbabwe
Cameroon
Morocco
Ivory Coast
Botswana
Tunisia
Africa (15 countries)
PPPs
(1)
Exchange rates
(2)
37
43
47
S3
73
82
88
94
115
115
117
154
176
205
256
100
20
29
37
30
55
62
76
94
145
105
121
128
186
167
199
100
Exchange rate
deviation index
(1)-(2)
(3)
1.85
1.48
1.27
1.77
1.33
1.32
1.16
1.00
0.79
1.10
0.97
1.20
0.95
1.23
1.29
1.00
Note: To prepare table 1, the figures in column 1 were converted to a basis of U.S. = 100 by
comparing the phase III and SOEC results for the three countries included in both studies (Malawi,
Kenya, and Zambia). The average phase Ill/SOEc 1980 ratio for these three countries, 8 percent,
was applied to the column 1 figures in this table to shift them to a U.S. base.
Source: SOEC(1985a).
Irving B. Kravis
1l
European countries are closely linked by extensive trading and institutional ties, differences among them in real per capita income are more
weakly correlated with the ERDI.
A similar analysis of the phase IV results for fifteen African countries
may be carried out on the basis of table 3. Here, ERDIs are highest for
the six lowest-income countries. An exception is found in that some of
the richer countries in the table have higher ERDIS than those in the
middle. For the world as a whole, however,the basic relationship still
applies: the poorer a country, the higher its ERDI. This receives further
support from the data for Asian countries in table 4, the remaining
region for which we can assemble more than a handful of benchmark
countries.
Comparisons
Price Levels
of
There are two possible explanations for the fact that the purchasing
power of the currency of low-income countries tends to be greater than
is suggested by their exchange rates. In one, the productivity differential
model, the productivity gap between rich and poor countries is held to
be smaller in nontradable goods (especially services) than in tradables.
This is consistent with the widespread observation, confirmed in the ICP,
that nontradables tend to be cheap in low-income countries. In 1975, for
example,
Average price levels (U.S. = 100)
Tradables
Nontradables GDP
Eight countries with per
capita incomes less than
15 percent of U.S. per
capita income
Nine countries with per
capita incomes from 60
to 90 percent of U.S.
per capita income
60
25
41
118
97
108
All goods were cheaper in the low-income countries, but the nontradables were cheaper by a larger margin (KHS 1982, p. 196). The reason is
that wages in a low-income country are set to a national standard, and
the relatively higher productivity in nontradables ensures low prices (KHS
1982, p. 333). With the prices of tradables more nearly aligned with
world levels, low prices for nontradables mean a low price level for GDP
as a whole. However, even tradable prices are pulled down because they
are always sold with a mixture of services (retailing, for example).
The alternative explanation, cast in terms of factor proportions, assumes that low-income countries are labor-abundant and that services
(an important part of nontradables) are labor-intensive. Since the price
equalizing tendencies of international trade operate weakly on nontrad12
Research Observer 1, no. 1 (January 1986)
Table4. Real and Nominal GDP Per Capita, Asian Countries, 1980 and 1983
Country
India
Pakistan
SriLanka
Thailand
Philippines
Korea
Malaysia
Syria
Israel
Japan
1980 GDP per capita
(U.S. = 100)
converted by
PPPs
Exchange rates
(1)
(2)
1983 GDP per capita
(U.S. = 100)
converted by
PPPs
Exchange rates
(3)
(4)
6.4
7.2
10.0
15.0
11.8
25.3
24.9
25.2
59.1
73.5
6.7
7.8
11.1
16.5
13.8
29.4
27.5
27.2
S9.0
80.3
2.2
2.6
2.4
6.3
6.5
14.4
15.1
12.9
47.8
77.1
1.9
2.2
2.4
5.9
4.8
13.8
14.2
14.8
44.2
69.3
Exchange rate
deviation index
1980
1983
(1) (2)
(3) (4)
(5)
(6)
2.91
2.77
4.17
2.38
1.82
1.76
1.65
1.95
1.24
0.95
3.59
3.55
4.63
2.80
2.88
2.13
1.94
1.84
1.33
1.16
Sources:PrPconversions:extrapolations from phase III(1975) results (KHS
1982), except for Israel(SOEC1985b) and Japan
(Ward 1985)for which 1980 benchmarkswere available; 1983 Israelextrapolated from 1980; Japan from Ward(1985).
Exchangerate conversions:based on IMF (1985) data on current GDP,population, and exchangerates, except for Israel and
Japan.
ables, they will be cheap in low-income countries and again produce a
low price level (Kravis and Lipsey 1983; Bhagwati 1984).
These and other structural factors affecting prices in different countries are also joined by short-run influences. Obvious examples include
changes in the supply of and demand for money in a given country
relative to changes in the numeraire country, and changes in expectations that produce a volatility of exchange rates relative to goods prices
(Kravis and Lipsey 1983, p. 18). The literature on the determination of
exchange rates has paid most attention to these and other short-run
influences. However, it has been argued (Kravis and Lipsey forthcoming)
that the price levels of different countries tend to conform to a long-run
structural relationship. Such a relationship should prove more useful
than the assumption that equilibrium exchange rates conform to purchasing power parities, but the issue needs further research.
The overall variation in price levels may be inferred from the relationships between nominal and real GDP per capita shown in tables 1 to 4.
The ERDI for countries in income class 1 of table 1 indicates, for example, that the 1980 average price level for the seven lowest-income countries was 48 percent of the U.S. level-that is, their price level is the
reciprocal of their ERDI. Table 5 examines more closely price level data
for four key countries. The first group of figures shows the variability of
exchange rates in recent years-a variability muted here by the use of
annual averages, but still large. It is far greater, for example, than the
tariff changes achieved by arduous trade negotiations. The next two
Irving B. Kravis
13
Table5. Comparative GDP PriceLevels, Selected Countries
and Dates
France
(F/US$)
Germany
(DM/US$)
Japan
( 3 1/US$)
United Kingdom
(f£US$)
Exchange rates
1975
1980
1983
1984
4.29
4.23
7.62
8.74
2.46
1.82
2.55
2.85
297
227
238
238
0.452
0.430
0.659
0.752
PPPs
1975
1980
1983
1984
4.62
5.24
5.93
6.18
2.79
2.37
2.19
2.17
277
240
207
202
0.349
0.487
0.503
0.511
Price levels
1975
1980
1983
1984
108
124
78
71
113
130
86
76
93
106
87
85
77
113
76
68
Source: Ward (1985).
banks of figures, the Ppps and the price levels, are unique to icp studies.
In the absence of icp data, an analyst might choose a base year and then
measure relative changes in price levels. If 1975 were picked as the base
and the German PPPs correctly reflected the relative movement of German and U.S. prices, what is often called the "real exchange rate" might
be calculated as shown in table 6. The index of the real exchange rate
(column 4) is the nominal rate adjusted for the relative price changes in
Germany and the United States. The same information may be derived
from the price-level data by converting it to an index series with 1975
100 and taking the reciprocals.
The icp price levels for Germany-113, 130, 86, 76-give information
that the real exchange rates do not. To be sure, the latter imply big
fluctuations in relative price levels, but they do not show that the German level shifted from 30 percent above that of the United States in 1980
to 24 percent below it in 1984.
Comparisons
of Economic
Structure
14
This article has concentrated so far on an exchange rate's deviation
from its purchasing power over the bundle of goods that comprise GDP.
However, the deviation of the exchange rate from Ppp is not uniform. It
varies from one good to another. This is, of course, a way of saying that
the relative price structures of countries differ. The varying deviations of
exchange rates from PPPsalso mean that intercountry quantity relationResearch Observer 1, no. 1 (January 1986)
Table6. Calculationof the Real ExchangeRate
Real exchange rate
1975
1980
1983
1984
Nominal
DM/US$
exchange
rate
(1)
Index of
German prices
to U.S. pricesa
(2)
Nominal rate
adjusted for
price change
(1).(2)
(3)
Index of
price-adjusted
rate (3) with
1975=100
(4)
ICP
price
levels
(5)
2.46
1.82
2.55
2.85
100.0
86.0
80.0
79.0
2.46
2.12
3.19
3.61
100
86
130
147
113
130
86
76
a. Ratio of German GDPdeflator to U.S. GDP deflator.
Sources: Column 1: table 5; column 2: IMF (1984,1985); and column5: table 5.
ships for components of GDP are not what exchange rate conversions
make them appear to be. Thus, the ICP results open the path to the study
of both price and quantity structure. Here we illustrate the possibilities
by showing the contrast for two sets of goods-producer
durables and
services-seen
first in terms of real quantity comparisons and then in
exchange rate conversions.
For convenience, table 7 groups the thirty-four countries from IcP
phase III into six classes according to the size of their 1975 real GDP per
capita. The figures in column 1 suggest that the four lowest-income
groups, consisting mainly of developing countries, devoted a larger proportion of their GDP to producer durable goods than did the industrial
countries. However, when all components of GDP (including the various
kinds of producer durables) are valued in every country at a common set
of world average prices, a different picture emerges. The real share of
GDP spent on producer durables (column 2) tends to rise with income.
This difference stems from the fact that producer durables are relatively
expensive in the price structure of a typical low-income country and
inexpensive in the price structure of a high-income country. The twist in
price relationships which produces this result may be seen in columns 3
and 4. Column 3 shows no marked association between the level of
producer goods prices per se and real GDP per capita. But most of the
other components of GDP do become more expensive as countries grow
richer, and the price-level indexes for GDP in column 4 reflect this. When
the prices of producer durables are expressed in relative terms-as
column 5 does, taking them in relation to the country's GDP price levelthey are indeed seen to be expensive relative to other GDP components in
poor countries, but comparatively cheap in rich countries. Developing
countries spend a relatively large part of their incomes on producer
durables, but do not get as much as appears for what they spend.
Irving B. Kravis
15
Table 7. Expendituresand PriceLevels for ProducerDurable
Goods, by Income Class, 1975
Income
class
(U.S.=100)a
1
2
3
4
5
6
0-14.9
15.0-29.9
30.0-44.9
45.0-59.9
60.0-89.9
90.0-100.0
Share of expenditures
in GDPb
In nominal
In real
GDP
GDP
(1)
(2)
10.7
11.6
10.5
11.9
8.9
6.9
5.1
8.8
7.5
10.5
11.2
9.9
Price levels
(U.S. = 100)
Producer
durables
(3)
130.1
105.6
135.8
116.4
125.8
100.0
Relative producergoods
GDP
(4)
price levels
(3) . (4)
(5)
40.7
51.7
64.5
73.6
107.4
100.0
3.20
2.04
2.11
1.58
1.17
1.00
a. U.S. per capita GDPof $7,176 is equal to 100. The countries in each real income class are:
(1) Malawi, Kenya, India, Pakistan, Sri Lanka, Zambia, Thailand, and Philippines; (2) Korea,
Malaysia, Colombia, Jamaica, Syria, and Brazil; (3) Romania, Mexico, Yugoslavia, Iran, Uruguay, and Ireland; (4) Hungary, Poland, Italy, and Spain; (5) United Kingdom, Japan, Australia,
Netherlands, Belgium, France, Luxembourg, Denmark, and Germany; and (6) United States.
b. Averages of country shares.
Source: KHS (1982), tables 6-6, 6-5, and 6-8.
This general argument can be strikingly illustrated by examples of
individual countries. In the phase III report, the Philippines was found to
have spent 13.9 percent of its 1975 GDP on producer durables while
Korea spent only 11.8 percent. Translated into dollars via exchange
rates, their respective expenditure per capita was $52.40 and $68.97.
Such figures are grossly misleading, however. Producer durables were 36
percent more costly in the Philippines than in the United States, while in
Korea they were 24 percent cheaper. When world prices are used as a
common measuring rod, Koreans bought nearly 2.5 times as many producer durables per capita as did Filippinos ($131.00 compared with
$55.60). The Korean share of real Ppp-converted GDP going to producer
durables was 8.8 percent; the Philippine share was 5.9 percent.
Another illustration of the misleading comparisons that can be produced by exchange rate conversion is the widely held belief that richer
countries produce and consume more and more of their output in the
form of services. This view seems to be justified by the figures in column
1 of table 8, showing the shares of GDP spent on services by countries in
the six income classes. However, when world average prices are used to
value the goods and services in each country's GDP, the share of services
remains virtually constant (column 2). The contrast can be explained by
the behavior of prices (columns 3 and 4). For both goods and services,
prices levels rise with income; but service prices are higher in the rich
countries by much larger margins than goods prices. For example, the
ratio of the price index for class S to class 1 countries is 4.6 for services,
16
Research Observer 1, no. 1 (January 1986)
Table 8. Share of Services in GDP and Services Price Levels
for Countries Grouped by Income Class, 1975
Share of services in GDP
Income
class,
National
prices
(1)
1
2
3
4
5
6
22.2
28.4
27.3
25.6
36.8
43.9
World World
average
prices
Goods
(2)
(3)
33.8
31.7
31.8
30.3
31.2
32.3
57.2
65.9
83.1
94.0
119.0
100.0
~~~~Price
levels
Services
(4)
GDP
(5)
20.7
34.1
41.2
46.3
94.6
100.0
40.6
51.7
64.7
73.5
107.5
100.0
a. See table 7.
Source: KHS (1982), tables 6-10 and 6-12.
only 2.1 for goods. Richer countries do not devote more of their real GDP
to services than poorer ones. The cross-country income elasticities of
demand for services and for goods are close to 1.0 (KHS 1983). However,
if the calculations are confined to consumption rather than all of GDP,
the income elasticities of demand are 1.13 for services and 0.93 for
goods.
The system of international comparisons developed through phase IV
will include benchmark estimates for about sixty countries, most of them
for only one or two reference dates. Extensions will clearly involve
extending the system to all countries and providing annual estimates of
at least real GDP per capita and the GDP price level. However, these
extensions will be a slow process. The UNSO is finding it difficult to
finance an adequate central staff, and some countries will lack the data
to participate in future rounds of the icP.
For nonbenchmark countries, estimates of real per capita GDP or of
the price level can be made by one of several methods. The "reduced
information" approach, experimented with at the World Bank, aims to
produce close-to-benchmark results with data that meet two criteria: (1)
they do not require special collection, but are at hand or easily made
available; and (2) the PPPsthey yield are close to the average Pppfor GDP
in the cases of the benchmark countries. Another approach is based on
relationships found between real GDP per capita in benchmark countries
and certain physical indicators such as per capita milk consumption
(Beckerman 1966; Economic Commission for Europe 1980). These physical indicators are then used to estimate the real per capita GDP of
Irving B. Kravis
Filling the
Gaps in the
System of
Comparisons
17
nonbenchmark countries. A third approach, often referred to as the
"shortcut" method, is based on estimating for the set of benchmark
countries an equation relating real GDP per capita (or the price level) to
certain variables that are widely available for all countries. The equation
is then used to estimate real per capita GDP (or the price level) for
nonbenchmark countries. An example of such an equation based on the
Phase III results is as follows (with t-ratios in parentheses):
In r= 1.57 + 0.89 In n
(7.0)
(7.7)
-
0.038 (In n) 2
(1.9)
-
0.103 In OP R2 = 0.97
(2.1)
SEE = 0.157
where r and n are indexes of real (Ppp-converted) and nominal
(exchange-rate-converted) GDP per capita, with the United States = 100;
OP (openness) is the sum of exports and imports divided by GDP. The
rationale for including n among the independent variables rests on the
earlier finding that price levels (PL) are positively correlated with r; this
implies that n, the product of PL and r, is positively associated with r.
The quadratic term picks up curvature in the relationship between n and
r. A high degree of openness tends to raise the prices of abundant
factors. In a low-income, labor-abundant country the result is likely to
raise the price of services, which tend to be labor-intensive, and thus to
raise the price level for GDP as a whole. With n held constant, a higher
price level means a lower real income.
In addition to estimates for nonbenchmark countries for the benchmark years, estimates are needed for nonbenchmark years. Although
annual repetition of benchmark surveys would be burdensome, different
components of the comparisons might be carried out at different times,
completing the cycle over, say, five years. However, benchmark studies
once every five years seem the most probable pattern. (Phase III was for
1975, phase IV for 1980, and phase V is being targeted for 1985.)
At first sight, the problem of filling in the between-benchmark years
seems simple. One has first to alter the benchmark year Ppp estimate by
the percentage change in a country's implicit deflator relative to that of
the numeraire country. If, for example, country A's Ppp was 10.0 pesos
per dollar in the benchmark year of 1980, and its implicit deflator rose
by 10 percent in 1981 while U.S. prices rose by 5 percent, the 1981 ppp
would be 10.0 x (1.10/1.05) = 10.48. The country's 1981 real per capita
income would then be obtained by dividing the new Ppr into the country's own-currency per capita GDP. However, closer inspection reveals
some drawbacks in this approach. Country A's increase of 10 percent in
prices is based on its own quantity weights, and the U.S. increase of 5
percent on U.S. weights. The relative change is applied to a 1980 Ppp for
country A based on yet another set of quantity weights. This disadvantage could be moderated by extending into the nonbenchmark years PPps
for individual components of GDP, not just GDP as a whole. Each Ppp
would be used to convert a particular component to the numeraire
18
Research Observer 1, no. 1 (January 1986)
currency and the results summedto get real per capita GDP. This has the
benefit of restricting domestic weights to within-category effects; the
aggregationof categoriescan be based on a common set of international
weights applied to all countries.
Several studies have applied these methods both to nonbenchmark
countries and nonbenchmark years. One study set out a basic approach
to a shortcut estimation method (KHS 1978b);another offered a refinement of the techniqueand provided annual estimates for 1950-80 (Summers and Heston 1984).Such efforts will have a firmer basis when the
phase IV comparisonsfor sixty countriesbecome available.
Despite the availabilityof these extrapolations from benchmark countries and years to nonbenchmark countries and years, widespread use
has continued to be made of exchange rate conversions. The use of the
exchangerate as a convertercan be justifiedonly on the ground that it is
the best approximation to the Ppp that is available. The question is then
whether exchange rate conversionsdo in fact come closer to benchmark
estimatesthan the shortcut estimatesbased on Ppp concepts.
Some newly available benchmark data for European and African
countries from phase IV (Ward 1985,SOEC 1985a)provide an opportunity to make some preliminary tests of this issue. Specifically,we can
match these new 1980benchmark figureswith the previous estimatesfor
1980 made on an exchange rate basis (see World Bank 1983)and with
the estimates of Summers and Heston (1984) derived from shortcut
methods. The new OECD phase IV estimatesof 1980 real GDP per capita
included five countries for which no previous benchmark studies had
been done.2 The OECD benchmark, World Bank, and shortcut estimates
Table 9. Estimates of Real GDP Per Capita, 1980
Absolute deviation
Country
OECD
benchmark
(1)
Shortcut'
(2)
World Bankb
(3)
Shortcut
minus
benchmark
(4)
Portugal
Greece
Finland
Norway
Canada
34.4
43.8
77.9
98.9
102.1
38
49
71
90
93
20
36
84
111
88
3.6
5.2
6.9
8.9
9.1
World Bank
minus
benchmark
(5)
14.4
7.8
6.1
12.1
14.1
a. The shortcut method (Summersand Heston 1984) was applied to obtain 1975 estimates for
these and other nonbenchmark countries. The estimates were then extrapolated to other years,
including1980 as shown here.
b. WorldBank (1983)estimates are for GNP.
Sources: Column 1: Ward(1985); column 2: Summersand Heston (1984); and column 3:
WorldBank(1983).
Irving B. Kravis
19
are listed in table 9. In four of the five new benchmark countries, the
shortcut method came closer to the benchmark estimate than the World
Bank's estimates based on exchange rate conversions.
Another comparison between World Bank and shortcut estimates is
possible for fifteen African countries for which 1980 benchmark estimates were recently published by the SOEC (1985a). These will eventually
be linked to the United States and other countries by the UNSO; at the
moment, the only official version is a within-Africa comparison. In
column 1 of table 10, the benchmark estimate of each country's real GDP
per capita is expressed as an index number based on the unweighted
average of the fifteen original indexes as 100. (The original indexes were
based on the weighted average of the real GDP of the fifteen countries;
the shift to unweighted averages is made here to facilitate comparisons
with World Bank and shortcut estimates.) Comparing columns 4 and 5,
showing the absolute deviations, it can be seen that in ten of the fifteen
cases the shortcut methods come closer to the benchmark results; their
Table 10. Comparison of Shortcut and World Bank Per
Capita GDPEstimates with Benchmark Estimates, Fifteen
Countries, 1980
Absolute deviations
Country
Ethiopia
Mali
Tanzania
Malawi,
Madagascar
Kenyaa
Senegal
Zambiaa
Nigeria
Zimbabwe
Cameroon
Morocco
Ivory Coast
Bostwana
Tunisia
Unweighted meanb
SOEC
benchmark
(1)
Shortcut
(2)
World Bank
(3)
Shortcut
minus
benchmark
(4)
33.5
39.0
42.6
48.0
66.2
74.3
79.8
85.2
104.2
104.2
106.0
139.6
159.5
185.8
232.0
100.0
38.1
27.6
54.3
37.5
60.2
49.8
75.7
77.1
171.6
103.6
103.3
137.4
163.5
186.2
214.1
100.0
21.7
30.1
45.2
31.8
58.5
65.2
70.2
97.0
145.5
130.4
122.1
138.8
185.6
157.2
210.7
100.0
4.6
11.4
11.7
10.5
6.0
24.5
4.1
8.1
67.4
0.6
2.7
2.2
4.0
0.4
17.9
-
World Bank
minus
benchmark
(5)
11.8
8.9
2.6
16.2
7.7
9.1
9.6
11.8
41.3
26.2
16.1
0.8
26.1
38.6
21.3
-
a. 1975 benchmark estimates, which were available for these countries, extrapolated to 1980
by Summers and Heston (1984).
b. The unweighted mean of the original estimates has been taken as 100 as a normalizing
device for columns 1 to 3.
Sources: Column 1: SOEC(1985a); column 2: Summers and Heston (1984); and column 3:
World Bank (1983).
20
Research Observer 1, no. 1 (January 1986)
J
;
average absolute deviation is nearly 30 percent less than that of the
World Bank estimates. The superiority of shortcut methods over exchange conversions is the more notable because all the fifteen countries
had low incomes; Tunisia, the richest country in the set, has a real GDP
per capita roughly one-fifth that of the United States.
Even if shortcut methods were used to complete the IcP's coverage, an
important gap in our ability to compare economic structures would
remain. The system of comparisons that has been developed is based on
a final expenditure breakdown of GDP, because that was the easier approach. However, much valuable information about the structure of the
world economy-for example, the comparative productivity of given
industries in different countries-requires comparisons of GDP by industry of origin. This work, begun by Paige and Bombach (1959), needs to
be picked up again. It also requires careful price comparisons-which
are more demanding, for an equal degree of disaggregation, than those
of the final expenditure approach. There is little justification for the
bland assumption that goods with the same name are of equal quality in
different countries. Rice, for example, seems like a simple product whose
price can easily be compared. But rice comes in numerous varieties
which dominate different national markets. And the average bag of rice
in a low-income country is likely to contain more impurities and broken
kernels than in a rich country. International comparisons of quantities
that ignore quality differences can be far off the mark.
Although the icP reports have been favorably reviewed in the professional journals (Hill 1976; Isard 1983), they have also provoked doubts
that the real-income gap between rich and poor countries is really reduced by so much. One objection has been to the use of world average
prices to value the components of the countries' GDPS (Isenman 1980); it
is claimed that world average prices are dominated by the large weights
of the rich countries. The Gerschenkron effect thus comes into operation; price weights that are very different from those of the low-income
countries push up their relative quantity indexes. While this argument is
valid in principle, empirical investigation shows that its quantitative
importance is small (Kravis 1984). For example, dividing the weights
equally between the set of poor countries and the set of rich ones lowers
the estimate of real per capita GDP for the eight lowest-income countries
(class 1) in phase III by between 9 and 13 percent. This difference is
much smaller than the one between the exchange-rate-converted GDP and
almost any reasonably devised PPp-type estimate. (The phase III report
put the average ERDI for the eight lowest-income countries at 2.6.) As
this suggests, the narrowing of the income gap between poor and rich
countries depends more on using a common set of average prices to
value the components of the different countries' GDPS than on which
Irving B. Kravis
What
Has Been
Questioned
21
particular set is chosen. For example, applying Indian prices in a 1975
binary comparison with the United States yields an India/United States
index of 4.1, twice the exchange-rate-converted
index of 2.03.
Another area of icP methods that has been questioned is the treatment
of services. Most services, such as haircuts and telephone calls, can be
compared in price. But some, like the services of teachers and government employees, are "comparison resistant"; they are in a sense "unpriceable," having no readily identifiable unit of output which can be
priced. In the national accounts of individual countries, price and quantity changes of such services are tracked over time in terms of their
inputs. The icP comparisons used the same approach over space. Phase
III tried to correct for international differences in productivity of the
providers of the services-that
is, for medical personnel, and teachers
(KHS 1982, chap. 5). Some allowances were also made for the use of
capital inputs. These corrections to the raw quantity data were based on
a careful sifting of the available evidence, but they cannot claim to be
solid.
Perhaps the most explicit challenge to the icP treatment of services is
that of Maddison (1983). His estimates of 1965 real GDP per capita for
ten developing countries are on average almost one-third less than the
1965 estimates extrapolated from icP results for 1975. Maddison says
that the "most important" source of the difference is the treatment of
services, but he does not offer any other explanation.
Maddison's statistical procedures raise serious doubts. His estimates,
based on a breakdown of GDP by industry of origin, utilized only secondary sources and were made without the benefit of careful price comparisons. Maddison focuses his criticisms on icp treatment of comparison
resistant services and on what he calls "disguised services." For the
former, he simply assumes that their productivity in different countries
varies from one-quarter to three-quarters of the U.S. level, depending on
productivity differentials in industry (Maddison 1970, p. 292). He offers
no justification for this assumption. Even if Maddison's productivity
ratios were correct, however, the change in the phase III results would be
small. As Maddison recognizes, comparison resistant services accounted
for only 10 percent of the GDP of most low-income countries; so if their
true productivity were one-third or one-half of the iCP estimate, the
estimate of real per capita GDP would be 5 to 7 percent smaller-tiny
compared with the difference between exchange rate and Ppp conversions.
Maddison ascribes greater importance to "disguised services," which
he defines as the difference between the service industry share in GDP and
the share of final product services in GDP. Substantively, Maddison seems
to have in mind distributive services. He criticises the icP for failing to
adjust for a larger amount of distributive service per unit of consumption in the rich countries, which would therefore lead to an overstate22
Research Observer 1, no. 1 (January 1986)
ment of the relative real income of developing countries. Again, the
figures suggest that the Maddison criticism is exaggerated. The share of
distributive services in total services is probably in the 15 to 18 percent
range for developing countries and below 15 percent for the developed
countries.3 The true value of distributive services would have to be
massively understated in order to swell the 15 percent by enough to raise
real per capita incomes in rich countries and thereby significantly widen
the spread between poor and rich countries.4
It is in any case doubtful that services alone can account for the bulk
of the differences between the Maddison and phase III estimates. Services constitute a little under one-third of the real income of developing
countries. For all of the difference between Maddison and icp estimates
to be due to an icP exaggeration of service consumption in poor countries, the absorption of services in low-income countries would need to
be zero. The icP results show that poor and rich countries divide their
income between goods and services in roughly the same proportions.
Critics who claim the icp estimates for service consumption in poor
countries are too high are suggesting some perverse economic behavior.
They imply that people in poor countries where goods are dear consume
lots of them, while they buy only small amounts of relatively cheap
services. People in rich countries also behave perversely, buying expensive services and economizing on cheap goods. The constant real share
of the icP (column 2 in table 8) seems much more plausible. It may be
added that the set of IcP outputs-prices,
quantities, and real incomesperformed well econometrically, when fitted both to simple demand
functions and to a complete demand system (KHS 1982, chap. 9).
There is little doubt that purchasing power parities are the right way
to convert GDP and its components from domestic currencies to dollars
(the usual numeraire). Using standard exchange rates as converters produces biased results, because exchange rates systematically understate
the purchasing power of the currencies of low-income countries. These
points are now well understood and accepted. Nonetheless, exchange
rates continue to be widely used as converters. One reason given for not
using PPPs is that the icp has unresolved methodological problems. In
fact, methodological improvements can and doubtless will be made, but
the indexes of real per capita GDP are little changed by the use of
alternative methods. In the European Community Ppp conversions, produced by the methods described above, are being used for policy purposes. Furthermore, it is not enough to claim that there are errors and
uncertainties in the Ppp conversions to reject them in favor of exchange
rate conversions; one has to ensure that exchange rates are better approximations to PPPs than are produced by the icP.
Irving B. Kravis
Concluding
Comments
23
A second objection, that PPls were available for only a limited number
of countries, will lose some of its force when the UNSO publishes benchmark comparisons for sixty countries later this year. More important,
shortcut methods could be used to estimate Ppp figures for nonbenchmark countries. They are a better guide to real GDP per capita than
figures obtained from exchange rate conversions. In addition, if benchmark studies can be repeated at five-year intervals, estimates for years
between the benchmarks can be obtained by extrapolation. The world
statistical system could therefore produce an annual set of estimates of
real GDP per capita for all the countries of the world.
Abstract
Purchasing power parities (PPPs),this article confirms, are the correct converters for
translating GDP and its components from own-currencies to dollars (the usual numeraire);
the alternative measure, exchange rates, obscures the relationship between the quantity
aggregates of different countries. Drawing on the reports of the United Nations International Comparison Project (IcP), the article contends that exchange rates systematically
understate the purchasing power of the currencies of low-income countries and thus
exaggerate the dispersion of national per capita incomes. Where full-scale (benchmark) ppi
estimates are not available, estimates based on shortcut methods better approximate what
the benchmark estimates would be than do the exchange rate conversions. The icP results
also illuminate price and exchange rate relationships among countries by providing a
measure of the difference in the levels of prices in different countries. iCP price comparisons
for components of GDP make possible the analysis of comparative price and quantity
structures of different countries and provide the raw materials for many types of analytical
studies.
Notes
1. The first three phases of the icP are reported in Kravis, Kenessey, Heston, and
Summers 1975; Kravis, Heston, and Summers 1978a; and Kravis, Heston, and Summers
1982 (hereafter, KKHS and KHS). A report on phase IV is expected from the United Nations
Statistical Office late in 1985.
2. They included thirteen other countries for which 1975 benchmarks were available
from phase III. For these countries Summers and Heston had only to update from 1975 to
1980; they did not have to use shortcut methods.
3. Based on data for Brazil, Colombia, India, Korea, Mexico, Pakistan, Philippines,
Spain, and Thailand; and for France, Germany, Italy, Japan, and the United Kingdom
(United Nations 1984).
4. It is not clear whether Maddison considers that nondistributive services are also
"disguised." In fact, they enter into the final product comparisons in appropriate ways.
Some, such as government employee compensation, are also final products and enter
directly. Others, such as financial services, enter into the prices of goods and services and
are captured in the price comparisons.
References
Beckerman, Wilfred. 1966. International Comparisons of Real Income. Paris: Organisation
for Economic Co-operation and Development (OECD)Development Center.
Bhagwati, Jagdish N. 1984. "Why Are Services Cheaper in the Poor Countries?" Economic
Journal 94 (June): 279-86.
Board of Trade. 1908a. Report on an Enquiry by the Board of Trade into Working Class
Rents, Housing and Retail Prices Together with the Rates of Wages in Certain Occupations
24
Research Observer 1, no. 1 (January 1986)
in the Principal Industrial Towns of the United Kingdom. Cd. 3864. London: Printed for
H.M. Stationery Office by Darling & Son.
1908b. German Towns. Cd. 4032.
_.___
__
._1909.French Towns. Cd. 4512.
1910. Towns of Belgium. Cd. 5065.
____.*
. 1911. American Towns. Cd. 5609.
Braithwaite, Stanley N. 1968. "Real Income Levels in Latin America." Review of Income and
Wealth 14, no. 2 (June): 113-82.
Clark, Colin. 1940. The Conditions of Economic Progress. London: Macmillan.
Economic Commission for Europe. 1980. Economic Bulletin for Europe 31 (2).
Gilbert, Milton, and Irving B. Kravis. 1954. An International Comparison of National
Products and the Purchasing Power of Currencies: A Study of the United States, the United
Kingdom, France, Germany, and Italy. Paris: Organisation for European Economic
Cooperation (OEEC).
Gilbert, Milton, and associates. 1958. Comparative National Products and Price Levels. Paris:
OEEC.
Hill, T. P. 1976. "Review of A System of International Comparisons." Economic Journal
(March): 16144.
IMF (International Monetary Fund). 1984a. International Financial Statistics 37, no. 7(July).
. 1984b. Yearbook of International Financial Statistics. Washington, D.C.
11985.International Financial Statistics 38, no. 7(July).
Isard, Peter. 1983. "Review of A System of International Comparisons." Journal of International Economics 15 (August): 177-81.
Isenman, Paul. 1980. "Inter-Country Comparison of 'Real' (Ppp)Incomes: Revised Estimates
and Unresolved Questions." World Development 8, no. 1 (January): 61-72.
King, Gregory. 1936. Two Tracts. George C. Barnett, ed. Baltimore, Md.: Johns Hopkins
University Press.
Kravis, Irving B. 1984. "Comparative Studies of National Incomes and Prices." Journal of
Economic Literature 22 (March): 1-39.
Kravis, Irving B., Alan W. Heston, and Robert Summers. 1978a. International Comparisons
of Real Product and Purchasing Power. Baltimore, Md.: Johns Hopkins University Press.
-____1978b. "Real GDP Per Capita for More than One Hundred Countries-" Economic
journal 88, no. 350 (June): 215-42.
-_____
1982. World Product and Income: International Comparisons of Real Gross Product.
Baltimore, Md.: Johns Hopkins University Press.
Kravis, Irving B., Zoltan Kenessey, Alan W. Heston, and Robert Summers. 1975. A System
of International Comparisons of Gross Product and Purchasing Power. Baltimore, Md.:
Johns Hopkins University Press.
Kravis, Irving B., and Robert E. Lipsey. 1983. Towards an Explanation of National Price
Levels. Special Studies in International Finance no. 52. Princeton, N.J.: Princeton University Press.
- Forthcoming. "The Assessment of National Price Levels." In S. Arndt and D.
Richardson, eds. Real-Financial Linkages in Open Economies. Washington, D.C.: American Enterprise Institute.
Maddison, Angus. 1970. Economic Progress and Policy in Developing Countries. New York:
Norton.
-____1983. "A Comparison of the Levels of GDP Per Capita in Developed and Developing
Countries, 1790-1980." Journal of Economic History (March): 27-41.
Irving B. Kravis
25
Paige, Deborah, and Gottfried Bombach. 1959. A Comparison of National Output and
Productivity in the United Kingdom and the United States. Paris: OEEC.
Salazar-Carrillo, Jorge. 1973. "Price, Purchasing Power and Real Product Comparisons in
Latin America." Review of Income and Wealth 19, no. 1 (March): 117-32.
(Statistical Office of the European Community). 1983. Comparisons in Real Values of
the Aggregates of ESA, 1980. Luxembourg: European Economic Communities (EEC).
SOEC
-_____.1985a. Comparison
of Price Levels and Economic
African Countries. Luxembourg:
Aggregates:
The Results for
EEC.
. 1985b. Comparison of National Accounts Aggregates between Israel and the
European Community. Luxembourg: EEC.
Summers, Robert. 1973. "International Comparisons Based upon Incomplete Data." Review
of Income and Wealth 19, no. 1 (March): 1-16.
Summers, Robert, and Alan W. Heston. 1984. "Improved International Comparisons of Real
Product and Its Composition: 1950-80." Review of Income and Wealth 30, no. 2 (June):
207-62.
United Nations. 1968. A System of National Accounts. Studies in Methods, ser. F, no. 2, rev.
3. New York: United Natons Statistical Office.
United Nations, Economic and Social Council, Statistical Commission and Economic
Commission for Europe, Conference of European Statisticians. Summary of the Results of
the European Comparison Programme CES/S14 (May). New York.
Ward, Michael. 1985. Purchasing Power Parities and Real Expenditures in the OECD. Paris:
OECD.
World Bank. 1983. 1983 World Bank Atlas. Washington, D.C.
26
Research Observer 1, no. 1 (January 1986)
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