Review of Income and Wealth
Series 35, Number 1, March 1989

INTERNATIONAL COMPARISON O F PURCHASING POWER, REALOUTPUT AND LABOUR PRODUCTIVITY: A CASE STUDY O FBRAZILIAN, MEXICAN AND U.S. MANUFACTURING, 1975

This study has a twofold objective: (a) a substantive analysis of purchasing power parities (PPP's),
real output and labour productivity in Brazil, Mexico and the U.S.A.; and (b) a methodologicalsurvey of the analytic problems in measuring PPP's from the production side, rather than the
expenditure approach used by the United Nations (ICP). Our main substantive findings were that
PPP's for manufacturing did not vary greatly from the 1975 exchange rates, that labour productivity
was surprisingly high in the two Latin American countries, and that there are substantial differencesin the coverage of national accounts between Mexico and Brazil. We found census concepts of value
added to be rather anachronistic, particularly in the U.S.A.; we developed a new short-cut matchingprocedure for industries with a complex product structure; and we found the unit value approach
not inferior to the specification pricing practiced by ICP.

The most direct way of comparing levels of output in different countries is
to use the official exchange rate to convert G D P in one country's prices into theprices of another country, and, in multicountry comparisons, to use some key
currency, such as the U.S. dollar, as a numiraire. However, exchange rates do
not indicate the average purchasing power of currencies over all goods andservices, but mainly reflect their purchasing power over tradeables. Furthermore
exchange rates are subject to fluctuation, and capital movements play a majorrole in determining their level, so even for tradeables, they could be substantiallymisleading as indicators of purchasing power. Hence measurement of real output
across countries is closely intertwined with the assessment of purchasing power.
Research on purchasing power parities (PPP's) has been under way for overthree decades in international agencies concerned with burden sharing or withthe relative need for aid. Hence the early work of OEEC (1954, 1958, 1959) for
Western countries, of Gosplan (1965) for the CMEA countries, and ECLA (1963)

Note: University of Groningen (The Netherlands). The authors are grateful to Harry van
Ooststroom and Paul Wieringa who helped launch the investigation, and to Aerdt Houben, Dirk
Pilat, and Eddy Szirmai who helped in the end phase. We had extensive and very helpful discussions
with Derek Blades. For help in interpreting and gathering data for particular countries, the authors
are grateful to Jerome Mark, Arthur Neef, Robert Parker, Angelo de Souza, Thomas Tibbetts, Victor
Urquidi, Maria Alice Gusmao Veloso, Gaylord Worden and Ralph Zerkowsky. Userul comments
were also received from Sultan Ahmad, Robert Ballance, Jean Baneth, Stephen Davies, Laszlo
Drechsler, Arun Ghosh, Alan Meston, Irving Kravis, Hugo Krijnse Locker, Valentin Kudrov, Jagdish
Kumar, Arabinda Kundu, Jaroslav Kux, Kees van der Meer, Jan Pen, Sigbert Prais, Anthony Smith,Robert Summers and Michael Ward. We are also grateful to the World Bank both for intellectual
cooperation, and for meeting some of our research expenses, particularly those for travel andtranslation.

for Latin America. This kind of measure is also useful in analysing military or
geopolitical potential: see the CIA studies of Block (1981) and Schroeder and
Edwards (1981); and U.S. Congress Joint Economic Committee studies (1981)
and (1982) on Eastern Europe and the U.S.S.R.
Most of the above studies develop PPP's for final demand components(consumption, investment, etc.) The largest and most sustained scholarly effort
using this "expenditure approach" was the International Comparisons Project(ICP) of the United Nations. The results of the first four phases are publishedin Kravis, Kenessey, Heston and Summers (1975), Kravis, Heston and Summers(1978) and (1982), and UN (1986). ICP methods are now used on a regional
basis by Eurostat (1983) and OECD (Ward, 1985).
The expenditure approach is useful for analysis of macreconomic performance, but cannot be directly used for sectoral analysis since it does not show real
product by industry. This handicaps comparative structural analysis, work on
labour or total factor productivity, growth accounting, and studies of technological performance. This latter group of problems is better illuminated by thealternative "industry of origin" approach which we use here.
This study has a twofold objective:(a) substantive analysis of manufacturing output levels, purchasing power
parities, and labour productivity in Brazil, Mexico and the U.S.A.;(b) a methodological survey of the analytical problems inherent in such an
exercise for any group of countries, in order to facilitate the task of
researchers who may wish to replicate our approach.
The present study is part of a series of comparative industry of origin
investigations in which we and our colleagues have been engaged. Houben (1988)
covers the mining sector in Brazil, Mexico and the U.S.A. Comparisons for the
manufacturing sectors for 1ndialU.S.A. (Van Ark, 1987) and Brazil1U.K. (VanArk, 1988) are available, and others are underway for Japan, Korea, France and
The Netherlands. A fourteen country comparison is available for agriculture by
Van Ooststroom and Maddison (1985). The 1975 benchmark was chosen to
facilitate comparison with the third phase of the ICP. The basic source is censusesof manufacturing which provide quantitative indicators of output levels in considerable detail as well as information on employment, gross output, value added,
and inputs at national prices.

Some economists have manipulated real expenditure PPP's to produce proxyestimates of real output levels by sector (see Table 1). Thus Simon Kuznets (1972)used OEEC and ECLA real expenditure studies to derive estimates of real output
for agriculture and industry. Jones (1976) used Kravis, Kenessey, Heston andSummers (1975) expenditure PPP's to estimate manufacturing output levels,
A. D. Roy (1982) used the same procedure with Kravis, Heston and Summers(1978), and Prais (1981) followed a more detailed procedure, using about halfof the expenditure items listed in Kravis, Kenessey, Heston and Summers (1975)
to derive a weighted average PPP for manufacturing. Klodt (1984), Jorgenson,

TABLE 1
O F REAL OUTPUT LEVELSI N MANUFACTURING
USING ANALOGOUS
PROXY COMPARISONSICP EXPENDITURECOMPONENTS
Kuznets (1972)
Jones (1976)
Prais (1981)
Roy, A. D. (1982)
Klodt (1984)
Guinchard (1984)

Jorgenson, Kuroda andNishimizu (1986)
Roy, D. J. (1987)

Used reweighted OEEC and ECLA expenditure PPP's to estimate
sector PPP's for large groups of countries.
Used reweighted Kravis, Kenessey, Heston and Summers (1975)
expenditure PPP's to derive sector PPP's.
Used reweighted Kravis, Kenessey, Heston and Summers (1975)
expenditure PPP's to derive PPP's for 10 manufacturingindustries in Germany, U.K. and U.S.A.
Used reweighted Kravis, Heston and Summers (1978) expenditure
PPP's to derive sector PPP's.
Applied Kravis, Heston and Summers (1978) PPP's to 16 branchesof manufacturing for Germany, Japan and U.S.A., 1960, 1970
and 1978.
Uses Kravis, Heston and Summers (1982) expenditure PPP's (withadjustment for taxes and trade margins) to derive PPP's for somebranches of manufacturing. For intermediate products he usedthe exchange rate.
Applied "remapped" Kravis et al. (1975, 1978) PPP's to estimate
productivity differentials in Japan and U.S.A. (1960-79).
Used reweighted expenditure PPP's from ICP IV, derived from atape provided by UNSO, for 60 countries for 1980.

Sources: See bibliographic references.

Kuroda and Nishimizu (1986), and D. J. Roy (1987) are the latest in thistradition.
Procedures of this type need to be crosschecked with independent estimates by industry of origin such as we present here. Until this is done for areasonable sample of countries, one must be sceptical about the value of suchproxies.
The initial impetus to "industry of origin" comparisons was given by Rostas(1948). The studies of Maddison (1952), Galenson (1955), Frankel (1957) andYukizawa (1978) replicated his method for measuring real output, which concentrated on comparisons of "physical" gross output of different countries. The mostambitious studies in terms of sample size were those of Paige and Bombach(1959), Kudrov (1969), West (1971), Smith, Hitchens and Davies (1982), andSmith (1985). Table 2 shows their coverage so far as we could determine. Anotherindicator of the adequacy of their sample is the number of items matched. On
the latter criterion, our study is amongst the most comprehensive. Some of thestudies cited used a mixed methodology, in the sense that they combined independently determined PPP's by industry of origin with some proxy PPP's derived
from expenditure studies. This was true of Paige and Bombach, and to smaller
extent also of Smith, Hitchens and Davies (1982) and Smith (1985). In our study
we kept strictly to the industry of origin approach, without using proxy PPP's.
It should be noted that Table 2 is not exhaustive. See also Heath (1957), Maizels(1958), Frank (1977), Davies and Caves (1987), van Ark (1988), Szirmai and
Pilat (1989), as well as the short-cut approach of Shinohara (1966) and Maddison(1970).

3. COMPARISONS
OF PURCHASING
POWER,REAL OUTPUTA N D LABOUR
FOR BRAZIL/
USA A N D MEXICO/USA
PRODUCTIVITY

Our analysis covered 17 industries, which were assumed to be representative
for total manufacturing. The sample accounted for about 40 percent of grossvalue of output in Brazil and Mexico, and almost 28 percent in the U.S.A.
TABLE 213 STUDIESO F REALOUTPUTLEVELSI N MANUFACTURING

AuthorNumber of
Products
SampledSize of Sample

Country
Coverage

Reference
Years-

Rostas (1948)

108

Maddison (1952)

34

Galenson (1955)23

Frankel (1957)

5ob

Paige and Bombach(1959)

380

Mensink (1966)

78

Kudrov (1969)

224'

Czech Statistical
Office/INSEE(1969)
West (1971)

113

150b

Yukizawa (1978)60

Smith, Hitchens
and Davies (1982)
Smith (1985)

487'"
350
386"

Maddisonand Van Ark(present study)

171-372
192-342200-157

22 percent of 1937 U.S.
employment
15 percent of Canadian,
14 per-cent of U.K.,
and 8 percent of U S .
employment in 1935
17 per cent of U.S.
industrial gross outpul
in 1939"
18 percent of 1947 U.S.
employment, 16
percent of U.K. 1948
employment
51 percent of U.K., and48 percent of U.S.
manufacturing value
added
14 percent of U.K. 1958
employment
substantial, but notstatedsubstantial, but notstated31 percentd of U.S.
shipments
26 percent of Japaneseand 24 percent of U.S.
value added in 1972
substantial, but notstated55 percent of U.K. value
a'dded and 53 percent
of U.S. value added
33 percent of value
added in Brazil, 39
percent in Mexico, 20
percent in U.S.A

U.K.1U.S.A.

1935 to 1939

CanadalU.K.1
U.S.A.

Czechslovakia/
France1962 and1967
1963
195819, 1963
1967, 1972

U.K./ U.S.A.
Germany1U.K.
U.K./U.S.A.

196817
1967181977"Galenson includes three mining industries (coal, iron ore, oil and natural gas).
'1n the absence of information from the authors, these are rough estimates.
'Information supplied by the authors.
d ~ e sdoestnot say how his sample is, but we derived this figure by comparing the large industry
codes he uses (pp. 59-61) with 1963 information in the General Summary volume of the 1977 Census
of Manufactures.
'Refers to number of "matches" instead of number of matched products

The basic procedure involved weighting physical output of individual commodities by a common set of price weights. These "prices" were unit values
derived from production censuses' by dividing gross value of output by corresponding quantities. Two sets of binary comparisons were made, i.e. Brazil/U.S.A.
and M ~ X ~ C O / U . S Each
. A . ~ involved (a) unit value weights of country X (Brazil
or Mexico) to compare gross volume of output of that country with that in the
United States:and each (b) used the unit value weights of the U.S.A. to derive a quantity ratio
between country X and the United States as follows:with Q, = quantity of product y, P, =unit value of product y, X = country X.
U = United States.
It is usually not possible to make these quantitative comparisons for all
products of an industry, because:(a) one cannot match each product with a corresponding one in the U.S.
Census;(b) some products are only specified by value and not by quantity.
In the Brazil/U.S.A. comparison 171 Brazilian product items and 372 U.S.
product items were matched; and in the Mexico/U.S.A. comparison 192 Mexican
product items and 342 U.S. product items were matched. Table 3 shows the ratiosof covered output to total gross value of output for each of the 17 industries. In
only two cases, i.e. the Brazilian motor vehicle industry and petroleum refining
industry, was the coverage below 40 percent-becauseof the unusually large
amount of "non-specified" output. On average the sample coverage ratios were
between 58 and 73 percent.
Thzre are two alternative procedures to move from the "covered output"
comparison to one for the industry as a whole. It can be assumed that the quantity
relationship between matched output in country X and country U applies to theindustry as a whole, or that the price (unit value) relationship for covered output
is representative for the entire industry. These two alternatives have been extensively discussed in the literature on measurement of production trends since Mills
first raised the issue (Mills, 1932). Burns (1934, pp. 260-261) stressed that pricesof different commodities are likely to be under the general influence of "common
monetary factors", whereas there is no such "single dominant force acting
pervasively" on quantitative movements for different commodities. Fabricant(1940) also preferred price indicators because "prices probably move together
within closer limits than do quantities." Stone (1956) stated that completenessof coverage is of less importance with price indicators compared to quantity'For an extensive discussion of the scope of the production censuses in Brazil, Mexico and the
U.S.A. see Maddison and Van Ark (1987).
*1n fact we also made a binary comparison of Brazil/Mexico, which is not shown here.

TABLE 3

Brazil/U.S.A.
Brazil(1975)U.S.A.
(1977)

Mexico/U.S.A.
Mexico(1975)U.S.A.
(1977)

Grain Mill Products
Sugar and Sugar Products
Malt and Malt Beverages
Tobacco and Tobacco Products
TextilesFootwear and Leather Products
Pulp and Paper
Soap and Detergents
PaintsAgricultural Fertilizers
Petroleum Refining and Products
Tires and Inner Tubes
CementBricksIron and SteelRadio and TV Receivers
Motor Vehicles
Weighted Average 17 industries
Note: For details on matching for individual industries see "Statistical Appendix" to our original,much larger, research report (Maddison and Van Ark, 1987).

indicators, because "prices charged for close substitutes by different firms or indifferent parts of a country are likely, in many cases, to show similar movementseven if their absolute level is a little different." We agree with the statements
above. Therefore our coverage adjustments are entirely based on the priceindicator method.
As a result the price ratios (or PPP's) for an industry as a whole were assumed
to be similar to the derived PPP's for the covered part of output. PPP's were
either weighted by quantities of the United States, i.e.

or by quantity weights of country X:

with "c" indicating covered output
PPPX = purchasing power parity using quantity weights of country X
PPP" =purchasing power parity using quantity weights of the U.S.A.

Table 4 presents the 1975 PPP estimates in terms of the number of currency
units of country X to the U.S. dollar for the 17 individual industries and comparesTABLE 4
PURCHASING
POWERPARITIES,BRAZIL/U.S.A.(CRUZEIROSTOTHE
U.S.$) A N D MEXICO/U.S.A.
(PESOS TO THE U.S.$), 1975
PPP: Cruzeiros/U.S. $U.S.
Quantity
Weights(1)

BrazilQuantity
Weights(2)

Geometric
Average(3)

PPP: Pesos/U.S. $U.S.
Quantity
Weights(4)

MexicoQuantity
Weights(5)

Geometric
Average(6)

Grain Mill Products
Sugar and Sugar Products
Malt and Malt Beverages
Tobacco and Tobacco
Products
TextilesFootwear and Leather
Products
Pulp and Paper
Soap and Detergents
PaintsAgricultural Fertilizers
Petroleum Refining and
Products
Tires and Inner Tubes
CementBricksIron and SteelRadio and TV Receivers
Motor Vehicles
Exchange Rates
Source and note: Includes adjustments for indirect taxes and subsidies for malt and malt beverages
tobacco and tobacco products and petroleum refining and products in the Mexico-U comparison,and for quality differences in the motor vehicles industry in both country comparisons.

them with the official 1975 exchange rates, i.e. 8.13 cruzeiros to the U.S. dollar
and 12.5 Mexican pesos to the U.S. dollar.
Thus the PPP's in the first and fourth columns of Table 4 are weighted by
U.S. quantities, and those in the second and fifth columns by the quantities ofeach of the Latin American countries. Geometric averages (Fisher indices) of
the two PPP's are also presented in the third and sixth columns. In theBrazil1U.S.A. comparison 31 of the 51 PPP's were below the exchange rate, andin the Mexico/U.S.A. comparison 27 of the 51 PPP's.~
Corresponding quantity relatives can be derived by applying the PPP's of
Table 4 to the gross value of output at national prices, because price and quantity
relatives are complementary to each other. The value ratio between country X
and base country U is divided by a Laspeyres price ratio, i.e. using quantity
3 ~thist stage the 1977 U.S. census figures were adjusted to a 1975 basis. Volume adjustment
were derived from the 1982 Industrial Outlook, in which gross value of output is shown at constant1972 U.S.$ for separate product groups. These ratios were applied to the 1977 U.S. census gross valueof output. The resulting 1975 figures at 1977 prices were compared with the product group figuresfor 1975 at 1975 prices derived from the Annual Survey of Manufactures 1975-1976 (ASM). From
this latter comparison we derived our unit value indices for 1975 relative to 1977.

weights of the base country (see formula (2a)). Thus the derived quantity ratio
is of the Paasche type, i.e. using unit value weights of country X (see formula la):The same is true for a combination of a Paasche price index and a Laspeyres
quantity index, i.e.:

Thus far the procedure described relates to gross value of output, but inorder to avoid double-counting in aggregating the individual industry results, wemust move on to derive quantity relatives for value added. The best way to do
this would be to make separate comparison of outputs and inputs (so-called"double deflation"). Unfortunately, the production censuses do not give figures
for individual inputs at the product level, so we had to tackle the problem bymaking a proportionate adjustment at national prices of the ratio of gross output
to value added.
It would be desirable to adjust the value added concept used in the censuses
to a national accounts basis. The "national accounts" concept of value added
avoids all duplication, because it deducts all inputs. The Brazilian and Mexican
censuses provide enough detailed information to reconcile census value added
to a national accounts basis, but this was not possible for the U.S.A.
In the detailed value added comparisons for the 17 industries, we were
therefore obliged to adjust the value added specifications in the three production
censuses to a common basis using the "U.S. census concept" of value added.
According to this concept only inputs directly related to the production process(i.e. raw materials, energy consumption, and packing expenses) are deductedfrom gross o u t p ~ t . ~Table 5 shows Brazilian and Mexican value added ("U.S. census concept")
converted to U.S. dollars at the official exchange rate, compared with the 1975
U.S. figures for value added derived from Annual Survey of Manufactures. Tables
6 and 7 show the results of applying the PPP's from Table 4 to the figures ofvalue added in order to convert them to a common currency unit for theBrazil/U.S.A. and Mexico/U.S.A. comparison respectively. The first two columns
show the results of the calculations in Brazilian and Mexican unit values respectively, and the fourth and fifth columns show value added at U.S. unit values.
The third and last columns show the ratios of value added in Brazil and Mexico
to the U.S.A.

4 ~ other estimates at branch level and manufacturing as a whole we were able to use the "former
national accounts" concept of value added, which is completely free of duplication. The "former"
concept is preferred, because it deducts inputs of financial services at the branch level, whereas thisparticular input is usually deducted on a global basis for the economy as a whole in present national
accounting practice.

TABLE 5
VALUE ADDED (U.S. CENSUS CONCEPT) I N BRAZIL,MEXICO A N D T H E U.S.A. I N 1975, AT
OFFICIALEXCHANGERATES (1975 U S . DOLLARS)
Brazil(milliondollars)

Mexico(milliondollars)

U.S.A.
(milliondollars)

Total Manufacturing Value Added
Grain Mill Products
Sugar and Sugar Products
Malt and Malt Beverages
Tobacco and Tobacco Products
TextilesFootwear and Leather Products
Pulp and Paper
Soap and Detergents
PaintsAgricultural Fertilizers
Petroleum Refining and Products
Tires and Inner Tubes
CementBricksIron and SteelRadio and TV Receivers
Motor Vehicles
Total in our sample
as % of Total Manufacturing

Source: Figures for Brazil from Censo Industrial, figures for Mexico from Resumen General(except for figures mentioned under footnotes (a) and (b)), and figures for U.S.A. from the Annual
Survey of Manufactures 1975-1976.
Note: Figures are converted at the exchange rate of 8.13 cruzeiros to the U.S. dollar and 12.5
pesos to the U.S. dollar.
"Indirect taxes and subsidies are deducted (see Table 2.3).
bIncludes 571.8 million U.S. dollars (excl. indirect taxes and subsidies) for petroleum refining,
not shown in the census, but taken from Sistema de Cuentas Nacionales de Mexico.

Previous investigators have followed different options in order to blow up theirsample for manufacturing as a whole. Rostas (1948), Maddison (1952), Galenson(1955), Frankel (1957), Mensink (1966), and Yukizawa (1978) simply assumed
that their sample results were representative for manufacturing as a whole (either
explicitly or implicitly). They gave the overall result in terms of labour productivity, not output or PPP's. Sometimes, as with Rostas and Yukizawa, the sample
aggregate result was derived by using labour weights.
Three studies explicitly discuss the aggregation problem in all three
dimensions (output, PPP's and labour productivity), i.e. Paige and Bombach(1959), the Czech Statistical Office/INSEE (1969) and West (1971), but theyeach followed different methods.

TABLE 6
QUANTITIES(VALUE ADDED,US. CENSUSCONCEPT),BRAZIL/U.S.A., 1975
At Brazilian "Prices"
UXA.
Brazil1975
1975(1975 Cr. million)

At U.S. "Prices"
BrazilUXA.
( %BrazilU.S.A.
1975
1975(1975 US.$ million)

BrazilU.S.A.
(Yo)

Grain Mill Products
Sugar and Sugar
Products
Malt and Malt
Beverages
Tobacco and Tobacco
Products
TextilesFootwear and Leather
Products
Pulp and Paper
Soap and Detergents
PaintsAgricultural Fertilizers
Petroleum Refining and
Products
Tires and Inner Tubes
CementBricksIron and SteelRadio and TV Receivers
Motor Vehicles
Total in our sample
Note: Includes adjustment for quality differences in the motor vehicles industry.

Paige and Bombach covered about half of output in their two countries, i.e.
the U.K. and the U.S.A., and their average result is very similar to that for theirsample, as they predominantly assumed their quantitative relationships to be
representative (see p. 102). They got their total for manufacturing by blowing up
the industries they covered to represent the situation by major branch (using
quantity relationships of their sample in 59 percent of cases, PPP relatives for
19 percent, other price information for 10 percent, and employment for 12
percent).
West did not make estimates by major branch, but assumed the average PPP
for his sample (with value added weights) was representative for the non-sampledindustries, using the sample average PPP to derive real output in the non-covered
sector (see p. 26). His overall labour productivity result was significantly lower
than that for his sample.
The authors of the Czech-French study used an unweighted average of theirsample PPP's (by branch) to get a PPP for each branch, with output derived forthe branch by applying this PPP to calculate branch value added in real terms.
Their manufacturing total was derived by summing branch totals. A similar
procedure was used by Smith, Hitchens and Davies (1982), and Smith (1985).

TABLE 7
QUANTITIES(VALUEADDED, U.S. CENSUSCONCEPT),MEXICO/U.S.,1975-At US "Prices"

At Mexican "Prices"
MexicoU.S.A.
1975
1975(1975 Ps. million)

MexicoU.S.A.
(%)

MexicoU.S.A.
1975
1975(1975 U.S.$ million)

MexicoU.S.A.
(% )Grain Mill Products
2,591.8
Sugar and Sugar
Products
3,216.1
Malt and Malt
Beverages
6,874.8
Tobacco and Tobacco
Products
1,816.8
Textiles
8,364.7
Footwear and Leather
Products
3,329.5
Pulp and Paper
6,278.8
Soap and Detergents
2,704.2
Paints
1,597.0
Agricultural Fertilizers
2,261.7
Petroleum Refining and
Products
8,561.7
Tires and Inner Tubes
2,954.4
Cement3,449.5
Bricks867.2
Iron and Steel
13,535.1
Radio and TV Receivers 2,565.7
Motor Vehicles
14,541.6
Total in our sample

85,510.9

Note: Includes adjustments to exclude indirect taxes and subsidies for malt and malt beverages,
tobacco and tobacco products and petroleum refining and products, and for quality differences in
the motor vehicles industry.

Our approach comes closest to that of the Czech-French study. We assumed
that the PPP's for our sample were representative for the non-sampled industries
in the same manufacturing branch. For reasons already explained above, we feelthat the PPP relationships are more representative than the quantitative relationships which Paige and Bombach predominantly used to establish their aggregate
result. Unlike the Czech-French study, we used a weighted average of ourindividual industry PPP's to arrive at the PPP for each branch. For example our
PPP for the food products branch is the average of the price ratios for grain milland sugar and confectionery products weighted by value added ( U S . census
concept). Table 8 shows our PPP's by manufacturing branch. They were used toconvert branch value added at national prices to a common currency unit (seethe quantity relatives in Tables 9 and 10).

One of the major purposes of our approach is to estimate comparative levelsof labour (and ultimately of total factor) productivity. Labour productivity ishere expressed as output per person engaged. Figures on working hours areTABLE 8
PURCHASINGPOWER P A R I T I E SBY MAJOR BRANCH O F M A N U F A C T U R I NBRAZIL/U.S.A.
G( C R U Z E I R OTO
S T H E U.S. DOLLAR)A N D MEXICO/U.S.(PESOSTO T H E U.S. DOLLAR),1975-

PPP: Cruzeiros/U.S. dollar
U.S.
Quantity
Weights

BrazilQuantity
Weights

Geometric
Average

PPP: Pesos/U.S. dollar
U.S.
Quantity
Weights

MexicoQuantity
Weights

Geometric
Average

Food Products
Beverage Products
Tobacco Products
Textiles and Wearing
ApparelFootwear and Leather
Products
Wood and Paper
products
Chemical Products
Rubber and Plastic
Products
Stone, Clay and Glass
Products
Metal ProductsElectrical Machinery
Machinery andTransport Equipment
Other
Total
Source and note: PPP's from Table 4. The PPP for food products is the weighted average forgrain mill products and sugar and confectionery products. The PPP for chemical products is aweighted average for soap and detergents, paints, agricultural fertilizers and petroleum refining andproducts. The PPP for stone, clay and glass products is a weighted average for cement and bricks.
In all cases value added ( U S . census concept) was used as weights. The Cruzeiro/U.S. dollar PPP'sand Peso/U.S. dollar PPP's for "Other Manufacturing" and "Total Manufacturing" are derived fromthe sum of the branch values in Tables 9 and 10, respectively.

generally not available for Brazil, and there are only rough figures for Mexico.
In 1975, average working hours in Mexico were 44.05 per week compared with
39.50 for production and non-supervisory workers in U.S. manufacturing.'
Reliable comparative information on time off for holidays and sickness is notavailable, so output per man hour cannot be calculated with any accuracy, but
it seems probable that aggregate hours per person engaged were longer in Brazil
and Mexico than in the U.S.A., perhaps around 10 percent higher.
The labour productivity ratios presented here do not account for activitiesof head offices and auxiliaries in any of the three counties. We d o not believethat the ratios would change significantly by including such activity. The head
office share of total manufacturing employment was 14 percent in both Brazil and
Mexico and 16 percent in the U.S.A.
Table 12 presents ratios of value added per person engaged in manufacturing
branches for the Brazil/U.S.A. and the Mexico/U.S.A. comparison. The produc'For Mexico, see INEGI (1985), Vol. 1, p. 60; for the U.S.A., see Employment and Earnings,
December 1978, p. 85.

TABLE 9
Q U A N T I T I E(VALUESADDED,F O R M E RNATIONALACCOUNTSCONCEPT)B Y MAJOR BRANCHO F MANUFACTURING,
BRAZIL/U.S.A.1975
At Brazilian "Prices"

At U.S. "Prices"

BrazilU.S.A.
1975
1975(1975 Cr.million)

BrazileU.S.A.

Food Products
Beverages
Tobacco Products
Textiles and Wearing Apparel
Footwear and Leather
Products
Wood and Paper Products
Chemical Products
Rubber and Plastic Products
Stone, Clay and Glass
Products
Metal ProductsElectrical Machinery
Machinery and Transport
Equipment
Other27,7594,565
2,987
22,940"

Total

(%)

BrazilU.S.A.
1975
1975(1975 U.S.$ million)

BrazilU.S.A.
(%)

144,744
41,774
12,203
270,854

19.18
10.93
24.48
8.47

10,337
590
682
2,339

25,421
5,155
2,469
20,325

40.66
11.45
27.62
11.51

3,977"
27,69642,511
10,26013,145482,290388,781
121,560

30.26
5.74
10.93
8.44

833
3,362
4,286
881

2,339
45,78832,627
9,231

35.63
7.34
13.14
9.55

15,36531,176
15,43784,899470,798
211,184

18.10
6.62
7.31

3,130
4,289
2,020

10,81752,61727,369

28.93
8.15
7.38

44,231
8,109

513,071
132,811

8.62
6.11

6,996
1,295

79,087
15,0998.85
8.58

257,0122,888,112

8.90

41,039328,343

12.50

Source: Brazil value added in national currencies from Censo Industrial, U.S. value added innational currencies from National Income and Products Accounts of the United States: 1929-76
Statistical Tables ( 1 9 8 1 ~after)
adjustment for inventories indirect taxes and subsidies and net interest.
PPP's from Table 8.
Note: The breakdown between food products and beverages for the U.S. on a national accounts
basis was assumed to be proportionately the same as on a U.S. Census basis (1975 figures derived
from Annual Survey of Manufactures).
"The footwear industry (2,675.9 million cruzeiros) was reallocated from wearing apparel tofootwear and leather.

tivity ratios show a very clear U.S. productivity advantage over both the othercountries.
In the Brazil1U.S.A. comparison labour productivity (the geometric "Fisher"index) varied between 33 percent of the U.S. for wood and wood products to 76
percent for food products, with a weighted average of 49 percent for manufacturing as a whole. The average Mexico/U.S.A. ratio is below that for Brazil/U.S.A.,
namely 39 percent, with a minimum of 22 percent of the U.S. level for wood andpaper products and a high of 48 percent for food products.

The most interesting feature of our results is that our PPP's (Table 13) do
not vary greatly from the exchange rate.6
6 ~shouldtbe stressed that the PPP's in Table 13 are our preferred summary measures, and are
not unique in character. As in all such studies the final outcome can be stated in alternative ways,
i.e. the price relations can be measured with the "quantity" weights of either one of the two countries
involved in each binary comparison. In complementary fashion, our quantity relations (see Table15) can be measured using the "price" weights of either one of the countries involved in each binary
comparison. The measure we show in Table 13 is a geometric (Fisher) average of these alternatives.

TABLE 10

At Mexican "Prices"
MexicoU.S.A.
1975
1975(1975 Ps. million)

MexicoU.S.A.
(%)

At U S . "Prices"
MexicoU.S.A.
1975
1975(1975 U.S.$ million)

MexicoU.S.A.
(%)

Food Products
Beverages
Tobacco Products
Textiles and Wearing Apparel
Footwear and Leather
Products
Wood and Paper Products
Chemical Products
Rubber and Plastic Products
Stone, Clay and Glass
Products
Metal ProductsElectrical Machinery
Machinery and Transport
Equipment
Other
Total
Source: Mexican value added in national currencies from Resumen General, U.S. value added
in national currencies from National Income and Products Accounts of the United States: 1929-76
Statistical Tables ( 1 9 8 1 ~after)
adjustment for inventories indirect taxes and subsidies and net interest.
PPP's from Table 8.
Note: The breakdown between food products and beverages for the U.S. on a national accounts
basis was assumed to be proportionately the same as on a U.S. Census basis (1975 figures derived
from Annual Survey of Manufactures).
"Indirect taxes and subsidies are deducted.
b~ncludes3,831.7 @lion pesos (excl. indirect taxes and subsidies) for petroleum refining, notshown in the census Resumen General, but taken from Sistema de Cuentas Nacionales de Mexico.

In fact the purchasing power of the Brazilian currency was somewhat greaterfor manufactured products than suggested by the exchange rate, while in Mexico
the reverse situation prevailed. These conclusions seem quite plausible. After the
first OPEC shock Brazil took steps to make its effective exchange rate morecompetitive in 1974 and 1975, whereas the Mexican currency is generally held
to have been overvalued in 1975, since the exchange rate had been unchanged
since 1954. The currency was substantially devalued in 1976.
Our PPP's and exchange rate deviation indices (Table 13) are quite different
from those of the ICP for GDP. This in itself does not mean that they are
incompatible as the ICP figures are strongly affected by services where theirexchange rate deviation index is particularly extreme.
Although the ICP authors have never used their results to derive proxyestimates for sectors of output, several other investigators have done so (seeTable 1). Using the same technique as such analysts, we can use ICP material
to derive the PPP's for manufacturing in Table 14. The proxy PPP for manufactur-TABLE 11
I N 1975PERSONSENGAGEDI N MANUFACTURING

BrazilMexicoUXA.

Food Products
Beverages
Tobacco Products
Textiles and Wearing Apparel
Footwear and Leather Products
Wood and Paper Products
Chemical Products
Rubber and Plastic Products
Stone, Clay and Glass Products
Metal ProductsElectrical Machinery
Machinery and Transport Equipment
Other

482,434
52,08023,965507,593"
129,231"524,402
177,920
120,866
311,361
429,539
170,425595,580
146,260

309,651
69,3928,645
229,027
48,101
164,595
157,170b
53,363
100,714206,509114,382
178,678
34,113

1,321,400
203,800
66,2002,049,300
239,700
2,642,700
983,100
585,000
588,800
2,505,800
1,523,600
3,571,200
893,200

Total Manufacturing

3,671,656

1,674,340

17,173,800'

Source: Brazil from IBGE, Censo Industrial (1981a), Mexico from SPP, Resumen General(1979a), USA from U.S. Dept. of Commerce, Annual Survey of Manufactures 1975-76 (1979).
"Employment in the footwear industry (95,358 employees) was reallocated from wearing apparelto footwear and leather.
"~ncludes25,989 employees in petroleum refining which are not covered by the industrial census
Resumen General, but taken from SPI, 1981.
'Excludes employees in administrative offices and auxiliaries, i.e. 152,682 in Brazil, 69,448 in
Mexico, and 1,128,200 in the U.S.A.

ing is identical with our average PPP result in the Brazil/U.S.A. comparison, but
substantially different for the Mexico/U.S.A. comparison.
Apart from the possible shortcomings of proxy PPP's, there is also a substantial problem when they are applied (see D. J. Roy, 1987) to the respective national
accounts at national prices, without adjustment for differences in the coverageof such accounts. The Mexican national accounts make a very large imputation
for manufacturing activity in the informal sector, whereas the Brazilian accounts
make virtually no adjustment. As there is no reason to expect the relative size ofthe informal sector to be much different in the two countries, use of inconsistentnational accounts can have serious results. The typical shortcut proxy procedure
would overstate Mexico's output position relative to Brazil's for two reasons:(a) by overstating the relative PPP of the peso, and(b) overstating Mexico's output in national currency terms vis-5-vis Brazil.
Table 15 shows the quantitative results (geometric averages) of our study
for the Brazil/U.S.A. and Mexico/U.S.A. comparison. The figures show clearly
that Brazil had a better performance than Mexico both in terms of labour
productivity and output per head of population, but it appears that the Latin
American performance per head of population is much lower than the productivity
standing, because manufacturing employment is relatively smaller than it is in
the U.S.A.
Table 16 compares our labour productivity results for Brazil, Mexico andthe U.S.A. with those of analogous studies for other countries. The studies ofPaige and Bombach for 1950, Smith, Hitchens and Davies for 1967-68, and SmithTABLE 12
PRODUCTIVITYRATIOS(VALUEADDED, F O R M E RNATIONALACCOUNTSCONCEPT)PER PERSON E N G A G E DB Y MAJORBRANCHOF M A N U F ATURING,CBRAZIL/U.S.A.A N D MEXICO/U.S.A.,
1975
Brazil/ U.S.A.
BrazilUnit
Value
Weights

UXA.
Unit
Value
Weights

Geometric
Average

Mexico/U.S.A.
MexicoUnit
Value
Weights

U.S.A.
Unit
Value
Weights

Geometric
Average

Food Products
Beverages
Tobacco Products
Textiles and Wearing
ApparelFootwear and Leather
Products
Wood and Paper
Products
Chemical Products
Rubber and Plastic
Products
Stone, Clay and Glass
Products
Metal ProductsElectrical Machinery
Machinery andTransport Equipment
Other
Total Manufacturing
Source: Value added from Tables 9 and 10 for the Brazil/U.S.A. and Mexico/U.S.A. comparison
respectively. Persons engaged from Table 11.

TABLE 13OF O U R PPP's FOR MANUFACTURINGW I T H T H E EXCHANGERATE A N D
CONFRONTATIONWITH T H E PPP's OF ICP FOR 1975

Our PPP's for Manufacturing (weighted by major branch)
ICP (Augmented Binary) PPP's for G D P
Exchange Rate
Our Exchange Rate Deviation Index for Manufacturing
ICP Exchange Rate Deviation Index for G D P (augmented
Binaries)

Brazil/U.S.A.
(Cr./U.S.$)

Mexico/U.S.A(Ps. / U S . $ )

7.42
5.40
8.13
1.10

12.77
7.17
12.50
0.98

1.51

1.74

Source: Our PPP's for Brazil/U.S.A. derived from Table 9 and for Mexico/U.S.A. from Table
10, respectively; ICP augmented binaries from Kravis, Heston and Summers (1982), pp. 255, 272. Infact the preferred ICP PPP's are multilaterally weighted, but we have shown their augmented binaries
here because they are conceptually closer to ours. The multilaterally weighted PPP's of ICP did notvary greatly, i.e. 5.20 and 7.40, respectively for 1975 (see Kravis, Heston and Summers, 1982, p. 177).
Exchange rates from IMF.
Note: The exchange rate deviation index is the ratio of the exchange rate to the PPP.

TABLE 14
WITH T H E PROXY PPP's DERIVEDCONFRONTATIONOF O U R PPP's FOR MANUFACTURING
FROM T H E ICP 1975 AUGMENTED
BINARYRESULTS

Our PPP's for Manufacturing (weighted by major branch)
Proxy PPP's for Manufacturing Derived from ICP
Augmented Binaries
Ratio of Our PPP/Proxy ICP PPP

Brazil/U.S.A.
(Cr./U.S.$)

Mexico/U.S.A.
(Ps. /U.S.$)

7.42

12.77

7.42
1.OO

10.66
1.20

Source: Top line from Table 13; Second line derived from Kravis, Heston and Summers (1982),
pp. 255,272 and 313 as follows: the ICP 111 augmented binary PPP's for expenditure on the consumer
items food, beverages, tobacco, clothing, footwear, furniture, appliances and transport equipment,
and for producer durables were used to make the weighted average. These are the ICP PPP's which
are conceptually closest to our type of comparison. The preferred PPP's of the ICP itself are in"international dollars."

TABLE 15SUMMARYRESULTSFOR M A N U F A C T U R I NOUTPUTGA N D PRODUCTIVITY
BRAZIL/U.S.A.AND
MEX~CO/U.S.A.
(1975)

Value Added (Former National Accounts Concept) as a
Percentage of the U S A .
Value Added (Former National Accounts Concept) per
Person engaged as a Percentage of the U.S.A.
Value Added (Former National Accounts Concept) per
Head of Population as a Percentage of the U.S.A.
Persons Engaged in Manufacturing as a Percentage of the
U.S.A.
Population as a Percentage of the U.S.A.

10.55

3.76

49.33

38.52

21.72

13.48

21.38
48.55

9.75
27.85

Source: Value added from Tables 9 and 10; value added per person employed from Table 12;
population figures for Brazil from IBGE, Censo Demografico (1983), Mexico from Bank of Mexico,
Indicadores Economicos (1986), U.S.A. from OECD, Labour Force Statistics (1987).
Note: Figures in the three upper lines are geometric averages.

for 1977 all found the U.K. productivity ratio to the U.S.A. (value added perperson employed) to be similar to what we found for Mexico/U.S.A. for 1975,
and below the Brazil/U.S.A. ratio we obtained for 1975.
Confirmation of the rather high level of productivity in Brazilian manufacturing can be found in a recent direct comparison by Van Ark (1988) of labour
productivity in Brazil and the United Kingdom for 1975. Using the same methods
as this study for a larger sample of 23 industries, it showed average Brazilian
output per person engaged to be not far from that of the U.K. in 1975.
It is at first sight surprising that real productivity levels in Brazilian and
Mexican manufacturing are as high by international standards as they appear.
However, evidence from estimates at national prices appears to confirm that
Brazil and Mexico have much higher productivity levels in manufacturing compared with the rest of the economy than is the case in the more advanced countries.

TABLE 16
RESULTSOF PREVIOUSSTUDIESA N D OUR STUDY OF OUTPUT PER PERSONENGAGEDI N
MANUFACTURING
AS A WHOLE,AS A PERCENTAGE
OF T H E U.S.A.
At LocalPricesPresent study

41.6

Present study

33.0

Paige and Bombach (1959)

34.2

Smith, Hitchens and Davies (1982)

36.2

Smith (1985)

38.3

Kudrov (1969)

33.6

Yukizawa (1978)

78.2

West (1971)

64.4

At U.S.
PricesBrazil/U.S.A. (1975)
58.5
Mexico/U.S.A. (1975)
45.0
U.K./U.S.A. (1950)
39.1
U.K. (1968)/U.S. (1967)
39.7
U.K./U.S.A. (1977)
41.5
U.S.S.R./U.S.A. (1963)
36.8
Japan/U.S.A. (1972)
62.1
Canada/U.S.A. (1963)
68.5

Geometric
Average

49.3
38.6
36.6
37.9
39.9
35.3
69.9
66.4

Sources: See bibliographic references.

There are several reasons for this relatively high level of labour productivity
in the manufacturing sectors of Brazil and Mexico. One is that in many sectorsof manufacturing, the nature of technology is such that it is often rational to use
processes which are labour saving and capital intensive, even in countries withlow wages. Low income countries do have some leeway in adapting technology
to a situation of low labour costs, but a large part of industrial technology wasdeveloped in countries where labour is more expensive, and there are problems
in adapting it to different factor cost situations.
A second reason for relatively high labour productivity in Brazilian and
Mexican manufacturing is the importance of policies which subsidize capital
inputs. As a result, scarce capital is funnelled by priority towards industry. These
policies are probably operative to a greater degree than in the OECD countries.
A few additional remarks should be added on the relatively high productivity
standing of Brazil and Mexico compared to the other countries. Firstly, the Latin
American standing in terms of output per man hour, which could not be measured
accurately, is probably lower than the productivity ratio in terms of output perperson engaged, because working hours appear to be higher than in the U.S.A.
Secondly, in comparison with the U.S.A. there is probably a greater amount of
informal manufacturing activity outside the scope of the census in Latin America
where productivity is lower. Thirdly, as already noted, Latin American performance per head of population is much lower than their productivity standing,because manufacturing employment is relatively much smaller than it is in the
U.S.A.
The present article deals with two binary comparisons, one between Brazil
and the U.S.A. and the other between Mexico and the U.S.A., and made someinferences about the relative productivity standing of Brazil/Mexico from thetwo other binaries. In fact we also made a direct binary comparison between
Brazil and Mexico, without using the U.S.A. as an intermediary, but have notpresented the details here as the quantitative results were not substantiallydifferent from the inferential comparison. The geometric average of the
Mexico/Brazil ratio of value added per person engaged was 82.70 percent in the
direct binary comparison against 78.09 percent according to the inferential comparison (which can be derived from Table 12).

One of the objectives of the present study was to provide a systematic
methodological survey of the analytical problems inherent in the industry oforigin approach, with whatever pragmatic contribution or recommendations we
could make to mitigate or solve those which characteristically emerge.
(a) An Integrated Three-Dimensional Approach
We tried to give full attention to each of the three main dimensions ofinternational comparison-real
output, PPP's and productivity, and to set out
their interrelation and complementary character clearly. Here our exposure to
ICP methodology was very useful, as its rigour in this respect is exemplary. We
feel that a good deal of previous work on industry-of-origin lines has sufferedfrom concentrating only on the productivity aspects (this is true of all studies
listed in Table 2 except Paige and Bombach, the CzechIINSEE study and thatof West).
(b) Reconciliation with the National Accounts Framework
There are obvious advantages in making sectoral output and productivity
studies of this kind in a conceptual framework compatible with the national
accounts. We made a careful confrontation between the census and the national
accounts, from which it appeared that the Mexican national accounts makeextensive (and perhaps excessive) allowance for informal activity not recordedin the manufacturing censuses.
It is also clear that census definitions of value added vary between countries,, and need adjustment to bring the comparisons for the three countries to a common
conceptual basis as is used in national accounting. The "national accounts"
concept of value added is obviously preferable to the census concepts, which arebecoming increasingly anachronistic by neglecting to deduct service inputs inmeasuring value added.
(c) Adjustment to a Common Benchmark Year
Our study meets the problem of comparing countries whose census dates
fall in different years. Our adjustment procedures have general applicability, andthey were applied here to the U.S.A., whose performance is often a yardstick forcomparison in such studies. In fact, using our approach, U.S. data can be adjusted
to any intercensal year needed for purposes of international comparison.

(d) A Systematic Shortcut Procedure for Matching
None of the previous studies mentioned in Table 2 used a systematic
procedure to select the particular "representative" products on which price andquantity comparisons are ultimately based. We therefore developed criteria fora systematic matching procedure which is economical in terms of time and effort.
Exact-matching is difficult to realize because strictly identical products are
only rarely available in two or more countries at the same date. In consequence,lower degrees of product comparability have to be accepted for international
comparisons than for inter-temporal comparisons within a single country. Thisis true not only for the present product-based study, but also for expenditure-based
studies such as the ICP.
The maximalist approach tries to match as many items as possible, but often
results in very wide ranges of PPP's within an industry. These widely divergent
PPP's for different products are a signal to the possibility that some of the matches
are false. In spite of having similar (or even identical) descriptions, we inferredthat some of these outliers were, in reality, different products.
For complex multiproduct industries, we therefore developed a procedure
which confines matching to the most important products. Only products that
accounted for more than 1 percent of the gross value of output of an industry
were considered for matching. Smaller items were only included when they
matched a similar product of importance in the other country, or when they wererequired to complete a "match" with an important product.
The advantages of a systematic matching procedure is important, when one
has to deal with:-a large industry with many product items, for example, textiles or footwear
and leatherware, and/or-a technically complicated industry producing items difficult for a technicallyinexperienced researcher to characterize, for example motor vehicles or ironand steel.
In these cases, an important risk of mismatching occurs when a less systematic
approach is used. For smaller, simpler industries the maximalist approach wasused.
(e) The Unit Value Approach is not Inferior to Specijication Pricing
It is sometimes suggested that unit values such as we derived from census
information are inherently inferior to specification pricing as practiced by ICP,
but we do not believe this to be the case.
Specification pricing involves meticulous characterisation of the items chosen
as representative, whereas our "prices" are unit values derived by confrontationof census information on values and quantities of product. In practice the"products" may be a mix of items and qualities and be very far from the idealof specification pricing, but there are compensatory advantages in the industryof origin approach:(1) the unit values are average transaction values for the whole year for all
producing locations of the countries compared, whereas ICP prices arequotes, shelf, list or monitored prices for one point in the year in alimited number of locations,(2) with the census one can judge the representativity of the "unit values"
which are selected from a much wider range of information than ICP
had at its disposal. For instance, our 17 industry sample yielded 1,434
Mexican unit values from which 192 were chosen to match with the
U.S.A., and 543 Brazilian unit values of which 171 were matched with
the U.S.A. ICP, by contrast, had to use what it got from national statistical
offices (at least for consumption goods). For Mexico it received only
284 of the much larger number of consumer prices it requested, as
compared with 359 for Brazil and 571 for the U.S.A. (Kravis, Heston
and Summers, 1982, p. 45).
Our unit value specification was particularly poor in the case of motor
vehicles, largely because of census confidentiality rules. The census information
was therefore supplemented in this case by using information on output andconsumer price structures from trade sources. Automotive News provides figures
furnished by trade associations from trade sources which are reasonably reliable(see the "Statistical Appendix" in Maddison and Van Ark, 1988). Producer prices
would have been preferable to consumer prices, but the U.S. producer price index
is based on information for only a limited number of models, and is as confidential
as the census itself. Our method of handling the problem produced a reasonable,
though not an optimal, adjustment for quality. In any case, we would stress that
our approach is not inferior to that of ICP for this particular industry. As the
ICP approach is a multilateral one, its products have to be "representative" ina global sense. ICP 111 used passenger car models which were characteristic
across its 34 countries, and its comparison for Brazil1U.S.A. and Mexico/U.S.A.
was based largely on Japanese and European models which were quite unrepresentative of the situation in these three markets.
(f) The Adequacy of the Sample
Our sample size (39 percent of Mexican, 33 percent of Brazilian and 20 per
cent of U.S. value added) was certainly large enough to illustrate most of themethodological problems one is likely to encounter in this kind of study and tohelp elaborate pragmatic solutions to them. Except as noted under (g) below,
the only failure in this respect was the problem of unique products, such as
atomic weaponry, guided missiles and space vehicles, which are unique to the
U.S.A. and for which it would be difficult to derive dummy Brazilian and Mexican
prices. There are also industries which are not unique, but near enough to impede
comparison (such as aircraft, computers, oil drilling and other specializedmachinery). These unique and quasi-unique industries were about 7 percent of
total U.S. manufacturing output in 1975. Otherwise, there are very few industries
which are truly comparison resistant, particularly if one makes supplementary
inquiries with trade associations (which we did for motor vehicles, paints,
petroleum products and bricks) where there were national idiosyncracies inmeasurement units or gaps in the census due to confidentiality rules. From thepoint of view of our other objective of comparing output, productivity and PPP
outcomes for the three countries, the results can always be improved by increasing
the sample size, but we felt that there was already reasonable coverage of majorindustry branches in Brazil and Mexico, and weaknesses only for food products
and electrical machinery for the U.S.A.
(g) Approaches to the Problem of Double DeJlation
The important unsolved problem in this study is that of double deflation.
Virtually all analysts who have used the industry of origin approach have been
unable to find separate PPP's for inputs. The double deflation approach is feasible
for agriculture (van Ooststroom and Maddison 1985), but it was not feasible for
manufacturing for these three countries, because the Brazilian and Mexican
censuses give global value figures on inputs with no detailed quantitative information, and the U.S. census gives detailed figures only for energy consumption,
contract work and inputs directly related to the production process.
In agriculture the difference between the gross output PPP's and the double
deflated PPP's was rather small. For Brazil the 1975 PPP (Brazil quantity weights)
was 7.35 cruzeiros to the U.S. dollar, 6.63 for inputs and 7.57 for value added.
For Mexico the 1975 PPP (Mexican weights) was 13.46 pesos to the U.S. dollar,
13.68 for inputs and 13.36 for value added.
In manufacturing, inputs are much bigger in relation to gross output thanin agriculture, but in the U.S.A. 60 percent of these are from manufacturing itself
and in Mexico 48 percent. For manufacturing as a whole therefore, it does notseem a priori likely that the PPP's resulting from "double deflation" would bevery different from those in our study, but for particular branches they mightvary a good deal more.
Previous investigators who have discussed this problem, have been able to
make only very partial adjustments for inputs. Paige and Bornbach did this forfuel inputs on an aggregate basis, and Smith, Hitchens and Davies made someillustrative calculations (whose basis is not clear) for fuels and raw materials.
However, a close look at the input-output tables which are available for Mexico(SPP, 1981) and the U.S.A. (U.S. Dept. of Commerce, 1984a and 1984b) showsthat fuel and raw material inputs are only a small part of the problem in mostindustries.
Our analysis of the relation of census to G D P concepts of value added helps
to clarify the nature of double deflation because it demonstrates the need to deal
with all inputs. Further progress can best be made, when industry of origin studies
such as the present one are available for all the major sectors of the economy,
i.e. for agriculture, mining, manufacturing, utilities, construction and services.
With this information and input-output tables for each of the countries undercomparison, one can return to the problem of double deflation much better
equipped to d o a thorough job. In the case of Mexico and the U.S.A., input-output
tables are available for the census years we covered, and the 1975 table for Brazil
is due to be published soon, so for these three countries, this work should befeasible.

Ahmad, S., Approaches to Purchasing Power Parity and Real Product Comparisons Using Shortcuts
and Reduced Information, World Bank Staff Working Paper, No. 418, Washington D.C., processed,
1980.

52

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