Measuring Divergence. A New Estimate of Real Output and Productivity in British and American Manufacturing in 1935
Herman de Jong and Pieter Woltjer Groningen Growth and Development Centre/N.W. Posthumus Instituut University of Groningen Email:
[email protected] Please do not quote without permission of the authors
Abstract This paper provides a new estimate of British and American comparative value added and productivity for manufacturing for the year 1935. Using the official census data, we calculate double deflated levels of real value added per worker. The new estimates for Anglo-American comparative manufacturing performance reveal important differences in productivity at industry level and highlight the relative productivity lead of the United States. We show that actual hours worked differed a lot between the U.S. and the U.K., and adjusted for this. On average the American manufacturing productivity level was 224 percent of the U.K. on a per worker basis, and 279 percent on a per man-hour basis. This level corroborates the view held by Alexander Field that the American productivity leadership in manufacturing was strengthened during the 1920s and 1930s.
1. Introduction There is a new emphasis on the Depression’s contribution to growth of potential output in the American economy. Recent studies by Robert Gordon and Alexander Field have shown that American growth in the first part of the twentieth century has been exceptionally high, especially between 1929 and 1941.1 Field conjectures that the United States’ fastest productivity growth took place in the middle of the depression of the 1930s and not during WWII, as is still the common conception.2 In this period the foundations were laid for much of the U.S. productivity growth of the 1950s: “…the golden age (1948-1973) no longer has to be understood sui generis, but can be seen as a period reflecting the extension and persistence of trends and technological foundations established during the interwar period... It overturns the conventional wisdom attributing achieved 1948 productivity levels principally to the war…”3 Thus, the Great Depression did not push down the underlying productivity trend of the American economy. How does this new view of U.S. growth compare with developments in Europe and the rest of the world? Indeed Field mentions a widening gap of productivity levels between the U.S. and Europe and Japan already before WWII, but he does not supply direct comparative evidence.4 If we focus here on manufacturing alone we find on the basis of existing estimates a U.S./U.K comparative productivity level of 250 in 1929 and of 192 in 1938, revealing in fact a ‘cyclical’ narrowing of the gap during the 1930s and
1
Gordon, “U.S. Economic Growth,” pp. 123-128. Field, “Most”, p. 1399: “…the years 1929-1941 were, in the aggregate, the most technologically progressive of any comparable period in U.S. economic history ….” Field stresses the central characteristics of this period, mentioning the important role of electrification and other bursts of technological and organisational creativity in the U.S. in the fields of manufacturing industry and in trade and transportation. Of great importance was the complementarity between human skills and disembodied technical change, characterized by a rise of both capital and labour productivity (new chemicals, better thermal efficiency, use of conveyer belts, efficient floor space, better materials etc.). These positive supply shocks resulted in an outward shift of the production possibility frontier. 3 Field, “Origins,” p. 65. Field, “Technological,” p. 205, 216, and 228: Between 1929 and 1941 TFP growth in the nonfarm economy grew at a rate of 2.31 percent per year, being ‘the highest peak to peacetime peak rate of the century.’ Almost 50 percent of TFP growth originated from the manufacturing sector. Between 1919 and 1929 total TFP growth was 2.02 percent per year, with manufacturing’s contribution estimated at more than 80 percent. 4 Field, “Equipment,” p. 49. 2
2
thus a relative decrease of U.S. comparative productivity.5 This estimate is hard to reconcile with Fields very optimistic account of U.S. manufacturing during the Depression. Doubts are strengthened by the fact that many authors provide a rather bleak picture of British manufacturing performance during the 1930s. In the literature on Britain we find a pessimistic account of the functioning of British capital markets, competition in product markets and effects of industrial relations, which were not very favorable for long-run productivity performance.6 There was a shortfall on a broad front nurtured by a ‘cosy collusive environment,’ that presumably differed a lot from the U.S. competitive environment characterized by modern anti trust legislation.7 The question of the paper is: can we find direct comparative evidence for this American productivity expansion before WWII, and the British shortfall at the same time? The most important quantitative assessment of the comparative performance of the British and American economies in the 1930s is the widely used study of Laszlo Rostas.8 Many studies of relative U.S./U.K. performance rely on his very detailed comparisons of physical output per worker from the manufacturing censuses of the U.K. (1935) and the U.S. (1937/39). Our study will also make use of these national censuses. However, we will apply new methods of comparison and will use a common census year for both countries, being 1935, to guarantee complete coverage of all industries that were reported. We believe that it is possible to use value added as the measure of output and productivity of industries instead of ‘traditional’ indicators such as physical quantities of output per worker. We will calculate comparative levels of value added and labour productivity for all 93 industries and industrial branches. Next, we will use sector specific purchasing power parities (PPP) to deflate output for each industry and branch by using data on quantities and related values in the British and the American census reports. Third, we will adjust for input price levels as well, and perform a double deflated analysis. And fourth, we will adjust for actual hours worked, as we believe that the variation in the interwar workweek between the U.S. and the U.K. is a fundamental factor 5
Broadberry, Productivity Race, p. 2; see also Broadberry and Crafts, “Britain’s,” p. 532-33: TFP growth in the British economy has been estimated at 1.9 percent between 1924 and 1937. 6 Crafts, Long-run growth, p. 22 7 Eichengreen, British Economy, p. 340. See Booth, “ Manufacturing,” for a revisionist interpretation of U.K. manufacturing performance in the trans-WWII period. 8 Rostas, Comparative.
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in explaining the differences in productivity growth rates and in comparative productivity levels. Our new estimates for the Anglo-American comparative manufacturing performance reveal much larger gaps in productivity levels than Rostas’ outcomes. The new results highlight the relative productivity lead of the United States well before World War II. We will show that in 1935 the American manufacturing productivity level was 224 percent of the U.K. on a per worker basis, and almost 280 percent on a per man-hour basis.
2. Sources and Data The data we need to make cross-country comparisons of levels of output and labour productivity in manufacturing come from the official production censuses. For the United Kingdom, we used the Fifth Census of Production of 1935, published by the Business Statistics Office (BSO) of the Board of Trade.9 For the United States, we took the Biennial Census of Manufactures of 1935 published by the Bureau of the Census of the U.S. Department of Commerce.10 Both surveys contain detailed information on quantities of produced items, prices, gross output, intermediate input, and employment. As the information for outputs and inputs is based on one and the same questionnaire - for which the information is supplied on the level of firms - internal consistency is guaranteed. Appendix A provides a discussion of the comparability of both censuses. The aim of any cross-country comparison of the level of relative industrial productivity is to get a better view of the realized and potential differences in labour productivity. Consequently the comparison year should be chosen carefully, as business cycle and capacity utilization effects can have a significant influence on output and productivity levels. Rostas addressed this issue in his study of prewar British and American manufacturing and came to the conclusion that 1937 was the best year for
9
Board of Trade, Final Report U.S. Department of Commerce, Biennial Census, 1935
10
4
comparison.11 He argued that this was a representative year for both the U.K. as well as the U.S., because the use of available capacity was roughly the same. Unfortunately, statistical material was not fully available for the U.K. in this year. The Import Duties Act Inquiry of 1937 does cover some of the manufacturing branches, but the majority of the manufacturing industries were not yet tabulated or published by the time Rostas started his study.12 To overcome this problem he chose to compare the year 1935 for Britain with the year 1939 for the United States and work back towards 1937. The primary reason why Rostas relied so heavily on the American 1939 Biennial Census of Manufactures and not the 1935 or 1937 censuses is that it met the sizable data requirements of the quantitative study he employed.13 For the purpose of the present paper however, both censuses for the U.K. and the U.S. of 1935 are perfectly suited for the task at hand. The 1935 comparison provides a good view of the realized labour productivity levels and, if necessary, can be adjusted for the effects of the business cycle, capacity utilization, and long term productivity movements. One way to realize this adjustment is to make use of existing productivity time series to calculate the average movement in productivity levels in the manufacturing sector for both countries between 1935 and 1937. The extension of the comparative productivity figures for the U.K. and the U.S. shows that the comparative levels of productivity in 1935 do not differ from 1937.14 The comparative levels of productivity for total manufacturing for the U.K. and the U.S. in 1937 are identical to 1935. Furthermore Figure 1, which shows unemployment levels for both countries, illustrates that the British and American business cycles showed a similar movement. This diminishes the scope for potential effects of differences in capacity utilization and labour hoarding/selective retention between both countries.
11
Rostas, Comparative, p. 24. Board of Trade, Preliminary Reports 13 This particular census is part of the 1940 decennial census and contains detailed figures on the size of plants, horse power of machinery installed, etc. See: U.S. Department of Commerce, Sixteenth Decennial Census 14 Broadberry, Productivity Race, p. 44. 12
5
Figure 1
Unemployment Rate, U.K. and U.S. (1929-1939)
25
Unemployment Rate (%)
20
15
U.K. U.S.
10
5
0 1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
Year
Sources: - U.K. from Boyer and Hatton “New Estimates” - U.S. from Darby, “Three-and-a-Half”
The production censuses cover not only the entire manufacturing sector, but contain also data on mining, construction works, public utilities and government industries. For the purpose of this study we will exclude the latter industries and focus primarily on the manufacturing sector. The British census distinguishes between 108 manufacturing industries or trades, whereas the American census covers no less than 327 industries and sub-industries. We have reclassified the industries of both countries into 12 branches and 93 common industries based on the classification of the U.K. Census (see Appendix B for further details). Admittedly, this arrangement is the easiest to implement - as the more detailed American census can be readily fitted into the British framework - but it also adheres to the classification of the British-German comparison by Rainer Fremdling, Herman de Jong and Marcel Timmer, making it feasible to compare the two studies as we will show in a later section.15
15
Fremdling et al., “British and German.”
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3. Methods of Productivity Comparison We measured output and productivity by using the industry-of-origin approach. In principle one can apply either the quantity or the value method. The first method was used by Rostas who made direct comparisons of physical quantities of output (tons, gallons, units). The second procedure starts with the measurement of the value of gross output and preferably net output by industry (in national currency) which is then translated into a common currency with a sector-specific purchasing power parity adjusted price ratio. If all output can be covered, the two approaches provide in principle the same results. In practice, however, both methods yield different results because of differences in sampling, weighting and coverage of output. In the case of less than full coverage, the first method assumes that the actually measured quantity relatives of matched output items are representative for the unknown quantity relatives of unmatched output. In contrast to this, the second method assumes that the price relatives of matched output are representative of the unknown price relatives of unmatched output. Price comparisons provide a much better representation of matched output for non-matched output than is the case with quantity ratios.16 In this study we will estimate the value of output and apply the currency conversion method. International comparisons of GDP and per capita income are now mostly made by converting national income to a common currency on the basis of purchasing power parities (PPPs). These PPPs are obtained by expenditure categories (private consumption, investment and government expenditure). While comparisons for the total economy can be made using an expenditure approach, it raises problems for comparisons by industry of origin (agriculture, industry, and services) as it requires a subjective allocation of PPPs to individual industries. As expenditure represents not only the production value of the industry in question but also the added value of industries further down the chain, these PPPs require adjustment for taxes and trade and transport margins. In addition, expenditure PPPs also need adjusting to exclude the relative prices of imported goods and include the relative prices of exported goods. And most importantly, expenditure PPPs exclude price ratios for intermediate products, which account for a substantial part of output in manufacturing and 16
Paige and Bombach, Comparison, p. 29.
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services. We therefore think that in comparisons of output and productivity in manufacturing, factory gate prices are more relevant than consumer prices.17 As Paige and Bombach have demonstrated, suitable conversion factors can be obtained by constructing new, so called industry-of-origin PPPs from either output price data alone (single deflation) or from price data for outputs as well as intermediate inputs (double deflation).18 This is how we will proceed: First we will make gross output, intermediate input and labour comparable at the level of individual industries. Value added and labour input need to be defined in a similar way between the countries and industrial classifications have to be matched. Then factory gate prices are calculated from the values and quantities of the items reported in the official production censuses. These average values for products and intermediate inputs, or unit values (UV), reflect domestic producer prices. Unit value ratios of identical products (UVRs) are used to convert output, and if possible intermediate inputs, of the two countries into a common currency or purchasing power parity for a certain benchmark year (1935) and for a specific industry or branch.19 The unit value approach effectively provides more information on productivity differences than the quantity approach. Most importantly, a study based on the unit value approach provides figures for labour productivity using data on gross output as well as value added.20
4. Comparison of the U.S. and U.K. censuses The methodology and formulae’s that we applied are identical to the procedures that were used in the recently published study on British and German manufacturing by Fremdling et al. We therefore refer to this study for the description of the methodology in the present
17
See van Ark and Timmer, “Notes and Communications” for an elaborate discussion. The pioneering study using currency conversions factors for international comparisons is Paige and Bombach, Comparison. 19 The derived UVRs can of course also be applied to the national accounts information on GDP. The manufacturing tables in this section are on a census basis. 20 The next paragraph will discuss the benefits of the double deflation in further detail. 18
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paper.21 Although data on gross output is quite abundant in both the U.K. and the U.S. censuses, specific value and quantity data for intermediate inputs is not available for most of the branches in the American census. We therefore estimated the intermediate input UVRs from the calculated output UVRs by making use of the flow of intermediate products between industries represented in British and American input-output tables. The procedure will be explained below. Except for the building materials and timber trades, we were able to construct intermediate input PPPs and thus value added PPPs. However, the American census does provide specific price and quantity data on the intermediate inputs for textiles and iron and steel. This allowed us to derive direct input PPPs from the census as well, which we used as a cross-check of our results from the input-output approach. The first step in the calculation of the PPPs for this productivity comparison is the matching of products between the two countries, both for gross output and for intermediate inputs as described in section 3. The level of detail of the census data with respect to output made it possible to match 361 products (see Appendix C for further details). On the intermediate input side we could match 67 input items (in textiles and iron and steel, see Appendix D for further details). The total coverage ratio for output the share of total gross production value covered by items that were matched - exceeds 40 percent for both countries, while the average number of UVRs per branch is 30. The coverage ratios as well as the number of matches differ across branches, which can be explained by the availability and heterogeneity of products, by differences in quantity specifications, the unique national character of some products and by differences in quality across countries.22 Coverage ratios were highest for the food, drink and tobacco trades and textiles, which together hold over one-third of the total value of production and employment of the entire manufacturing sector (see Appendix B). The paper trades yielded the lowest coverage ratios, mainly because printing products could not be matched. Table 1 features the Laspeyres, Paasche and Fisher Gross Output PPPs. These PPPs are based solely on output UVRs, aggregated to the branch and sector level using a 21
Fremdling et al, “ British and German”; The methodology is also described in Fremdling et al, “Censuses Compared”, www.ggdc.net 22 Fremdling et al., “British and German”
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Table 1
Purchasing Power Parities in Manufacturing, U.K. and U.S. (1935)†
Textile trades Leather trades Clothing trades Iron and Steel trades Engineering, Shipbuilding trades Non-ferrous Metals trades Food, Drink and Tobacco trades Chemical and Allied trades Clay and Building Materials trades Timber trades Paper trades Miscellaneous trades Total Manufacturing
Gross Output PPP ($ / £) LaspeyPaasche Fisher res 6.4 5.5 5.9 5.6 5.9 5.8 5.3 5.0 5.1 5.6 5.4 5.5 4.3 3.9 4.1 5.4 5.2 5.3 5.9 5.2 5.5 5.1 3.2 4.1 5.4 5.5 5.5 2.2 2.2 2.2 4.0 3.7 3.9 6.2 4.5 5.3 5.4 4.3 4.8
Intermediate Input PPP ($ / £) ‡ Paasche Fisher Laspeyres 6.2 5.2 5.7 (5.5) 5.5 5.8 5.7 6.1 5.4 5.7 5.8 5.2 5.5 (5.4) 5.4 4.9 5.1 5.4 5.2 5.3 5.7 5.7 5.7 5.3 3.8 4.5
4.1 5.3 5.5
3.6 5.7 4.9
3.8 5.5 5.2
Value Added PPP ($ / £) ζ Paasche Fisher Laspeyres 6.7 5.9 6.3 5.7 6.1 5.9 4.3 4.5 4.4 5.3 5.6 5.4 3.2 3.1 3.2 5.3 5.1 5.2 6.2 4.2 5.1 4.9 2.6 3.5
3.9 7.1 5.3
3.9 3.8 3.7
3.9 5.2 4.4
Value Added PPP as Percentage of Gross Output PPP 107 102 86 98 78 98 93 85
100 98 92
†) Sources: Barna, T. (1953), “Experience”; Leontief, W. (1951), The Structure; additional sources see Appendix B ‡) The intermediate input PPPs are based on output UVRs of intermediate products weighted by data on the flow of these goods from input-output tables. The intermediate input PPPs between brackets are based on input UVRs taken directly from the British and American census (see Appendix D for further details). ζ) The value added PPPs are based on the input-output weighted intermediate input PPPs and the single deflated gross output PPPs. The Laspeyres and Paasche value added PPPs are derived using the formulae below. See Fremdling, de Jong, and Timmer, “British and German” for further details.
VAPPPjAB ( A) =
GO jA ⋅ GOPPPjBA( A) − II jA ⋅ IIPPPjBA( A) GO jA − II jA
VAPPPjAB ( B ) =
GO Bj − II Bj GO Bj ⋅ GOPPPjBA( B ) − II Bj ⋅ IIPPPjBA( B )
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stratified sampling approach.23 The overall Fisher Gross Output PPP is 4.84 U.S. dollar per pound sterling, which is very close to the official exchange rate of 4.94 dollar. Still, the large cross-industry variation of the output PPPs shows that the exchange rate would function poorly as a PPP on a sector level. Although the single deflation of gross output in itself provides important new insights into the Anglo-American comparative productivity during the 1930s particularly on the disaggregated level of branches - double deflation is still the preferred method of productivity comparison, as it takes variations in input per unit of output of individual commodities into account. Single deflation will inevitably give too much weight to those of the industry’s products with relatively high inputs per unit of output (and vice versa), since these commodities are weighted by ex-factory output prices instead of value added figures. Furthermore, in cross-country comparisons, differences in the technical input-output coefficient of an industry can result in notable variations in the results between single- and double deflation. For instance, the labour productivity of a country relying heavily on imported or otherwise expensive materials may be considerably overstated when the single deflation method is used. Another factor that needs to be taken into account is the difference in price level between inputs and outputs; the single deflation approach implicitly assumes that price movements/levels of inputs are similar to those of outputs, while this is not necessarily the case.24 As direct quantity and price information for inputs is not widely available in the American census, we constructed intermediate input PPPs by using information on the flow of goods between industries from published input-output tables. We used the 1935-
23
A detailed description of the stratified sampling approach is provided in Timmer, Asian Manufacturing. In this study the minimum number of matches for a sample to be accepted was 2 with a coefficient of variation of 10 percent or below. The coefficient of variation is given by the formulae below; where Ij is the number of matches for industry ‘j’; wij the relative weight of product ‘i’ in the total value of production of industry ‘j’; UVRij the unit value ratio of product ‘i’; and UVRj the unit value ratio, or purchasing power parity, of industry ‘j’.
[
]
var UVR j =
(
1 Ij ∑ wij ⋅ ln UVRij / UVR j I j − 1 i =1
)
2
24
Ij ⎛ ⎞ ⋅ ⎜⎜1 − ∑ wij ⎟⎟ i =1 ⎝ ⎠
Studies applying the double deflation technique, such as the Anglo-German comparison by Fremdling et al., “British and German”, confirm that the method itself is feasible and generates reliable results in line with expectations.
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table for the U.K. by Barna and for the U.S. we applied the 1939-table by Leontief.25 By definition inputs for one industry are made up of the output of another industry; the intermediate input PPP for an industry can thus be derived as a weighted set of output PPPs from the industries furnishing its inputs. For the moment we only used the detailed Anglo-American output PPPs for manufacturing as described above and not relative prices from sectors outside of manufacturing. The input-output tables for the U.S. and U.K. reveal however that the large majority of the intermediate inputs for manufacturing industries originate from within the manufacturing sector itself. The method is therefore feasible, particularly for the very substantial clothing and engineering trades which acquire nearly 90 percent of their inputs from other manufacturing industries. We did not take differences in the cost of transport or trade margins into account, however as we are working solely with ex-factory output prices. Still, the difference in these costs for both countries is unlikely to be so large as to have a substantial effect on the resulting input PPPs, hence we implicitly assumed the trade and transport margins to be identical for both countries. To construct the intermediate input PPPs we first had to estimate the American 1935 input-output table based on the available 1939 table. We adjusted the row and column totals for the 1939 input-output table to the 1935 gross output and intermediate inputs taken from the 1935 Census of Manufacturing. The changes in the structure of the manufacturing sector could then be translated to the cells of the matrix itself to create as close a fit as possible to the original input-output table. Secondly, we estimated output PPPs for the supplying industries for both countries based on the industry classification of the respective input-output table. From the complete set of unit values - used for the calculation of the gross output PPPs - the quantity and price data for intermediate products (thus excluding the final products) were used to estimate industry output PPPs. Based on the structure of the British manufacturing sector, the Laspeyres output PPPs were then weighted by the flow of goods in the British input-output table to estimate industry and branch specific intermediate input PPPs. The same was done for the U.S.; in this case the resulting PPPs were based on the American structure and Paasche PPPs.
25
Barna, “Experience”; Leontief, The Structure
12
In addition to the gross output PPPs Table 1 also presents the intermediate input PPPs and the resulting double deflated value added PPPs. The Fisher intermediate input PPPs between brackets are based on input unit values derived directly from the manufacturing censuses, whereas all other intermediate input PPPs are derived from the input-output procedure. For the textile and iron and steel trades the intermediate input PPPs constructed by the alternative procedures differ within a margin of less than four percent, which we believe is reassuringly close. Table 1 also shows that PPPs for inputs are different from those for output. The last column of Table 1 gives the ratio of the (Fisher) value added PPP to the (Fisher) gross output PPP. This ratio reflects the efficiency in the use of capital and labour in the production process. A lower PPP for output than for intermediate input (as e.g. for engineering) indicates that the American engineering industries face lower costs (labor costs, capital costs, or profit margins) per unit of output than the U.K. industries; this implies that the U.S. was able to mobilize its labour and capital inputs more efficiently. For three important branches and the manufacturing sector as a whole the value added PPP is substantially lower than the gross output PPP, in these cases single deflation of output will inevitably undervalue U.S. comparative labour productivity. The substantial gaps between the value added and gross output PPPs underline the necessity of estimating intermediate input PPPs on the branch and sectoral level.
The structure of value added, employment and labour productivity An overview of the structure of the British and American manufacturing sector is provided in table 2. The U.K. and U.S. columns for value added and employment show the shares of branches in the manufacturing sector of both countries. The last columns of the value added and employment sections show the size of the American branches relative to the British branches. The U.S. figures for value added were converted into pounds using the (Fisher) value added PPPs of Table 1. In terms of value added, the engineering and food sector constituted the largest share for both countries. However, the greater portion of employment was located in the textile and engineering, shipbuilding and vehicle trades; particularly in Britain the former branches employed a large
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percentage of the working population. We can quantify the measure of similarity between the structures of the manufacturing sector in the two countries by a similarity index.26 This index results in a ratio of 94 percent measured between industries and 98 percent between branches. Table 2 also shows that the U.K. and U.S. textile, leather and clothing trades were the most labour intensive industries, whereas the food and chemicals sectors enjoyed relatively high labour productivity levels. The difference in labour productivity can be explained by the relatively high capital intensity of the latter branches.
The Structure of the Manufacturing Sector, U.K. and U.S. (1935)†
Table 2. Branch / Sector
Textile trades Leather trades Clothing trades Iron and Steel trades Engineering, Shipbuilding trades Non-ferrous Metals trades Food, Drink and Tobacco trades Chemical and Allied trades Clay and Building Materials trades Timber trades Paper trades Miscellaneous trades Total Manufacturing
Value Added (%) U.K. U.S. U.S./ U.K.‡ 13 9 171 1 1 276 7 7 386 9 10 323 21 20 489 3 3 357 17 16 292 8 9 534 5 3 3 4 9 12 513 3 5 474 100 100 363
Employment (%) U.K. U.S. U.S. / U.K. 20 15 118 1 1 176 10 10 163 10 11 174 21 20 150 2 3 197 10 12 193 4 5 203 5 3 95 4 7 294 8 9 185 3 4 205 100 100 162
†) Sources: see Appendix B ‡) The values in national currencies were converted with the (Fisher) double deflated value added PPPs from table 1.
In absolute terms the American branches (except for the clay and building materials trades) employed more people than their British counterparts. In the U.K. 5,158,695 The formula of the similarity index is given below; where Sjb and Sja are the branch/industry share in manufacturing value added in respectively the U.K. and the U.S. The index varies between zero and one, and is lower in case of greater dissimilarity. Source: Timmer, Asian Manufacturing, pp 88-90
26
I
ba
=
∑
m j =1
S bj S aj
∑ (S ) ∑ (S ) m
j =1
b 2 j
m
j =1
a 2 j
14
people were engaged in the manufacturing sector, whereas in the U.S. a total of 8,416,898 workers were employed (1.6 times the employment in the U.K.). The total value added of the British manufacturing sector was £1,187,307,000 while the total value added of the American census data came down to $19,055,728,000 or about £4,324,786,000 using the PPP for total manufacturing (3.6 times the total value added in the U.K.). These statistics already hint at the large productivity lead of the U.S. over the U.K.
5. A new U.S./U.K. productivity comparison for 1935 Table 3 shows the double deflated labour productivity (real value added per worker) estimates resulting from our procedure. We also show a column with value added per worker deflated by the official exchange rate. As was to be expected, the use of the official exchange rate smoothes out the differences in labour productivity across branches. Effects are particularly large in engineering, food and beverages, and paper.
Table 3
Value Added per Worker, U.K. and U.S. (1935)†
Branch / Sector
Textile Trades Leather Trades Clothing Trades Iron and Steel Trades Engineering, Shipbuilding … Non-ferrous Metals Trades Food, Drink and Tobacco Trades Chemical and Allied Trades Clay and Building Materials Trades Timber Trades Paper Trades Miscellaneous Trades Total Manufacturing
Comparative Productivity (% U.S. / U.K.) Rostas This Study‡ Exchange rateζ
144 (136) 157 237 186 (177) 327 182 152 263 278 231 224
15
150 148 223 191 235 156 222 235 222 129 223 226 211
Relative Comparison Rostas / This Study
151
1.05
165 180 268
0.70 0.97 0.82
175 198 197
1.15 0.75
252 203 212-15ξ
0.91 0.88 0.95
†) Sources: Rostas, L. (1948), Comparative;see Appendix B for further details. ‡) The value added per worker estimates for this study were deflated by the ‘input-output’ (Fisher) double deflated value added PPPs listed in table 1. The figures in brackets were deflated by ‘standard’ (Fisher) double deflated value added PPPs based on input UVRs taken directly from the British and American census. ζ) The value added per worker estimates were deflated by the official exchange rate, which was approximately 4.94 U.S. dollars per pound sterling. ξ) The figure for the manufacturing sector as a whole as listed in Rostas, Comparative. Due to the reduced coverage of the Rostas study it is not possible to assign weights to his branch estimates to arrive at the same value for manufacturing as a whole.
In addition to the exchange rate comparison, we also listed the outcome of the 1948 industry-of-origin study by Rostas based on physical quantities in the table.27 Whereas we were able to draw on nearly complete sets for all manufacturing industries in the censuses, Rostas’ choice was dictated by the availability of 31 pairs of industries for which quantity and employment data was available in the statistics for both countries. To make the two studies comparable we took, as far as possible, the same years (mostly 1935) and used an implicit weighting method to aggregate Rostas’ comparative (physical) productivity estimates.28 The last column of table 3, which presents a relative comparison of the two studies, illustrates that on an aggregate level the outcome of the industry-oforigin studies is quite resistant against different research strategies. The index of Rostas’ value added per worker figure for the manufacturing sector as a whole is 212-215, which is fairly close to our own estimate of 224. On the branch level however, there are large differences. The estimates of productivity by Rostas are higher in the food, drink and tobacco industries, but substantially lower in clothing and chemicals. These differences can be traced back to the industry level, where the estimates by Rostas deviate even further from our own. In general the discrepancies can be traced back to both the theoretical objections to the quantity approach - as discussed in section 3 and 4 - and to various additional shortcomings of the method of productivity research as employed by Rostas. In particular his use of different census years for the benchmark estimate poses a problem in practice. 27
Rostas, Comparative This procedure is based on the assumption that the representativity of PPPs of the covered industries for uncovered industries is better than that of productivity in these industries. Implicitly weighted comparative productivity figures can be attained by transforming the comparative productivity figures based on the quantitative approach into implicit PPPs using the available census data. These implicit industry PPPs can then be weighted by value added to obtain implicit adjusted single indicator Value Added PPPs, which in turn can be used to calculate comparative productivity estimates on the branch and sector level. 28
16
Our present estimate reveals a clear American productivity lead in the large tailoring, dressmaking and millinery trade, which raises the overall comparative productivity in the clothing branch significantly compared to the original estimate. The only industry covered by Rostas in the clothing branch was the boots and shoe trade. The relatively low estimate for this industry can most likely be explained by the nonhomogeneity of the end-products for this category. Rostas had to rely on a rather rudimentary conversion factor and in addition had to integrate the sizable American ‘boot and shoe, cut stock and findings’ trades into the industry. The differences in the estimates for the chemicals and allied trades reflect another crucial weakness in the quantitative approach adopted by Rostas. He was not able to deal with the largest section of this branch (chemicals, dyestuffs and drugs) because of its complex structure. As this industry encompasses well over 200 appreciably different products, it was simply not possible for Rostas to find a common conversion factor, or to assign labour to the various products. Consequently Rostas had to omit this industry, even though it is by far the largest industry of the branch. Our new estimate of the chemical and allied trades - which includes the chemicals, dyestuffs and drugs trades and is based on 83 of the major products in this category (see Appendix C for further details) - thus presents a major improvement over the original estimation. Regardless of the differences on the industry level between the present study and Rostas’ comparisons, our estimates do confirm the relatively small productivity gap in the textile, iron and steel, and food, drink and tobacco trades. In addition this study corroborates the substantial productivity lead of the U.S. in the engineering, shipbuilding and vehicles trades. The extent of the American lead in engineering is however undervalued by the method of Rostas, because it does not take the cross-country differences in the comparative price ratios between inputs and outputs into account, which as we noted in section 4, can have a large effect on the comparative productivity estimate. To illustrate this point table 4 below shows the comparative productivity figures for the major industries in the engineering branch based on the different deflation procedures. The first column shows the comparative productivity estimates based on the single deflation of gross output, whereas the second column shows the double deflated
17
value added results. Although the variation in the double deflated figures tend to be rather high across the industries it does show that electrical engineering and the motor and cycle industries are in fact the sources of the American lead in engineering, whereas the British performance in the mechanical engineering sector came very close to the U.S. level.
Table 4
Comparative Productivity in Engineering, U.K. and U.S. (1935)† Comparative Productivity per Worker (% U.S. / U.K.) Single Deflated Input-Output Deflated Gross Output Value Added
Industry / Branch
Mechanical Engineering Electrical Engineering Shipbuilding Motor and Cycle Aircraft Total Engineering
2.18 2.45 1.70 4.39 1.88 2.85
1.18 3.18 2.24 4.62 2.25 3.27
†) Sources: see Appendix B for details.
Overall, the discrepancies between our new estimates and the quantity method challenge studies relying on Rostas’ disaggregated figures. As the study by Rostas is not based on a representative cross-section of the manufacturing sector, any study depending on Rostas’ estimates as the only source of comparative productivity figures for British and American manufacturing industries is undoubtedly affected. Regardless of the shortcomings of his approach though, the comparative productivity estimate by Rostas for the manufacturing sector as a whole is remarkably close to our own estimate. Still, Rostas’ credible figure for the total manufacturing sector is more likely to mirror the hard work and impeccable judgment of Lazlo Rostas than the validity and practicality of the quantity approach.
6. Adding German manufacturing to the productivity comparison The study of comparative productivity in the British and American manufacturing sector can easily be extended to include Germany. Fremdling et al. calculated comparative value
18
added levels, based on newly explored 1936 archival data on German manufacturing together with the British Fifth Census of Production of 1935.29 The authors adjusted for differences in prices for outputs as well as for inputs by applying the double deflation procedure. In addition, both studies rely on an identical industry classification based on the U.K. Census, which makes it feasible to compare the manufacturing sectors of the three largest economies of the interwar period. The double deflated figures of labour productivity per worker for the U.S. and Germany, relative to the U.K. in the year 1935, are given in Figure 2.
Figure 2
Comparative Productivity in Manufacturing, U.K., U.S. and Germany, 1935, 1936; Double Deflation (U.K.=100)†
Comparative Productivity (U.K.=100)
350 300 250 200 150 100
U.K. Germany U.S.
50
Total Manufacturing sector
Miscellaneous trades
Paper trades
Timber trades
Clay and Building Materials trades
Chemical and Allied trades
Food, Drink and Tobacco trades
Non-ferrous Metals trades
Engineering, Shipbuilding trades
Iron and Steel trades
Clothing trades
Leather trades
Textile trades
0
†) Sources: Fremdling et al., “British and German”; see Appendix B for further details.
29
Fremdling et al., “British and German.” For a comparison based on the quantity approach see Broadberry and Fremdling, ” Comparative.”
19
The comparison above reveals that the American labour productivity per worker in the manufacturing sector was, on average, twice as high as in Germany. As with the British and American comparison however, on a disaggregated level the comparative productivity figures deviate substantially from the average for total manufacturing. The American relative performance was much higher in the chemicals and paper industries, in the sizable engineering, shipbuilding and vehicle sector and in food, drink and tobacco. In contrast however, it was nearly at par with the German level of productivity for iron and steel. The German blast furnaces, steelworks and foundries combined were even able to surpass the performance of their American counterparts, which accounts for the high German level of comparative productivity for the iron and steel trades. On the other hand, the American engineering, shipbuilding and vehicle branch outperformed the respective German industries by a wide margin. Only the German electrical engineering industry was able to maintain a productivity level above the sector average. As was to be expected, the comparative level of labour productivity in the German light industries was considerably lower than in the American light industries. Summing up, the figures reveal a large transatlantic productivity gap in engineering, chemicals, and paper. These industries showed not only an above average productivity difference between ‘Europe’ and the United States, but also a much higher real volume of output in the latter. Differences were less pronounced in textiles, while food products and iron and steel reveal a more ambiguous result. Looking at the United Kingdom and Germany only, we see a German labour productivity lead in paper, chemicals, and iron and steel. Britain had a lead in textiles, clothing, and food products.
7. Estimating Hours Worked Now we turn to the issue of labour input. Most historical cross-country productivity comparisons apply the concept of output per worker or value added per worker. However, we think that the concept of value added per man-hour is in fact more relevant here, especially since Field has based his story of fast U.S. interwar growth on John
20
Kendricks estimates of output per hour (and not output per worker).30 For the present study this distinction is of particular importance since weekly actual hours worked declined during the 1930s much faster in the U.S. than in Britain. The practice of worksharing was widespread in the American Depression-economy. If we do not adjust for this we would heavily underestimate U.S. comparative productivity. Colin Clark estimated the average working week in Great Britain in 1935 at 47.8 hours, compared to only 37.2 hours in the United States.31 Likewise, Rostas assumed the average length of the U.K. and U.S. working week to be 47.8 and 36.6 hours respectively.32 The lower levels of American working hours are confirmed in the study of actual hours of work per week by Ethel Jones.33 For the U.K. systematic evidence is more difficult to find.34 There are some occasionally published government statistics which give an idea of the amount of short-time workers and the level of short-time work.35 However, we made estimates of actual hours worked on the basis of information given by Robert Hart, and Michael Huberman and Chris Minns.36 In addition, we took the values for the total annual hours worked in the German manufacturing sector from Statistisches Handbuch vor
Deutschland.37 The actual hours of work per week for the U.K., U.S. and Germany from 1929 up to 1938, are given in figure 3. Figure 3 shows that actual working hours in the American economy declined during the larger part of the 1930s, resulting in an American working week in the manufacturing sector which was much shorter than the British one. From 1929 onwards the British and German working week became only slightly shorter due to the introduction of short-time, but by 1934 the average working week had basically returned to its pre-Depression level. The American average working week on the other hand dropped by nearly 30 percent in the period 1929 to 1934 and it did not attain its predepression level again, not even after the outbreak of the Second World War.
30
Kendrick, Productivity, pp. 466-75. Colin Clark, Conditions, p 68 32 Rostas, Comparative ¸ pp. 29, 43-44, 48. However, he did not adjust for this, although he was well aware of the effects this would have on comparative productivity levels. 33 Jones, "New Estimates"; see also ILO, Year-book, 1939 and the Historical Statistics of the United States. 34 Whiteside and Gillespie, “Deconstructing,” p. 674, 677. 35 Thomas, “Unemployment,” p. 136. 36 Hart, “Hours”; Huberman and Minns, “Hours.” 37 Länderrat des Amerikanische Besatzungsgebiet, Statistisches Handbuch, 1949 31
21
Weekly Hours in Manufacturing, U.K., U.S., and Germany (1929-1938)†
Figure 3 55
Weekly Hours Worked
50
45
Germany U.K.
40
U.S.
35
30 1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
Year
†) Sources: - Germany from Länderrat des Amerikanische Besatzungsgebiet, Statistisches Handbuch, 1949 and Huberman and Minns, “Hours of Work”, p 27. - U.K. from Hart, “Hours” and Colin Clark, Conditions. (See also Metcalf p. 397 1938 = 47.4) - U.S. from Jones, "New Estimates”.
We can also adjust for differences in the number of holidays and vacations and for variations in working hours per branch. The Yearbook of Labour Statistics of 1939 contains detailed statistics on average hours of work per worker per week for several industries and industry-groups for both the U.K. and the U.S. We weighed these outcomes by employment to obtain the familiar branch classification that adheres to the British census of production.38 Data by Huberman and Minns on the number of vacations and holidays for the U.K. and U.S. in 1938 allowed us to construct the total number of annual hours worked. The data on weekly and annual average hours worked in 1935 are presented in table 5 below.
38
ILO, Year-book, 1939
22
Table 5
Weekly and Annual Average Hours Worked, U.K. and U.S. (1935)† U.K. Annual Weekly hours hours worked‡ worked†
Branch / Sector
47.7 48.8 45.4 48.2 48.2 48.2 48.5 48.0 48.0 48.3 48.6 48.2 47.8
Textile Trades Leather Trades Clothing Trades Iron and Steel Trades Engineering, Shipbuilding and Vehicle Trades Non-ferrous Metals Trades Food, Drink and Tobacco Trades Chemical and Allied Trades Clay and Building Materials Trades Timber Trades Paper Trades Miscellaneous Trades Manufacturing Sector
2,250 2,302 2,142 2,274 2,274 2,274 2,288 2,264 2,264 2,278 2,292 2,274 2,255
Weekly hours worked
U.S. Annual hours worked
35.8 38.6 32.2 36.6 36.5 37.1‡ 39.5 38.1 36.5 39.5 38.2 33.9 36.6
1,774 1,915 1,597 1,813 1,809 1,838‡ 1,962 1,892 1,812 1,958 1,896 1,682 1,817
†) Sources: ILO, Year-book, 1939; HMSO Department of Employment and Productivity, British Labour Statistics, 1971; Huberman and Minns, “Hours of Work”. ‡) The sectoral averages - provided by the 1939 Yearbook of Labour Statistics - were used when detailed industry level data for hours worked was unavailable.
Both figure 3 and table 5 illustrate that during the 1930’s the declines in weekly hours were ‘deep, prolonged, and widespread’ in the United States.39 The reasons for the persistence of high unemployment lie beyond the scope of this paper, however we will shortly touch upon the causes of the widespread practice of short-time compared to U.K. and Germany. Bernanke explained the drop of the American workweek and the introduction of work-sharing as an efficient way of firms to react to falling demand: firms cut production by running certain operations only part time; at the same time the work force was left intact by spread-work schedules. Firms recognized that a similar cut in wages would bring workers below their subsistence level, hence real hourly earnings rose, which explains a countercyclical pattern in real wage rates.40 Margo has argued that the legislation connected to the National Industry Recovery Act (1933-1935) promoted
39 40
Margo, “Employment,” p. 48 Bernanke, “Employment,” p. 89
23
worksharing provisions leading to reductions in the length of the workweek. The New Deal legislation as such had created a climate that made wage cutting difficult.41 In Britain short-time working had been a traditional response to trade recessions, and it developed in the 1920s systematically into the so-called OXO-system, an arrangement for days of work (O) and leisure (X).42 The cuts in working time in British firms during the interwar period have been explained by hourly wage rate inertia through centralized wage bargaining or through the benefit-wage ratio. But is was not as widespread and extensive as in the U.S.43
Table 6
Value Added per Worker and per Hour, U.K. and U.S. (1935)†
Branch / Sector Textile Trades Leather Trades Clothing Trades Iron and Steel Trades Engineering, Shipbuilding and Vehicle Trades Non-ferrous Metals Trades Food, Drink and Tobacco Trades Chemical and Allied Trades Clay and Building Materials Trades Timber Trades Paper Trades Miscellaneous Trades Manufacturing Sector
Value added per Worker‡ (% U.S. / U.K.)
Value Added per Hour‡ (% U.S. / U.K.)
144 157 237 186 327 182 152 263
182 190 318 235 410 226 177 316
278 231 224
338 313 279
†) Sources: see table 3 and table 5 for further details. ‡) The value added per worker/man-hour estimates were deflated by the (Fisher) double deflated value added PPPs listed in table 1.
How large are the effects of employment in hours on measured productivity? Table 6 presents the labour productivity per man-hour statistics. The branch specific employment data has been multiplied by the data on annual hours worked from table 5. The result of this is that the average level of labour productivity (in hours) for total manufacturing is 41
Margo, “Microeconomics,” p. 339 Thomas, “Unemployment,” 135-136; Bowden et al, “Underemployment,” p. 97-98. 43 Estimates based on information from Dale, “Interpretation,” p. 89-90 reveal that in 1934 for manufacturing as a whole the effect of short-time schemes on the standard working week was not larger than 3.5 percent. See also Hart, “Hours,” p. 500 42
24
raised by 25 percent, to 279 percent. On the level of branches the rise in labour productivity ranges from 16 percent (food, drink and tobacco trades) up to 39 percent (clothing trades). We can conclude from table 6 that hourly productivity in the U.S. during the 1930 was nearly three times higher than in the U.K. Hourly levels were especially high in the engineering branch, whereas the differences in food were relatively modest. These new outcomes seem difficult to reconcile with the earlier mentioned outcomes of Rostas and the Anglo-American time series extensions by Broadberry based on this benchmark. However, Rostas does mention the possibility that output per manhour was 2.8 times as high in the U.S. as in Britain, when measured in hours.44 Broadberry based the backward and forward extensions on the per worker comparison of Rostas. By making these extrapolations Broadberry implicitly assumed that working hours have moved broadly in similar ways in the U.K. and the U.S. Figure 4 shows the comparative labour productivity for the American and British manufacturing sector over the period 1869-1961, which is similar to the overview of comparative manufacturing productivity in the work of Broadberry.45 On the basis of this graph Broadberry assumed a long term 2:1 ratio in comparative productivity in manufacturing between the U.S. and the U.K. With our new information on differential working hours we extended backward and forward the same time series on output and employment but now adjusted for hours. Figure 4 shows that the level of comparative value added per man hour was slightly below the level of value added per worker in 1889. During the nineteenth century the U.S. indeed had a labour productivity lead of about 2:1 compared to the U.K. From the final decades of the nineteenth century however the comparative American level increased, both in terms of worker and worker-hour. The two series move in unison up to the year 1929. During the 1930s however, the value added per man-hour series does not show the downward movement in comparative labour productivity, which Broadberry observed for the value added per worker series. Instead the hours-line follows the upward trend of the pre-1929 period and continues to rise over de trans-WWII period. After the war there is still a difference between the two series, which persists well into the 1960s.
44 45
Rostas, Comparative, p. 27 Broadberry, Productivity Race, p 2
25
The comparative productivity on a man-hour basis reached a peak slightly above 300 percent in 1953.
Comparative Productivity in Manufacturing, U.K. and U.S. (1889-1989)†
Figure 4.
Comparative Productivity (U.K. = 100)
350
300
250
200
150
100
U.S. VA per Worker U.S. VA per Man-Hour
50
1989
1984
1979
1974
1969
1964
1959
1954
1949
1944
1939
1934
1929
1924
1919
1914
1909
1904
1899
1894
1889
1884
1879
1874
1869
0
Year †) Sources: - Benchmark (1935) from own calculations - Time Series Output and Employment from Broadberry, S. (1997) Productivity Race - U.K. Hours of Work from Huberman andMinns, “Hours of Work”; Hart, “Hours”; Colin Clark, Conditions; ILO, Year-book, 1931, 1939 and 1962; ; The Conference Board and Groningen Growth and Development Centre, Total Economy Database, January 2007, www.ggdc.net - U.S. Hours of Work from Jones, “New Estimates” and Huberman and Minns, “Hours of Work”; The Conference Board and Groningen Growth and Development Centre, Total Economy Database, January 2007, www.ggdc.net
We conclude from this new series that there is a clear trend in the growth of the AngloAmerican productivity gap when we measure actual hours worked. There is no cyclical narrowing of the gap before WWII. This observation is in correspondence with the conclusions reached by Field, who characterized the 1930s in the U.S. as “the most
26
technologically progressive decade of the century”.46 Figure 4 confirms that the postDepression period was an era in which the productivity lead of the U.S. was strengthened further. It was a time of implementation and exploitation of new technologies and practices which were to form the basis of much of the labour and multifactor productivity of the post-war period. We can view from figure 4 that the U.S. comparative productivity based on value added per man-hour reveals an upward trend over the 1889-1961 period. This is a long term process that does not appear to be affected by either the world wars or the Great Depression. During this period of the Second Industrial Revolution U.S. manufacturing increased its productivity lead (measured in hours) over the U.K. from 196 percent in 1889 to 303 percent in 1952, an increase of more than 50 percent. Productivity measured in hours thus gives a fundamentally different picture of the long-term comparative industrial performance of the U.S. We believe that the stylized fact of a 2:1 productivity ratio between the U.S. and the U.K. can only be substantiated when looking at productivity per worker. But we also believe that in transatlantic comparisons it is important to employ the proper measure of productivity based on annual hours worked. Finally we can also look at the long-term comparative level of productivity from the perspective of groups of branches. For this we combined the branches into 5 sectors: 1. food, drink and tobacco; 2. textiles, leather and clothing; 3. chemicals and allied products; 4. ferrous and non-ferrous metals; 5. engineering. As with figure 4 we used the 1935 benchmark level as the central point from which we extended backward and forward the individual series. These series are long-term estimates on comparative real value added per working hour. Figure 5 shows the long-run comparative movements across the sectors from 1900 to 1957. Levels of comparative performance vary widely across the sectors. Food and drink etc. moves initially around 100, but rises to a comparative level of around 200. Engineering was already high in the pre-WW1 period and increased to a level above 400. A very strong comparative U.S. performance took place in chemicals; it rose from 150 to 600. Furthermore the graph shows that in both transwar periods the prewar tendencies in comparative performance were continued after the wars, indicating less strong direct effects of the wars. The 1930s reveal a large increase in food and chemicals and to a lesser extent in engineering. Not only did these 46
See the literature mentioned in the introduction
27
sectors display high productivity growth in the U.S., at the same time the relative size of these industries was also increasing, and to a larger extent than in Great Britain (see Table 7).
Figure 5.
Comparative Productivity by Branch, U.K. and U.S. (1900-1957)†
700 Food, Drink and Tobacco Textile, Leather and Clothing
Comparative Productivity per Hour (U.K. = 100)
600
Chemicals and Allied products Metals, ferrous and nonferrous Engineering
500
400
300
200
100
1955
1950
1945
1940
1935
1930
1925
1920
1915
1910
1905
1900
0
Year
†) Sources: - Benchmark (1935) from own calculations - Time Series Output and Employment from Kendrick, Productivity; Lomax, “Production”. - U.K. Hours of Work see Figure 4 for further details. - U.S. Hours of Work see Figure 4 for further details.
The combination of high levels and growth of productivity in sectors that increased their employment share as well is a central characteristic of the U.S. productivity upsurge during the Second Industrial Revolution. The actual impact of structural shifts within the British and American labour force on comparative productivity can be quantified in a shift-share analysis; an exercise which we will employ in future work.
28
Table 7.
Sectoral Shares of Hours in Manufacturing for Benchmark Years†
U.K. Food, Drink and Tobacco Textile, Leather and Clothing Chemicals and Allied products Metals, ferrous and nonferrous Engineering
1907 8 41 3 13 20
1924 9 37 4 13 23
1930 9 32 4 12 24
1935 10 32 4 12 21
1948 9 22 6 14 31
1957 9 19 7 14 33
U.S. Food, Drink and Tobacco Textile, Leather and Clothing Chemicals and Allied products Metals, ferrous and nonferrous Engineering
1907 11 26 4 13 17
1924 10 21 6 14 24
1929 10 21 6 14 24
1935 13 24 6 14 19
1948 10 17 7 14 30
1957 9 13 7 14 35
†) Sources: see Figure 5 for further details.
8. Explaining the interwar productivity gap During the 1920s and 1930s differences in productivity performance of U.S. and U.K. manufacturing steadily increased. The fundamental long-run forces of this gap have been analysed extensively by Broadberry and Broadberry and Crafts.47 These forces range from factors related to market size, economies of scale, quality of human capital (factors that were all more favourably developed in the U.S.) to differences in mass and standardised production versus flexible production based on shop floor skills. During the interwar period institutional factors also have played a significant role such as the movement away from competition through restrictive practices in the U.K. Adjustment to the innovations of the Second Industrial Revolution was hampered, there was less rapid technical change compared with the U.S., maintaining a low effort equilibrium that was carried over into the postwar period.48 Our new figures suggest that there was more going on: U.S. manufacturing managed to expand those sectors in which it already had a comparative leadership much faster, in some sectors it could take another leap during the crisis. We do not deny that part of this fast acceleration of the American productivity level during the interwar period 47 48
Broadberry, Productivity Race; Broadberry and Crafts, “Britain’s,” Broadberry and Crafts, “Britain’s,” p. 554; Magee, “ Manufacturing,” p. 95.
29
was of a cyclical nature. Claudia Goldin has pointed to mechanisms of selective retention in the 1930s: the workers who were laid off were less productive.49 This could explain the occurrence of rising real wages, the persistence of unemployment and the countercyclicality of labour productivity in the U.S. However, measured within a period of a full cycle between 1929 and 1941 there has been found a positive relationship between a rise in the unemployment rate and a decline in TFP, which suggests a pro-cyclicality of productivity. The role of selective retention is therefore small.50 In general, physical capital deepening does not seem to have been a decisive factor in the interwar productivity growth in the U.S. Field shows on the basis of estimations of Kendrick that rates of TFP growth and of output per hour between 1919 and 1941 were almost identical.51 The story of the American manufacturing industry in the interwar period is that disembodied technical change was responsible for an outward shift of the American production possibility frontier. Anecdotal evidence of important process and product breakthroughs as drivers of productivity advance are mentioned in the literature, such as floor space savings, automatic process control, larger units of installations, thermal efficiency, and improved materials. Future analysis of the new gross output and intermediate input PPPs at industry level, combined with the detailed data on labour and capital inputs will ultimately result in systematic estimates of the comparative levels of TFP for the U.K. and U.S. industries. Besides technical change there was also a change in the composition of firms, within and between industries. Within industries we find examples of productivity improvements directly caused by the Depression itself. Due to the fall in demand weak firms went out of business. The American motor vehicles industry provides an archetypical example of growth of efficiency within an industry. A study by Timothy Bresnahan and Daniel Raff on the basis of an establishment-level panel dataset reveals that the removal of the low productivity tail in the spread of plants was responsible for a one-off change in the composition of the total branch, leading to an increase of the 49
Cited in Field, “ Most,” p. 1409; Bernanke, “Employment,” p. 91 mentions the role of a changing skill mix over the cycle; Margo, “Microeconomics,” pp. 333-341 also mentions the higher age and the lower levels of schooling of the unemployed; see also Margo, “Employment,” p. 46. 50 Bernanke & Parkinson, “Procyclical,” p. 457, find procyclical patterns due to labour hoarding in steel, rubber, and stone, clay and glass. 51 Field, “Impact,” p.5. In contrast, the post-1941 period reveals much larger growth rates of output per hour compared with TFP.
30
average productivity level.52 Only the large plants survived in the Depression years and new entrants had a higher productivity. This evolutionary event was brought on by lower levels of demand and changed technological practice for the industry as a whole. If we calculate from our present figures the comparative level of hourly productivity for motor vehicles between the U.S. and the U.K. we arrive at a real productivity level of 5.8 to 1 (double deflated).53 Likewise we find for 1935 very high levels of productivity in such industries as hosiery (344), blast furnaces (405), electrical engineering (389), chocolate and sugar confectioning (339), malt liquors (225), and rubber (300). Fast comparative productivity advances were manifest in many branches in American manufacturing. Our comparative data show that Field is right in stressing that it is not the Second World War that was the decisive factor in creating the transatlantic gap. The long term forces of the fast productivity growth in the U.S. were in place much earlier, setting the stage for the expansion of those industries that had high comparative productivity levels. The supply shock that was the result of the Depression forms a characteristic part of this process.
9. Conclusions In this paper we presented an industry-of-origin study dealing with the American and British manufacturing sector in the interwar period. We re-examined the Anglo-American comparative labour productivity levels by applying a double deflation methodology. Several conclusions can be drawn. First, on an aggregate level the outcome of the industry-of-origin studies is surprisingly resistant against different research methods; the double deflated value added estimate for comparative productivity in the manufacturing sector was fairly close to the previous estimate by Rostas, which was based on the quantitity approach. On average the comparative American/British manufacturing productivity level was 224 on a per worker basis. Second, on a disaggregate level the 52
Bresnahan and Raff, “Intra-Industry” However, comparative data from the 1935-censuses of both countries reveals additional information that explains the high productivity level. American car manufacturers acquired a much larger percentage of gross output from intermediate inputs and components obtained from industries lower in the chain (70%) against Britain (40%) which points at a more developed pattern of specialisation in the U.S.Lewchuk, pp. 138-42. 53
31
differences in the results from varying research strategies are substantial. The advantages of double deflation and thus adjusting for price levels of intermediate inputs, become particularly evident when looking at cross-industry productivity differences. Adjusting for actual hours worked is essential in the U.S./U.K. comparison because average annual hours worked in both countries diverged a lot in the interwar period. Such an adjustment moves the level of American comparative productivity up to 279 in 1935. It also changes the trend in long term comparative productivity between the two countries, the U.S. steadily moving from a level of 200 around 1900 to a level of 300 in the trans-WWII period. This finding is well in line with recent interpretations of prewar developments in technology and productivity in American manufacturing.
References van Ark, Bart and Timmer, Marcel, “Notes and Communications: Industry Productivity Comparisons,” De Economist (Quarterly Review of the Royal Netherlands Economic Association) 150, No.1 (2002), pp. 95-109 Barna, Tibor, “Experience with input-output analysis in the United Kindom,” In InputOutput Relations, edited by The Netherlands Economic Institute (1953), pp. 123166. Leiden: H.E. Stenfert Kroese N.V. Bernanke, Ben S., “Employment, Hours, and Earnings in the Depression: An Analysis of Eight Manufacturing Industries,” The American Economic Review, Vol. 76, No.1 (1986), pp. 82-109 Bernanke, B.S. and Parkinson, Martin L., “Procyclical Labor Productivity and Competing Theories of the Business Cycle: Some Evidence from Interwar U.S. Manufacturing Industries,” The Journal of Political Economy, Vol. 99, No. 3 (1991), pp. 439-459 Board of Trade, Final Report on the Fifth Census of Production and the Import Duties Act Inquiry, 1935 Board of Trade, Preliminary Reports of the Import Duties Act Inquiry, 1937 Booth, A., ”The manufacturing failure hypothesis and the performance of British industry during the long boom,” Economic History Review, LVI, No. 1 (2003), pp. 1-33 Bowden, S., Higgins, D.M. and Price, C., “A Very Peculiar Practice: Underemployment in Briain During the Interwar Years,” European Review of Economic History, Vol. 10, No. 1 (2006), pp. 89-108 Boyer, George R. and Hatton, Timothy J., “New Estimates of British Unemployment,” The Journal of Economic History, Vol. 62, No. 3 (2002), pp. 643-675 Bresnahan, Timothy F. and Raff, Daniel M.G., “Intra-Industry Heterogeneity and the Great Depression: The American Motor Vehicles Industry,” The Journal of Economic History, Vol. 51, No. 2 (1991), pp. 317-331
32
Broadberry, Stephen N., “How Did the United States and Germany Overtake Britain? A Sectoral Analysis of Comparative Productivity Levels, 1870-1990,” The Journal of Economic History, Vol. 58, No. 2 (1998), pp. 375-407 Broadberry, S. N., The Productivity Race: British Manufacturing in International Perspective, 1850-1990, Cambridge: Cambridge University Press, 1997 Broadberry, S. and Crafts, N., “Britain’s Productivity Gap in the 1930s: Some Neglected Factors,” The Journal of Economic History, Vol. 52, No. 3 (1992), pp. 531-558 Broadberry, S. and Fremdling, R., “Comparative Productivity in British and German Industry, 1907-37.” Oxford Bulletin of Economics and Statistics, Vol. 52, No. 4 (1990), pp. 403-22. Clark, Colin M., The Conditions of Economic Progress, 2nd Edition, London: MacMillan, 1951 Conference Board and Groningen Growth and Development Centre (2007), Total Economy Database, www.ggdc.net Crafts, Nick .F. “Long-run growth.” In The Cambridge Economic History of Modern Britain. Vol II Economic Maturity, 1860-1939, edited by R. Floud and P. Johnson, 1-24. Cambridge: Cambridge University Press, 2004. Dale, J.A., “The Interpretation of the Statistics of Unemployment,” Journal of the Royal Statistical Society, Vol. 97, No. 1 (1934), pp. 85-113 Darby, Michael R., “Three-and-a-Half Million U.S. Employees Have Been Mislaid: Or, an Explanation of Unemployment, 1934-1941,” The Journal of Political Economy, Vol. 84, No. 1 (1976), pp.1-16 Department of Employment and Productivity, British Labour Statistics: Historical Abstract 1886-1968, London: Her Majesty’s Stationery Office, 1971 Eichengreen, Barry., “The British economy between the wars,” In The Cambridge Economic History of Modern Britain. Vol II Economic Maturity, 1860-1939, edited by R. Floud and P. Johnson, pp. 314-343. Cambridge: Cambridge University Press, 2004. Field, Alexander J., “The Most Technologically Progessive Decade of the Century,” The American Economic Review 93, no. 4 (2003), 1399-1413 Field, A. J., “Technological Change and U.S. Productivity Growth in the Inerwar Years,” The Journal of Economic History, Vol. 66, No. 1 (2006), pp. 203-236 Field, A.J., “The origins of U.S. total factor productivity growth in the golden age,” Cliometrica Vol. , No. 1 (2007), pp. 63-90 Field, A.J., “The equipment hypothesis and U.S. economic growth,” Explorations in Economic History, Vol. 44 (2007), pp. 43-58 Fremdling, Rainer., de Jong, Herman, and Timmer, Marcel., “Censuses Compared. A New Benchmark for British and German Manufacturing 1935/1936,” Research Memorandum GD-90 (2007), Groningen Growth and Development Centre, www.ggdc.net Fremdling, R., de Jong, H. and Timmer, M., “British and German Manufacturing Productivity Compared”, The Journal of Economic History 67, No. 2 (2007), pp. 350-378 Gordon, Robert J., “U.S. Economic Growth since 1870: One Big Wave?” The American Economic Review Vol. 89, Nr. 2 (1999), pp. 123-128
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Hart, R., “Hours and Wages in the Depression: British Engineering 1926-1938”, Explorations in Economic History, Vol. 38 (2001), pp. 478-502. Huberman, M. and Minns, C., “Hours of Work in Old and New Worlds: The Long View, 1870-2000”, Working Paper (2005), Montreal: Universite de Montreal International Labour Office, The ILO Year-book, Geneva: International Labour Office, 1931 International Labour Office, Year-book of Labour Statistics, Geneva: International Labour Office, 1939 International Labour Office, Year-book of Labour Statistics, Geneva: International Labour Office, 1962 Jones, Ethel B., "New Estimates of Hours of Work per Week and Hourly Earnings, 19001957", The Review of Economics and Statistics 45, No. 4 (1963), pp. 374-385 Kendrick, John. Productivity Trends in the United States. Princeton, NJ: Princeton University Press, 1961 Länderrat des Amerikanische Besatzungsgebiet, Statistisches Handbuch vor Deutschland 1928-1944, Munchen: Franz Ehrenwirth-Verlag, 1949 Leontief, W., The Structure of the American Economy, 1919-1939, New York : Oxford University Press, 1951 Lewchuk, W.. “The Motor Vehicle Industry” in B. Elbaum and W. Lazonick (eds.) The Decline of the British Economy. Oxford: Oxford University Press, pp. 135-161, 1986 Lomax, K.S. “Production and Productivity Movements in the United Kingdom since 1900,” Journal of the Royal Statistical Society, Series A, 122 (1959), pp. 185-210. Maddison, Angus., Monitoring the World Economy 1820-1992, Paris: Development Center of the OECD, 1995 Maddison, A., The World Economy: A Millennial Perspective, Paris: Development Center of the OECD, 2001 Magee, Gary B., “Manufacturing and technological change.” In The Cambridge Economic History of Modern Britain. Vol II Economic Maturity, 1860-1939, edited by R. Floud and P. Johnson, pp. 74-98. Cambridge: Cambridge University Press, 2004 Margo, Robert A., “The Microeconomics of Depression Unemployment,” The Journal of Economic History, Vol. 51, No. 2 (1991), pp. 333-341 Margo, Robert A. “Employment and Unemployment,” The Journal of Economic Perspectives, Vol. 7, No. 2 (1993), pp. 41-59 Metcalf, David, Nickell, Stephen J. and Floros, Nicos “Still Searching for an Explanation of Unemployment in Interwar Britain,” The Journal of Political Economy, Vol. 90, No. 2 (1982), pp. 386-399 Paige, D. and Bombach, G., A Comparison of National Output and Productivity of the United Kingdom and the United States, Paris: Organization for European Economic Cooperation, 1959 Rostas, L., Comparative Productivity in British and American Industry, Cambridge: Cambridge University Press, 1948 Sutch, Richard and Carter, Susan B., Historical Statistics of the United States, New York: Cambridge University Press, 2006
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Thomas, Mark,, “Labour Market Structure and the Nature of Unemployment in Interwar Britain,” In Interwar Unemployment in International Perspective, edited by Barry Eichengreen and T.J. Hatton, pp. 97-148. Dordrecht, Boston, London: Kluwer Academic Publishers, 1988 Timmer, Marcel P., The Dynamics of Asian Manufacturing: A Comparative Perspective, 1963-1993, Eindhoven: Universiteitsdrukkerij, Eindhoven University of Technology, 1999United States Department of Commerce, Biennial Census of Manufactures, Washington: U.S. Government Printing Office, 1935 United States Department of Commerce, Sixteenth Decennial Census of the United States, Washington: U.S. Government Printing Office, 1940 Whiteside, Noel, and James A. Gillespie, “Deconstructing Unemployment: Developments in Britain in the Interwar Years,” The Economic History Review, New Series, Vol. 44, No. 4 (1991), pp. 665-682
35
APPENDIX A: Comparing the British and American Censuses The British enquiry of 1935 covers the whole of Great Britain and Northern Ireland, and includes all industrial operations in the United Kingdom. Following the method adopted at the 1930 census, detailed returns were not obtained from firms employing not more than 10 persons as a yearly average; the only information required from these firms was a statement of the nature of their business and the average number of their male and female employees in the year. From this data Rostas estimated that about 55,200 firms, employing 536,600 persons, were excluded from the U.K. census.1 The average number of operatives employed during the year, covered by the census, was 4,482,600, whereas the number of administrative, clerical and technical staff employed amounted to approximately 675,000. The U.S. census covers the 48 contiguous states of the mainland of America and the District of Columbia (thus excluding Alaska and Hawaii), and it represents the calendar year’s 1935 operations. All establishments that had been engaged in manufacturing, printing or publishing during any part of 1935, and whose production during the year had been valued at $5,000 or more, were required to participate in the inquiry.2 For the U.S. census, the reported average number of operatives and staff employed were 7,346,800 and 1,070,100 respectively. The less stringent exemption levels of the U.K. census allowed for a greater number of small firms to be excluded from the figures for Great Britain, which will undoubtedly influence the levels of comparative productivity. In line with the estimate by Fremdling et al., this would result in a downward bias of average productivity for U.S. manufacturing as a whole vis-à-vis the U.K. of 2 percent at maximum.3 Even though the terminology employed by the British and the Americans differs slightly, the concepts of gross output, intermediate input and value added are equivalent for both censuses. The gross output is the ex-factory value of products (the selling value at the factory or plants), whereas intermediate input represents the cost of materials, fuel 1
Rostas, Comparative¸ pp. 24-25. As the value of production per employee was $5,450 in 1935, the scope of the U.S. census is considerably wider than the British census. The American census did not require the exempted firms to produce any information regarding their total workforce or the nature of their business however, making it difficult to determine the percentage of the workforce that was excluded from the survey. 3 Fremdling et al, “British and German.” 2
36
and contract work. The net output, or value added, is the figure which results from the deduction of the intermediate input from the total value of gross output. This figure constitutes the sum of wages, salaries, rent, royalties, rates and taxes, depreciation of plant and machinery, advertisement and selling expenses and all other similar charges, as well as profits. In some cases, excise duties and consumer taxes were included in the ex-factory value of products. To obtain a comparable measure of productivity at the industry level, we deducted these excises from the value of gross output. For the U.K., we subtracted excises on silk and artificial silk, sugar and glucose, beer, aerated waters, tobacco, chemicals, dyestuffs and drugs, matches and printing. In addition we adjusted the gross output value of tobacco for the U.S. All values of the excise duties have been taken from the respective censuses, with the sole exception of the U.K. excise on tobacco, which has been based on the estimate in the study of British and German manufacturing productivity by Fremdling et al.4
4
Ibid.
37
APPENDIX B.1: Census 1935 UNITED KINGDOM U.K. Census 1935 Industry / Branch
(1)
Average number of operatives employed (2) No.
Wages
Administrative, clerical and technical staff
Salaries
(3) £ 000
(4) No.
(5) £ 000
Average number of persons employed (6) No.
Value of products
(7) £ 000
Cost of materials Value added (excess and contract of col. (7) over col work (8)) (8) £ 000
(9) £ 000
Value added per person employed (10) £
Textile Trades Cotton Trade Wool and Hair Trade Silk and Artificial Silk Trade Linen and Hemp Trade Jute Trade Hosiery Trade Textile Finishing Trade Lace Trade Rope, Twine and Net Trade Canvas Goods and Sack Trade Asbestos Goods and Engine Boiler Packing Trade Flock, Rag and Packing Trade Roofing Felts Trade
343,067 231,257 76,265 65,620 23,264 105,622 89,620 14,469 13,956 7,699 7,727 9,151 1,196
28,341 21,158 8,020 4,233 1,981 9,372 9,948 1,490 997 650 954 823 166
12,817 15,010 5,560 3,532 926 9,651 10,464 1,873 1,320 1,145 1,818 1,425 406
… … … … … … … … … … … … …
355,884 246,267 81,825 69,152 24,190 115,273 100,084 16,342 15,276 8,844 9,545 10,576 1,602
145,654 131,696 34,019 24,026 8,079 39,486 30,462 7,155 5,536 5,447 4,980 6,034 1,302
104,027 87,418 19,920 16,963 5,173 22,224 12,111 4,320 3,360 3,998 2,002 4,146 711
41,627 44,278 14,099 7,063 2,906 17,262 18,351 2,835 2,176 1,449 2,978 1,888 591
117 180 172 102 120 150 183 173 142 164 312 179 369
29,350 15,756
3,717 1,252
3,367 2,060
… …
32,717 17,816
28,684 5,676
20,611 3,081
8,073 2,595
247 146
323,590 114,106 27,383 9,565 6,295 2,435
26,263 11,970 2,849 772 902 207
38,744 8,628 2,705 691 1,352 392
… … … … … …
362,334 122,734 30,088 10,256 7,647 2,827
116,770 42,017 10,719 3,036 5,484 1,090
64,854 21,936 5,757 1,649 3,234 691
51,916 20,081 4,962 1,387 2,250 399
143 164 165 135 294 141
14,551 122,848 99,234 87,641 50,845 24,593 21,067 22,555 9,723 11,333 1,181
2,334 19,335 12,976 8,504 5,284 3,375 2,681 2,307 901 1,003 142
1,264 12,426 10,409 10,137 5,938 3,794 2,360 2,953 1,086 1,129 218
… … … … … … … … … … …
15,815 135,274 109,643 97,778 56,783 28,387 23,427 25,508 10,809 12,462 1,399
21,047 101,792 39,018 35,931 21,357 16,589 15,723 7,955 3,623 3,203 422
16,964 68,129 16,160 17,925 10,722 9,666 9,953 3,028 1,245 1,139 135
4,083 33,663 22,858 18,006 10,635 6,923 5,770 4,927 2,378 2,064 287
258 249 208 184 187 244 246 193 220 166 205
Leather Trades Leather Tanning and Dressing Trade Leather Goods Trade
Clothing Trades Tailoring, Dressmaking and Millinery Trade Boot and Shoe Trade Hat and Cap Trade Glove Trade Fur Trade Umbrella and Walking Stick Trade
Iron and Steel Trades Iron and Steel Blast Furnaces Iron and Steel Smelting and Rolling Trade Iron and Steel Foundries Hardware, hollow-ware and tinware Trade Chain, Nail and Screw Trade Wrought Iron and Steel Tube Trade Wire Trade Tools Trade Cutlery Trade Needle, Pin and Metal Smallwares Trade Firearms Trade
38
U.K. Census 1935 Industry / Branch
(1)
Average number of operatives employed (2) No.
Wages
Administrative, clerical and technical staff
Salaries
(3) £ 000
(4) No.
(5) £ 000
Average number of persons employed (6) No.
Value of products
(7) £ 000
Cost of materials Value added (excess and contract of col. (7) over col work (8)) (8) £ 000
(9) £ 000
Value added per person employed (10) £
Engineering, Shipbuilding and Vehicles Trades Mechanical Engineering Trade Electrical Engineering Trade Shipbuilding Trade Motor and Cycle Trade Aircraft Trade Railway Carriage and Wagon Building Trade Carriage Cart and Wagon Trade
360,052 192,992 75,058 242,240 29,143 18,200 5,444
48,510 22,749 10,383 36,637 4,449 2,603 597
72,759 54,956 6,962 37,508 5,889 2,451 709
… … … … … … …
432,811 247,948 82,020 279,748 35,032 20,651 6,153
171,788 106,853 35,814 151,026 13,919 9,757 2,261
73,761 49,509 19,890 86,648 5,467 5,650 1,171
98,027 57,344 15,924 64,378 8,452 4,107 1,090
226 231 194 230 241 199 177
48,095 1,893 30,769 21,320 3,519
6,691 286 3,276 2,214 367
7,195 474 4,055 4,267 510
… … … … …
55,290 2,367 34,824 25,587 4,029
54,592 31,182 11,542 9,194 1,412
37,792 30,155 4,787 4,577 664
16,800 1,027 6,755 4,617 748
304 434 194 180 186
22,843 83,414 36,495 61,924 40,031 15,723 11,527 14,653 4,974 5,965 1,564 43,946 3,235 32,026 35,695
3,499 10,766 3,350 5,887 3,676 1,917 1,434 2,377 538 735 269 6,990 478 3,473 4,439
7,292 27,223 7,506 12,245 9,939 3,972 3,558 1,854 569 3,097 281 11,863 913 9,158 7,164
… … … … … … … … … … … … … … …
30,135 110,637 44,001 74,169 49,970 19,695 15,085 16,507 5,543 9,062 1,845 55,809 4,148 41,184 42,859
65,125 63,986 16,867 36,804 36,762 34,733 28,740 42,225 4,324 10,461 993 67,100 12,006 63,157 42,633
53,175 35,670 7,681 19,237 20,993 28,383 21,884 36,962 3,312 6,880 222 23,090 8,669 43,990 14,253
11,950 28,316 9,186 17,567 15,769 6,350 6,856 5,263 1,012 3,581 771 44,010 3,337 19,167 28,380
397 256 209 237 316 322 454 319 183 395 418 789 804 465 662
Non-ferrous Metals Trades Aluminum, Copper, Brass, Lead and Tin Smelting and Rolling Trade Gold and Silver Refining Trade Finished Brass Trade Plate and Jewellery Trade Watch and Clock Trade
Food, Drink and Tobacco Trades Grain Milling and Rice Cleaning Trade Bread Trade Biscuit Trade Chocolate and Sugar Confectionery Trade Preserved Foods Trade Meat Curing and Sausage Trade Butter, Cheese, Condensed Milk and Margarine Trade Sugar and Glucose Trade Fish Curing Trade Feeds Trade Ice Trade Malt Liquors Trade Distilled, Rectified and Blended Liquors Trade Waters, Cider, Vinegar and Wine Trade Tobacco Trade
39
U.K. Census 1935 Industry / Branch
(1)
Average number of operatives employed (2) No.
Wages
Administrative, clerical and technical staff
Salaries
(3) £ 000
(4) No.
(5) £ 000
Average number of persons employed (6) No.
Value of products
(7) £ 000
Cost of materials Value added (excess and contract of col. (7) over col work (8)) (8) £ 000
(9) £ 000
Value added per person employed (10) £
Chemical and Allied Trades Chemicals, Dyestuffs and Drugs Trade Fertiliser, Disinfectant and Glue Trade Soap, Candle and Perfumery Trade Paint, Colour and Varnish Trade Seed Crushing Trade Oil and Tallow Trade Petroleum Refining Trade Explosives and Fireworks Trade Starch and Polishes Trade Match Trade Ink, Gum and Typewriter Requisites Trade
79,449 7,440 20,437 15,526 9,735 5,896 4,326 8,420 6,317 3,384 3,180
10,714 960 2,225 2,074 1,434 792 714 1,053 783 398 548
21,165 2,179 8,677 9,367 1,807 3,821 663 1,450 2,405 383 1,819
… … … … … … … … … … …
100,614 9,619 29,114 24,893 11,542 9,717 4,989 9,870 8,722 3,767 4,999
75,478 7,348 26,308 22,140 22,625 17,644 9,159 5,566 7,126 2,235 4,275
34,938 4,380 13,140 11,294 18,203 11,980 5,815 2,255 2,821 718 1,728
40,540 2,968 13,168 10,846 4,422 5,664 3,344 3,311 4,305 1,517 2,547
403 309 452 436 383 583 670 335 494 403 510
150,338 40,818 8,278 28,919
115,445 5,058 1,359 4,020
10,273 5,383 1,942 3,487
… … … …
160,611 46,201 10,220 32,406
42,145 17,209 9,706 15,875
12,851 6,649 3,938 7,411
29,294 10,560 5,768 8,464
182 229 564 261
59,166 100,940 2,508 10,562
7,247 11,525 330 1,159
8,908 11,554 267 989
… … … …
68,074 112,494 2,775 11,551
32,180 40,454 1,622 4,414
18,392 19,657 1,012 2,341
13,788 20,797 610 2,073
203 185 220 179
92,544 5,082 145,053 37,761 49,070 6,714
10,538 581 20,879 3,657 12,869 626
9,103 1,014 24,363 6,961 30,384 918
… … … … … …
101,647 6,096 169,416 44,722 79,454 7,632
54,544 3,264 57,336 15,730 50,772 2,518
30,692 1,277 19,348 7,184 12,964 1,038
23,852 1,987 37,988 8,546 37,808 1,480
235 326 224 191 476 194
Clay and Building Materials Trades Brick,Fireclay, China and Earthenware Trade Glass Trade Cement Trade Building Materials Trade
Timber Trades Saw-mill Products Trade Furniture and Basketware Trade Coopering Trade Wooden Crates, Cases and Boxes Trade
Paper Trades Paper and Cardboard Trade Wallpaper Trade Printing, Bookbinding, Stereotyping and Engraving Trade Manufactured Stationery Trade Printing and Publication of Newspapers and Periodicals Pens, Pencils and Artists' Materials Trade
40
U.K. Census 1935 Industry / Branch
(1)
Average number of operatives employed (2) No.
Wages
Administrative, clerical and technical staff
Salaries
(3) £ 000
(4) No.
(5) £ 000
Average number of persons employed (6) No.
Value of products
(7) £ 000
Cost of materials Value added (excess and contract of col. (7) over col work (8)) (8) £ 000
(9) £ 000
Value added per person employed (10) £
Miscellaneous Trades Rubber Trade Scientific Instruments, Appliances and Apparatus Trade Coke and By-products Trade Linoleum and Oilcloth Trade Musical Instruments Trade Brush and Brooms Trade Games and Toys Trade Sports Requisites Trade Manufactured Abrasives Trade
45,870 24,544 12,879 10,809 9,898 8,552 9,868 7,119 2,393
5,373 2,949 2,035 1,355 1,276 765 839 767 368
9,723 5,515 1,182 1,646 1,332 2,419 1,039 1,134 739
… … … … … … … … …
55,593 30,059 14,061 12,455 11,230 10,971 10,907 8,253 3,132
28,069 11,522 16,495 9,145 4,312 3,548 2,993 2,919 2,572
13,736 4,767 12,340 4,611 1,756 1,700 1,380 1,305 1,154
14,333 6,755 4,155 4,534 2,556 1,848 1,613 1,614 1,418
258 225 295 364 228 168 148 196 453
21,164 1,167 768
… 97 80
821 104 84
… … …
21,985 1,271 852
13,925 406 1,439
9,011 148 966
4,914 258 473
224 203 555
4,482,598
616,390
674,989
…
5,157,587
2,694,286
1,512,624
1,181,662
229
Unassigned Trades Tinplate Trade Incandescent Mantles Trade Cinematograph Film Printing Trade
Total Manufacturing
Source(s): Board of Trade, Final Report on the Fifth Census of Production and the Import Duties Act Inquiry , 1935
41
APPENDIX B.2: Census 1935 UNITED STATES U.S. Census 1935 Industry / Branch
(1)
Average number of operatives employed (2) No.
Wages
Administrative, clerical and technical staff
Salaries
(3) $ 000
(4) No.
(5) $ 000
Average number of persons employed (6) No.
Value of products
(7) $ 000
Cost of materials Value added (excess and contract of col. (7) over col work (8)) (8) $ 000
(9) $ 000
Value added per person employed (10) $
Textile Trades Cotton Trade Wool and Hair Trade Silk and Artificial Silk Trade Linen and Hemp Trade Jute Trade Hosiery Trade Textile Finishing Trade Lace Trade Rope, Twine and Net Trade Canvas Goods and Sack Trade Asbestos Goods and Engine Boiler Packing Trade Flock, Rag and Packing Trade Roofing Felts Trade
387,891 193,722 176,458 1,754 4,595 259,661 86,608 7,858 12,260 17,832 14,396 9,245 3,576
251,061 179,385 146,172 1,354 3,521 212,798 80,470 8,686 9,074 14,312 14,035 7,347 3,438
13,460 11,286 10,083 211 413 16,624 10,312 952 1,174 3,081 2,346 1,355 398
29,669 28,839 21,839 419 1,059 36,494 24,286 2,127 2,841 6,668 4,994 3,597 969
401,351 205,008 186,541 1,965 5,008 276,285 96,920 8,810 13,434 20,913 16,742 10,600 3,974
1,049,211 822,263 539,385 5,607 16,294 773,950 286,001 27,528 46,956 147,605 62,421 66,022 23,697
637,731 487,207 257,775 3,439 7,360 421,085 130,453 10,940 23,710 106,766 28,917 42,217 13,500
411,480 335,056 281,610 2,168 8,934 352,865 155,547 16,588 23,247 40,839 33,503 23,805 10,197
1,025 1,634 1,510 1,103 1,784 1,277 1,605 1,883 1,730 1,953 2,001 2,246 2,566
50,877 29,680
55,683 26,427
3,946 4,438
10,957 8,852
54,823 34,118
308,345 132,504
197,970 69,722
110,375 62,782
2,013 1,840
517,188 220,388 26,862 17,858 18,944 2,186
448,650 189,130 27,718 12,988 28,601 1,712
46,029 16,210 2,457 1,130 4,298 246
101,828 32,368 5,609 2,161 9,833 555
563,217 236,598 29,319 18,988 23,242 2,432
2,139,415 755,451 107,322 47,071 165,124 10,086
1,251,508 409,316 55,413 23,757 95,091 6,140
887,907 346,135 51,909 23,314 70,033 3,946
1,576 1,463 1,770 1,228 3,013 1,622
15,178 400,327 102,499 130,074 48,252 10,720 46,715 18,974 13,715 10,104 4,855
18,916 484,270 104,746 133,127 50,754 11,793 49,878 20,078 13,532 9,494 5,499
1,521 39,190 15,234 19,377 7,622 1,070 6,292 3,467 1,758 1,190 614
3,813 92,560 30,301 42,197 16,953 2,937 14,651 7,051 4,304 2,980 1,079
16,699 439,517 117,733 149,451 55,874 11,790 53,007 22,441 15,473 11,294 5,469
374,651 2,163,626 410,865 709,440 233,150 73,849 244,987 75,373 51,171 32,830 13,027
300,648 1,239,763 159,978 396,769 119,916 42,001 124,180 25,079 12,591 9,288 3,388
74,004 923,863 250,887 312,671 113,234 31,848 120,807 50,294 38,580 23,541 9,639
4,432 2,102 2,131 2,092 2,027 2,701 2,279 2,241 2,493 2,084 1,762
Leather Trades Leather Tanning and Dressing Trade Leather Goods Trade
Clothing Trades Tailoring, Dressmaking and Millinery Trade Boot and Shoe Trade Hat and Cap Trade Glove Trade Fur Trade Umbrella and Walking Stick Trade
Iron and Steel Trades Iron and Steel Blast Furnaces Iron and Steel Smelting and Rolling Trade Iron and Steel Foundries Hardware, hollow-ware and tinware Trade Chain, Nail and Screw Trade Wrought Iron and Steel Tube Trade Wire Trade Tools Trade Cutlery Trade Needle, Pin and Metal Smallwares Trade Firearms Trade
42
U.S. Census 1935 Industry / Branch
(1)
Average number of operatives employed (2) No.
Wages
Administrative, clerical and technical staff
Salaries
(3) $ 000
(4) No.
(5) $ 000
Average number of persons employed (6) No.
Value of products
(7) $ 000
Cost of materials Value added (excess and contract of col. (7) over col work (8)) (8) $ 000
(9) $ 000
Value added per person employed (10) $
Engineering, Shipbuilding and Vehicles Trades Mechanical Engineering Trade Electrical Engineering Trade Shipbuilding Trade Motor and Cycle Trade Aircraft Trade Railway Carriage and Wagon Building Trade Carriage Cart and Wagon Trade
671,915 277,834 44,830 392,894 11,384 21,481 1,592
823,419 300,300 55,422 550,628 14,893 25,756 1,284
119,077 59,210 6,491 37,924 3,547 3,079 266
253,393 123,042 14,887 77,480 6,582 5,974 483
790,992 337,044 51,321 430,818 14,931 24,560 1,858
2,783,235 1,470,578 154,900 3,965,100 45,347 100,542 6,845
1,084,733 633,698 60,487 2,830,051 14,015 61,710 3,683
1,698,502 836,880 94,413 1,135,048 31,332 38,832 3,162
2,147 2,483 1,840 2,635 2,098 1,581 1,702
129,607 1,559 17,483 36,191 20,042
144,043 1,720 18,197 38,589 20,608
21,505 585 3,736 6,734 2,613
45,823 1,472 7,611 13,234 5,057
151,112 2,144 21,219 42,925 22,655
1,246,915 79,801 91,043 149,790 68,186
878,441 72,708 42,375 61,027 25,306
368,474 7,092 48,668 88,762 42,880
2,438 3,308 2,294 2,068 1,893
43,747 191,848 29,241 62,715 116,298 138,707 49,733 26,008 13,335 11,606 19,032 40,608 14,035 23,052 90,543
45,379 226,923 25,888 49,664 70,612 156,334 50,178 24,782 6,310 11,068 20,635 62,963 12,888 23,103 59,448
10,487 19,278 2,918 7,545 10,206 26,187 15,710 3,767 972 3,821 7,551 8,834 2,736 8,156 5,046
22,552 35,168 6,172 16,058 19,200 51,703 26,052 7,197 1,949 7,281 14,261 23,457 5,181 17,970 11,881
54,234 211,126 32,159 70,260 126,504 164,894 65,443 29,775 14,307 15,427 26,583 49,442 16,771 31,208 95,589
1,147,645 1,084,805 182,608 400,702 649,644 2,798,097 1,013,742 498,655 60,588 288,662 128,385 495,148 252,005 272,123 615,518
903,123 594,799 89,313 235,084 409,146 2,387,958 762,522 425,617 39,192 230,588 28,021 196,221 133,202 111,317 331,136
244,523 490,006 93,296 165,618 240,498 410,140 251,219 73,038 21,396 58,073 100,365 298,928 118,802 160,806 284,382
4,509 2,321 2,901 2,357 1,901 2,487 3,839 2,453 1,496 3,764 3,776 6,046 7,084 5,153 2,975
Non-ferrous Metals Trades Aluminum, Copper, Brass, Lead and Tin Smelting and Rolling Trade Gold and Silver Refining Trade Finished Brass Trade Plate and Jewellery Trade Watch and Clock Trade
Food, Drink and Tobacco Trades Grain Milling and Rice Cleaning Trade Bread Trade Biscuit Trade Chocolate and Sugar Confectionery Trade Preserved Foods Trade Meat Curing and Sausage Trade Butter, Cheese, Condensed Milk and Margarine Trade Sugar and Glucose Trade Fish Curing Trade Feeds Trade Ice Trade Malt Liquors Trade Distilled, Rectified and Blended Liquors Trade Waters, Cider, Vinegar and Wine Trade Tobacco Trade
43
U.S. Census 1935 Industry / Branch
(1)
Average number of operatives employed (2) No.
Wages
Administrative, clerical and technical staff
Salaries
(3) $ 000
(4) No.
(5) $ 000
Average number of persons employed (6) No.
Value of products
(7) $ 000
Cost of materials Value added (excess and contract of col. (7) over col work (8)) (8) $ 000
(9) $ 000
Value added per person employed (10) $
Chemical and Allied Trades Chemicals, Dyestuffs and Drugs Trade Fertiliser, Disinfectant and Glue Trade Soap, Candle and Perfumery Trade Paint, Colour and Varnish Trade Seed Crushing Trade Oil and Tallow Trade Petroleum Refining Trade Explosives and Fireworks Trade Starch and Polishes Trade Match Trade Ink, Gum and Typewriter Requisites Trade
156,243 20,726 24,286 29,514 15,576 8,653 77,402 11,757 4,380 5,075 3,014
166,500 14,501 24,524 34,123 8,561 9,734 109,611 12,077 4,556 4,693 3,902
38,124 3,878 6,795 11,124 2,713 2,751 14,709 1,706 2,330 420 1,326
90,003 7,743 15,064 24,963 5,232 6,405 33,841 4,117 5,656 798 3,672
194,367 24,604 31,081 40,638 18,289 11,404 92,111 13,463 6,710 5,495 4,340
1,328,512 168,547 363,416 431,811 248,152 126,555 1,838,622 73,479 61,250 30,440 41,549
562,728 108,441 186,356 237,317 209,349 79,616 1,478,225 29,827 25,956 19,039 21,655
765,784 60,106 177,060 194,494 38,803 46,939 360,397 43,652 35,294 11,401 19,895
3,940 2,443 5,697 4,786 2,122 4,116 3,913 3,242 5,260 2,075 4,584
73,933 77,825 24,080 35,436
63,114 82,339 24,348 35,452
7,173 7,781 3,125 7,283
15,255 17,456 7,651 13,997
81,106 85,606 27,205 42,719
179,896 352,664 146,705 204,368
56,863 139,171 51,849 90,977
123,032 213,492 94,857 113,392
1,517 2,494 3,487 2,654
304,358 170,354 9,879 40,016
225,785 143,498 7,982 30,833
22,767 21,220 790 4,562
42,405 40,403 1,854 10,397
327,125 191,574 10,669 44,578
750,331 553,095 46,556 135,092
317,854 261,682 29,970 63,759
432,476 291,413 16,586 71,333
1,322 1,521 1,555 1,600
184,300 4,265 186,158 48,525 118,684 9,312
186,450 4,486 253,482 46,418 192,890 8,000
22,324 623 54,516 8,774 115,765 1,877
56,427 1,496 124,953 21,044 223,872 3,808
206,624 4,888 240,674 57,299 234,449 11,189
1,196,039 19,658 972,176 322,184 1,192,819 40,318
703,268 9,890 310,099 180,063 302,954 15,260
492,771 9,768 662,077 142,122 889,865 25,058
2,385 1,998 2,751 2,480 3,796 2,239
Clay and Building Materials Trades Brick,Fireclay, China and Earthenware Trade Glass Trade Cement Trade Building Materials Trade
Timber Trades Saw-mill Products Trade Furniture and Basketware Trade Coopering Trade Wooden Crates, Cases and Boxes Trade
Paper Trades Paper and Cardboard Trade Wallpaper Trade Printing, Bookbinding, Stereotyping and Engraving Trade Manufactured Stationery Trade Printing and Publication of Newspapers and Periodicals Pens, Pencils and Artists' Materials Trade
44
U.S. Census 1935 Industry / Branch
(1)
Average number of operatives employed (2) No.
Wages
Administrative, clerical and technical staff
Salaries
(3) $ 000
(4) No.
(5) $ 000
Average number of persons employed (6) No.
Value of products
(7) $ 000
Cost of materials Value added (excess and contract of col. (7) over col work (8)) (8) $ 000
(9) $ 000
Value added per person employed (10) $
Miscellaneous Trades Rubber Trade Scientific Instruments, Appliances and Apparatus Trade Coke and By-products Trade Linoleum and Oilcloth Trade Musical Instruments Trade Brush and Brooms Trade Games and Toys Trade Sports Requisites Trade Manufactured Abrasives Trade
114,681 51,907 36,776 10,058 8,805 10,976 20,293 9,979 6,776
133,715 57,884 49,625 12,304 8,738 9,079 16,489 9,308 8,351
16,845 14,275 9,426 1,151 1,446 1,769 2,565 1,688 1,917
35,700 30,540 18,620 2,644 2,764 3,868 5,213 3,113 4,456
131,526 66,182 46,202 11,209 10,251 12,745 22,858 11,667 8,693
677,659 279,344 589,584 86,719 26,633 56,430 67,668 38,009 53,867
368,582 109,893 281,815 47,126 10,132 26,069 31,071 17,628 20,732
309,077 169,451 307,769 39,593 16,502 30,361 36,596 20,381 33,135
2,350 2,560 6,661 3,532 1,610 2,382 1,601 1,747 3,812
14,138 6,005 3,033 27,248 8,985 153 14,671
12,126 5,306 2,776 6,519 6,639 201 11,087
3,179 974 337 1,104 848 50 2,296
7,214 1,965 736 987 1,663 94 4,555
17,317 6,979 3,370 28,352 9,833 203 16,967
222,606 47,599 13,987 19,233 80,368 2,050 89,078
158,422 31,800 7,020 7,320 59,765 1,239 55,303
64,184 15,799 6,966 11,913 20,603 811 33,775
3,706 2,264 2,067 420 2,095 3,996 1,991
7,346,807
7,513,691
1,070,091
2,278,553
8,416,898
45,140,903
26,085,175
19,055,728
2,264
Unassigned Trades Food Preparations Not Elsewhere Classified Trade Macaroni, Spaghetti, Vermicelli, and Noodles Trade Cork Products Trade Turpentine and Rosin Trade Wood Preserving Trade Lapidary Work Trade House furnishings
Total Manufacturing Source(s): United States Department of Commerce, Biennial Census of Manufactures , 1935
45
APPENDIX C: Unit Value Ratios for Output Product Group Cotton yarn: single Cotton yarn: doubled Waste: cotton (unmanufactured) Woven products: cotton Pile fabrics: cotton Handkerchiefs: cotton Bed coverings: cotton Towels: cotton Tops: wool Noils: wool Yarns: wool, mohair, etc. Woollen and worsted tissues Carpets and rugs: Wilton, wool Carpets and rugs: velvet and tapestry, wool Carpets and rugs: Axminster, wool Blankets: wool Hosiery: cotton Hosiery: wool Hosiery: silk Hosiery: artificial silk Underwear: cotton Underwear: wool Underwear: silk Underwear: artificial silk Fancy hosiery Neckties, knitted Knitted fabric: cotton Knitted fabric: wool Knitted fabric: artificial silk Cotton net: finished Twine: hard hemp, manila Twine: hard hemp, sisal Cordage: hard hemp, manila Cordage: hard hemp, sisal Twine, soft hemp Cordage, soft hemp Twine: cotton Twine: jute Twine: flax Cordage: cotton Waste: wool (manufactured) Waste: cotton (manufactured) Hide leather: soles Upper leather: calf and kip Upper leather: goat Upholstery leather Glove leather: sheep and goat Machinery belting: leather Overcoats: men's and boys' Rubber/oil proofed garments: male Rainproof garments: male Rubber proofed garments: male Oil proofed garments: female Aprons and overalls: male Aprons: female Undergarments: male Collars and cuffs Corsets and allied garments Millinery: trimmed hats
U.S. Value U.K. Value $ 000 £ 000 133,569 53,287 13,948 16,658 21,027 2,634 561,232 52,679 21,981 959 18,122 1,269 5,503 1,410 30,944 2,036 6,192 19,771 5,615 1,802 101,595 35,068 60,094 42,318 15,884 1,927 30,269 44,239 23,608 33,575 2,516 201,399 25,184 62,958 13,888 59,126 45,722 120,807 1,019 3,856 10,650 21,383 3,666 19 3,017 9,050 547 228 49 13,948 2,617 779 5,908 2,725 9,248 66,206 80,744 36,106 6,231 8,948 10,903 78,792 12,801 13,884 3,207 95 60,188 8,698 147,568 2,652 64,232 85,189
1,215 6,793 2,218 1,332 6,167 4,542 4,025 4,322 3,726 165 2,530 9,721 166 228 529 4,391 365 25 435 992 180 613 116 706 149 167 307 2,586 968 7,534 1,284 1,476 1,715 1,107 714 2,475 1,320 2,742 962 60 2,039 3,559 6,427 841 4,197 2,367
UVR $/£ 7.45 2.99 5.69 5.16 6.13 5.09 6.25 6.40 8.90 8.13 8.31 5.78 7.27
Product Group Neckties and scarves Suspenders and allied garments Handkerchiefs Boots and shoes: leather, men's Boots and shoes: leather, women's Boots and shoes: leather, boys' and youths' Boots and shoes: leather, girls' Boots and shoes: leather, infants' Slippers Pig iron Ferro-manganese Spiegeleisen Ingots Steel castings, direct Steel blooms, billets and slabs Sheet and tinplate bars Wire rods Steel bars Flats, strips and hoop Stainless steel, bars, rods, etc. Scrap bars Structural steel Steel plates, 1/8 in. / 3/16 in. Steel plates, 3/16 in. and over Steel plates, under 1/8 in. Stainless-steel plates and sheets Rails and railway material Tyres and axles Iron and steel pipes and fittings Black plates (tinning) Tin plates Terne plates Copper wire in coils Safety razors Safety razor, blades Locomotives: non-regular Tractors Road rollers Boilers Marine engines: steam reciprocating Marine engines: gasoline Marine engines: diesel Generators, A.C.: under 2,000 kW Generators, A.C.: over 2,000 kW
10.34 5.82 15.67 3.82 5.78 5.25 3.29 4.98 4.79 2.46 3.23 5.46 4.20 3.38 5.75 2.74 19.55 10.70 6.19 8.78 5.89 7.51 5.73 6.93 6.30 7.18 4.67 6.21 6.59 6.06 7.33 5.08 3.94 3.08 6.22 13.11 5.38 2.93 7.44 5.89 3.98 3.23 3.94 7.99 4.96 3.59
Motors, A.C.: 1 h.p. and under 200 h.p. Motors, A.C.: over 200 h.p. Motors, D.C.: 1 h.p. and under 250 (200) h.p. Motors, D.C.: over 200 (250) h.p. Motors, fractional: under 1 h.p. Power transformers Vacuum cleaners Ignition magnetos Incandescent light bulb Radio apparatus: receiving sets Radio apparatus: tubes Electricity meters Ships, boats, etc.: over 5 tons Private cars
46
U.S. Value U.K. Value $ 000 £ 000 58,418 2,583 11,944 908 18,122 177 210,175 12,951 281,067 16,526
UVR $/£ 5.09 5.16 2.07 5.19 5.43
27,922 47,429 13,325 25,290 314,165 20,220 2,145 9,473 67,442 133,158 75,799 35,980 187,357 45,405 7,639 874 160,085 58,894 19,887 181,966 9,148 39,112 10,951 35,315 27,410 175,730 16,593 5,986 3,524 17,733 1,002 5,028 576 9,066 244 2,237 5,137 1,086 10,694
1,712 2,386 828 2,219 18,469 696 100 4,314 2,398 10,862 9,298 3,124 1,728 8,662 743 79 3,640 824 6,842 8,385 536 5,805 1,679 7,122 1,747 11,545 231 3,797 349 1,319 239 1,358 262 3,160 993 269 432 260 656
6.97 6.17 7.64 5.42 5.29 9.16 4.71 6.98 4.79 5.10 5.73 5.26 4.07 5.68 5.23 8.47 9.54 6.05 6.02 5.03 5.76 4.82 4.92 5.02 6.25 5.42 5.43 6.04 3.98 5.48 9.47 15.37 6.97 9.04 3.62 1.42 4.60 4.19 5.88
20,203 3,021
2,590 565
5.47 5.18
6,306 2,183 36,980 21,335 24,191 5,264 60,981 129,109 30,991 13,466 7,080 1,752,794
1,175 179 703 2,517 3,286 284 3,689 10,463 2,215 2,499 3,831 48,255
6.21 8.03 1.91 6.45 2.71 3.34 3.11 3.82 2.10 6.42 3.46 3.69
Product Group Taxicabs Busses: designed to seat not more than 20 passengers Busses: designed to seat over 20 and not more than 32 passengers Busses: designed to seat over 32 passengers Trucks: capacity not exceeding 1.5 short tons (30 cwts.) Trucks: capacity exceeding 1.5 short tons (30 cwts.) Ambulances Chassis: private cars Chassis: busses Chassis: trucks Bodies: private cars Bodies: busses Bodies: trucks Trailers Car parts: internal-combustion engine Car parts: axles, including shafts Car parts: spark plugs Bicycles Airplanes Aircraft engines Railway carriages Ingots: copper Plates and sheets: copper Rods: copper Tubes: copper Ingots: brass Plates and sheets: brass Rods: brass Tubes: brass Castings: brass Ingots: aluminium Castings: aluminium Ingots: lead Plates and sheets: lead Plates, sheets and rods: nickel Solder: tin Ingots: tin Ingots: zinc Plates and sheets: zinc Ingots: anti friction metal (white base) Ingots: type metal Gold leaf Clocks: complete Clocks: movements Watches: complete, jeweled Watches: complete, nonjeweled Watches: watchcases Wheat: meal, flour, etc. Maize: flour and meal Rice: cleaned Animal feeds Bread Biscuits Cocoa: powdered Chocolate: bars and blocks
U.S. Value U.K. Value $ 000 £ 000 2,914 124
UVR $/£ 4.43
1,410
50
2.05
13,420
295
5.34
12,346
612
5.83
227,393
4,253
3.91
43,809 589 13,453 785 71,702 351,682 10,015 23,880 15,919
4,393 76 3,278 3,107 14 5,234 2,897 1,941 576
4.05 5.55 2.24 1.52 1.96 4.33 1.65 3.54 6.34
6,583 58,326 17,176 12,060 17,242 12,610 7,552 4,935 26,143 22,387 12,039 14,381 42,335 23,894 16,626 19,156 16,154 17,924 11,429 2,309 14,113 16,720 2,712 3,044 8,131
2,996 1,080 451 6,664 4,602 3,918 990 883 2,004 2,840 1,362 1,187 2,622 2,902 1,023 2,416 2,642 2,183 1,428 1,448 3,031 1,605 7,606 982 348
4.49 5.19 2.36 5.47 5.00 3.40 7.75 5.67 5.53 5.78 5.42 6.04 5.81 6.54 4.38 4.34 4.60 5.90 6.67 8.15 4.07 4.70 5.03 7.39 7.13
4,982 4,234 1,188 19,733 1,274 18,882 8,236 2,597 792,164 32,485 41,581 222,698 706,898 179,602 1,520 43,938
783 302 114 653 108 71 36 239 46,381 4,934 556 5,384 44,700 16,654 1,778 8,192
3.17 5.27 6.19 1.69 2.75 9.42 4.49 2.68 7.46 9.56 5.87 5.48 11.94 4.39 3.28 4.07
Product Group Confectionery: chocolat Confectionery: hard goods Confectionery: soft goods Confectionery: toffees Peas: canned and bottled Vegetables: canned and bottled Hams: cooked Pork: salted, pickled and smoked Lard Sausages and meat puddings Sausage casings Butter Cheese: cheddar Cheese: cream Condensed milk: whole, sweetened Condensed milk: skimmed, sweetened Condensed milk: not sweetened Powdered milk: whole Powdered milk: skimmed Margarine Casein Sugar: unrefined Sugar: refined Beet pulp: dry Beet pulp: molassed Beet pulp: wet Cured fish: herring Cured fish: cod Manufactured ice Beer Malt Fruit juices, syrups and cordials Cigarettes Natural dyestuff: logwood Natural dyestuff: fustic Tanning: quebracho Tanning: other Naphtha Tar oils Acids: acetic Acids: nitric Acids: sulphuric Sulphates: aluminium Sulphates: alums Ammonia: liquor Bleaching material: calcium oxide Chloroform Sulphates: copper Ether: ethyl Compressed gas: sulphur dioxide Iodine Iodides: other Acetates: lime Sulphates: magnesium Magnesium compounds: other Mercury compounds: other Alcohols: methyl Iodides: potassium Sulphates: potassium Potassium compounds: other Carbonates: sodium
47
U.S. Value U.K. Value $ 000 £ 000 120,620 10,030 28,109 4,666 15,018 5,335 14,991 3,459 50,820 1,138 134,550 1,014 35,581 2,196 393,507 9,810 128,815 3,474 228,464 7,373 32,245 870 464,579 8,508 70,494 341 8,136 34 9,779 2,618 5,086 118,750 3,232 15,824 47,257 4,273 15,953 468,607 1,525 1,732 928 1,614 1,595 126,621 336,490 70,926 66,771 294,221 744 100 1,404 5,184 13,223 194 5,455 2,143 31,908 7,748 1,457 1,235 909 324 2,002 1,305 1,170 238 104 826 1,117 883 739 5,076 572 157 359 57,580
1,075 1,080 776 195 6,186 24 2,703 33,652 148 938 24 2,143 822 970 54,898 4,470 533 38,461 15 71 129 574 185 1,880 327 237 1,958 375 54 264 278 104 447 104 38 26 16 7 79 195 110 212 83 14 262 6,852
UVR $/£ 3.82 4.37 4.58 3.87 3.96 3.47 6.17 4.74 5.04 5.10 4.09 6.37 7.48 3.46 4.23 4.48 3.19 3.51 5.61 7.76 4.80 6.81 6.18 3.33 3.71 3.47 12.55 9.02 5.25 4.79 4.90 5.39 3.64 6.06 6.60 3.62 3.20 1.63 10.98 3.90 6.03 2.94 5.88 8.69 10.13 5.13 1.28 6.39 6.08 9.30 6.08 5.98 3.14 4.36 7.43 5.23 4.11 5.17 7.77 5.98 3.94
Product Group Chromates: sodium Phosphates: sodium Sulphates: sodium Sodium compounds: other Tartrates: potassium Chlorides: tin Charcoal Arsenic compounds: other Acetates: butyl Sulphur Sulphonated oils Carbons Fertilisers: superphosphates Fertilisers: nitrogenous Fertilisers: bone meal Fertilisers: other Glue and size Gelatine Glycerin: crude Glycerin: refined Soap: intermediate product Soap: soft Soap: bar Soap: toilet Soap: shaving Soap: abrasive Soap: powder Soap: flakes and chips Soap: liquid Paints: paste, white lead Paints: colors and pigments Bone-, carbon- and lampblack Paints: water and calcimines Paints: paste, other Varnishes and lacquers Thinners and driers Oils: cotton seed Oils: linseed Cake and meal: cotton seed Cake and meal: linseed Tallow: unrefined Tallow: refined Acids: stearic Refined petroleum: kerosene Refined petroleum: gasoline Refined petroleum: lubricating oil Refined petroleum: gas oil Refined petroleum: fuel oil Explosives: high explosives Explosives: blasting powder Dextrine Washing and scouring materials Matches: safety Matches: strike-anywhere Ink: printers' Building bricks Glass: beer bottles Glass: mineral water bottles Glass: liquor bottles Glass: other bottles and jars Glass: milk bottles Glass: tubing
U.S. Value U.K. Value $ 000 £ 000 4,763 197 6,552 53 5,303 224 17,125 1,799 642 15 4,151 98 3,052 51 6,496 43 3,687 190 1,650 113 3,378 172 6,460 120 19,778 825 93,092 2,620 1,414 150 3,358 3,011 22,724 913 8,199 482 2,366 569 12,973 288 270 356 5,842 390 51,812 7,078 53,325 2,473 7,816 453 7,688 381 53,029 3,641 36,329 1,804 1,523 64 12,937 735 87,012 1,894 15,454 64 5,298 742 10,331 1,417 91,427 4,260 14,569 424 91,849 3,455 43,272 2,451 54,023 1,955 13,387 1,275 27,008 571 4,915 381 2,777 306 1,224 482 1,023,578 4,374 186,534 298 85,550 652 60,983 1,169 30,196 1,770 2,148 391 1,591 135 4,169 690 4,112 957 19,877 3,314 32,561 2,356 25,495 15,376 3,708 897 6,373 306 22,983 864 75,204 3,395 10,980 638 3,666 194
UVR $/£ 3.90 4.19 8.72 2.28 4.72 4.44 1.94 5.67 2.69 6.26 11.35 3.60 4.68 5.13 5.48 5.02 6.06 9.11 7.17 5.31 7.68 7.47 3.84 4.50 4.81 4.44 4.83 4.17 5.90 5.71 3.53 3.89 4.15 8.38 4.07 3.08 7.38 8.47 8.38 3.94 6.02 5.03 7.63 2.34 2.21 7.00 2.59 4.60 2.73 2.66 7.74 8.11 2.10 1.46 4.96 5.19 4.39 4.68 4.52 6.10 5.58 2.65
Product Group Cement Gypsum Concrete: irrigation Concrete: paving materials Concrete: roofing tiles Concrete: blocks and bricks Hardwood lumber: mahogany Hardwood lumber: walnut Hardwood lumber: oak Hardwood lumber: ash Hardwood lumber: beech Hardwood lumber: elm Hardwood lumber: other Softwood lumber: redwood and Douglas fir Softwood lumber: other Dressed lumber Coopering: wet, breweries and distilleries Coopering: wet, other Coopering: dry Printing paper: newsprint Printing paper: other Writing paper Packing paper: kraft Packing paper: sulphite Packing paper: manila Greaseproof paper Paper: oiled, waxed and waterproof Cigarette paper Blotting paper Vegetable parchment Building paper Strawboard, leatherboard and imitation leatherboard Cardboard and millboard Pressboard Folding boxes Toilet paper Threads: rubber Reclaimed rubber Hose: rubber Tubing: rubber
48
U.S. Value U.K. Value $ 000 £ 000 113,505 8,791 13,529 517 10,735 431 243 1,363 862 805 7,360 1,737 1,423 158 1,755 14 32,433 1,054 2,688 213 2,230 139 1,670 216 46,230 344
UVR $/£ 6.10 6.21 4.32 3.32 11.35 3.28 4.00 2.92 1.56 1.45 1.83 2.07 1.61
86,006 224,049 225,767
1,851 1,782 6,107
2.02 2.61 2.15
17,503 7,552 10,021 33,354 110,268 70,620 66,180 26,337 6,743 2,256 8,011 5,739 1,965 1,813 19,450
291 134 134 8,051 7,714 4,781 1,805 291 155 315 1,131 451 389 443 340
2.63 2.78 3.43 4.20 4.19 4.76 4.73 4.85 3.94 9.18 5.40 1.81 3.01 4.53 4.10
24,700 76,126 947 51,696 17,318 2,551 11,774 24,390 2,236
662 2,621 106 5,687 389 317 165 760 114
4.53 3.10 2.36 1.34 2.37 3.10 3.78 5.47 2.96
Tyres, outer: motor car and aeroplane
321,859
10,685
3.86
Tyres, inner: motor car and aeroplane Belting: rubber Valves, washers, rings, etc.: rubber Boots: rubber Shoes: rubber Fabrics: rubberized Gloves: rubber Water bottles: rubber Buttons: casein Buttons: mother-of-pearl Coke Linoleum: inlaid Linoleum: printed Cork carpet Floor coverings: felt base Floor coverings: oilcloth
44,453 32,299 2,106 5,534 31,931 20,059 2,857 2,496 3,856 7,348 32,510 13,193 1,000 189 14,461 1,593
1,071 1,422 237 462 1,580 832 72 226 489 46 9,971 2,181 2,744 96 1,027 270
3.89 6.29 5.05 9.06 9.92 6.47 2.80 4.67 1.65 1.50 9.93 6.79 7.08 6.04 8.93 4.93
Product Group Leather cloth and other oilcloth Pianos: complete Pianos: player, complete Organs: complete Wind instruments (except accordians) Tennis rackets: complete Tennis rackets: frames, unstrung Golf clubs: complete Golf balls Tennis balls Gloves: crisket/baseball and boxing Footballs Skates
U.S. Value U.K. Value $ 000 £ 000 17,130 2,827 11,628 1,242 60 13 1,438 222 3,126 803 474 4,406 3,975 1,264 1,162 910 3,344
22 495 146 350 509 428 67 100 25
UVR $/£ 5.20 7.90 3.23 2.62 3.43 2.22 4.37 4.44 4.65 6.10 5.37 3.37 4.50
Sources: United States Department of Commerce, Biennial Census of Manufactures , 1935 Board of Trade, Final Report on the Fifth Census of Production and the Import Duties Act Inquiry , 1935
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APPENDIX D: Unit Value Ratios for Intermediate Inputs Product Group Cotton: raw Waste: cotton Yarn: cotton Staple fibre: rayon Yarn: rayon Yarn: wool Wool: raw Wool: recovered Tops Yarn: wool Cotton: raw Waste: cotton Yarn: cotton Yarn: silk Staple fibre: rayon Yarn: rayon (continuous filament) Yarn: staple rayon Waste: silk Silk: raw Yarn: cotton Yarn: woollen Yarn: worsted Cotton: short staple Silk: thrown Yarn: spun silk Yarn: rayon (continuous filament) Staple fibre: rayon Flax Flax: tow Hemp: soft Yarn: flax Jute: raw Waste: jute Yarn: cotton
U.S. Value $ 000 324,420 8,156 47,503 1,157 10,773 1,030 20,629 12,528 51,490 14,856 2,039 875 18,410 877 60 161 1,273 965 44,990 5,011 622 678 1,141 4,999 7,924 88,720 1,352 2,142 593 277 942 5,077 399 67,472
U.K. Value £ 000 37,476 2,252 46,881 405 3,279 142 30,870 1,566 16,610 3,325 174 190 2,312 119 23 347 18 266 1,544 1,469 47 73 148 233 208 5,983 185 157 344 262 807 2,696 37 4,062
UVR $/£ 4.48 6.28 7.48 7.96 3.91 8.70 3.69 8.27 8.56 6.23 4.81 5.69 5.51 5.19 3.03 4.40 5.37 2.63 3.70 5.76 7.75 6.89 8.00 2.85 2.44 4.11 6.41 6.29 7.13 7.12 13.17 5.29 8.10 6.08
Product Group Yarn: wool Yarn: silk Yarn: rayon Yarn: cotton Yarn: silk Yarn: rayon Hard hemp: Manila Hard hemp: Sisal Hard hemp: New Zealand Yarn: cotton Iron ore Limestone Cinder and scale Dolomite Scrap: iron and steel Pig iron Ferro-alloys Scrap: iron and steel Ingots: steel Blooms, billets and slabs: steel Sheets: steel Pig iron Scrap: iron and steel Lead Solder: tin Black plates: iron and steel Sheets: iron and steel Tinplate Copper, brass and bronze Shapes: iron and steel Wire rods: iron and steel Copper Brass
Sources: United States Department of Commerce, Biennial Census of Manufactures , 1935 Board of Trade, Final Report on the Fifth Census of Production and the Import Duties Act Inquiry , 1935
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U.S. Value U.K. Value $ 000 £ 000 45,904 8,479 39,727 1,483 32,770 3,197 5,936 1,255 338 42 413 364 3,136 545 4,922 436 4 16 1,841 655 169,156 7,415 9,126 492 4,917 330 1,235 198 8,192 462 268,153 13,029 44,142 2,679 129,755 12,054 7,480 2,912 118,347 9,379 10,265 5,283 14,768 5,134 5,783 1,676 97 15 3,522 2,264 4,650 1,800 12,082 1,649 151321.88 4171 314.801 886 1040.236 95 27054.319 3372 13,446 1,901 758 179
UVR $/£ 6.92 4.03 4.00 6.72 4.03 4.89 5.99 4.33 8.67 8.08 9.37 4.93 2.79 1.89 4.84 5.14 5.11 4.22 4.85 5.05 9.02 4.87 3.96 12.48 2.46 7.76 5.94 5.53 7.56 2.70 5.16 6.01 5.69
