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Let’s Get This Right: Swiss GDP
and Value Added by Industry
from 1851 to 2008
Christian Stohr
September 2014
Let’s Get This Right: Swiss GDP and Value Added by Industry from 1851 to 2008 Christian Stohr University of Geneva Paul Bairoch Institute for Economic History Abstract This paper combines various data sources on value added and GDP for Switzerland in order to construct long-­‐term series from 1851 to 2008. I provide an extensive discussion of deflation methods and show that the recent update of the Swiss GDP per capita series in the Maddison database relies on a statistical artifact. This update suggests that Switzerland was already an extremely rich country in 1851 and that it was by far the richest economy in the world for practically the whole period between 1890 and 1980. Important relative price changes have occurred in Switzerland between 1945 and 1990. Double-­‐deflated GDP estimates like those of the recent update are erroneous, when price indices are not regularly rebased, and even then, they do not account for gains and losses from relative price changes. In the case of Switzerland, this leads to significant underestimation of the growth rate and, since GDP is constructed backward from the 1990 benchmark, to a GDP level, which is between 40 and 70% too high for the whole period before 1945. I propose an alternative GDP series, which is deflated by the consumer price index. This series suggest that Switzerland was not all that rich. The contributions of this paper are three-­‐fold. First, it provides a GDP series for Switzerland that builds on reliable sources and is very much in line with other types of evidence (international benchmark comparisons and international wage comparisons). Second, it points out a methodological problem of double deflation that might also be a source of error in the GDP series of other (small open) economies. Third, it throws a different light on the development trajectory of Switzerland shifting the accent from proto-­‐industry and the first industrial revolution to the second industrial revolution and the post-­‐WWII boom. This has also an incidence on the identification of the possible sources of Swiss growth shifting the focus from protestant immigration to market integration during the second half of the 19th century and the post-­‐1945 boom. Limited openness might be responsible for the Swiss growth slack between 1973 and 2000. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 2 Introduction This paper elaborates a new GDP series for Switzerland from 1851 to 2008. Currently, several long-­‐run series of real GDP for Switzerland are available. The best known are the series proposed by Maddison (2003) and the one proposed in the latest Maddison update (Bolt & van Zanden 2013). Both series suggest that Switzerland was a very rich economy between 1948 and 1990, before falling back in comparison to the USA and a few European countries. For the period before 1948, the two series are highly contradictory. While the older Maddison series indicates that Swiss GDP per capita moved from slightly below the European average in the 1850s up to the UK and US level in 1939, the updated series suggests that Switzerland was much richer than the USA already in 1885 and remained the richest country in Western Europe and North America almost all the time until 1980. The deviation between the two series is enormous rising up to 79%. I show that none of the two series seems to be reasonably truthful. The updated series clearly underestimates the long-­‐run growth rate, leading to strongly upward biased GDP levels for earlier periods. The long-­‐run trend of the old Maddison series seems to be more accurate but it relies on two unrealistic growth spurts at the end of the two world wars. The series proposed in this paper depicts the evolution of an economy that was clearly below the European average in the mid-­‐19th century, caught up with the UK and the USA by 1910, registered average growth until 1945, caught up again with the USA by 1975, and fell back during the last decades of the 20th century. My series uses the same data sources as the Maddison update, but it relies on a different deflation method. I provide an extensive discussion of deflation methods showing that double-­‐
deflation is inappropriate, when relative prices are changing rapidly. This problem is particularly important in the case of Switzerland, where the strong appreciation of the national currency and price regulations have caused important relative price changes during the period 1930 to 1990. My solution is to deflate nominal GDP with a consumer price index as proposed by Kohli (2004). Applying the same deflation method to the updated Maddison series of the UK and USA has only a minor impact. In fact, the theoretical discussion of double deflation implies that the double-­‐deflation problem is more acute for small open economies. My series is corroborated by direct benchmark comparisons of GPD per capita and international wage comparisons. My series has important implications on the discussion of potential sources of Swiss growth. The fact that Switzerland was much less rich than suggested by the Maddison update discredits the protestant ethic and early industrialization as the dominant cause of Swiss wealth. These would imply that Switzerland became rich before 1850. The fact that Switzerland was already rich in 1910 throws doubt on the argument that the strong financial sector or corporatist arrangements, which reached their climax only later, were the main cause of Swiss wealth. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 3 Instead my series suggests that market integration and Switzerland’s favorable geographical location might be the main explanatory factor. As a matter of fact, the periods, when Switzerland experienced fast growth in international comparison, are periods when market integration was fast. The period when Switzerland fell behind is characterized by lacking openness of Switzerland while the other European countries integrated quickly. The structure of the paper is as follows. Section I reviews the original datasets and currently existing long-­‐run series of Swiss GDP. Section II establishes the nominal GDP and value added series. Section III discusses deflation methods, Swiss price indices, and relative price changes in Switzerland. Section IV proposes international comparisons, provides a cross-­‐check of the series, and highlights the implications for Swiss economic history. Existing series of Swiss GDP and value added This section reviews existing series of Swiss GDP and value added. I start with original data sources before discussing existing long-­‐run combinations of them. Original data sources The contemporary GDP series of the Federal statistical office, which is based on the production approach, starts only in 1990 (BFS 01). Before 1990, National accounting was based on the income and the expenditure approach and was published only since 1948. Today these estimates are not available from the statistical office any more but from the historical statistics of Switzerland (HSSO Q.06), which is not an official publication but a collection of historical data elaborated by a group of historians in the 1990s. This publication has now been numerized, updated, and made accessible on the web. For the pre-­‐1948 period contemporary statisticians have elaborated only a few punctual estimates for certain years1. However, all these estimates focus on national income rather than GDP and value added. Hence, in order to study long-­‐term economic growth one has to combine a number of heterogeneous sources. The official GDP series and production account of the Federal statistical office starts in 1990 (BFS 01). However, for the period 1990 to 1996, value added is broken down only into very large aggregates (10 sectors; manufacturing is lumped together in one single sector). The complete production account for 50 industries is available only since 1997. This corresponds to the date when the Federal statistical office adopted the European industrial classification, NOGA. For the early 1990s (1990 to 1994) the statistical office had previously published production accounts by industry relying on the Swiss ASWZ classification (BFS 02). But apparently it was impossible to convert these into more detailed NOGA industries than the 10 sectors that are 1 See Andrist (2000) for a complete review. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 4 available now. Hence, even the official estimates for the period 1990 to 2008 rely on fragmented data. The estimates are reported in current Swiss francs and in annual growth rates in prices of the preceding year (BFS 1). For the period 1960 to 1990, the Sankt Galler Zentrum für Zukunftsforschung has estimated value added by industry. The estimates are benchmarked by the production account of the 1985 industrial census. They are based on the Swiss ASWZ classification and composed of 23 industries. The data is available from the historical statistics of Switzerland in current Swiss francs and in constant prices of 1985 (HSSO Q.02). In the early 1990s, the Swiss National Research Fund project “Money supply and economic growth in Switzerland 1851-­‐1913” has established GDP estimates for the period 1851 to 1913. These estimates are based on the production approach and provide also value added by industry. However, the lack of data made the estimation for certain sectors impossible, so that GDP had to be estimated by a simplistic projection of the evolution of value added from the estimated industries on those for which data was lacking. Industry value added is available in current Swiss francs. GDP was reported in nominal terms and deflated by the consumer price index (HSSO Q.01). In 2000, Andrist et al. have elaborated an indicator-­‐based estimate of Swiss GDP for the period 1914 to 1947 in order to close the gap between official post-­‐1948 estimates and the National Fund project’s series. But this data does not provide any information on industries’ value added (Andrist et al. 2000). Recently, earlier but previously unpublished estimates of Ritzmann-­‐
Blickenstorfer for the period 1890 to 1960 have become available (HSSO Q.17). These estimates provide value added by industry in current Swiss francs and in prices of 1926/29. Most of the series were estimated from the production approach, but in a few cases it was necessary to rely on the income approach or even basic rough estimations. A description of parts of the estimation procedure can be found in Ritzmann et al. (Ritzmann-­‐Blickenstorfer & David 2012). Internationally comparable long-­‐run series Early attempts of international GDP comparisons in historical perspective have been made by Clark (1940) and Bairoch (1976). But since the 1990s, the Maddison database has been the standard source for international comparisons of historical GDP series (Maddison 1995). A first update was proposed 8 years after the first publication (Maddison 2003) and recently a group of researchers affiliated to the Maddison project of the Growth and Development Center of the University of Groningen have proposed another update (Bolt & van Zanden 2013). The series are constructed backward and forward from a 1990 benchmark, for which Maddison has used purchasing power parities from different sources based on the method proposed by Geary and Khamis (Maddison 1995, p.98). Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 5 For Switzerland, the first Maddison database relied on Clark and on the official estimates for the period after 1948. However, Maddison highlighted that “the historical estimates are poor and weaker than for all other West European countries. I took 1899-­‐1950 real product in international units from C. Clark, Conditions of Economic Progress (3rd ed.), Macmillan, London, 1957, pp. 188-­‐9. For 1870-­‐99 it was assumed that per capita product moved as in Germany.” (Maddison 1995, p. 83). In 2003, Maddison integrated the estimates of HSSO Q.01 for the period 1851-­‐1913 and those of Andrist et al (2000) for the period 1913-­‐1924, while the estimates for 1924-­‐1950 still relied on Clark (1940). For the period 1820-­‐1851, Maddison assumed that GDP movement was equal to the average of France and Germany (Maddison 2003, p.31). Recently, Hiestand et al. proposed an update of Maddison’s series by connecting Maddison’s post-­‐1948 estimates with those of HSSO Q.17 and the pre-­‐1890 evolution of HSSO Q.01 (Hiestand et al. 2012). The resulting series has now been integrated in the last update of the Maddison database (Bolt & van Zanden 2013). Figure 1 illustrates the 2003 and 2013 Maddison series of GDP per capita in comparison to other Western European countries and the USA. The two series for Switzerland are equivalent for the period between 1948 and 1990 but for the period before 1948 they clearly diverge. The difference is largest in 1917, when the newly updated series lays 79% above the old series. This divergence is mainly due to an enormous upsurge of the old Maddison series between 1944 and 1948 (+50%) compared to a more modest increase in the updated series (+18%). The old Maddison series also suggests an early recovery at the end of WWI (around 1917), while the new series exhibits a strong and durable crisis until 1922. Common sense would recommend that the new series should be more accurate than the old one. Actually, the new series uses more thoroughly estimated statistics that rely on more data and are less fragmented for the period 1890 to 1948. While the old series is a combination of three sources for this period (HSSO Q.01; Andrist et al. 2000; and Clark 1957), the new series uses the figures from Ritzmann-­‐Blickenstorfer (HSSO Q.17) who complemented the estimations of HSSO Q.01 with additional data and extended the series until 1960. As a matter of fact the growth patterns at the end of the two world wars proposed by the old Maddison series seem much less plausible than those of the new series. Swiss historiography describes the period after WWI as a durable and very hard crisis from which Switzerland recovered only in 1922 (Jost 2004; Degen 2012). The end of WWII is known as a fast growth period for Switzerland, but the upsurge proposed by the old Maddison series, which implies an average annual growth rate of more than 10% per year between 1944 and 1948 seems exaggerated. Only countries like France, Italy, the Netherlands, and Norway that were invaded and experienced rapid reconstruction after the war experienced such high growth rates. The Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 6 growth rate implied by the new series (4.2%) on the other hand is comparable to that of Sweden, another neutral country and seems realistic. From these considerations it follows that the short-­‐ and medium-­‐term growth patterns of the new series are certainly more accurate, but how about the long-­‐term trend of the two series, which represents their most striking difference? The best way to evaluate the accuracy of the long run growth patterns are direct level comparisons of GDP per capita with other countries. This is the purpose of an alternative dataset elaborated by Prados de la Escosura (2000). I combine the relative estimates from Prados de la Escosura with Maddison’s UK series in order to obtain alternative GDP per capita estimates for Switzerland, assuming that Maddison’s UK series is correct (see figure 1). These punctual estimates corroborate the 1880 to 1913 GDP per capita level of the old Maddison series rather than the new one. Confronting the two series to international wage comparisons offers an additional crosscheck of GDP per capita levels. Studer (2008) has constructed internationally comparable nominal and real wage series for the period 1800 to 1913. His comparison reveals that Swiss living standards were rather low in comparison to other European countries. Around 1850, Swiss construction workers earned only about one third of their counterparts in Britain, and about 60% of French, Belgian, and Dutch workers. In 1910, Swiss wages were about 70% of those in Britain. Of course, wages depend on bargaining power and the size of the city, where data was collected. If workers had weaker bargaining power than those in other countries and if the rural-­‐urban divide was less pronounced, these wages are only a weak proxy for GDP per capita or productivity. But even then, it is practically impossible to reconcile the extremely high GDP per capita of the Maddison update with the wage data of Studer. In sum, none of the two Maddison series for Switzerland seems to be really correct. The new series clearly overestimates Swiss GDP per capita of the 19th and early 20th century. The long-­‐
run growth trend of the old series appears to be more realistic, but it relies on an implausible growth surge at the end of WWII and an early recovery after WWI, which stands at odds to Swiss historiography. It is essential for Swiss economic history and particularly for the study of Swiss economic growth to resolve this paradox and elaborate a series with an accurate long-­‐run growth trend and well-­‐founded short-­‐ and medium-­‐term fluctuations. Nominal GDP and value added from 1851 to 2008 Different data sources often report different GDP and value added for the same year. For example, total value added in 1990 is 4% higher according to BFS 01 than according to HSSO Q.02. Such differences can occur because estimates rely on different data sources, methodologies, or definitions. Various procedures are possible to connect the different production accounts. First, connections can be operated backward or forward. In the former Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 7 case, estimates of earlier periods are adjusted to the level of later periods, whereas in the latter case, later periods are adjusted to earlier ones. Given that the latest GDP estimates are certainly the best in terms of quality, backward connections are usually preferred. Second, connections can be operated either by adjusting each industry’s value added separately or by adjusting the entire production account by a single scalar, which adjusts aggregate value added without changing the relative weight of different industries. My series is essentially a backward connection of the different sources. That is, I adjusted HSSO Q.02 to the 1990 level of BFS 09, then I adjusted HSSO Q.17 to the 1960 level of the adjusted HSSO Q.02, and finally I adjusted HSSO Q.01 to the 1890 level of the adjusted HSSO Q.17. However, a slight transformation of BFS 01 seemed adequate, before adjusting the earlier series. BFS 01 includes production of goods and services by households for their own consumption. This is an important definitional difference to the other series. I subtracted this element, reducing thereby aggregate value added by 6.5% in 1990. The choice between industry-­‐wise or single-­‐scalar adjustment is crucial. Industry-­‐wise adjustment of value added series could introduce important changes of relative industry weight. Such changes can have an impact on aggregate GDP. For example if the adjustment increases the weight of fast growing industries and reduces that of slow growing ones, the growth rate of GDP will be higher. When connecting series backwards this would lead to a lower GDP level in earlier periods. Changing the relative weight of industries value added will also have an impact on relative levels of value added per worker or productivity. As we will see, such distortions can cause significant biases in inter-­‐industry productivity comparisons. This is a strong argument for single-­‐scalar adjustment. However, the disadvantage of single-­‐scalar adjustment is that it leaves a clear break in individual industries’ value added series. The choice depends on what the data is being used for. In practice, the industry-­‐wise connection is also delicate because industrial classifications have to be harmonized. Visibly, the Federal statistical office has refrained from such a harmonization of the production accounts of 1990 to 1994 and the production account of 1997, providing only a 10-­‐sector classification for the period before 1997. Hiestand et al. (2012) have been more courageous and propose such a harmonization (HSSO Q.18). They do not propose a backward connection with HSSO Q.02 for the nominal value added series (HSSO Q.18a), although they do so for the constant price data (HSSO Q.18b). I have computed such a connection and tried to evaluate the distortions this introduces to inter-­‐industry differences of value added per worker. The first column of table 1 reports the ratios by which the industry series of Q.02 must be multiplied to adjust to their Q.18a counterparts. Some of these ratios deviate very strongly from 1, so that the distortions in relative value added per worker introduced by this method must be considerable. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 8 However, one might argue that HSSO Q.18 could be more accurate than HSSO Q.02. In order to test this, I have compared the resulting value added per worker to wage data (HSSO G.09). The comparisons were made for 1970, 1975, and 1980 because distortions become more visible as one moves away from the year for which the series were connected. Table 2 reports a measure of the similarity between relative value added per worker and relative wages of industries. Perfect similarity would yield a value of zero. Positive values symbolize dissimilarities. The correspondence is better at the original Q.02 level of value added (column 2) than at a level resulting from industry-­‐wise backward connection (column 1). Figures 1 to 6 compare value added per worker and wages by industry. According to classical economic theory, wages should be equal to marginal labor productivity. Value added per worker, however, corresponds to average labor productivity. In capital-­‐intensive industries like electricity, gas, and water supply, chemicals, and the paper industry marginal labor productivity (and wages) are lower than average labor productivity. This can be seen from figures 2 to 7. Excluding these industries from the comparison yields therefore a better correspondence. Other industries, e.g. Bekleidung und Schuhe, Uhren und Schmuck, Graphische Gewerbe, and Textilindustrie register levels of value added per worker that are rather low compared to wages. Already at the original Q.02 level, value added per worker appears to be so low in Bekleidung und Schuhe and in Uhren und Schmuck that these industries appear to be practically non-­‐viable. As a matter of fact these industries were actually very hardly hit by the 1970s crisis. However, adjusting these industries to the Q.18 level brings value added per worker to implausibly low levels. In figure 3 annual wages of Bekleidung und Schuhe correspond to 200% of value added per worker! I conclude that industry-­‐wise adjustment of value added, as it is proposed in Q.18b introduces too large biases in relative value added per worker between industries. Single-­‐scalar adjustment is clearly preferable. How about the connection of HSSO Q.17 with HSSO Q.02? Column 2 of table 1 reports the industry-­‐specific ratios that adjust HSSO Q.17 to HSSO Q.02. Clearly, the two datasets propose very different relative levels of value added between industries. An industry-­‐wise adjustment would therefore introduce major distortions. Table 2 suggests that HSSO Q.17 (column 3) yields 1970 relative levels of value added per worker that correspond better to relative wages than HSSO Q.02 (column 2). An industry-­‐wise adjustment of HSSO Q.17 to the Q.02 levels would therefore be inadequate. The all-­‐industries comparison suggests that it would even be best to make a forward industry-­‐wise connection, because relative value added per worker between industries of the HSSO Q.17 seems more plausible when compared to wages. However, when capital-­‐intensive industries are taken away from the comparison the fit between wages and value added per worker of HSSO Q.17 is better only in 1970, so that value added by industry Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 9 would be increasingly distorted. I decided to apply the single-­‐scalar backward connection between the two datasets, analogous to the connection between BFS 01 and HSSO Q.02. The estimates of value added by industry for the period 1851 to 1890 stem from the Nationalfondsprojekt Geldmenge und Wirtschaftswachtum in der Schweiz 1851-­‐1913 (HSSO Q.01). This was the first attempt to estimate a continuous series of value added by industry for the period before WWI. This series was not connected to any benchmark production account so that the level of individual and aggregate value added series is questionable. The authors of the project were aware of this shortcoming and noted themselves that the value added series by industry were more reliable in terms of their evolution over time than in terms of absolute level (Projer 1990, p. 3). This has important implications for inter-­‐industry differences of value added per worker. Also the authors of the project were unable to estimate value added of all industries. In manufacturing, the industries for which estimates were elaborated accounted for approximately 82% of employment. Projer solved this problem by assuming that the industries for which they had no estimates evolved in parallel to the industries for which they managed to estimate value added. Hence they simply divided the sum of industries’ value added by 0.82 (the employment share of the estimated industries) in order to estimate value added of the entire sector (Projer 1990). Now that a reliable series for the subsequent period exists, namely HSSO Q.17, it makes sense to connect the estimates for the period 1851-­‐1890 of the Nationalfondsprojekt to that level. In this case, it seems to be better to connect the value added series industry by industry, in order to adjust the between industry differences in value added to the more accurate level of HSSO Q.17. By the same token, this allows for a better solution of the problem concerning the industries for which value added could not be estimated. Instead of assuming a parallel evolution of the missing series to the evolution of the whole aggregate, my method assumes parallel evolution of these industries to a more narrowly defined aggregate. For example, the missing value added series for the wool industry is assumed to evolve in parallel to the estimated textile industries, not the entire manufacturing sector. This extrapolation requires the combination of two databases: the one on value added discussed here and data on employment discussed in Stohr (2014). There I also provide more details on how the different industrial classifications had to be harmonized. To summarize, I have connected the different data sets of value added by industry going backward in time. The three datasets concerning the period after 1890 were connected with a single scalar for all industries, because industry-­‐wise adjustments would have introduced large and implausible distortions of relative value added between industries. The series for the period before 1890, on the contrary, were connected industry-­‐wise, because the relative industry weights of Ritzmann’s estimates (HSSO Q.17) are supposed to be more accurate than those of Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 10 HSSO Q.01. This also allowed for an improved extrapolation of value added for those industries that were not estimated in the project. The methodological choices made in this section are different from those of Hiestand et al. (2012). This leads to differences in GDP and individual industries’ value added. The differences in GDP are negligible. But the differences at the industry level are considerable. Real GDP and value added from 1851 to 2008 This section starts with a few methodological considerations before discussing the different deflators available for Switzerland. The third subsection investigates relative price changes and their impact on the GDP deflator. How to deflate GDP and value added? There are different ways to deflate value added. Today it is common practice to construct series of value added in constant prices with a so-­‐called “double deflation” procedure. This procedure consists of deflating intermediates consumption by input prices and output by final goods prices. The resulting real value added is therefore calculated as a residual. The advantage of this method is that every item is deflated by the closest corresponding price index. This method was proposed by Fabricant (1940) and first used by Geary (1944). The System of National Accounts 1993 (SNA 1993) recommends this procedure for the construction of value added and GDP at constant prices and most statistical offices today follow this recommendation. Historical estimates sometimes rely on deflation by a single price index because the necessary data for double deflation is not available. In such cases GDP and value added is deflated either by the corresponding output prices or by a consumer price index. The double deflation method has been criticized in numerous respects. Paul David (1962) insisted on the fact that double deflation of value added can yield negative values even if original value added in current prices is positive. This problem stems from the fact that real value added is measured as a residual when double deflation is used. In fact, double deflation imposes not only the general price-­‐level of the base year on other years but also the relative price structure. Negative real value added simply reveals that the precise output and intermediate consumption quantities of the observed year would not be economically viable if relative prices of the base year had prevailed. As David pointed out, such distortions of the residual measure of real value added are present whenever relative prices have changed and technological progress has occurred between the base year and the observed period. The problem with this particular type of index number problem is that it is impossible to know the direction of the bias. In later paper, David (1966) has therefore proposed to deflate value added of each industry by the price index of its output. SNA 1993 proposes another solution, which is to use chain indices when double Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 11 deflating value added. Relative prices and technology of consecutive years are supposed to be least divergent, so that biases are minimized (SNA 1993, p.490). Sims (1969) has demonstrated that double deflation yields a Divisia index of value added if the production function is separable and the price index is continuously chained. However, in practice, time is not continuous and production functions might well be inseparable (e.g. one can imagine that materials can be substituted for by investing in capital). Also, chaining or rebasing indices of sub-­‐aggregates leads to non-­‐additivity problems, i.e. the sum of deflated components of GDP is not equal to the deflated sum of components (Baffigi 2011, p.64; SNA 1993, p.493). Fenoaltea (1976) has criticized both double deflation and deflation by industry specific output prices. The problem with these industry-­‐specific deflators is that they change the inter-­‐industry value added ratios of all years except the base year. If observed current-­‐price value added ratios between industries are right, then the ratios obtained from double deflated or output-­‐price deflated value added are wrong 2. Hence, according to Fenoaltea, current values added of different industries must be deflated by the same price index. He proposes two possible deflators: a nominal wage index or a price index of a composite good. The former index is downward biased because it includes also increases of the value of labor (i.e. the real wage component of nominal wages), while the latter index is upward biased because it does not account for the fact that increasing wealth reduces the value of goods themselves. Kohli (2004) provides a theoretical model that allows for the comparison of the index of real GDP and its implicit deflator with the index of real domestic income (GDI) and its implicit deflator. GDI differs from GDP in the sense that it includes terms of trade gains. Hansen (1974) already made this distinction when criticizing the single deflation with output prices proposed by David (David 1966). According to Hansen, David’s measure is not a substitute for the GDP deflator but precisely a way to obtain real GDI. He claimed that GDP measures should not include terms of trade gains. Kohli, on the other hand, argues convincingly that terms-­‐of-­‐trade gains have a real effect on income and welfare, which should not be neglected. He thus advocates the use of a single common deflator for the trade account and the value of domestic outputs. 2 “Now with the usual sort of real value added index, such calculated relatives do not in general coincide with directly observed ones; but if the observed (A1/B1) and (A2/B2) are correct real measures, then this ‘index-­‐
number problem’ means that the calculated (A2/B2) is wrong, and wrong because (A1/A2) or (B1/B2) is wrong. These indices are wrong, i.e. not ‘real’ in the proper sense of ‘constant-­‐worth’, precisely because they are ordinary quantity indices: ‘real’ magnitudes being thus identified with industry-­‐specific physical ones; current values added being thus deflated by industry-­‐specific price indices, production is clearly measured in a variety of disparate units, and a common (‘real value’) measure is not achieved at all.” (Fenoaltea 1976, p.121). Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 12 Ideally, this deflator should be a superlative index such as the Törnqvist index and it should rely only on domestic prices (Kohli 2004). Double deflation is also much more sensitive to measurement errors than single deflation, particularly in the case of industries where value added accounts for only a small proportion of output value. SNA 1993 therefore proposes to abandon double deflation if the series of input and output value are subject to errors (SNA 1993, p.491). Edquist (Edquist 2013) has also drawn attention to another problem with double deflation. Changes in the share of value added in output value have a strong impact on growth of double deflated value added measures. Finally, any price index should account for changes in quality. Jorgenson (2005) strongly advocates constant quality price indices, in particular for the information and communication technology (ICT) sector, where improvements in quality are very important. Edquist (2004) shows that growth in labor productivity and value added in the Swedish ICT sector since 1993 was significantly overestimated because the underlying deflators do not account for quality improvements. International comparisons between countries that use hedonic price indices and countries that don’t are seriously hampered. For historians, however, quality adjusted price indices are practically impossible to find, unless one is able to engage in extensive data collection on product characteristics and prices in order to construct them. Edquist (2010) has undertaken such an attempt for the electric motor industry of the early 20th century. He finds that prices decreased rapidly during this period suggesting rapid productivity growth. However, the phenomenon is much less dramatic than in today’s ICT sector. In sum, all methods of deflation have their disadvantages. Deflation by the nominal wage index or a composite good index is somewhat arbitrary because output and intermediates are not deflated by their actual prices. However, intuitively the two deflation methods are quite appealing. The first measures value added in units of labor and the second in units of consumption. If the sum of all industries’ value added is theoretically equivalent to the sum of all incomes, or to the sum of expenditures, then these standards seem straightforward. The essential question then is: how representative are the underlying group of workers and consumption baskets? Industry specific deflators, on the other hand, tend to introduce large biases when they are not based on chain indices. This makes industry comparisons impossible. If they are chained, on the other hand, they suffer from non-­‐additivity. Swiss price indices The constant price series of the three datasets concerning the period after 1890 are based on double deflation. The series for 1990 to 2008 is reported in annual percentage change based on prices of the previous year (BFS 01). Combining these growth rates with the nominal value added levels for 1990 yields constant price series in 1990 Swiss francs. Methodologically, this Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 13 corresponds to double deflation with a chain index. The series for 1960 to 1990 is based on 1985 input and output prices (HSSO Q.02). And the series for 1890 to 1960 is based on 1926/29 prices (HSSO Q.17b). Most manufacturing industries of the latter dataset were double deflated. But services, agriculture, and those industries that were estimated from the income approach were deflated with single indicators: either the consumer price index or industry-­‐specific output prices (Ritzmann-­‐Blickenstorfer & David 2012). For the series 1851 to 1890 no industry-­‐specific deflators have been constructed. The authors deflated the aggregate value added with a consumer price index that was elaborated during the same research project (HSSO Q.01). In order to construct a double deflated constant price series for the whole period I applied the same procedure as for the nominal series. I connected the last three constant price series by means of a single scalar adjusting the series of the earlier period to the GDP level of the subsequent period. Since I did not connect the nominal series industry by industry it would not have made sense to connect industry-­‐specific deflators in order to construct industry deflators for the whole period either. Hence, the deflators always rely on base years within the considered time period. This prevents non-­‐additivity problems (except from the period 1990 to 2008, where non-­‐additivity problems arise from the chain index method). The connection of the series 1851 to 1890 was again operated industry by industry in order to adjust the relative value added levels of HSSO Q.01 to those in HSSO Q.17, which are supposed to be more accurate. As for the current price series, my GDP estimates are very close to those of Hiestand et al. (2012) but the industries’ value added estimates are clearly diverging. Since double deflation and industry-­‐specific deflators in general suffer from a number of conceptual problems, particularly if they do not rely on chain indices, it is worthwhile to consider also alternative deflators. The most straightforward deflator is probably the consumer price index (CPI). The Federal statistical office proposes a monthly consumer price index that spans the period 1921 to 2014 (BFS 03). The consumer basket of this index was adjusted 5 times before 2000 (1939, 1966, 1977, 1982, and 1993). First this index was mainly based on food, clothing, and fuel prices as well as housing rents, but since 1966 it is based on a complete consumption basket. Since 2000 the weights are adjusted every year and the index controls for quality changes. Methodologically the index is based on a Laspeyres type formula. Superlative indices such as the Fisher or the Törnqvist index are not available for Switzerland. However, the statistical office highlights that the Lowe chain index, which is used since 2000, yields results that are very close to those of the two superlative indices (BFS 2011). For the period before 2000, when weights were fixed over longer periods, the CPI might be less accurate. Theoretically, a Laspeyres index overestimates consumer-­‐price inflation, because it does not account for substitution behavior. In practice, however, the bias depends on the price elasticity of demand. At the bottom line, this CPI is certainly the best available price index for Switzerland Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 14 between 1921 and 2008. I have calculated 12-­‐months averages for every year and rebased the index to base year 1990. The Swiss historical statistics provide a CPI that covers the whole 19th and 20th centuries (HSSO H.39). This index has been recomposed from different sources of heterogeneous quality. For the period after 1914, the index relies on official retrospective statistics of the Federal statistical office. From 1890 to 1914, the index evolves like the consumer price index elaborated for the National research project “Real wages of Swiss industrial workers 1890 to 1921” (HSSO H.18). For the period before 1890 the series seems to be of inferior quality. This can be seen by simple inspection, because the index is subject to much higher volatility in this period. Higher volatility could of course be due to weaker market integration and efficiency. However, the fact that volatility decreases abruptly in 1890, when the more elaborated series begins, suggests that the strong fluctuations are due to the weak statistical basis of the index. In order to make the series more homogeneous I decided to smooth the series before 1890 with a five year moving average. The movement of the resulting index was used to prolong the Federal statistical office’s CPI backward until 1851. Figures 7 and 8 plot the two deflators and the corresponding real GDP. Theoretically, the CPI and the GDP deflator could be used as substitutes. If GDP can be interpreted as output, income, or expenditure, both deflators have their own justification and should yield similar results. Balke and Gordon (1989) for example argue that the implicit GNP deflators of post-­‐1909 US GNP estimates are more volatile and probably less accurate than the consumer price index. Ritzmann (2012) also suggests that the CPI could be used as an alternative deflator for Swiss GDP; and he interprets the fact that his implicit GDP deflator is strongly correlated to the CPI as a sign that both the GDP deflator and the CPI are accurate deflators3. Ritzmann notes the divergence of the CPI and GDP deflator during the period 1945 to 1960. The same type of divergence can also be observed between the CPI and the GDP deflator of the series constructed by the Sankt Galler 3 “Eine Deflatorenanalyse auf der Ebene der Branchen kann im Rahmen dieses Beitrags nicht geleistet werden. Es muss der Hinweis genügen, dass der aggregierte Branchepreisindex (BPI), der sich aus der Division des nominalen durch das reale BIP ergibt, von 1890 bis 1960 weitgehend synchron zum KPI verläuft. Im ersten Weltkrieg geht der BPI etwas weniger stark und in der Periode 1930-­‐1945 etwas stärker zurück als der KPI. Und unmittelbar nach dem Zweiten Weltkrieg verzeichnete der KPI einen merklich steileren Anstieg als der BPI. Doch insgesamt darf von einer engen positiven Korrelation zwischen den beiden Indizes gesprochen werden, was nicht selbstverständlich ist, da sie ja weder eine gemeinsame Datenbasis besitzen noch nach derselben Methode ermittelt wurden. Es ist wohl nicht falsch, diese Beobachtung als Indiz dafür zu nehmen, dass sowohl der KPI als auch der BPI den Minimalanforderungen genügen, die ein Deflator erfüllen sollte. Eine zweite Schlussfolgerung lautet, dass ein fehlender BPI allenfalls durch einen KPI, keinesfalls aber durch einen GPI ersetzt werden darf.” (Ritzmann-­‐Blickenstorfer & David 2012). Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 15 Zentrum für Zukunftsforschung (HSSO Q.02) during the period 1960 to 1985. As a result the connection of the two GDP deflators resulting from the construction of a long run series cumulates these two divergences, so that choosing one or the other type of deflation implies enormous differences in backward constructed GDP levels. The ratio between CPI and GDP deflator in figure 7 indicates by how much the double deflated GDP series lies above the CPI deflated one. This graph must be read from right to left because the base year is situated toward the end. After 1985 the ratio fluctuates only little and remains close to one. But as one moves further back in time the ratio strongly increases, reaching 48.7% in 1929. This suggests a clear trend difference between the two deflators. Between 1945 and 1985, the short-­‐term fluctuations of the ratio remain relatively small, suggesting that in the short-­‐term the deflators are strongly correlated. During the period 1890 to 1945 the ratio does not show a clear trend, but the volatility is clearly higher. This suggests a lower short-­‐term correlation between the deflators, stemming either from higher price volatility or from reduced accuracy of some of the involved price series. For the period 1851 to 1890 the ratio logically remains stable because both series rely on the CPI. The presence of minor fluctuations in the ratio stems from the fact that double deflation of the Ritzmann series changes the relative weight between industries and these changes are imposed on the earlier period because I connected the two datasets industry-­‐wise. Relative price changes in Switzerland between 1929 and 1990 Where does the divergence between CPI and GDP deflator come from? Different reasons might be behind the divergence of the two deflators between 1929 and 1985. For example, the divergence might be due to bad quality of the data. As we have seen double deflation tends to amplify measurement errors. However, the divergence between the CPI and the GDP deflator occurs in HSSO Q.17 and in HSSO Q.02, i.e. in two adjacent periods but in datasets that rely on different data sources. This suggests that the divergence is a result of the actual price evolution rather than measurement error. The matter at hand, here, are changes in relative prices. Double deflation imposes relative prices of the base year on other periods, while deflation with the CPI changes only the general price-­‐level. Industries that see the price of their output increase more rapidly than intermediate prices benefit from some sort of industry-­‐terms-­‐of-­‐trade gain. Double deflation eliminates such benefits while single deflation by output prices or by the CPI includes them. In a closed economy, gains and losses from industry-­‐terms-­‐of-­‐trade compensate each other at the aggregate level, but in an open economy inputs can be imported, so that double and single deflation can yield strongly diverging results for GDP growth. This links the industry-­‐
terms-­‐of-­‐trade effect to the country terms of trade effect analyzed by Kohli (2004). Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 16 Output and intermediate consumption quantities result from profit maximization through the comparison of a set of possible technological choices with prevailing relative prices. The relevant relative prices are those between final goods and intermediates in the same industry but also those between final goods and intermediates of different industries. These prices direct technological choices within industries but also structural change between industries. Imposing irrelevant prices of a distant base year to the data can seriously alter the estimated growth rate. In the extreme case, on which David (1962) insisted, positive value added can become negative after double deflation. But in any case, where relative prices change, double deflation introduces distortions into the measure of value added. At the aggregate level, if country-­‐terms-­‐of-­‐trade improve double-­‐deflated GDP underestimates economic growth. This is exactly the case of Swiss GDP between 1929 and 1990. Double-­‐deflated GDP grows at a rate of 2.16% per year between 1929 and 1960 compared to 2.91% for the CPI-­‐deflated growth rate. For the period 1960 to 1990 the corresponding growth rates are 2.72% and 3.31%. This makes an important difference, in particular if GDP is extrapolated backwards using these growth rates. Which industries are responsible for the difference? Tables 3 and 4 assess the contribution of each industry to the divergence between double-­‐deflated and CPI-­‐deflated GDP. The analysis relies on the base years of the original datasets. The fact that the GDP deflator is steeper than the CPI implies that double deflated GDP grows at a slower rate (figure 8). In table 3 this translates into negative values in the bottom line, i.e. double-­‐deflated GDP lies below CPI-­‐deflated GDP because the base year (1926/29) is situated in an earlier period. In table 4, the base year (1985) is posterior to the observed periods, so that double-­‐deflated GDP is higher than CPI-­‐deflated GDP. The tables show clearly that a few industries account for the lion share of the divergence between the two GDP series. Before 1960 the divergence is due to faster price inflation in the machine industry, construction, watchmaking, and commerce. Furniture/wood and the metal industry also contribute to the divergence but to a lesser extent. After 1960 the divergence is mainly driven by fast rising prices in the health sector. Construction and watchmaking again contribute significantly to the divergence, while the machine industry’s contribution is confirmed for the first year but then decreases and becomes negative. Two particularities of the 20th-­‐century Swiss economy explain the important changes in relative prices. First, Switzerland experienced a strong appreciation of its national currency, both in nominal and real exchange rates (see figures 10 and 11). Monetary and financial stability was the main priority of Swiss economic policy making during the 20th century. It is well known that Switzerland stuck to the gold standard for a very long time in the Great Depression (Bordo et al. 2006). Only in 1936 the Swiss franc was devaluated but even then gold convertibility was maintained. During WWII, Switzerland continued to sustain convertibility of the franc and to limit public debt. This allowed for the maintenance of the dollar exchange rate under the Bretton Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 17 woods system whereas several other countries, including some of the most important trading partners, devaluated their currencies during the early post-­‐war period. As a consequence the Swiss franc was revalued against these currencies. During the 1950s and 1960s the expansive monetary policy of the USA and Switzerland’s position as a tax haven combined with the strict maintenance of the fixed exchange rates led to capital inflows, increases of the monetary mass, and inflation pressure. But after the adoption of flexible exchange rates capital inflows resulted in a sharp appreciation of the Swiss franc in respect to most other countries (Halbeisen & Straumann 2012). The strong appreciation of the Swiss franc in nominal and real terms limited price inflation of imported intermediate goods. Figure 12 illustrates the producer price index of imports (HSSO H.39). The stability of the index is astonishing. Between 1945 and 1972 the index remained practically stable (+5%), whereas domestic producer prices rose by 57%. Only with the two oil shocks imported intermediates became more expensive. Until 1985 they rose by 62%, while domestic prices more than doubled (+139%). After 1985 both indices flattened out. Import prices even fell by 16% while domestic prices continued to rise by 4% until 2003. The favorable evolution of import prices must have profited to the metal, the machine, and the watchmaking industry, which acquire raw materials mainly through imports and probably also the construction industry. The consequences of the strong appreciation of the Swiss franc were not limited to imports, they also obliged exporting firms to move into high quality niches. According to Müller (2012, p.406) in 1980 Swiss exports were to 64% composed of high and medium high technology sectors. This is the case of the watchmaking and the machine industry. By 2003 this proportion increased to 73%. This translated into export prices that grew much faster than import prices. A direct export price index is not available for the considered period, but implicit import and export prices can be calculated from GDP by expenditure (HSSO Q.16). Figure 13 presents these indices. Until 1993 the two indices strongly diverged. The implicit import price index increased by roughly 60% compared to 150% for the export price index. The resulting terms of trade improvement amounted to 67% (figure 14). That is for a given quantity of exports Switzerland could import 67% more in 2004 than in 1948 without deteriorating its trade balance. Another relative price effect came from Switzerland’s dualist economic structure. The early development of the Helvetic economy occurred within weak institutional structures that made an active trade policy impossible. Helvetic trade policy was therefore distinctively liberal (Siegenthaler 1982). Toward the end of the 19th century, however, the Federal state pursued an increasingly protectionist trade policy (Humair 2004). During the interwar period this tendency has been re-­‐enforced and complemented with the formation of powerful cartels that regulated production, prices, and distribution in numerous domestic sectors, notably agriculture and the Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 18 food industry (Tissot & Moser 2012), construction and associated material industries (Cortat 2009; Hiestand 2010; Tissot & Moser 2012), but also in the watchmaking industry (Piotet 1988) Switzerland’s trade policy of the 20th century has been subsumed under the label of “selective protectionism”, that is a combination of protective measures for domestic sectors with integrative policies for export sectors and liberal capital markets (David et al. 2008). This duality of the Swiss economy has also contributed to a distortion of relative prices, namely between consumer prices and domestic producer prices. This can be seen from figure 12. Consumer prices have increased by 376% between 1945 and 2003, while domestic producer prices increased by only 147%. This leaves comfortable margins for industries that buy and sell within Switzerland. To conclude, Switzerland experienced important relative price shifts between 1929 and 1985. The double-­‐deflation method fails to account for these shifts. Both HSSO Q.17 and the HSSO Q.02 use fixed weight-­‐price indices over relatively long periods, imposing thereby irrelevant relative prices to observed economic structures. The double deflation of HSSO Q.17 relies on fixed weights of 1926/29 for the whole period 1890 to 1960 and HSSO Q.02 uses fixed weights of 1985 for the entire period 1960 to 1990. This reduces the estimated growth rate dramatically compared to single deflation with the CPI and lifts the GDP level of earlier periods accordingly. In the next section I show that international comparisons of Swiss GDP are seriously hampered by this measurement problem. Swiss GDP in international comparison This section provides a discussion of the different GDP series. Growth trajectories can be interpreted only in a certain context. Comparisons between different series and international comparisons are therefore essential for assessing the Swiss growth performance. Comparison of the different series Figure 16 presents the Maddison 2003 series, the Maddison update (Bolt & van Zanden 2013), and the double-­‐deflated and CPI-­‐deflated series discussed in the previous section. The new Maddison update and my double-­‐deflated series are practically identical. Both series rely on double deflation for the period after 1890 and on single deflation with the CPI before 1890. Slight differences between 1961 and 1990 stem from the fact that the new Maddison series between 1948 and 1990 relies on GDP estimates resulting from the expenditure approach (HSSO Q.06), while my series relies on the output approach estimates of HSSO Q.02 after 1960 and on HSSO Q.17 between 1948 and 1960. The close correlation of the two series between 1848 and 1960 can be interpreted as a sign of good quality of the Ritzmann series. For the period 1890 to 1948 the two series logically show exactly the same evolution, since both rely on HSSO Q.17. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 19 Before 1890 my series is less volatile because I smoothed the CPI before proceeding to deflation. Additional differences can stem from the fact that I connected the value added series industry-­‐
wise, while the other series was connected by a single scalar. The older Maddison series corresponds exactly to the new one after 1948. Between 1890 and 1948 it deviates clearly, and between 1851 and 1890 it evolves almost in parallel to the updated version. Small differences stem from the fact that Maddison (2003) used the average of two alternative deflators from HSSO Q.01, while the update uses only the CPI of the same source. As pointed out in section I of the paper, the different long-­‐term trend stems mainly from the unplausible growth spurts after the two world wars. The CPI-­‐deflated series relies on the same nominal series as my double-­‐deflated series. Hence the difference is entirely due to the different deflation procedure. As is clear from the preceding discussion, this series shows significantly faster growth between 1929 and 1985, when important relative price changes have occurred in the Swiss economy. This faster growth rate brings GDP to a 1930-­‐level that is comparable to that of the older Maddison series. However, the boom of the 1920s is shorter than in Maddison (2003) due to the later recovery after WWI, while growth is faster during the Belle Epoque. In order to situate Switzerland internationally, the figure depicts also GDP per capita of the UK, the USA, and an aggregate of 12 Western European countries. Table 5 provides numerical detail on this comparison. The stories told by the three series are clearly different, particularly concerning the initial situation around the mid-­‐19th century. In the original Maddison series Switzerland ranked 8th out of 13 countries, 11% below the European average and 38% below the UK level. According to the CPI-­‐deflated series Swiss GDP per capita ranked 10th and laid 18% below European average and 43% below the UK. But the double-­‐deflated series takes a completely different stance: Switzerland was already the third economy only 9% behind the UK, 7% behind the Netherlands, and 31% ahead of the European average. Until WWI, Switzerland registered comparatively fast growth rates according to all series, although growth of the old Maddison series is somewhat slower. According to the double-­‐
deflated series, Switzerland forged way ahead, became the richest economy in the world already in 1890 and by 1910 it reached a GDP per capita level almost twice as high as the European average and 36% ahead of the second nation, the USA. In the old Maddison series, Switzerland was “only” the third richest economy in 1910, still 13% behind the USA but 26% ahead of the European average. The CPI-­‐deflated series, while starting from a lower level, exhibits faster growth than the other series describing a rapid catch-­‐up movement reaching the European average between 1882 and 1890. However, even in 1910, Swiss GDP per capita remains 5% below the US level. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 20 During the period 1910 to 1945 the relative position of Swiss GDP per capita is subject to important fluctuations. But given the different 1910 levels of the three series, the interpretations are diverging. The double deflated series starts with such a large advance over the European level that Switzerland remains in the top position practically all along and way ahead of the European average. According to the Maddison 2003 series Switzerland increases its advance between 1910 and 1945, so that in 1945 the Swiss advantage is even bigger than in the double deflated series. According to the CPI deflated series, Switzerland changes between rank 2 and 5 and the relative position to the European average in 1945 is practically the same as in 1910. During the post-­‐war growth boom the three series diverge as well. Both the Maddison and the new double-­‐deflated series suffer from the double deflation problem and do not account for the important relative price changes that occurred in Switzerland during this period. This leads to serious underestimation of the growth rate. According to these two series the Swiss advance over the European average shrinks. Whereas, according to the CPI-­‐deflated series, the Swiss advance actually increases between 1945 and 1973. During the last period, 1973 to 2008, which is situated around the benchmark year, the GDP per capita level is logically quite similar in all series. But they also corroborate in terms of growth, showing that Switzerland was clearly loosing its advantage and falling behind. The crisis of the 1990s appears most strongly in the CPI deflated series In sum, the double-­‐deflated series depicts a Swiss economy, which was very rich already early on, reached a huge advantage in 1910, and remained almost undisputedly the richest economy between 1890 and 1980 (with the exception of a short American boom at the end of WWII). The old Maddison series shows a slow upgrading from below average to the top until 1960. Here the leadership over the USA was never more than 10%. Finally, the CPI-­‐deflated series tells a more nuanced story: rapid catch-­‐up from below average in 1851 to a level close to the USA in 1910; a struggle within the top five during the interwar period; and another catch-­‐up with the USA around 1973. What is common to all three series is the falling-­‐behind after 1973 although the 1990s crisis is stronger in the CPI deflated series. Table 6 puts growth rates of Swiss GDP in international comparison. I concentrate on the more thoroughly elaborated series, leaving the old Maddison series aside. Clearly and according to both series, 1882 to 1910 stands out as the most extraordinary growth period for Switzerland. According to the double-­‐deflated series, Switzerland was also a good performer in the 1920s. While post-­‐1945 Switzerland ranks between average and bad according to the double-­‐deflated series, the CPI-­‐deflated series suggests that Swiss growth was comparatively good between 1950 and 1973 and during the 1980s. But the bad performance of the 1970s and 1990s as well as the good performance during the early 21st century is common to both series. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 21 An interesting characteristic of Swiss growth is illustrated by the grey coloration of cells. Grey cells in columns 1 and 4 notify periods of contraction in international business cycles, while grey cells in columns 3 and 6 mark periods when Swiss growth is slower than that of the 12 European countries in total. The correspondence between grey cells in columns 1 and 3 with columns 4 and 6 illustrates that Swiss growth is rather pro-­‐cyclic, i.e. Switzerland, as a small open economy, is more affected by the international business cycle than other countries. The Long Depression of the 19th century and WWII are exceptions to this pattern. Table 7 compares GDP per capita growth internationally. For several growth periods the rankings are worse in per capita terms (1900-­‐1910, 1945-­‐1973, 1980-­‐1990, and 2000-­‐2008) than for aggregate GDP growth. This suggests that during these periods population growth, i.e. immigration, has contributed significantly to the good ranking. During the period 1922 to 1929, on the other hand, the ranking is better in per capita terms. Which series is right? In section II, I have highlighted a few serious shortcomings of double deflation. This method imposes relative prices of the base year on other years, which is an anachronism by definition. Historians should therefore be particularly reluctant to this method, at least if price indices are not frequently rebased. But also in a statistical perspective, double deflation yields correct measures only if price indices are continuously rebased (so that relative price changes are infinitesimal) and if the production function is separable. As demonstrated in the last section, relative price changes were very important in Switzerland between 1945 and 1990, and price indices have not been rebased regularly. Hence, the double deflated series is subject to important measurement errors. But, as Kohli (2004) shows, even if indices were chained continuously, double deflated GDP or value added does not include the gains or losses from relative price change. Theoretically this corresponds to measuring shifts of but not movements along the production possibilities frontier. However, the exclusion of gains from relative price changes is for most research questions rather counterintuitive. If GDP per capita growth is used as an indicator for welfare gains, all kinds of gains should be included. If GDP per capita growth is supposed to measure efficiency, one should not exclude efficiency of allocation, i.e. the result of adjustment to relative prices. If GDP is supposed to exclude windfall benefits, such as changes in world prices that are not influenced by a particular country, then one should also distinguish between endogenous innovation and technology transfers. Furthermore, the relative price changes that occurred in the Swiss economy between 1945 and 1990 are not all that exogenous because strict monetary policies and cartelization have caused them. Such interventions are not completely costless, either: consumers pay for cartelization through higher prices and export industries see their price competitivity eroded. But double-­‐deflated GDP is particularly inappropriate for international comparisons of GDP levels. The purpose of such comparisons is to assess the Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 22 relative wealth of nations at a particular moment in time and it does not make sense to assume that relative prices were those of another year. In my international comparison of Swiss GDP this becomes particularly clear: Monetary stability and cartelization during the second half of the 20th century cannot have contributed to Switzerland’s wealth or poverty in 1851. I argue therefore that the CPI deflated GDP series measures Switzerland’s wealth more accurately and that its growth trajectory is less distorted4. CPI deflation in other countries The comparisons presented in the last section suffer from an evident shortcoming. I have changed the deflation method for Swiss GDP but not that for the other countries. It might well be that changing the deflation method would also shift the GDP series of other countries down-­‐
ward, just like in the case of Switzerland. The elements that lay behind the important relative price changes in Switzerland, the strong appreciation of the national currency and cartelization, must not be unique to Switzerland. However, one can certainly say that few other countries have experienced these phenomena in such a strong way. Germany is probably the candidate that comes closest to Switzerland in this respect, although the appreciation of the Deutschmark was less pronounced than that of the Swiss franc, and cartels have been eliminated much earlier than in Switzerland. Furthermore, Germany is a much larger economy than Switzerland and it disposes of more raw materials, so that the terms of trade effect is probably much weaker, since a smaller proportion of inputs have to be imported. How much do GDP deflators and consumer price indices diverge in other countries? A test can be operated with the GDP deflators from the OECD National Accounts database. Figure 20 plots the ratio between the two deflators (CPI / GDP Deflator) for 13 countries. In most cases data is available from 1970 onwards. In order to have a longer period of observation, I used the 2005 benchmark year. These are recent National Accounts in which price indices were rebased at least every 10 years, so that the difference between relative prices of the base year and the observation year do not differ too much. Recall that in the case of Switzerland the deviation was as high as 64% at its maximum in 1857 and that a deviation of 46% accumulated over only 43 years (between 1929 and 1972). For most countries in figure 20 the divergence over the observed 35 years remains within 15%. In Norway the two deflators diverge temporarily by 35% but converge again by 1985. Italy, the USA, and Japan also deviate by more than 15%. However, for the USA and Japan the divergence goes in the opposite direction of what we found for Switzerland. In fact, in most countries the CPI appears to be steeper than the GDP deflator over the observed period. Only in Norway, Spain, Italy, and the UK the CPI is less steep. For all 4 See also Kohli’s arguments for including terms of trade benefits (Kohli 2004). Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 23 other countries deflating GDP with the CPI instead of the GDP deflator would lead to slower growth and to a higher GDP level as one constructs GDP backward from the benchmark. How about the Maddison series to which I compared Swiss GDP? Ideally, all the series should be deflated with the CPI in order to compare the Swiss CPI-­‐deflated GDP series internationally. Unfortunately the Maddison database does not provide nominal GDP series or GDP deflators. This means that in order to deflate these series differently one has to go through all the original sources from which Maddison and his successors have drawn their series. I could not do this for all the countries to which I compared the Swiss series, but I have done this investigation for the UK and the USA. Figures 18 and 19 provide the comparisons of the GDP Deflators and CPIs for those two countries. The graphs are analogous to figure 8. For the UK the ratio is remarkably stable. The fluctuations remain within 10% all the way back to 1870. Between 1855 and 1870 a few peaks appear but the divergence never trespasses the 20% line. For the USA, the fluctuations are more important but they remain within the 15% range. Contrary to the Swiss case, between 1950 and 1977 the US ratio is less than unity. Between 1900 and 1950 it is again around unity; and before 1900 it fluctuates around 1.1. In figure 17, I use these ratios to convert the Maddison series for the UK and the USA from double deflation to CPI deflation5. Apart from higher volatility before 1870 this changes only little for the UK series. For the US series the conversion leads to a slight downward shift before 1900. As a result, Switzerland passes ahead of the USA between 1892 and 1899. On the other hand, CPI deflation shifts the US series upwards after 1950, so that the USA has a larger advantage over Switzerland and the UK. In sum, for other countries the divergence between the CPI and the GDP deflator is not as important as it is for Switzerland. The comparison between Switzerland, the UK, and the USA is not significantly altered if one deflates UK and US GDP with the CPI. In most countries price indices were rebased more regularly than in Switzerland. The extreme case is Sweden, where National Accounts rely on annual Fischer chain indices all the way back to 1800 (Krantz & Schön 2007). Furthermore, the divergence between CPI and GDP deflator can go in both directions so that it seems reasonable to assume that downward biases and upward biases compensate each other to a certain extent. Hence, my interpretation of the Swiss CPI-­‐deflated GDP per capita series should hold also if a similar deflation was carried out on the other countries’ series. Cross-­‐checking with international benchmark comparisons of GDP per capita and wages So far, my argumentation in favor of the CPI deflated series has drawn on two types of arguments: a theoretical discussion of the problems with double deflation and an investigation 5 I supposed that the US ratio remained stable between 1851 and 1870 and that the UK ratio remained stable between 1851 and 1855. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 24 of relative price changes in Switzerland. Additional confirmation can be provided by the confrontation of my international comparisons with real wage comparisons and with direct benchmark comparisons of GDP per capita. Studer (2008) shows that, in 1850, Swiss nominal wages were only one third of British ones and 60% of French, Belgian, and Dutch salaries. By 1910 Swiss wages caught-­‐up and were about 70% of those in Britain. In real terms, Swiss wages were even lower. Certainly, wage levels depend also on bargaining power of workers, and the size of the city where the data comes from. London being much larger, it seems natural that wages are somewhat higher, and Swiss workers might well have suffered from weak bargaining power. But the GDP level suggested by the double deflated series is so high that it is hardly reconcilable with the low Swiss wages reported by Studer. For international comparisons, monetary aggregates have to be converted to a common currency. In order to be meaningful, such a conversion must take account of the different price levels, i.e. they must be purchasing-­‐power-­‐parity converted. The Maddison database and my GDP series rely on a single PPP benchmark, which was operated for the year 1990 (Maddison 1995). Then GDP levels were extrapolated backward and forward from this benchmark using the movement of real GDP. Several authors have argued that such time series projections over long periods are inadequate, because index number problems and methodological differences cumulate making comparisons across space spurious (Prados de la Escosura 2000; Ward 2001; Ward & Devereux 2003). The alternative to time series projections is the direct comparison with several benchmarks. However, just like time series projections are inaccurate for comparisons across space, benchmark estimates are inadequate for comparisons over time (Ward & Devereux 2004). Theoretically it is impossible to construct a database, which allows for comparisons in both dimensions. Empirically, however, it is possible to reconcile time series projections and benchmarks within a certain error margin (Broadberry 2003; Broadberry & Burhop 2007; Broadberry & Klein 2011). Table 8 provides a benchmark comparison of UK, US, and Swiss GDP per capita levels around 1905. Among the three countries Switzerland had the lowest and the USA the highest price level. These price levels can be used to construct PPP exchange rates and convert nominal GDP per capita into a common currency. According to this benchmark comparison the Swiss GDP per capita level between 1900 and 1910 was 9% below that of the UK and 14% below that of the USA. According to the CPI deflated time series projection the corresponding percentages are 1% and 6%. This lies within a 10% error margin. According to the double deflated time series projection Swiss GDP per capita would have been 35% above the UK and 31% above the USA. This is clearly very different from the situation described by the benchmark comparison. The Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 25 corresponding error is 48.4% for the Swiss-­‐UK comparison and 52.1% for the Swiss-­‐USA comparison. This benchmark comparison is of course very simplistic, because the underlying consumption basket covers only a small part of GDP and the prices are from a few cities only. However the fact that time series projections and benchmark comparisons corroborate each other suggests that both estimation methods seem to be reasonably accurate. For the US-­‐UK comparison both deflation methods are very well in line with the benchmark comparison. In accordance with my argumentation, the correspondence of the CPI deflated series is even better than that of the double deflated series. For the case of Switzerland, the benchmark corroborates the CPI deflated series but clearly shows that the double deflated series is not accurate. In fact, the double-­‐deflated Swiss GDP series provides an extreme example of the problem highlighted by Ward and Devereux (2003), namely an index number problem that leads to complete fallacy of the historical GDP estimates: “We are left with a basic index number problem. Each country uses different weights in the calculation of their domestic GDP series. Revisions of the weights also occur at differing intervals. Furthermore, each country includes new goods and adjusts for quality change differently. We suspect that these factors explain most of the discrepancies between the direct and long-­‐span income estimates because they result in growth rates that are measured differently.” (Ward & Devereux 2003, p.844). The list of possible sources of error drawn by Ward and Devereux can be extended by the impact of changes in terms of trade. Even if all growth rates were constructed the same way and perfect price indices were chosen, changes in terms of trade would lead to discrepancies between double-­‐deflated time series projections and benchmark comparisons because double deflation excludes the gains from terms of trade changes, while benchmark estimates include all gains realized under the prevailing price structure. Hence, single-­‐deflated GDP series have a better chance to be corroborated by benchmarks than double deflated series, i.e. they are probably more accurate. Prados de la Escosura (2000) has presented a database with 19 benchmark comparisons for the period 1820 to 1990. Switzerland enters the dataset only in 1880, so that only 11 benchmark comparisons for Switzerland are available. Since only few PPPs are available for the period before 1950, the author uses a short-­‐cut method. This method consists of estimating, in a first step, a structural relationship between PPPs and a number of explanatory variables including exchange-­‐rate converted nominal GDP for the period when PPPs are available. In a second step, the estimated structural relationship is used to predict PPPs for the period, when they are not available, and convert nominal GDP with these estimated PPPs. I combine the ratio between Swiss and UK GDP per capita levels from Prados de la Escosura with Maddisons GDP per capita levels for the UK to obtain alternative estimates for Swiss GDP. Figure 16 presents these estimates along with the different GDP series from the Maddison databse and myself. These Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 26 punctual estimates clearly infirm the Maddison update and my double deflated series; confirming the long-­‐run trend of the old Maddison series and my CPI deflated series. The estimates for 1950 and 1960 clearly confirm the CPI deflated series against the three others, which rely on double deflation. I conclude that there is ample evidence that my CPI deflated series is more accurate than all other Swiss real GDP series. This conclusion relies on theoretical considerations, an empirical investigation of relative price changes in Switzerland, real wage comparisons, and direct benchmark comparison with PPPs from a limited consumption basket or from a short-­‐cut estimation method. Implications for Swiss economic history An obvious implication of my new real GDP series is that Switzerland was much less rich than suggested by the series published in the Maddison update (Bolt & van Zanden 2013). According to this series, Switzerland was the richest country in the world for almost a century (1890 to 1980) with a large advance between 1890 and WWII. According to my CPI deflated series, Switzerland was always among the top five in Western Europe and North America but it took the lead only at two short moments and it never enjoyed a large advance. The growth trajectory of my series has also an implication on the discussion about the sources of Swiss growth. Different potential sources of Swiss growth have been advocated: the strong financial sector, Protestantism, stability (including neutrality, corporatism, and monetary stability), and market access (including the geographical location, openness, and internal market integration). The impact of Protestantism was most important from the 15th to 18th centuries, when protestant immigrants developed numerous proto-­‐industrial activities in Switzerland. Market access was most important during the second half of the 19th century, when international markets integrated rapidly. The construction of the Swiss railway system and its connection to the European networks between 1850 and 1910 allowed Switzerland to take fully advantage of its central geographical location. The Swiss financial sector has become a global player only in the second half of the 20th century. Stability, as well, was a distinct characteristic of Switzerland during the 20th century, notably after 1930, when corporatist regulations were most important and the defense of the Swiss franc became the top priority of economic policy making. The growth trajectory of my CPI deflated series identifies the period 1850 to 1910 as the most important growth period for Switzerland. In doing so it draws the attention away from Protestantism and stability, highlighting the importance of the extraordinary market access that Switzerland enjoyed mainly due to its favorable geographical location. Hence geography, rather than culture and institutions, explains the extraordinary wealth of Switzerland. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 27 Conclusion This paper provides a discussion of the data, which is available on Swiss GDP and value added, the way this data can be combined to form a long-­‐term series, and how it can be deflated and compared internationally. In most cases the methodological choices were made in favor of the method, which introduced no changes in relative value added levels between industries. The only exception to this rule was the connection of the estimates for 1851 to 1890 to the estimates for the subsequent period, because the levels of the 1851 to 1890 value added series were supposed to be less accurate than those of the subsequent period. This methodological choice has reduced non-­‐additivity problems in my database, and it increases the coherence between current price and constant price series. As a result the real value added series can be used for both types of comparisons: time series and cross section of industries. Recently, the Maddison database has been updated with a new series for Switzerland. This new series suggests that Switzerland was already very rich in 1851 and that it became the richest country in the world by 1890 staying in that position for almost the whole time until 1980. I show that this comparatively extremely high GDP level is a statistical artifact that stems from double deflation without frequently rebased price indices and from enormous relative price changes that occurred in Switzerland between 1945 and 1990. As a solution I propose a simple CPI-­‐deflation of nominal GDP. This generates a real GDP series, which is again closer to the old Maddison series, but with faster growth during the second half of the 19th century and the period 1950 to 1990. I argue that the measurement problem with double deflation is less important in other countries, so that the CPI-­‐deflated series can be compared to the Maddison series for other countries. Further support for the CPI deflated series and against the double deflated series comes from international wage comparisons elaborated by Studer (2008) and from an international benchmark comparison of UK, US, and Swiss GDP per capita levels. The international comparison suggests that, in 1851, Switzerland was on rank number 10 among 12 Western European countries plus the USA, 18% below the European average. Between 1851 and 1910 Switzerland operated a rapid catch-­‐up movement to the US and UK level. Between 1910 and 1945 Switzerland’s position relative to Europe fluctuated in the medium term but remained roughly stable in the long-­‐term. Another catch-­‐up with the USA occurred during the 1950s and 1960s. Between 1973 and 2000, Switzerland has fallen back to the European level and 28% behind the USA; and eight other countries have passed ahead of Switzerland. Finally, in the early 21st century Switzerland’s relative position improved again. The contributions of this paper are three-­‐fold. First, it provides a GDP series for Switzerland that builds on reliable sources and is very much in line with other types of evidence (international benchmark comparisons and international wage comparisons). Second, it points out a Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 28 methodological problem of double deflation that might also be a source of error in the GDP series of other (small open) economies. Third, it throws a different light on the development trajectory of Switzerland shifting the accent from proto-­‐industry and the first industrial revolution to the second industrial revolution and the post-­‐WWII boom. This has also an incidence on the identification of the possible sources of Swiss growth shifting the focus from protestant immigration and stability to market integration. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 29 Data sources BFS 01: Bundesamt für Statistik. Gross domestic product (GDP), production approach 1990-­‐
2008. Data files: www.bfs.admin.ch, je-­‐e-­‐04.03.01 and je-­‐e-­‐04.03.02. BFS 02: Bundesamt für Statistik. Produktionskonto der Schweiz 1990-­‐1994. Neuchâtel: BFS, years 1993 to 1996. BFS 03: Bundesamt für Statistik. Landesindex der Konsumentenpreise, Totalindex auf allen Basen seit seiner Einführung (Total Multibasis) 1921-­‐2014 (su-­‐d-­‐05.02.10). I used column 1. The different columns differ only because of rounding errors. HSSO G.09. Historische Statistik der Schweiz Online, table G.09. Available at: http://www.fsw.uzh.ch/histstat/main.php. HSSO H.18. Historische Statistik der Schweiz Online, table H.18. Index der Konsumentenpreise nach Bedarfsgruppen 1890-­‐1921. HSSO H.26. Historische Statistik der Schweiz Online, table H.26. Kleinhandelspreise für Lebensmittel und Kohle in den Städten Zürich, Bern und Basel 1890-­‐1921. HSSO H.39. Historische Statistik der Schweiz Online, table H.39. Produzenten-­‐ und Importpreisindex (GPI) und Konsumentenpreisindex (KPI) nach Herkunft der Ware 1804-­‐2003. HSSO Q.01. Historische Statistik der Schweiz Online, tables Q.01, K.16, M.01, N.01, O.10, P.01, U.01. Bruttowertschöpfung nach Branchen 1860-­‐1890. See also explanations in Siegenthaler, H. & Ritzmann-­‐Blickenstorfer, H. éd., 1996. Historische Statistik der Schweiz, Zürich: Chronos; and Projer, E., 1990. III Schätzung der Bruttowertschöpfung im 2. Sektor NF-­‐Projekt: Geldmenge und Wirtschaftswachstum in der Schweiz, 1851 bis 1913 1. Aufl., Zürich: Sozialökonomisches Seminar, Abt. Wirtschaftsgeschichte. HSSO Q.02. Historische Statistik der Schweiz Online, table Q.02. Bruttowertschöpfung nach Branchen 1960-­‐1990. See also Kneschaurek, F. et al., 1983. Daten für Branchenmodelle der Schweizerischen Wirtschaft, Zürich. HSSO Q.06: Historische Statistik der Schweiz Online, table Q.06. Sozialprodukt nach Verwendungsarten, 1948-­‐1990. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 30 HSSO Q.16: Historische Statistik der Schweiz Online, table Q.16. Bruttoinlandprodukt nach Verwendungsarten zu Preisen von 1990 und nominal, 1948-­‐2005 HSSO Q.17. Historische Statistik der Schweiz Online, table Q.17. Bruttowertschöpfung nach Branchen 1890-­‐1960. See also Ritzmann-­‐Blickenstorfer, H., 1998. « Alte Statistiken » -­‐ ein Eldorado für Langzeitreihenbildner. Indikatoren zur regionalen Wirtschaftsentwicklung im Zeitraum 1888-­‐1965. Geschichte und Informatik, 9, p.103‑120; and Ritzmann-­‐Blickenstorfer, H. & David, T., 2012. Bruttoinlandprodukt 1890-­‐1960. In Wirtschaftsgeschichte der Schweiz im 20. Jahrhundert. Zürich. I also used unpublished data on value added by industry and corresponding employment figures provided to me by Ritzmann. 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!
!
!
! (𝑤!
− 𝑎! )! where 𝑤! stands for fitted wages of industry i, 𝑎! for, value added per worker in industry i. Wages were fitted in such a way that the average industry wage is equal to average value added of all industries. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 37 Table 3 : Industry contribution to the divergence between GDP deflator and CPI (base year : 1926/29) R 01 R 02 R 03 R 04 R 05 R 06 R 07 R 08 R 09 R 10 R 11 R 12 R 13 R 14 R 15 R 16 R 17 R 18 R 20 R 21 R 22 R 23 R 24 R 25 R 26 R 27 R 28 R 29 R 31 R 32 R 33 R 34 R 35 R 36 R 37 R 38 R 39 R 40 R 41 R 42 R 46 Rationale: Landwirtschaft Gartenbau, Forstwirtschaft, Fischerei Bäckerei, Müllerei Schokoladefabrikation Metzgerei Bierbrauerei übige Nahrungsmittelindustrie Bearbeitung des Tabaks Baumwolle Seide Kunstseide Wolle Stickerei Textilveredelung übrige Textilindustrie Wirkerei und Strickerei Konfektion, Wäsche und übrige Bekleidung Schuhe Leder Kautschuk, Kunststoff Papier, Karton Graphisches Gewerbe Holz, Möbel, Musikinstrumente Steine, Erden Chemie Metalle Maschinenindustrie Uhren, Schmuck Bergbau Bauwirtschaft Elektrizität, Gas, Wasser Handel Banken Versicherungen Gastgewerbe Transport PTT, Radio, TV öffentliche Verwaltung Gesundheitswesen, Körperpflege, Unterricht, Wissenschaft, Kunst, Erholung Reinigungsgewerbe, Hausdienst,( Taglöhnerei) Vermittlungsdienstleistungen Total 1955 -­‐0.5 -­‐0.3 0.0 0.0 -­‐0.2 0.0 -­‐0.1 0.2 -­‐0.3 0.4 0.5 0.2 -­‐0.1 -­‐0.2 -­‐0.1 -­‐0.3 1956 -­‐0.4 -­‐0.3 -­‐0.1 0.0 -­‐0.2 0.0 -­‐0.1 0.2 -­‐0.2 0.4 0.4 0.2 -­‐0.1 -­‐0.2 0.0 -­‐0.2 1957 -­‐0.8 -­‐0.3 -­‐0.2 0.0 -­‐0.2 0.0 -­‐0.1 0.2 -­‐0.2 0.4 0.4 0.2 -­‐0.1 -­‐0.2 0.0 -­‐0.3 1958 -­‐0.2 -­‐0.2 -­‐0.2 0.0 -­‐0.2 0.0 -­‐0.1 0.3 -­‐0.1 0.4 0.4 0.2 -­‐0.1 -­‐0.2 0.0 -­‐0.3 1959 -­‐0.5 -­‐0.2 -­‐0.2 0.0 -­‐0.2 0.0 -­‐0.1 0.2 0.0 0.4 0.4 0.2 -­‐0.1 -­‐0.1 0.0 -­‐0.2 1960 0.0 -­‐0.2 -­‐0.3 0.0 -­‐0.2 0.0 -­‐0.2 0.2 0.0 0.4 0.4 0.2 0.0 -­‐0.2 0.0 -­‐0.2 -­‐0.3 0.1 0.1 0.2 0.2 -­‐0.3 -­‐1.4 0.1 -­‐0.6 -­‐1.1 -­‐4.5 -­‐2.8 -­‐0.1 -­‐4.0 1.0 -­‐2.5 0.0 0.0 -­‐0.5 1.3 0.0 0.0 -­‐0.3 0.0 0.1 0.3 0.2 -­‐0.3 -­‐1.5 0.0 -­‐1.0 -­‐1.3 -­‐4.6 -­‐2.9 -­‐0.1 -­‐4.0 0.8 -­‐2.7 0.0 0.0 -­‐0.7 1.4 -­‐0.1 0.0 -­‐0.3 0.0 0.1 0.1 0.1 -­‐0.5 -­‐1.4 -­‐0.5 -­‐1.2 -­‐1.2 -­‐4.4 -­‐3.0 -­‐0.1 -­‐4.8 0.8 -­‐2.9 0.0 0.0 -­‐0.8 1.4 -­‐0.1 0.0 -­‐0.3 0.0 0.0 0.0 0.1 -­‐0.6 -­‐1.4 -­‐0.4 -­‐1.3 -­‐1.0 -­‐5.1 -­‐2.5 -­‐0.1 -­‐4.2 1.2 -­‐2.4 0.0 0.0 -­‐0.9 1.5 -­‐0.1 0.0 -­‐0.2 0.0 0.1 0.0 0.2 -­‐0.7 -­‐1.6 -­‐0.2 -­‐1.2 -­‐0.8 -­‐4.9 -­‐2.2 -­‐0.1 -­‐5.0 0.9 -­‐2.1 0.0 0.0 -­‐1.2 1.4 -­‐0.1 0.0 -­‐0.2 -­‐0.1 0.1 0.1 0.1 -­‐0.7 -­‐1.7 -­‐0.5 -­‐0.8 -­‐0.8 -­‐5.3 -­‐2.2 -­‐0.1 -­‐5.6 1.1 -­‐1.9 0.0 0.0 -­‐1.2 1.3 -­‐0.1 0.0 -­‐0.1 -­‐0.1 -­‐0.1 -­‐0.1 -­‐0.1 -­‐0.1 0.0 0.0 -­‐16.3 0.0 0.0 -­‐17.4 0.0 0.0 -­‐20.0 0.0 0.0 -­‐18.0 0.0 0.0 -­‐18.3 0.0 0.0 -­‐18.9 This table decomposes the difference between double deflated GDP and CPI deflated GDP into industries’ contribution. Industries that use imported raw materials and strongly regulated sectors have contributed most to the divergence between the two deflators. Notes: Industry deflators are obtained by dividing nominal value added by real value added. These industry deflators can then be compared to the CPI. The implicit aggregate GDP deflator is a weighted average of the industry deflators, where the weights correspond to the industries’ shares in total nominal value added. The reported industry contributions are ratios between double-­‐deflated GDP and CPI-­‐deflated GDP multiplied by the industry’s share in nominal GDP. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 38 Table 4 : Industry contribution to the divergence between GDP deflator and CPI (base year : 1985) 1960 1961 1962 1963 1964 -­‐0.57 -­‐0.77 -­‐0.95 -­‐0.82 -­‐0.92 0.66 0.78 0.68 0.38 0.42 -­‐0.70 -­‐0.74 -­‐0.63 -­‐0.60 -­‐0.59 0.07 0.06 0.06 0.08 0.07 Leder, Kautschuk, Kunststoff -­‐0.35 -­‐0.32 -­‐0.21 -­‐0.09 -­‐0.09 SGZ 06 Papier und Karton -­‐0.24 -­‐0.22 -­‐0.22 -­‐0.17 -­‐0.15 SGZ 07 Graphisches Gewerbe 0.37 0.30 0.31 0.27 0.29 SGZ 08 Chemische Produkte -­‐1.06 -­‐0.87 -­‐1.11 -­‐1.25 -­‐1.37 SGZ 09 Metalle -­‐0.63 -­‐0.68 -­‐0.38 -­‐0.03 -­‐0.20 SGZ 10_11 Maschinen und Elektronik 1.22 0.88 0.47 0.31 -­‐0.10 SGZ 12 1.37 1.28 1.28 1.23 1.14 SGZ 13 Uhren und Schmuck Uebrige Industrien: Holz und Möbel, Steine und Erden, Bergbau, Musikinstrumente, Spielwaren, Sportgeräte 0.07 -­‐0.14 -­‐0.26 0.04 -­‐0.06 SGZ 14 Bauwirtschaft 2.71 2.10 1.68 1.22 0.88 SGZ 15 Elektrizität, Gas und Wasser -­‐0.26 -­‐0.25 -­‐0.35 -­‐0.36 -­‐0.57 SGZ 16 Banken, Versicherungen 0.99 0.93 0.90 0.84 0.75 SGZ 17 Gastgewerbe 0.45 0.35 0.26 0.25 0.15 SGZ 18 Verkehrs-­‐ und Nachrichtenwesen Übrige Dienstleistungen: Oeffentliche Verwaltung, Gesundheit, Bildung, Kunst, Erholung, Kirche 0.12 0.16 0.09 -­‐0.06 -­‐0.13 8.05 7.27 7.19 6.19 5.44 12.27 10.13 8.80 7.42 4.97 SGZ 01 Primärsektor SGZ 02 Nahrungs-­‐ und Genussmittel SGZ 03 Textilien SGZ 04 Bekleidung und Schuhe SGZ 05 SGZ 19 Total Rationale: This table decomposes the difference between double deflated GDP and CPI deflated GDP into industries’ contribution. Industries that use imported raw materials and strongly regulated sectors have contributed most to the divergence between the two deflators. Notes: Industry deflators are obtained by dividing nominal value added by real value added. These industry deflators can then be compared to the CPI. The implicit aggregate GDP deflator is a weighted average of the industry deflators, where the weights correspond to the industries’ shares in total nominal value added. The reported industry contributions are ratios between double-­‐deflated GDP and CPI-­‐deflated GDP multiplied by the industry’s share in nominal GDP. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 39 Table 5: Swiss GDP per capita in international comparison 1851 to 2000 GDP per capita in 1990 Geary-­‐Khamis dollars USA France Germany Belgium Netherlands Denmark 12 Western Europe Switzerland (Maddison 2003) Switzerland (double deflation) Switzerland (CPI) 1568 2219 2288 2376 2876 2965 3610 4710 4793 2573 5186 7398 12824 14766 17647 20392 22057 1408 2112 2044 2428 2985 3348 3331 4051 5406 4514 3881 7705 11966 14114 15929 18944 20801 1886 2861 3136 3428 3731 4064 4413 5054 5150 4333 5462 6952 12170 14467 17197 20809 23701 2388 2876 2985 3186 3329 3783 4599 5689 5544 2686 5996 8287 13081 14705 17262 22148 25112 1662 2112 2240 2523 3017 3705 4166 5075 5993 5066 6943 8812 13945 15227 18452 22966 24789 1697 2369 2449 2703 3155 3442 3609 4452 5095 4129 4944 7498 12070 13958 16793 20131 22359 1514 2645 2400 3182 3833 4331 4618 6332 6360 7752 9064 12457 18204 18779 21487 22475 25104 2222 3309 3597 4711 5765 6732 6343 8418 7915 7322 9023 12238 18022 18732 21487 21642 24690 1385 2058 2286 3041 3936 4732 4310 5660 5872 5663 7260 10323 17424 17513 21487 20805 24371 Switzerland (CPI) Ratio Switzerland/Highest Switzerland (double deflation) 1851 8 3 10 0.89 1.31 0.82 1875 4 2 8 1.12 1.40 0.87 1882 5 2 6 0.98 1.47 0.93 1890 5 1 5 1.18 1.74 1.13 1900 3 1 3 1.21 1.83 1.25 1910 3 1 2 1.26 1.96 1.38 1922 3 1 5 1.28 1.76 1.19 1929 2 1 3 1.42 1.89 1.27 1939 2 1 4 1.25 1.55 1.15 1945 2 2 3 1.88 1.77 1.37 1950 2 2 2 1.83 1.83 1.47 1960 1 1 2 1.66 1.63 1.38 1973 1 1 1 1.51 1.49 1.44 1980 1 1 2 1.35 1.34 1.25 1990 2 2 2 1.28 1.28 1.28 2000 4 5 9 1.12 1.08 1.03 2008 5 7 9 1.12 1.10 1.09 Rationale: This table compares the different GDP per capita series internationally. Switzerland (Maddison 2003) Ratio Switzerland/Europe 12 Switzerland (CPI) Switzerland (double deflation) Switzerland (Maddison 2003) Ranking Switzerland among 13 1924 2599 3338 3392 4091 4964 5540 6899 6561 11709 9561 11328 16689 18577 23201 28702 31251 Switzerland (CPI) 2451 3434 3643 4009 4492 4611 4637 5503 6262 7056 6939 8645 12025 12931 16430 21046 24602 Switzerland (double deflation) UK 1851 1875 1882 1890 1900 1910 1922 1929 1939 1945 1950 1960 1973 1980 1990 2000 2008 Switzerland (Maddison 2003) 0.62 0.77 0.66 0.79 0.85 0.87 0.83 0.92 0.97 0.66 0.95 1.10 1.09 1.01 0.93 0.78 0.80 0.91 0.96 0.99 1.18 1.28 1.36 1.15 1.22 1.21 0.63 0.94 1.08 1.08 1.01 0.93 0.75 0.79 0.57 0.60 0.63 0.76 0.88 0.95 0.78 0.82 0.90 0.48 0.76 0.91 1.04 0.94 0.93 0.72 0.78 The periodization corresponds to international business cycles. Between 1890 and 2000 the periodization corresponds to the one proposed by (Müller et al. 2012). 1875 has been chosen because several of the selected countries witnessed negative growth in this year. 1882 corresponds to a financial crisis in Lyon (Bairoch 1997, vol. 2, Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 40 p. 407-­‐408) and to a down-­‐turn in Switzerland. And 1851 was chosen simply because it is the beginning of the Swiss series. Sources: Switzerland: see text; others: the Maddison database (Bolt & van Zanden 2013). 12 Western European countries: Austria, Belgium, Denmark, Finland, France, Germany, Italy, Netherlands, Norway, Sweden, Switzerland, United Kingdom. Table 6: Swiss GDP growth in international comparison Swiss GDP growth (double deflation) Ranking Switzerland among 13 Difference: Switzerland-­‐
Europe12 Swiss GDP (CPI) Ranking Switzerland among 13 Difference: Switzerland-­‐
Europe12 1851-­‐1875 2.3 6 0.2 2.2 6 0.2 0.5 1.9 0.8 2.1 3 0.8 4.0 1 2.1 3.8 2 1.4 3.1 3 1.3 -­‐0.5 12 -­‐0.9 4.5 5 0.8 0.8 10 -­‐1.1 0.2 5 3.6 6.4 8 2.0 5.0 4 0.0 5.6 2 1.1 -­‐0.1 13 -­‐2.3 1875-­‐1882 1.8 6 1882-­‐1890 3.8 1 1890-­‐1900 3.2 3 1900-­‐1910 2.8 3 1.0 -­‐0.6 1.0 -­‐2.1 1910-­‐1922 -­‐0.2 12 1922-­‐1929 4.7 3 1929-­‐1939 -­‐0.2 13 1939-­‐1945 -­‐0.5 3.0 1.1 -­‐0.5 0.0 5.6 9 1950-­‐1960 4.5 7 1960-­‐1973 4.5 7 0.4 5 1945-­‐1950 1973-­‐1980 13 1980-­‐1990 2.1 9 1990-­‐2000 0.7 13 -­‐1.9 0.0 -­‐1.5 0.6 2.8 3 0.6 0.3 13 -­‐1.9 2000-­‐2008 2.2 4 2.5 3 1.0 Rationale: This table compares GDP growth rates internationally. The Period 1882 to 1910 stands out as the most important growth period. Grey cells in columns 1 and 4 notify periods of contraction in international business cycles, while grey cells in columns 3 and 6 mark periods when Swiss growth is slower than that of the 12 European countries in total. The correspondence between grey cells in columns 1 and 3 with columns 4 and 6 illustrates that Swiss growth is rather pro-­‐cyclic. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 41 Table 7: Swiss GDP per capita growth in international comparison Swiss GDP growth (double deflation) Ranking Switzerland among 13 Difference: Switzerland-­‐
Europe12 1851-­‐1875 1.7 4 0.3 1875-­‐1882 1.2 3 0.7 2.2 0.5 0.7 1882-­‐1890 3.4 1 1890-­‐1900 2.0 3 1900-­‐1910 1.6 5 1910-­‐1922 -­‐0.5 12 1922-­‐1929 4.1 2 1929-­‐1939 -­‐0.6 13 1939-­‐1945 -­‐1.3 5 1.1 -­‐2.0 2.2 1945-­‐1950 4.3 10 0.6 -­‐0.9 1950-­‐1960 3.1 7 1960-­‐1973 3.0 12 1973-­‐1980 0.6 13 -­‐1.2 -­‐0.7 -­‐1.5 1980-­‐1990 1.4 12 -­‐0.5 0.1 13 1.7 5 -­‐1.8 0.3 1990-­‐2000 2000-­‐2008 Rationale: see table 6. Swiss GDP (CPI) Ranking Switzerland among 13 Difference: Switzerland-­‐
Europe12 1.7 4 0.3 1.5 2 1.0 3.6 1 2.4 2.6 1 1.1 1.9 4 1.0 -­‐0.8 12 -­‐1.2 4.0 3 0.9 0.4 9 -­‐1.0 -­‐0.6 5 2.8 5.1 8 1.4 3.6 6 -­‐0.7 4.1 6 0.4 0.1 13 -­‐2.0 2.1 6 0.2 -­‐0.3 13 -­‐2.2 2.0 4 0.7 Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 42 Table 8: Benchmark comparison and time series projection for 1905 GDP per capita Tea, coffee (1lb) UK USA Expendi-­‐
Expendi-­‐
Budget Prices ture Prices ture shares (pence) (pence) (pence) (pence) 0.053 18.000 0.954 15.415 0.817 Sugar (1lb) 0.044 Bacon and sausage (1lb) 0.064 Beef and veal (1lb) 0.139 Pork (1lb) 0.052 Lamb and mutton (1lb) 0.054 Cheese (1lb) 0.027 Butter and margarine (1lb) 0.117 Potatoes (7lb) 0.057 Flour and meal (7lb) 0.060 Bread (4lb) 0.187 Milk (qt) 0.091 Eggs (doz) 0.054 Total 1.000 8.000 0.512 8.000 1.112 8.000 0.416 8.250 0.446 7.000 0.189 1.521 3.000 0.171 9.000 0.540 5.000 0.935 0.088 13.000 2.000 3.500 0.319 12.000 0.648 7.850 Currency conversion PPP 100 1.00 1.00 Benchmark comparison Nominal GDP per capita GDP per capita in 1905 PPP £ GDP per capita relative to UK GDP per capita relative to USA Time series projection Relative to UK Relative to USA Relative to UK Relative to USA Real GDP pc (double deflation) Real GDP pc (CPI deflation) 9.250 0.592 7.375 1.025 6.500 0.338 7.375 0.398 10.000 0.270 16.750 1.960 7.000 0.399 12.500 0.750 11.125 2.080 4.500 0.410 14.400 0.778 Exchange rate (per £) 0.121 9.938 Price level relative to UK 2.750 £M. 47.8 100 97 GK $ 4340 100 95 $M. Double deflation USA/UK 0.108 4.758 0.304 8.218 1.142 8.520 0.443 8.218 0.444 8.607 0.232 14.143 1.655 3.330 0.190 11.505 0.690 5.017 0.938 2.170 0.197 10.298 0.556 7.194 310.6 GK $ 50.5 106 100 25.17 23.07 SFr.M. PPP £ 1004.0 43.5 91 86 4660 92 GK $ 6109 103 135 100 131 GK $ GK $ 4302 106 99 100 94 Error margin between benchmark series projection and time 0.293 2.465 127 4.86 6.15 4521 5.536 47.8 PPP £ 100 95 PPP £ GK $ CH Expendi-­‐
Prices ture (pence) (pence) 4583 -­‐2.41 CH/USA CH/UK 52.06 48.40 CPI deflation -­‐0.02 8.89 8.86 Rationale: This table confronts international benchmark comparisons and time series projections. The confrontation corroborates the CPI deflated GDP series and invalidates the double deflated one. Notes: The underlying consumption basket, budget shares, as well as British and American prices are from Williamson (1995). Swiss prices are from HSSO H.26 averages for Zürich, Bern and Basel. I excluded housing rents from the PPP consumption basket, because these are highly dependent on the sample cities and might not be representative for the national price level. Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 43 Figure 1: Swiss GDP per capita according to different sources Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 44 Figure 2: Value added per worker (HSSO Q.02 original level) and wages (HSSO G.02), 1970 Rationale: Figures 1 to 6 compare relative productivity differentials between industries with relative wage differences. At all considered periods, the productivity differentials from the original value-­‐added level fits wage differentials better. Figure 3: Value added per worker (HSSO Q.02 adjusted industry-­‐wise to HSSO Q.18a) and wages (HSSO G.02), 1970 Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 45 Figure 4: Value added per worker (HSSO Q.02 original level) and wages (HSSO G.02), 1975 Figure 5: Value added per worker (HSSO Q.02 adjusted industry-­‐wise to HSSO Q.18a) and wages (HSSO G.02), 1975 Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 46 Figure 6: Value added per worker (HSSO Q.02 original level) and wages (HSSO G.02), 1980 Figure 7: Value added per worker (HSSO Q.02 adjusted industry-­‐wise to HSSO Q.18a) and wages (HSSO G.02), 1980 Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 47 Figure 8: GDP deflator and consumer price index (1990=100), 1851-­‐2008 Figure 9: Real GDP according to different deflation methods Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 48 Figure 10: Nominal exchange rates of the Swiss franc (1946=100), 1946-­‐1999 Source: Officer (2014). Figure 11: Real exchange rates of the Swiss franc (1946=100), 1946-­‐1999 Note: Real exchange rate = nominal exchange rate (1946=100) + CPI growth Switzerland – CPI growth other country Source: nominal exchange rates from Officer (2014); CPI from Schularick and Taylor (2012). Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 49 Figure 12: Import prices and domestic prices (1945=100), 1914-­‐2003 Source: Producer prices from HSSO H.39; CPI from BFS 03. Figure 13: Implicit import and export price indices (1948=100), 1948-­‐2004 Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 50 Figure 14: Terms of trade (1948=100), 1948-­‐2004 Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 51 Figure 16: Swiss real GDP per capita in international comparison Figure 17: Swiss, British and American real GDP per capita (CPI-­‐deflated) Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 52 Figure 18: GDP Deflator and CPI, UK 1851 to 2003 Rationale: In the case of the UK, the GDP deflator and the CPI diverge only little (cp. Figure 7). Sources: GDP deflator: after 1965 from OECD National Accounts; 1855-­‐1965 from Feinstein (Feinstein 1972, p.table 61). CPI from O’Donoghue et al (2004). Figure 19: GDP Deflator and CPI, USA 1851 to 1990 Rationale: In the case of the USA, the GDP deflator and the CPI diverge much less than in Switzerland (cp. Figure 7). Sources: GDP deflator: 1870-­‐1890 from Balke and Gordon (1989); 1890-­‐1929 NGDP/RGDP from Kendrik (1961, p.293, 296); 1929-­‐1950 from BEA (United States Bureau of Economic Analysis 1993, p.171); 1950-­‐1959 from BEA (United States Department of Commerce 1998, p.159), 1959-­‐1990 from Seskin (1999). CPI from Schularik et al. (2012). Christian Stohr / Let’s get this right: Swiss GDP and value added by industry from 1851 to 2008 53 Figure 20: CPI / GDP Deflator (2005=1) for 13 countries Rationale: In most OECD countries the GDP deflator and the CPI diverged only little over the last 40 years. Contrary to Switzerland, the CPI is steeper than the GDP deflator (cp. Figure 7). Sources: GDP Deflator from OECD National Accounts, GDP by output approach 2005 benchmark; CPI from Schularick and Taylor (Schularick & Taylor 2012).