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Japanese episodic long swings in economic growth
Explorations in Economic History Explorations in Economic History 44 (2007) 224–241 www.elsevier.com/locate/eeh
Japanese episodic long swings in economic growth Solomos Solomou a
a,*
, Masao Shimazaki
q
b
Faculty of Economics, University of Cambridge, UK b Ministry of Finance, Tokyo, Japan Received 20 April 2005 Available online 3 February 2006
Abstract Prior to World War II Japanese economic growth was characterised by episodic ‘long swings,’ low frequency fluctuations in economic growth averaging about 20–25 years in duration. At the aggregate level, these inter-period growth variations dominated both shorter-term fluctuations and longer-term trend acceleration. The paper describes the long swings of the Japanese economy and re-evaluates conventional explanations. Ó 2006 Elsevier Inc. All rights reserved. Keywords: Episodic Economic Growth; Long swings; Japanese Economic History
1. Introduction The path of modern economic growth has displayed punctuated features. Recent examples are: the global slowdown in the 1970s; the slow growth episodes observed in Argentina, Brazil, Mexico, and Chile during the 1980s; and in Japan and Germany since the 1990s. Because the amplitude of such movements in economic growth is high, and the average period of adjustment is long, relative to the business cycle frequency, the economic and social costs can be high. Historical analysis of the process of growth shows us that q Research for this paper has been supported by a Research Grant from the UK ESRC (No. L138 25 1045). We thank the Editor and an anonymous referee for useful comments and guidance. Andrew Harvey, Mark Metzler, Carl Monk, Adrian Pagan, Hugh Patrick, Cristiano Ristuccia, Miyohei Shinohara, Graeme Snooks, Jeff Williamson, Weike Wu and participants of the Institute of Advanced Studies seminar at the ANU gave us useful comments on a previous version of this paper. * Corresponding author. E-mail address: [email protected] (S. Solomou).
0014-4983/$ - see front matter Ó 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.eeh.2005.12.001
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there are many more examples of such episodic growth phases. Treated individually, there is a bias to account for such periods by analysing the effects of specific shocks; treated as a general feature of economic growth, we are forced to consider the possibility of broader explanations for such processes. Kehoe and Prescott (2002) use the real business cycle (RBC) framework to explain episodic ‘‘Great depressions,’’ averaging durations of approximately a decade, as the result of institutional failings and policy mistakes. In contrast to the idea of one-off ‘‘Great depressions,’’ the long swing perspective to historical economic growth has observed fluctuations of high and low economic growth of approximately 20 years in duration (Abramovitz, 1959, 1961; Kuznets, 1958). The existing evidence suggests that long swings were a pervasive aspect of national historical economic growth, and were observed in a wide set of economies, including America, Argentina, Australia, Brazil, Britain, Canada, France, and Germany.1 Similar results have been reported for Japan (Minami, 1986; Mosk, 2001; Nakamura, 1983; Ohkawa, 1979; Ohkawa and Rosovsky, 1973; Shinohara, 1962; Yamazawa and Yamamoto, 1979). Our aim here is to use Japan as a historical case study to develop our understanding of such growth episodes. Japan is an interesting case study because, for most of the period before World War II, the magnitude of inter-period variations in growth is high, allowing us to evaluate the long swing hypothesis, that there is a cyclical or quasi-cyclical component to episodic growth, against the alternative RBC hypothesis that these observed phases are purely random. Section 2 outlines the trend-cycle decomposition methods used to describe Japan’s growth swings and identify whether there is a cyclical component. The existing literature has described Japan’s episodes of growth using conventional statistical techniques such as moving averages (Ohkawa and Rosovsky, 1973; Shinohara, 1962, 1978). It is now well known that such methods may generate statistical artifacts (Bird et al., 1965) and hence we use developments in trend-cycle decomposition to offer a more general description of the observed historical trends and reinforce the view that Japanese long swings are not a product of data transformation. Sections 2.1 and 2.2 present an analysis of Japanese long swings looking at aggregate and disaggregate evidence. Section 3 evaluates some of the proximate causes of the observed swings in economic growth and discusses the results in the context of the existing literature. Finally, Section 4 evaluates the role of policy regime in helping us to understand long swings in economic growth. 2. Methodology To shed some light on the empirical features of trend movements and low frequency fluctuations in economic growth during this period, we use the following unobserved components (UC) structural model of time series decomposition (Harvey, 1985, 1989): y t ¼ lt þ wt þ et ;
ð1Þ
where lt ¼ lt1 þ bt1 þ nt ;
1
See Solomou (1987, 1998) for references to the national case studies of long swings listed here.
ð2Þ
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bt ¼ bt1 þ mt ;
ð3Þ
wt ¼ ð1 q cos kLÞxt þ ðq sin kLÞxt =ð1 2q cos kL þ q2 L2 Þ; where lt stands for the trend component of yt; nt allows for level shifts to the trend component; mt accounts for shocks to the slope, bt; wt captures the cyclical regularities in yt; L represents the lag operator; xt and xt represent shocks to the cyclical component; et accounts for short-term erratic movements and possible measurement errors in yt. et, nt, mt, and xt are assumed to be mutually independent white noise processes, with xt arising by construction under the constraint that r(x) = r(x*); k is the frequency of the cycle and q is the damping factor. The existence of short (high frequency) and long (low frequency) cycles makes it necessary to model a number of cycles simultaneously. Maximum likelihood estimates of the unknown parameters r(n), r(v), r(e), r(x), and q can be obtained by the Kalman filter algorithm (Harvey, 1989). Although such a time-series structural model has the limitation of imposing a specific structure upon the data, it has the advantage of modelling the trend and low frequency fluctuations jointly, without sample selection biases. In choosing this methodology, we have also considered other trend-cycle filters. For example, the wavelet methodology was used to evaluate the sensitivity of our results to the use of the UC model. Wavelet decomposition also has the advantage of being able to model a number of cycles that can change in amplitude and period over time. In fact the wavelet methodology yields very similar long swing phases to those reported here (in the case of GDP the correlation coefficient between the long swing cyclical components of the two methods is 0.91). For a technical discussion and application of the wavelet methodology to the study of long swings see Solomou and Wu (2006). The Hodrick–Prescott (H–P) filter, which has been employed widely in the recent business cycle literature, is not considered appropriate here as it explicitly neglects low frequency long swings by assumption. 2.1. Aggregate long swings Fig. 1 presents the smoothed estimate of the trend growth rate for Japan’s Gross Domestic Product, from the expenditure estimates of the national accounts.2 From the early 20th century, we observe some trend acceleration, with the trend growth rate increasing gradually from 2.6 percent in the 1880s to near 4.0 percent by the end of the 1930s. Fig. 2 displays the cyclical decomposition of GDP. Long swings of growth averaging 2 Although the output side of GDP yields similar long swing phases, the expenditure estimate is more reliable for the study of long swings; much of the output side of GDP is derived by assumption using the information from the expenditure side of GDP. For example, in analysing the ‘‘commerce’’ sector, accounting for 1/3 to 1/2 of GDP, the data are derived as the residual difference between the expenditure series of GDP and the actual production data for manufacturing, agriculture, construction, and transportation. Since sectoral long swings are not synchronised the sum of manufacturing, agriculture, construction, and transportation output displays trend linearity. Thus, commerce sector output follows the cycles of the expenditure estimate of GDP by assumption. Reliable annual GDP figures for Japan are only available from 1885. Using the GDP data compiled by Maddison (2003) shows that the period of the 1870s and early 1880s was a phase of slow economic growth, averaging a growth rate of 1.73 percent per annum, suggesting that the long swing feature of Japanese growth is observed since ca.1870.
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0.045 0.04 0.035 0.03 0.025
1940
1935
1930
1925
1920
1915
1910
1905
1900
1895
1890
1885
0.02
Fig. 1. Estimate of trend growth rate in Japan’s Gross Domestic Product 1885–1940. 0.08 0.06
1939
1937
1935
1933
1931
1929
1927
1925
1923
1921
1919
1917
1915
1913
1911
1909
1907
1905
1903
1901
1899
1897
1895
1893
1891
-0.02
1889
0
1887
0.02
1885
Deviation from Trend
0.04
-0.04 -0.06 -0.08 Short Cycle
Long Swing
Fig. 2. Long swings and short cycles in GDP: Japan 1885–1940 deviations from trend. Table 1 Long swings of GDP: expenditure estimate of GDP
1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
Percent growth rate per annum
Inter-period percent growth change
4.16 1.64 4.11 1.78 5.41
— 2.52 +2.47 2.33 +3.63
Sources: see Appendix A for sources to the GDP series.
approximately 20 years were an important fluctuation in the Japanese economy.3 The inter-period growth changes over these long swing phases are large. Table 1 reports geo3
The diagnostic statistics for this model are reported in the working paper version of this paper (Solomou and Shimazaki, 2006). In implementing the Kalman filter trend-cycle decomposition, we used Stamp 6.0. We followed a general to specific estimation procedure, initially allowing for the possibility of a stochastic level and a stochastic slope, up to three cycles of different durations and an irregular component. Based on the evaluation of the hyperparameter estimates, we were able to move to more efficient parsimonious models, which are the final models depicted in Figs. 1 and 2.
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metric growth rates for GDP over these phases. The amplitude of these ebbs and flows of economic growth was also large when compared to similar swings in the major industrial countries (Solomou, 1998). Comparing the descriptive phasing for long swings in GDP outlined here with earlier empirical work on Japan (Fujino, 1968; Ohkawa, 1979; Ohkawa and Rosovsky, 1973; Shinohara, 1962) highlights some noteworthy similarities and differences. Shinohara (1962) used a 5-year moving average (MA) methodology to describe the long swings in GDP and found the following phases: 1883/87–1898/02 1898/02–1903/07 1903/07–1918/22 1918/22–1928/32 1928/32–1933/37
Upswing Downswing Upswing Downswing Upswing
Ohkawa (1979) used a 7-year MA methodology and found the following long swing phases: 1887–1897 Upswing 1897–1904 Downswing 1904–1919 Upswing 1919–1930 Downswing 1930–1938 Upswing These phases of Japanese economic growth are similar to the long swings depicted in Fig. 2 suggesting that the MA methodology has not created statistical artefact swings in the data. As expected, however, the MA method fails to capture the timing of the actual historical turning points. Fujino (1968, p.36) equated macroeconomic long swings with construction sector swings: ‘‘The construction cycle, as defined by us, is thus not confined to the long swings observed in the behaviour of expenditure on construction, but covers the long swings in the economy as a whole.’’ Using this framework he derived the following phasing: 1885–1896 Upswing 1896–1904 Downswing 1904–1908 Upswing 1908–1914 Downswing 1914–1921 Upswing 1921–1932 Downswing 1932–1937 Upswing For much of the time, however, the macroeconomic swings of GDP and those of the construction sector are not synchronous.4 Thus, during 1896–1908 and 1908–1921, the long swings in construction sector output are of a much shorter duration than swings 4 The construction sector has also been seen as playing a key role in accounting for long swing fluctuations in America (Abramovitz, 1961), Britain (Thomas, 1973), and France (Le´vy-Leboyer, 1978). In the case of Japan, however, the trend-cycle decomposition for construction output shows that the longest significant cycle averaged 12.4 years in duration. Given that the length of the aggregate long swings in Japan was approximately double this duration, over the period 1885–1931 the construction sector had a small counter-cyclical effect on the long swings of GDP growth (see Solomou and Shimazaki, 2006, for a discussion of this sectoral evidence). Only during the 1930s does the sector have a role to play, accounting for 12 percent of the upswing of growth.
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in GDP. Clearly, Fujino’s assumption that the phasing of long swings in Japan can be determined by construction sector swings is invalid. An interesting result is that because the construction sector swings were of a shorter duration than the observed aggregate swings in GDP, the sector had a very limited effect on aggregate swings in the Japanese economy. 2.2. Disaggregate features of long swings To consider some of the disaggregate features of the observed swings, we employ a national accounting framework to quantify the impact of expenditure components of GDP on the aggregate swings over the GDP long swing reference cycle (See Table 2). Beginning with consumption, which accounted for approximately 70–85 percent of GDP over this period, we observe a high amplitude long swing as the dominant cyclical fluctuation.5 Consumption swings played a key role in accounting for the aggregate swings during the period 1885–1931, although the magnitude of the effect was declining over time (accounting for over 70 percent of the inter-period growth swing of 1885–1908, less than 60 percent of the swing over 1895–1919, and only 44 percent of the swing over 1908–1931). As is well known, consumption expenditure did not contribute to the marked growth revival of the 1930s. Private investment accounted for approximately 7–11 percent of GDP over this period. The unobserved components structural model decomposition identifies two high amplitude cycles, one of which is at the long swing frequency (with an average period of 25.4 years). The phases of the swings are similar to the aggregate GDP swings, with investment turning points leading the aggregate swings. The national income accounting results reported in Table 2 show that private investment played a key role in the episodes of growth after 1908. Investment accounted for 37, 65, and 46 percent of the inter-period growth changes during 1895–1919, 1908–1931, and 1919–1938, respectively. During the pre-1908 period, a low investment share and a relatively low amplitude investment swing meant that investment was not central to explaining the observed growth episodes.6 Shifts in government expenditure do not follow the long swing movements. Instead, stochastic changes are observed, mainly associated with war-related expenditure and long-term trend changes. Both the Sino-Japanese war (1894–1895) and the Russo-Japanese war (1904–1905) resulted in major increases in government expenditure and the immediate post-war periods were followed by large government expenditure reductions. The cycle generated from these shocks was of a shorter duration than the long swing frequency. These stochastic shifts in government expenditure had a major effect on the economy during the inter-war period. During the 1920s, high levels of government expenditure acted to partially compensate for other components of low demand; during the 1930s the rapid growth of government expenditure reinforced private investment and exports as rapidly growing components of aggregate demand. As can be seen from 5 The phases of the swings in consumption are similar, but not identical, to the aggregate swings before World War I but differ significantly in the inter-war period. Detailed cyclical decompositions for the expenditure components are reported in Solomou and Shimazaki (2006). 6 This result differs from Ohkawa (1979) who emphasises investment swings as being important to aggregate swings over the whole period 1885–1940.
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Table 2 Long swings in expenditure components of GDP (analysed over GDP reference swings) Long swing episode
Consumption 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938 Investment 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
(1) Annual growth rate
3.78 1.65 3.47 2.14 2.13
(2) Proportion of GDP
0.845 0.820 0.779 0.800 0.712
(3) Weighted effect on GDP growth
(4) Weighted inter-period growth effect
(5) Proportion of swing in GDP
3.19 1.35 2.70 1.71 1.52
— 1.84 1.35 0.99 0.19
— 0.73 0.58 0.44 0.05
5.33 2.40 9.50 3.67 12.38
0.0755 0.0792 0.1113 0.1056 0.1035
0.40 0.19 1.06 0.39 1.28
— 0.21 0.87 1.45 1.67
— 0.08 0.37 0.65 0.46
Government expenditure 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
7.74 2.77 2.57 5.62 9.74
0.0907 0.1512 0.1339 0.1764 0.2153
0.70 0.42 0.34 0.99 2.10
— 0.28 0.08 0.65 1.11
— 0.11 0.04 0.29 0.31
Exports 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
8.32 6.53 8.48 4.16 9.59
0.0348 0.0621 0.1166 0.1259 0.2136
0.29 0.41 0.99 0.52 2.10
— 0.12 0.58 0.47 1.58
— 0.05 0.25 0.21 0.44
Imports 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
10.77 7.15 6.48 4.84 6.18
0.0462 0.1133 0.1379 0.2109 0.2136
0.50 0.81 0.89 1.02 1.32
— 0.31 0.08 0.13 0.30
— 0.12 0.03 0.06 0.08
Notes to Table 2: see Appendix A for data sources. Column (1) is calculated as the geometric annual growth rate over the specified period. Column (2) is the share of the expenditure component in GDP averaged over the specified period. Column (3) is derived as the product of column (1) and column (2). Column (4) is the inter-period growth difference of the weighted growth rate reported in column (3). Column (5) is calculated as the ratio of the inter-period growth changes reported in column (4) and the aggregate inter-period GDP growth changes reported in Table 1.
Table 2, during the pre-1919 period the direct effect of shifts in government expenditure was of relatively minor importance to the large swings of economic growth.7
7
This does not rule out indirect effects via effects on private sector consumption, as discussed below.
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Japan’s export share was trended upwards during the period 1885–1938, rising from 3.5 percent in the 1880s to 21 percent in the 1930s. The unobserved components structural model identifies stochastic shifts in the level of exports and a long swing averaging 19.7 years, with the amplitude of the long swings increasing after ca.1908. Given the small share of exports in GDP and the relatively low amplitude swings of export growth in the period 1885–1908, exports were not important to accounting for the segmentation of economic growth over this period. In fact, export growth had a counter-cyclical effect on the inter-period growth changes of 1885–1908. Only after 1908 does export growth have a large effect on the observed growth swings, accounting for 25 percent of the growth upswing of 1908–1919 and 21 percent of the downswing of 1919–31. Rapid export growth had its largest impact on the growth revival of the 1930s, accounting for 44 percent of the inter-period growth step (see final column of Table 2). Japan’s import share is similarly trended upwards over this period. However, considering imports as a negative component of aggregate demand suggests that most of the effect of trade on Japanese long swings is due to the effect of export swings rather than swings in imports. Summarising the disaggregate evidence, whilst the observed aggregate GDP growth swings before World War II are described as relatively stable in amplitude and average period, the components of expenditure are less regular, displaying important shifts over time. An explanatory framework for the observed swings has to note that the pre-1908 swings were mainly accounted for by swings in private sector consumption whilst swings of growth during 1908–1931 were determined by swings in private sector investment and exports. The upswing of the 1930s was accounted by movements in government expenditure, private investment, and exports. 3. Explanations for Japan’s long swings The existing literature has offered a number of conflicting explanations for the observed long swings. Fujino (1965, 1968) emphasises an endogenous perspective assigning a central role to the production structure of the construction sector. In contrast, Shinohara (1962, 1978) emphasises specific historical shocks for each segmented growth episode. For example, the upswing of 1883/87–1898/02 is attributed to the expansion of the railway network, the growth of electricity, expansion of exports in a phase of silver depreciation, and the reparation payments following the Sino-Japan war of 1894–1895. The downswing of 1898/1902–1903/07 is attributed to reduced railway construction, international price deflation, and depression of exports. The boom up to 1918/22 is attributed to WWI and an expansion of exports. The downswing of the 1920s is attributed to high domestic prices, high levels of imports, and an efflux of gold. Devaluation and militarism in the 1930s caused a revival of economic growth. Williamson and De Bever (1977, p.164) emphasise war shocks, postulating ‘‘. . .war-related ‘stop-go’ explains most of Japanese long swing experience and investment spurts.’’ In contrast, Ohkawa (1979, p. 18) concludes, ‘‘The evidence is at best ambiguous, and it is my view no long-term trends or swings can be related to the level of military spending.’’ To clarify this debate, we evaluate the kind of shocks affecting long swings. To do so, we model the long-run determinants of exports, consumption, and investment, which have been shown to be important in the national accounting framework as a descriptive
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Table 3 Japan’s exports, trading partners’ income, real exchange rate, and percent tariff rate
1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
Total exports
Trading partners’ income
Real effective exchange rate
Weighted tariff rate of Japan’s trading partners
8.32 6.53 8.48 4.16 9.59
2.35 2.71 3.19 1.61 4.01
2.99 2.70 0.98 0.12a 2.99
9.44 9.29 6.83 9.15 18.04
Sources: see Appendix A for data sources. Exports, trading partners’ income, and real exchange rate are expressed as growth rates per annum. a The actual path of the real exchange rate shows a peak of appreciation in the early 1920s and a ‘correction’ in the 1920s. This low appreciation over the whole period may not capture the full impact of exchange rate movements.
explanation of long swings. We use two methodologies to derive these long-run relationships. First, given the non-stationary nature of the data series, we use the Johansen co-integration methodology to evaluate whether the key variables share common trends. However, given the low statistical power of the unit root tests we also use the ARDL methodology of Pesaran and Shin (1999) to derive a second set of coefficients to compare with the Johansen co-integration results. What determined export swings and why was the effect of exports on GDP growth swings larger in the post-1908 period? We model the determinants of Japans’ exports as entailing a long-run relationship with Japan’s multilateral real effective exchange rate, the weighted tariff rate of Japan’s main trading partners, and an index of trading partners’ income.8 The path of these variables over the reference swings in GDP is presented in Table 3. Table 3 shows that in the pre-World War I period, trend movements in world income and the real exchange rate are likely to have had counter-acting effects (the average tariff rate showed little change over this period).9 The adverse effect on exports of a real exchange rate appreciation during 1895–1908 was partly counter-balanced by a favourable trading partners’ income effect, although the net effect depends on relative magnitudes of these effects. In contrast, during the interwar period we observe a cluster of synchronised shocks. For example, during 1919–1931 an overvalued yen reinforced an adverse trading partners’ income effect. During the 1930s, rapid growth in trading partners’ income was reinforced by rapid yen depreciation.
8
The data are described in Appendix A to this paper. Comparing the real effective exchange rate used here with other series displays major discrepancies. For example, Minami (1986) uses the terms of trade data, adjusted for nominal dollar–yen exchange rate as the real exchange rate. Comparing our real effective exchange rate (REER) data with Minami’s index, whilst the data for the REER shows that Japan witnessed large real yen depreciation during 1885–94, Minami’s index shows a stable, although cyclical, level. Whilst we find a trend of appreciation during 1894–1913, Minami’s index shows appreciation in the late 1890s and depreciation during 1900–1913. Our data suggest that the 1920s witnessed a persistently high REER index (despite the mild depreciation during 1921– 1930) whilst Minami’s data suggest a larger depreciation. 9 Japan gained the right to set tariffs only in 1899 but until 1911 a series of treaties with the USA and European countries resulted in a low tariff regime over this early period.
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Over the period 1885–1938 exports, the real effective exchange rate, the weighted tariff rate of Japan’s main trading partners, and an index of trading partners’ income are integrated of order 1.10 We first estimated the optimal lag order of the unrestricted VAR model of these variables, which was found to be 1. In estimating the Johansen co-integration methodology, we begin with the most general models and move to more restricted models, evaluating the existence of cointegrating vectors.11 The results suggest that there exists one cointegrating vector between exports, the real effective exchange rate, trading partners’ income, and trading partners’ weighted average tariff rate.12 The long-run income and exchange rate coefficients have the expected sign and are statistically significant (all variables in logs; t values in parentheses) ECM ¼ Exports 2:5622 Trading Partners’ Income ð7:24Þ þ 1:1848 Real Exchange Rate 0:3182 Tariff. ð3:91Þ ð0:70Þ An alternative method of estimating the long-run coefficients is to use single equation auto-regressive distributed lag models (ARDLs) where dependent and independent variables enter the right-hand side with lags of order p and q, respectively Yt ¼ a þ
p X i¼1
bY ti þ
q X
cXtj þ et ;
j¼0
where Y is the dependent variable, in this case exports, and X is a vector of three explanatory variables (trading partners income, the real exchange rate, and tariff rates). This ‘classical’ time-series model has been extended by Pesaran and Shin (1999) who demonstrate consistency and super consistency results for the short- and long-run parameter estimates, respectively, when there exists a cointegrating relationship between the variables. Further, cointegration is not a pre-requisite for employing an ARDL representation. Given the low power of unit root and cointegration tests for small sample sizes, the ARDL method provides a good alternative to cointegration. The ARDL model above can be re-parameterised in first differences to derive long-run coefficients for exogenous variables of interest. We employ the two-step procedure for estimating the ARDL (p, q) model. In the first step, we chose the order of the ARDL using the Schwartz–Bayesian criterion of
10 Since our focus in this paper is on the long swing movements, we only report the long-run coefficients. The framework used can also be applied to modelling short-run movements within the ECM framework. The variables are considered in log form. Using the AIC to choose the optimal lag order of the ADF tests shows that we fail to reject the unit root hypothesis for all these variables. 11 The co-integration models considered are, from most general, unrestricted intercept and unrestricted trend, unrestricted intercept and restricted trend, unrestricted intercept and no trend, restricted intercept and no trend, and no intercept and no trend. The estimation was undertaken using Microfit (Pesaran and Pesaran, 1997). 12 The co-integration model that yields a cointegrating vector is the no trend and no intercept model. The model evaluated treated tariffs, world income, and the real effective exchange rate as having exogenous effects on Japan’s exports. The tariff rate is found to be insignificant. One problem to note in this regard is that during the 1930s a significant shift in Japan’s trade regionalisation means that the weighted tariff rate is not representative during this decade. Data limitations prevented us from improving on this index. Whilst the weight of the 13 countries covered by the tariff data account for over 70 percent of Japan’s trade between 1880 and 1930, the coverage fell to 41 percent by 1938. The new trade regionalisation arising in the 1930s implies that the tariff hike of the 1930s was not as large as the calculated series implies.
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Table 4 Estimated long-run coefficients using the ARDL approach Regressor
Coefficient
t ratio
Trading partners’ income Real effective exchange rate Weighted tariff rate
2.9346 1.4185 0.1107
25.26 13.19 0.27
model selection, allowing for up to four lags. The selected model (which is found to be an ARDL (1, 0, 0, 0) model with an insignificant time trend) is then used to estimate the longrun parameters of interest (see Table 4). The two approaches yield very similar estimates for the long-run coefficients. Given the large shifts in trading partner income and Japan’s real effective exchange rate these key variables determined the large swings in Japan’s exports.13 This analysis illustrates some important aspects regarding the impact of shocks on Japan’s economic growth. In the pre-1908 period, the relatively low amplitude of export swings was not due to an absence of shocks, but was the outcome of favourable and adverse shocks to competitiveness and world incomes that partly counter-balanced each other. In contrast, during 1908–1938 a co-movement of shocks resulted in high amplitude export swings that had large effects on the swings of economic growth.14 In the period of adjustment after the First World War this cluster of adverse shocks resulted in a halving of Japan’s export growth rate relative to the pre-1913 period (see Table 3). The swings of consumption have been shown to be important in the aggregate swings during 1885–1931. If the movements of consumption are anything more than endogenous responses to long swings in income, we need to model consumption behaviour in the Japanese economy as being influenced by some exogenous variables, resulting in consumption shifts. We extend the work of Minami (1986) who estimated a consumption function in terms of personal disposable income in three ways. First, we include government consumption as a possible explanatory variable allowing us to evaluate the contrasting hypotheses of Ohkawa (1979) and Williamson and De Bever (1977) regarding war and long swings. This can be interpreted within a framework of Ricardian equivalence or simply as capturing crowding-out effects of war-related movements in government expenditure on private consumption. In this light, the rapid increase in Government expenditure observed in the Sino-Japanese war (1894–1895) and the Russo-Japanese war (1904–1905) may have had significant exogenous effects on the private sector.15 Second, we also consider real money balances16 in explaining consumption movements, capturing monetary, and price effects on consumption. Finally, given the non-trend-stationary
13
The existing literature offers mixed results on the role of prices in the determination of Japan’s exports. For the pre-1913 period, Shinohara (1962) argues that the relative price effect was large, whilst Minami (1986) finds that the relative price effect was relatively unimportant. In the light of our results these differences can be resolved by noting limitations in Minami’s real exchange rate measure. 14 This analysis allows us to comment on the literature on Japan’s recovery in the 1930s. Cha (2003) found that exports had a short-run effect during 1931–1932. This result is contradicted by our finding of a long-run effect. The paradox can be resolved by noting that Cha uses VAR analysis, a methodology that relies on stationary data and thus cannot comment on the long-run relationship between exports and economic growth in the 1930s. 15 In both wars, bond issues and increased taxation financed government expenditure. 16 Money supply is taken as M2.
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Table 5 The determinants of private sector consumption (growth per annum)
1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
Private sector consumption
Personal disposable income
Government consumption
Real money balances
3.78 1.65 3.47 2.14 2.13
4.66 1.58 4.49 1.31 4.53
8.42 0.60 3.06 5.15 7.10
6.95 6.27 8.51 7.33 4.89
Sources: see Appendix A for sources.
nature of the data, we use cointegration methods to estimate the long-run coefficients of interest. Our formal model explains real aggregate personal consumption in terms of real aggregate personal disposable income (rpdi), real government consumption (rgc), and real money balances (rmb).17 The path of these variables over the long swing reference periods is presented in Table 5. The optimal lag order of the unrestricted VAR model for consumption was found to be 2. The results suggest that there exists one cointegrating vector between private consumption, personal disposable income, real money balances, and government consumption. The long-run coefficients have the expected sign and are statistically significant (t values in parentheses): ECM ¼ aggregate personal consumption 0:72097 rpdi 0:21806 rmb ð4:61Þ ð2:57Þ þ 0:2628 rgc ð3:40Þ The selected ARDL model for consumption (based on the Schwartz–Bayesian criterion) ARDL (1, 2, 0, 0) generated the long-run coefficients of interest reported in Table 6. The results suggest that war and shifts in government consumption had two major channels of influence on consumption (see Table 6). Large tax increases, such as those after the Sino-Japan War (1894–1895), directly affected disposable income and large increases in Government consumption had a significant crowding-out effect on private sector consumption.18 Thus, the rapid growth of Government consumption during war and the trended growth during 1908–1938 contributed to the retarded growth rates of private consumption. Swings in private investment are found to be important in accounting for swings in GDP growth during the period 1908–1938. What need to be identified are the exogenous shocks driving swings in investment. Minami (1986) estimates an investment function (covering non-primary fixed capital formation)19 for the period 1907–1940 employing 17
We also included ex post real interest rates but this proved insignificant in all the estimations. All the variables are considered in log form. Using the AIC to choose the optimal lag order of the ADF tests shows that we fail to reject the unit root hypothesis for all these variables. 18 A similar result is reported in Ohkawa (1979, p. 17). Despite this, as noted above, Ohkawa argued that war was not critical to the swings. This does not sit well with the evidence. Within a multi-variate perspective to the swings, war is one of the important shocks affecting the Japanese economy on a number of occasions during 1885–1940. 19 Government and primary sector investment are excluded.
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Table 6 Estimated long-run coefficients of consumption function using the ARDL approach Regressor
Coefficient
t ratio
Personal disposable income Real money balances Real government consumption Constant
0.6901 0.1709 0.1355 3.0879
6.28 4.05 3.43 3.87
Table 7 Estimated long-run coefficients for investment using the ARDL approach Regressor
Coefficient
t ratio
Real interest rate Rate of profit Log capital stock Constant Time trend
4.18 0.075 5.23 32.00 0.2220
4.74 4.89 5.71 5.20 4.45
one period lags of the real return to capital, the real interest rate, and the capital stock. Minami’s specific results are problematic given the presence of autocorrelation in his estimates, invalidating the significance tests. This may reflect the lagged dependent variable effects and the non-trend stationary structure of the time-series data analysed by Minami. The ARDL framework allows us to re-estimate Minami’s model to overcome these problems.20 Moreover, since our focus is on long swings, the ARDL method also allows us to estimate long-run relationships. Using variables similar to those of Minami (1986), we estimate an ARDL model of non-primary fixed capital formation for the sample period 1907– 1940.21 In using the ARDL specification, we do not follow Minami in imposing a fixed one period lag on the structure of the model. In the first step, we chose the optimal order of the ARDL using the Schwartz–Bayesian criterion of model selection and allowing for a wide ARDL lag structure. The selected model is an ARDL (0, 2, 3, 4) model with a significant time trend. The model suggests a two period lag on the real interest rate, a three period lag on the rate of profit, and a four period lag on the capital stock. The selected model is then used to estimate the long-run parameters of interest (Table 7). The results are not directly comparable to those of Minami but they confirm Minami’s intuition that capital formation is influenced by real interest rates, the rate of profit, and the level of the capital stock. The ARDL model suggests that the long-run effect of the capital stock is positive, i.e., a high level of the capital stock stimulates investment.22 However, beyond this proximate explanation we need to emphasise that real interest rate movements were, in turn, determined by a multitude of real and monetary shocks. For example, with regard to nominal interest rates the business cycle literature on Japan shows that during the gold standard period changes in the discount rate often depended on the balance of payments position and gold flows (Fujino, 1965, 1968; Oshima, 1955; Takamura, 1975).
20
Given the limited sample time period, we limit ourselves to working with the ARDL model. We also included Government investment as an explanatory variable to evaluate the existence of crowdingout effects but found this to be statistically insignificant. 22 Minami (1986) also observed a positive capital stock effect. 21
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Nominal interest rates were also influenced by policy regime shocks; the attempt to return to the gold standard at the 1913 parity forced a high interest regime on Japan for much of the 1920s. In contrast, the devaluation of the 1930s allowed an expansionist monetary policy. 4. Discussion and future research What insights does the study of Japan offer for our understanding of the causes of episodic long swings of economic growth? Clearly the RBC approach that emphasises one-off ‘‘Great depressions’’ is misleading in that the approach neglects relevant information about the growth process; the historical record suggests that the other side of the existence of ‘‘Great depressions’’ is the existence of long swing boom periods that need to be accounted for within a unified framework. The evidence considered suggests that the ebbs and flows of economic growth are partly the result of ‘‘shocks.’’ As examples, we have shown how shocks affected the episodic long swing movements of exports, consumption, and investment. In focusing on the determinants of these shocks, we have emphasised, inter alia, shifts in world income, the real exchange rate, the growth of government expenditure, and monetary shocks related to major institutional changes. This analysis has allowed us to extend the inferences of Shinohara (1962), Williamson and De Bever (1977), and Ohkawa (1979) regarding the type of shocks that impacted on long swings. It seems clear that a diverse set of shocks affected Japanese growth swings over this period.23 However, the pervasive nature of long swings in economic growth in the 19th and 20th centuries should encourage researchers to discuss the possibility of endogenous explanations of quasi-cyclicality—it is in this light that we offer some speculative thoughts in this section. Business cycle theories have alternated between endogenous theories versus a discussion of the shocks and propagation mechanisms to account for economic cycles. After surveying American long swings in the period 1840–1914 some time ago Abramovitz (1959) concluded: It is not yet known whether they are the result of some stable mechanism inherent in the structure of the US economy, or whether they are set in motion by the episodic occurrence of wars, financial panics, or other unsystematic disturbances. (Abramovitz, 1959) What Abramovitz seems to have had in mind is that the question of endogeneity is an open one. It is quite clear from our discussion of Japan that mechanical ideas of endogenous swings are unable to explain Japanese long swings. Thus, Fujino’s emphasis on endogenous construction cycles is of little help to understand Japanese macroeconomic swings. Given the historical record of Japan and a number of other countries an avenue of future research is to consider the role of the policy framework in long swing fluctua-
23 Our approach here has focused on shocks to expenditure. Looking at the output side of the national accounts suggests that structural change and sector-specific shocks were also important in particular episodes. For example, although the declining share of agriculture meant that the sector had a declining role in economic growth over long-run time horizons, the path of agricultural decline was not linear and, as a result, this sector had a large one-off effect on the episode of slow economic growth during 1919–1931(Solomou and Shimazaki, 2006).
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tions. In choosing a rules-based policy framework, such as the gold standard, a necessary outcome is the need for cyclical adjustment. This type of adjustment was manifested in a number of ways. In the case of the core industrial countries before World War I they were able to sustain the gold standard rule as their policy framework and were able to use migration, capital flow, trade, and real exchange rate adjustment to cope with a changing and stochastic economic environment (Cata˜o and Solomou, 2005). The slow-relaxing nature of these variables meant that most of the movement is observed in the long swing frequency rather than the shorter business cycle frequency. The same set of adjustments was not available to all countries. For example, in the case of Japan neither migration nor capital flows provided effective adjustment and the real exchange rate fluctuations contributed to shocks. A more limited set of adjustment mechanisms may have resulted in high amplitude swings in Japan. The growth swings of Japan in the period of the gold standard (1897–1931) can be thought of as being determined/influenced by the workings of this system. For example, large increases in Government expenditure (which had inflationary effects) had to be mean reverting over time to maintain a credible commitment to the gold standard. During the inter-war period, a similar framework can be used to analyse the slow economic growth of the 1920s in terms of policies to facilitate the return to the gold standard (Patrick, 1971). Thus, for much of the pre-WWII period the policy regime modulated economic growth via feedback rules driven by the need to maintain policy credibility. To a large extent long swings of economic growth can be thought of as an endogenous response of adjustment processes to sustain the gold standard policy framework. Clearly, in this context, the effects of shocks have to be seen in the context of a particular set of policy institutions; a different combination would have yielded different types of cyclicality. As economies attempt to re-create rules-based monetary and fiscal policy frameworks, we may find that long swings of growth will be observed in future paths of economic growth. Appendix A A.1. Japan’s macroeconomic data The data sources we use are the revised estimates reported originally in LTES (Estimates of Long-Term Economic Statistics of Japan) (1965–1979). The revisions to these series as reported in Ohkawa Shinohara, M. (Eds.) with L. Meissner, 1979), Patterns of Japanese Economic Development, New Haven, Yale University Press. The original data reported in LTES were revised because of revisions to the price series for imports and exports as reported in volume 14 of LTES. The GDP series and the component series are based on 1934–1936 prices. A.2. Average tariff rate of main trading partners Tariff data are revenue tariff data, based on the work of Clemens and Williamson (2004). We were able to include 13 countries: UK, USA, China, Canada, India, Egypt, Australia, France, Italy, Germany, Indonesia, Russia, and Thailand, accounting for approximately 75% of Japan’s trade for most of the period. To construct the average tariff rate for the period 1870–1913, we weight tariff rates with trade shares in 1879 and 1913 and
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use the geometric average of these two series. For the period 1913–38, we use the weights of 1913 and 1929 and take a geometric average. Trade weights were derived from the following sources: Japan Statistical Association (1988), Historical Statistics of Japan, Tokyo; Yamazawa and Yamamoto (1979), Foreign Trade and Balance of Payments, Estimates of Long-Term Economic Statistics of Japan since 1868, vol. 14; and Toyo Keizai Shinposha, Tokyo (in Japanese). Toyo Keizai Shinposha (1935), Foreign Trade of Japan: A Statistical Survey. A.3. Real effective exchange rates For the period 1870–1938, we spliced together the real effective exchange rate index of Cata˜o and Solomou (2005), covering the period 1870–1913 and the index of Shimazaki and Solomou (2001), covering the period 1913–1938. Both series are based on 1913 = 100. Details of the data sources used to construct the Catao–Solomou index are reported in http://www.e-aer.org/data/sept05_app_catao.pdf. The data sources used by Shimazaki and Solomou (2001) are reported in the Appendix to that paper. A.4. Trading partners’ income The construction of this series was constrained by the availability of reliable GDP data—although China was an important trading partner, the lack of reliable annual GDP data for China before WWII prevented its inclusion in the index. For the period 1879–1902, we constructed an income index as the weighted average for six of Japan’s main trading partners, accounting for approximately 75% of trade in 1879 (US, UK, France, Germany, Italy, and Australia). Taiwan, India, and Dutch India were added for the period 1903–1913). Income of each country is expressed as 1903 = 100. An index of trading partner income is constructed using bilateral trade weights for 1879 and 1903, respectively. A geometric mean is used to derive an ideal index over this period. For the period 1903–1913 income indices were constructed using bilateral trade weights for 1903 and 1913, respectively. For the period 1913–1938 an income series is constructed as the weighted average for 10 of Japan’s main trading partners (USA, UK, France, Germany, Italy, Australia, Taiwan, Korea, India, and Dutch India), accounting for 56–62% of Japan’s visible trade, using trade weights for 1913 and 1938, respectively. A geometric mean was then used to derive an ideal index over this period. These indices are spliced together to derive a series over the whole period 1885–1938. GDP data for USA, UK, France, Germany, Italy, and Australia and India are reported in Maddison (1995): Monitoring the World Economy 1820–1992, OECD, Paris, and Maddison (2003). Data for Japan’s colonies can be found in Mizoguchi and Umemura (1988), Basic Economic Statistics of Former Japanese Colonies 1895–1938. Estimates and Findings. Toyo Keizai Shinposha, Tokyo. References Abramovitz, M., 1959. Historical and Comparative Rates of Production, Productivity and Prices, Statement in US Congress, Joint Economic Committee, Employment, Growth and Price Levels, Hearings (86th Congress), Pt. II, Washington, pp. 411–466.
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Abramovitz, M., 1961. The nature and significance of Kuznets cycles. Economic Development and Cultural Change IX (3), 225–249. Bird, R.C., Desai, M.J., Enzler, J.J., Taubman, P.J., 1965. ‘‘Kuznets cycles’’ in growth rates: the meaning. International Economic Review 6 (2), 229–239. Cata˜o, L.A.V., Solomou, S.N., 2005. Effective exchange rates and the classical gold standard adjustment. American Economic Review 95 (4), 1259–1275, 2005. Cha, Myung Soo, 2003. Did Takahashi Korekiyo rescue Japan from the great depression?. Journal of Economic History 63 (1) 127–144. Clemens, M.A., Williamson, J.G., 2004. Why did the tariff-growth correlation reverse after 1950? Journal of Economic Growth 9 (5), 5–46. Fujino, S., 1965. Nihon no Keike Junkan (Japan’s business cycles). Kwiso Shobo, Tokyo. Fujino, S., 1968. Construction cycles and their monetary-financial characteristics. In: Klein, L., Ohkawa, K. (Eds.), Economic Growth: The Japanese Experience since the Meiji Era. Richard D. Irwin, Inc., Illinois. Harvey, A.C., 1985. Trends and cycles in macroeconomic time series. Journal of Business & Economic Statistics 3 (3), 216–227. Harvey, A.C., 1989. Forecasting, Structural Time Series Models and the Kalman Filter, Cambridge. Kehoe, T.J., Prescott, E.C., 2002. Great depressions of the 20th century. Review of Economic Dynamics 5, 1–18. Kuznets, S.S., 1958. Long swings in the growth of population and in related economic variables. In: Proceedings of the American Philosophical Society, vol. 102, No. 1, pp. 25–52. Le´vy-Leboyer, M., 1978. Capital investment and economic growth in France, 1820–1930. In: Mathias, P., Postan, M. (Eds.), Cambridge Economic History of Europe, VII. Cambridge University Press. LTES [Estimates of Long-Term Economic Statistics of Japan]. 1965–1979. Series edited by Kazushi Ohkawa, Miyohei Shinohara, Mataji Umemura, vols. 1–14, Toyo Keizai Shinposha, Tokyo. Maddison, A., 1995. Monitoring the World Economy 1820–1992. OECD, Paris. Maddison, A., 2003. The World Economy: Historical Statistics. OECD, Paris. Meissner, 1979. In: Ohkawa, K., Shinohara, M. (Eds.), Patterns of Japanese Economic Development. Yale University Press, New Haven. Minami, R., 1986. The Economic Development of Japan: A Quantitative Study, second ed. Macmillan Press, London. Mizoguchi, T., Umemura, M., 1988. Basic Economic Statistics of Former Japanese Colonies 1895–1938 Estimates and Findings. Toyo Keizai Shinposha, Tokyo. Mosk, C., 2001. Japanese Industrial History: Technology, Urbanization, and Economic Growth. New York and London. Nakamura, T., 1983. Economic Growth in Prewar Japan. Yale University Press, New Haven and London. Ohkawa, K., 1979. Aggregate growth and product allocation. In: Ohkawa, K., Shinohara, M., Meissner, L. (Eds.), Patterns of Japanese Economic Development. Yale University Press, New Haven, pp. 3–33. Ohkawa, K., Rosovsky, H., 1973. Japanese Economic Growth: Trend Acceleration in the Twentieth Century. Stanford University Press, Stanford. Oshima, K., 1955. Nihon Kyoko Shi Ron (Depression History of Japan). Tokyo University Press. Patrick, H.T., 1971. The economic muddle of the 1920s’. In: Morley, J.W. (Ed.), Dilemmas of Growth in Prewar Japan. Princeton University Press, Princeton. Pesaran, M.H., Pesaran, B., 1997. Working with Microfit 4.0: Interactive Econometric Analysis. Oxford University Press. Pesaran, M.H., Shin, Y., 1999. An autoregressive distributed lag modelling approach to cointegration analysis. In: Strom, S. (Ed.), Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch Centennial Symposium. Cambridge University Press, Cambridge. Shimazaki, M., Solomou, S.N., 2001. Effective exchange rates in Japan, 1879–1938. Japan and the World Economy 13, 161–177. Shinohara, M., 1962. Growth and Cycles in the Japanese Economy. Kinokuniya Bookstore Co., Ltd, Tokyo. Shinohara, M., 1978. Kuznets cycles and Juglar cycles. In: Ohkawa, K., Hayami, Y. (Eds.), Long-Term Analysis of Japanese Economy. Nihon Keizai Shinbunsha, Tokyo. Solomou, S.N., 1987. Phases of Economic Growth, 1850–1973: Kondratieff Waves and Kuznets Swings. Cambridge University Press. Solomou, S.N., 1998. Economic Cycles. Manchester University Press. Solomou, S.N., Shimazaki, M., 2006. Japanese Long Swings in Economic Growth. Mimeo.
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Solomou, S.N., Wu, W., 2006. Long Swings in Economic Growth Since 1870: An Application of Wavelet Analysis. Mimeo. Takamura, N., 1975. Kyoko. In: Oishi, K. (Ed.), Nihon Sangyo Kakumei no Kenkyu, vol. 2. Tokyo University Press. Thomas, B., 1973. Migration and Economic Growth. Cambridge University Press, Cambridge. Toyo Keizai Shinposha, 1935. Foreign Trade of Japan: A Statistical Survey. Tokyo. Williamson, J.G., De Bever, L., 1977. Savings, accumulation and modern economic growth: the contemporary relevance of Japanese history. Journal of Japanese Studies 4 (1), 125–167. Yamazawa, I., Yamamoto, Y., 1979. Foreign Trade and Balance of Payments, Estimates of Long-Term Economic Statistics of Japan since 1868. vol. 14.
Japanese episodic long swings in economic growth Solomos Solomou a
a,*
, Masao Shimazaki
q
b
Faculty of Economics, University of Cambridge, UK b Ministry of Finance, Tokyo, Japan Received 20 April 2005 Available online 3 February 2006
Abstract Prior to World War II Japanese economic growth was characterised by episodic ‘long swings,’ low frequency fluctuations in economic growth averaging about 20–25 years in duration. At the aggregate level, these inter-period growth variations dominated both shorter-term fluctuations and longer-term trend acceleration. The paper describes the long swings of the Japanese economy and re-evaluates conventional explanations. Ó 2006 Elsevier Inc. All rights reserved. Keywords: Episodic Economic Growth; Long swings; Japanese Economic History
1. Introduction The path of modern economic growth has displayed punctuated features. Recent examples are: the global slowdown in the 1970s; the slow growth episodes observed in Argentina, Brazil, Mexico, and Chile during the 1980s; and in Japan and Germany since the 1990s. Because the amplitude of such movements in economic growth is high, and the average period of adjustment is long, relative to the business cycle frequency, the economic and social costs can be high. Historical analysis of the process of growth shows us that q Research for this paper has been supported by a Research Grant from the UK ESRC (No. L138 25 1045). We thank the Editor and an anonymous referee for useful comments and guidance. Andrew Harvey, Mark Metzler, Carl Monk, Adrian Pagan, Hugh Patrick, Cristiano Ristuccia, Miyohei Shinohara, Graeme Snooks, Jeff Williamson, Weike Wu and participants of the Institute of Advanced Studies seminar at the ANU gave us useful comments on a previous version of this paper. * Corresponding author. E-mail address: [email protected] (S. Solomou).
0014-4983/$ - see front matter Ó 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.eeh.2005.12.001
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there are many more examples of such episodic growth phases. Treated individually, there is a bias to account for such periods by analysing the effects of specific shocks; treated as a general feature of economic growth, we are forced to consider the possibility of broader explanations for such processes. Kehoe and Prescott (2002) use the real business cycle (RBC) framework to explain episodic ‘‘Great depressions,’’ averaging durations of approximately a decade, as the result of institutional failings and policy mistakes. In contrast to the idea of one-off ‘‘Great depressions,’’ the long swing perspective to historical economic growth has observed fluctuations of high and low economic growth of approximately 20 years in duration (Abramovitz, 1959, 1961; Kuznets, 1958). The existing evidence suggests that long swings were a pervasive aspect of national historical economic growth, and were observed in a wide set of economies, including America, Argentina, Australia, Brazil, Britain, Canada, France, and Germany.1 Similar results have been reported for Japan (Minami, 1986; Mosk, 2001; Nakamura, 1983; Ohkawa, 1979; Ohkawa and Rosovsky, 1973; Shinohara, 1962; Yamazawa and Yamamoto, 1979). Our aim here is to use Japan as a historical case study to develop our understanding of such growth episodes. Japan is an interesting case study because, for most of the period before World War II, the magnitude of inter-period variations in growth is high, allowing us to evaluate the long swing hypothesis, that there is a cyclical or quasi-cyclical component to episodic growth, against the alternative RBC hypothesis that these observed phases are purely random. Section 2 outlines the trend-cycle decomposition methods used to describe Japan’s growth swings and identify whether there is a cyclical component. The existing literature has described Japan’s episodes of growth using conventional statistical techniques such as moving averages (Ohkawa and Rosovsky, 1973; Shinohara, 1962, 1978). It is now well known that such methods may generate statistical artifacts (Bird et al., 1965) and hence we use developments in trend-cycle decomposition to offer a more general description of the observed historical trends and reinforce the view that Japanese long swings are not a product of data transformation. Sections 2.1 and 2.2 present an analysis of Japanese long swings looking at aggregate and disaggregate evidence. Section 3 evaluates some of the proximate causes of the observed swings in economic growth and discusses the results in the context of the existing literature. Finally, Section 4 evaluates the role of policy regime in helping us to understand long swings in economic growth. 2. Methodology To shed some light on the empirical features of trend movements and low frequency fluctuations in economic growth during this period, we use the following unobserved components (UC) structural model of time series decomposition (Harvey, 1985, 1989): y t ¼ lt þ wt þ et ;
ð1Þ
where lt ¼ lt1 þ bt1 þ nt ;
1
See Solomou (1987, 1998) for references to the national case studies of long swings listed here.
ð2Þ
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bt ¼ bt1 þ mt ;
ð3Þ
wt ¼ ð1 q cos kLÞxt þ ðq sin kLÞxt =ð1 2q cos kL þ q2 L2 Þ; where lt stands for the trend component of yt; nt allows for level shifts to the trend component; mt accounts for shocks to the slope, bt; wt captures the cyclical regularities in yt; L represents the lag operator; xt and xt represent shocks to the cyclical component; et accounts for short-term erratic movements and possible measurement errors in yt. et, nt, mt, and xt are assumed to be mutually independent white noise processes, with xt arising by construction under the constraint that r(x) = r(x*); k is the frequency of the cycle and q is the damping factor. The existence of short (high frequency) and long (low frequency) cycles makes it necessary to model a number of cycles simultaneously. Maximum likelihood estimates of the unknown parameters r(n), r(v), r(e), r(x), and q can be obtained by the Kalman filter algorithm (Harvey, 1989). Although such a time-series structural model has the limitation of imposing a specific structure upon the data, it has the advantage of modelling the trend and low frequency fluctuations jointly, without sample selection biases. In choosing this methodology, we have also considered other trend-cycle filters. For example, the wavelet methodology was used to evaluate the sensitivity of our results to the use of the UC model. Wavelet decomposition also has the advantage of being able to model a number of cycles that can change in amplitude and period over time. In fact the wavelet methodology yields very similar long swing phases to those reported here (in the case of GDP the correlation coefficient between the long swing cyclical components of the two methods is 0.91). For a technical discussion and application of the wavelet methodology to the study of long swings see Solomou and Wu (2006). The Hodrick–Prescott (H–P) filter, which has been employed widely in the recent business cycle literature, is not considered appropriate here as it explicitly neglects low frequency long swings by assumption. 2.1. Aggregate long swings Fig. 1 presents the smoothed estimate of the trend growth rate for Japan’s Gross Domestic Product, from the expenditure estimates of the national accounts.2 From the early 20th century, we observe some trend acceleration, with the trend growth rate increasing gradually from 2.6 percent in the 1880s to near 4.0 percent by the end of the 1930s. Fig. 2 displays the cyclical decomposition of GDP. Long swings of growth averaging 2 Although the output side of GDP yields similar long swing phases, the expenditure estimate is more reliable for the study of long swings; much of the output side of GDP is derived by assumption using the information from the expenditure side of GDP. For example, in analysing the ‘‘commerce’’ sector, accounting for 1/3 to 1/2 of GDP, the data are derived as the residual difference between the expenditure series of GDP and the actual production data for manufacturing, agriculture, construction, and transportation. Since sectoral long swings are not synchronised the sum of manufacturing, agriculture, construction, and transportation output displays trend linearity. Thus, commerce sector output follows the cycles of the expenditure estimate of GDP by assumption. Reliable annual GDP figures for Japan are only available from 1885. Using the GDP data compiled by Maddison (2003) shows that the period of the 1870s and early 1880s was a phase of slow economic growth, averaging a growth rate of 1.73 percent per annum, suggesting that the long swing feature of Japanese growth is observed since ca.1870.
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0.045 0.04 0.035 0.03 0.025
1940
1935
1930
1925
1920
1915
1910
1905
1900
1895
1890
1885
0.02
Fig. 1. Estimate of trend growth rate in Japan’s Gross Domestic Product 1885–1940. 0.08 0.06
1939
1937
1935
1933
1931
1929
1927
1925
1923
1921
1919
1917
1915
1913
1911
1909
1907
1905
1903
1901
1899
1897
1895
1893
1891
-0.02
1889
0
1887
0.02
1885
Deviation from Trend
0.04
-0.04 -0.06 -0.08 Short Cycle
Long Swing
Fig. 2. Long swings and short cycles in GDP: Japan 1885–1940 deviations from trend. Table 1 Long swings of GDP: expenditure estimate of GDP
1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
Percent growth rate per annum
Inter-period percent growth change
4.16 1.64 4.11 1.78 5.41
— 2.52 +2.47 2.33 +3.63
Sources: see Appendix A for sources to the GDP series.
approximately 20 years were an important fluctuation in the Japanese economy.3 The inter-period growth changes over these long swing phases are large. Table 1 reports geo3
The diagnostic statistics for this model are reported in the working paper version of this paper (Solomou and Shimazaki, 2006). In implementing the Kalman filter trend-cycle decomposition, we used Stamp 6.0. We followed a general to specific estimation procedure, initially allowing for the possibility of a stochastic level and a stochastic slope, up to three cycles of different durations and an irregular component. Based on the evaluation of the hyperparameter estimates, we were able to move to more efficient parsimonious models, which are the final models depicted in Figs. 1 and 2.
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metric growth rates for GDP over these phases. The amplitude of these ebbs and flows of economic growth was also large when compared to similar swings in the major industrial countries (Solomou, 1998). Comparing the descriptive phasing for long swings in GDP outlined here with earlier empirical work on Japan (Fujino, 1968; Ohkawa, 1979; Ohkawa and Rosovsky, 1973; Shinohara, 1962) highlights some noteworthy similarities and differences. Shinohara (1962) used a 5-year moving average (MA) methodology to describe the long swings in GDP and found the following phases: 1883/87–1898/02 1898/02–1903/07 1903/07–1918/22 1918/22–1928/32 1928/32–1933/37
Upswing Downswing Upswing Downswing Upswing
Ohkawa (1979) used a 7-year MA methodology and found the following long swing phases: 1887–1897 Upswing 1897–1904 Downswing 1904–1919 Upswing 1919–1930 Downswing 1930–1938 Upswing These phases of Japanese economic growth are similar to the long swings depicted in Fig. 2 suggesting that the MA methodology has not created statistical artefact swings in the data. As expected, however, the MA method fails to capture the timing of the actual historical turning points. Fujino (1968, p.36) equated macroeconomic long swings with construction sector swings: ‘‘The construction cycle, as defined by us, is thus not confined to the long swings observed in the behaviour of expenditure on construction, but covers the long swings in the economy as a whole.’’ Using this framework he derived the following phasing: 1885–1896 Upswing 1896–1904 Downswing 1904–1908 Upswing 1908–1914 Downswing 1914–1921 Upswing 1921–1932 Downswing 1932–1937 Upswing For much of the time, however, the macroeconomic swings of GDP and those of the construction sector are not synchronous.4 Thus, during 1896–1908 and 1908–1921, the long swings in construction sector output are of a much shorter duration than swings 4 The construction sector has also been seen as playing a key role in accounting for long swing fluctuations in America (Abramovitz, 1961), Britain (Thomas, 1973), and France (Le´vy-Leboyer, 1978). In the case of Japan, however, the trend-cycle decomposition for construction output shows that the longest significant cycle averaged 12.4 years in duration. Given that the length of the aggregate long swings in Japan was approximately double this duration, over the period 1885–1931 the construction sector had a small counter-cyclical effect on the long swings of GDP growth (see Solomou and Shimazaki, 2006, for a discussion of this sectoral evidence). Only during the 1930s does the sector have a role to play, accounting for 12 percent of the upswing of growth.
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in GDP. Clearly, Fujino’s assumption that the phasing of long swings in Japan can be determined by construction sector swings is invalid. An interesting result is that because the construction sector swings were of a shorter duration than the observed aggregate swings in GDP, the sector had a very limited effect on aggregate swings in the Japanese economy. 2.2. Disaggregate features of long swings To consider some of the disaggregate features of the observed swings, we employ a national accounting framework to quantify the impact of expenditure components of GDP on the aggregate swings over the GDP long swing reference cycle (See Table 2). Beginning with consumption, which accounted for approximately 70–85 percent of GDP over this period, we observe a high amplitude long swing as the dominant cyclical fluctuation.5 Consumption swings played a key role in accounting for the aggregate swings during the period 1885–1931, although the magnitude of the effect was declining over time (accounting for over 70 percent of the inter-period growth swing of 1885–1908, less than 60 percent of the swing over 1895–1919, and only 44 percent of the swing over 1908–1931). As is well known, consumption expenditure did not contribute to the marked growth revival of the 1930s. Private investment accounted for approximately 7–11 percent of GDP over this period. The unobserved components structural model decomposition identifies two high amplitude cycles, one of which is at the long swing frequency (with an average period of 25.4 years). The phases of the swings are similar to the aggregate GDP swings, with investment turning points leading the aggregate swings. The national income accounting results reported in Table 2 show that private investment played a key role in the episodes of growth after 1908. Investment accounted for 37, 65, and 46 percent of the inter-period growth changes during 1895–1919, 1908–1931, and 1919–1938, respectively. During the pre-1908 period, a low investment share and a relatively low amplitude investment swing meant that investment was not central to explaining the observed growth episodes.6 Shifts in government expenditure do not follow the long swing movements. Instead, stochastic changes are observed, mainly associated with war-related expenditure and long-term trend changes. Both the Sino-Japanese war (1894–1895) and the Russo-Japanese war (1904–1905) resulted in major increases in government expenditure and the immediate post-war periods were followed by large government expenditure reductions. The cycle generated from these shocks was of a shorter duration than the long swing frequency. These stochastic shifts in government expenditure had a major effect on the economy during the inter-war period. During the 1920s, high levels of government expenditure acted to partially compensate for other components of low demand; during the 1930s the rapid growth of government expenditure reinforced private investment and exports as rapidly growing components of aggregate demand. As can be seen from 5 The phases of the swings in consumption are similar, but not identical, to the aggregate swings before World War I but differ significantly in the inter-war period. Detailed cyclical decompositions for the expenditure components are reported in Solomou and Shimazaki (2006). 6 This result differs from Ohkawa (1979) who emphasises investment swings as being important to aggregate swings over the whole period 1885–1940.
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Table 2 Long swings in expenditure components of GDP (analysed over GDP reference swings) Long swing episode
Consumption 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938 Investment 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
(1) Annual growth rate
3.78 1.65 3.47 2.14 2.13
(2) Proportion of GDP
0.845 0.820 0.779 0.800 0.712
(3) Weighted effect on GDP growth
(4) Weighted inter-period growth effect
(5) Proportion of swing in GDP
3.19 1.35 2.70 1.71 1.52
— 1.84 1.35 0.99 0.19
— 0.73 0.58 0.44 0.05
5.33 2.40 9.50 3.67 12.38
0.0755 0.0792 0.1113 0.1056 0.1035
0.40 0.19 1.06 0.39 1.28
— 0.21 0.87 1.45 1.67
— 0.08 0.37 0.65 0.46
Government expenditure 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
7.74 2.77 2.57 5.62 9.74
0.0907 0.1512 0.1339 0.1764 0.2153
0.70 0.42 0.34 0.99 2.10
— 0.28 0.08 0.65 1.11
— 0.11 0.04 0.29 0.31
Exports 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
8.32 6.53 8.48 4.16 9.59
0.0348 0.0621 0.1166 0.1259 0.2136
0.29 0.41 0.99 0.52 2.10
— 0.12 0.58 0.47 1.58
— 0.05 0.25 0.21 0.44
Imports 1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
10.77 7.15 6.48 4.84 6.18
0.0462 0.1133 0.1379 0.2109 0.2136
0.50 0.81 0.89 1.02 1.32
— 0.31 0.08 0.13 0.30
— 0.12 0.03 0.06 0.08
Notes to Table 2: see Appendix A for data sources. Column (1) is calculated as the geometric annual growth rate over the specified period. Column (2) is the share of the expenditure component in GDP averaged over the specified period. Column (3) is derived as the product of column (1) and column (2). Column (4) is the inter-period growth difference of the weighted growth rate reported in column (3). Column (5) is calculated as the ratio of the inter-period growth changes reported in column (4) and the aggregate inter-period GDP growth changes reported in Table 1.
Table 2, during the pre-1919 period the direct effect of shifts in government expenditure was of relatively minor importance to the large swings of economic growth.7
7
This does not rule out indirect effects via effects on private sector consumption, as discussed below.
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Japan’s export share was trended upwards during the period 1885–1938, rising from 3.5 percent in the 1880s to 21 percent in the 1930s. The unobserved components structural model identifies stochastic shifts in the level of exports and a long swing averaging 19.7 years, with the amplitude of the long swings increasing after ca.1908. Given the small share of exports in GDP and the relatively low amplitude swings of export growth in the period 1885–1908, exports were not important to accounting for the segmentation of economic growth over this period. In fact, export growth had a counter-cyclical effect on the inter-period growth changes of 1885–1908. Only after 1908 does export growth have a large effect on the observed growth swings, accounting for 25 percent of the growth upswing of 1908–1919 and 21 percent of the downswing of 1919–31. Rapid export growth had its largest impact on the growth revival of the 1930s, accounting for 44 percent of the inter-period growth step (see final column of Table 2). Japan’s import share is similarly trended upwards over this period. However, considering imports as a negative component of aggregate demand suggests that most of the effect of trade on Japanese long swings is due to the effect of export swings rather than swings in imports. Summarising the disaggregate evidence, whilst the observed aggregate GDP growth swings before World War II are described as relatively stable in amplitude and average period, the components of expenditure are less regular, displaying important shifts over time. An explanatory framework for the observed swings has to note that the pre-1908 swings were mainly accounted for by swings in private sector consumption whilst swings of growth during 1908–1931 were determined by swings in private sector investment and exports. The upswing of the 1930s was accounted by movements in government expenditure, private investment, and exports. 3. Explanations for Japan’s long swings The existing literature has offered a number of conflicting explanations for the observed long swings. Fujino (1965, 1968) emphasises an endogenous perspective assigning a central role to the production structure of the construction sector. In contrast, Shinohara (1962, 1978) emphasises specific historical shocks for each segmented growth episode. For example, the upswing of 1883/87–1898/02 is attributed to the expansion of the railway network, the growth of electricity, expansion of exports in a phase of silver depreciation, and the reparation payments following the Sino-Japan war of 1894–1895. The downswing of 1898/1902–1903/07 is attributed to reduced railway construction, international price deflation, and depression of exports. The boom up to 1918/22 is attributed to WWI and an expansion of exports. The downswing of the 1920s is attributed to high domestic prices, high levels of imports, and an efflux of gold. Devaluation and militarism in the 1930s caused a revival of economic growth. Williamson and De Bever (1977, p.164) emphasise war shocks, postulating ‘‘. . .war-related ‘stop-go’ explains most of Japanese long swing experience and investment spurts.’’ In contrast, Ohkawa (1979, p. 18) concludes, ‘‘The evidence is at best ambiguous, and it is my view no long-term trends or swings can be related to the level of military spending.’’ To clarify this debate, we evaluate the kind of shocks affecting long swings. To do so, we model the long-run determinants of exports, consumption, and investment, which have been shown to be important in the national accounting framework as a descriptive
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Table 3 Japan’s exports, trading partners’ income, real exchange rate, and percent tariff rate
1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
Total exports
Trading partners’ income
Real effective exchange rate
Weighted tariff rate of Japan’s trading partners
8.32 6.53 8.48 4.16 9.59
2.35 2.71 3.19 1.61 4.01
2.99 2.70 0.98 0.12a 2.99
9.44 9.29 6.83 9.15 18.04
Sources: see Appendix A for data sources. Exports, trading partners’ income, and real exchange rate are expressed as growth rates per annum. a The actual path of the real exchange rate shows a peak of appreciation in the early 1920s and a ‘correction’ in the 1920s. This low appreciation over the whole period may not capture the full impact of exchange rate movements.
explanation of long swings. We use two methodologies to derive these long-run relationships. First, given the non-stationary nature of the data series, we use the Johansen co-integration methodology to evaluate whether the key variables share common trends. However, given the low statistical power of the unit root tests we also use the ARDL methodology of Pesaran and Shin (1999) to derive a second set of coefficients to compare with the Johansen co-integration results. What determined export swings and why was the effect of exports on GDP growth swings larger in the post-1908 period? We model the determinants of Japans’ exports as entailing a long-run relationship with Japan’s multilateral real effective exchange rate, the weighted tariff rate of Japan’s main trading partners, and an index of trading partners’ income.8 The path of these variables over the reference swings in GDP is presented in Table 3. Table 3 shows that in the pre-World War I period, trend movements in world income and the real exchange rate are likely to have had counter-acting effects (the average tariff rate showed little change over this period).9 The adverse effect on exports of a real exchange rate appreciation during 1895–1908 was partly counter-balanced by a favourable trading partners’ income effect, although the net effect depends on relative magnitudes of these effects. In contrast, during the interwar period we observe a cluster of synchronised shocks. For example, during 1919–1931 an overvalued yen reinforced an adverse trading partners’ income effect. During the 1930s, rapid growth in trading partners’ income was reinforced by rapid yen depreciation.
8
The data are described in Appendix A to this paper. Comparing the real effective exchange rate used here with other series displays major discrepancies. For example, Minami (1986) uses the terms of trade data, adjusted for nominal dollar–yen exchange rate as the real exchange rate. Comparing our real effective exchange rate (REER) data with Minami’s index, whilst the data for the REER shows that Japan witnessed large real yen depreciation during 1885–94, Minami’s index shows a stable, although cyclical, level. Whilst we find a trend of appreciation during 1894–1913, Minami’s index shows appreciation in the late 1890s and depreciation during 1900–1913. Our data suggest that the 1920s witnessed a persistently high REER index (despite the mild depreciation during 1921– 1930) whilst Minami’s data suggest a larger depreciation. 9 Japan gained the right to set tariffs only in 1899 but until 1911 a series of treaties with the USA and European countries resulted in a low tariff regime over this early period.
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Over the period 1885–1938 exports, the real effective exchange rate, the weighted tariff rate of Japan’s main trading partners, and an index of trading partners’ income are integrated of order 1.10 We first estimated the optimal lag order of the unrestricted VAR model of these variables, which was found to be 1. In estimating the Johansen co-integration methodology, we begin with the most general models and move to more restricted models, evaluating the existence of cointegrating vectors.11 The results suggest that there exists one cointegrating vector between exports, the real effective exchange rate, trading partners’ income, and trading partners’ weighted average tariff rate.12 The long-run income and exchange rate coefficients have the expected sign and are statistically significant (all variables in logs; t values in parentheses) ECM ¼ Exports 2:5622 Trading Partners’ Income ð7:24Þ þ 1:1848 Real Exchange Rate 0:3182 Tariff. ð3:91Þ ð0:70Þ An alternative method of estimating the long-run coefficients is to use single equation auto-regressive distributed lag models (ARDLs) where dependent and independent variables enter the right-hand side with lags of order p and q, respectively Yt ¼ a þ
p X i¼1
bY ti þ
q X
cXtj þ et ;
j¼0
where Y is the dependent variable, in this case exports, and X is a vector of three explanatory variables (trading partners income, the real exchange rate, and tariff rates). This ‘classical’ time-series model has been extended by Pesaran and Shin (1999) who demonstrate consistency and super consistency results for the short- and long-run parameter estimates, respectively, when there exists a cointegrating relationship between the variables. Further, cointegration is not a pre-requisite for employing an ARDL representation. Given the low power of unit root and cointegration tests for small sample sizes, the ARDL method provides a good alternative to cointegration. The ARDL model above can be re-parameterised in first differences to derive long-run coefficients for exogenous variables of interest. We employ the two-step procedure for estimating the ARDL (p, q) model. In the first step, we chose the order of the ARDL using the Schwartz–Bayesian criterion of
10 Since our focus in this paper is on the long swing movements, we only report the long-run coefficients. The framework used can also be applied to modelling short-run movements within the ECM framework. The variables are considered in log form. Using the AIC to choose the optimal lag order of the ADF tests shows that we fail to reject the unit root hypothesis for all these variables. 11 The co-integration models considered are, from most general, unrestricted intercept and unrestricted trend, unrestricted intercept and restricted trend, unrestricted intercept and no trend, restricted intercept and no trend, and no intercept and no trend. The estimation was undertaken using Microfit (Pesaran and Pesaran, 1997). 12 The co-integration model that yields a cointegrating vector is the no trend and no intercept model. The model evaluated treated tariffs, world income, and the real effective exchange rate as having exogenous effects on Japan’s exports. The tariff rate is found to be insignificant. One problem to note in this regard is that during the 1930s a significant shift in Japan’s trade regionalisation means that the weighted tariff rate is not representative during this decade. Data limitations prevented us from improving on this index. Whilst the weight of the 13 countries covered by the tariff data account for over 70 percent of Japan’s trade between 1880 and 1930, the coverage fell to 41 percent by 1938. The new trade regionalisation arising in the 1930s implies that the tariff hike of the 1930s was not as large as the calculated series implies.
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Table 4 Estimated long-run coefficients using the ARDL approach Regressor
Coefficient
t ratio
Trading partners’ income Real effective exchange rate Weighted tariff rate
2.9346 1.4185 0.1107
25.26 13.19 0.27
model selection, allowing for up to four lags. The selected model (which is found to be an ARDL (1, 0, 0, 0) model with an insignificant time trend) is then used to estimate the longrun parameters of interest (see Table 4). The two approaches yield very similar estimates for the long-run coefficients. Given the large shifts in trading partner income and Japan’s real effective exchange rate these key variables determined the large swings in Japan’s exports.13 This analysis illustrates some important aspects regarding the impact of shocks on Japan’s economic growth. In the pre-1908 period, the relatively low amplitude of export swings was not due to an absence of shocks, but was the outcome of favourable and adverse shocks to competitiveness and world incomes that partly counter-balanced each other. In contrast, during 1908–1938 a co-movement of shocks resulted in high amplitude export swings that had large effects on the swings of economic growth.14 In the period of adjustment after the First World War this cluster of adverse shocks resulted in a halving of Japan’s export growth rate relative to the pre-1913 period (see Table 3). The swings of consumption have been shown to be important in the aggregate swings during 1885–1931. If the movements of consumption are anything more than endogenous responses to long swings in income, we need to model consumption behaviour in the Japanese economy as being influenced by some exogenous variables, resulting in consumption shifts. We extend the work of Minami (1986) who estimated a consumption function in terms of personal disposable income in three ways. First, we include government consumption as a possible explanatory variable allowing us to evaluate the contrasting hypotheses of Ohkawa (1979) and Williamson and De Bever (1977) regarding war and long swings. This can be interpreted within a framework of Ricardian equivalence or simply as capturing crowding-out effects of war-related movements in government expenditure on private consumption. In this light, the rapid increase in Government expenditure observed in the Sino-Japanese war (1894–1895) and the Russo-Japanese war (1904–1905) may have had significant exogenous effects on the private sector.15 Second, we also consider real money balances16 in explaining consumption movements, capturing monetary, and price effects on consumption. Finally, given the non-trend-stationary
13
The existing literature offers mixed results on the role of prices in the determination of Japan’s exports. For the pre-1913 period, Shinohara (1962) argues that the relative price effect was large, whilst Minami (1986) finds that the relative price effect was relatively unimportant. In the light of our results these differences can be resolved by noting limitations in Minami’s real exchange rate measure. 14 This analysis allows us to comment on the literature on Japan’s recovery in the 1930s. Cha (2003) found that exports had a short-run effect during 1931–1932. This result is contradicted by our finding of a long-run effect. The paradox can be resolved by noting that Cha uses VAR analysis, a methodology that relies on stationary data and thus cannot comment on the long-run relationship between exports and economic growth in the 1930s. 15 In both wars, bond issues and increased taxation financed government expenditure. 16 Money supply is taken as M2.
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Table 5 The determinants of private sector consumption (growth per annum)
1885–1895 1895–1908 1908–1919 1919–1931 1931–1938
Private sector consumption
Personal disposable income
Government consumption
Real money balances
3.78 1.65 3.47 2.14 2.13
4.66 1.58 4.49 1.31 4.53
8.42 0.60 3.06 5.15 7.10
6.95 6.27 8.51 7.33 4.89
Sources: see Appendix A for sources.
nature of the data, we use cointegration methods to estimate the long-run coefficients of interest. Our formal model explains real aggregate personal consumption in terms of real aggregate personal disposable income (rpdi), real government consumption (rgc), and real money balances (rmb).17 The path of these variables over the long swing reference periods is presented in Table 5. The optimal lag order of the unrestricted VAR model for consumption was found to be 2. The results suggest that there exists one cointegrating vector between private consumption, personal disposable income, real money balances, and government consumption. The long-run coefficients have the expected sign and are statistically significant (t values in parentheses): ECM ¼ aggregate personal consumption 0:72097 rpdi 0:21806 rmb ð4:61Þ ð2:57Þ þ 0:2628 rgc ð3:40Þ The selected ARDL model for consumption (based on the Schwartz–Bayesian criterion) ARDL (1, 2, 0, 0) generated the long-run coefficients of interest reported in Table 6. The results suggest that war and shifts in government consumption had two major channels of influence on consumption (see Table 6). Large tax increases, such as those after the Sino-Japan War (1894–1895), directly affected disposable income and large increases in Government consumption had a significant crowding-out effect on private sector consumption.18 Thus, the rapid growth of Government consumption during war and the trended growth during 1908–1938 contributed to the retarded growth rates of private consumption. Swings in private investment are found to be important in accounting for swings in GDP growth during the period 1908–1938. What need to be identified are the exogenous shocks driving swings in investment. Minami (1986) estimates an investment function (covering non-primary fixed capital formation)19 for the period 1907–1940 employing 17
We also included ex post real interest rates but this proved insignificant in all the estimations. All the variables are considered in log form. Using the AIC to choose the optimal lag order of the ADF tests shows that we fail to reject the unit root hypothesis for all these variables. 18 A similar result is reported in Ohkawa (1979, p. 17). Despite this, as noted above, Ohkawa argued that war was not critical to the swings. This does not sit well with the evidence. Within a multi-variate perspective to the swings, war is one of the important shocks affecting the Japanese economy on a number of occasions during 1885–1940. 19 Government and primary sector investment are excluded.
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Table 6 Estimated long-run coefficients of consumption function using the ARDL approach Regressor
Coefficient
t ratio
Personal disposable income Real money balances Real government consumption Constant
0.6901 0.1709 0.1355 3.0879
6.28 4.05 3.43 3.87
Table 7 Estimated long-run coefficients for investment using the ARDL approach Regressor
Coefficient
t ratio
Real interest rate Rate of profit Log capital stock Constant Time trend
4.18 0.075 5.23 32.00 0.2220
4.74 4.89 5.71 5.20 4.45
one period lags of the real return to capital, the real interest rate, and the capital stock. Minami’s specific results are problematic given the presence of autocorrelation in his estimates, invalidating the significance tests. This may reflect the lagged dependent variable effects and the non-trend stationary structure of the time-series data analysed by Minami. The ARDL framework allows us to re-estimate Minami’s model to overcome these problems.20 Moreover, since our focus is on long swings, the ARDL method also allows us to estimate long-run relationships. Using variables similar to those of Minami (1986), we estimate an ARDL model of non-primary fixed capital formation for the sample period 1907– 1940.21 In using the ARDL specification, we do not follow Minami in imposing a fixed one period lag on the structure of the model. In the first step, we chose the optimal order of the ARDL using the Schwartz–Bayesian criterion of model selection and allowing for a wide ARDL lag structure. The selected model is an ARDL (0, 2, 3, 4) model with a significant time trend. The model suggests a two period lag on the real interest rate, a three period lag on the rate of profit, and a four period lag on the capital stock. The selected model is then used to estimate the long-run parameters of interest (Table 7). The results are not directly comparable to those of Minami but they confirm Minami’s intuition that capital formation is influenced by real interest rates, the rate of profit, and the level of the capital stock. The ARDL model suggests that the long-run effect of the capital stock is positive, i.e., a high level of the capital stock stimulates investment.22 However, beyond this proximate explanation we need to emphasise that real interest rate movements were, in turn, determined by a multitude of real and monetary shocks. For example, with regard to nominal interest rates the business cycle literature on Japan shows that during the gold standard period changes in the discount rate often depended on the balance of payments position and gold flows (Fujino, 1965, 1968; Oshima, 1955; Takamura, 1975).
20
Given the limited sample time period, we limit ourselves to working with the ARDL model. We also included Government investment as an explanatory variable to evaluate the existence of crowdingout effects but found this to be statistically insignificant. 22 Minami (1986) also observed a positive capital stock effect. 21
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Nominal interest rates were also influenced by policy regime shocks; the attempt to return to the gold standard at the 1913 parity forced a high interest regime on Japan for much of the 1920s. In contrast, the devaluation of the 1930s allowed an expansionist monetary policy. 4. Discussion and future research What insights does the study of Japan offer for our understanding of the causes of episodic long swings of economic growth? Clearly the RBC approach that emphasises one-off ‘‘Great depressions’’ is misleading in that the approach neglects relevant information about the growth process; the historical record suggests that the other side of the existence of ‘‘Great depressions’’ is the existence of long swing boom periods that need to be accounted for within a unified framework. The evidence considered suggests that the ebbs and flows of economic growth are partly the result of ‘‘shocks.’’ As examples, we have shown how shocks affected the episodic long swing movements of exports, consumption, and investment. In focusing on the determinants of these shocks, we have emphasised, inter alia, shifts in world income, the real exchange rate, the growth of government expenditure, and monetary shocks related to major institutional changes. This analysis has allowed us to extend the inferences of Shinohara (1962), Williamson and De Bever (1977), and Ohkawa (1979) regarding the type of shocks that impacted on long swings. It seems clear that a diverse set of shocks affected Japanese growth swings over this period.23 However, the pervasive nature of long swings in economic growth in the 19th and 20th centuries should encourage researchers to discuss the possibility of endogenous explanations of quasi-cyclicality—it is in this light that we offer some speculative thoughts in this section. Business cycle theories have alternated between endogenous theories versus a discussion of the shocks and propagation mechanisms to account for economic cycles. After surveying American long swings in the period 1840–1914 some time ago Abramovitz (1959) concluded: It is not yet known whether they are the result of some stable mechanism inherent in the structure of the US economy, or whether they are set in motion by the episodic occurrence of wars, financial panics, or other unsystematic disturbances. (Abramovitz, 1959) What Abramovitz seems to have had in mind is that the question of endogeneity is an open one. It is quite clear from our discussion of Japan that mechanical ideas of endogenous swings are unable to explain Japanese long swings. Thus, Fujino’s emphasis on endogenous construction cycles is of little help to understand Japanese macroeconomic swings. Given the historical record of Japan and a number of other countries an avenue of future research is to consider the role of the policy framework in long swing fluctua-
23 Our approach here has focused on shocks to expenditure. Looking at the output side of the national accounts suggests that structural change and sector-specific shocks were also important in particular episodes. For example, although the declining share of agriculture meant that the sector had a declining role in economic growth over long-run time horizons, the path of agricultural decline was not linear and, as a result, this sector had a large one-off effect on the episode of slow economic growth during 1919–1931(Solomou and Shimazaki, 2006).
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tions. In choosing a rules-based policy framework, such as the gold standard, a necessary outcome is the need for cyclical adjustment. This type of adjustment was manifested in a number of ways. In the case of the core industrial countries before World War I they were able to sustain the gold standard rule as their policy framework and were able to use migration, capital flow, trade, and real exchange rate adjustment to cope with a changing and stochastic economic environment (Cata˜o and Solomou, 2005). The slow-relaxing nature of these variables meant that most of the movement is observed in the long swing frequency rather than the shorter business cycle frequency. The same set of adjustments was not available to all countries. For example, in the case of Japan neither migration nor capital flows provided effective adjustment and the real exchange rate fluctuations contributed to shocks. A more limited set of adjustment mechanisms may have resulted in high amplitude swings in Japan. The growth swings of Japan in the period of the gold standard (1897–1931) can be thought of as being determined/influenced by the workings of this system. For example, large increases in Government expenditure (which had inflationary effects) had to be mean reverting over time to maintain a credible commitment to the gold standard. During the inter-war period, a similar framework can be used to analyse the slow economic growth of the 1920s in terms of policies to facilitate the return to the gold standard (Patrick, 1971). Thus, for much of the pre-WWII period the policy regime modulated economic growth via feedback rules driven by the need to maintain policy credibility. To a large extent long swings of economic growth can be thought of as an endogenous response of adjustment processes to sustain the gold standard policy framework. Clearly, in this context, the effects of shocks have to be seen in the context of a particular set of policy institutions; a different combination would have yielded different types of cyclicality. As economies attempt to re-create rules-based monetary and fiscal policy frameworks, we may find that long swings of growth will be observed in future paths of economic growth. Appendix A A.1. Japan’s macroeconomic data The data sources we use are the revised estimates reported originally in LTES (Estimates of Long-Term Economic Statistics of Japan) (1965–1979). The revisions to these series as reported in Ohkawa Shinohara, M. (Eds.) with L. Meissner, 1979), Patterns of Japanese Economic Development, New Haven, Yale University Press. The original data reported in LTES were revised because of revisions to the price series for imports and exports as reported in volume 14 of LTES. The GDP series and the component series are based on 1934–1936 prices. A.2. Average tariff rate of main trading partners Tariff data are revenue tariff data, based on the work of Clemens and Williamson (2004). We were able to include 13 countries: UK, USA, China, Canada, India, Egypt, Australia, France, Italy, Germany, Indonesia, Russia, and Thailand, accounting for approximately 75% of Japan’s trade for most of the period. To construct the average tariff rate for the period 1870–1913, we weight tariff rates with trade shares in 1879 and 1913 and
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use the geometric average of these two series. For the period 1913–38, we use the weights of 1913 and 1929 and take a geometric average. Trade weights were derived from the following sources: Japan Statistical Association (1988), Historical Statistics of Japan, Tokyo; Yamazawa and Yamamoto (1979), Foreign Trade and Balance of Payments, Estimates of Long-Term Economic Statistics of Japan since 1868, vol. 14; and Toyo Keizai Shinposha, Tokyo (in Japanese). Toyo Keizai Shinposha (1935), Foreign Trade of Japan: A Statistical Survey. A.3. Real effective exchange rates For the period 1870–1938, we spliced together the real effective exchange rate index of Cata˜o and Solomou (2005), covering the period 1870–1913 and the index of Shimazaki and Solomou (2001), covering the period 1913–1938. Both series are based on 1913 = 100. Details of the data sources used to construct the Catao–Solomou index are reported in http://www.e-aer.org/data/sept05_app_catao.pdf. The data sources used by Shimazaki and Solomou (2001) are reported in the Appendix to that paper. A.4. Trading partners’ income The construction of this series was constrained by the availability of reliable GDP data—although China was an important trading partner, the lack of reliable annual GDP data for China before WWII prevented its inclusion in the index. For the period 1879–1902, we constructed an income index as the weighted average for six of Japan’s main trading partners, accounting for approximately 75% of trade in 1879 (US, UK, France, Germany, Italy, and Australia). Taiwan, India, and Dutch India were added for the period 1903–1913). Income of each country is expressed as 1903 = 100. An index of trading partner income is constructed using bilateral trade weights for 1879 and 1903, respectively. A geometric mean is used to derive an ideal index over this period. For the period 1903–1913 income indices were constructed using bilateral trade weights for 1903 and 1913, respectively. For the period 1913–1938 an income series is constructed as the weighted average for 10 of Japan’s main trading partners (USA, UK, France, Germany, Italy, Australia, Taiwan, Korea, India, and Dutch India), accounting for 56–62% of Japan’s visible trade, using trade weights for 1913 and 1938, respectively. A geometric mean was then used to derive an ideal index over this period. These indices are spliced together to derive a series over the whole period 1885–1938. GDP data for USA, UK, France, Germany, Italy, and Australia and India are reported in Maddison (1995): Monitoring the World Economy 1820–1992, OECD, Paris, and Maddison (2003). Data for Japan’s colonies can be found in Mizoguchi and Umemura (1988), Basic Economic Statistics of Former Japanese Colonies 1895–1938. Estimates and Findings. Toyo Keizai Shinposha, Tokyo. References Abramovitz, M., 1959. Historical and Comparative Rates of Production, Productivity and Prices, Statement in US Congress, Joint Economic Committee, Employment, Growth and Price Levels, Hearings (86th Congress), Pt. II, Washington, pp. 411–466.
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