The economic geography of Japanese industrialization ( )

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1 International Workshop on The Economic Geography of Long-Run Industrialization (ca ) International Institute of Social History, Amsterdam, March 2018 The economic geography of Japanese industrialization ( ) Jean-Pascal Bassino (IAO, ENS Lyon, University of Lyon; Kyoji Fukao (Institute of Economic Research, Hitotsubashi University; Tokihiko Settsu (Department of Economics, Musashi University; 1

2 Outline 1. The age of cottage industry ( ) 2. The gradual shift to manufacturing ( ) 3. The emergence of an industrial power ( ) 4. High speed growth and itsaftermath ( ) 2

3 1. The age of cottage industry ( ) Modest growth rate of output, but some technical change (Odaka 1996) - Steady increase in cotton processing between ca 1800 and 1850 (stagnation between 1850 and 1875) - Steady increase of iron production between ca 1800 and 1830; technological shift in the mid-19 th century from old (nanban ) to modern European technology Political and economic fragmentation ; conducive to the development of cottage industry during the Tokugawa period, particularly in the late 18 th and early 19 th century (estimates for 1804 and 1846) - Cottage industry in all regions ; but no more that 5% of GDP in most regions - Concentration in the Edo (Tokyo) and Osaka areas (around 15% of GDP) - Some degree of regional specialization (based on data for 1874) After the opening to international trade (1858), - winners: port-cities (Yokohama and Kobe) and silk processing areas (Kanto and Tosan) - losers: rural cotton processing areas of western Japan 3

4 Figure 1. Value added per resident in the secondary sector in rice equivalent (kg) Eastern Tohoku Western Tohoku Eastern Kanto Western Kanto Tosan Hokuriku Tokai Kinai (inner) Kinai (periphery) San-in Sanyo Shikoku Northern Kyushu Southern Kyushu Japan average 4

5 Figure 2. Value added in the secondary sector in % of GDP in

6 Figure 3. regional specialization in 1874 (% of total output value in manufacturing) 100% 80% 60% 40% 20% 0% East Tohoku North Tohoku East Kanto West Kanto Tosan Hokuriku Tokai Kinai (inner) Kinai (outer) San-in Sanyo Shikoku North Kyushu South Kyushu Food and beverages Tobacco Textiles Books Chemical Ceramics Wood products Metal Machinery Paper Misc. 6

7 2. The gradual shift to manufacturing ( ) In most prefectures (exception of the most urbanised) -Labour input shares increasing much faster in the secondary sector than in the tertiary sector in Meiji I ( ): labour intensive industrialisation -But labour input shares increasing slower in the secondary sector than in the tertiary sector in Meiji II ( ): gradual shift toward a more physical and human capital intensive industrialisation Regional migrations: probably limited in Meiji I Increasing in Meiji II: enhanced by the development of the railway network, particularly local lines (Saito 1998). 7

8 Increase of Labor Input Share in the Secondary and the Tertiary Sector: , in percentage points Tokyo Osaka Kanagawa Hyogo Kyoto Hokkaido Aichi Nara Fukuoka Wakayama Toyama Tochigi Akita Kagawa Mie Miyagi Shizuoka Yamaguchi Ehime Hiroshima Shiga Yamagata Miyazaki Okayama Kochi Fukushima Kumamoto Niigata Saga Iwate Saitama Ishikawa Fukui Nagasaki Gumma Gifu Aomori Tokushima Nagano Tottori Kagoshima Yamanashi Chiba Oita Shimane Ibaraki Okinawa Increase of the labor input share of the secondary sector Increase of the labor input share of the tertiary sector Figure 4: Increase of labour input share in the secondary and the tertiary sectors ( , in percentage points) Source: Calculation based on underlying data in Fukao et al. (2015) Note: Prefectures are ordered by labour productivity of each prefecture in

9 Increase of Labor Input Share in the Secondary and the Tertiary Sector: , in percentage points Tokyo Osaka Kanagawa Hyogo Kyoto Hokkaido Aichi Nara Fukuoka Wakayama Toyama Tochigi Akita Kagawa Mie Miyagi Shizuoka Yamaguchi Ehime Hiroshima Shiga Yamagata Miyazaki Okayama Kochi Fukushima Kumamoto Niigata Saga Iwate Saitama Ishikawa Fukui Nagasaki Gumma Gifu Aomori Tokushima Nagano Tottori Kagoshima Yamanashi Chiba Oita Shimane Ibaraki Okinawa -6.0 Increase of the labor input share of the secondary sector Increase of the labor input share of the tertiary sector Figure 5: Increase of labour input share in the secondary and the tertiary sectors ( , in percentage points) Source: Calculation based on underlying data in Fukao et al. (2015) Note: Prefectures are ordered by labour productivity of each prefecture in

10 Regional productivity gaps and concentration Small regional gaps in labour productivity in the secondary sector ca 1874 Secondary sector: - gap increasing in Meiji I ( ): modern manufacturing techniques with high labour productivity only in a few prefectures - but stable in Meiji II ( ): diffusion of best practices (e.g. silk reeling) and imported technologies (e.g. British cotton spinning technology) Share of manufacturing increasing rapidly after 1890, -In Osaka and Tokyo -in a number of new industrial districts (e.g. mechanical industry and/or shipbuilding in Aichi and Fukuoka) -in silk reeling district of eastern Japan (in particular in Nagano and Yamanashi prefectures) 10

11 3. The emergence of an industrial power ( ) Quantitative investigation of regional gaps in labour productivity during the Japanese manufacturing catch-up based on recent estimates (Fukao et al. 2015) : - value added for 9 manufacturing subsectors: food, textile, wood, printing, chemicals, ceramics, metals, machinery, and misc. manuf. (available for 1874, 1890, 1909, 1925, 1935, 1940 at the prefecture level). - labour force (adjusted for by-employment) in these 9 subsectors (prefecture levelfor 1909, 1925, 1935, and 1940) Methodology: 1) Calculation of regional gap in productivity: technology frontier vs. rest of the country 2) Calculation of indicators of changes in prefectural ranking (correlation matrices; Spearman's rho and Person s index) 11

12 Labour productivity in the frontier (yf) and in other regions (yb), and ratio yf/yb (frontier: top 5 prefectures; yf and yb as indices, 1 for yb in 1909) Manufacturing Labour productivity of the frontier (yf) Labour productivity of other regions (yb) Productivity gap (yf/yb) Figure 6: changes in regional labour productivity gaps 12

13 Regional productivity levels in manufacture: correlation matrix and ranking stability Table 1: correlation matrix of regional productivity levels Spearman's rho p-value *** *** *** *** Pearson Table 2: ranking stability of regional productivity levels 13

14 Changes in the technological frontier Listof bottom 10 and top 10 relatively stable, butinstability in ranking. Top 5 ( frontier ) also instable; e.g. manufacturing as a whole: 1909: 1 Tokyo, 2 Osaka, 3 Hyogo (Kobe), 4 Hokkaido, 5 Aichi (Nagoya) 1925: 1 Osaka, 2 Tokyo, 3 Hyogo, 4 Kanagawa (Yokohama), 5 Hokkaido 1935: 1 Kanagawa, 2 Fukuoka (north Kyushu), 3 Osaka, 4 Tokyo, 5 Yamaguchi 1940: 1 Fukuoka, 2 Yamaguchi (west Honshu), 3 Kanagawa, 4 Hyogo, 5 Tokyo Rapid relative decline of Kyoto prefecture, former core area of Japanese proto-industry (high-quality tea, traditional handicraft, and textile products): rank 7 in 1909, rank 9 in 1925, rank 16 in 1935, rank 18 in

15 Regional gaps by manufacturing subsector Decline of regional gaps (ratio yf/yb) in all subsectors, particularly between 1909 and 1925 (strong demand for manufactured goods duringwwi) 8,0 7,0 6,0 5,0 4,0 3,0 2,0 1, ,0 Food Textile Wood Printing Chemicals Ceramics Metals Machinery Figure 7: regional gaps in productivity level (ratio yf/yb) Misc. 15

16 4. High speed growth and its aftermath Rapid regional convergence occurred from the 1950s to the 1970s Figure 2.1 Long-term trends in the coefficient of variation of per capita GPP (in local and national prices) CV unweighted (local prices) CV weighted (local prices) CV weighted (data, national prices) CV weighted (interpolation, national prices)

17 Japan continued to have a large productivity gap across sectors. Rapid industrialization in rural Japan in the high-growth era must have contributed to the regional convergence. Relative Labor Productivity between Sectors 100% 90% 80% 70% 60% 50% 40% Share of Labor Input by Sector Secondary sector/primary sector Tertiary sector/primary sector 30% 20% 10% % Primary sector Secondary sector Tertiary sector 17

18 50,000,000 Number of Workers by Sector 45,000,000 40,000,000 35,000,000 30,000,000 25,000,000 20,000,000 15,000,000 10,000,000 5,000, Primary sector Secondary sector Tertiary sector 18

19 Pace of structural transformation Year Fukuoka Kochi Kanagawa Ishikawa Tokyo Diverse trajectories of structural transformation Source: Paul and Fukao (2017) Note: By-employment is considered while calculating man-hour input shares. The primary sector consists of agriculture, forestry and fisheries. See Fukao et al. (2015) for a detailed discussion on the data estimation methodology. 19

20 60.0% 1955, GPP weighted CV of value added share of the manufacturing sector= Value added share of the manufacturing sector 50.0% 40.0% 30.0% 20.0% 10.0% GPP per capita (thousand yen) 0.0% Tokyo Osaka Kanagawa Hyogo Aichi Shizuoka Wakayama Fukuoka Yamaguchi Hokkaido Kyoto Toyama Mie Ishikawa Hiroshima Shiga Tottori Fukui Gifu Tochigi Okayama Akita Kagawa Nara Niigata Nagano Ehime Miyagi Gumma Fukushima Oita Chiba Ibaraki Tokushima Saga Saitama Kochi Yamagata Miyazaki Shimane Kumamoto Aomori Yamanashi Nagasaki Iwate 0.0 Value added share of the manufacturing sector GPP per capita (thousand yen) In 1955, manufacturing activity was still concentrated in rich prefectures. 20

21 Value added share of the manufacturing sector 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 1970, GPP weighted CV of value added share of the manufacturing sector= GPP per capita (thousand yen) 0.0% Tokyo Osaka Kanagawa Aichi Wakayama Yamaguchi Hiroshima Hyogo Shizuoka Toyama Okayama Mie Kyoto Shiga Ishikawa Chiba Tochigi Fukuoka Kagawa Gifu Gumma Ehime Ibaraki Nagano Fukui Hokkaido Tottori Saitama Niigata Oita Nara Tokushima Miyagi Akita Kochi Fukushima Yamanashi Saga Yamagata Iwate Miyazaki Aomori Shimane Kumamoto Nagasaki Kagoshima 0.0 Value added share of the manufacturing sector GPP per capita (thousand yen) From 1955 to 1970, the value added share of the manufacturing sector increased substantially in middle-income regions. 21

22 60.0% 1990, GPP weighted CV of value added share of the manufacturing sector= Value added share of the manufacturing sector 50.0% 40.0% 30.0% 20.0% 10.0% GPP per capita (thousand yen) 0.0% Tokyo Aichi Osaka Shiga Shizuoka Toyama Tochigi Hiroshima Fukui Okayama Ishikawa Gumma Yamaguchi Mie Hyogo Kagawa Nagano Ibaraki Fukushima Kanagawa Niigata Kyoto Hokkaido Oita Ehime Fukuoka Yamanashi Tottori Miyagi Gifu Saga Akita Iwate Tokushima Wakayama Yamagata Chiba Shimane Kochi Aomori Miyazaki Nagasaki Kagoshima Kumamoto Saitama Okinawa Nara 0.0 Value added share of the manufacturing sector GPP per capita (thousand yen) From 1970 to 1990, the CV did not decline substantially. 22

23 1955, weighted CV of labor productivity in the manufacturing sector=0.29 (weight=number of workers in the manufacturing sector) Labor productivity in the manufacturing sector Tokyo Osaka Kanagawa Hyogo Aichi Shizuoka Wakayama Fukuoka Yamaguchi Hokkaido Kyoto Toyama Mie Ishikawa Hiroshima Shiga Tottori Fukui Gifu Tochigi Okayama Akita Kagawa Nara Niigata Nagano Ehime Miyagi Gumma Fukushima Oita Chiba Ibaraki Tokushima Saga Saitama Kochi Yamagata Miyazaki Shimane Kumamoto Aomori Yamanashi Nagasaki Iwate Kagoshima GPP per capita Labor productivity in the manufacturing sector (thousand yen) GPP per capita (thousand yen) 23

24 Labor productivity in the manufacturing sector , weighted CV of labor productivity in the manufacturing sector=0.32 (weight=number of workers in the manufacturing sector) Tokyo Osaka Kanagawa Aichi Wakayama Yamaguchi Hiroshima Hyogo Shizuoka Toyama Okayama Mie Kyoto Shiga Ishikawa Chiba Tochigi Fukuoka Kagawa Gifu Gumma Ehime Ibaraki Nagano Fukui Hokkaido Tottori Saitama Niigata Oita Nara Tokushima Miyagi Akita Kochi Fukushima Yamanashi Saga Yamagata Iwate Miyazaki Aomori Shimane Kumamoto Nagasaki Kagoshima GPP per capita Labor productivity in the manufacturing sector (thousand yen) GPP per capita (thousand yen) From 1955 to 1970, the labor productivity gap across regions within the manufacturing sector slightly increased. 24

25 Labor productivity in the manufacturing sector , weighted CV of labor productivity in the manufacturing sector=0.25 (weight=number of workers in the manufacturing sector) Tokyo Aichi Osaka Shiga Shizuoka Toyama Tochigi Hiroshima Fukui Okayama Ishikawa Gumma Yamaguchi Mie Hyogo Kagawa Nagano Ibaraki Fukushima Kanagawa Niigata Kyoto Hokkaido Oita Ehime Fukuoka Yamanashi Tottori Miyagi Gifu Saga Akita Iwate Tokushima Wakayama Yamagata Chiba Shimane Kochi Aomori Miyazaki Nagasaki Kagoshima Kumamoto Saitama Nara Okinawa GPP per capita Labor productivity in the manufacturing sector (thousand yen) GPP per capita (thousand yen) But from 1970 to 1990, the labor productivity gap across regions within the manufacturing sector declined. 25

26 Labor productivity differences across prefectures declined, because (1) Manufacturing activities spread to middle-income regions during the period of (2) In contrast, within-manufacturing-sector differences in labor productivity across prefectures declined during the period of

27 Decomposition of Labor Productivity Differences between top 20% and bottom 20% of prefectures: ln(labor productivity of top 20%/bottom 20%) =differences of industrial structure +within-industry differences (1)contribution of TFP (2)contribution of capital-labor ratio (3)contribution of labor quality We use R-JIP database, which comprises, for the period , various types of annual data necessary for estimating total factor productivity (TFP) in 10 manufacturing and 13 non-manufacturing industries covering each prefecture s economy as a whole. 27

28 Factor decomposition of labor productivity differences Differences in labor productivity Differences in industrial structure Within-industry differences in labor productivity Contribution of T FP Contribution of capital labor ratio Contribution of labor quality Measurement error (100.0) (100.0) (100.0) (42.8) (26.3) (23.5) (57.2) (73.7) (76.5) (25.3) (45.2) (68.7) (23.2) (14.7) (2.3) (16.9) (22.7) (15.9) (-8.2) (-8.8) (-10.4) Fukao et al. (2015) Regional Inequality and Industrial Structure in Japan:

29 Labor productivity differences between the top and bottom 20 % declined, because (1) Industrial structures in the top and bottom prefectures became similar. (2) In contrast, within-industry differences in labor productivity across prefectures declined only marginally. (3) The decomposition of within-industry differences reveals opposite/offsetting movements of TFP and capital-labor ratio. 29

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