Reallocation of Production Factors in the Regional Economies in Japan : Towards an Application to the Great East-Japan Earthquake

Examining the recovery processes of the Great East-Japan Earthquake and the Hanshin-Awaji Earthquake, we find that the reallocation mechanism affects economic growth of the recovery period in the devastated regions. Using the R-JIP databas, which provides value added and production factors at the prefectural and industry levels, we break down labor productivity growth into the capital deepening effect, a few reallocation effects, and the pure technological effect. We do not find an efficient movement of labor in the 2000s, although capital has moved within a prefecture efficiently. When we focus on Hyogo prefecture where the Hanshin-Awaji Earthquake occurred in 1995, we find that the decline in reallocation effects slowed labor productivity growth after the earthquake.Article学習院大学経済経営研究所年報.28:103-120(2014)departmental bulletin pape

Embodied Technological Progress and the Productivity Slowdown in Japan

Concerns over the rise in the vintage of capital in the Japanese economy have focused attention on the technological progress embodied in capital. In this paper, we derive the theoretical relationship between the rate of technological progress embodied in capital, the obsolescence rate of capital, and the average vintage of capital, then we estimate these rates by using firm-level panel data from the Ministry of Economy, Trade and Industry (METI) Basic Survey of Japanese Business Structure and Activities in the period between 1997 and 2002. To measure the obsolescence rate of capital by estimating the production function, it is necessary to construct a capital stock series that takes only physical depreciation into account for each vintage capital held by each firm. To do that, we prepared industry-specific patterns of the physical depreciation ratio of capital goods, based on the pattern of the physical depreciation ratio of each type of capital goods by obtaining information from the U.S. Bureau of Labor Statistics (BLS), and the Japan Industrial Productivity Database (JIP) 2006's investment matrices cross-classified by types of capital goods and industries. We applied these industry-specific patterns of the physical depreciation ratio of capital goods to the individual firms' investment series, constructing a capital stock series in each firm. We measured the obsolescence rate by estimating the production function, which is similar to the one employed in Sakellaris and Wilson (2004). We added several control variables to their equations. The estimated obsolescence rate of machinery and equipment is found to be between 8 and 22 percent per annum, which is very close to the estimated ratios in other previous research using the production function. This estimation result implies that the average rate of technological progress embodied in machinery and equipment is between 0.2 and 0.4 percent in Japan. The average vintage of capital in the manufacturing industry in the 1990s was estimated to increase by almost two years, because of weak investment during that decade, and it has the effect of lowering the rate of productivity growth in the industry by 0.4 to 0.8 percentage points.

Productivity Disparities Between Self-Employed Workers and Employees (Japanese)

This paper measures the productivity disparities between self-employed workers (i.e. business owners and unpaid family workers) and employees by estimating a production function based on enterprise-level micro data from the Census of Manufactures between 1981 and 2000. As a result, we find that, compared with male employees, 1) the productivity of male self-employed workers is significantly higher, and 2) no significant disparities in productivity are found with that of female self-employed workers. Using these results, we re-estimate the labor input indices and the labor quality indices for the manufacturing industries of the 2006 JIP database. As a result of this re-estimation, the annual growth rate of the labor quality index for the whole manufacturing industry between 1970 and 2002 becomes smaller than that of the 2006 JIP estimates by 0.43 percentage points. If we apply the productivity disparities among various types of employees estimated by Kawaguchi, et al. (2007) rather than using wages as productivity indices, the annual growth rate of the labor quality index is further reduced by 0.10 percentage points. Combining both results we get an annual 0.53 percentage points decline of the growth rate of the labor quality index, and the labor input index. This suggests that the annual growth rate of TFP in this period is underestimated by approximately by 0.4 percentage points.

Estimation Procedures and TFP Analysis of the JIP Database 2006 Provisional Version

(Introduction) The purpose of this paper is to explain the preliminary version of the newly compiled Japan Industrial Productivity Database (JIP 2006) and report some results of our growth accounting analysis based on this database. The JIP 2006 contains information on 108 sectors from 1970 to 2002 that can be used for total factor productivity analyses. These sectors cover the whole Japanese economy. The JIP Database was compiled as part of the RIETI (Research Institute of Economy, Trade and Industry) research project "Study on Industry-Level and Firm-Level Productivity in Japan." The original version of the JIP Database (ESRI/Hi-Stat JIP Database 2003) was compiled in a collaboration between ESRI (Economic and Social Research Institute, Cabinet Office, Government of Japan) as part of its research project on "Japan's Potential Growth" and Hitotsubashi University as part of its Hi-Stat project (A 21st-Century COE Program, Research Unit for Statistical Analysis in the Social Sciences). The authors are grateful to ESRI and members of the Hi-Stat team for the support and cooperation provided for our present RIETI project. At this moment, the major data available are sectoral capital service input indices and labor service input indices, including information on real capital stocks and the nominal cost of capital by type of capital and by industry, the nominal and real values of sectoral gross output and intermediate input, as well as some supplementary tables, such as statistics on trade, inward and outward FDI, and Japan's industrial structure. All real values are based on 1995 prices. For growth accounting, nominal labor costs and nominal capital services for 108 industries are also estimated. The sum of these two values for each industry is not adjusted to be equal to the value added of that industry at factor cost base. The final version of the JIP 2006 is scheduled to be released by November, 2006. The final version will include nominal and real annual input-output tables, detailed information on ICT capital services and some additional statistics, such as R&D stocks and capacity utilization rates at the detailed sectoral level. For scholars familiar with the JIP 2003, we here briefly summarize the main differences between and the main similarities of the 2006 and 2003 versions of the JIP. 1. The JIP 2003 is based on the 1968 SNA, while the JIP 2006 is based on the 1993 SNA. The capital stock of the JIP 2006 includes order-made software, plant engineering, and assets accumulated by the search for minerals. The JIP 2003 uses SNA statistics as control totals. Following Japan's present SNA statistics, capital stock in the preliminary version of the JIP 2006 does not include prepackaged and in-house software. However, the final version of the JIP 2006 will include two sets of statistics, one in which capital stock does not include prepackaged and in-house software and one in which it does. 2. In the case of the JIP 2006, labor input data include detailed information on labor input cross-classified by categories of labor. The paper is organized as follows: In the next section, we report the estimation procedures of our annual input-output tables. In Sections 2 and 3, we explain the capital service input data and the labor input data of the JIP 2006, respectively. Finally, in Section 4, we analyze Japan's sectoral and macro TFP growth.

The Economic Impact of Supply Chain Disruptions from the Great East Japan Earthquake

The Great East Japan Earthquake of March 11, 2011 had a serious negative economic impact on the Japanese economy. The earthquake substantially reduced production not only in regions directly hit by the earthquake but also in other parts of Japan through supply chain disruptions. We examine the economic impact of the supply chain disruptions immediately following the earthquake using regional input-output (IO) tables, the Japan Industrial Productivity (JIP) database, and other regional statistics. To conduct our analysis, we modify the forward linkage methodology to take into account the first-stage bottleneck effect in the intermediate input of manufacturing production. We also create our own interregional input-output table by combining two different regional IO tables. Our estimates show that the production loss caused by the supply chain disruptions would be a maximum of 0.41% of the country's gross domestic product (GDP). We also analyzed the possible damage mitigating effects of establishing multiple supply chains to cope with potential natural disasters in the future. However, as multiple supply chains may lose production efficiency at the firm level, we need some policies that give incentives to firms which diversify supply chains.ArticleRIETI Discussion Paper Series. : 15-E-094(2015)technical repor

Regional Factor Inputs and Convergence in Japan: A macro-level analysis, 1955-2008

Using the Regional-Level Japan Industrial Productivity (R-JIP) Database, which provides data on aggregate industry value added and production factor inputs by prefecture for 1955-2008, we examined the reasons for the decline in prefectural economic inequality from the supply side. In addition, we focused on the role of capital accumulation and changes in total factor productivity (TFP) in economic convergence. We examined how the relatively rapid capital accumulation in low-income prefectures was financed and what brought about the decline in differences in TFP. The main findings of the analysis are as follows.1) In 1955, the most important reason for prefectural labor productivity differences was differences in TFP, followed by differences in capital-labor ratios and then by differences in labor quality. Differences in capital-labor ratios and TFP declined substantially between 1955 and 2008, leading to a dramatic reduction in prefectural labor productivity differences. On the other hand, depending on the period, prefectural differences in labor quality either did not contribute to the contraction in labor productivity differences or in fact worked in the direction of increasing such differences. 2) During the high-speed growth era from 1955-1970, the main factor underlying the decline in prefectural labor productivity differences was the decline in TFP differences. On the other hand, from 1970 onward, Japan experienced a strong decline in regional differences in inputs, so that the contribution of variation in inputs to variation in output steadily dropped after 1970. 3) Migration from poorer to richer prefectures and the decline in prefectural TFP differences from 1955 to 2008 consistently contributed to the decline in per capita gross prefectural product (GPP) differences, although the contribution of the decline in prefectural TFP differences to β-convergence—for the period as a whole—was more than twice as large as the contribution of migration. On the other hand, capital accumulation actually worked in the direction of increasing prefectural inequality in the period 1955-1970, but from 1970 onward, it consistently operated in the direction of reducing inequality. 4) The accumulation of social capital, measured in relation to working hours, in post-war Japan, was concentrated in prefectures with lower per capita GPP. Given that the accumulation of social capital likely raises the efficiency of economic activity and hence has a positive effect on TFP, the emphasis on improving social infrastructure in poorer rural areas very likely contributed to the decline in prefectural TFP differences. Meanwhile, the expansion of firms with high labor productivity into rural areas and technology transfers to technologically lagging prefectures through intra-firm technology diffusion, as well as the growing agglomeration of industry in rural areas through the expansion of manufacturing in rural areas, also likely contributed greatly to the decrease in prefectural TFP differences.ArticleRIETI Discussion Paper Series. : 15-E-123(2015)technical repor

Embodied Technological Progress and the Productivity Slowdown in Japan

Concerns over the rise in the vintage of capital in the Japanese economy have focused attention on the technological progress embodied in capital. In this paper, we derive the theoretical relationship between the rate of technological progress embodied in capital, the obsolescence rate of capital, and the average vintage of capital, then we estimate these rates by using firm-level panel data from the Ministry of Economy, Trade and Industry (METI) Basic Survey of Japanese Business Structure and Activities in the period between 1997 and 2002.To measure the obsolescence rate of capital by estimating the production function, it is necessary to construct a capital stock series that takes only physical depreciation into account for each vintage capital held by each firm. To do that, we prepared industry-specific patterns of the physical depreciation ratio of capital goods, based on the pattern of the physical depreciation ratio of each type of capital goods by obtaining information from the U.S. Bureau of Labor Statistics (BLS), and the Japan Industrial Productivity Database (JIP) 2006’s investment matrices cross-classified by types of capital goods and industries. We applied these industry-specific patterns of the physical depreciation ratio of capital goods to the individual firms’ investment series, constructing a capital stock series in each firm.We measured the obsolescence rate by estimating the production function, which is similar to the one employed in Sakellaris and Wilson (2004). We added several control variables to their equations. The estimated obsolescence rate of machinery and equipment is found to be between 8 and 22 percent per annum, which is very close to the estimated ratios in other previous research using the production function. This estimation result implies that the average rate of technological progress embodied in machinery and equipment is between 0.2 and 0.4 percent in Japan. The average vintage of capital in the manufacturing industry in the 1990s was estimated to increase by almost two years, because of weak investment during that decade, and it has the effect of lowering the rate of productivity growth in the industry by 0.4 to 0.8 percentage points.ArticleRIETI Discussion Paper Series. : 08-E-017(2008)technical repor