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How to measure company productivity using value-added: A focus on Pohang Steel (POSCO)

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Abstract

How should the performance of a manufacturing company be assessed, relative to firms making similar products, at home and abroad? This paper shows how company-level productivity measures can be developed from public financial data to provide a more comprehensive gauge of firm performance than profit rates alone. As a specific example, we focus on the Korean steelmaker, POSCO. Founded four decades ago, POSCO is commonly regarded as the world’s most efficient and profitable integrated steel producer, and our analysis documents POSCO’s superior record of profitability and labor productivity. We find, however, that a broader assessment of POSCO’s performance is tempered by the firm’s high capital intensity relative to producers in Japan and the United States.

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Notes

  1. Usinor of France, Arbed of Luzembourg, and Aceralia of Spain merged to form Arcelor, and in 2006 Arcelor was acquired by Mittal Steel, becoming the largest steelmaker in the world as Arcelor-Mittal. Two major Japanese producers, Kawasaki Steel and NKK Corporation, merged in 2003 to become JFE Steel. As of December 2006, POSCO is ranked as the third largest steelmaker after Arcelor-Mittal and Nippon Steel.

  2. World Bank report, quoted in Amsden (1989: 291).

  3. POSCO was a major project in the Heavy and Chemical Industry (HCI) Plan, launched in 1972 as a part of five-step national economic planning. The HCI Plan focused on the “strategic industries” of iron and steel, machinery, non-ferrous metals, electronics, shipbuilding, and petrochemicals. The objective of this policy was to help overcome Korea’s limits of being a small domestic market, and emphasize construction of large-sized facilities to achieve economies of scale (Rhee, 1994).

  4. Additional details on productivity measurement are provided in various sources including Coelli, Rao and Battese (1998), Lieberman, Lau and Williams (1990), Mammone (1980), and publications of the American Productivity Center.

  5. The data on value-added, capital investment, and total number of employees are from POSCO annual reports (1968–2006). Data on working hours are from POSCO’s internal reports and authors’ estimates. For most companies, working hours are not reported, although estimates can be developed from government data.

  6. Equivalently, value-added can be computed by subtracting the costs of purchased materials, services and utilities from the firm’s total revenue. However, complete information on these items is seldom provided in company financial reports, so the summation approach is preferable.

  7. This price deflator was calculated by dividing POSCO’s sales by its tons shipped, using data from annual reports data. Alternatively, a more general price deflator for the steel industry could be used. Such price deflators are commonly published by government sources and thus are available for most industries. For firms that are significantly diversified, a weighted average of industry price deflators is required.

  8. For a more detailed explanation of this method, see Hulten and Wykoff (1981) and Lieberman et al. (1990).

  9. We considered 10% reasonable given the composition of the gross capital stock and the rates of economic depreciation estimated by Hulten and Wykoff (1981).

  10. We used the following standard formula to compute multi-factor productivity:

    $${\text{Change}}\;{\text{in}}\;{\text{MFP}}\;{\text{from}}\;{\text{year}}\;t\;{\text{to}}\;{\text{year}}\;t + 1 = {\left[ {\ln \;Q_{{t + 1}} - \ln \;Q_{t} } \right]} - {\left( {1 - s_{t} } \right)}{\left[ {\ln \;K_{{t + 1}} - \ln \,K_{t} } \right]} - s_{t} {\left[ {\ln L_{{t + 1}} - \ln L_{t} } \right]}$$

    where Q t is the firm’s value-added in year t, K t is the capital stock, L t is labor input, s t is the fraction of value added which is paid to employees, (1 − s t ) is the fraction which goes implicitly as a payment to capital, and “ln” refers to logarithms. We set MFP for each year relative to a base index of 100 for POSCO in 1975. Ideally, materials and energy inputs should also be included in the MFP calculations, but sufficient information is not normally available in company annual financial reports. To perform inter-firm comparisons, we established each firm’s MFP relative to Nippon Steel in the year 1980 by substituting the comparison firm values for the t-subscripted variables, and values for Nippon Steel for the t − 1 subscripted variables. Labor’s share, s t, was taken as the average of the shares for Nippon and the comparison firm in 1980.

  11. The data and computations are described in Lieberman and Johnson (1999).

  12. These calculations are sensitive to the weights assigned to capital and labor input in the MFP formula, which are conventionally based on income shares. In the calculations underlying Figure 3, POSCO’s weights for labor input are lower than corresponding values for the US and Japanese producers, given that POSCO’s wages have been lower. POSCO’s proportion of value-added paid to labor ranged from 10 to 27% over the sample period, while the implicit proportion paid for capital services ranged from 73 to 90%. If the US or Japanese weights are used for POSCO, the firm’s MFP appears higher.

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Authors and Affiliations

  1. UCLA Anderson School of Management, Los Angeles, CA, 90095-1481, USA

    Marvin B. Lieberman

  2. Seoul National University, Seoul, 151-742, South Korea

    Jina Kang

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  1. Marvin B. Lieberman
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  2. Jina Kang
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Correspondence to Marvin B. Lieberman.

Additional information

We thank Mike Peng and an anonymous referee for helpful suggestions and comments. This study received support from the UCLA Center for International Business Education and Research, and from the steel project, “Competitiveness in the Global Steel Industry,” funded by the Alfred P. Sloan Foundation and the American Iron and Steel Institute.

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Lieberman, M.B., Kang, J. How to measure company productivity using value-added: A focus on Pohang Steel (POSCO). Asia Pacific J Manage 25, 209–224 (2008). https://doi.org/10.1007/s10490-007-9081-0

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