Scale Economies on Wireless Telecommunications Industry

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ARTICLE IN PRESS
Telecommunications Policy 33 (2009) 29–40

Contents lists available at ScienceDirect

Telecommunications Policy
URL: www.elsevierbusinessandmanagement.com/locate/telpol

Estimating scale economies of the wireless telecommunications industry using EVA data$ Changi Nam a, Youngsun Kwon a,Ã, Seongcheol Kim b, Hyeongjik Lee c a b c

School of IT Business, Information and Communications University, 119, Munjiro, Yuseong-gu, Daejon 305-732, Republic of Korea Associate Professor, School of Journalism and Mass Communication, Korea University, 5-1, Anam-dong, Seongbuk-gu, Seoul, 136-701, Republic of Korea Full-time instructor, Department of Management Science, Republic of Korea Naval Academy, 88-1 Angok-dong, Jinhae, Kyungnam, 645-797, Republic of Korea

a r t i c l e in fo

abstract
This paper proposes a new estimation method of total cost and average cost curves and applies it to the telecommunications industry. The method is more flexible and entails less hassle for data collection than traditional methods. The results show that the longrun average cost (LRAC) curve is downward sloping, revealing the presence of economies of scale in production. The two largest Korean mobile network operators are realizing full economies of scale, while the smallest operator is not. Finally, the paper recommends three policy alternatives that the Ministry of Information and Communication of Korea can draw on to increase efficiency in the Korean mobile telecommunications market. & 2008 Elsevier Ltd. All rights reserved.

Keywords: Scale economy estimation Economic value-added (EVA) Telecommunications Asymmetric regulation

1. Introduction Empirically estimating the long-run average cost (LRAC) curve and the minimum efficient scale (MES) of production has been an important research topic in the field of regulatory economics because data relating to both are critical for measuring production efficiency in industries, especially in public utility variants. One major problem in estimating the LRAC curve and the MES has been obtaining the appropriate data, especially data related to production factors other than capital and labor. Nowadays, firms are capitalizing more than ever before on the benefits of intangible assets, such as computer and management software, brand, and intellectual property rights.1 The traditional estimation method for the LRAC curve and the MES focusing on traditional production factors in manufacturing industries has been of decreasing validity and usefulness in the information age. According to Brynjolfsson and Hitt (2000, 2003), information and communication technology increases the productivity of firms by complementing organizational capital and streamlining business processes. Because of the increasing importance of intangible assets, researchers who pay attention only to traditional production factors are likely to omit a proportion of input cost items. Therefore, this paper develops a new method of estimating the LRAC curve, free from changes in the composition of production factors. The purpose of this paper is to propose a new model to estimate the LRAC curve of firms, and to apply it to Korean mobile network operators (MNOs). This paper estimates the LRAC curve of production using annual sales data, estimated economic value-added (EVA) data, and annual

$ This research was supported by the Ministry of Information and Communication (MIC), Republic of Korea, under the Information Technology Research Center (ITRC) support program supervised by the Institute of Information Technology Assessment (IITA) ‘‘(IITA-2006-C1090-0603-0041)’’ Ã Corresponding author. Quello Center, Michigan State University, MI, USA. Tel.: +1 517 803 0497; fax: +1 517432 8065. E-mail addresses: cgnam@icu.ac.kr (C. Nam), yskwon@icu.ac.kr (Y. Kwon), hiddentree@korea.ac.kr (S. Kim), chandler@navy.ac.kr (H. Lee). 1 Refer to Whitwell, Lukas, and Hill (2007) on the growing importance of intangible assets.

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