Guest Editors’ Introduction

• DOI: http://doi.org/10.1111/1468-0106.12237
• Author: Tsu‐Tan Fu,Cliff J. Huang
• Date: 01 October 2017
• Published date: 01 October 2017

GUEST EDITORS’INTRODUCTION

TSU-TAN FUSoochow University

CLIFF J. HUANG*Vanderbilt University

This Special Issue is a sequel to the Special Issue on economic growth, produc-

tivity and efficiency that was published in October 2016 (vol. 21:4). Both issues

emerged out of the call for papers following the Taipei Efficiency and Productiv-

ity Workshop held at the School of Business at Soochow University in Taiwan in

July 2015. In this issue, we assemble six papers on world productivity growth,

and some country-specific studies on efficiency: Taiwan’s local tax collection

and management; productivity in Japanese banking; productivity dynamics of

the Korean manufacturing sector; the Czech food processing industry; and dairy

farms in Quebec, Canada.

The multiple methods and models available to measure productivity growth

frequently makes it difficult for policy-makers to determine how to choose

among them. The lead paper by Duygun, Isaksson, Hao, and Sickles proposes

a model of averaging to construct a ‘consensus’productivity indicator. Using

the United Nations Industrial Development Organization (UNIDO) data over

the period between 1970 and 2000, the authors demonstrate how to develop a

consensus estimate of the world total factor productivity growth.

In the second paper, Huang, Yu, Huang, Wei, and Chen develop a network

data envelopment analysis with a Russell directional distance function to evalu-

ate operating efficiency in Taiwanese local tax offices in 2013. The novelty of this

study is that it treats local tax office operation as a network of the collection and

management stages. The approach thus enables the evaluation and the compar-

ison of tax offices in various regions over the different stages of operation.

In the third paper, Fukuyama and Weber develop a multi-period dynamic

network model for Japanese banks that explicitly accounts for weak input and

output disposability issues. More specifically, past nonperforming loans are un-

desirable inputs that reduce future production possibilities. The authors provide

details on how to incorporate weak disposability of undesirable inputs and out-

puts on the dynamic network technology. The dynamic network model is ap-

plied empirically to estimate the productivity for 100 Japanese banks during

the period 2007–2012.

The fourth paper by Lee, Lee, and Baek critically examines the productivity

dynamics and the so-called ‘cleansing effect’(i.e. an improvement in productiv-

ity by means of resource reallocation from less productive firms that exit the in-

dustry to more productive firms that remain in the industry) during the 1990s

and 2000s recession periods in Korea. The authors adopt two existing methods:

*Address for Correspondence:Cliff J. Huang, 405 Woodward Blvd, Pasadena, California 91107, USA.

E-mail: cliff.huang@vanderbilt.edu

Pacific Economic Review, 22: 4 (2017) pp. 585–586

doi: 10.1111/1468-0106.12237

© 2017 John Wiley & Sons Australia, Ltd

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