A generalized Okun's Law: Uncovering the myth of China's labor market resilience

• Author: Raphael Lam,Guangjun Shen,Xiaoguang Liu,Alfred Schipke
• DOI: http://doi.org/10.1111/rode.12379
• Date: 01 August 2018
• Published date: 01 August 2018

REGULAR ARTICLE

A generalized Okun’s Law: Uncovering the myth of

China’s labor market resilience

Xiaoguang Liu

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Raphael Lam

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Alfred Schipke

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Guangjun Shen

4

1

Renmin University of China, Beijing,

China

2

International Monetary Fund,

Washington, D.C

3

Harvard University, Cambridge,

Massachusetts

4

Central University of Finance and

Economics, Beijing, China

Correspondence

Guangjun Shen, School of Economics,

Central University of Finance and

Economics, Haidian District, Beijing,

China 102202.

Email: hnshgj@126.com

Funding information

The National Social Science Foundation,

Grant/Award Number: 16CJL049; Natural

Science Fund of China, Grant/Award

Number: 71603296

Abstract

A stable labor market is a policy priority for most coun-

tries, especially after the burst of the global financial crisis.

Unlike most countries, the labor market in China appears

to be holding up well, despite sharp slowdown in economic

growth. This paper argues that there are underlying funda-

mental mechanisms that help explain the resilience of Chi-

na’s labor market. The key to understanding labor market

dynamics in China is that rural-to-urban migrant flows are

more sensitive to growth than urban workers in the process

of fast urbanization, which serves as a main shock absorber

to buffer employment against adverse shocks. Therefore,

we propose a generalized Okun’s Law (GOL) that incorpo-

rates migrant flows with unemployment rates to capture the

relation between labor market dynamics and economic

cycles. The original Okun’s Law can be regarded as a spe-

cial case of the GOL for developed countries that have

already completed urbanization. Conducting empirical

analysis with both China’s national- and city-level data and

cross-country panel data, we find strong evidence support-

ing the GOL theory. Findings in the paper have implica-

tions for a deeper understanding of the wisdom of Okun’s

Law and its application in labor market policies.

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INTRODUCTION

A stable labor market is a policy priority for most countries, especially after the burst of the

global financial crisis. Unlike most countries, labor market conditions appear to be holding up

well in China, even as economic growth has been slowing down for years from 14.7 percent in

DOI: 10.1111/rode.12379

Rev Dev Econ. 2018;22:1195–1216. wileyonlinelibrary.com/journal/rode ©2018 John Wiley & Sons Ltd

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2007 to 6.9 percent in 2015. The registered unemployment rate remains stable at about 4 per-

cent. It seems that the responsiveness of unemployment to economic growth in China is extre-

mely weak.

Most literature attributes it to the data shortcomings of the official registered unemployment rate

in China that does not well reflect the real condition of the labor market (Cai, Du, & Wang,

2013). However, this argument turns out to be incomplete as the surveyed unemployment rate, a

newly released indicator that has not been available until 2011, does not show a significant rise in

unemployment, either. The surveyed unemployment rate is stable at about 5 percent, just slightly

higher than the registered unemployment rate. Besides, complementary indicators also sugges t that

the labor market in China remain resilient despite a much slower growth. For example, newly cre-

ated urban jobs have exceeded official targets by a significant margin, and average wages have

grown in line with nominal GDP as well. In a nutshell, the labor market remains resilient overall

and Okun’s Law, which describes a negative relation between GDP growth and unemployment,

does not work well in China.

Beyond data shortcomings, the key to understanding labor market dynamics in China is that

rural-to-urban migrant flows are more sensitive to growth than urban local workers, partly because

of the household registration (hukou) system (Meng, 2012). It serves as a shock absorber during

economic downturns, contributing to labor market stability in the short term. The number of

migrant workers is about 270 million, which is a third of the total labor force and half of urban

employment. These migrant flows are closely related to GDP growth and reflect short-term dynam-

ics in labor markets more sensitively than do unemployment rates. As illustrated in Figure 1, vari-

ous measurements of unemployment rates appear to be muted during economic cycles (left panel),

while growth in migrant flows tends to track GDP growth much more closely (right panel), acting

as a shock absorber against a rise in unemployment.

Although there are different versions of Okun’s Law (Knotek, 2007), rural-to-urban labor

migration has never been included in the relationship, mainly because the migration process along

with urbanization has almost completed in developed countries and hence rural-to-urban migrant

flows are no longer significant. However, the rural–urban migration shapes our understanding of

how China’s labor market reacts to output shocks. As illustrated above, the “unique ”feature in

China’s labor market—rural-to-urban migrant flows—buffer against adverse shocks and support

labor market resilience during the growth slowdown after 2008.

In this paper, we argue that migrant flows are the key to understanding China’s resilient labor

market conditions in the process of urbanization and industry transformation. Therefore, we

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1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Official registered urban unemployment rate

Estimates based on Xue and Zhong (2003) 2/

Estimates based on population census and one-percent household survey

Official surveyed unemployment rate based on 31 cities

Estimates based on Urban Labor Survey data

Official and Estimates of Urban Unemployment Rates

(in percent)

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Migrant flows (y/y growth)

GDP Growth and Migrant Flows

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FIGURE 1 Labor market developments in China [Color figure can be viewed at wileyonlinelibrary.com]

Source: Xue and Zhong (2003); National Bureau of Statistics, Urban Labor Survey: online database.

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