Compliance with Legal Minimum Wages in China: 2007-2013 2016

I

Working Paper: CIIDWP No.50

Compliance with Legal Minimum

Wages in China: 2007-2013

Authors: Ye, Linxiang; Li, Shi; Tim Gindling

2016

北京师范大学中国收入分配研究院

The China Institute for Income Distribution

II

Working Paper: CIIDWP No.50

Compliance with Legal Minimum Wages in China:

2007-2013

Ye, Linxiang

(School of Economics, Nanjing University of Finance & Economics)

Li, Shi

(IZA and Business School, Beijing Normal University)

Tim Gindling

(IZA and Department of Economics, UMBC)

Version: 2016/7/2

III

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0

Compliance with Legal Minimum Wages in China: 2007-2013

Linxiang Ye (Department of Economics, Nanjing University of Finance and

Economics, No. 3 Wenyuan Road, Yadong New Area, Nanjing China;

[email protected]),

Shi Li (IZA and School of Economics and Business Administration, Rear Main

Building 1618, Beijing Normal University, Outer St. 19, Xin Jiekou, Beijing, China;

[email protected]) , and

T. H. Gindling (IZA and Department of Economics, UMBC, 1000 Hilltop Circle,

Baltimore, MD, USA; [email protected])

1

Compliance with minimum wages in China: 2007-2013

1 Introduction

Developing countries are notorious for poor labour market conditions (Ronconi,

2010). Although most developing countries have extensive labour regulations,

compliance is generally low (Maloney and Mendez, 2004; Ronconi, 2010; Strobl and

Walsh, 2003). There is a growing theoretical and empirical literature on the problem

of non-compliance with minimum wage laws in developing countries (Andalon and

Pages, 2008; Basu et al., 2010). There is also quite a few papers about compliance

with minimum wages in China, for example, Fang and Lin (2013),Yang and

Gunderson (2014),Ma and Li (2014), Xie (2010),Sun and Shu (2011),Du and Wang

(2008) ,Ye et al.(2015).Almost all of them used the data surveyed at or before year

2009.But from year 2010, almost all provincial governments greatly increase

minimum wages. Different from year 1995 to year 2010,minimum wage increases

tend to be higher than increases in average wages after year 2010.So the minimum

wage/average wage ratio has been increasing gradually from year 2010.Are there any

new changes about compliance with minimum wages?

In the empirical literature, a standard way of measuring non-compliance is as the

fraction of all covered workers whose wages are below the minimum. However, this

measure does not distinguish between different degrees of violation. For example, a

wage just below the minimum is counted the same as a wage at one third of the

minimum, surely an inexact way to measure a violation of regulation.

In this paper we present a family of violation indices that, by analogy with poverty

indices, can emphasize the depth of violation to different degrees. We used CHIPs

2007 and 2013 to examine the extent to which minimum wages are complied with in

China. And make a comparison with them.

We found that 3.62 per cent of employees in year 2007 and 7.34 per cent of employees

in year 2013 were receiving sub-minimum wages. Overall, there are more workers

whose wage below minimum wage in year 2013 than year 2007.When using the

relative violation indicators, we found that violated workers earned 26.12 per cent of

the minimum in year 2007 and 43.77 per cent of the minimum in year 2013.Violated

workers got higher wages in year 2013, compared to year 2007.They became better. It

is interesting. The results imply that both the level and the depth of violation are

important when quantifying violation. Workers worse off in terms of the absolute

violation measure may not necessarily be equally worse off in relative terms and vice

versa. It suggests that both an absolute and a relative measure of violation matter when

examining minimum wage compliance.

In comparing wages to minimum wages, the regulations make it clear the wage should

exclude overtime pay. When we consider weekly working hours, the proportion of

2

violated workers increased a lot.13.95 per cent of employees in year 2007 and 12.95

per cent of employees in year 2013 were receiving sub-minimum wages. What is

interesting is that the proportion of violated workers almost did change or even

decreased from year 2007 to year 2013 when considering working hours. This is

because working hours of low-skill workers decreased a lot from year 2007 to year

2013.

2 Legal minimum wages and overtime pay regulations in China

Prior to 1994, China had no minimum wage regulations. In 1993, the first regulations

on minimum wages were issued by the Labor Ministry of China (the “Enterprise

Minimum Wage Regulations”). In July 1994, a minimum wage was written into

China’s new version of the Labor Law. Clause 48 of that law states that all types of

enterprises in China should comply with paying local minimum wages.

In 2004, the Enterprises Minimum Wage Regulations were replaced by more general

Minimum Wages Regulations issued by the Department of Labor and Social Security.

In these regulations the adjustment frequency of minimum wages was set to be more

than once every two years and coverage was extended to town-village enterprises, to

employees in micro-enterprises, and to part-time workers. Penalties for violations

were increased substantially from an earlier range of 20-100 per cent of the wage that

was owed to a new range of 100-500 per cent of the wage that was owed. Restrictions

were also placed on what employers could include as part of the wage when

comparing to the minimum wage (Wang and Gunderson, 2012). In determining if

the wage is above the legal minimum, employers must not include overtime pay and

legally-mandated supplements to the wage such as those for night shifts and

dangerous environmental conditions such as high temperature, low temperature,

underground working conditions and working in poisonous or noxious conditions.

There is no unified minimum wage level for the entire nation. Instead, the task of

setting minimum wages is delegated to the local governments. Clause 48 of the 1994

labor law requires that local governments set the minimum wage according to five

principles: local minimum living expenses; the average wage level; local productivity;

unemployment; and local economic development. In practice, each province-level

government determines several possible minimum wage levels that could be adopted

by local governments, generally three to five levels, according to local economic

conditions and living standards. Then each prefectural city-level government within

the province-level administrative area chooses the appropriate minimum wage levels

from this published list, also based on local economic conditions and living standards.

The law provides considerable flexibility for provinces and prefectural cities in setting

their minimum wages. Typically, urban and suburban counties within a prefectural

city have different minimum wage levels. Consequently, not only each

province-level administrative area, but also each prefectural city-level administrative

area, may have multiple county-level minimum wages.

The monthly minimum wage is based on a 40 hour work week. According to labor

regulations passed in 1994, laborers shall work no more than eight hours per day, five

3

days per week. After consultation with trade unions and workers, a firm can extend

the work day. If workers work more than the legal maximum of 40 hours per week,

they must be paid at least 150% the wage they receive for regular hours, at least 200%

of the regular wage if the overtime is on a “day of rest” (weekend), and at least 300%

the regular wage if the overtime is on a statutory holiday. Fines for violating overtime

pay regulations include back pay plus an additional 50 to 100 percent of the wage

owed.

The monthly minimum wage does not apply to part-time workers. Instead, in 2004

the government mandated a separate hourly minimum wage for part-time workers.

Because employers are not required to pay some non-wage benefits for part-time

workers, the part-time hourly minimum wage is set above the monthly minimum

wage for full-time workers (or, more specifically, the monthly minimum wage divided

by the number of hours worked per month by a full-time worker). For this reason, it

is not appropriate to compare the hourly wage of full-time workers to the hourly legal

minimum wage for part-time workers when examining compliance.

In order to measure minimum wages at national level, for years with minimum wages

adjustment, we first calculate average minimum wages in each province according to

minimum wages applied in different regions in that province. And then for years

without minimum wages adjustment, we simply use average minimum wages in the

last adjustment; for years with multiple minimum wages adjustment, we calculate

weighted average minimum wages with the weight being the actual days of

implementation of each minimum wages. At last, we can calculate average minimum

wages at the national level. Figure 1 gives a demonstration of basic trend of minimum

wages in China from 1995 to 2015. We can see from Figure 1 that minimum wages

have been increasing since 1995. In January 2004,China promulgated the new

minimum wages regulations, leading to frequent and substantial increases in

minimum wages in the subsequent years. For example, the average increasing rate

from year 1995 to year 2005 was 6.24%,However,the average increasing rate from

year 2005 to year 2015 increased to 11.34%.Figure 2 gives a demonstration of the

number of provinces which adjusted minimum wages in each year. We can see from

Figure 2 there is an apparent shift in the number of provinces that raised the minimum

wage standards in 2004,indicating that the minimum wage adjustment had become

more frequent since that year. We can also find that there is no provinces which

adjusted minimum wage in year 2009.The reason is that at the end of 2008,

Department of Human Resources and Social Securities instructed local governments

to restrain from increasing minimum wages in 2009 as a way to ease the negative

influence of international financial crisis. However, as the influence of financial crisis

faded out, there was a new round of minimum wages increase since 2010. In 2010, 30

of the 31 provinces increased minimum wages and the average increase was around

20%.

In order to examine the relative level of minimum wages in China, Figure 3 gives the

increasing rate of average wage and minimum wage from year 1995 to year 2014.We

can know from figure 3 that minimum wage increases tend to be lower than increases

4

in average wages from year 1995 to year 2010,but minimum wage increases tend to

be higher than increases in average wages after year 2010.Figure 4 gives minimum

wage/average wage ratio in China from year 1995 to year 2014.We can know from

figure 4 that the minimum wage/average wage ratio has been decreasing gradually

from year 1995 until year 2010,then it began to increase. Overall, the minimum wage

in China is low compared to average wages. As of 2009, this ratio in OECD countries

was well above 35% while in China this ratio was only a little more than 20%.

Figure 1 Minimum wage in China:1995-2015

Figure 2 The number of provinces which adjusted minimum wages

year=2005

6.14%

6.24%

6.52%

15.58%

11.34%

12.56%

380

252.5

125

2030

1000

1515

690

462.5

235

0

500

100

01

50

02

00

0w

ag

e

1995 2000 2005 2010 2015year

max(minmum) min(minmum) mean(minmum)

minimum wage in china:1995-2015

year=2005

01

02

03

0

num

ber

1995 2000 2005 2010 2015year

Number of Provinces Which Adjusted Minmum Wage

5

Figure 3 The increasing rate of minimum wage and average wage

Figure 4 Minimum wage as a percentage of average wage

0

.05

.1.1

5.2

rate

1995 2000 2005 2010 2014year

The Increasing Rate of Minimum Wage Standard

The Increasing Rate of Average Wage

year=2010

.2.2

5.3

.35

.4

rate

1995 2000 2005 2010 2014year

Minimum wage as a percentage of average wage

6

3 Literature review

There have been relatively few empirical studies examining evidence of

non-compliance with minimum wage and overtime pay regulations among a wide

range of Chinese firms. As noted in the last section, because of the complex nature

of minimum wages in China, and confusion about what should or should not be

included as “earnings” when comparing earnings to minimum wages, this is not a

trivial task. Fang and Lin (2013), using the annual Urban Household Survey from

2002 to 2009, find that the proportion of civilian employees (excluding self-employed

and students) whose total monthly wage is below the minimum wage is 5.6%.

Yang and Gunderson (2014), using a survey of internal migrants from 2011 and 2012,

estimate that approximately 5% of migrants earn at or below the monthly minimum

wage, Ma and Li (2014),using household survey data for 1995, 2002 and 2007, find

that less than 5% of workers earn less than the monthly minimum wage in any year.

While these nationally-representative empirical studies suggest broad compliance

with minimum wage laws in China, there are several studies that present anecdotal

evidence that compliance with minimum wages in China is far from complete (i.e.

Rowski, 2006; Li, 2007). Other studies present empirical evidence of possible

non-compliance when hours of work are taken into account, but only for a sub-set of

Chinese workers and firms. For example, Xie (2010) surveys 485 rural migrants in

three cities in Jiangsu province in 2009, finding that the proportion of workers whose

total monthly wage is below the monthly minimum wage is 3.9%. However, he also

notes that many rural migrants work more than the legally-mandated 40 hours per

week. To take into account overtime hours, Xie (2010) calculates an hourly wage

and compares that to an implicit hourly minimum wage based on the monthly

minimum wage divided by the number of hours worked by a full-time worker in a

month, finding that over 25% of workers in his sample earn less than the hourly

minimum wage when overtime hours are taken into account. When he also takes

into account that overtime hours should be paid 1.5 times the regular minimum wage

(and 2.0 times the regular minimum wage for weekend hours), the percent who earn

less than the minimum wage increases to over 60%.

Sun and Shu (2011) study rural migrants in 9 cities in Guangdong province in 2006,

2008, 2009 and 2010. They find that the proportion of workers whose monthly wage

is less than the monthly minimum wage is 9.0%, 7.7%, 4.0% and 4.2%, respectively,

in these four years. However, when they take into account overtime hours they find

that the proportion of workers whose hourly wage is below the implicit hourly

minimum wage for full-time workers was 45.3%, 33.3%, 28.1% and 23.8%. Du and

Wang (2008) use data from five capital cities in Shanghai, Wuhan, Shenyang, Fuzhou

and Xian in 2001 and 2005 and find that the monthly wage is below the monthly

minimum wage for 11.2% of workers, but that the hourly wage was below the implicit

hourly minimum wage for full-time workers for 52.2% of workers.

7

4 Data and descriptive analysis

The 2007 CHIP survey includes three parts: the urban household survey, the rural

household survey, and the rural-to-urban migrant household survey. The urban survey

covered 5,000 households containing 14,683 individuals selected from 18 cities in

nine provinces, whereas the rural survey covered 8,000 households containing 31,791

individuals selected from 69 counties in nine provinces. The migrant survey covered

nearly 5,000 households containing 8,446 individuals selected from 18 cities in nine

provinces.

Minimum wage is the lowest remuneration of labor pays by the employer if the

workers provide normal work in the working hours or in the hours which is agreed by

the legal labor contract. Minimum wage standard including monthly minimum wage

standard applied to full-time workers and hourly minimum wage standard applied to

part-time workers in China. As we just examine the compliance with minimum wage

in China, so we need to constrain our data. First, the sample of rural area was dropped

as area of countryside is not covered by minimum wage policy. Secondly, we just

keep employee. That is to say, unemployed population was excluded. The sample of

family worker, self-employed, temporary job are also dropped. Thirdly, according to

the definition of labor, we only keep the employee whose age is between 16 to 60.As

our data is mainly about full-time workers, so we only keep part-time workers. After

cleaning the data,6,008 urban individuals and 4,907 migrant individuals in migrant

left.

Similar with the 2007 CHIP survey, the 2013 CHIP survey also includes three parts :

the urban household survey, the rural household survey, and the rural-to-urban

migrant household survey. The urban survey covered 6,674 households containing

19,887 individuals selected from 126 cities in fourteen provinces, whereas the rural

survey covered 10,490 households containing 39,065 individuals selected from 123

counties in fourteen provinces. The migrant survey covered 726 households

containing 2,210 individuals selected from 87 cities in fourteen provinces.

For stratified samples such as CHIP, where the numbers of urban versus rural

respondents and of respondents in different regions and provinces are not proportional

to the populations in these different locations. Such is the case for CHIP, using

weights to adjust the sample to achieve overall representativeness may be needed

when the sample sizes of the strata and sampled groups are not proportional to their

population shares. Historically the CHIP survey sample was stratified on two

geographic dimensions, rural/urban and East/Center/West, In the construction of

weights it is possible to disaggregate the sample further among provinces within each

of the East/Central/West regions. Weights can be used to adjust for the fact that the

provincial sample sizes are not proportional to their populations. The CHIP survey,

however, does not cover all of China’s provinces, the numbers of provinces differ

among the three regions, and the provinces covered have changed across rounds of the

survey. Consequently, in the discussion below we mainly use rural/urban/migrant x

region x province (three level) weights. The three regions are subdivided into their

8

respective provinces, and the provinces are further subdivided into their respective

rural, urban, and migrant populations. Weights are constructed accordingly based on

the sample sizes versus population sizes of these subgroups or strata. In our discussion,

however, all statistical descriptions is reported with reweighting.

Table 1 Statistical Descriptions of Variables

Number of

Obs Mean Min Max

2007 2013 2007 2013 2007 2013 2007 2013

Variables

Age 10915 8935 35 40 16 60 16 60

Gender

Proportion Male 10915 8935 0.588 0.560 0 0 1 1

Marital

Proportion Married 10915 8932 0.721 0.876 0 0 1 1

Experience 10783 8796 9 11 0 0 43 45

Educational Attainment

Junior High School or

Below 10915 8935 0.368 0.331 0 0 1 1

High school 10915 8935 0.354 0.288 0 0 1 1

Junior College 10915 8935 0.164 0.185 0 0 1 1

College or Above 10915 8935 0.114 0.196 0 0 1 1

Industry Sectors

Manufacturing 10915 8935 0.219 0.183 0 0 1 1

Construction 10915 8935 0.075 0.058 0 0 1 1

Wholesale and retail

trade 10915 8935 0.123 0.049 0 0 1 1

Hotels and catering

services 10915 8935 0.101 0.033 0 0 1 1

Other industry 10915 8935 0.483 0.678 0 0 1 1

Firm Ownership

State Funded

Enterprises 10801 8919 0.356 0.406 0 0 1 1

Collective Enterprises 10801 8919 0.057 0.052 0 0 1 1

Private Enterprise 10801 8919 0.339 0.321 0 0 1 1

Foreign Funded

Enterprise 10801 8919 0.060 0.038 0 0 1 1

Self employed and

Other 10801 8919 0.188 0.183 0 0 1 1

Firm Size

Micro 10701 8748 0.151 0.178 0 0 1 1

Small 10701 8748 0.427 0.438 0 0 1 1

Medium 10701 8748 0.301 0.268 0 0 1 1

Large 10701 8748 0.120 0.116 0 0 1 1

Region

East 10915 8935 0.433 0.536 0 0 1 1

Middle 10915 8935 0.313 0.294 0 0 1 1

West 10915 8935 0.254 0.170 0 0 1 1

9

Table 2 Increasing rate of average monthly wage,average monthly minimum wage,

average hourly wage and average weekly hours from 2007 to 2013.

Average

Monthly

Wage

Average

Monthly

Minimum

Wage

Average

hourly

Wage

Average

Weekly

Hours

ALL 76.9 88.3 80.0 -4.0

Ascending sort by workers’ total monthly wage

The first quintile 48.0 80.0 66.7 -15.6

The second quintile 87.2 86.2 100.0 -5.7

The third quintile 88.2 93.6 100.0 0.0

The fourth quintile 80.8 92.6 81.8 2.3

The fifth quintile 69.5 88.3 56.0 5.0

Age Cohort

Age 16-20 91.9 99.7 120.0 -8.5

Age 21-25 67.4 91.0 85.7 -7.4

Age 26-30 56.4 91.6 54.5 -4.0

Age 31-35 77.8 89.8 81.8 -2.0

Age 36-40 72.7 87.2 72.7 -2.0

Age 41-45 76.9 87.8 63.6 2.1

Age 46-50 70.8 81.5 54.5 4.3

Age 51-55 54.5 83.2 38.5 4.4

Age 56-60 37.6 79.3 28.6 2.2

Gender

Male 77.3 89.1 77.8 -4.1

Female 78.7 87.6 72.7 -3.9

Marital Status

Unmarried 86.3 94.3 100.0 -11.1

Married 69.3 86.7 63.6 0.0

Experience Cohort

Experience 1-2 91.0 87.7 100.0 -9.1

Experience 3-5 67.5 90.1 66.7 -2.0

Experience 6-10 58.5 90.3 72.7 -2.0

Experience 11-15 53.9 87.0 53.8 0

Experience 16-20 54.3 83.6 50.0 4.5

Experience 20+ 66.6 83.8 46.7 7.1


Junior High School or Below 84.1 86.7 85.7 -5.5

High school 74.3 87.8 77.8 -4.0

Junior College 53.2 86.0 42.9 7.0

College or Above 47.8 90.0 35.0 4.8

Industry Sectors

Manufacturing 71.7 94.4 60.0 2.0

Construction 92.5 79.7 125.0 -13.8

Wholesale and retail trade 69.1 84.8 62.5 0.0

Hotels and catering services 271.7 102.0 333.3 -22.0

Other industry 58.0 85.9 50.0 2.2

10

Firm Ownership

State Funded Enterprises 65.7 85.5 50.0 4.7

Collective Enterprises 58.8 86.6 60.0 0.0

Private Enterprise 95.8 90.0 100.0 -7.4

Foreign Funded Enterprise 87.5 113.6 71.4 2.2

Self employed and Other 72.0 84.6 85.7 -7.1

Firm Size

Micro 79.1 81.2 85.7 -10.5

Small 75.3 88.2 70.0 -4.0

Medium 81.8 88.9 66.7 0.0

Large 91.5 97.5 76.9 -2.1

Region

East 65.9 65.3 66.7 -2.0

Middle 84.5 114.5 66.7 -4.0

West 74.4 98.3 66.7 -5.9

Type of Workers

Urban 49.6 81.1 28.6 9.3

Migrant 115.6 101.5 150.0 -10.3

5 A family of violation indices

In the enforcement literature, non-compliance is generally measured as the

fraction of all covered workers whose wages fall below the minimum. However, this

method of measuring compliance does not distinguish between different degrees of

violation. We propose here an index of violation to capture both the number of wage

earners falling below the minimum and also how far below the minimum they fall.

Consider a distribution of actual wages F(w) with density function f(w), and an

official minimum wage wm. If there is full compliance, strictly speaking, we should

not see any wages at all below wm. As those who would otherwise pay wages below

wm have no reason to pay above wm, compliance means paying a wage wm, and

non-compliance is paying a wage strictly less than wm. We define the measure of

individual violation as:

[1]

where v is positive if and only if w is strictly less than wm, and zero if w is equal to or

greater than wm. When w is strictly less than wm, v is weakly decreasing in w and

weakly increasing in wm. A particular functional form that satisfies these properties

is:

[2]

;]/)[(

;0{),(mm wwwm wwv

),( wwvv m

m

m

ww

ww

11

for a greater than or equal to zero. In fact, when a = 0, v becomes an indicator

function, taking on the value 1 when w is strictly less than wm, and a value of 0 when

w is greater than or equal to wm. When a = 1, v is the gap between the actual wage

and the official minimum wage, expressed as a fraction of the minimum wage. For

values of a greater than 1, the violation function emphasizes large gaps more — a

particular value of interest in empirical application will be a = 2, which simply

squares the gap to produce a measure of the violation.

Having specified a measure of violation for an individual wage, the issue now is

how to aggregate these individual violations, and how to normalize this aggregation.

A straight forward method would be to simply take the expectation E of v( ) over the

entire wage distribution, defining overall violation V as:

[3]

With v(wm

, w) defined as (2) above, V becomes:

[4]

This will be recognized immediately as the analogue of the Foster et al. (1984), ‘FGT’

measure of poverty, with wm acting as the poverty line and w as the income. In the

poverty context, a higher value of a captures greater ‘poverty aversion’. In our context,

increasing the value of a similarly captures ‘violation aversion’, giving greater weight

to the worst violations. What difference is made by different degrees of violation

aversion is an empirical question.

6 Compliance with minimum wages in China:2007-2013

The values for V with a= 0, 1, and 2, denoted V0, Vi, and V2, respectively, were

estimated. The results are shown in Table 3. Also included are estimates of the ratio Vi

to V0. Although V0 measures the percentage of workers violated, i.e. earning below the

minimum, the ratio (V1/V0) allows for the interpretation of V1, as it denotes the

percentage shortfall of the average wage of violated workers from the minimum wage.

Put differently, violated workers in this sample are earning on average (V1/V0) below

the relevant minimum.

The estimates in the first row of Table 3 show that 3.62 per cent of employees in year

2007 and 7.34 per cent of employees in year 2013 were receiving sub-minimum wages.

The change pattern of violations measured by V1 and V2 from year 2007 to year 2013

is quite similar to the change pattern of violations measured by V0.Overall,there are

more workers whose wage below minimum wage in year 2013 than year

2007.Generally,the proportion of workers earning less than the minimum wage in

China is higher for women than men, for unmarried than married,for younger and

less-experienced workers, and for workers with less education. The proportion of

workers earning below the minimum wage is also substantially higher in firms with self

employed owners, and in East Region of China.

mw

mm dwwfwwwV0

)(}]/){[(

}{v ），（ wwEV m

12

The estimates in the first row of Table 3 also shows that V1/V0 increase from 26.12%

in year 2007 to 43.77% in year 2013.That means that violated workers earned 26.12

per cent of the minimum in year 2007 and 43.77 per cent of the minimum in year

2013.Indicators of V1/V0 increased for almost all kinds of workers. Violated workers

got higher wages in year 2013,compared to year 2007.They became better. It is

interesting. The results imply that both the level and the depth of violation are

important when quantifying violation. Workers worse off in terms of the absolute

violation measure may not necessarily be equally worse off in relative terms and vice

versa. The above suggests that both an absolute and a relative measure of violation

matter when examining minimum wage compliance.

13

Table 3 Estimates of the index of violation in year 2007 and 2013

v0 v1 v2 v1/v0

2007 2013 2007 2013 2007 2013 2007 2013

ALL 3.62 7.34 0.95 3.21 0.46 2.09 26.12 43.77

[3.27 to 3.97] [6.8 to 7.89] [0.82 to 1.07] [2.92 to 3.51] [0.36 to 0.55] [1.87 to 2.32] [23.75 to 28.48] [41.48 to 46.06]

Age Cohort

Age 16-20 9.43 12.26 2.67 3.49 1.25 1.79 28.28 28.48

[7.53 to 11.32] [3.64 to 20.88] [1.96 to 3.37] [0.1 to 6.88] [0.73 to 1.77] [-0.51 to 4.09] [23.45 to 33.12] [3.07 to 53.89]

Age 21-25 2.75 8.54 0.64 3.72 0.27 2.44 23.25 43.60


Age 26-30 2.03 6.20 0.56 3.31 0.33 2.47 27.42 53.43


Age 31-35 2.01 4.46 0.55 2.43 0.27 1.70 27.62 54.59


Age 36-40 2.77 5.93 0.86 2.53 0.54 1.62 31.00 42.61


Age 41-45 4.09 6.59 0.96 2.96 0.45 1.90 23.53 44.86


Age 46-50 3.92 9.28 0.90 3.49 0.37 2.12 23.01 37.57


Age 51-55 4.57 8.77 1.01 2.97 0.39 1.56 22.13 33.93


Age 56-60 6.17 13.24 1.78 6.46 0.76 4.40 28.82 48.77


Gender

Female 4.77 10.00 1.13 3.98 0.53 2.53 23.76 39.83


14

Male 2.81 5.26 0.81 2.61 0.41 1.75 28.92 49.67


Marital Status

Unmarried 4.63 7.35 1.24 3.14 0.56 2.08 26.75 42.76


Married 3.24 7.35 0.83 3.23 0.42 2.09 25.77 43.92


Experience Cohort

Experience

1-2 6.27 10.36 1.50 3.87 0.64 2.33 23.86 37.38


Experience

3-5 3.05 9.20 0.73 3.62 0.38 2.30 23.96 39.35


Experience

6-10 1.90 7.18 0.55 3.46 0.27 2.43 29.12 48.18


Experience

11-15 1.90 6.05 0.67 3.04 0.44 2.01 35.13 50.27


Experience

16-20 1.84 3.54 0.69 1.64 0.45 0.95 37.57 46.45

[0.88 to 2.79] [2.33 to 4.75] [0.22 to 1.16] [1.02 to 2.27] [0.06 to 0.83] [0.52 to 1.37] [18.53 to 56.61] [37.91 to 55]

Experience 20+ 2.71 5.26 0.84 2.65 0.41 1.78 30.98 50.39



Junior High

School or

Below

5.35 9.68 1.31 3.73 0.57 2.28 24.48 38.57

15


High school 3.53 8.82 0.83 4.01 0.40 2.69 23.52 45.47


Junior College 1.90 5.58 0.72 2.85 0.41 1.99 37.82 51.06


College or

Above 0.79 2.90 0.46 1.52 0.36 0.99 57.41 52.25


Industry Sectors

Manufacturing 2.57 5.61 0.70 2.85 0.34 1.98 27.45 50.79


Construction 3.12 4.85 0.82 1.73 0.34 1.04 26.44 35.77


Wholesale and

retail trade 4.41 9.37 1.19 2.92 0.61 1.60 26.91 31.16


Hotels and

catering

services

7.20 3.51 1.09 1.79 0.28 1.16 15.07 50.97


Other industry 3.23 8.06 0.98 3.53 0.53 2.29 30.45 43.77


Firm Ownership

16

State Funded

Enterprises 2.08 5.67 0.68 2.55 0.39 1.66 32.60 45.00


Collective

Enterprises 3.64 8.28 0.88 3.63 0.36 2.34 24.17 43.83


Private

Enterprise 4.11 7.43 0.87 3.44 0.36 2.35 21.27 46.29


Foreign Funded

Enterprise 0.80 2.62 0.20 1.38 0.06 1.00 24.92 52.74

[0.1 to 1.5] [0.81 to 4.42] [0.01 to 0.39] [0.26 to 2.5] [0 to 0.12] [0.14 to 1.87] [10.81 to 39.03] [28.24 to 77.23]

Self employed

and Other 6.52 11.51 1.82 4.52 0.91 2.74 27.91 39.27


Firm Size

Micro 7.50 11.93 2.23 5.04 1.14 3.21 29.69 42.29


Small 4.07 7.58 0.98 3.27 0.46 2.14 24.04 43.16


Medium 2.01 5.25 0.56 2.45 0.26 1.64 28.01 46.62


Large 1.29 3.71 0.29 1.72 0.13 1.10 22.64 46.32

[0.68 to 1.91] [2.56 to 4.86] [0.09 to 0.49] [1.09 to 2.35] [-0.02 to 0.29] [0.64 to 1.56] [10.61 to 34.67] [37.3 to 55.35]

Region

East 5.70 6.02 1.38 2.88 0.61 1.95 24.30 47.90


17

Middle 1.71 8.61 0.55 3.35 0.35 2.02 32.14 38.92


West 2.44 9.34 0.69 4.03 0.33 2.65 28.13 43.12


Type of

Workers

Urban 2.56 7.50 0.80 3.25 0.46 2.10 31.24 43.35


Migrant 4.91 6.63 1.12 3.05 0.46 2.04 22.88 45.98

[4.3 to 5.51] [4.92 to 8.33] [0.94 to 1.31] [2.09 to 4] [0.33 to 0.59] [1.3 to 2.77] [20.36 to 25.41] [37.83 to 54.13]

Note:Ninety-five per cent confidence intervals shown in square brackets

18

7 Compliance with minimum wages in China considering working hours

In order to examine the compliance with minimum wages, we had compared

monthly total wage with monthly minimum wage. It is not accurate. In comparing

wages to minimum wages, the regulations make it clear the wage excludes overtime

pay. The monthly minimum wage is based on a 40 hour work week. According to

labor regulations passed in 1994, laborers shall work no more than eight hours per

day, five days per week. After consultation with trade unions and workers, a firm can

extend the work day. If workers work more than the legal maximum of 40 hours per

week, they must be paid at least 150% the wage they receive for regular hours, at

least 200% of the regular wage if the overtime is on a “day of rest” (weekend), and

at least 300% the regular wage if the overtime is on a statutory holiday.

Our data gives the information about weekly working hours of workers. If workers’

weekly working hours are longer than 40 hours, we could regard the workers’

weekly working hours minus 40 hours as overtime. Then we can also get overtime

pay. We have two ways to calculate overtime pay. One way is that we suppose

overtime pay is 100% the wage they receive for regular hours. Another way is that

we suppose overtime pay is 150% the wage they receive for regular hours. At last we

can get monthly wage excluding overtime pay. Then we compare this wage with

monthly minimum wage. The results are as Table 4 and Table 5.Table 4 is

compliance with hourly minimum wage when we suppose overtime pay equals

hourly wage for regular hours. Table 5 is compliance with hourly minimum wage

when we suppose overtime pay equals 150% of hourly wage for regular hours.

When we consider working hours, the proportion of violated workers increased a lot.

Table 4 gives compliance with hourly minimum wage when we suppose overtime

pay equals hourly wage for regular hours. The estimates in the first row of Table 4

show that 13.95 per cent of employees in year 2007 and 12.95 per cent of employees

in year 2013 were receiving sub-minimum wages. From table3,without considering

working hours,3.62 per cent of employees in year 2007 and 7.34 per cent of

employees in year 2013 were receiving sub-minimum wages. What is interesting is

that the proportion of violated workers almost did change from year 2007 to year

2013 when considering working hours. This is because working hours of low-skill

workers decreased a lot. Table 6 gives increasing rate of average weekly working

hours. Overall, average working hours of workers decreased 4%.But for low skill

workers, average weekly working hours decreased a lot, for example, low wage

workers(-15.6%),workers of age 16-20(-8.5%),workers in Hotels and catering

services industry(-22%),workers in construction industry(-13.8%),workers in

Micro-firms(-10.5%),Migrant workers(-10.3%).

The results from Table 5 is quite similar to the results from Table 4.

19

Table 4 Compliance of Hourly Minimum Wage(Overtime Wage=1* Hourly Wage)

v0 v1 v2 v1/v0

2007 2013 2007 2013 2007 2013 2007 2013

ALL 13.95 12.59 3.78 4.57 1.55 2.69 27.07 36.28

[13.3 to 14.6] [11.9 to 13.28] [3.55 to 4] [4.24 to 4.9] [1.42 to 1.69] [2.44 to 2.93] [26.1 to 28.04] [34.62 to 37.95]

Age Cohort

Age 16-20 34.53 31.64 10.23 8.93 4.39 3.65 29.62 28.22


Age 21-25 15.86 15.99 4.07 5.75 1.57 3.30 25.65 35.97


Age 26-30 9.57 9.65 2.42 4.30 0.99 2.97 25.24 44.62


Age 31-35 10.37 7.48 2.57 3.31 0.99 2.16 24.77 44.23


Age 36-40 12.24 10.50 3.32 3.64 1.40 2.06 27.12 34.63


Age 41-45 12.40 11.47 3.30 4.08 1.35 2.41 26.60 35.58


Age 46-50 10.28 15.92 2.66 5.25 1.05 2.88 25.90 33.00


Age 51-55 12.74 14.91 3.46 4.55 1.41 2.23 27.16 30.48


Age 56-60 13.84 21.13 5.00 8.32 2.41 5.16 36.17 39.37


Gender

Female 16.63 16.68 4.54 5.78 1.83 3.28 27.31 34.65


Male 12.08 9.38 3.24 3.62 1.36 2.22 26.84 38.57


Marital Status

20

Unmarried 19.43 13.32 5.32 4.79 2.16 2.76 27.38 35.97


Married 11.83 12.49 3.18 4.54 1.32 2.68 26.87 36.33


Experience Cohort

Experience

1-2 24.76 20.78 6.84 6.60 2.77 3.39 27.64 31.78

[23.33 to 26.19] [18.76 to 22.8] [6.34 to 7.35] [5.75 to 7.46] [2.48 to 3.06] [2.77 to 4] [26.4 to 28.89] [29.12 to 34.44]

Experience

3-5 13.81 15.77 3.52 5.38 1.43 3.08 25.46 34.10

[12.35 to 15.27] [14.03 to 17.51] [3.03 to 4] [4.58 to 6.18] [1.14 to 1.72] [2.48 to 3.69] [23.23 to 27.69] [30.77 to 37.43]

Experience

6-10 10.40 12.38 2.59 4.77 1.03 3.06 24.86 38.51


Experience

11-15 6.65 9.65 1.83 3.87 0.88 2.41 27.60 40.07


Experience

16-20 4.01 5.82 1.27 2.22 0.62 1.28 31.76 38.24


Experience

20+ 3.80 6.89 1.19 3.04 0.55 1.94 31.28 44.08



Junior High

School or

Below

23.35 20.07 6.38 6.36 2.58 3.36 27.33 31.70


High school 12.80 13.45 3.29 5.25 1.31 3.27 25.72 39.02


21

Junior College 4.02 7.87 1.18 3.39 0.57 2.25 29.34 43.09


College or

Above 1.44 3.18 0.60 1.66 0.43 1.10 41.86 52.16


Industry Sectors

Manufacturing 9.03 10.46 2.35 4.08 0.97 2.53 25.96 38.96


Construction 18.04 7.43 4.23 2.57 1.59 1.46 23.46 34.67


Wholesale and

retail trade 19.35 21.61 5.10 6.98 2.06 3.38 26.37 32.29


Hotels and

catering

services

31.09 5.94 8.67 2.15 3.27 1.33 27.89 36.21


Other industry 10.60 13.28 3.00 4.81 1.33 2.85 28.28 36.26


Firm Ownership

State Funded

Enterprises 5.18 7.75 1.48 3.08 0.69 1.90 28.58 39.69


Collective

Enterprises 10.60 16.26 2.65 5.47 1.07 3.16 24.99 33.66

[8.18 to 13.03] [12.88 to 19.64] [1.86 to 3.44] [3.92 to 7.02] [0.64 to 1.5] [2 to 4.33] [20.18 to 29.81] [26.86 to 40.45]

22

Private

Enterprise 18.92 14.05 4.77 5.24 1.77 3.15 25.19 37.33


Foreign

Funded

Enterprise

2.96 4.97 0.78 1.94 0.35 1.20 26.31 38.92


Self employed

and Other 26.12 21.18 7.67 6.97 3.34 3.79 29.36 32.89


Firm Size

Micro 27.88 22.69 8.60 7.83 3.84 4.39 30.84 34.50


Small 15.49 12.68 4.10 4.57 1.66 2.72 26.46 36.07


Medium 8.80 8.46 2.07 3.26 0.76 2.02 23.53 38.57


Large 4.68 5.63 1.13 2.23 0.43 1.31 24.09 39.50


Region

East 21.36 11.37 6.12 4.02 2.50 2.42 28.67 35.33


Middle 7.67 13.69 1.74 5.00 0.72 2.77 22.63 36.51


West 9.06 14.55 2.29 5.57 0.97 3.37 25.29 38.26


Type

Urban 5.79 12.32 1.50 4.49 0.71 2.65 25.95 36.40


Migrant 23.83 13.85 6.53 4.95 2.58 2.84 27.40 35.78


23

Table 5 Compliance of Hourly Minimum Wage(Overtime Wage=1.5* Hourly Wage)

v0 v1 v2 v1/v0

2007 2013 2007 2013 2007 2013 2007 2013

ALL 18.71 13.92 5.62 4.91 2.48 2.84 30.02 35.25


Age Cohort

Age 16-20 44.79 33.82 14.71 10.49 6.79 4.29 32.84 31.02


Age 21-25 23.11 18.29 6.42 6.36 2.68 3.55 27.76 34.74


Age 26-30 13.50 11.41 3.83 4.56 1.63 3.08 28.39 39.94


Age 31-35 14.13 8.70 4.01 3.60 1.69 2.28 28.41 41.37


Age 36-40 15.44 11.76 4.91 3.95 2.22 2.20 31.78 33.54

[13.68 to 17.21] [10.05 to 13.48] [4.22 to 5.6] [3.18 to 4.71] [1.8 to 2.65] [1.64 to 2.75] [29.22 to 34.35] [29.08 to 38]

Age 41-45 16.36 12.39 4.75 4.32 2.09 2.54 29.07 34.84

[14.46 to 18.26] [10.79 to 14] [4.05 to 5.45] [3.57 to 5.06] [1.67 to 2.5] [1.98 to 3.09] [26.44 to 31.69] [30.81 to 38.88]

Age 46-50 14.50 17.11 3.92 5.59 1.65 3.04 27.00 32.69


Age 51-55 15.23 16.16 4.87 4.96 2.18 2.40 32.01 30.66


Age 56-60 16.58 22.33 6.37 8.74 3.33 5.39 38.40 39.16


Gender

Female 21.33 17.81 6.53 6.12 2.89 3.45 30.63 34.35

[20.13 to 22.52] [16.61 to 19] [6.07 to 6.99] [5.57 to 6.66] [2.62 to 3.16] [3.04 to 3.86] [29.34 to 31.91] [32.3 to 36.39]

24

Male 16.87 10.87 4.97 3.96 2.19 2.36 29.49 36.42

[15.95 to 17.78] [10 to 11.73] [4.63 to 5.32] [3.55 to 4.37] [1.99 to 2.39] [2.05 to 2.67] [28.27 to 30.72] [33.95 to 38.89]

Marital Status

Unmarried 26.34 14.70 7.97 5.22 3.49 2.95 30.26 35.50


Married 15.75 13.82 4.71 4.87 2.09 2.83 29.87 35.21


Experience Cohort

Experience

1-2 31.76 23.22 10.07 7.23 4.47 3.67 31.69 31.13


Experience

3-5 19.72 17.21 5.45 5.78 2.34 3.27 27.65 33.56


Experience

6-10 14.20 13.63 4.01 5.08 1.70 3.20 28.27 37.28


Experience

11-15 10.53 10.93 2.80 4.15 1.30 2.54 26.59 38.01


Experience

16-20 5.80 6.28 1.78 2.42 0.85 1.38 30.67 38.58


Experience

20+ 5.08 7.18 1.49 3.14 0.69 1.99 29.35 43.65



Junior High

School or

Below

31.10 22.72 9.54 7.07 4.20 3.68 30.69 31.12

25


High school 17.35 14.72 4.97 5.51 2.13 3.39 28.67 37.46


Junior College 5.53 8.20 1.59 3.49 0.75 2.30 28.78 42.55

[4.47 to 6.59] [6.92 to 9.48] [1.2 to 1.98] [2.8 to 4.18] [0.5 to 1] [1.76 to 2.84] [24.17 to 33.38] [37.45 to 47.65]

College or

Above 1.78 3.31 0.70 1.71 0.47 1.13 39.40 51.60


Industry Sectors

Manufacturing 13.16 12.46 3.63 4.42 1.54 2.67 27.55 35.46


Construction 25.87 9.43 7.04 2.89 2.81 1.59 27.20 30.64


Wholesale and

retail trade 26.04 24.11 7.60 7.88 3.30 3.91 29.17 32.67


Hotels and

catering

services

40.31 6.23 12.88 2.23 5.60 1.34 31.96 35.73


Other industry 13.74 14.34 4.28 5.13 1.99 2.99 31.15 35.76


Firm Ownership

26

State Funded

Enterprises 6.75 8.19 2.04 3.18 0.97 1.95 30.29 38.84


Collective

Enterprises 14.12 16.67 3.90 5.70 1.67 3.29 27.62 34.19


Private

Enterprise 26.34 15.55 7.41 5.66 3.05 3.34 28.15 36.38


Foreign

Funded

Enterprise

3.57 6.23 1.17 2.18 0.54 1.28 32.61 34.89


Self employed

and Other 33.68 24.45 11.11 7.74 5.20 4.13 32.99 31.67


Firm Size

Micro 35.37 25.09 12.27 8.55 5.90 4.74 34.70 34.09


Small 20.30 14.01 6.06 4.90 2.65 2.86 29.85 34.99


Medium 12.86 9.10 3.29 3.40 1.28 2.08 25.56 37.36


Large 7.62 6.56 1.90 2.41 0.78 1.39 24.95 36.80


Region

East 26.94 12.94 8.72 4.35 3.94 2.55 32.38 33.63


27

Middle 11.99 14.50 2.96 5.32 1.20 2.95 24.68 36.68


West 12.95 16.03 3.59 5.95 1.56 3.58 27.75 37.15


Type

Urban 7.75 13.35 2.05 4.76 0.95 2.78 26.46 35.63


Migrant 31.96 16.59 9.93 5.61 4.33 3.12 31.07 33.84


28

Table 6 increasing rate of average weekly working hours

Average Weekly Hours

2007 2013 Growth(%)

ALL 50 48 -4.0

Ascending sort by workers’ total monthly wage

The first quintile 64 54 -15.6

The second quintile 53 50 -5.7

The third quintile 48 48 0.0

The fourth quintile 44 45 2.3

The fifth quintile 40 42 5.0

Age Cohort

Age 16-20 59 54 -8.5

Age 21-25 54 50 -7.4

Age 26-30 50 48 -4.0

Age 31-35 49 48 -2.0

Age 36-40 49 48 -2.0

Age 41-45 47 48 2.1

Age 46-50 46 48 4.3

Age 51-55 45 47 4.4

Age 56-60 46 47 2.2

Gender

Male 49 47 -4.1

Female 51 49 -3.9

Marital Status

Unmarried 54 48 -11.1

Married 48 48 0.0

Experience Cohort

Experience 1-2 55 50 -9.1

Experience 3-5 51 50 -2.0

Experience 6-10 49 48 -2.0

Experience 11-15 48 48 0

Experience 16-20 44 46 4.5

Experience 20+ 42 45 7.1


Junior High School or Below 55 52 -5.5

High school 50 48 -4.0

Junior College 43 46 7.0

College or Above 42 44 4.8

Industry Sectors

Manufacturing 49 50 2.0

Construction 58 50 -13.8

Wholesale and retail trade 53 53 0.0

Hotels and catering services 59 46 -22.0

Other industry 46 47 2.2

Firm Ownership

29

State Funded Enterprises 43 45 4.7

Collective Enterprises 47 47 0.0

Private Enterprise 54 50 -7.4

Foreign Funded Enterprise 46 47 2.2

Self employed and Other 56 52 -7.1

Firm Size

Micro 57 51 -10.5

Small 50 48 -4.0

Medium 47 47 0.0

Large 47 46 -2.1

Region

East 49 48 -2.0

Middle 50 48 -4.0

West 51 48 -5.9

Type

Urban 43 47 9.3

Migrant 58 52 -10.3

30

8 Conclusion

We used CHIPs 2007 and 2013 to examine the extent to which minimum wages are

complied with in China.We found that 3.62 per cent of employees in year 2007 and

7.34 per cent of employees in year 2013 were receiving sub-minimum wages.

Overall,there are more workers whose wage below minimum wage in year 2013 than

year 2007.When using the relative violation indicators,we found that violated

workers earned less 26.12 per cent of the minimum(73.88% of minimum wage) in

year 2007 and less 43.77 per cent of the minimum (56.23% of minimum wage ) in

year 2013.Violated workers got lower wages in year 2013,compared to year

2007.They became worse.

When we consider weekly working hours,the proportion of violated workers

increased a lot.13.95 per cent of employees in year 2007 and 12.95 per cent of

employees in year 2013 were receiving sub-minimum wages. What is interesting is

that the proportion of violated workers almost did not change or even decreased from

year 2007 to year 2013 when considering working hours.This is because working

hours of low-skill workers decreased a lot from year 2007 to year 2013.Overtime

work and overtime work without overtime pay is widespread in Chinese labor

market.Since the Labor Contract Law of the People’s Republic of China took effect on

May 1, 2008,minimum wage regulations had become more and more strict.As

enterprise should pay overtime work by law,so they will decrease overtime work.So

as a result,the average working hours of workers,especially for workers below

minimum wage decreased.

31

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Compliance with Legal Minimum Wages in China: 2007-2013 2016

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