Immigration and Earnings Inequalities

in Hong Kong, 1996-2006

By

LAM Kit-ChunDepartment of Economics

Hong Kong Baptist Universityand

LIU Pak-WaiChinese University of Hong Kong

Objectives To study the pattern of inequalities by using

ratios of percentile earnings, as well as their changes from 1996 to 2006

to study the socio-demographic and economic characteristics of working individuals in different percentile groups, including proportion of immigrants, and identify intercensal changes in profile.

To study the different characteristics of immigrants and local people as a possible explanation for earnings inequalities

Objectives

To study how different socio-demographic and economic variables may affect earnings of employees in year 2006, and identify changes in pattern over time.

To study the contribution of different factors to total difference in log earnings for various groups.

Data

The data we use are the 1/14 sample of the 1996 and 2006 by-censuses.

We confine our samples to working population of age 18 to 60

our samples do not include imported domestic helpers.

Measure of inequalities

We will focus our attention to three earnings ratios

between the 90th and 10th percentiles (90-10 earnings ratio),

between the 90th and 50th percentiles (90-50 earnings ratio),

between the 50th and 10th percentiles (50-10 earnings ratio).

Percentile earnings ratios

Dummy variables on Immigrant Status

IMMIGOLD is a dummy variable for old immigrants who were born in China, have indicated their nationality as Chinese, and have resided in Hong Kong for seven years or more at the time of the census;

IMMIGNEW refers to new immigrants who were born in China, have indicated their nationality as Chinese, and have resided in Hong Kong for less than 7 years at the time of the census

IMMIGOTH refers to immigrants who do not belong to the IMMIGOLD or the IMMINGNEW categories.

The omitted dummy variable HKBORN refers to workers born in Hong Kong.

Schooling dummy variables

• SCH2 is a dummy variable for junior secondary education,

• SCH3 for senior secondary education,

• SCHC4 for post-secondary education and SCH5 for university education.

• The reference group consists of individuals with primary education and below.

Experience & Gender

• EXP refers to the years of working experience of the individual computed as (Age – years of schooling – 6),

• and EXPSQ is its square term.

• MALE is a dummy variable for male individuals;

Industry dummies

IND2WRR is a dummy for wholesale and retail trade and restaurants and hotels;

IND3FIN for financing, insurance, real estate and business services;

IND4SER for community and social Services;

IND5OTH for other industries including agriculture, forestry and fishing; mining and quarrying; electricity, gas and water; construction; storage and communication.

The reference group refers to manufacturing industry.

Characteristics of different percentile groups

Gender & Schooling

Characteristics of different percentile groups

Age profile

Characteristics of different percentile groups

Industrial composition

Characteristics of different percentile groups

Immigrant composition

Characteristics of different immigrant groups

Characteristics of different immigrant groups

Estimates of Earnings Regressions for working population

Contributions to differences in log earnings, 90th & 10th percentiles

Contributions to differences in log earnings, 50th & 10th percentiles

Conclusion & Discussions

It is found that earnings inequality as measured by earnings ratio between the 90-10 percentiles increases from 5.2 in year1996 to 6.2 in year 2006, representing a considerable increase of more than 19%.

However, the increase in spread comes largely from

the increase in spread between the 90 percentile and 50 percentile (an increase of 13.6%)

while the increase in inequality between the 50 percentile and the 10 percentile is relatively small.

The gross earnings disadvantage of new immigrants relative to local people is about 62% in year 2006, which is reduced to about 35% when other factors like schooling, working experience and gender are held constant.

At the same time, the average year of schooling of immigrants (i.e. around 9.7 years) is lower than that of people born in Hong Kong (i.e. 11.9 years).

The earnings disadvantage of immigrants together with their lower education has resulted in their over-representation in the 10th percentile earnings group.

Conclusion & Discussions

Our findings indicate that the gross effect of immigrant status can explain 5.9% of the total earnings differential between 90th and 10th percentile groups,

which is further reduced to 3.8% when other factors are being held constant.

How can we explain this in face of the large earnings differential between immigrants and local people.

The answer lies in the small share of new immigrants in the whole population, which is just about 2.7% in both 1996 and 2006.

Conclusion & Discussions

A far more important contribution to earnings inequalities is years of schooling.

Holding other factors constant, the contribution of schooling to the earnings differential between the 90th and 10th percentile groups amounts to about 30%, and about 23% between the 50th and 10th percentile groups.

Note that other than the coefficient effect of schooling on earnings, part of the schooling effect works through the quantity effect due to different schooling profile of immigrants.

Conclusion & Discussions

It is also found that the earnings differential between local people and immigrants of a particular education level is different for different education levels.

Besides, if we take into consideration the difference in quality of school which has not been measured in this paper, the contribution of schooling could be even larger.

Conclusion & Discussions

Given the important role of the education gap in explaining earnings inequalities, there is a strong argument for government to adopt a policy to enhance the educational attainment of new immigrants for the sake of reducing the earnings gap between immigrants and local people.

Policy Implications

Policy Implications

• First, as far as possible new immigrants should be allowed or encouraged to immigrate to Hong Kong at a pre-school or early school age, so that they can benefit from the Hong Kong school system which enables them to have a higher return to schooling.

Second, for new immigrants who have passed the normal school age when they immigrate to Hong Kong

government should actively promote its menu of subsidized job training, re-training and continuing education opportunities that are available

This should enhance the marketable skills of the new immigrants and improve their relative earnings position.

Policy Implications

Third, our results show that controlling the year of schooling, new immigrants suffer from a sizeable earnings disadvantage.

one reason could be the difference in culture and the lack of soft skills.

Women are particularly disadvantaged as they are often required to wait many years, often idling in the Mainland or in Hong Kong with a two-way permit, for final approval to come to Hong Kong for reunion with their husbands under the one-way permit scheme.

Early approval of OWP for reunion with spouse should alleviate the situation.

Policy Implications