living alone in china: projection of one-person household

Living Alone in China: Projection of One-person Household, 2010 to 2050

Abstract

Today, more than 60 million of Chinese live alone. One-person household is the fasted growing

household type in China and is expected to increase dramatically due to rapid urbanization,

migration, aging and changing demographic behaviors. In the next few decades, China will

house the largest number of persons living alone in the world. It is important to anticipate the

volume and composition of this population and consider implications of this trend. We apply a

newly-developed method of household projection, the ProFamy Extended Cohort-component

Method to forecast the changes in one-person households in China from 2010 to 2050. Distinct

from traditional household projection methods such as extrapolation of household headship-rates

(United Nations 1973, 1989), ProFamy is an individual-based macro-simulation method for

household projection, which simulates the changes of household based on individuals grouped

by age, sex, race, marital/union status, parity, and number of co-residing children/parents,

rural/urban residence.

INTRODUCTION

One-person household is the fasted growing household type in China. Today, more than

60 million of Chinese live alone. Recent studies have documented that due to the aging trend,

economic development and increase migration, there has been a continued rise of one-person

households in China for the past three decades (Guo, 2008; Zhao & Chen, 2008; Cheung and

Yeung, 2013). According to the National Bureau of Statistics in China, while about 6% of the

Chinese households were one-person households in 1995, this figure has more than doubled to

14% in 2011; meanwhile, the number of solo-living Chinese has tripled from about 19 million in

1995 to about 59 million in 2011 (National Bureau of Statistics of China, 2013). Recent work

documents the historical temporal-spatial patterns of one-person households in China and find

that OPH have become increasingly heterogeneous over time. Industrialization and internal

migration largely explain the changing spatial variation of OPH. Lengthened life expectancy and

a decline in fertility help to explain the increase in widowed OPH, while industrialization and

migration are relevant to the rise of non-widowed OPH. It is expect that OPH will continue to

increase in China in the next few decades due to the rapid aging trend, a potential decline in

marriage and fertility rates, and a rapid increase in migration (Yeung and Cheung, 2015). In the

next few decades, China will likely become the country with the largest number of one-person

households in the world due to its sheer population size, the unique demographic changes, and

rapid socioeconomic transformation.

The growth of the one-person household in China has raised important concerns by

researchers and policymakers, as solo-living has implications in multiple social and economic

dimensions, such as the well-being of the individuals, the functioning of the family system, the

role of community and neighborhood, and the efficiency of resource utilization. From both

policy planning and individual well-being points of view, it is thus important to anticipate the

temporal changes of the total number of one-person households in China, and to explore the

future compositions of this special type of households in terms of important demographic

characteristics.

The objective of this paper is to project the future trend of one-person household in China

by age, gender, rural/urban residence and marital status from 2010 to 2050. Considering the vast

heterogeneity of distribution of one-person households in China across geographic areas with

different demographic profiles and uneven socioeconomic development (Cheung and Yeung

2013), we further conduct sub-national projections in order to better illustrate the possible

scenarios of changes of one-person households at different regions of China for the next three

decades. That is, together with the national projections which reflect the overall changes of one-

person household in China, we additionally develop a provincial-level projection with Hebei

province chosen as a representative case, and a city-level projection based on the Beijing city,

the capital of China. Hebei province is a northern province of China, along the costal line. It is a

typical middle-level province of China in term of economic development. In contrast, Beijing is

one of most developed metropolitan areas of China. These two sub-national projections represent

not only different geographical levels but also different economic developmental stages within

China, and thus provide good supplementary information for us to understand the varieties

within the national trends.

METHOD

In this study, we apply a newly-developed method of household projection, the ProFamy

Extended Cohort-component Method (thereafter ProFamy), to forecast the changes of one-

person household in China from 2010 to 2040. This method is developed by Zeng, Vaupel and

Wang (1997; 1998) and further extended by Zeng, Land, Wang and Gu (2006; 2013), and

employed in various applications such as the population and household projection, the

automobile market analyses, the housing development planning, and energy consumption

estimations (e.g. Prskawetz et al. 2004; Dalton et al. 2008; Smith et al. 2008; Zeng et al 2008;

Feng et al. 2011). Distinct from traditional household projection methods such as extrapolation

of household headship-rates (United Nations 1973, 1989), ProFamy is an individual-based

macro-simulation method for household projection, which simulates the changes of household

based on individuals grouped by age, sex, race, marital/union status, parity, and number of co-

residing children/parents, rural/urban residence; and it is also a cohort-component method, in

which projection of changes in demographic components (fertility, mortality, marriage/union,

co-residence of children/parents, and migration) are made for each of the cohorts that produce

household distributions in future years.

ProFamy is an appropriate method for projecting the one-person household. First, it directly

incorporates the household size, which is usually not projectable using headship-rate methods

(e.g. Crone and Mills 1991; Nishioka et al 2011). Recent studies revealed that the headship-rate

method, without incorporating the household size in projection, may produce substantial forecast

errors in applications such as forecasts of future housing demand and vehicle consumption

(Prskawetz et al. 2004; Zeng 2013). By incorporating the household size in projection, ProFamy

not only avoids biases in the household projection, but also become a good choice for projections

on one-person household, in which the household size is the key concern.

Second, ProFamy is also able to provide detailed and accurate projections of the one-person

household by major demographic characteristics such as age, gender, and marital status. The

ProFamy method uses demographic rates as input and thus incorporate projected or assumed

changes in the propensity and timing of demographic processes, which could not be applied in

the headship rate methods (Spicer et al. 1992). Therefore, the ProFamy generates more detailed

projection information with less forecast errors in comparison with the headship-rate approach

(Zeng et al. 2006; Zeng et al. 2008).

Third, the ProFamy method avoids the problematic headship designation inherent in the

traditional headship-rate projections. A household head in the headship rate method is often a

vague, ill-defined, and sometimes arbitrary choice (Mason and Racelis 1992). For instance, if the

census or survey is done in daytime rather than evening, more women as house makers might be

designated as household head. In contrast, ProFamy does not suffer from the issue of household

head designation.

Finally, the ProFamy method has recently been extended to the subnational levels such as the

state/provincial level, and city/country level (Zeng et al. 2013), which enables us to conduct the

sub-national projections in the current projection. Demographic projections at these sub-national

levels are particular useful for the local business and policy planning. Zeng and colleagues

(2013) had already acquired good evidence to support advantages of ProFamy in comparison

with the traditional headship-rate method in the sub-national levels: in a validation exercise on

the American future housing demand, the headship rate method indeed produced substantially

more serious downward forecast errors than the ProFamy projections.

DATA AND ASSUMPTIONS

The ProFamy projection usually needs three kinds of data: 1) information about the baseline

population including distribution of age, sex, marital/union status, relationship to the householder,

whether living in a private or institutional household, and rural/urban residence, which could be

acquired from census or surveys; 2) the model standard schedules, i.e. the age-sex-specific

occurrence/exposure (o/e) rates of marital and non-marital fertility, mortality, marriage/union

formation and dissolution, leaving parental home, and immigration/emigration, which could be

estimated from census, surveys, or acquired from official statistics; and 3) the projected or

assumed summary parameters, such as total fertility rate (TFR), sex-specific life expectancy at

birth, mean age of first marriage and birth, rates of marriage/union formation and dissolution,

number of male and female migrants, and proportion of urban residents which often could be

estimated by census or surveys (for more details, see Zeng et al. 2008; 2013).

Baseline populations

In this projection, the baseline populations of China, Hebei province, and Beijing city are all

based on the micro-data of the 2010 census. According to the census, in the baseline year of

2010, China had 1340.9 million people, among which 51.3% were males and 48.7% were

females, and 49.9% were urban residents and 50.1% were rural residents. For the two

subnational baseline populations, Hebei province had 71.9 million people with 50.7% male and

49.3% female, 44.5% urban residents and 55.5% rural residents; for Beijing city, the total

population was 19.6 million with 51.6% males and 48.4% females, 85.9% urban residents and

14.1% rural residents.

Model standard schedules

The model standard schedules have been estimated at the national level (for the detail of the

calculation methods, see Appendix A of Zeng et al. 2008). These model standard schedules can

be used as well for the subnational projections in Hebei province and Beijing city, as has been

justified and validated in the previous methodological discussions on the ProFamy (Zeng et al.

2013). Therefore, when local data are not available, the model standard schedules at the national

level were used for subnational projections.

The following standard schedules are estimated and used in this projection, including age-sex-

rural/urban-specific rates of fertility by parity (based on the census counts of parity and month of

births from all women aged 15 to 50 who gave birth within the 12 months prior to the standard

census time), mortality (based on census data on household members who died during the 12

months prior to the standard census time), first marriage (based on census counts of year and

month of first marriage from all adults over age 15), and leaving parental homes (based on the

2000 and 2010 census data with the iterated interpolating method within cohorts proposed by

Coale (1984, 1985) and extended by Stupp (1988)). The age-sex-specific rates of divorce and

remarriages are estimated from data of the Chinese In-depth Fertility Survey and the Chinese

Longitudinal Healthy Longevity Survey. We also use the census data to estimate the age-sex-

specific net migration rate between rural and urban areas, and between the local and outside

(based on residence locations at the census time and one year and five years prior).

Summary Parameters

Total Fertility Rate (TFR)

It is well known that TFR is under-reported in the Chinese censuses. In the 2010 census, the TFR

was reported as low as 1.18 in China, 1.31 in Hebei province, and 0.71 in Beijing City.

Adjustment is thus needed for the accurate projections. We adopted the following strategy to fix

the under-reporting TFRs. Firstly, based on the 2010 census data for ages 10-19, we used a

“backward forecasting” method to estimate the under-reporting rate for ages 0-9 in the 2000

census. We then used the 2000 census as a source of basic data for women of reproductive age to

perform “forward-forecasting” to estimate the number of children aged 0-9 in 2010, and the

forecast is adjusted by the under-reporting rate acquired before. Using such an adjustment , in the

year of 2010, the actual TFR was about 1.63 in China, 1.71 in Hebei province, and 0.94 in

Beijing. These TFRs are highly consistent with the opinions by the government experts and

scholars in this field.

For the future trend of TFR, we consider that the current one-child policy will be gradually

relaxed to a universal two-child policy, i.e. one couple is allowed to have two children (Zeng

2013). Under such a scenario, we assume that the TFR in 2030 will slowly increase to 1.81 for

the whole China (2.15 for rural and 1.67 for urban), 1.85 in Hebei province (2.10 for rural and

1.70 for urban), and 1.52 in Beijing (1.80 for rural and 1.50 for urban). These rates will maintain

at the similar level until the year of 2050. The detailed adjustments and assumptions on TFRs are

summarized in Table 1.

Life Expectancy at Birth

For Hebei province, we firstly estimated the sex-rural/urban-specific life expectancy at birth in

1990-2010 based on the mortality rates collected in the 1990, 2000, and 2010 censuses and the 1%

population survey data collected in 1995 and 2005, and then extrapolated it to future years up to

2050. For Beijing city, the sex-specific life expectancy at birth in 2010 comes from Beijing

Public Health Information Center. For the life expectancy in future years, we first estimated the

annual increase of life expectancy from 2006 to 2011 (0.16) and extrapolated the future life

expectancy under the assumptions that the annual increase will be about 70% from 2010-2015,

65% from 2015-2030, and the whole increase from 2030 to 2050 will be equivalent to the

increase from 2015 to 2030. The rural/urban specific life expectancy was estimated based on the

rural/urban difference observed in the 2000 census. The details of the life expectation at birth are


Mean Age of First marriage and First birth

General Marriage/Divorce Rate

In Hebei province, we estimated the rural/urban-specific general marriage and divorce rates

using the age-sex-specific standard model schedules of marriage and divorce rates, the 2010

census data, and the total number of marriages and divorces in the published reports or

yearbooks. The results and assumptions are summarized in Table 1.

Number of Immigrants and Emigrants

The number of migrants is assumed to be negligible in the projection of China due to the sheer

size of the total population. For Hebei province, based on the extrapolation method and data

from the censuses conducted in 1990, 2000, and 2010, we estimated the sex-specific number of

net-immigrants from other provinces (mainly from other poorer provinces in the middle and

western parts of the country). We assume the age and sex distributions of net migrants in the

future years maintain the same as those observed in 2010 and also assume a gradual increase of

net immigrants in Hebei province from 2010 to 2050 (for details, see Table 1). For Beijing city,

the numbers of migrants in 2010 come from the census data with immigrants of 765.6 thousands

and emigrants of 81.0 thousands. For the future trend, we assume the number of immigrants in

2015 will be 65% of the year of 2010, it will decline to be 50% of the year of 2010 in 2030, and

it will maintain the same until 2050; we assume the number of emigrants in 2015 will be 85% of

the year of 2010, and it will maintain the same until 2050 (for details, see Table 1).

Proportion of Urban Residents

Following an extrapolation approach based on time series data of proportion of urban population

from the censuses and annual surveys of population changes, we estimated/projected that the

proportion of urban residents in China as 71.0% in 2030 and 87.0% in 2050, and Hebei province

as 63.0% in 2030 and 75.0% in 2050. For Beijing city, which is already highly urbanized in 2010

with 85.0% residents being urban, we assume that the proportion of urban population will reach

as high as 95% in 2035 and then maintain the same until 2050. These summary parameters are


<Table 1 is about here>

RESULTS

One-person Household in China

Table 2 summarizes the projected changes of one-person household in comparison with the

changes of other types of households in China from 2010 to 2050. As we can see from the

projection results, the total number of households in China will increase from about 401 million

to 552 million from 2010 to 2050, and the number of one-person household increase even more

rapid in the same period, almost doubled from 56 million in 2010 to 162 million in 2050. The

married couple with children will eventually lose ground to OPH right before 2050, its

proportion among the total households will significantly decline from 42.7% to 28%; meanwhile

the one-person household becomes the most popular type of household, rising from 13.9% to

29.3%. That is, by 2050, virtually one third of the Chinese households will be those who live

alone.

It is also worthy of note that a greater proportion of one-person households is projected to live in

urban areas in future decades: in 2010, about 59.6% of the one-person households are living in

the urban areas, whereas by 2050, this rate will increase to 89.5%. With regard to the rural areas

in China, although the one-person household is expected to decline in number from 23 million to

17 million due to the rapid urbanization, the proportion of one-person household in rural areas

will still increase from 11.7% to 24.3% during this period.


Table 3.1 and 3.2 further decompose the one-person household by age and rural/urban areas. It is

shown that the proportion of the elderly who live alone among all one-person households will

increase from 3.6% in 2010 to 12.5% in 2050. As a result, in 2010, only about26% one-person

households consists of an elderly; in contrast, the rate increases to 42% by 2050. In the urban

areas, the youth maintains the major force of living alone in this projection period; however in

the rural area, the number of elderly one-person households will increase very rapidly during this

period and become about 3 times of the young one-person household by 2050.

<Table 3.1 and 3.2 are about here>

The age-gender-rural/urban-marital status specific projections reveal more detailed scenarios on

the one-person household in China (Figure 1A and 1B). For the rural China, the majority of

OPH remains to be widowed in 2010 & 2050, NOT the young unmarried people.

There is currently a large group of young unmarried people living alone, both female and male;

however, in 2050, this young group significantly decline. Widowhood maintains to be a primary

reason of living alone for the elderly population. It is also interesting to see that there will be a

large group of never-married old man at ages of 60 to 80 rising up as a significant source of one-

person household by the year of 2050 reflecting the skewed sex rations as a result of the one-

child policy. In the urban areas, the decline (it does not decrease, it increases now.) of the young

unmarried group and the significant role of widowhood for living alone in old age are similar as

the rural part of China. However in the next four decades, we expect to see significantly more

middle-aged people unmarried individuals who live alone. In addition, for middle-age men,

divorce is becoming another major reason for living alone.

<Figure 1A and 1B are about here>

One-person Household in Hebei Province

The proportion of one-person household in Hebei province is 9.3% in 2010 and 16.0% in 2050,

both of which are lower than the national average, i.e. 13.8% and 22.1% (See Table 4). The

changes of the one-person households in rural areas of Hebei province are similar to the national

results, and it is worth mentioning that the young one-person household with age less than 65

will be 7.1% by 2050 in rural Hebei, higher than the national level as 4.4%. However the urban

areas of Hebei have a different scenario such that the proportion of one-person household is

significantly lower than the national average from 2010 and 2050. In particular, when the urban

households were decomposed to young and old groups, the rates of young people who live alone

in urban Hebei are much less than the national averages (6.6 % versus 15.2% in 2010 and 8.6%

versus 13.9% in 2050).


As can been seen from Figure 2A, the young unmarried group, and old widowed group are the

major sources of one-person household in the rural part of Hebei province. For rural men,

singlehood in the middle age is also a main reason of living alone. And such patterns will remain

consistent from 2010 to 2050. For the urban areas of Hebei (see Figure 2B), the unmarried status

is not a main reason to live alone for young persons, whereas the middle-age divorced men and

the widows will make up a substantial proportion for people who live alone by the year of 2050.


One-person Household in Beijing City

As one of largest cities of China, Beijing has a higher proportion of one-person household than

the national average (Table 5). In 2010, about one fifth of the local households are one-person

household; in 2050, about 40% of them will be people living alone. Because Beijing is highly

urbanized and most of the local population is urban residents, the urban projections are very

similar to the projection of the entire population: the proportions of both young and old one-

person households among the total one-person households by the year of 2050 are higher than

the national average. However, these two types of one-person households will experience

different trajectories in the following four decades: the old group is expected to drastically

increase from 3.7% in 2010 to about 20.0% in 2050, whereas the young group rises only slightly

from 18.2% to 20.3%. For the rural area in Beijing, by 2050, the proportions of both young and

old one-person households are also higher than the national level, whereas most people who live

alone are above age 65, which is exactly the national pattern.


As can be seen in Figure 3A, at Beijing city, young people who never get married are the current

major source of one-person household, either in rural or urban areas. Moreover, in the next four

decades, remaining single will not only be a main reason for the youth to live alone, but also for

the middle-aged and the elderly population (Figure 3B). This is true both for rural and urban,

female and male, in the Beijing city by 2050.


CONCLUSION

This paper applies a new household projection method, ProFamy, to forecast the changes of one-

person households in China from 2010 to 2050 with additional two subnational projections in

Hebei province and Beijing city. We conduct a series of projections for the country as a whole,

Hebei province, and Beijing city, which shows a good variety of change patterns for the one-

person households in China. The projections and have important policy implications, which can

inform the government and related agencies to better plan for future needs.

From the projections, we see that the one-person households will increase very rapidly in China

and will become one of the major types of living arrangement for Chinese in the next several

decades. From 2010 to 2050, there will be more young people who live alone and they are more

likely to live in urban areas. However, with regard to the increase rate of the proportions in the

all households from 2010 to 2050, the one-person household will rise more rapidly in rural areas

(89.8% in rural versus 30.0% in urban) and for the elderly population (265.3% for old versus

11.8% for young). This could be an outcome of immigration of the young population from rural

to urban areas. Consequently, by 2050, the elderly one-person households will exceed the young

in rural areas (9.8 million versus 3.1 million).

We show three important trends in the marital status-specific projections for China. Firstly, the

one-person household due to widowhood is increasing fast in China, which is related to the

growing elderly population and the lack of children available to live with. Second, as a result of

postponed marriages, divorce, and the skewed sex ratios, people in the middle and old age are

replacing the youth who are not married as a major source of one-person household in China,

especially for rural men, in the next few decades. The severe gender imbalance in China is

leaving more men unmarried during their lifetime due to the difficulty to find wives, which is

particularly true in rural areas. Additionally, the urban women who remain single until later ages

are also expected to increase, which is more associated with a life style due to the higher

education and employment in the cities. Finally, people who divorce in the middle or later age is

expected to become a substantial group of one-person households. This again may be related to

the higher education and employment rate of women and the greater normative acceptance of

divorce in the society in the next few decades.

Our projections at the subnational levels reveal the important varieties which are hidden under

the national trends in general. We find that, as one of the most economically advanced areas of

China, Beijing city has very unique trends in one-person household in the following four decades,

namely the drastic increase of unmarried people in the middle and old age. Delaying or forgoing

marriage has recently become a trend among people in the metropolitan areas of China, and our

projection has shown how significantly such a trend could affect the population and household

structure in the near future. Because many other cities/provinces will likely follow the same

trends of Beijing with regard to the marriage behaviors of its residents, the projections of Beijing

could be very suggestive for many other parts of China beyond the current projection period. In

contrast to Beijing, the future trend of one-person household in Hebei represents a different

model: among females, the widowhood at late age will be the major source of one-person

household; and for the males, living alone will be driven by mechanisms such as not being

married in young and middle age, divorce in middle age, and widowhood in old age. Such as a

mixed pattern could be applied to many other Chinese provinces which is still not as developed

as the metropolitan areas.

These projections contribute to the recent literature on one-person households. The projections

reveal the fast rate of increase of the one-person household in the next few decades in China and

the vast heterogeneity across different regions in the country. These trends reflect demographic

consequences from the one-child policy, lower fertility, skewed sex ratio, and changes in social

development such as the increase of education and labor force population, as well as normative

changes in postponing or even forgoing marriages among young Chinese population. Our results

suggest there is an urgent need for the Chinese policy makers to be better prepared for a future of

significant growth of people who live alone.

Our projections is limited in the sense that certain assumptions applied in our projection may not

be accurate in the long run, although these assumptions have represented the most likely

scenarios based on the expert opinions and our best efforts of justification. Therefore, as many

other projections alike, this study should be consider as exploratory, and cautions are definitely

needed when these projections are used. We also call for more future work to further improve

such projections.

References

Chong A. and Yeung, W.J. 2013. Temporal-spatial patterns of one-person households in China,

1982 – 2005: Demographic trends, economic development and internal migration. Paper

presented at the 2013 International Sociological Association RC28 meeting in Brisbane,

Australia.

Coale, A. J. 1984. Life table construction on the basis of two enumerations of a closed

population. Population Index, 50, 193-213

Coale, A. J. 1985. An extension and simplification of a new synthesis of age structure and

growth. Asian and Pacific Forum, 12, 5–8.

Crone, T.M. and Mills, L.O. 1991. Forecasting trends in the housing stock using age-specific

demographic projections. Journal of Housing Research 2(1): 1-20.

Feng, Q., Z. Wang, D. Gu, and Y. Zeng. 2011. “Household Vehicle Consumption Forecasting in

the United States, 2000 to 2015.” International Journal of Market Research 53(5):593-618.

Guo, Z. (2008). Study on changes of China family households in recent years. Chinese Journal

of Population Science(3), 2-10.

Mason, A. and R Racelis. 1992. A comparison of four methods for projecting households.

International Journal of Forecasting 8: 509–527.

National Bureau of Statistics of China. (2013). China Statistics: National Statistics. Retrieved

30 November 2013, from http://www.stats.gov.cn/enGliSH/

Nishioka, Hachiro, Yasuyo Koyama, Toru Suzuki, Masakazu Yamauchi, and Keita Suga. 2011.

Household Projections by Prefecture in Japan: 2005 – 2030: Outline of Results and

Methods. The Japanese Journal of Population 9(1):78-133.

Prskawetz, A., Jiang, L., and O’Neill, B.C. 2004. Demographic composition and projections of

car use in Austria, in T. Fent and A. Prskawetz (eds), Vienna yearbook of population

research 2004, Vienna, Austria: Austrian Academy of Sciences Press, 274-326

Smith, S.K., S. Rayer and E. A. Smith. 2008. Aging and Disability: Implications for the Housing

Industry and Housing Policy in the United States. Journal of the American Planning

Association 74(3):289-305.

Spicer, K., Diamond, I. and Ni Bhrolchain, M. 1992. Into the twenty-first century with British

households. International Journal of Forecasting 8: 529–539.

Stupp, P. W. 1988. A general procedure for estimating intercensal age schedules. Population

Index, 54, 209–234.

United Nations. 1973. Methods of Projecting Households and Families. New York: United Nation

Publications.

United Nations. 1989. Projection Methods for Integrating Population Variables into

Development Planning. New York: United Nation Publications.

Zeng, Y. 2013. Considering current population policy in China. Administration Reform 5:24-31

(in Chinese).

Zeng, Y., K.C. Land, Z. Wang, and D. Gu. 2006. U.S. Family Household Dynamics and

Momentum-- Extension of ProFamy Method and Application. Population Research and

Policy Review 25:1-41.

Zeng, Y., Land K.C., Wang, Z., and Gu, D. 2013. Household and living arrangement projections

at the subnational level: an extended cohort-component approach. Demography

50(3):827-52.

Zeng, Y., J.W. Vaupel, and Z. Wang. 1997. A Multidimensional Model for Projecting Family

Households -- with an Illustrative Numerical Application. Mathematical Population

Studies 6: 187-216.

http://www.stats.gov.cn/enGliSH/

Zeng, Y., J.W. Vaupel, and Z. Wang. 1998. Household Projection Using Conventional

Demographic Data. Population and Development Review 24:59-87.

Zeng, Y., Z. Wang, L. Jiang, and D. Gu. 2008. Future trend of family households and elderly

living arrangement in China. GENUS - An International Journal of Demography LXIV

(No. 1-2): 9-36.

Zhao, Z., & Chen, W. (2008). Changes in household formation and composition in China since

the mid-twentieth century. Journal of Population Research, 25(3), 267-286.

13

Table 1: Summary Parameters Used for Projections in China, Hebei Province and Beijing City

China Total Rural Urban

2010 2030 2050 2010 2030 2050 2010 2030 2050

Total fertility rate 1.63 1.81 1.77 2.01 2.15 2.13 1.24 1.67 1.72

Male life expectancy at birth (years) 72.1 76.5 80.0 70.1 73.6 76.5 74.2 77.7 80.5

Female life expectancy at birth (years) 75.9 80.6 83.6 73.9 77.6 80.7 77.9 81.8 84

General marriage rate (per thousand) 64.0 62.0 61.0 68.0 68.0 67.0 60.0 60.0 60.0

General divorce rate (per thousand) 4.0 5.0 5.0 2.0 2.0 3.0 6.0 6.0 6.0

Proportion of urban population 50% 71% 87%

Hebei Total Rural Urban

2010 2030 2050 2010 2030 2050 2010 2030 2050



Female life expectancy at birth (years) 76.3 80.8 84.1 74.7 78.3 81.3 78.3 82.3 85.0




Beijing Total Rural Urban

2010 2030 2050 2010 2030 2050 2010 2030 2050



Female life expectancy at birth (years) 82.6 84.3 85.3 80.6 81.4 82.5 82.9 84.5 85.5




14

Table 2: Projection of Households by Type in China, 2010 and 2050

China Rural Urban

2010 2050 Annual change rate (%)



One generation

One person only 55,794,936 162,075,488 2.70 22,568,502 17,078,914 -0.69 33,226,436 144,996,576 3.75

13.92% 29.34% 11.65% 24.34% 16.05% 30.07%

One person and other 4,621,974 15,394,662 3.05 1,323,850 1,001,830 -0.69 3,298,124 14,392,832 3.75

1.15% 2.79% 0.68% 1.43% 1.59% 2.98%

Married couple 74,475,864 143,243,664 1.65 32,632,878 16,574,793 -1.68 41,842,988 126,668,864 2.81

18.59% 25.93% 16.84% 23.62% 20.22% 26.27%

Two generation

Married couple 171,045,184 154,582,400 -0.25 83,076,128 19,615,702 -3.54 87,969,056 134,966,704 1.08

42.69% 27.99% 42.88% 27.96% 42.50% 27.99%

Lone mother 13,496,315 19,042,720 0.86 5,964,189 6,188,565 0.09 7,532,126 12,854,155 1.35

3.37% 3.45% 3.08% 8.82% 3.64% 2.67%

Lone father 8,611,564 16,315,165 1.61 3,828,130 4,007,238 0.11 4,783,434 12,307,927 2.39

2.15% 2.95% 1.98% 5.71% 2.31% 2.55%

Three generation 72,661,904 41,714,092 -1.38 44,347,124 5,700,301 -5.00 28,314,780 36,013,792 0.60

18.13% 7.55% 22.89% 8.12% 13.68% 7.47%

Total 400,707,744 552,368,192 0.81 193,740,800 70,167,344 -2.51 206,966,944 482,200,832 2.14

15

Table 3.1: Percentage of One-person Households among Total Households by Age and Rural/Urban Areas, China, from 2010 to 2050

2010 2015 2020 2025 2030 2035 2040 2045 2050

% Change from 2010-2050

China 13.92 19.14 20.71 21.45 23.09 25.02 26.73 28.27 29.34 110.78

young (<65) 10.31 14.89 15.68 15.46 15.67 15.91 16.12 16.66 16.9 63.92

old (>=65) 3.61 4.25 5.04 5.99 7.42 9.1 10.6 11.6 12.45 244.88

Rural Areas 11.65 16.17 17.41 17.98 18.84 20.07 21.48 22.9 24.34 108.93

young (<65) 7.44 10.82 10.71 9.78 8.57 7.53 7.13 7.28 7.34 -1.34

old (>=65) 4.21 5.35 6.69 8.2 10.27 12.54 14.35 15.62 17 303.80

Urban Areas 16.05 21.38 22.7 23.12 24.69 26.54 28.04 29.32 30.07 87.35

young (<65) 13 17.95 18.66 18.2 18.34 18.5 18.37 18.5 18.29 40.69

old (>=65) 3.05 3.43 4.04 4.92 6.34 8.04 9.67 10.82 11.78 286.23

Table 3.2: Size of One-person Households among Total Households by Age and Rural/Urban Areas, China, from 2010 to 2050

2010 2015 2020 2025 2030 2035 2040 2045 2050

China 55,794,936 86,213,360 99,600,768 106,794,136 118,459,256 131,803,440 143,704,128 154,457,392 162,075,488

Young (<65) 41,329,884 67,064,324 75,384,552 76,982,880 80,404,120 83,845,184 86,698,640 91,049,432 93,325,808

Old (>=65) 14,465,058 19,149,014 24,216,252 29,811,242 38,055,124 47,958,220 57,005,504 63,407,968 68,749,704

Rural Areas 22,568,502 31,238,376 31,457,076 29,143,966 26,451,362 24,932,878 23,079,540 20,437,252 17,078,914

Young (<65) 14,419,148 20,910,686 19,358,904 15,858,601 12,031,938 9,354,156 7,663,850 6,496,968 5,150,806

Old (>=65) 8,149,361 10,327,695 12,098,174 13,285,362 14,419,425 15,578,720 15,415,693 13,940,280 11,928,110

Urban Areas 33,226,436 54,974,984 68,143,696 77,650,168 92,007,896 106,870,560 120,624,592 134,020,144 144,996,576

Young (<65) 26,910,734 46,153,640 56,025,644 61,124,276 68,372,184 74,491,032 79,034,792 84,552,464 88,175,000

Old (>=65) 6,315,696 8,821,320 12,118,077 16,525,879 23,635,700 32,379,502 41,589,812 49,467,688 56,821,596

16

Figure 1A: Number of One-person Household by Gender, Age and Marital Status in Rural China, 2010 and 2050

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Figure 1B: Number of One-person Household by Gender, Age and Marital Status in Urban China, 2010 and 2050

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Table 4: Percentage of One-person Households among Total Households by Age and Rural/Urban Areas, Hebei province, from 2010 to 2050

2010 2015 2020 2025 2030 2035 2040 2045 2050 % Change

from 2010-2050

Hebei Province 9.25 12.22 12.53 13.42 14.06 14.46 15.15 15.66 16.04 73.41 Young (<65) 5.93 8.97 8.95 9.36 9.32 8.85 8.78 8.69 8.24 38.95

Old (>=65) 3.32 3.25 3.58 4.06 4.74 5.61 6.37 6.97 7.80 134.94

Rural Areas 8.94 10.10 10.87 12.22 13.41 13.87 15.06 16.19 17.18 92.17

Young (<65) 5.42 6.21 6.46 7.29 7.73 6.67 6.78 7.13 7.09 30.81

Old (>=65) 3.52 3.89 4.40 4.93 5.68 7.19 8.29 9.06 10.09 186.65

Urban Areas 9.64 13.96 13.71 14.18 14.42 14.71 15.18 15.47 15.67 62.55

Young (<65) 6.57 11.25 10.71 10.67 10.21 9.76 9.57 9.26 8.62 31.20

Old (>=65) 3.07 2.72 3.00 3.51 4.21 4.95 5.61 6.22 7.04 129.32

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Figure 2A: Number of One-person Household by Gender, Age and Marital Status in Rural Hebei, 2010 and 2050

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Figure 2B: Number of One-person Household by Gender, Age and Marital Status in Urban Hebei, 2010 and 2050

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Table 5: Percentage of One-person Households among Total Households by Age and Rural/urban Areas, Beijing City, from 2010 to 2050

2010 2015 2020 2025 2030 2035 2040 2045 2050 % Change

from 2010-2050

Beijing City 20.27 23.62 25.85 27.92 30.20 31.72 34.06 36.78 39.71 95.91 Young (<65) 16.72 19.76 20.99 21.62 21.96 21.48 21.56 20.62 19.62 17.34

Old (>=65) 3.56 3.86 4.87 6.30 8.24 10.24 12.50 16.15 20.10 464.61

Rural Areas 12.24 13.68 15.43 16.87 18.57 20.62 23.39 25.83 29.37 139.95

Young (<65) 9.13 10.14 10.80 10.66 10.04 9.47 9.15 8.28 7.27 -20.37

Old (>=65) 3.11 3.54 4.63 6.21 8.54 11.15 14.24 17.56 22.09 610.29

Urban Areas 21.86 25.33 27.46 29.44 31.60 32.89 35.01 37.56 40.28 84.26

Young (<65) 18.21 21.42 22.55 23.13 23.40 22.75 22.67 21.51 20.30 11.48

Old (>=65) 3.65 3.91 4.90 6.32 8.20 10.15 12.35 16.05 19.98 447.40

22

Figure 3A: Number of One-person Household by Gender, Age and Marital Status in Rural Beijing, 2010 and 2050

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Figure 3B: Number of One-person Household by Gender, Age and Marital Status in Urban Beijing, 2010 and 2050

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living alone in china: projection of one-person household

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