China Living Standards Survey (CLSS) consists of one household survey and one community (village) survey, conducted in Hebei and Liaoning Provinces (northern and northeast China) in July 1995 and July 1997 respectively. Five villages from each three sample counties of each province were selected (six were selected in Liaoyang County of Liaoning Province because of administrative area change). About 880 farm households were selected from total thirty-one sample villages for the household survey. The same thirty-one villages formed the samples of community survey. This document provides information on the content of different questionnaires, the survey design and implementation, data processing activities, and the different available data sets.
The China Living Standards Survey (CLSS) was conducted only in Hebei and Liaoning Provinces (northern and northeast China).
Sample survey data [ssd]
The CLSS sample is not a rigorous random sample drawn from a well-defined population. Instead it is only a rough approximation of the rural population in Hebei and Liaoning provinces in Northeastern China. The reason for this is that part of the motivation for the survey was to compare the current conditions with conditions that existed in Hebei and Liaoning in the 1930’s. Because of this, three counties in Hebei and three counties in Liaoning were selected as "primary sampling units" because data had been collected from those six counties by the Japanese occupation government in the 1930’s. Within each of these six counties (xian) five villages (cun) were selected, for an overall total of 30 villages (in fact, an administrative change in one village led to 31 villages being selected). In each county a "main village" was selected that was in fact a village that had been surveyed in the 1930s. Because of the interest in these villages 50 households were selected from each of these six villages (one for each of the six counties). In addition, four other villages were selected in each county. These other villages were not drawn randomly but were selected so as to "represent" variation within the county. Within each of these villages 20 households were selected for interviews. Thus the intended sample size was 780 households, 130 from each county.
Unlike county and village selection, the selection of households within each village was done according to standard sample selection procedures. In each village, a list of all households in the village was obtained from village leaders. An "interval" was calculated as the number of the households in the village divided by the number of households desired for the sample (50 for main villages and 20 for other villages). For the list of households, a random number was drawn between 1 and the interval number. This was used as a starting point. The interval was then added to this number to get a second number, then the interval was added to this second number to get a third number, and so on. The set of numbers produced were the numbers used to select the households, in terms of their order on the list.
In fact, the number of households in the sample is 785, as opposed to 780. Most of this difference is due to a village in which 24 households were interviewed, as opposed to the goal of 20 households
Face-to-face [f2f]
Household Questionnaire
The household questionnaire contains sections that collect data on household demographic structure, education, housing conditions, land, agricultural management, household non-agricultural business, household expenditures, gifts, remittances and other income sources, and saving and loans. For some sections (general household information, schooling, housing, gift-exchange, remittance, other income, and credit and savings) the individual designated by the household members as the household head provided responses. For some other sections (farm land, agricultural management, family-run non-farm business, and household consumption expenditure) a member identified as the most knowledgeable provided responses. Identification codes for respondents of different sections indicate who provided the information. In sections where the information collected pertains to individuals (employment), whenever possible, each member of the household was asked to respond for himself or herself, except that parents were allowed to respond for younger children. Therefore, in the case of the employment section it is possible that the information was not provided by the relevant person; variables in this section indicate when this is true.
The household questionnaire was completed in a one-time interview in the summer of 1995. The survey was designed so that more sensitive issues such as credit and savings were discussed near the end. The content of each section is briefly described below.
Section 0 SURVEY INFORMATION
This section mainly summarizes the results of the survey visits. The following information was entered into the computer: whether the survey and the data entry were completed, codes of supervisor’s brief comments on interviewer, data entry operator, and related revising suggestion (e.g., 1. good, 2. revise at office, and 3. re-interview needed). Information about the date of interview, the names of interviewer, supervisor, data enterer, and detail notes of interviewer and supervisor were not entered into the computer.
Section 1 GENERAL HOUSEHOLD INFORMATION
1A HOUSEHOLD STRUCTURE 1B INFORMATION ABOUT THE HOUSEHOLD MEMBERS’ PARENTS 1C INFORMATION ABOUT THE CHILDREN WHO ARE NOT LIVING IN HOME
Section 1A lists the personal id code, sex, relationship to the household head, ethnic group, type of resident permit (agricultural [nongye], non-agricultural [fei nongye], or no resident permit), date of birth, marital status of all people who spent the previous night in that household and for household members who are temporarily away from home. The household head is listed first and receives the personal id code 1. Household members were defined to include “all the people who normally live and eat their meals together in this dwelling.” Those who were absent more than nine of the last twelve months were excluded, except for the head of household. For individuals who are married and whose spouse resides in the household, the personal id number of the spouse is noted. By doing so, information on the spouse can be collected by appropriately merging information from the section 1A and other parts of the survey.
Section 1B collects information on the parents of all household members. For individuals whose parents reside in the household, parents’ personal id numbers are noted, and information can be obtained by appropriately merging information from other parts of the survey. For individuals whose parents do not reside in the household, information is recorded on whether each parent is alive, as well as their schooling and occupation.
Section 1C collects information for children of household members who are not living in home. Children who have died are not included. The information on the name, sex, types of resident permit, age, education level, education cost, reasons not living in home, current living place, and type of job of each such child is recorded.
Section 2 SCHOOLING
In Section 2, information about literacy and numeracy, school attendance, completion, and current enrollment for all household members of preschool age and older. The interpretation of pre-school age appears to have varied, with the result that while education information is available for some children of pre-school age, not all pre-school children were included in this section. But for ages 6 and above information is available for nearly all individuals, so in essence the data on schooling can be said to apply all persons 6 age and above. For those who were enrolled in school at the time of the survey, information was also collected on school attendance, expenses, and scholarships. If applicable, information on serving as an apprentice, technical or professional training was also collected.
Section 3 EMPLOYMENT
3A GENERAL INFORMATION 3B MAJOR NON-FARM JOB IN 1994 3C THE SECOND NON-FARM JOB IN 1994 3D OTHER EMPLOYMENT ACTIVITIES IN 1994 3E SEARCHING FOR NON-FARM JOB 3F PROCESS FOR GETTING MAJOR NON-FARM JOB 3G CORVEE LABOR
All individuals age thirteen and above were asked to respond to the employment activity questions in Section 3. Section 3A collects general information on farm and non-farm employment, such as whether or not the household member worked on household own farm in 1994, when was the last year the member worked on own farm if he/she did not work in 1994, work days and hours during busy season, occupation and sector codes of the major, second, and third non-farm jobs, work days and total income of these non-farm jobs. There is a variable which indicates whether or not the individual responded for himself or herself.
Sections 3B and 3C collect detailed information on the major and the second non-farm job. Information includes number of months worked and which month in 1994 the member worked on these jobs, average works days (or hours) per month (per day), total number of years worked for these jobs by the end of 1994, different components of income, type of employment contracts. Information on employer’s ownership type and location was also collected.
Section 3D collects information on average hours spent doing chores and housework at home every day during non-busy and busy season. The chores refer to cooking, laundry, cleaning, shopping, cutting woods, as well as small-scale farm yard animals raising, for example, pigs or chickens. Large-scale animal
The graph shows the Consumer Price Index (CPI) in China as of December 2024, by sector and area. That month, the CPI for transportation and communication in urban areas resided at 97.7 index points. Measuring inflation The Consumer Price Index (CPI) is an economic indicator that measures changes in the price level of a representative basket of consumer goods and services. It is calculated by taking price changes for each item in the market basket and averaging them. Goods and services are weighted according to their significance. The CPI can be used to assess the price changes related to the cost of living. It is also useful for identifying periods of inflation and deflation. A significant rise in CPI during a short period of time denotes inflation and a significant drop during a short period of time suggests deflation. Development of inflation in China Annual projections of China’s inflation rate forecast by the IMF estimate a relatively low increase in prices in the coming years. The implications of low inflation are two-fold for a national economy. On the one hand, price levels remain largely stable which may lead to equal or increased spending levels by domestic consumers. On the other hand, low inflation signifies an expansion slowdown of the economy, as is reflected by China’s gross domestic product growth. In recent years, inflation rates in rural areas have on average been slightly higher than in the cities. This reflects a shift of economic growth from the largest cities and coastal regions to the inner provinces and the countryside. Higher price levels in rural areas in turn relate to higher inflation rates of food products.
South Korea's capital Seoul had the highest cost of living among megacities in the Asia-Pacific region in 2024, with an index score of 70.3. Japan's capital Tokyo followed with a cost of living index score of 57.4. AffordabilityIn terms of housing affordability, Chinese megacity Shanghai had the highest rent index score in 2024. Affordability has become an issue in certain megacities across the Asia-Pacific region, with accommodation proving expensive. Next to Shanghai, Japanese capital Tokyo and South Korean capital Seoul boast some of the highest rent indices in the region. Increased opportunities in megacitiesAs the biggest region in the world, it is not surprising that the Asia-Pacific region is home to 28 megacities as of January 2024, with expectations that this number will dramatically increase by 2030. The growing number of megacities in the Asia-Pacific region can be attributed to raised levels of employment and living conditions. Cities such as Tokyo, Shanghai, and Beijing have become economic and industrial hubs. Subsequently, these cities have forged a reputation as being the in-trend places to live among the younger generations. This reputation has also pushed them to become enticing to tourists, with Tokyo displaying increased numbers of tourists throughout recent years, which in turn has created more job opportunities for inhabitants. As well as Tokyo, Shanghai has benefitted from the increased tourism, and has demonstrated an increasing population. A big factor in this population increase could be due to the migration of citizens to the city, seeking better employment possibilities.
In 2024, the average annual per capita disposable income of rural households in China was approximately 23,119 yuan, roughly 43 percent of the income of urban households. Although living standards in China’s rural areas have improved significantly over the past 20 years, the income gap between rural and urban households is still large. Income increase of China’s households From 2000 to 2020, disposable income per capita in China increased by around 700 percent. The fast-growing economy has inevitably led to the rapid income increase. Furthermore, inflation has been maintained at a lower rate in recent years compared to other countries. While the number of millionaires in China has increased, many of its population are still living in humble conditions. Consequently, the significant wealth gap between China’s rich and poor has become a social problem across the country. However, in recent years rural areas have been catching up and disposable income has been growing faster than in the cities. This development is also reflected in the Gini coefficient for China, which has decreased since 2008. Urbanization in China The urban population in China surpassed its rural population for the first time in 2011. In fact, the share of the population residing in urban areas is continuing to increase. This is not surprising considering remote, rural areas are among the poorest areas in China. Currently, poverty alleviation has been prioritized by the Chinese government. The measures that the government has taken are related to relocation and job placement. With the transformation and expansion of cities to accommodate the influx of city dwellers, neighboring rural areas are required for the development of infrastructure. Accordingly, land acquisition by the government has resulted in monetary gain by some rural households.
According to latest figures, the Chinese population decreased by 1.39 million to around 1.408 billion people in 2024. After decades of rapid growth, China arrived at the turning point of its demographic development in 2022, which was earlier than expected. The annual population decrease is estimated to remain at moderate levels until around 2030 but to accelerate thereafter. Population development in China China had for a long time been the country with the largest population worldwide, but according to UN estimates, it has been overtaken by India in 2023. As the population in India is still growing, the country is very likely to remain being home of the largest population on earth in the near future. Due to several mechanisms put into place by the Chinese government as well as changing circumstances in the working and social environment of the Chinese people, population growth has subsided over the past decades, displaying an annual population growth rate of -0.1 percent in 2024. Nevertheless, compared to the world population in total, China held a share of about 18 percent of the overall global population in 2022. China's aging population In terms of demographic developments, the birth control efforts of the Chinese government had considerable effects on the demographic pyramid in China. Upon closer examination of the age distribution, a clear trend of an aging population becomes visible. In order to curb the negative effects of an aging population, the Chinese government abolished the one-child policy in 2015, which had been in effect since 1979, and introduced a three-child policy in May 2021. However, many Chinese parents nowadays are reluctant to have a second or third child, as is the case in most of the developed countries in the world. The number of births in China varied in the years following the abolishment of the one-child policy, but did not increase considerably. Among the reasons most prominent for parents not having more children are the rising living costs and costs for child care, growing work pressure, a growing trend towards self-realization and individualism, and changing social behaviors.
According to latest figures published by the National Bureau of Statistics of China, the average annual inflation rate in China ranged at around 0.2 percent in 2024 compared to the previous year. This was lower than formerly expected by the IMF. For 2025, projections by the IMF published in October 2024 expected the inflation rate to reach around 1.7 percent. The monthly inflation rate in China dropped to negative values in the second half of 2023 and remained comparatively low in 2024. Calculation of inflation The inflation rate is calculated based on the Consumer Price Index (CPI) for China. The CPI is computed using a product basket that contains a predefined range of products and services on which the average consumer spends money throughout the year. Included are expenses for groceries, clothes, rent, power, telecommunications, recreational activities, and raw materials (e.g. gas, oil), as well as federal fees and taxes. The product basked is adjusted every five years to reflect changes in consumer preference and has been updated in 2020 for the last time. The inflation rate is then calculated using changes in the CPI. As the inflation of a country is seen as a key economic indicator, it is frequently used for international comparison. China's inflation in comparison Among the main industrialized and emerging economies worldwide, China displayed comparatively low inflation in 2023 and 2024. In previous years, China's inflation ranged marginally above the inflation rates of established industrialized powerhouses such as the United States or the European Union. However, this changed in 2021, as inflation rates in developed countries rose quickly, while prices in China only increased moderately. According to IMF estimates for 2024, Zimbabwe was expected to be the country with the highest inflation rate, with a consumer price increase of about 561 percent compared to 2023. In 2023, Turkmenistan had the lowest price increase worldwide with prices actually decreasing by about 1.7 percent.
Residential Real Estate Market Size 2024-2028
The residential real estate market size is forecast to increase by USD 482.1 billion at a CAGR of 4.6% between 2023 and 2028.
The market is experiencing significant growth, driven by increasing demand from a growing population and urbanization trends. This demand is further fueled by marketing initiatives from real estate developers and agents, who are leveraging digital platforms and creative campaigns to attract buyers. However, regulatory uncertainty poses a challenge to market growth, with varying regulations and policies in different regions impacting investment decisions. For companies seeking to capitalize on market opportunities, it is essential to stay informed of regulatory changes and adapt strategies accordingly. Additionally, collaboration with local experts and partnerships with regulatory bodies can help navigate complex regulatory landscapes and ensure compliance. Overall, the market presents significant opportunities for growth, but requires a strategic approach to address regulatory challenges and effectively target demand. Companies that can navigate these challenges and adapt to local market conditions will be well-positioned to succeed in this dynamic market.
What will be the Size of the Residential Real Estate Market during the forecast period?
Request Free SampleThe market continues to exhibit activity, driven by strong economic fundamentals and population growth. In nominal terms, the market size reached an all-time high in the latest fiscal year, with discerning buyers demonstrating continued interest in spacious accommodations. However, macroeconomic headwinds, such as rising interest rates and inflation, pose challenges for some potential homebuyers. Economic factors, including GDP per capita and purchasing power, remain essential support for the housing market. Despite these conditions, property launches in the luxury residential sector have shown resilience, catering to the demand for high-end living spaces. Residential construction remains a critical component of the market, with new housing units being added to meet the growing demand for homes. Overall, the market is expected to remain a significant contributor to the economy, offering opportunities for both investors and homebuyers.
How is this Residential Real Estate Industry segmented?
The residential real estate industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. Mode Of BookingSalesRental/LeaseTypeApartments and condominiumsLanded houses and villasGeographyAPACChinaJapanNorth AmericaUSEuropeGermanyUKSouth AmericaMiddle East and Africa
By Mode Of Booking Insights
The sales segment is estimated to witness significant growth during the forecast period.
Get a glance at the market report of share of various segments Request Free Sample
The Sales segment was valued at USD 896.60 billion in 2018 and showed a gradual increase during the forecast period.
Regional Analysis
APAC is estimated to contribute 54% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
For more insights on the market size of various regions, Request Free Sample
The market in the Asia Pacific (APAC) region held the largest market share in 2023 and is anticipated to continue leading the market growth during the forecast period. Key drivers of this expansion include population growth and increasing purchasing power, leading to a in demand for spacious accommodations. Rapid urbanization and economic fundamentals, such as GDP per capita, have fueled the construction of new housing units, particularly in countries like India and China. Furthermore, domestic demand and foreign homebuyers have contributed to the unsold inventory overhang, creating investment opportunities in underconstruction properties. Despite these positive indicators, challenges persist, including affordability concerns and critical input costs. In the context of the US housing market, the residential real estate sector offers investment opportunities through traditional options, such as home ownership and rental cash flow, as well as low-risk methods, like investment portfolios. Key economic factors, such as interest rates and supply metrics, impact residential property prices, which may vary in real and nominal terms. The market is also influenced by changing consumer preferences, regulatory reforms, and technological transformation, including home automation and cutting-edge strategies.
Market Dynamics
Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holi
China is the largest labor force market in the world. China’s economic prosperity wouldn’t exist without the large number of people working in this country. With increasing living standards and growing inflation, the wages of employees in China are increasing as well. As of 2022, average wages in China increased to114,029 yuan from 47,593 yuan in 2012.
Wage gap between regions
The wages vary in China depending on sector, position, gender and region like in any other country. Since China’s different regions have developed unequally, the wage gaps between people working in different regions can also be very large. This is a reason for no single minimum wage being set for the entire nation. The local governments set minimum wages based on local living standards. Considering the city tier, the wage standards are higher in cities with higher rankings. Shanghai and Beijing have the highest minimum wage standards in China. Although the minimum wages in China have been increasing, the standards are still lower than in developed countries.
Challenges of increasing labor costs
Increasing wages also make the labor force market less attractive. Affected by increasing labor costs and the China-United States trade war, many companies are transferring their investment destinations, especially in the manufacturing sector. Local governments are also taking measures to ensure the living costs remain at a reasonable level to retain companies and employees. These measures include regulating the residential housing market more strictly.
A regional breakdown of the Consumer Price Index (CPI) in China reveals considerable variations across different regions. In December 2024, Hainan province displayed a CPI of about 98.4 points (same month previous year = 100), whereas the CPI in Tibet reached 101.2 points. Consumer price development in China The Consumer Price Index measures the average changes over time in the price level of a market basket of consumer goods and services purchased by consumers. It is closely related to the inflation rate. The consumer inflation rate is derived from the annual percentage increase of the CPI. After 2011, China experienced a slight decrease in domestic inflation. Between 2014 and 2018, the annual inflation rate ranged at around two percent or lower. In 2019, inflation increased again to 2.9 percent and remained high during 2020, but is forcast to decrease in the coming years. Monthly inflation rates peaked at 5.4 percent in January 2020 due to the coronavirus pandemic, but declined quickly in the following months and reached negative values in November 2020. Regional and sectoral inflation rates In recent years, inflation rates in the largest cities and developed regions often remained below those in developing regions in the inner provinces. The CPI in rural regions was on average slightly higher than in urban areas. The annual CPI of food, tobacco and liquor in China ranged among the highest during 2020 - mainly driven by rising pork and meat prices, whereas the transportation and communication’s CPI was one of the lowest. With the travel sector recovering from the coronavirus pandemic in the first half of 2021, monthly prices for transportation started to increase again.
In 2024, there were around 719 million male inhabitants and 689 million female inhabitants living in China, amounting to around 1.41 billion people in total. China's total population decreased for the first time in decades in 2022, and population decline is expected to accelerate in the upcoming years. Birth control in China From the beginning of the 1970s on, having many children was no longer encouraged in mainland China. The one-child policy was then introduced in 1979 to control the total size of the Chinese population. According to the one-child policy, a married couple was only allowed to have one child. With the time, modifications were added to the policy, for example parents living in rural areas were allowed to have a second child if the first was a daughter, and most ethnic minorities were excepted from the policy. Population ageing The birth control led to a decreasing birth rate in China and a more skewed gender ratio of new births due to boy preference. Since the negative economic and social effects of an aging population were more and more felt in China, the one-child policy was considered an obstacle for the country’s further economic development. Since 2014, the one-child policy has been gradually relaxed and fully eliminated at the end of 2015. However, many young Chinese people are not willing to have more children due to high costs of raising a child, especially in urban areas.
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China Living Standards Survey (CLSS) consists of one household survey and one community (village) survey, conducted in Hebei and Liaoning Provinces (northern and northeast China) in July 1995 and July 1997 respectively. Five villages from each three sample counties of each province were selected (six were selected in Liaoyang County of Liaoning Province because of administrative area change). About 880 farm households were selected from total thirty-one sample villages for the household survey. The same thirty-one villages formed the samples of community survey. This document provides information on the content of different questionnaires, the survey design and implementation, data processing activities, and the different available data sets.
The China Living Standards Survey (CLSS) was conducted only in Hebei and Liaoning Provinces (northern and northeast China).
Sample survey data [ssd]
The CLSS sample is not a rigorous random sample drawn from a well-defined population. Instead it is only a rough approximation of the rural population in Hebei and Liaoning provinces in Northeastern China. The reason for this is that part of the motivation for the survey was to compare the current conditions with conditions that existed in Hebei and Liaoning in the 1930’s. Because of this, three counties in Hebei and three counties in Liaoning were selected as "primary sampling units" because data had been collected from those six counties by the Japanese occupation government in the 1930’s. Within each of these six counties (xian) five villages (cun) were selected, for an overall total of 30 villages (in fact, an administrative change in one village led to 31 villages being selected). In each county a "main village" was selected that was in fact a village that had been surveyed in the 1930s. Because of the interest in these villages 50 households were selected from each of these six villages (one for each of the six counties). In addition, four other villages were selected in each county. These other villages were not drawn randomly but were selected so as to "represent" variation within the county. Within each of these villages 20 households were selected for interviews. Thus the intended sample size was 780 households, 130 from each county.
Unlike county and village selection, the selection of households within each village was done according to standard sample selection procedures. In each village, a list of all households in the village was obtained from village leaders. An "interval" was calculated as the number of the households in the village divided by the number of households desired for the sample (50 for main villages and 20 for other villages). For the list of households, a random number was drawn between 1 and the interval number. This was used as a starting point. The interval was then added to this number to get a second number, then the interval was added to this second number to get a third number, and so on. The set of numbers produced were the numbers used to select the households, in terms of their order on the list.
In fact, the number of households in the sample is 785, as opposed to 780. Most of this difference is due to a village in which 24 households were interviewed, as opposed to the goal of 20 households
Face-to-face [f2f]
Household Questionnaire
The household questionnaire contains sections that collect data on household demographic structure, education, housing conditions, land, agricultural management, household non-agricultural business, household expenditures, gifts, remittances and other income sources, and saving and loans. For some sections (general household information, schooling, housing, gift-exchange, remittance, other income, and credit and savings) the individual designated by the household members as the household head provided responses. For some other sections (farm land, agricultural management, family-run non-farm business, and household consumption expenditure) a member identified as the most knowledgeable provided responses. Identification codes for respondents of different sections indicate who provided the information. In sections where the information collected pertains to individuals (employment), whenever possible, each member of the household was asked to respond for himself or herself, except that parents were allowed to respond for younger children. Therefore, in the case of the employment section it is possible that the information was not provided by the relevant person; variables in this section indicate when this is true.
The household questionnaire was completed in a one-time interview in the summer of 1995. The survey was designed so that more sensitive issues such as credit and savings were discussed near the end. The content of each section is briefly described below.
Section 0 SURVEY INFORMATION
This section mainly summarizes the results of the survey visits. The following information was entered into the computer: whether the survey and the data entry were completed, codes of supervisor’s brief comments on interviewer, data entry operator, and related revising suggestion (e.g., 1. good, 2. revise at office, and 3. re-interview needed). Information about the date of interview, the names of interviewer, supervisor, data enterer, and detail notes of interviewer and supervisor were not entered into the computer.
Section 1 GENERAL HOUSEHOLD INFORMATION
1A HOUSEHOLD STRUCTURE 1B INFORMATION ABOUT THE HOUSEHOLD MEMBERS’ PARENTS 1C INFORMATION ABOUT THE CHILDREN WHO ARE NOT LIVING IN HOME
Section 1A lists the personal id code, sex, relationship to the household head, ethnic group, type of resident permit (agricultural [nongye], non-agricultural [fei nongye], or no resident permit), date of birth, marital status of all people who spent the previous night in that household and for household members who are temporarily away from home. The household head is listed first and receives the personal id code 1. Household members were defined to include “all the people who normally live and eat their meals together in this dwelling.” Those who were absent more than nine of the last twelve months were excluded, except for the head of household. For individuals who are married and whose spouse resides in the household, the personal id number of the spouse is noted. By doing so, information on the spouse can be collected by appropriately merging information from the section 1A and other parts of the survey.
Section 1B collects information on the parents of all household members. For individuals whose parents reside in the household, parents’ personal id numbers are noted, and information can be obtained by appropriately merging information from other parts of the survey. For individuals whose parents do not reside in the household, information is recorded on whether each parent is alive, as well as their schooling and occupation.
Section 1C collects information for children of household members who are not living in home. Children who have died are not included. The information on the name, sex, types of resident permit, age, education level, education cost, reasons not living in home, current living place, and type of job of each such child is recorded.
Section 2 SCHOOLING
In Section 2, information about literacy and numeracy, school attendance, completion, and current enrollment for all household members of preschool age and older. The interpretation of pre-school age appears to have varied, with the result that while education information is available for some children of pre-school age, not all pre-school children were included in this section. But for ages 6 and above information is available for nearly all individuals, so in essence the data on schooling can be said to apply all persons 6 age and above. For those who were enrolled in school at the time of the survey, information was also collected on school attendance, expenses, and scholarships. If applicable, information on serving as an apprentice, technical or professional training was also collected.
Section 3 EMPLOYMENT
3A GENERAL INFORMATION 3B MAJOR NON-FARM JOB IN 1994 3C THE SECOND NON-FARM JOB IN 1994 3D OTHER EMPLOYMENT ACTIVITIES IN 1994 3E SEARCHING FOR NON-FARM JOB 3F PROCESS FOR GETTING MAJOR NON-FARM JOB 3G CORVEE LABOR
All individuals age thirteen and above were asked to respond to the employment activity questions in Section 3. Section 3A collects general information on farm and non-farm employment, such as whether or not the household member worked on household own farm in 1994, when was the last year the member worked on own farm if he/she did not work in 1994, work days and hours during busy season, occupation and sector codes of the major, second, and third non-farm jobs, work days and total income of these non-farm jobs. There is a variable which indicates whether or not the individual responded for himself or herself.
Sections 3B and 3C collect detailed information on the major and the second non-farm job. Information includes number of months worked and which month in 1994 the member worked on these jobs, average works days (or hours) per month (per day), total number of years worked for these jobs by the end of 1994, different components of income, type of employment contracts. Information on employer’s ownership type and location was also collected.
Section 3D collects information on average hours spent doing chores and housework at home every day during non-busy and busy season. The chores refer to cooking, laundry, cleaning, shopping, cutting woods, as well as small-scale farm yard animals raising, for example, pigs or chickens. Large-scale animal