User:Wuwenhao19960507/sandbox
Definition and Calculation Method
The surveyed unemployment rate is defined as the percentage of the unemployed population relative to the sum of the employed and unemployed populations, calculated through a sample survey estimation. The formula is as follows:
Number of Unemployed Persons
Surveyed Unemployment Rate = ———————————————————————————————————— × 100%
Number of Unemployed Persons + Number of Employed Persons
In this formula, the numerator represents the number of unemployed persons, while the denominator represents the labor force, which is the sum of the unemployed and employed populations, rather than the total population aged 16 and above. Since the non-labor force population is not included in the calculation of the surveyed unemployment rate, this indicator measures the proportion of the unemployed population within the labor force, not within the entire population aged 16 and above. For example, if the urban surveyed unemployment rate is 5.0%, it indicates that 5 out of every 100 people in the labor force are unemployed, rather than 5 out of every 100 people aged 16 and above.[1]
The definition of employed and unemployed persons are in accordance with resolutions released by the 19th International Conference of Labour Statisticians of ILO. Employed Persons are defined as those who are 16 years and above, and work at least one hour for remuneration or business profit during the reference week. Those who are temporarily absent from job for training, vacation or illness, or because of suspension of work and will return to the same job/business within one month, are also included in the employed. Unemployed Persons are defined as those aged 16 and above who are not employed during the reference week, and had looked for job activity during the 3-month before the reference week, and are available to work in two weeks, including those waiting for a job due to start in 3 months.Urban Unemployment Rate refers to the percent of the unemployed population to the sum of the employed and unemployed population in urban areas.[2]
Survey Methodology and Data Collection
The surveyed unemployment rate in China is derived from the Monthly Labor Force Survey, which employs a stratified, multi-stage, probability proportional to size (PPS) sampling method. The sampling process involves randomly selecting neighborhood (or village) committees within China, followed by a systematic random sampling of households within the selected committees. Each month, approximately 340,000 households are surveyed, covering all prefecture-level cities and county-level regions across mainland China. Based on the current sampling design, at a 90% confidence level, the relative error of China’s urban surveyed unemployment rate is within 2%. For example, if the estimated urban surveyed unemployment rate is 5%, the true unemployment rate is expected to fall within the range of 4.9% to 5.1% with 90% confidence. During specific periods each month, enumerators collect employment and unemployment information from selected households using electronic devices (PADs) and directly report the data to the National Bureau of Statistics of China (NBS) via an online reporting system. The NBS processes the submitted data, performs weighted aggregation, and estimates the national and provincial urban surveyed unemployment rates.[1]
Data Coverage
According to the National Bureau of Statistics of China (NBS Website), the unemployment data is compiled based on the Monthly Labor Force Survey, which covers the entire mainland China. The survey does not include data from Hong Kong, Macao, or Taiwan.[2]
Recent Data
| Year | Urban unemployment (10,000 persons) | Unemployment rate (%) | source |
|---|---|---|---|
| 1980 | 541.5 | 4.9 | [3] |
| 1981 | 439.5 | 3.8 | |
| 1982 | 379.4 | 3.2 | |
| 1983 | 271.4 | 2.3 | |
| 1984 | 235.7 | 1.9 | |
| 1985 | 238.5 | 1.8 | |
| 1986 | 264.4 | 2.0 | |
| 1987 | 276.6 | 2.0 | |
| 1988 | 296.2 | 2.0 | |
| 1989 | 377.9 | 2.6 | |
| 1990 | 383.2 | 2.5 | |
| 1991 | 352.2 | 2.3 | |
| 1992 | 363.9 | 2.3 | |
| 1993 | 420.1 | 2.6 | |
| 1994 | 476.4 | 2.8 | |
| 1995 | 519.6 | 2.9 | |
| 1996 | 552.8 | 3.0 | |
| 1997 | 576.8 | 3.1 | |
| 1998 | 571 | 3.1 | |
| 1999 | 575 | 3.1 | |
| 2000 | 595 | 3.1 | |
| 2001 | 681 | 3.6 | |
| 2002 | 770 | 4.0 | |
| 2003 | 800 | 4.3 | |
| 2004 | 827 | 4.2 |
2018
As of the end of 2018, the total employed population in China was 775.86 million, with 434.19 million employed in urban areas. During the year, 13.61 million new jobs were created in urban regions, an increase of 0.10 million compared to the previous year. The surveyed unemployment rate in urban areas stood at 4.9% at the end of 2018, 0.1 percentage point lower than the previous year, while the registered unemployment rate was 3.8%, also down by 0.1 percentage point. The total number of migrant workers reached 288.36 million in 2018, an increase of 0.6% over 2017. Of these, 172.66 million were employed outside their hometowns, up by 0.5%, while 115.70 million worked locally, an increase of 0.9%.[4]
2019
As of the end of 2019, the total employed population was 774.71 million, including 442.47 million people employed in urban areas. Urban employment accounted for 57.1% of the national total, an increase of 1.1 percentage points compared to the end of 2018. Throughout the year, 13.52 million new jobs were added in urban areas, a decrease of 90 thousand compared to the previous year. The surveyed urban unemployment rate stood at 5.2% at the end of 2019, while the registered urban unemployment rate was 3.6%. The number of migrant workers nationwide reached 290.77 million, a growth of 0.8% from 2018. Of these, 174.25 million migrant workers were employed outside their hometowns, up by 0.9%, while 116.52 million worked locally, an increase of 0.7%.[5]
2020
As of the end of 2020, the number of newly employed people in urban areas had reached 11.86 million, a decrease of 1.66 million compared to the previous year. The surveyed unemployment rate in urban areas stood at 5.2%, while the registered urban unemployment rate was 4.2% at the end of the year. The total number of migrant workers in 2020 was 285.60 million, representing a decrease of 1.8% from 2019. Of these, 169.59 million were migrant workers employed outside their hometowns, a decline of 2.7%, while 116.01 million worked within their localities, a decrease of 0.4%.[6]
2021
As of the end of 2021, the total employed population stood at 746.52 million, with 467.73 million employed in urban areas, making up 62.7% of the total employed population. This proportion was 1.1 percentage points higher than that at the end of the previous year. In 2021, 12.69 million new jobs were created in urban areas, an increase of 0.83 million compared to the previous year. The average surveyed unemployment rate in urban areas was 5.1% throughout 2021, with the rate at the year’s end also at 5.1%, while the registered unemployment rate was 3.96%. The total number of migrant workers reached 292.51 million, up by 2.4% compared to 2020. Among them, 171.72 million migrant workers left their hometowns to work elsewhere, a rise of 1.3%, while 120.79 million worked locally, an increase of 4.1%.[7]
2022
As of the end of 2022, the total employed population was 733.51 million, of which 459.31 million were employed in urban areas, accounting for 62.6% of the total employed population. In 2022, 12.06 million new jobs were created in urban areas, a decrease of 0.63 million compared to the previous year. The average surveyed unemployment rate in urban areas for 2022 was 5.6%, while the rate at the end of the year stood at 5.5%. The total number of migrant workers reached 295.62 million, reflecting an increase of 1.1% over 2021. Of these, 171.90 million were employed outside their hometowns, a slight rise of 0.1%, while 123.72 million worked locally, an increase of 2.4%.[8]
In March 2022, due to the intensification of the COVID-19 outbreak in certain regions, the recovery of production and business activities was affected. Sectors such as construction, transportation, accommodation and catering, wholesale and retail, residential services, and cultural tourism were significantly impacted, leading to a weakening in labor demand. As a result, the urban surveyed unemployment rate rose to 5.8%, an increase of 0.3 percentage points compared to the previous month. The unemployment rate for the primary working-age group (adults aged 25-59) increased by 0.4 percentage points from the previous month, reaching 5.2%. Among key groups, the unemployment rate of migrant workers with rural household registration, who typically return to the labor market after the Spring Festival, rose by 0.7 percentage points from January to 5.6% in February. In March, due to the ongoing impact of the pandemic, the unemployment rate of this group continued to rise, reaching 5.9%, exceeding the overall urban unemployment rate for two consecutive months.[9]
2023
As of the end of 2023, the total number of employed people in China was 740.41 million, with 470.32 million in urban areas, representing 63.5% of the total employed population. Throughout 2023, 12.44 million new jobs were created in urban areas, an increase of 0.38 million compared to the previous year. The average surveyed urban unemployment rate was 5.2% in 2023, while the rate at the end of the year was 5.1%. The total number of migrant workers reached 297.53 million, an increase of 0.6% over 2022. Among them, 176.58 million were employed outside their hometowns, up by 2.7%, while 120.95 million worked locally, a decrease of 2.2%.[10]
| Month | The Urban Surveyed Unemployment Rate(%) | The Urban Surveyed Unemployment Rate of the Population Aged from 16 to 24(%) | The Urban Surveyed Unemployment Rate of the Population Aged from 25 to 59(%) | Average Weekly Working Hours of Urban Employess in Enterprises(hour) | source |
|---|---|---|---|---|---|
| January | 5.5 | 17.3 | 4.7 | 47.9 | [11] |
| February | 5.6 | 18.1 | 4.8 | 47.9 | |
| March | 5.3 | 19.6 | 4.3 | 48.7 | |
| April | 5.2 | 20.4 | 4.2 | 48.8 | |
| May | 5.2 | 20.8 | 4.1 | 48.6 | |
| June | 5.2 | 21.3 | 4.1 | 48.7 | |
| July | 5.3 | unreleased | unreleased | 48.7 | |
| August | 5.2 | unreleased | unreleased | 48.7 | |
| September | 5.0 | unreleased | unreleased | 48.8 | |
| October | 5.0 | unreleased | unreleased | 48.7 | |
| November | 5.0 | unreleased | unreleased | 48.9 | |
| December | 5.1 | unreleased | unreleased | 49.0 |
2024
Since December 2023, the National Bureau of Statistics of China has adopted a new method for calculating unemployment rates. Under this approach, the unemployment rate for the labor force aged 16 to 24 no longer includes students currently enrolled in school, aiming to provide a more accurate reflection of the actual employment situation. Additionally, for the labor force aged 25 to 59, the bureau has further segmented the unemployment rate into two sub-groups: the unemployment rate for those aged 25 to 29 and the unemployment rate for those aged 30 to 59, with data released separately for each group.[12]
| Month | The Urban Surveyed Unemployment Rate(%) | Average Weekly Working Hours of Urban Employess in Enterprises(hour) | source |
|---|---|---|---|
| January | 5.2 | 49.0 | [11] |
| February | 5.3 | 48.0 | |
| March | 5.2 | 48.6 | |
| April | 5.0 | 48.5 | |
| May | 5.0 | 48.7 | |
| June | 5.0 | 48.6 | |
| July | 5.2 | 48.7 | |
| August | 5.3 | 48.7 | |
| September | 5.1 | 48.8 |
Causes
China's unemployment trends are influenced by globalization, technological advancements, and industrial restructuring. As China has integrated into the global market, its manufacturing and export-oriented industries have become central to its economy. However, global economic fluctuations and changes in demand directly impact employment in these sectors. For instance, increased import competition has been linked to significant labor market disruptions in developed economies, highlighting the sensitivity of employment to global trade dynamics. [13]
Technological innovation and automation have also played a role in shaping China's labor market. The adoption of advanced manufacturing technologies has led to a reduced demand for low-skilled labor, as machines and automated systems replace human workers in certain tasks. Studies have shown that automation can lead to job displacement in manufacturing enterprises, particularly affecting low-skilled positions, while potentially creating opportunities for high-skilled labor. [14]
Additionally, China's efforts to adjust its industrial structure—from traditional manufacturing to high-tech and service industries—have contributed to unemployment trends. This transition often results in a mismatch between the skills of the existing workforce and the requirements of emerging industries, leading to structural unemployment. Research indicates that such industrial upgrading can have significant implications for employment, necessitating policies that address skill development and labor market flexibility. [15]
Policy Interventions and Their Effectiveness
To mitigate unemployment and support labor market stability, the Chinese government has introduced various policy measures, notably unemployment insurance, vocational training, and reemployment programs. These policies aim to cushion the impact of job loss and facilitate workforce adaptation to economic restructuring and technological advancements.
Unemployment Insurance
Unemployment insurance (UI) in China, a system introduced during the 1990s economic reforms, has evolved to offer financial support to involuntarily unemployed workers while they seek new employment. UI aids in stabilizing household consumption and fosters social stability, primarily benefiting urban areas where layoffs are more common due to industrial shifts. Besides providing a financial cushion, UI encourages an efficient labor allocation process by allowing job seekers adequate time to find roles that align with their skills, ultimately reducing labor market volatility.[16]Unemployment insurance (UI) not only provides immediate financial assistance to individuals but also indirectly supports regional economies by sustaining consumer demand during economic downturns. Studies have shown that UI can alleviate poverty and reduce economic inequality, contributing to stability in communities with high unemployment rates. Research indicates that by supporting basic living standards, UI helps prevent extreme poverty among urban populations, particularly in regions facing economic vulnerabilities.[17]
Vocational Training Programs
In response to growing skill mismatches amid rapid industrial and technological advancements, the Chinese government has heavily invested in vocational training. These programs aim to improve the employability of displaced workers, specifically targeting skills required in expanding sectors like automation and service industries. Research indicates that such training significantly enhances reemployment prospects by equipping workers with relevant skills, effectively reducing structural unemployment.[18]China's labor market is undergoing profound structural changes, showing new characteristics of task structure transformation. Further research shows that vocational training has played an important role in this transformation, not only improving workers' employability, but also promoting labor market flexibility, enabling recession-affected regions to transfer labor to high-demand emerging industries, thereby alleviating the government's fiscal pressure. By adapting to task-biased technological progress and helping workers acquire new skills that match technological changes, these programs not only improve individuals' re-employment ability, but also enhance the adaptability of the labor market to economic structural adjustments.[19]
- ^ a b "什么是调查失业率 - 国家统计局" [What is the survey unemployment rate - National Bureau of Statistics]. www.stats.gov.cn. Retrieved 2024-10-06.
- ^ a b "Dissemination Standards Bulletin Board". dsbb.imf.org. Retrieved 2024-10-06.
- ^ LU, Ming; GAO, Hong. "Labour market transition, income inequality and economic growth in China". International Labour Review. 150 (1–2): 101–126. doi:10.1111/j.1564-913x.2011.00107.x. ISSN 0020-7780.
- ^ "Statistical Communiqué of the People's Republic of China on the 2018 National Economic and Social Development". www.stats.gov.cn. Retrieved 2024-10-06.
- ^ "Statistical Communiqué of the People's Republic of China on the 2019 National Economic and Social Development". www.stats.gov.cn. Retrieved 2024-10-06.
- ^ "Statistical Communiqué of the People's Republic of China on the 2020 National Economic and Social Development". www.stats.gov.cn. Retrieved 2024-10-06.
- ^ "Statistical Communiqué of the People's Republic of China on the 2021 National Economic and Social Development". www.stats.gov.cn. Retrieved 2024-10-06.
- ^ "STATISTICAL COMMUNIQUÉ OF THE PEOPLE'S REPUBLIC OF CHINA ON THE 2022 NATIONAL ECONOMIC AND SOCIAL DEVELOPMENT". www.stats.gov.cn. Retrieved 2024-10-06.
- ^ "王萍萍：受疫情影响城镇调查失业率有所上升 _中国经济网——国家经济门户" [Wang Pingping: Affected by the epidemic, the urban survey unemployment rate has increased _China Economic Net]. www.ce.cn. Retrieved 2024-10-06.
- ^ "STATISTICAL COMMUNIQUÉ OF THE PEOPLE'S REPUBLIC OF CHINA ON THE 2023 NATIONAL ECONOMIC AND SOCIAL DEVELOPMENT". www.stats.gov.cn. Retrieved 2024-10-06.
- ^ a b "National Data". data.stats.gov.cn. Retrieved 2024-11-04.
- ^ "关于完善分年龄组调查失业率有关情况的说明 - 国家统计局" [Explanation on Improvements in Surveying Unemployment Rates by Age Group]. www.stats.gov.cn. Retrieved 2024-11-04.
- ^ Dix-Carneiro, Rafael; Pessoa, João Paulo; Reyes-Heroles, Ricardo; Traiberman, Sharon (May 2023). "Globalization, Trade Imbalances, and Labor Market Adjustment". The Quarterly Journal of Economics.
- ^ Jiang, Hong; Ge, Yingfan; Yang, Chunhao; Yu, Hongxin (2024-03-05). "How automated machines influence employment in manufacturing enterprises?". PLOS ONE. 19 (3): e0299194. doi:10.1371/journal.pone.0299194. ISSN 1932-6203. PMC 10914295. PMID 38442127.
{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link) - ^ Vermeulen, Ben; Kesselhut, Jan; Pyka, Andreas; Saviotti, Pier Paolo. "The Impact of Automation on Employment: Just the Usual Structural Change?". Sustainability. 10 (5): 1661. doi:10.3390/su10051661. ISSN 2071-1050.
{{cite journal}}: CS1 maint: unflagged free DOI (link) - ^ Giles, John; Park, Albert Francis; Cai, Fang (2006). "Reemployment of Dislocated Workers in Urban China: The Roles of Information and Incentives". SSRN Electronic Journal. doi:10.2139/ssrn.705203. ISSN 1556-5068.
- ^ "Liberalisation, unemployment, inequality and poverty in urban China", Trade Policy, Growth and Poverty in Asian Developing Countries, Routledge, pp. 77–91, 2003-12-08, ISBN 978-0-203-42276-2, retrieved 2024-11-03
- ^ Wong, Linda; Ngok, Kinglun (2006-03-09). "Social Policy between Plan and Market: Xiagang (Off‐duty Employment) and the Policy of the Re‐employment Service Centres in China". Social Policy & Administration. 40 (2): 158–173. doi:10.1111/j.1467-9515.2006.00482.x. ISSN 0144-5596.
- ^ "中国劳动力市场结构变迁-中国社会科学网". www.cssn.cn. Retrieved 2024-11-03. [Structural changes in China's labor market——From the perspective of task-oriented technological progress]