Statistical investigation report on labor wages
I. Historical Evolution of Labor Wage Statistics System Labor Wage Statistics began in 1950s, when the National Bureau of Statistics was established in 1952, and then the employment situation of urban and rural laborers was investigated. Since then, labor wage statistics have undergone a series of changes, and the scope of statistical objects has been expanding.
(a) from the 1950s to the 1980s, the statistical scope of labor wages was units above the urban collective, mainly counting the number and wages of the whole people and urban collective workers; 1990 In 2004, the National Bureau of Statistics expanded the statistical scope to non-private units in cities and towns, and the statistical objects were the whole people, collectives and other economic units of ownership (domestic capital: joint-stock cooperation, joint ventures, limited liability companies and joint stock limited companies; Foreign investment: investment by Hong Kong, Macao and Taiwan businessmen; Foreign investment), excluding township enterprises, private units and individual businesses.
(2) In 2005-2007, in addition to non-private units in cities and towns, "Three Up" private enterprises (that is, private enterprises in industries above designated size, construction industry, real estate industry, wholesale and retail industry above designated size and accommodation and catering industry) were added to the statistical scope of labor wages. In 2007, other private units began to increase: 19 units used typical surveys, and units with more than 20 employees conducted sampling surveys.
(3) After 2008, the labor wage statistics system is divided into two types: urban non-private units and private units. The survey scope of non-private units remains unchanged, and the survey scope of private units adopts the following methods: a set of enterprises (that is, "four-top" enterprises, whose statistical scope covers industries above designated size, qualified construction industries, all real estate development and management industries, wholesale and retail industries above designated size, accommodation and catering industries above designated size, national key service industries and provincial service industries) conduct a comprehensive survey. Other non-single private units are classified by employees, with full survey 100, sampling survey 20-99 and typical survey 19. However, the comprehensive survey and sampling survey were conducted separately, and the data were not merged. In addition, the sampling data is not representative at the county level, so it is impossible to calculate the population and publish it to the public. At present, labor wage statistics are directly reported online, and labor and capital statements are submitted in paper media (except for industrial activities such as banks, which are regarded as legal persons, paper statements are still continued).
Second, the current situation and main problems of labor wage statistics
1. There are some restrictions on the statistical range.
With the increasing diversification of investors and the development of various economic components, the individual and private economy has become the backbone of economic development. In 20 13 years, the added value of non-state-owned economy accounted for 86. 1% of GDP. However, the current labor wage statistics mainly focus on reflecting the labor conditions of non-private and "four-to-four" private enterprises in cities and towns, and small-scale private, individual industrial and commercial households and township enterprises are not included. Therefore, the statistics do not reflect or can not truly reflect the employment situation and wage level of private, individual and other economic properties that have gradually become the main body of employment absorption, and the statistical scope has obvious limitations. It is precisely because of this statistical law that lags behind the current economic structure that most employees with lower wages who should be highly valued are not included in the statistics. At present, all employees with higher wages have been counted, which has improved the average wage level of employed people to a certain extent, resulting in the data released by the statistical department being unacceptable to ordinary people. For example, the vast majority of urban non-private enterprises belong to monopoly industries, and the wage level remains high, which affects the wage level of urban non-private units in this county. In 20 13, the average wage of employees in urban non-private units in the county was 63,848 yuan, which was higher than that of the whole country, the whole province and the whole city12,374 yuan, 7,277 yuan and 4,065 yuan respectively, while the per capita GDP in 20 13 was only 39,705 yuan, which was lower than that of the whole country, the whole province and the whole city.
2. The setting of statistical indicators is not reasonable.
(1) The setting of statistical indicators is complicated and lacks practicality. First, the setting of statistical indicators is complicated. Complex indicator setting will only affect the accuracy of data. Statisticians at the grass-roots level change frequently, and they don't have a deep understanding of the interpretation of indicators, so they only fill in the meaning of indicators based on their own understanding. For example, the indicator of "person in charge of the unit" is considered as the legal representative by most people at first glance, but in fact, the indicator explanation includes the middle level of the unit; For example, the following three indicators of employees are classified by personnel type: on-the-job employees, labor dispatchers and other employees, not to mention the explanation of their respective indicators. Just saying the difference is a headache. On-the-job employees belong to the employees of the original unit, according to the principle of whoever pays the salary, and the labor dispatch personnel should be unified to the actual employer, not according to the principle of who pays the salary. The definition of labor dispatch workers is a series of explanations. County-level professionals should also carefully study the interpretation of indicators to determine the boundaries. Statisticians in grass-roots units can imagine that most of them just fill in the data according to their own understanding. There is also the wage classification index of on-the-job employees, which is obscure and difficult to understand, and it is easy for grassroots statisticians to have ambiguity. For example, the "performance salary" government agencies mistakenly think that it is only the performance salary on the payroll of public officials, but the actual indicator is the salary of bonus nature, and government officials also have this project. Second, statistical indicators lack practicality. For a long time, the indicators reflecting the level of labor wages mainly include the number of employed people at the end of the period, the average number of employed people, the total wages of employed people, and the average wages of employed people. Its practicality and flexibility have lagged behind the needs of society to a great extent, especially the indicators reflecting the decision-making of governments at all levels, the needs of enterprises and social focus issues. For example, social security hotspots such as college students' employment, migrant workers' employment, industry employment demand, and re-employment of laid-off workers are generally concerned by all sectors of society. In these index groups, labor wages are still blank.
(2) The index reflecting the wage level of employed persons is single. In the current labor wage statistics, only the average wage of all employees in this unit is an indicator. The average wage is an overall concept, and its data and increase represent the overall level. The problem brought by simple average is to cover up the inequality under average. On the one hand, it covers up the inequality between different industries and different units. According to the 20 13 annual labor wage report, the industry average wage is 6.3 times that of the lowest industry. On the other hand, it covers up the inequality within the unit. At present, the wage gap between business owners and ordinary employees is getting bigger and bigger, with a difference of dozens or even hundreds of times. However, providing only the average salary of one unit does not explain more inequality. From the perspective of wage distribution, the wage level of all groups in the whole society is "skewed" distribution, with a small number of people with high wages and a large number of people with low wages. The existing data cannot reflect these situations. Because the indicators are single and the deep-seated reasons are unclear, ordinary people understand these data from their own perspective, so when the average wage data is released to the society, it causes the public to question the data and brings about the phenomenon of low quality of statistical services.
3. The statistical task is heavy, but the data utilization rate is not high.
(1) has a wide statistical range and a heavy task. At present, labor wage statistics involve many units, heavy tasks and great pressure, including not only the "four-up" enterprises in industries such as industry, construction, real estate, wholesale and retail, accommodation and catering, service industry, but also all the "four-down" non-private units, totaling more than 400 units, and the workload is very heavy. However, at present, the opening time of online direct reporting is short, and grassroots statisticians frequently change or hold several positions. Only a few units can actively and directly report during the reporting period. Most units often need county-level statisticians to remind and urge newspapers repeatedly by telephone, QQ, office assistants and other forms, and individual units have to urge newspapers many times, which is more difficult. At the same time, within the specified time, county-level professionals not only have a lot of supervision work, but also endless comparison work, which needs to be filled out one by one by industry and unit, and the workload is greatly increased.
(2) Online direct reporting operation platform needs to be improved. The collection method of labor wage statistics report is changed from paper report to online direct report, which reduces the workload of grassroots statistics. However, due to more and more statistical units, short reporting time, weak system stability and low degree of cooperation between enterprises, it is more and more difficult to collect reports. First, the submission time of the online operation platform is tight. Online direct reports have a strong time limit, especially quarterly reports. Generally, the time from opening the network to closing the network nationwide is quite short, usually 5-7 days. County-level labor professionals should rush to report and review hundreds of labor reports within 5-7 days. Due to the short reporting time, a large number of units reported centrally, and different statisticians in some units also reported different reports at the same time, resulting in network congestion. During the peak period of reports, it often happens that web pages can't be opened or reports can't be reported normally, which brings a lot of inconvenience to enterprises. Some units have a standardized system, and the time for paying wages is relatively late. Before reporting, it is necessary to check at all levels, often in time to report. Therefore, it will become more and more difficult to urge all units to report in a short time. Second, the online direct reporting operation procedure is too cumbersome. The direct reporting system requires a higher browser. If you use a lower version of IE browser and do not use interception software, you can successfully download certificates or report stably. Many basic statisticians have limited computer operation ability and are often at a loss about the operation process of online direct reporting. They need telephone guidance from county-level labor professionals or computer remote operation certificate installation, browser settings and other programs. The repeated operation of similar problems consumes a lot of time and energy, which makes professionals exhausted. Even some units gave up direct reporting and issued paper reports because of repeated unsuccessful operations, making data collection more difficult. Third, the system audit formula is not rigorous enough. Before the system is turned on, the audit formula should have completely passed the test, but the actual situation is that the audit formula will be added from time to time after the system is turned on, which greatly increases the workload of the later audit. Due to the audit formula added in the later period, many units reported it, and there were many mistakes after the audit. County-level labor professionals can only inform enterprises to correct their mistakes by SMS or telephone, and some enterprises often go away after reporting, and do not modify or fill in the instructions as required. If it is urged again and again, it will easily arouse the resentment of enterprise statisticians. In addition, for statisticians in grass-roots units, simpler and clearer error information prompts are needed to help them understand the logical relationship in the audit and correct or explain the errors in time. For example, the "person in charge of a unit" evolved from the original "manager", and the correct understanding of the "person in charge of a unit" should be the middle-level or above managers. However, there are indicators of "person in charge of the unit" at the bottom of the report and the basic information table of the unit, so statisticians can easily confuse these indicators with the same item and mistakenly think that they all refer to the first person in charge of the unit. Therefore, many statisticians fill in "person in charge of a company" in their statements. Another example is "1- quarter". Because the numbers and symbols set are not obvious, statisticians easily mistake the salary corresponding to this column for the data of this quarter, and often mistakenly fill in the accumulated salary as the salary of this quarter. For the "part-time" index, statisticians can easily misunderstand it as "part-time" in terms of academic qualifications. In addition, some indicators have multiple calibers. For example, the total wages of employees in the labor table and the wages payable in the financial table have also troubled many grassroots statisticians. Literally, both indicators refer to wages, but in fact, total wages and wages payable are not the same concept. The difference is that the total wages do not include the "five insurances and one gold" paid by the unit, but this part should be included in the wages payable. Fourth, data quality is difficult to guarantee. For county-level professionals, there are a large number of reporting units, so it is difficult to urge them to report on time in a short time, and it is too late to conduct a detailed audit of each unit. During the reporting period, dozens or even hundreds of phone calls were made every day to urge the newspaper, and the direct reporting unit was not regularly used to solve the problems in the system at any time through the network or telephone, and sometimes the obvious errors in the inquiry and feedback from the national, provincial and municipal statistical departments were verified. A report cannot be submitted for review in a short time, and only the units with obvious errors can be reviewed in batches or queried; For grassroots statisticians, the reporting time is short, and statisticians are in a hurry to report, so it is impossible to strictly check the data. Some just reported an estimated data on time, which has a certain gap with the actual data. Fifth, the database of labor dictionary is not updated in time. The labor dictionary database of the direct reporting platform is imported from the directory database once a year, but grass-roots units cannot modify the basic information table of legal entities themselves when reporting quarterly reports. Too long a time span will easily lead to inaccurate information in the dictionary database, and grassroots statisticians will have a great response.
(3) The data utilization rate is not high. First, the annual labor wage statistics indicators are grouped too finely, and the data utilization rate is not high. There are 55 statistical indicators without supplementary information in the annual report of 20 13, and few of them are really useful. Some indicators in the system are not needed by local governments, but are not needed by local governments. Party and government leaders at all levels urgently need to master the statistical data of the distribution, transfer, employment and unemployment of urban labor force in order to better formulate employment policies and guide the transfer of urban labor force. However, the current labor statistics methods and systems do not involve this aspect, and the statistical department cannot obtain relevant data from the existing statistical reports. For a long time, the county-level statistical department has been busy with the report tasks assigned by the higher-level statistical department, and has not made too much statistics, attention and analysis on the development of local economy and indicators with local characteristics. Statistical indicators such as employment and labor remuneration are far less than GDP, total investment in fixed assets of the whole society, and per capita net income of farmers, which are concerned and valued by leaders and the public, resulting in the data that labor statisticians spend a lot of time and energy producing being ignored, which is "thankless". Second, the report is not representative and the value of data development and utilization is low. The current rules for releasing professional data of labor wage statistics are: the data of the "top four" enterprises counted by "a set of enterprise tables" are not released to the public, but only the data of non-private units in cities and towns are released. From the perspective of county-level labor and wage professionals, after the implementation of online direct reporting, the workload has doubled due to the increase in the number of "one set of tables for enterprises", but this hard-won statistical data failed to play its due role, just to complete the tasks assigned by superiors. Because the statistical objects of non-private units in cities and towns are incomplete, the report is not representative and the analysis is of little significance, which also weakens the enthusiasm of labor statisticians for the development and utilization of their data.
4. The professional quality of grassroots statisticians does not meet the requirements of statistical work.
Most grass-roots units do not have full-time statisticians. Generally, the labor and wage statisticians in government agencies and institutions are part-time personnel or financial personnel, while those in enterprises are part-time financial personnel. The frequent personnel changes often lead to the failure to report statements on time. At the same time, because part-time workers have to take care of a lot of work, labor wage statistics can only be regarded as incidental work, especially in enterprises. Statisticians should not only do a good job in their own units, but also undertake the reporting work of finance, taxation, industry and commerce, statistics and other departments. The task is very heavy, which leads to the fact that most statisticians have worked in statistical posts for many years, but they still have a little knowledge of statistical business and cannot master the necessary knowledge of labor and wage statistics skillfully. The understanding of the meaning, statistical caliber, statistical scope and calculation method of index interpretation is not in place, and the reported statements are often prone to errors and extremely irregular, and the data quality is difficult to guarantee.
Three, some thoughts on doing a good job in labor wage statistics.
1. Adapt to the demand and further improve the system of labor statistics methods. The first is to improve the statistical investigation methods. Innovate the wage statistics system and change the labor wage statistics from a comprehensive survey to a sampling survey. Many problems in labor wage statements are caused by too many reporting units. The implementation of sampling survey can reduce the number of reporting units and make the comprehensive statistical department shift its work energy from urging reports to auditing and correcting errors. The sampling survey takes the latest basic unit directory database as the sample box, and verifies the samples according to the national economic industry and the actual situation, and then incorporates the samples into the dictionary database of labor wage statistical survey. Methods Sampling by industry, setting up a summary weight index for each industry, investigating all small industries with few units, and estimating the overall employment and income through sample data. At the same time, labor force survey can be combined with census and population sampling survey, which can not only save manpower and financial resources, but also improve data quality and work efficiency. The second is to adjust the scope of statistical investigation. Form statistics covering all workers in the whole society to make up for the shortcomings of the current labor wage statistics system. The general individual industrial and commercial households as special economic organizations will be included in the scope of labor wage statistics, so as to comprehensively and truly reflect the distribution and composition of labor employment and the income and distribution of labor remuneration in the whole society, and better meet the needs and utilization of labor wage statistics by the government and the public. The third is to reduce the frequency of statistical surveys. In view of the disadvantages of the current labor statistics, such as heavy workload and poor representativeness, it is suggested to replace the current quarterly report with an annual report. One reason is that the quarterly data has not changed much. The data in the annual report of labor wages can fully reflect the employment and wages in this region. On the one hand, labor remuneration is not only reflected in the monthly salary, but also closely related to the year-end bonus from the actual situation of many units, so the annual income can more accurately reflect the remuneration of employees in a region. On the other hand, from the previous quarterly data, the number of employees has not changed much in each quarter. Except for special periods such as the Spring Festival and the graduation season of college students, the employment situation in most units is relatively stable at other times of the year. We can add employment survey indicators such as increasing or decreasing personnel in the annual report to meet the needs of employment policy formulation and guidance. The second reason is that the quarterly data utilization rate is not high. Since 20 10, except for five major industries, quarterly data has been used for "GDP" accounting, and the state stipulates that quarterly data will no longer be released to the outside world, which is basically a unified situation. Cancellation of quarterly reports can reduce the burden of grassroots statisticians and improve work efficiency. For non-profit industries involving "GDP" accounting, relevant data can be obtained from relevant departments such as education, health or financial accounting centers. The fourth is to improve the statistical index system. According to the principles of precise definition, clear connotation and clear attributes, we should break through the restrictions of urban and rural areas, ownership forms and employees' identities, improve and formulate the labor wage statistical index system that fully reflects the market economy, and make it more scientific, predictable, timely and relatively stable, and pay attention to the connection between the statistical index system and other departments. It is necessary to reduce outdated, unnecessary or difficult to accurately count labor indicators, such as labor dispatch personnel in personnel classification and some personnel categories subdivided by posts. According to the needs, special indicators reflecting social hot spots and focus issues, such as "individual housing provident fund", "people not included in old-age insurance", "migrant workers" and "employment of college students", can reflect the situation of talents, labor transfer and education level, better reflect economic and social development and changes, and provide high-quality statistical services for party and government organs and the public. At the same time, it is best to use simple and clear indicators to unify the indicators of each report, so that the reports and indicators of various professions and departments can be shared, play their respective roles, and reduce the burden on grass-roots units. For example, changing "person in charge of the unit" to "management personnel" is in line with the thinking of most people and can reduce the artificial data deviation to a certain extent. The interpretation of indicators should be intuitive, easy to understand and easy to fill in, so as to ensure the accuracy and authenticity of statistical data. It is necessary to strengthen the wage level index. The first is to downplay the concept of social average and strengthen the concept of occupational average wage. Judging from the effect of wages and the formulation of the minimum wage standard, there is no very small data, but there is an unusually large data, and the average wage level can be moved up with a slight change in the unusually large data. Unusually large wages often exist in management. Comparatively speaking, the wage gap of the same occupation in non-management will not be very large. Therefore, to some extent, providing average wages by occupation is closer to the psychological orientation of ordinary people, and it can also improve the level and quality of statistical services. The second is to calculate and publish the median wage level of employed people. The average wage is easily influenced by the extreme value, while the median wage is relatively insensitive to the deviation between the maximum value and the minimum value, which can be used as a supplementary indicator to reflect the wage situation of employed people.
2. Optimize the program of network direct reporting system to improve the efficiency of direct reporting. The first is to strengthen the stability of the network direct reporting system. Improve the running speed of the program, reduce the inconvenience caused by poor network, and ensure that the unit can report normally and unimpeded even during the peak reporting period. At the same time, it reduces the operation difficulty of the system, strengthens the compatibility with browsers, and makes the application unit download certificates simple and smooth. The second is to strengthen the function of the network direct reporting system. On the one hand, the index design is more concise and clear, and the index explanation is added in the system. The reporting unit clicks the reporting box, and without pressing F 1, it will automatically jump out of the detailed description of the indicators. On the other hand, the audit formula of the system needs to be improved. In view of the problems existing in the formula audit of online direct reporting software, the audit formula should be tested repeatedly before opening the network, and improved as soon as possible to ensure the integrity and accuracy of the audit formula, so that the reporting unit can submit data with high quality at the first time. The third is to decentralize the updating authority of the unit dictionary database and set the network system as super summary according to the specialty. At present, a set of table units in China and a set of non-table units in the province are the updating authority of dictionary database. It is suggested that the updating of the dictionary database of non-tabular units should be decentralized to the county level, so as to facilitate the units to update, increase or decrease and change the basic information in time. At the same time, banks and other industrial activity units regarded as legal entities are put on the direct reporting platform, the paper media reporting method is completely eliminated, and the super-summary program is set up on the network platform to reduce a series of workload such as the introduction program of county-level professionals.
Article 2 Statistical investigation report on labor wages
In order to further consolidate the data base of labor wage statistics, recently, Zhou Huiling, chief statistician of Ya 'an Municipal Bureau of Statistics, led a team to investigate the labor wage statistics in Lushan County, tianquan county County and Yingjing County in combination with the related activities of "big study, big visit and big investigation" in the whole city. The research team went deep into tianquan county Wellcome Business Service Co., Ltd., Yingjing County Xingheng Yang Kang Service Co., Ltd. and other sample survey enterprises, and had in-depth exchanges with enterprise labor wage statisticians to understand their understanding of labor wage statistics caliber and statistical indicators, observed the establishment of wage ledger on the spot, and gave on-site guidance on the problems existing in enterprise labor wage statements.
Article 3 Statistical investigation report on labor wages
In order to further improve the data quality of labor wage statistics and research, Jinzhou Municipal Bureau of Statistics promotes the work of labor wage statistics and research from three aspects: strengthening the sense of responsibility of grassroots statisticians, strengthening the submission and review of data, and standardizing the explanations of research units. First, improve ideological understanding and enhance the sense of responsibility of grassroots statisticians. The Notice on Carrying out the Statistical Survey of Labor Wages in 20021year was issued, requiring all research units to deeply understand the significance of the statistical survey of labor wages, support the statistical survey, earnestly fulfill the obligation of statistical statements, fill in the statistical data in a true, accurate, complete and timely manner, and further consolidate the quality of the survey data from the source.
The second is to improve the verification mechanism and strengthen the verification of data as soon as it is reported. Real-time monitoring of statistical data, irregular distribution of key industries and key units of data verification table, by the city and county statistical agencies of extreme units in the industry for "one-on-one" telephone verification and spot checks, layers of verification of abnormal data units, to ensure that the research data should be unified, not heavy and not leaking.
The third is to standardize the system review to ensure that the explanation of the research unit is sufficient and reasonable. Screen the error descriptions of the platform report system one by one, and once found, return the data change explanation to the research unit for modification to ensure that the data change reason is clear and well-founded.