This statistic illustrates the unemployment rate of legal professionals in the United states in the second quarter of 2017. In that period, some *** percent of the lawyers were not employed in the U.S.

Dataset

This dataset was created by VasL

Contents

The number of law graduates in the United States steadily ******** between 2013 and 2019. Between 2020 and 2022 there was a slight ******** in the number of graduates, however this number fell again in 2023. In 2024, this figure increased again and reached almost ******. The share of unemployed law graduates in the United States followed approximately the same trend: the percentage of law students who did not find a job after graduating in 2019 was roughly half the share recorded in 2013, before increasing again in 2020, and falling in the following years. Career opportunities Law school graduates can undertake many career paths. Legal occupations can be primarily distinguished between lawyers, judges, and judicial workers on one hand, and legal support workers, such as paralegals and legal assistants, on the other. In 2024, the outright majority of professionals employed in legal occupations in the United States were lawyers. According to the same study, lawyers were also the highest-paid workers in the sector, followed by judges and magistrates. Leading law firms The United States are home to some of the most renowned law firms in the world. In 2024, Wachtell was the leading law firms in the country in terms of revenue per lawyer, as Kirkland & Ellis generated the highest gross revenue. Baker Mckenzie was the company in the United States with the highest number of lawyers employed. In fact, the multinational firm headquartered in Chicago employed roughly 500 more lawyers than DLA Piper, who were second in the rankings.

Context

This is a dataset that I built by scraping the United States Department of Labor's Bureau of Labor Statistics. I was looking for county-level unemployment data and realized that there was a data source for this, but the data set itself hadn't existed yet, so I decided to write a scraper and build it out myself.

Content

This data represents the Local Area Unemployment Statistics from 1990-2016, broken down by state and month. The data itself is pulled from this mapping site:

https://data.bls.gov/map/MapToolServlet?survey=la&map=county&seasonal=u

Further, the ever-evolving and ever-improving codebase that pulled this data is available here:

https://github.com/jayrav13/bls_local_area_unemployment

Acknowledgements

Of course, a huge shoutout to bls.gov and their open and transparent data. I've certainly been inspired to dive into US-related data recently and having this data open further enables my curiosities.

Inspiration

I was excited about building this data set out because I was pretty sure something similar didn't exist - curious to see what folks can do with it once they run with it! A curious question I had was surrounding Unemployment vs 2016 Presidential Election outcome down to the county level. A comparison can probably lead to interesting questions and discoveries such as trends in local elections that led to their most recent election outcome, etc.

Next Steps

Version 1 of this is as a massive JSON blob, normalized by year / month / state. I intend to transform this into a CSV in the future as well.

Okun's law is an empirical relationship that measures the correlation between the deviation of the unemployment rate from its natural rate and the deviation of output growth from its potential. In this paper, we estimate Okun's coefficients for each U.S. state and examine the potential factors that explain the heterogeneity of the estimated Okun relationships. We find that indicators of more flexible labor markets (higher levels of education achievement in the population, lower rate of unionization, and a higher share of nonmanufacturing employment) are important determinants of the differences in Okun's coefficient across states. Finally, we show that Okun's relationship is not stable across specifications, which can lead to inaccurate estimates of the potential determinants of Okun's coefficient.

As of April 2024, almost ** percent of law students who graduated in 2023 in the United States were employed in law firm positions, while **** percent were working for the government.

The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels. Disclaimer: For information regarding future updates or preliminary/final data releases, please refer to the Bureau of Labor Statistics Release Calendar: https://www.bls.gov/cew/release-calendar.htm

In Denmark, the highest unemployment rate in 2022 could be found among youth between 25 and 29 years, who had an unemployment rate of 4.4 percent that year. People between 30 and 34 years had the second highest unemployment rate. On the other hand, the lowest unemployment rate was among people between 50 and 54 years of age. The unemployment rate in Denmark rose sharply in 2020 following the outbreak of COVID-19, but decreased again the following years.

 Receiving unemployment benefits in Denmark 

By law, Danes have the right to receive unemployment benefits. There are requirements to be eligible for unemployment benefits in Denmark: being a member of an unemployment insurance fund called “A-kasse” is necessary as well as having earned a specific amount of money in the past. In addition, being registered at the Public Employment Service is required and as of January 2019, only people who have stayed in Denmark, Greenland, Faroe Islands or another EU/EEA country in seven out of the last eight years can claim unemployment benefits.

Labor market

Since 2012, the number of employed Danes was growing each year, but experienced a setback in 2020 due to COVID-19. The Danish labor market is known for the Flexicurity Model – a combination of market economy and a welfare state, and due to this model, the labor market can reflect the needs of employers and guarantee the welfare of employees which creates many possibilities for both sides.

The Law of 14 November 1996 implementing the City Recovery Pact (PRV) distinguishes three levels of intervention: sensitive urban areas, urban revitalisation zones (ZRUs), urban free zones (ZFU). These three levels of intervention ZUS, ZRU and ZFU, characterised by schemes of increasing importance, aim to respond to different degrees of difficulties encountered in these neighbourhoods.The sensitive urban areas are suburban areas defined by the public authorities to be the priority target of city policy, depending on local considerations linked to the difficulties faced by the inhabitants of these territories. Sensitive urban areas are defined in the PRV Act as areas “characterised by the presence of large settlements or degraded areas of habitat and by an increased imbalance between housing and employment”. The SEZs were determined on qualitative criteria (large sets, employment/habitat imbalance) through a joint community-state analysis. These areas are now part of the priority areas of urban social cohesion contracts (CUCS).In addition, the PRV law states that “urban revitalisation areas correspond to those of sensitive urban areas [...] which face particular difficulties, assessed according to their situation in the agglomeration, their economic and commercial characteristics and a summary index. taking into account the number of inhabitants of the neighbourhood, the unemployment rate, the proportion of young people under the age of 25, the proportion of people leaving the school system without a diploma, and the fiscal potential of the municipalities concerned.”The former ZUS are archived and are no longer included in this dataset.

This data collection is part of a continuing series of monthly surveys that evaluate the Bush presidency and solicit opinions on a variety of political and social issues. Topics covered include the economy, foreign affairs, the most important problem facing this country, who was most responsible for doing something about this problem, and which political party better represented the interests of poor people, rich people, and the middle class. In addition, respondents were questioned on whether they thought people in government wasted a lot of money and whether most of them were dishonest. Respondents were also asked if they had a favorable impression of certain people who might run in the presidential election, whom they would vote for if the House of Representatives election were held that day, and toward which candidate they were leaning. Other subjects addressed included whether respondents supported a federal law requiring businesses with more than 50 employees to allow workers 12 weeks of unpaid leave and a federal law giving unemployed people as much as 20 weeks of extra unemployment benefits, whether the United States should cut military spending because of the changes in the Soviet Union, and whether the Senate should have confirmed Clarence Thomas's nomination to the Supreme Court. Background information on respondents includes political alignment, 1988 presidential vote choice, education, age, religion, social class, marital status, number of people in household, labor union membership, employment status, race, income, sex, and state/region of residence.

The German social benefit system, which is shown in different overviews in this data compilation, has a long history. It was constructed mainly in the last 130 years but his has some substantially older roots. The present data tables give an overview over the historical perspective of the current social benefit system. Based on the suggestions of Bismarck, the emperor Wilhelm I. announced the social security legislation on November 17th of 1881. One of the main reasons for the development of social security institutions in the 80s of the 19th century was increasing importance of the working class movement in addition to the growing awareness of the need to improve the social status of workers. The social security legislation was introduced due to the convictions that “for healing the social damages is not enough to repress the socio-democratic movement, it is also necessary positively promote the welfare of the workers.” In its following sessions the Reichstag adopted the three pillars of social security: 1. the law concerning the health insurance of workers from June 15th of 1883, 2. the law on accident insurance from July 6th of 1884; and 3. the law concerning the invalidity and old age security from July 22 of 1889. In the Weimar Republic labor market policies were newly developed. In 1927 the tasks of occupational counselling, employment services and unemployment insurance were summarized trough the law of employment services and unemployment insurance and delegated to the responsibility of the Reich´s institute of employment („Reichsanstalt für Arbeit“)With the foundation of the Federal Republic of Germany, the political goal of a welfare state was revived and cultivated. In 1952 the self-administration of insurance providers was reintroduced. Besides the former social security system, which includes the protection against risks of accidents, sickness, old-age and unemployment, in the Federal Republic of Germany, the system of social security was expanded: Social-compensation schemes (war victims, load balancing), minimum social security (social assistance, basic security in old age and disability), long-term care and other social transfers (in the context of housing policy, the policy educational grants, family policy, youth and elderly care, the promotion of wealth creation). The legal basis of the minimum benefit until the reporting period until 2004 is the federal law on public welfare from 1961, the law on a need orientated basis security in old ages and in case of the reduction of income from 2003 (both laws were transferred in the 12th volume of the Social Security Code), the Asylum Seekers Benefits Act from 1993 and the "basic support for job seekers" which became law in 2005. Central variables of the statistics on social security, as well as on supplementary systems of social security, are the number of insured persons or beneficiaries (by sex, age, nationality, etc.), the financial status of the insurance providers (especially the statistics on income and expenditure), where concerning the expenditures a distinct differentiation by benefits will be undertaken. Other important statistical values are the contribution rates of the different schemes of social security and the employee distributions of social security. The Federal Ministry of Labor and Social Affairs generates a social budget on a regular basis, which represents the social benefits divided by institutions, functions and types as well as the financing of the social benefits. The total amount of social benefits is then expressed in relation to the (nominal) gross domestic product through the so called social expenditure ratio. This key ratio is a rough indicator on the inclusion of social benefits in the entire economic system. Data tables in HISTAT:The following overview contains the structure of the data tables:A. Overviews, published by the Federal Ministry of Labor and Social A.01 Basic data on social security in the Federal Republic of Germany (FRG)A.02 Health insurance in the FRD A.03 Pension insurance in the FRD A.04 Accident insurance in the FRD A.05 Promotion of employment / unemployment benefits (I and II) in the FRGA.06 War victim benefits in the FRG A.07 Asylum seekers benefits in the FRG A.08 Child benefits in the FRG A.09 Social assistance in the FRG A.10 Nursing care insurance in the FRG B. Social security in Germany from 1960 on B.01 Pension insuranceB.02 Health insurance B.03 Overviews on the social budget (Date in 10 – year intervals)B.04 Social nursing care insurance B.05 Basic parameters concerning the unemployment insuranceB.06 Assessment ceiling and contribution rates for different schemes of social securityB.07 Social assistanceC. Development of the German social security systems until 1938 C.01 Statutory health insurance (1885-1938)C.02 Statutory accident insurance (1885-1938)C.03 Statutory pension insurance for workers (1891-1938)C.04 Statutory pension insurance for clerical employees (1913-1938)C.05 Pen...

The Law of 14 November 1996 implementing the City Recovery Pact (PRV) distinguishes three levels of intervention: sensitive urban areas, urban revitalisation zones (ZRUs), urban free zones (ZFU). These three levels of intervention ZUS, ZRU and ZFU, characterised by schemes of increasing importance, aim to respond to different degrees of difficulties encountered in these neighbourhoods.The sensitive urban areas are suburban areas defined by the public authorities to be the priority target of city policy, depending on local considerations linked to the difficulties faced by the inhabitants of these territories. Sensitive urban areas are defined in the PRV Act as areas “characterised by the presence of large settlements or degraded areas of habitat and by an increased imbalance between housing and employment”. The SEZs were determined on qualitative criteria (large sets, employment/habitat imbalance) through a joint community-state analysis. These areas are now part of the priority areas of urban social cohesion contracts (CUCS).In addition, the PRV law states that “urban revitalisation areas correspond to those of sensitive urban areas [...] which face particular difficulties, assessed according to their situation in the agglomeration, their economic and commercial characteristics and a summary index. taking into account the number of inhabitants of the neighbourhood, the unemployment rate, the proportion of young people under the age of 25, the proportion of people leaving the school system without a diploma, and the fiscal potential of the municipalities concerned.”The former ZUS are archived and are no longer included in this dataset.

The survey charted young adults' attitudes towards politics, their opinions on the principal issues in politics, and their views on the current political questions. The respondents' interest in politics was queried, as well as how firm the respondents considered their political views and party preference to be. They were also presented with a set of attitudinal statements on topics such as voting, political parties, the Government, political system in Finland, politicians, values, the EU, development aid, immigrants, leadership, democracy, large-scale enterprises, welfare state, social benefits, traditional Finnish values, law, equality between men and women, animal rights, patriotism, and competition. Background variables included the respondent's municipality of residence, gender, age, marital status, type of accommodation, education level, duration of residence in the current municipality, and socio-economic status. Those who were employed were asked about their industry of employment and occupational status, students were asked about their educational institution and main subject, and those who were unemployed were in turn asked about the duration of unemployment during the past two years. Additional background variables included membership in various organisations or associations (e.g. sports clubs, youth organisations, student associations), how citizens should relate to elections and voting, whether R were going to use the right to vote in the future, which party R would vote for in parliamentary elections, which party R voted for in the recent municipal elections, and which candidate R is going to vote for in the upcoming 2000 presidential elections.

• Degree of interest in current news on various topics.
• Opinion on the degree of danger to humans and the environment of scientific advances in fields such as biotechnology or genetic engineering.
• Assessment of different uses of genetic engineering.
• Willingness to consume potatoes genetically treated with corn genes (to increase their nutritional value).
• Degree according to the use of genetic engineering, for different purposes, in human cells.
• Knowledge of the meaning of the concept 'cloning'.
• Assessment of the possibility that in a few years animal cloning will be a common scientific practice. Opinion on whether in 10 or 20 years it will be possible, scientifically, human cloning.
• The phrase with which he most agrees on the need to legally limit research and experiments on human cloning. Opinion on whether a law should be made in Spain that would prevent or limit human cloning.
• Assessment of the risks and benefits that the development of science and technology will entail in the next 20 years.
• Opinion on the three main problems in Spain.
• Assessment of the current economic situation of the country, retrospective and expectations to one year. Attitude to the existence in our country of the jury trial.
• Personal preference by judge or jury, for sentencing, in the case of being charged in a criminal trial.
• Phrase with which he agrees most about whether judges or juries are the fairest in their decisions.
• Personal attitude towards being part of a jury in a trial.
• Knowledge of the 'Otegui case' (the acquittal, by a jury of San Sebastian, of the accused for the death of two ertzainas).
• Phrase with which he agrees more on the need to review and modify the Law of the Jury after experiences such as the 'Otegui case'.
• Degree according to different opinions on the limits of jurisdiction of the popular jury.
• Opinion on the importance of political agreement to carry out a reform of the Jury Law.
• Assessment of the current political situation in the country and one-year expectations.
• Knowledge about the celebration in the Senate of the debate of the State of the Autonomies. Interest with which he has followed the news about the debate and means of communication by which it was reported.
• Opinion on the influence of the debate on improving the functioning of the State of Autonomies.
• Ideology scale of the interviewee.
• Remembrance of vote in the general elections of March 1996.
• Electoral volatility in general elections in March 1996.
• Employment and unemployment expectations.

This dataset contains the perimeters (surface objects) of sensitive urban areas (ZUS) including those of the urban revitalisation zone (ZRU) of the New Aquitaine region. PLEASE NOTE: this dataset is not exhaustive on the perimeter of New Aquitaine. It concerns the perimeter of the former Aquitaine region. The Law of 14 November 1996 implementing the City Recovery Pact (PRV) distinguishes three levels of intervention: sensitive urban areas, urban revitalisation zones (ZRUs), urban free zones (ZFU). These three levels of intervention ZUS, ZRU and ZFU, characterised by devices of increasing importance, aim to respond to different degrees of difficulties encountered in these neighbourhoods. Sensitive urban areas are infra-urban areas defined by the public authorities to be the priority target of city policy, depending on local considerations related to the difficulties faced by the inhabitants of these territories. Sensitive urban areas are defined in the PRV Act as areas “characterised by the presence of large settlements or degraded areas of habitat and by an increased imbalance between housing and employment”. The SEZs were determined on qualitative criteria (large sets, employment/habitat imbalance) through a joint community-state analysis. These areas are also part of the priority areas of urban social cohesion contracts (CUCS). In addition, the PRV law states that 'urban revitalisation areas correspond to those in sensitive urban areas... which face particular difficulties, assessed on the basis of their situation in the agglomeration, their economic and commercial characteristics and a synthetic index. It is established, under conditions laid down by decree, taking into account the number of inhabitants of the neighbourhood, the unemployment rate, the proportion of young people under the age of 25, the proportion of people leaving the school system without a diploma and the tax potential of the municipalities concerned.’

The Law of 14 November 1996 implementing the City Recovery Pact (PRV) distinguishes three levels of intervention: sensitive urban areas, urban revitalisation zones (ZRUs), urban free zones (ZFU). These three levels of intervention ZUS, ZRU and ZFU, characterised by devices of increasing importance, aim to respond to different degrees of difficulties encountered in these neighbourhoods. Sensitive urban areas are infra-urban areas defined by the public authorities to be the priority target of city policy, depending on local considerations related to the difficulties faced by the inhabitants of these territories. Sensitive urban areas are defined in the PRV Act as areas “characterised by the presence of large settlements or degraded areas of habitat and by an increased imbalance between housing and employment”. The SEZs were determined on qualitative criteria (large sets, employment/habitat imbalance) through a joint community-state analysis. These areas are now among the priority areas of urban social cohesion contracts (CUCS). In addition, the PRV Law states that ‘urban revitalisation areas correspond to those in sensitive urban areas... which face particular difficulties, assessed on the basis of their situation in the agglomeration, their economic and commercial characteristics and a summary index. This is established, under conditions laid down by decree, taking into account the number of inhabitants of the district, the rate of unemployment, the proportion of young people under 25 years of age, the proportion of persons leaving the school system without a diploma and the fiscal potential of the municipalities concerned’. The old ZUS are archived and are no longer included in this dataset.

The Law of 14 November 1996 implementing the City Recovery Pact (PRV) distinguishes three levels of intervention: sensitive urban areas, urban revitalisation zones (ZRUs), urban free zones (ZFU). These three levels of intervention ZUS, ZRU and ZFU, characterised by devices of increasing importance, aim to respond to different degrees of difficulties encountered in these neighbourhoods. Sensitive urban areas are infra-urban areas defined by the public authorities to be the priority target of city policy, depending on local considerations related to the difficulties faced by the inhabitants of these territories. Sensitive urban areas are defined in the PRV Act as areas “characterised by the presence of large settlements or degraded areas of habitat and by an increased imbalance between housing and employment”. The SEZs were determined on qualitative criteria (large sets, employment/habitat imbalance) through a joint community-state analysis. These areas are now among the priority areas of urban social cohesion contracts (CUCS). In addition, the PRV Law states that ‘urban revitalisation areas correspond to those in sensitive urban areas... which face particular difficulties, assessed on the basis of their situation in the agglomeration, their economic and commercial characteristics and a summary index. This is established, under conditions laid down by decree, taking into account the number of inhabitants of the district, the rate of unemployment, the proportion of young people under 25 years of age, the proportion of persons leaving the school system without a diploma and the fiscal potential of the municipalities concerned’. The old ZUS are archived and are no longer included in this dataset.