Unemployment or joblessness is a situation in which able-bodied people who are looking for a job cannot find a job. The causes of unemployment are debated. Classical economics, new classical economics, the Austrian School of economics argued that market mechanisms are reliable means of resolving unemployment; these theories argue against interventions imposed on the labor market from the outside, such as unionization, bureaucratic work rules, minimum wage laws and other regulations that they claim discourage the hiring of workers. Keynesian economics emphasizes the cyclical nature of unemployment and recommends government interventions in the economy that it claims will reduce unemployment during recessions; this theory focuses on recurrent shocks that reduce aggregate demand for goods and services and thus reduce demand for workers. Keynesian models recommend government interventions designed to increase demand for workers, its namesake economist John Maynard Keynes, believed that the root cause of unemployment is the desire of investors to receive more money rather than produce more products, not possible without public bodies producing new money.
A third group of theories emphasize the need for a stable supply of capital and investment to maintain full employment. On this view, government should guarantee full employment through fiscal policy, monetary policy and trade policy as stated, for example, in the US Employment Act of 1946, by counteracting private sector or trade investment volatility, reducing inequality. In addition to theories of unemployment, there are a few categorizations of unemployment that are used to more model the effects of unemployment within the economic system; some of the main types of unemployment include structural unemployment and frictional unemployment, as well as cyclical unemployment, involuntary unemployment, classical unemployment. Structural unemployment focuses on foundational problems in the economy and inefficiencies inherent in labor markets, including a mismatch between the supply and demand of laborers with necessary skill sets. Structural arguments emphasize causes and solutions related to disruptive technologies and globalization.
Discussions of frictional unemployment focus on voluntary decisions to work based on each individuals' valuation of their own work and how that compares to current wage rates plus the time and effort required to find a job. Causes and solutions for frictional unemployment address job entry threshold and wage rates; the unemployment rate is a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals in the labor force. During periods of recession, an economy experiences a high unemployment rate. Millions of people globally or 6% of the world's workforce were without a job in 2012; the state of being without any work yet looking for work is called unemployment. Economists distinguish between various overlapping types of and theories of unemployment, including cyclical or Keynesian unemployment, frictional unemployment, structural unemployment and classical unemployment; some additional types of unemployment that are mentioned are seasonal unemployment, hardcore unemployment, hidden unemployment.
Though there have been several definitions of "voluntary" and "involuntary unemployment" in the economics literature, a simple distinction is applied. Voluntary unemployment is attributed to the individual's decisions, whereas involuntary unemployment exists because of the socio-economic environment in which individuals operate. In these terms, much or most of frictional unemployment is voluntary, since it reflects individual search behavior. Voluntary unemployment includes workers who reject low wage jobs whereas involuntary unemployment includes workers fired due to an economic crisis, industrial decline, company bankruptcy, or organizational restructuring. On the other hand, cyclical unemployment, structural unemployment, classical unemployment are involuntary in nature. However, the existence of structural unemployment may reflect choices made by the unemployed in the past, while classical unemployment may result from the legislative and economic choices made by labour unions or political parties.
The clearest cases of involuntary unemployment are those where there are fewer job vacancies than unemployed workers when wages are allowed to adjust, so that if all vacancies were to be filled, some unemployed workers would still remain. This happens with cyclical unemployment, as macroeconomic forces cause microeconomic unemployment which can boomerang back and exacerbate these macroeconomic forces. Classical, or real-wage unemployment, occurs when real wages for a job are set above the market-clearing level causing the number of job-seekers to exceed the number of vacancies. On the other hand, most economists argue that as wages fall below a livable wage many choose to drop out of the labor market and no longer seek employment; this is true in countries where low-income families are supported through public welfare systems. In such cases, wages would have to be high enough to motivate people to choose employment over what they receive through public welfare. Wages below a livable wage are to result in lower labor market participation in the above-stated scenario.
In addition, consumption of goods and services is the primary driver of increased demand for labor. Higher wages lead to workers having more income available to consume services. Therefore, higher wages increase gene
In economics, a discouraged worker is a person of legal employment age, not seeking employment or who does not find employment after long-term unemployment. This is because an individual has given up looking or has had no success in finding a job, hence the term "discouraged". In other words if a person is still looking for a job, that person may have fallen out of the core statistics of unemployment rate after long-term unemployment and is therefore by default classified as "discouraged". In some cases, their belief may derive from a variety of factors including a shortage of jobs in their locality or line of work; as a general practice, discouraged workers, who are classified as marginally attached to the labor force, on the margins of the labor force, or as part of hidden unemployment, are not considered part of the labor force, are thus not counted in most official unemployment rates—which influences the appearance and interpretation of unemployment statistics. Although some countries offer alternative measures of unemployment rate, the existence of discouraged workers can be inferred from a low employment-to-population ratio.
In the United States, a discouraged worker is defined as a person not in the labor force who wants and is available for a job and who has looked for work sometime in the past 12 months, but, not looking because of real or perceived poor employment prospects. The Bureau of Labor Statistics does not count discouraged workers as unemployed but rather refers to them as only "marginally attached to the labor force"; this means that the measured unemployment captures so-called "frictional unemployment" and not much else. This has led some economists to believe that the actual unemployment rate in the United States is higher than what is reported while others suggest that discouraged workers voluntarily choose not to work. Nonetheless, the U. S. Bureau of Labor Statistics has published the discouraged worker rate in alternative measures of labor underutilization under U-4 since 1994 when the most recent redesign of the CPS was implemented; the United States Department of Labor first began tracking discouraged workers in 1967 and found 500,000 at the time.
Today, In the United States, according to the U. S. Bureau of Labor Statistics as of April 2009, there are 740,000 discouraged workers. There is an ongoing debate as to whether discouraged workers should be included in the official unemployment rate. Over time, it has been shown that a disproportionate number of young people, blacks and men make up discouraged workers. Nonetheless, it is believed that the discouraged worker is underestimated because it does not include homeless people or those who have not looked for or held a job during the past twelve months and is poorly tracked. According to the U. S. Bureau of Labor Statistics, the top five reasons for discouragement are the following: The worker thinks no work is available; the worker could not find work. The worker lacks training; the worker is viewed too old by the prospective employer. The worker is the target of various types of discrimination. In Canada, discouraged workers are referred to as hidden unemployed because of their behavioral pattern, are described as on the margins of the labour force.
Since the numbers of discouraged workers and of unemployed move in the same direction during the business cycle and the seasons, some economists have suggested that discouraged workers should be included in the unemployment numbers because of the close association. The information on the number and composition of the discouraged worker group in Canada originates from two main sources. One source is the monthly Labour Force Survey, which identifies persons who looked for work in the past six months but who have since stopped searching; the other source is the Survey of Job Opportunities, much closer in design to the approach used in many other countries. In this survey, all those expressing a desire for work and who are available for work are counted, irrespective of their past job search activity. In Canada, while discouraged workers were once less educated than "average workers", they now have better training and education but still tend to be concentrated in areas of high unemployment. Discouraged workers are not seeking a job for one of two reasons: labour market-related reasons and personal and other reasons.
Unemployment statistics published according to the ILO methodology may understate actual unemployment in the economy. The EU statistical bureau EUROSTAT started publishing figures on discouraged workers in 2010. According to the method used by EUROSTAT there are 3 categories. In 2012 there were 9.2 million underemployed part-time workers, 2.3 million jobless persons seeking a job but not available f
United States Census Bureau
The United States Census Bureau is a principal agency of the U. S. Federal Statistical System, responsible for producing data about the American people and economy; the Census Bureau is part of the U. S. Department of Commerce and its director is appointed by the President of the United States; the Census Bureau's primary mission is conducting the U. S. Census every ten years, which allocates the seats of the U. S. House of Representatives to the states based on their population; the Bureau's various censuses and surveys help allocate over $400 billion in federal funds every year and it helps states, local communities, businesses make informed decisions. The information provided by the census informs decisions on where to build and maintain schools, transportation infrastructure, police and fire departments. In addition to the decennial census, the Census Bureau continually conducts dozens of other censuses and surveys, including the American Community Survey, the U. S. Economic Census, the Current Population Survey.
Furthermore and foreign trade indicators released by the federal government contain data produced by the Census Bureau. Article One of the United States Constitution directs the population be enumerated at least once every ten years and the resulting counts used to set the number of members from each state in the House of Representatives and, by extension, in the Electoral College; the Census Bureau now conducts a full population count every 10 years in years ending with a zero and uses the term "decennial" to describe the operation. Between censuses, the Census Bureau makes population projections. In addition, Census data directly affects how more than $400 billion per year in federal and state funding is allocated to communities for neighborhood improvements, public health, education and more; the Census Bureau is mandated with fulfilling these obligations: the collecting of statistics about the nation, its people, economy. The Census Bureau's legal authority is codified in Title 13 of the United States Code.
The Census Bureau conducts surveys on behalf of various federal government and local government agencies on topics such as employment, health, consumer expenditures, housing. Within the bureau, these are known as "demographic surveys" and are conducted perpetually between and during decennial population counts; the Census Bureau conducts economic surveys of manufacturing, retail and other establishments and of domestic governments. Between 1790 and 1840, the census was taken by marshals of the judicial districts; the Census Act of 1840 established a central office. Several acts followed that revised and authorized new censuses at the 10-year intervals. In 1902, the temporary Census Office was moved under the Department of Interior, in 1903 it was renamed the Census Bureau under the new Department of Commerce and Labor; the department was intended to consolidate overlapping statistical agencies, but Census Bureau officials were hindered by their subordinate role in the department. An act in 1920 changed the date and authorized manufacturing censuses every two years and agriculture censuses every 10 years.
In 1929, a bill was passed mandating the House of Representatives be reapportioned based on the results of the 1930 Census. In 1954, various acts were codified into Title 13 of the US Code. By law, the Census Bureau must count everyone and submit state population totals to the U. S. President by December 31 of any year ending in a zero. States within the Union receive the results in the spring of the following year; the United States Census Bureau defines four statistical regions, with nine divisions. The Census Bureau regions are "widely used...for data collection and analysis". The Census Bureau definition is pervasive. Regional divisions used by the United States Census Bureau: Region 1: Northeast Division 1: New England Division 2: Mid-Atlantic Region 2: Midwest Division 3: East North Central Division 4: West North Central Region 3: South Division 5: South Atlantic Division 6: East South Central Division 7: West South Central Region 4: West Division 8: Mountain Division 9: Pacific Many federal, state and tribal governments use census data to: Decide the location of new housing and public facilities, Examine the demographic characteristics of communities and the US, Plan transportation systems and roadways, Determine quotas and creation of police and fire precincts, Create localized areas for elections, utilities, etc.
Gathers population information every 10 years The United States Census Bureau is committed to confidentiality, guarantees non-disclosure of any addresses or personal information related to individuals or establishments. Title 13 of the U. S. Code establishes penalties for the disclosure of this information. All Census employees must sign an affidavit of non-disclosure prior to employment; the Bureau cannot share responses, addresses or personal information with anyone including United States or foreign government
Labour economics seeks to understand the functioning and dynamics of the markets for wage labour. Labour markets or job markets function through the interaction of employers. Labour economics looks at the suppliers of labour services and the demanders of labour services, attempts to understand the resulting pattern of wages and income. Labour is a measure of the work done by human beings, it is conventionally contrasted with such other factors of production as capital. Some theories focus on human capital. There are two sides to labour economics. Labour economics can be seen as the application of microeconomic or macroeconomic techniques to the labour market. Microeconomic techniques study individual firms in the labour market. Macroeconomic techniques look at the interrelations between the labour market, the goods market, the money market, the foreign trade market, it looks at how these interactions influence macro variables such as employment levels, participation rates, aggregate income and gross domestic product.
The labour force is defined as the number of people of working age, who are either employed or looking for work. The participation rate is the number of people in the labour force divided by the size of the adult civilian noninstitutional population; the non-labour force includes those who are not looking for work, those who are institutionalised such as in prisons or psychiatric wards, stay-at home spouses and those serving in the military. The unemployment level is defined as the labour force minus the number of people employed; the unemployment rate is defined as the level of unemployment divided by the labour force. The employment rate is defined as the number of people employed divided by the adult population. In these statistics, self-employed people are counted as employed. Variables like employment level, unemployment level, labour force, unfilled vacancies are called stock variables because they measure a quantity at a point in time, they can be contrasted with flow variables. Changes in the labour force are due to flow variables such as natural population growth, net immigration, new entrants, retirements from the labour force.
Changes in unemployment depend on inflows made up of non-employed people starting to look for jobs and of employed people who lose their jobs and look for new ones, outflows of people who find new employment and of people who stop looking for employment. When looking at the overall macroeconomy, several types of unemployment have been identified, including: Frictional unemployment – This reflects the fact that it takes time for people to find and settle into new jobs. Technological advancement reduces frictional unemployment. Structural unemployment – This reflects a mismatch between the skills and other attributes of the labour force and those demanded by employers. Rapid industry changes of a technical and/or economic nature will increase levels of structural unemployment; the process of globalization has contributed to structural changes in labour markets. Natural rate of unemployment – This is the summation of frictional and structural unemployment, that excludes cyclical contributions of unemployment.
It is the lowest rate of unemployment that a stable economy can expect to achieve, given that some frictional and structural unemployment is inevitable. Economists do not agree on the level of the natural rate, with estimates ranging from 1% to 5%, or on its meaning – some associate it with "non-accelerating inflation"; the estimated rate varies from country from time to time. Demand deficient unemployment – In Keynesian economics, any level of unemployment beyond the natural rate is due to insufficient goods demand in the overall economy. During a recession, aggregate expenditure is deficient causing the underutilisation of inputs. Aggregate expenditure can be increased, according to Keynes, by increasing consumption spending, increasing investment spending, increasing government spending, or increasing the net of exports minus imports, since AE = C + I + G +. Neoclassical economists view the labour market as similar to other markets in that the forces of supply and demand jointly determine price and quantity.
However, the labour market differs from other markets in several ways. In particular, the labour market may act as a non-clearing market. While according to neoclassical theory most markets attain a point of equilibrium without excess supply or demand, this may not be true of the labour market: it may have a persistent level of unemployment. Contrasting the labour market to other markets reveals persistent compensating differentials among similar workers. Models that assume perfect competition in the labour market, as discussed below, conclude that workers earn their marginal product of labour. Households are suppliers of labour. In microeconomic theory, people are assumed to be rational and seeking to maximize their utility function. In the labour market model, their utility function expresses
In statistics, quality assurance, survey methodology, sampling is the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt for the samples to represent the population in question. Two advantages of sampling are lower cost and faster data collection than measuring the entire population; each observation measures one or more properties of observable bodies distinguished as independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design in stratified sampling. Results from probability theory and statistical theory are employed to guide the practice. In business and medical research, sampling is used for gathering information about a population. Acceptance sampling is used to determine if a production lot of material meets the governing specifications. Successful statistical practice is based on focused problem definition. In sampling, this includes defining the "population".
A population can be defined as including all people or items with the characteristic one wishes to understand. Because there is rarely enough time or money to gather information from everyone or everything in a population, the goal becomes finding a representative sample of that population. Sometimes what defines. For example, a manufacturer needs to decide whether a batch of material from production is of high enough quality to be released to the customer, or should be sentenced for scrap or rework due to poor quality. In this case, the batch is the population. Although the population of interest consists of physical objects, sometimes it is necessary to sample over time, space, or some combination of these dimensions. For instance, an investigation of supermarket staffing could examine checkout line length at various times, or a study on endangered penguins might aim to understand their usage of various hunting grounds over time. For the time dimension, the focus may be on discrete occasions.
In other cases, the examined'population' may be less tangible. For example, Joseph Jagger studied the behaviour of roulette wheels at a casino in Monte Carlo, used this to identify a biased wheel. In this case, the'population' Jagger wanted to investigate was the overall behaviour of the wheel, while his'sample' was formed from observed results from that wheel. Similar considerations arise when taking repeated measurements of some physical characteristic such as the electrical conductivity of copper; this situation arises when seeking knowledge about the cause system of which the observed population is an outcome. In such cases, sampling theory may treat the observed population as a sample from a larger'superpopulation'. For example, a researcher might study the success rate of a new'quit smoking' program on a test group of 100 patients, in order to predict the effects of the program if it were made available nationwide. Here the superpopulation is "everybody in the country, given access to this treatment" – a group which does not yet exist, since the program isn't yet available to all.
Note that the population from which the sample is drawn may not be the same as the population about which information is desired. There is large but not complete overlap between these two groups due to frame issues etc.. Sometimes they may be separate – for instance, one might study rats in order to get a better understanding of human health, or one might study records from people born in 2008 in order to make predictions about people born in 2009. Time spent in making the sampled population and population of concern precise is well spent, because it raises many issues and questions that would otherwise have been overlooked at this stage. In the most straightforward case, such as the sampling of a batch of material from production, it would be most desirable to identify and measure every single item in the population and to include any one of them in our sample. However, in the more general case this is not possible or practical. There is no way to identify all rats in the set of all rats. Where voting is not compulsory, there is no way to identify which people will vote at a forthcoming election.
These imprecise populations are not amenable to sampling in any of the ways below and to which we could apply statistical theory. As a remedy, we seek a sampling frame which has the property that we can identify every single element and include any in our sample; the most straightforward type of frame is a list of elements of the population with appropriate contact information. For example, in an opinion poll, possible sampling frames include an electoral register and a telephone directory. A probability sample is a sample in which every unit in the population has a chance of being selected in the sample, this probability can be determined; the combination of these traits makes it possible to produce unbiased estimates of population totals, by weighting sampled units according to their probability of selection. Example: We want to estimate the total income of adults living in a given street. We visit each household in that street, identify all adults living there, randomly select one adult from each household..
We interview the selected person and find their income
Civilian noninstitutional population
In the United States, the civilian noninstitutional population refers to people 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions, who are not on active duty in the Armed Forces. The data series can be obtained from the Federal Reserve Economic Database; as of September 2014, there were 248,446,000 persons in the civilian noninstitutional population out of a U. S. population of 320 million. It has grown along with the U. S. population 1% per year for 2005-2013 period. The measure is used to help gauge the percentage of the population, employed or in the workforce, as the denominator in the "civilian employment to population ratio" called the EM ratio, the "civilian labor force participation rate." Trends in these figures are shown in the first graphic. Current Population Survey Bureau of Labor Statistics Unemployment in the United States Civilian noninstitutional population in glossary, U. S. Bureau of Labor Statistics Division of Information Services