Total Nonfarm and Private Sector Jobs Increased in February 2023

Total Nonfarm and Private Sector Jobs (in 1000s), January 1990 – February 2023

Statewide Unemployment

February 2023 – Seasonally Adjusted

The Labor Force Increased and Number of Unemployed Fell in February

Total Labor Force & Number of Unemployed, January 2009 – February 2023

Unemployment Rate Held Steady in NYS and Increased in the US

Unemployment Rate, NYS & US, January 2009 – February 2023

Unemployment Rate Increased in NYC and Decreased in Balance of State

Unemployment Rate, NYC & BOS, January 2009 – February 2023

Substate and Industry Employment

February 2023 – Not Seasonally Adjusted

New York State Matched Nation in Private Sector Job Growth

Over-the-Year Change in Total Nonfarm & Private Sector Jobs, February 2022 – February 2023

Note: The sum of sub-state area job estimates will usually differ from the New York State total. This is because the State total is calculated separately from the sub-state areas and is estimated based on an independent sample.

The Number of Leisure & Hospitality Jobs Increased by 9.6% Over the Year

Over-the-Year Change in Jobs by Major Industry Sector, February 2022 – February 2023

*Government includes public education and public health services.

Note: The responsibility for the production of monthly estimates of state and metro area nonfarm employment by industry moved from the NYS Department of Labor’s Division of Research and Statistics to the U.S. Bureau of Labor Statistics (BLS), starting with the March 2011 estimates. More detailed information on the change is available on the BLS web site.[1]

Many economic data series have a seasonal pattern, which means they tend to occur at the same time each year (e.g., retail jobs usually increase in December). Seasonal adjustment is the process of removing seasonal effects from a data series. This is done to simplify the data so that they may be more easily interpreted and help to reveal true underlying trends. Seasonal adjustment permits comparisons of data from one month to data from any other month.

In New York State, payroll jobs data by industry come from a monthly survey of business establishments conducted by the U.S. Bureau of Labor Statistics. Data are preliminary and subject to revision. Jobs data by industry do not include agricultural workers, the self-employed, unpaid family workers, or domestic workers in private households.

Labor force statistics, including the unemployment rate, for New York and every other state are based on statistical regression models specified by the U. S. Bureau of Labor Statistics. The state’s unemployment rate is based partly upon the results of the Current Population Survey, which contacts approximately 3,100 households in New York each month.

 Jobs and Unemployment Fact Sheet

This fact sheet conveys important technical information that will contribute to a better understanding of labor force data (“household survey”), including resident employment/unemployment rates, and jobs by industry data (“business survey”), which are presented in the New York State Department of Labor’s monthly press release.

State Unemployment Rates Based on Regression Model

Beginning with data for January 1996, unemployment rates for New York State and all other states (as well as New York City and the City of Los Angeles) have been estimated using time-series regression statistical models developed by the U.S. Bureau of Labor Statistics (BLS).

Advantage of Regression Model

Use of a time-series regression model reduces the month-to-month variation in unemployment rates and resident employment by reducing variation caused by sampling errors and other components of statistical noise (irregularities).

Benchmarking of Estimates

Once each year, labor force estimates, such as civilian labor force and the unemployment rate, are revised to reflect updated input data including new Census Bureau populations controls, newly revised establishment jobs data and new state-level annual average data from the Current Population Survey (CPS). As part of this procedure, all state figures are reviewed, revised as necessary and then re-estimated. This process is commonly referred to as “benchmarking.”

Changes in Methodology

Labor force estimates are now produced with an improved time-series regression model, which utilizes “real-time” benchmarking. “Real-time” benchmarking reduces end-of-year revisions, which also means that major economic events will be reflected in a more timely manner in state labor force estimates.

In addition, the new methodology includes an updated way of estimating for sub-state areas (e.g. counties, metro areas) the number of unemployed who are new entrants or re-entrants into the labor force. This change in methodology will result in lower unemployment rates in some areas and increased rates in others.

Unemployed and UI Beneficiaries

The estimate of the number of unemployed includes all persons who had no employment during the reference week (the week including the 12th of the month), were available for work, except for temporary illness, and had made specific efforts to find employment sometime during the 4-week period ending with the reference week. Unemployment insurance (UI) beneficiaries include those who apply for and qualify for UI benefits. Consequently, the estimate of the number of unemployed and the number of UI beneficiaries do not necessarily move in tandem.

Jobs Data

Jobs data are obtained from a separate joint federal-state survey of business establishments. The survey, called the Current Employment Statistics of Establishments, has a sample size of 18,000 establishments in New York State. It excludes self-employed workers, agricultural workers, unpaid family workers and domestic workers employed by private households. This data represents a count of jobs by place of work. Data for each month is revised the following month as more complete information becomes available.

The New York State Department of Labor is an Equal Opportunity Employer/Program.

Auxiliary aids and services are available upon request to individuals with disabilities.