- What is the Median Female Earnings?
- What is the Median Male Earnings?
- What is the Median Female Earnings (Full Time)?
- What is the Median Male Earnings (Full Time)?
- What is the Median Earnings Less Than High School?
- What is the Median Earnings High School?
- What is the Median Earnings Some College or Associates?
- What is the Median Earnings Bachelor Degree?
- What is the Median Earnings Graduate or Professional Degree?
- What is the Percent Earning less than $10,000?
The median earnings of New Orleans Metro Area (LA) was $30,544 in 2013.
Earnings and Gender
Earnings and Education
Jobs and Earnings Datasets Involving New Orleans Metro Area (LA)
- API data.nola.gov | Last Updated 2015-10-13T21:53:14.000Z
This dataset is created by the City's Office of Performance and Accountability using data on household income from the U.S. Census Bureau's Public Use Microdata Samples. It includes data for the following cities: Tampa, Florida; Memphis, Tennessee; Louisville, Kentucky; Nashville, Tennessee; Raleigh, North Carolina; Atlanta, Georgia; Baton Rouge, Louisiana; New Orleans, Louisiana. This data is compiled annually beginning in 2005.
- API data.nola.gov | Last Updated 2016-02-16T21:27:01.000Z
This data on median household income by race and ethnicity comes from the U.S. Census Bureau's American Community Survey (ACS) one-year estimates, which are published on an annual basis. It includes data for the following cities: Tampa, Florida; Memphis, Tennessee; Louisville, Kentucky; Nashville, Tennessee; Raleigh, North Carolina; Atlanta, Georgia; Baton Rouge, Louisiana; New Orleans, Louisiana. This data covers the time period of 2007 to present.
- API opendata.utah.gov | Last Updated 2014-10-31T18:29:13.000Z
Median Household Income All States 2000-2012
- API data.orcities.org | Last Updated 2016-12-06T21:28:37.000Z
This is the survey responses for the 2017 State of the Cities Report. This data has been coded based on survey response choices. Please consult the attached copy of the survey for more information.
- API data.ny.gov | Last Updated 2016-06-30T19:36:57.000Z
The dataset presented in this forum is monthly data. The Port Authority collects monthly data for domestic and international, cargo, flights, passengers and aircraft equipment type from each carrier at PANYNJ-operated airports. The data is aggregated and forms the basis for estimating flight fees, parking, concession, and PFC revenues at the Port Authority Airports.
- API mydata.iadb.org | Last Updated 2017-06-21T16:17:36.000Z
This database provides information on the currency and maturity structure of firm liabilities for 10 Latin American Countries. The database builds on a joint project carried out by the research department of the IADB and 6 country teams in 2002. Country average data is available for immediate download in excel format below. Detailed information on the variables, sample and sources are provided in the documentation file (included in the zip file). Studies using this data should cite the source as: H. Kamil (2004), 'A new database on the currency composition and maturity structure of firms' balance sheets in Latin America, 1990-2002". Years covered: 1990-2002.
- API data.ny.gov | Last Updated 2016-06-30T19:26:37.000Z
The dataset presented in this forum is monthly data. The Port Authority collects monthly data for domestic and international cargo, flights, passengers and aircraft equipment type from each carrier at PANYNJ-operated airports. The data is aggregated and forms the basis for estimating flight fees, parking, concession, and PFC revenues at the Port Authority Airports.
- API data.imls.gov | Last Updated 2016-12-07T00:10:49.000Z
Pull up a state's profile to find state-level totals on key data such as numbers of libraries and librarians, revenue and expenditures, and collection sizes.<br><br>These data include imputed values for libraries that did not submit information in the FY 2014 data collection. Imputation is a procedure for estimating a value for a specific data item where the response is missing. <br><br>Download PLS data files to see imputation flag variables or learn more on the imputation methods used in FY 2014 at https://www.imls.gov/research-evaluation/data-collection/public-libraries-survey/explore-pls-data/pls-data
- API data.cambridgema.gov | Last Updated 2017-03-16T21:11:24.000Z
This dataset outlines the ways in which the Laborforce commutes to work in Cambridge, organized by characteristics of the population. Specifically, by age, vehicles available, time arriving, time spent traveling, and annual household income. The data for this dataset originates from three sources: Journey to Work data supplied to the Massachusetts Central Transportation Planning Staff by the Census Bureau, a special tabulation of 2000 Decennial Census data the 2000 Census Transportation Planning Products (CTPP), and the most recent version of the CTPP. For more information on Journey to Work data in Cambridge, please see the full 2015 report (https://www.cambridgema.gov/~/media/Files/CDD/FactsandMaps/profiles/moving_forward_20150930.ashx?la=en).
- API mydata.iadb.org | Last Updated 2017-06-30T18:16:07.000Z
The database allows estimating structural fiscal balances for 20 countries in the region under different assumptions regarding the output gap and commodity structural prices. It is a unique database of its kind since: 1) It takes into consideration the distinct responsiveness of different types of revenues to changes in the output gap: In order to adjust for the impact of the business cycle on revenues, we calculate individual elasticities for each source of revenue (i.e. direct taxes, indirect taxes, revenues from non-renewable resources, etc.). Since the different types of revenues in the region have different sensitivities to changes in the output gap, this disaggregated approach allows for a more fine-tuned adjustment. 2) It includes estimations of SFBs based on output gaps’ projections available in “real time”. In addition to giving estimations of the actual SFBs, we provide with estimations of the SFBs that would have resulted should the projections on output gaps available to policymakers at the time of designing fiscal policy (data in “real time”) have been correct. This is in contrast to much of the existing work on structural fiscal balances that makes only an “ex post” analysis using actual and revised information on the output gaps. 3) It allows assessing the response of fiscal policy to the business cycle. We provide with measures of the fiscal impulse, assessing not only the actual but also the intentional fiscal stance, as well as the degree of procyclicality of fiscal policy.<br><br><b>Click here to access the data: https://mydata.iadb.org/idb/dataset/3itg-avtz</b></br></br>