labor force

NYC and NYMA Pop Change Graph 2000 to 2019

New York’s Population and Migration Trends in the 2010s

The Weissman Center for International Business at Baruch College just published my paper, “New York’s Population and Migration Trends in the 2010s“, as part of their Occasional Paper Series. In the paper I study population trends over the last ten years for both New York City (NYC) and the greater New York Metropolitan Area (NYMA) using annual population estimates from the Census Bureau (vintage 2019), county to county migration data (2011-2018) from the IRS SOI, and the American Community Survey (2014-2018). I compare NYC to the nine counties that are home to the largest cities in the US (cities with population greater than 1 million) and the NYMA to the 13 largest metro areas (population over 4 million) to provide some context. I conclude with a brief discussion of the potential impact of COVID-19 on both the 2020 census count and future population growth. Most of the analysis was conducted using Python and Pandas in Jupyter Notebooks available on my GitHub. I discussed my method for creating rank change grids, which appear in the paper’s appendix and illustrate how the sources and destinations for migrants change each year, in my previous post.

Terminology

  • Natural increase: the difference between births and deaths
  • Domestic migration: moves between two points within the United States
  • Foreign migration: moves between the United States and a US territory or foreign country
  • Net migration: the difference between in-migration and out-migration (measured separately for domestic and foreign)
  • NYC: the five counties / boroughs that comprise New York City
  • NYMA: the New York Metropolitan Area as defined by the Office of Management and Budget in Sept 2018, consists of 10 counties in NY State (including the 5 NYC counties), 12 in New Jersey, and one in Pennsylvania
Map of the New York Metropolitan Area
The New York-Newark-Jersey City, NY-NJ-PA Metropolitan Area

Highlights

  • Population growth in both NYC and the NYMA was driven by positive net foreign migration and natural increase, which offset negative net domestic migration.
  • Population growth for both NYC and the NYMA was strong over the first half of the decade, but population growth slowed as domestic out-migration increased from 2011 to 2017.
  • NYC and the NYMA began experiencing population loss from 2017 forward, as both foreign migration and natural increase began to decelerate. Declines in foreign migration are part of a national trend; between 2016 and 2019 net foreign migration for the US fell by 43% (from 1.05 million to 595 thousand).
  • The city and metro’s experience fit within national trends. Most of the top counties in the US that are home to the largest cities and many of the largest metropolitan areas experienced slower population growth over the decade. In addition to NYC, three counties: Cook (Chicago), Los Angeles, and Santa Clara (San Jose) experienced actual population loss towards the decade’s end. The New York, Los Angeles, and Chicago metro areas also had declining populations by the latter half of the decade.
  • Most of NYC’s domestic out-migrants moved to suburban counties within the NYMA (representing 38% of outflows and 44% of net out-migration), and to Los Angeles County, Philadelphia County, and counties in Florida. Out-migrants from the NYMA moved to other large metros across the country, as well as smaller, neighboring metros like Poughkeepsie NY, Fairfield CT, and Trenton NJ. Metro Miami and Philadelphia were the largest sources of both in-migrants and out-migrants.
  • NYC and the NYMA lack any significant relationships with other counties and metro areas where they are net receivers of domestic migrants, receiving more migrants from those places than they send to those places.
  • NYC and the NYMA are similar to the cities and metros of Los Angeles and Chicago, in that they rely on high levels foreign migration and natural increase to offset high levels of negative domestic migration, and have few substantive relationships where they are net receivers of domestic migrants. Academic research suggests that the absolute largest cities and metros behave this way; attracting both low and high skilled foreign migrants while redistributing middle and working class domestic migrants to suburban areas and smaller metros. This pattern of positive foreign migration offsetting negative domestic migration has characterized population trends in NYC for many decades.
  • During the 2010s, most of the City and Metro’s foreign migrants came from Latin America and Asia. Compared to the US as a whole, NYC and the NYMA have slightly higher levels of Latin American and European migrants and slightly lower levels of Asian and African migrants.
  • Given the Census Bureau’s usual residency concept and the overlap in the onset the of COVID-19 pandemic lock down with the 2020 Census, in theory the pandemic should not alter how most New Yorkers identify their usual residence as of April 1, 2020. In practice, the pandemic has been highly disruptive to the census-taking process, which raises the risk of an under count.
  • The impact of COVID-19 on future domestic migration is difficult to gauge. Many of the pandemic destinations cited in recent cell phone (NYT and WSJ) and mail forwarding (NYT) studies mirror the destinations that New Yorkers have moved to between 2011 and 2018. Foreign migration will undoubtedly decline in the immediate future given pandemic disruptions, border closures, and restrictive immigration policies. The number of COVID-19 deaths will certainly push down natural increase for 2020.

atcoordinates YouTube Channel

Video Tutorials for Finding US Census Data

I have recently created an atcoordinates YouTube channel that features a series of how-to videos on finding and accessing US census data using a variety of websites and tools. I explain basic census concepts while demonstrating how to access data. At this point there are four videos:

  1. Exploring US Census Data: Basic Concepts. This is a narrated slide show where I cover the essential choices you need to make and concepts you need to understand in order to access census data, regardless of the tool or platform: data set, time period, subjects or topics, and geography. I discuss the decennial census, American Community Survey, and population estimates. This video is intended as a prerequisite for viewing the others, so I don’t have to explain the same concepts each time and can focus on demonstrating each particular application.
  2. American Community Survey Census Profiles with MCDC Apps. This screencast illustrates how you can quickly and easily access census profiles for any place in the US using the Missouri Census Data Center’s profile applications. It’s also a good introduction to census data in general, if you’re unfamiliar with the scope of data that’s available.
  3. Search Strategies for data.census.gov. I demonstrate how to use the Census Bureau’s primary application for accessing current census data, using the advanced search tool and filters.
  4. Using TIGERweb to Explore US Census Geography. I show you how to use this web map application for viewing census geography, while explaining what some of the small-area census geographies are.

I plan on adding additional videos every month or so. The pandemic lock down and uncertainty over whether classes will be back in session this fall inspired me to do this. While I prefer written tutorials, I find that I’ve been watching YouTube more often for learning how to do certain tasks with particular software, so I thought this would be useful for others. The videos average about 10 to 15 minutes in length, although the introductory one is a bit longer. The length is intentional; I wanted to explain the concepts and describe why you’re making certain choices, instead of simply pointing and clicking without any explanation.

Feel free to spread the news, share and embed the videos in research guides or web pages, and use them in classes or workshops. Of course, for a more in-depth look at US census data, check out my book: Exploring the US Census: Your Guide to America’s Data published by SAGE.

FRED Chart - Pesronal Savings Rate

Finding Economic Data with FRED

I attended ALA’s annual conference in DC last month, where I met FRED. Not a person, but a database. I can’t believe I hadn’t met FRED before – it is an amazingly valuable resource for national, time-series economic data.

FRED was created by the Economic Research unit of the Federal Reserve Bank of St. Louis. It was designed to aggregate economic data from many government sources into a centralized database, with straightforward interface for creating charts and tables. At present, it contains 567,000 US and international time series datasets from 87 sources.

Categories of data include banking and finance (interest and exchange rates, lending, monetary data), labor markets (basic demographics, employment and unemployment, job openings, taxes, real estate), national accounts (national income, debt, trade), production and business (business cycles, production, retail trade, sector-level information about industries),  prices (commodities, consumer price indexes) and a lot more. Sources include the Federal Reserve, the Bureau of Labor Statistics, the Census Bureau, the Bureau of Economic Analysis, the Treasury Department, and a mix of other government and corporate sources from the US and around the world.

On their home page at https://fred.stlouisfed.org/ you can search for indicators or choose one of several options for browsing. The default dashboard shows you some of the most popular series and newest releases at a glance. Click on Civilian Unemployment Rate, and you retrieve a chart with monthly stats that stretch from the late 1940s to the present. Most of FRED’s plots highlight periods of recession since these have a clear impact on economic trends. You can modify the chart’s date range, change the frequency (monthly, quarterly, annually – varies by indicator), download the chart or the underlying data in a number of formats, and share a link to it. There are also a number of advanced customization features, such as adding other series to the chart. Directly below the chart are notes that provide a clear definition of the indicator and its source (in this case, the Bureau of Labor Statistics) and links to related tables and resources.

FRED - Chart of Civilian Unemployment Rate

The unemployment rate is certainly something that you’d expect to see, but once you browse around a bit you’ll be surprised by the mix of statistics and the level of detail. I happened to stumble across a monthly Condo Price Index for the New York City Metro Area.

Relative to other sources or portals, FRED is great for viewing and retrieving national (US and other countries) economic and fiscal data and charts gathered from many sources. It’s well suited for time-series data; there are lots of indexes and you can opt for seasonally adjusted or unadjusted values. Many of the series include data for large regions of the US, states, metro areas, and counties. The simplest way to find sub-national data is to do a search, and once you do you can apply filters for concepts, frequencies, geographies, and sources. FRED is not the place to go if you need data for small geographies below the county level. If you opt to create a FRED account (purely optional) you’ll be able to save and track indicators that you’re interested in and build your own dashboards.

If you’re interested in maps, visit FRED’s brother GeoFRED at https://geofred.stlouisfed.org/.  The homepage has a series of sample thematic maps for US counties and states and globally for countries. Choose any map, and once it opens you can change the geography and indicator to something else. You can modify the frequency, units, and time periods for many of the indicators, and you have basic options for customizing the map (colors, labels, legend, etc.) The maps are interactive, so you can zoom in and out and click on a place to see its data value. Most of the county-level data comes from the Census Bureau, but as you move up to states or metro areas the number of indicators and sources increase. For example, the map below shows individual income taxes collected per capita by state in 2018.

GeoFRED - State Income Tax

There’s a basic search function for finding specific indicators. Just like the charts, maps can be downloaded as static images, shared and embedded in websites, and you can download the data behind the map (it’s simpler to download the same indicator for multiple geographies using GeoFRED compared to FRED).

Take a few minutes and check it out. For insights and analyses of data published via FRED, visit FRED’s blog at https://fredblog.stlouisfed.org/.

Business and Labor Force Data: The Census and the BLS

I’m still cranking away on my book, which will be published by SAGE Publications and is tentatively titled Exploring the US Census: Your Guide to America’s Data. I’m putting the finishing touches on the chapter devoted to business datasets.

Most of the chapter is dedicated to the Census Bureau’s (CB) Business Patterns and the Economic Census. In a final section I provide an overview of labor force data produced by the Bureau of Labor Statistics (BLS). At first glance these datasets appears to cover a lot of the same ground, but they do vary in terms of methodology, geographic detail, number of variables, and currency / frequency of release. I’ll provide a summary of the options in this post.

The Basics

Most of these datasets provide data for business establishments, which are individual physical locations where business is conducted or where services or industrial operations are performed, and are summarized by industries, which are groups of businesses that produce similar products or provide similar services. The US federal government uses the North American Industrial Classification System (NAICS), a hierarchical series of codes used to classify businesses and the labor force into divisions and subdivisions at varying levels of detail.

Since most of these datasets are generated from counts, surveys, or administrative records for business establishments they summarize business activity and the labor force based on where people work, i.e. where the businesses are. The Current Population Survey (CPS) and American Community Survey (ACS) are exceptions, as they summarize the labor force based on residency, i.e. where people live. The Census Bureau datasets tend to be more geographically detailed and present data at one point in time, while the BLS datasets tend to be more timely and are focused on providing data in time series. The BLS gives you the option to look at employment data that is seasonally adjusted; this data has been statistically “smoothed” to remove fluctuations in employment due to normal cyclical patterns in the economy related to summer and winter holidays, the start and end of school years, and general weather patterns.

Many of the datasets are subject to data suppression or non-disclosure to protect the confidentiality of businesses; if a given geography or industrial category has few establishments, or if a small number of establishments constitutes an overwhelmingly majority of employees or wages, data is either generalized or withheld. Most of these datasets exclude agricultural workers, government employees, and individuals who are self-employed. Data for these industries and workers is available through the USDA’s Census of Agriculture and the CB’s Census of Governments and Nonemployer Statistics.

The CB datasets are published on the Census Bureau’s website via the American Factfinder, the new data.census.gov, the FTP site and API, and via individual pages dedicated to specific programs. The BLS datasets are accessible through a variety of  applications via the BLS Data Tools. For each of the datasets discussed below I link to their program page, so you can see fuller descriptions of how the data is collected and what’s included.

The Census Bureau’s Business Data

Business Patterns (BP)
Typically referred to as the County and ZIP Code Business Patterns, this Census Bureau dataset is also published for states, metropolitan areas, and Congressional Districts. Published on an annual basis from administrative records, the number of employees, establishments, and wages (annual and first quarter) is published by NAICS, along with a summary of business establishments by employee size categories.
Economic Census
Released every five years in years ending in 2 and 7, this dataset is less timely than the BP but includes more variables: in addition to employment, establishments, and wages data is published on production and sales for various industries, and is summarized both geographically and in subject series that cover the entire industry. The Economic Census employs a mix of enumerations (100% counts) and sample surveying. It’s available for the same geographies as the BP with two exceptions: data isn’t published for Congressional Districts but is available for cities and towns.

Bureau of Labor Statistics Data

Current Employment Statistics (CES)
This is a monthly sample survey of approximately 150k businesses and government agencies that represent over 650k physical locations. It measures the number of workers, hours worked, and average hourly wages. Data is published for broad industrial categories for states and metropolitan areas.
Quarterly Census of Employment and Wages (QCEW)
An actual count of business establishments that’s conducted four times a year, it captures the same data that’s in the CES but also includes the number of establishments, total wages, and average annual pay (wages and salaries). Data is tabulated for states, metropolitan areas, and counties at detailed NAICS levels.
Occupational Employment Statistics (OES)
A bi-annual survey of 200k business establishments that measures the number of employees by occupation as opposed to industry (the specific job people do rather than the overall focus of the business). Data on the number of workers and wages is published for over 800 occupations for states and metro areas using the Standard Occupational Classification (SOC) system.

Labor Force Data by Residency

Current Population Survey (CPS)
Conducted jointly by the CB and BLS, this monthly survey of 60k households captures a broad range of demographic and socio-economic information about the population, but was specifically designed for measuring employment, unemployment, and labor force participation. Since it’s a survey of households it measures the labor force based on where people live and is able to capture people who are not working (which is something a survey of business establishments can’t achieve). Monthly data is only published for the nation, but sample microdata is available for researchers who want to create their own tabulations.
Local Area Unemployment Statistics (LAUS)
This dataset is generated using a series of statistical models to provide the employment and unemployment data published in the CPS for states, metro areas, counties, cities and towns. Over 7,000 different areas are included.
American Community Survey (ACS)
A rolling sample survey of 3.5 million addresses, this dataset is published annually as 1-year and 5-year period estimates. This is the Census Bureau’s primary program for collecting detailed socio-economic characteristics of the population on an on-going basis and includes labor force status and occupation. Data is published for all large geographies and small ones including census tracts, ZCTAs, and PUMAs. Each estimate is published with a margin of error at a 90% confidence interval. Labor force data from the ACS is best used when you’re OK with generally characterizing an area rather than getting a precise and timely measurement, or when you’re working with an array of ACS variables and want labor force data generated from the same source using the same methodology.

Wrap Up

In the book I’ll spend a good deal of time navigating the NAICS codes, explaining the impact of data suppression and how to cope with it, and covering the basics of using this data from an economic geography approach. I’ve written some exercises where we calculate location quotients for advanced industries and aggregate ZIP-Code based Business Patterns data to the ZCTA-level. This is still a draft, so we’ll have to wait and see what stays and goes.

In the meantime, if you’re looking for summaries of additional data sources in any and every field I highly recommend Julia Bauder’s excellent Reference Guide to Data Sources. Even though it was published back in 2014 I find that the descriptions and links are still spot on – it primarily covers public and free US federal and international government sources.

BLS Data Portal

Bureau of Labor Statistics Data Tools