Useful Stats

As the world begins to emerge from the “Great Lockdown” and governments increasingly turn their efforts towards reopening economies, many will look to past recessions for lessons on recovery. This edition of Useful Stats examines the rate of real GDP recovery by state following the recessions of 2001 and 2008.

According to their latest projections, the Congressional Budget Office expects that the U.S. economy will not recover from the current recession until after 2021. However, as seen after the recession in 2001 and again after the Great Recession of 2008, states recover at widely different rates. As shown in the map below, nearly every state had fully recovered to pre-recession levels of GDP within one year following the recession from March to November of 2001. Only three states took longer to recover — with Connecticut taking two years, and Delaware and New York both fully recovering after three years.

This edition of Useful Stats examines — by state and over the period from 2000 to 2018 — how many new establishments were founded, how many jobs these new establishments created, how many establishments closed, and how many jobs were lost from those closing establishments. In only one year, the last year of the period, 2018, all states experienced positive net gains in employment and establishments, based on data from the Bureau of Labor Statistics. As shown in the interactive map below, the states that had the greatest number of new establishments in 2018 were California (63,073), Florida (31,063), Texas (28,079), Washington (20,525), and New York (13,967). The states that experienced the greatest net employment numbers in 2018 were California (177,061), Florida (117,746), Texas (115,624), Washington (45,394), and New York (44,045).

Although changes in gross domestic product (GDP) give us an idea of how economies are changing, this measure fails to tell the full story. This edition of Useful Stats examines county-level GDP-per-capita, the measure of economic output for each resident in an area. What we see is strongly skewed data with high 2018 GDP-per-capita levels and high 10-year growth rates concentrated primarily in low population-high output counties. We also see that rural populations have declined over the period while metropolitan areas have grown, yet the median GDP-per-capita growth rates between the groups are essentially the same.

Building on SSTI’s recent analysis of county-level GDP by industry, this edition moves beyond a single year and examines the changes in real — adjusted for inflation — county GDP and the changes in industry-specific contributions to county GDP for the 10-year period from 2009 to 2018. As shown in the interactive map below, the total 10-year growth rate for counties averaged approximately 21 percent.

All 10 of the counties that experienced the greatest percentage increases in total GDP between 2009 and 2018 are in Texas. The increases for these top 10 counties ranged from 709 percent to more than 3000 percent. The growth in most of these counties was driven by dramatic increases in the mining industry and related activities such as transportation and utilities.

PitchBook and NVCA’s Venture Monitor for 2019 largely depicts continued trends from 2018: $100 million-plus investments, $2 million-plus average for angel and seed deals, and more than 10,000 investments of more than $100 billion. In a few cases, 2019 data suggests average deal sizes may have peaked in 2018, but more time is needed to clarify the trend. At the state level, California’s lead in VC deals continues to be eaten away by the next 10-15 most active states, while those in the bottom two-thirds of the country by deal volume continue to show limited growth.

Taking a deeper dive into R&D expenditures at U.S. institutions of higher education, this week’s edition of Useful Stats examines the fields in which this R&D was performed at the metropolitan level in 2018. Expanding on a previous SSTI report showing that R&D activity at universities and colleges is clustered heavily on the coasts, this analysis uses the NSF’s Higher Education R&D (HERD) data on the research expenditures at individual institutions to determine how this funding is distributed among the various fields of study, with life sciences outpacing all other fields.

As shown in the map below, HERD expenditures in the life sciences (primarily the biological, biomedical, and health sciences) accounted for the vast majority of all higher education R&D activity in the U.S. — accounting for 57.8 percent ($45.8 billion) of the total performed in 2018. Engineering R&D was a distant second, accounting for 15.6 of the total.

This edition of Useful Stats examines the Bureau of Economic Analysis’ first full release of county-level gross domestic product (GDP) data. Specifically, this analysis considers total county GDP in 2018 and the contributions to each county’s GDP by industry.

While finance and insurance in New York ($222.5 billion) accounted for the single largest contribution to both total county GDP and total U.S. GDP in 2018 — followed by real estate and rental and leasing in Los Angeles ($150.2 billion) — the manufacturing sector was the highest contributor to county GDP in the greatest number of counties. Manufacturing was the primary source for county GDP in 927 out of more than 3100 counties — accounting for nearly $2.3 trillion of total U.S. GDP in 2018. Government and government enterprises (768 counties) accounted for the second most frequent leader in county GDP contributions — totaling $2.4 trillion nationally — followed by real estate and rental and leasing (647 counties) — totaling $2.7 trillion nationally. The next closest industry was agriculture, forestry, fishing and hunting which was the top contributor to GDP in only 209 counties — and only accounting for a national total of $138.4 billion.

The map below shows counties with manufacturing, government, real estate, mining, and agriculture  as their predominant industry. The map shows that manufacturing is the leading industry in counties in the Midwest and South while agriculture is centered primarily within the Plains region.

This week’s edition of Useful Stats covers Higher Education Research & Development (HERD) expenditures at the metropolitan level, pulling from the recent NSF updates to its HERD performance data. High levels of college and university R&D activity is not surprisingly clustered heavily in the East Coast — ranging from the District of Columbia up to Boston — and on the West Coast in California. The 10-year average HERD expenditures were the greatest in the New York-Northern New Jersey metro area ($3.7 billion), Boston ($2.8 billion), Baltimore ($2.8 billion), Los Angeles ($2.6 billion), and Houston ($2.0 billion). These five metro areas account for nearly 21 percent of the nation’s total 10-year average R&D spending by universities and colleges. Of the 209 metro areas included in this analysis — and excluding nonmetropolitan areas — the top 15 metros account for approximately 45 percent of the 10-year average of total HERD expenditures.

Across the U.S., the federal government provided 53 percent of R&D funding at institutions of higher education in FY 2018. Those institutions provided 26 percent of the funding themselves, and most of the remainder was provided by a mix of nonprofit organizations (7 percent), industry (6 percent), and state and local government (5 percent). The specific contributions varied from state to state, however, with some relying more on specific relationships to support R&D within the state.

As covered recently by SSTI, NSF’s National Center for Science and Engineering Statistics provides survey data on R&D funding at institutions of higher education. NSF’s report includes source of funding, attributable to federal government, state and local government, institutions, business, nonprofit organizations, or other sources.

Expenditures in higher education R&D (HERD) grew in FY 2018, increasing by $4.1 billion over FY 2017, the largest year-over-year increase since FY 2010-2011 according to an SSTI analysis of recently released data from the National Science Foundation’s National Center for Science and Engineering Statistics. For the 10-year period from FY 2009 to FY 2018, HERD grew by 38.4 percent nationally, representing an increase of nearly $22 billion. Higher education R&D expenditures grew the fastest over this 10-year period in the District of Columbia (78.2 percent), Connecticut (65.5 percent), Washington (59.5 percent), and Utah (59.3 percent). The largest absolute gains over the same period were seen in California ($2.5 billion increase), New York ($2.3 billion), and Pennsylvania ($1.6 billion). The map below shows the one-, five- and 10-year percentage changes in each state’s higher education R&D expenditures.

From 2006 to 2018, income inequality has risen continuously both nationwide and in all states (but not in the District of Columbia). Annual changes vary widely for state income inequality, with some states experiencing increases year after year, and others displaying more volatile trends consisting of both sharp annual decreases and increases. This edition of SSTI’s Useful Stats examines trends in the Gini index —a measure of household income inequality that increases as the distribution of income becomes more concentrated within a smaller share of the population — at the state level from 2006 to 2018.

While rankings and annual indices are catnip for some looking to gain attention for their latest rankings, SSTI has always argued that it’s long-term trends that give the best sense of where a state or region stands. With recent release of income data, SSTI has examined the last 34 years data in median household income for each state. SSTI found that while median household income — adjusted to 2018 dollars — has risen in nearly every state and the U.S. since 1984 with an average annual rate of increase of 0.8 percent, the growth, not surprisingly, varies widely among individual states.