The Business Dynamics Statistics of U.S. High Tech Industries (BDS-HT) is an experimental data product extending the set of statistics published by the Business Dynamics Statistics program. BDS-HT is a component of a broader set of approaches aimed at better measuring the business dynamics of innovative firms (BDS-IF), described in greater detail in Goldschlag & Perlman (2017). BDS-HT provides annual measures of business dynamics for High Tech and non-High Tech industries, defined by Science, Technology, Engineering, and Math (STEM) occupation intensity. Additional details on the industry classification can be found on the Methodology page.

BDS-HT data tables show key economic data including the number of establishments, firms, and employment, job creation and destruction, establishment openings and closings, and number of startups and firm shutdowns for the High Tech sector. The BDS-HT series provides annual statistics for 1978 to 2020 for the High Tech sector by firm size and firm age, initial firm size, establishment size and establishment age, initial establishment size, state, metro/non-metro, and MSA.

Notable Patterns in High Tech Employment and Entry by Geography

The release of the Business Dynamics Statistics-High Tech (BDS-HT) tables provides the first ever view of the geographic distribution of employment in the High Tech sector. Figure 1 shows the variation in High Tech sector employment across MSAs (represented by points). Each MSA point conveys two pieces of information: total employment in the High Tech sector (through the size of the point) and the intensity of High Tech employment defined as High Tech employment as a percentage of total employment (through the shade of the point). Larger points have more High Tech employment and darker points have a higher share of employment in the High Tech sector. The MSAs shown in the map account for 94% of High Tech employment, with the remaining 6% in micropolitan and non-metro areas.

Several patterns in Figure 1 are worth noting. First, there are a number of MSAs with a significant amount of High Tech employment, many of which are on the coasts. Second, MSAs vary significantly in their intensity of High Tech employment including: San Jose (28%), Washington D.C. (15%), San Francisco (14%), Boston (11%), New York City (5%). In the following figures we will focus on these five MSAs, which are among the largest in terms of High Tech employment and explore variation in High Tech employment intensity and High Tech entry over time.

Figure 1. High Tech Employment and Employment Share in 2020

The BDS-HT tables allow users to see how High Tech employment intensity evolves over time within each MSA. Figure 2 shows the average High Tech employment intensity in each of our focus MSAs over time. The groups of years are designed to show the 1990s, a period of particularly high growth in High Tech activity. Consistent with the map in Figure 1, San Jose has a significantly higher share of employment in the High Tech sector. Over 29% of employment in San Jose in the 1980s was in the High Tech sector and that fell to an average of 24% after 2002. San Jose, Boston, and New York City saw a decrease in the High Tech employment intensity since the 1980s. In stark contrast, Washington DC and San Francisco saw marked increases in the High Tech employment intensity, more than doubling in the case of San Francisco.

Figure 2. High Tech Employment Intensity Over Time

The BDS-HT data also allow users to see the share of new establishments in an MSA that are in the High Tech sector. In Figure 3, we find very different patterns in the share of establishment entrants in the High Tech sector in these MSAs. San Jose, Washington DC, and San Francisco all show robust growth in the share of new establishments that were in the High Tech sector. San Jose, for instance, rose from roughly 4% in 1978 to over 16% in 2020—in 2000 and 2012 this share reached over 19%. Washington DC and San Francisco also exhibit a consistent increase in the share of entrants in High Tech with the notable sharp rise and fall around 2000. Boston and New York City show a rise in the share of establishment entrants in the High Tech sector through the early 2000s but a relatively flat trend afterwards.

Figure 3. High Tech Share of Establishment Entrants

Despite the differences in the share of establishment entrants that are in High Tech across these MSAs, we find very similar patterns in the High Tech entry rate---the share of all High Tech establishments in an MSA that are entrants. Figure 4 shows the establishment entry rate within the High Tech sector for each of these MSAs. For comparison, we also show the High Tech establishment entry rate for all MSAs. We see an overall trend decline aside from the marked rise in the 1990s, which is consistent with prior research on the business dynamics of High Tech industries (Haltiwanger, Hathaway, and Miranda (2014), Goldschlag and Miranda (2020)). Despite significant differences in the share of new establishments that are in the High Tech sector (shown in Figure 3), there has been a declining share of High Tech establishments that are entrants and a rising share of High Tech activity among older establishments. Over time, fewer and fewer of the High Tech establishments in these MSAs are newly formed entrants.

Figure 4. High Tech Establishment Entry Rate

These figures serve to demonstrate some of the interesting patterns across geographies. The BDS-HT data products allow data users to explore the dynamics of High Tech industries across firm and establishment characteristics including size, age, and geography.

References

Goldschlag, Nathan, & Miranda, Javier. (2020). Business Dynamics Statistics of High Tech Industries. Journal of Economics & Management Strategy, 29(1), 3-30.

Goldschlag, Nathan & Perlman, Elisabeth. (2017). Business Dynamic Statistics of Innovative Firms. CES Discussion Paper Series, CES-WP-17-72, Center for Economic Studies, U.S. Census Bureau.

Haltiwanger, John, Hathaway, Ian, & Miranda, Javier. (2014). Declining business dynamism in the US high-technology sector. Discussion paper, Ewing Marion Kauffman Foundation.