A Productivity-Focused Growth Policy Model

Abstract

This paper responds to a multi-decade decline in the rate of U.S. economic growth by proposing a four-element technology-based growth policy, emphasizing productivity as the key policy target. Multiple indicators are presented to demonstrate the negative impacts of declining investment in key growth variables. The length of the U.S. decline, although in some cases not the magnitude, has also been experienced by most western economies, so the following discussion has broad relevance. In the U.S. case, a decline in productivity growth has resulted not only in slower income growth but also in increased income inequality. The consequence has been varying degrees of social and political turmoil, which has been accentuated by policy mistakes, such as imposition of tariffs and withdrawal from international trade agreements. The growth policy problem is explained in terms of systematic underinvestment in four major categories of economic assets—technology, capital formation (hardware and software), skilled labor, and technology-based infrastructure—that are required to drive long-term productivity growth. Economic growth policy research has for decades emphasized investment in technology (R&D) and a rather strained extension to economic impact. The reason for the conceptual inadequacy is the fact that three other major asset categories are critical to achieving sustained economic growth: capital formation, skilled labor, and technical infrastructure. These latter three asset classes are absolutely essential to the technology-based economy, but they receive incomplete attention at best. Failure to adopt this four-asset growth model has greatly constrained rates of growth in general and particularly in workers’ incomes over the past 40 years.

Notes

1 See Tassey (2019) for a detailed discussion of regional technology-based economic development (TBED) strategies in the United States and globally.

2 Basu, Fernald, and Shapiro (2001). For an excellent review of the economic growth literature, see Bonvillian and Singer (2017).

3 Dobbs et al. (2015) make this distinction between engineering and scientific innovation, especially with respect to the evolution of the Chinese economy.

4 Bureau of Economic Analysis (BEA), Income and Product Accounts, Section 1. Retrieved from https://apps.bea.gov/iTable/iTable.cfm?reqid=19&step=2#reqid=19&step=2&isuri=1&1921=survey.

5 Federal Reserve Board, “Household Debt-to-Income Ratios in the Enhanced Financial Accounts, Accessible Data.” This ratio of household debt to income reached a peak of 130% in 2007, contributing to the financial market collapse that triggered the “Great Recession” of 2008–2009.

6 Kurt Anderson (2020) cites numerous examples of actions by the U.S. private and public sectors that have been counterproductive with respect to preserving high rates of economic growth.

7 Brill et al. (2017). The decision of which deflator to use significantly affects the relative trends in this chart. Specifically, using the CPI makes the inflation-adjusted RHC track multifactor productivity. See Tassey (2020a) for more discussion of productivity trends in a growth policy context, including how the choice of deflator affects policy analysis.

8 Fernald (2014).

9 In fact, real average manufacturing earnings were 3.9% lower in 2020 than in 1978.

10 Sources: Average Hourly Earnings: https://data.bls.gov/pdq/SurveyOutputServlet; Employment, Hours, and Earnings from the Current Employment Statistics survey (National). Series Id: CES3000000008. Adjusted for inflation using the CPI.

11 Saez and Zucman (2014). Using Census data, the State Science and Technology Institute (SSTI) shows that the trend continues to worsen. In most OECD countries, income inequality has also experienced long-term declines. Today, the richest 10% of the population in the OECD area earn 9.5 times the income of the poorest 10%. In the 1980s, this ratio stood at 7:1. See Cingano (2014).

12 Lazonick (2014).

13 Lazonick (2014). See also Chuck Schumer and Bernie Sanders, “Schumer and Sanders: Limit Corporate Stock Buybacks,” New York Times. February 3, 2019.

14 Lazonick et al. (2020).

15 This unemployment rate compares with a low of 4.6% in 2007 before the Great Recession and 4.0% in 2000 before the 2001 recession.

16 See https://www.federalreserve.gov/monetarypolicy/bst_recenttrends.htm.

17 For an excellent assessment of the failures of economic growth policy and the needed reforms, see Atkinson (2021).

18 Jones and Williams (1998, 2000).

19 Fayer et al. (2017). This range reflects several definitions of what constitutes “high-tech”, as discussed in the section “Skilled Labor.”

20 For a thorough discussion of alternative types of efficiency in both neoclassical and innovation economics and the implications for economic growth policy, see Atkinson and Audretsch (2008).

21 The requirements for timing specific policy interventions over a technology’s life cycle are under-researched. See Tassey (2013b).

22 See Tassey (2007, 2020a).

23 Tassey (2019).

24 Technology life cycles and their importance for managing growth policy are discussed in the section “The Growth Policy Challenge.”

25 See Bonvillian and Singer (2017) and Tassey (2005) for assessments of the limitations of traditional knowledge production functions.

26 The TEM explicitly identifies three of the four major asset categories. The fourth, skilled labor, is ubiquitous to the entire development and utilization of technical knowledge.

27 Adapted from Tassey (2016). See this paper for a complete development, including expansion path characteristics of commercialized technologies.

28 See Tassey (2020a) for an expanded discussion of the roles and impacts of infratechnologies that compose the content of high-tech infrastructure.

29 Tassey (2017).

30 Thus, the expression $e^{{-K}_N/R_E}$ is a measure of the risk faced by companies contemplating additional R^E, as indicated in Figure 7. See Tassey (2016).

31 Source: OECD (https://stats.oecd.org/Index.aspx?DataSetCode=PDB_GR#).

32 Atkinson and Foote (2019a).

33 See https://www.aaas.org/sites/default/files/2020-05/Budget.png.

34 Chandra and Yadoo (2016).

35 Manyika et al. (2015).

36 Jones (2014) estimated a 70% premium for STEM (science, technology, engineering, and mathematics) jobs plus additional jobs with technical skills “that are dependent upon STEM knowledge,” while Fayer et al. (2017) estimated a 92% premium just for STEM jobs. Using the broader definition, Jones estimated “technical” employment to be 13% of the U.S. workforce, while Fayer et al. estimated STEM’s share to be 6% of total employment. The bottom line is clear: high-tech sector workers make substantially more than the average for all workers but are too small a portion of the workforce.

37 World Economic Forum. See WEF_FOJ_Executive_Summary_Jobs.pdf (weforum.org).

38 Manyika et al. (2017), “Jobs Lost, Jobs Gained: What the future of work will mean for jobs,skills, and wages” (https://www.mckinsey.com/featured-insights/future-of-work/retraining-and-reskilling-workers-in-the-age-of-automation).

39 See Deloitte and The Manufacturing Institute Skills Gap and Future of Work Study at https://documents.deloitte.com/insights/2018DeloitteSkillsGapFoWManufacturing, and Bonvillian and Sarma (2021).

40 Pharmaceutical Researchers and Manufacturers of America (2017), “New Reports Highlight Increasing Global Competition in Biopharmaceutical R&D, Posing Significant Challenges to Future U.S. Standing” (https://www.phrma.org/Press-Release/new-reports-highlight-increasing-global-competition-in-biopharmaceutical-randd-posing-significant-challenges-to-future-u-s-standing).

41 See https://www.act.org/content/dam/act/unsecured/documents/STEM/2017/STEM-Education-in-the-US-2017.pdf.

42 “The Elephant in the Truck—Retraining Low-Skilled Workers,” The Economist, January 12, 2017 (https://www.economist.com/special-report/2017/01/12/retraining-low-skilled-workers).

43 See Industrial Strategy: Building a Britain Fit for the Future. November 2017. https://www.gov.uk/government/publications/industrial-strategy-building-a-britain-fit-for-the-future.

44 Link (forthcoming) estimates a positive and statistically significant relationship between standardized calibration tests, and U.S. productivity growth.

45 See Gallaher (2007); Tassey (2017).

46 The official name of this infrastructure investment effort is the “Materials Genome Initiative” (MGI). See Scott et al., 2021.

47 Ian Hathaway, “America’s Rising Startup Communities” (http://www.startupsusa.org/americas-rising-startup-communities/).

48 Bonvillian and Singer (2017).

49 Tassey (2013b). A classic example of successive technology platforms is the evolution of electronics from vacuum tubes to transistors to integrated circuits. The latter two are based on a different scientific base (solid state physics) from vacuum tubes.

50 Note that Figure 11 does not portray the entire technology life cycle, only the path to maximum global performance relative to price.

51 Abernathy and Utterback (1975).

52 This transition is also slowed by installed-base and installed-wisdom effects (legacies of past investment and learning), as described in Tassey (2020a, Chapter 1).

53 This is an example of adaptive efficiency discussed in Section “The Growth Policy Framework.”

54 See Tassey (2019).

55 NBS had for almost a century had the singular mission of developing the infratechnology bases for standards.

56 Similarly, the Department of Energy’s version of DARPA, ARPA-E, also exists by virtue of the Department of Energy’s non-economic growth mission. While ARPA-E’s portfolio has helped develop new technology platforms, the rest of the economy has no comparable early-phase technology development entity to manage an early-phase technology portfolio.

57 The authorizing legislation was the Revitalize American Manufacturing and Innovation Act of 2013. For current programs, see https://www.manufacturingusa.com/.

58 Manufacturing USA receives little direct funding from Congress. Instead, funding comes from existing R&D agency budgets for technology development relevant to these agencies’ missions. See Bonvillian and Singer (2017) for an excellent assessment of this program.

59 It should also be noted that policy tools exist for supporting later-phase (applied) industry R&D; in particular, the R&E tax credit. The United States was the first economy to use this mechanism. However, in terms of strength of the credit, it now ranks 24th out of 34 economies. See Lester and Warda (2020).