Good and bad periods of economic growth
This article discusses how economic growth will be improving over the next decade or two and how less stupid policy could make it even better.
Throughout these periods of faster and slower growth, expectations for the economy's long-run prospects often turned pessimistic not long before a resurgence. Harvard professor Alvin Hansen famously predicted in 1938 that the US economy was floundering in an era of "secular stagnation" that was likely to continue for an extended period; a growth surge during the 1940s,
1950s, and 1960s proved him wrong.
In the early 1970s, a significant slowdown in productivity began that persisted into the 1990s. Shortly before the end of that episode, Paul Krugman (1990) concluded that productivity growth would likely remain weak and that Americans should just get used to it. By the mid-1990s, official forecasts of long-run productivity growth reflected this pessimism. In 1997, for example, the Congressional Budget Office's estimate of the average annual growth rate of labor productivity in the long run was just over 1 percent. These downbeat assessments were confounded in the mid-1990s, as productivity growth revived to a pace of more than 3 percent from 1995 to 2004, driven by information and communication technologies
19 years slow growth (about 1.6% per year) (1889-1917)
11 years mod fast growth (about 3.3% per year) (1917-1927)
15 years of moderate growth (about 2.8% per year) (1927-1941)
7 years of very fast growth (about 4% per year) (1941-1948)
26 years of mod fast growth (about 3.2% per year) (1949-1973)
23 years of slow growth (about 1.5% per year) (1973-1995)
10 years of mod fast growth (about 3.2% per year) (1995-2004)
11 years of slow growth (about 1.3% per year) (2004-2015)
Advances in information technology (IT) drove the most recent productivity surge, which took off in the mid-1990s. During the second half of the decade, semiconductor producers improved designs and manufacturing processes, causing IT prices to fall rapidly.
Has that engine of progress ground to a halt? Robert Gordon and many other economists have noted that the prices of high-tech equipment have fallen at a much slower pace in recent years than in earlier decades. Indeed, official published measures of prices for many high-tech products are barely falling at all. Gordon and others focus on prices because economists often use trends in relative prices in a sector to infer rates of innovation. However, a growing body of literature suggests that significant biases exist in these official price measures. Byrne, Oliner, and Sichel developed a (an hedonic index) more fully captures ongoing quality change and reveals rapid price declines after this quality change is taken into account.
Byrne and Corrado (2016) document rapid price declines for a range of other high-tech products, pointing to ongoing brisk technical advances in a wide range of high-tech sectors. This evidence suggests that the IT revolution is still going strong.
Big data, AI, robotics and other potential high impact productivity boosters
* the healthcare community is increasingly combining its growing data analytics capabilities with large-scale data sharing among regional healthcare systems
* physicians are increasingly using clinical decision support systems that use artificial intelligence to catch and
prevent costly medical errors
* telemedicine via smartphones and the declining cost of systems of sensors. Medical experts can monitor key biophysical characteristics, evaluate uncertain medical situations, assist in emergencies, and even manage chronic diseases from a distance, saving time and transportation costs while avoiding expensive hospitalizations.
A study by McKinsey (Manyika et al. 2011) concludes that deploying these kinds of technologies could raise the annual productivity growth of the healthcare sector by 0.7 percentage point for years, perhaps even a decade or two. Given the massive size of the sector-roughly one-fifth of US GDP-the McKinsey estimates imply a boost to aggregate productivity growth of 0.14 percentage point a year.
Nextbigfuture notes that gene therapy, stem cell treatments and other advanced medicine could transform chronic diseases into diseases that are actually fully cured. Actually progressing to actual medical cures could massively lower medical costs and curing people could increase the overall health of the workforce which could also boost productivity. Being closer to fully healthy could massively increase productivity.
One analysis of robotics assumes a lower bound of just 7 basis points of additional productivity growth per year from widespread deployment of new robotics technologies throughout the economy. One could imagine a productivity boost more than three times as large (25 basis points) as robots become a significant complement to labor in both
services and manufacturing.
The baseline projections of Byrne, Oliner, and Sichel assume a minimal increase in educational attainment and labor quality that contributes only 7 basis points a year to aggregate labor productivity growth. The possibilities
opened up by new educational technology (E-learning) suggest a potential contribution of at least 15 basis points a year. Even faster growth in the human capital stock could boost labor productivity by as much as 30 basis points a year.
Higher education is spreading rapidly in emerging markets like China and India (see Freeman 2009 and Freeman and Huang 2015). In just the past dozen years, China expanded the number of bachelor's degrees it grants in science and engineering by about 300,000, to more than 1.3 million per year (NSF 2016). By contrast, the United States awards only about 250,000 bachelor's degrees in science and engineering per year. The average quality of an engineering education in China or India remains well below that of Western countries, and the ability of either China or India to innovate at the global technology frontier through the efforts of its indigenous firms is still limited. With computer-assisted design software, internet videoconferencing, and the ability to quickly access terabytes of test data, it is now increasingly possible for Chinese and Indian engineers to collaborate closely, in almost real time, with seasoned technology experts in the United States, Western Europe, and Japan. Fernald and Jones (2014) estimate that about 1.3 percentage points of the average 2 percent annual increase in US labor productivity from 1950 to 2007 stemmed from higher research intensity (that is, the rising fraction of the population engaged in invention) in the advanced countries.
A separate study suggests productivity growth and GDP growth should increase.
The 10-year productivity drought is almost over. The next waves of the information revolution-where we connect the physical world and infuse it with intelligence-are beginning to emerge. Increased use of mobile technologies, cloud services, artificial intelligence, big data, inexpensive and ubiquitous sensors, computer vision, virtual reality, robotics, 3D additive manufacturing, and a new generation of 5G wireless are on the verge of transforming the traditional physical industries-healthcare, transportation, energy, education, manufacturing, agriculture, retail, and urban travel services.
At the current expected growth rate of 2% annually, the country will struggle to meet its obligations and invest in the future. But if growth accelerates to 2.7% annually, as this paper's analysts project, it will add a cumulative $8.6 trillion in wages and
salaries over the next 15 years (measured in 2016 dollars).
The pessimism about growth ignores the fact that information has revolutionized only 30% of the private-sector economy. Applying the power of information to the remaining 70% will replicate the gains of digital industries, but on a much larger scale. In the process, many physical industries, firms, and jobs will become digital industries, firms, and jobs. Even this optimistic view, however, understates the vast potential.
Nextbigfuture notes that just as China has a far less productive state run company part of their economy the USA and European countries have large competition shielded and unproductive areas of the economy (things like only one cable internet provider or limited wireless competition for many areas or almost no true healthcare options). Those areas end up having almost no improvement and often escalating costs. Broadband speeds get stuck at 10 Mbps instead of going to lower costs and gigabit or multi-gigabit per second speed.
Lasik surgery generally has to be paid for out of the patients own pocket and has many competing providers. This provided the incentive for lower costs for the procedures.
