Why does the growth rate of labor productivity in the United States continue to decline?

  Original title: Why does the growth rate of labor productivity in the United States continue to decline?

  Source: Xiao Lisheng Macroeconomic Analysis

   Emily Moss, Ryan Nunn, and Jay Shambaugh, translated by Mu Yarui and proofread by Xiao Lisheng.

  Introduction: This article comes from the 200th Think Tank Seminar compiled by the Institute of World Economics and Politics, Chinese Academy of Social Sciences. The original title is “The Slowdown in Productivity Growth and Policies That Can Restore It” and the authors are Emily Moss, Ryan Nunn and Jay Shambaugh. Emily Moss is a research assistant for the Hamilton Project. Ryan Nunn is the Assistant Vice President of Applied Research for Community Development at the Federal Reserve Bank of Minneapolis. Jay Shambaugh is Professor of Economics at the Elliott School of International Affairs at George Washington University. He has recently joined the Economic Advisory Council of Biden’s new administration. This article is a research article published in the Brookings Institution in June 2020. The full text is compiled as follows:

  The increase in labor productivity has promoted economic growth. However, with the exception of a brief surge in productivity in the mid-1990s and early 2000s, productivity growth has generally slowed in the past half century. Since 2004, the growth rate of work output per hour has been only 1.4%, only half of the growth rate since the 30 years after World War II. The slowdown in productivity growth is not unique to the United States. All major advanced economies have experienced similar declines in productivity growth. In this article, we mainly explore the reasons for the slowdown in productivity growth in the United States and public policies that help restore productivity growth.

  Introduction

   At present, the United States is at a time of a public health crisis and the worst economic contraction since the Great Depression. Usually academic discussions related to productivity may appear Profound and difficult to understand. At present, the most important issue in the United States is to save lives, take care of the sick, and prevent more jobs from collapsing and businesses going bankrupt. The current order is stable, and the short-term goal is to revive the economy and restore normal social operations.

   However, historical experience tells us that the economy is likely to suffer from long-term unemployment, reduced income, reduced living standards, and low output. Putting the issue of productivity growth at the top and center of economic policy is crucial. Can we establish reasonable mechanisms and develop new technologies so that we can overcome epidemics, climate change and a series of other challenges? Can we revive the long-term economic growth in order to improve people’s living standards and help propose solutions for economic development under the pandemic?

   Over time, in order to improve people’s living standards, people need to be able to produce more things under a certain workload. The increase in output does not guarantee an increase in wages or an equal distribution of benefits, but it is necessary for the continuous improvement of living standards. Increasing people’s working hours will definitely affect output, but the amount of labor that society can or wants to mobilize is limited. Therefore, to achieve sustained growth in output, it is necessary to increase labor productivity. This increase may be due to the improvement of workers’ skills or education, because workers can use more tangible capital for their work, or this increase may also be due to the overall productivity brought about by a combination of factors. improve. The last factor is usually simply described as an increase in output that cannot be explained by an increase in labor or capital. This factor is usually attributed to better technology, better management, and better institutions.

   100 years ago, about half of the working-age labor force in the United States had a job. Before the 2020 recession, about 61% of the population over 16 had jobs. But these people tend to work about 40 hours a week, which is much lower than the 50 hours that people usually worked a century ago. Therefore, the average number of working hours per person today is roughly the same as a century ago. However, during this period, the per capita output of the United States has increased by more than six times. We don’t work more, but we work more efficiently, and this has greatly improved people’s living standards over the past century.

   The continuous growth of productivity in the past 100 years means that people have more food and resources, better health care and housing conditions, and in an era when cars are just beginning to dominate the roads and phones are luxury goods. Consumer goods that people never dream of. Innovation and productivity have promoted the improvement of living standards.

  The ability to innovate and create new technologies is as important today as ever. People are currently facing various challenges from pandemics to climate change, and these challenges require new ideas and technologies. New vaccines, clean energy and many other innovations can not only gradually improve living standards, they are also vital to our lifestyle. In addition, over time, we need to achieve faster output growth, so as to deal with the huge investment in manpower and health care required for the COVID-19 pandemic, as well as the huge investment required to deal with climate change.

   However, with the exception of a brief surge in productivity in the mid-1990s and early 2000s, productivity growth has generally slowed in the past half century. In a world where new technologies seem to change our consumption and lifestyles on a regular basis, this may be surprising, but since 2004, the output per hour of work has only increased by 1.4%. This is only World War II. Half the growth rate in the next 30 years. Over time, in order to improve the living standards of Americans, it is important to develop policies that increase productivity growth. Sometimes wage levels will increase with productivity growth, and at other times, productivity growth will only be controlled by a small group of people. We need appropriate competition policies and labor market institutions to ensure that people can share the advantages of productivity growth.

   In this article, we review the recent experience of labor productivity growth in the United States and explore some of the reasons for the slowdown in productivity growth in the past 15 years. We have noticed that both capital investment and total factor productivity growth have slowed. Then, we will discuss some of the broad reasons for the slowdown in productivity growth and their policy implications. Although there are certain errors in the measurement of GDP and productivity, we cannot attribute the slowdown in economic growth solely to calculation errors in the measurement. Similarly, the shift in employment from industries with higher productivity to industries with lower productivity can explain part of the economic slowdown, but this is certainly not the whole reason. We also seem to have not reached the limit of economic growth. We still don’t know the form and timing of the next wave of innovation, and it may not happen.

   Our research and analysis will derive a clear meaning of policy guidance. Obviously, no policy alone can redirect American innovation and productivity growth. Although there are many reasons for slowing growth, it is not impossible to start. In order to promote faster innovation and productivity growth, we need to explore the reasons for the slowdown in growth.

  ** The goal of macroeconomic policy is to achieve full employment to support productivity growth, especially after the economic recession, because during the recession, companies will not invest so much investment or innovation.

  ** By strengthening the federal government’s commitment to R&D and public capital expenditure, it reverses the current downward trend in R&D expenditure and public capital expenditure.

  ** Solve the problem of hindering innovation rather than encouraging innovation in the intellectual property system.

  ** Reform regulations that limit productivity without meeting other social goals.

  ** Remove barriers that lead to a decline in economic vitality, which hinder the formation of enterprises and the flow of workers.

  ** Ensuring access to education allows Americans to have access to more education and training, partly in response to the recent slowdown in productivity growth and the aging of the workforce will reduce productivity.

   Over time, these policies are important ways to increase the rate of productivity growth. By implementing such a policy, people’s living standards can be improved faster than in recent decades, and we can embark on a more prosperous path than before the pandemic spread.

  What happened to productivity growth?

   People usually use GDP to measure the total output of an economy, which refers to the value of all goods and services produced in a certain year. Although GDP ignores many important factors that affect happiness, it is still a very useful way to summarize the output that an economy can consume, invest, or use by the government. Therefore, GDP per capita is a rough indicator of people’s average living standards. The economy and its measurement methods may be complicated, but GDP per capita is just a combination of the number of hours each person works and the output they produce per hour.

  Macroeconomics mainly focuses on the total output of the economy, and the total output of the economy depends on how many people have jobs, how many people are unemployed, and how many people are labor. But in the long run, what is more important is the efficiency of an economy’s total output, that is, the GDP per hour of work. This efficiency measure is called labor productivity, and its growth is crucial to improving people’s living standards.

   can be seen in Figure 1 the relationship between productivity and living standards, which depicts the relationship between the growth of labor productivity and the growth of the unit hourly wage adjusted for inflation. It can be found that wage growth is closely related to productivity growth: during periods of rapid productivity growth, wages increase more rapidly, and during periods of slow productivity growth, wage growth is less.

  Figure 11948-2018 The relationship between labor productivity and real hourly wages in the United States

  Source: U.S. Bureau of Labor Statistics 2020b; calculated by the author. Note: The data reflects all employees in private non-agricultural enterprises. The average annual growth rate of labor productivity and real hourly wages refers to the index level value of labor productivity and the compound change rate of real hourly wages from 1948-1974, 1974-1995, 1995-2004, and 2004-2018.

   Figure 1 divides productivity and wage growth into four generally discussed post-war periods. The first period occurred from 1948 to 1974, which was a period of rapid productivity growth and salary growth. The second period was 1974-1995, when both productivity growth and salary growth slowed. During this period, the slowdown in real wage growth actually far exceeded the slowdown in productivity growth, reflecting a variety of economic and policy resistances that limited workers’ profits, including the role of private sector unions The impact of trade, and the increase in the market power of companies in setting wages. 1995-2004 was a short transition period for rapid productivity growth, followed by 2004-2018, when productivity and wage growth slowed to their lowest levels after the war. After 1973, the persistent gap between productivity and wage growth showed that merely increasing the rate of productivity growth was not enough to increase the wages and living standards of ordinary Americans. However, productivity growth has a significant impact on wage growth, which shows that it is still an important factor in continuously improving people’s living standards.

  According to standard growth accounting, the growth of labor productivity has three forms: the change of labor composition, the deepening of capital, and the growth of total factor productivity. Differentiating these three factors can better understand the respective roles of education, capital investment, and other advancements. The growth of material and human capital may be limited by our savings, investment capacity, and diminishing returns on capital. But the growth of total factor productivity is much less restricted. It is mainly restricted by our understanding and imagination. Figure 2 shows the aforementioned components of labor productivity growth during the same period as Figure 1.

   Figure 21948-2018 United States Components of labor productivity growth

   Source: U.S. Bureau of Labor Statistics 2020 c; author’s calculations. Note: The data is for the private non-agricultural business sector. The contribution of total factor productivity is the total output of unit labor and capital input. The contribution of capital deepening is the capital service per hour multiplied by the share of capital in current dollar costs. The contribution of labor composition is the labor composition multiplied by labor’s share of current dollar costs. The composition of the labor force measures the impact of changes in labor force age, education level, and gender composition. The graph shows the compound rate of change calculated based on the index level values ​​of the beginning and ending years of each period.

   During the period 1948-1974, the deepening of total factor productivity and capital made relatively large contributions to productivity growth, and then during the period 1974-1995, total factor productivity fell sharply. In contrast, the change in the composition of the labor force in this period contributed more to economic growth, and in the subsequent periods, it contributed an average of 0.2-0.3 percentage points per year. During the period 1995-2004, productivity growth was driven by the increase in total factor productivity and capital deepening, of which capital deepening contributed the most. However, in the past 15 years, overall productivity growth has then declined again, following the same pattern as in the period 1974-1995. As shown in Figure 2, the growth rate of total factor productivity fell to the lowest level in all periods after the war, which was accompanied by a sharp decline in capital deepening.

   From a long-term perspective, neither the change in the composition of the labor force nor the deepening of capital can promote the rapid growth of labor productivity indefinitely. In other words, simply adding more machines, more education or more training will never be able to drive productivity growth alone. The growth of total factor productivity is an important part of long-term productivity growth and improvement of people’s living standards.

   Unfortunately, we cannot directly measure the growth of total factor productivity. More precisely, on the contrary, the growth of total factor productivity is the component after deducting the change in the composition of labor and the deepening of capital from the growth of labor productivity. It should be noted that the growth of total factor productivity is actually a measure of our ignorance, and it can only be measured indirectly by us. Economists usually refer to total factor productivity growth as technological progress, but it contains more content, including changes in management practices, improvements in the use of capital and labor, and changes in the institutional structure that can increase or decrease production efficiency. Although we cannot say exactly what the growth of total factor productivity is, it accounts for a considerable part of the annual growth of economic output, as shown in Figure 3. Even during the low growth period of 2004-2018, the growth of total factor productivity accounted for 24% of the real GDP growth for the whole year.

   Figure 31953-2018 U.S. real GDP and total factor productivity

   Source: U.S. Bureau of Economic Analysis 2020b; U.S. Bureau of Labor Statistics 2020d; Author’s calculation results. Note: The data is for the private non-agricultural business sector. The 5-year moving average of 1953 is calculated using data from 1949 to 1953. The shaded bars indicate periods of decline.

   The recent decline in labor productivity growth and total factor productivity growth has become a global phenomenon, indicating that the productivity slowdown is unlikely to be caused by factors unique to the United States. As shown in Figure 4, since 1995, labor productivity growth and total factor productivity growth in all G7 economies have shown a downward trend. Although the annual growth rate of labor productivity in the United States fell sharply during these two periods, during the period 2004-2018, the growth rate of labor productivity in the United States still increased at an annual rate of 1.1%, the fastest growing among the G7 Economy. During the same period, Canada followed closely with a rate of 0.9%, followed by Italy with a rate of 0.1%. In all the economies shown, the decline in total factor productivity growth is the main reason for the decline in labor productivity growth. This decline even extends to regions outside the advanced economies. Although China’s productivity growth rate remained strong before the 2008 financial crisis, its contribution to output growth has been much smaller since then.

   Figure 41995-2018 July Labor productivity growth and total factor productivity growth in large industrial countries

   Source: Organization for Economic Cooperation and Development, 2020; author’s calculations. Note: The data is the overall economic data. Labor productivity growth is the GDP per hour of work. The average annual growth rate is calculated based on the GDP indicator in constant U.S. dollars calculated in 2015 purchasing power parity. The cross part of each horizontal line represents the contribution of total factor productivity growth to the country’s overall labor productivity growth during a certain period of time.

  Why does productivity growth decline, and how to use public policies to ease it?

   The decline in productivity growth is determined by many factors: there are too many explanations for this trend, and some of them overlap. Some explanations indicate that productivity growth is still at a relatively high level, and that the decline in productivity growth is just a measurement error, while other explanations point out that this is because of changes in the industry or labor composition. Some explanations indicate that we are simply exhausting the easily available innovation resources and that over time we will face a significant slowdown in productivity growth, while other explanations attribute part of the recent slowdown in productivity growth to The aftermath of the Great Recession. Regulations will also affect innovation, and incentives for public and private investment will also affect the speed of capital deepening and the discovery and use of new innovations.

   In this section, before explaining potential policy responses, we will first explore several core explanations for the slowdown in productivity growth. Given that productivity began to slow down before 1973, when economists tried to explain this slowdown, many of these issues had been discussed. At present, we cannot determine a single, clear cause of the economic slowdown, but to a certain extent, the multiple causes of the economic slowdown are optimistic because they provide many channels through which policies can promote productivity growth and improvement. Standard of living.

  1. The wrong measurement of productivity growth

   The economic measurement is not perfect, and the calculation of productivity is no exception. Therefore, some people wonder whether the decline in productivity growth is a product of this miscalculation, rather than a real economic change. Considering that total factor productivity growth is measured by the remaining GDP growth after excluding labor and capital input changes, any measurement error in these data, especially the measurement of total factor productivity, will affect the overall measurement of labor productivity growth.

   In the measurement of productivity and real GDP, a particularly worrying issue is the correct assessment of inflation. As we all know, as time goes by and the quality of products and services improves, or new products and services are launched, it is very difficult to adjust data according to the improvement of products and services. If the quality or value of a new product is not properly reflected in the price, then GDP itself will be miscalculated. If these measurement problems get worse over time, productivity growth may decline.

   Reflections on recent technology and product innovations provide evidence for the false positive hypothesis. Although many services on the Internet contribute greatly to the welfare of consumers at reduced prices, these services are free for consumers. Therefore, even if statistical agencies do their best, they may not be enough to capture the progress of information age products such as smartphones. Even more problematic is the quality improvement in the service sector, which is difficult to measure, and the share of these sectors in the economy is increasing. If the proportion of industries whose output and quality are difficult to measure in the economy increases, then the overall misjudgment problem may become more and more serious.

   However, the available evidence suggests that measurement errors alone cannot explain the decline in productivity growth. First, many new products or services appeared before productivity slowed after 2004. It is unclear whether the introduction of new, high-quality products and services is increasing. However, research shows that, before the economic slowdown after 2004, it was the information technology hardware that was difficult to measure productivity growth that was the more important factor leading to calculation errors. The miscalculation of adjusting these commodities actually exacerbated the decline in labor productivity growth, which must be explained. In addition, the scale of the decline in productivity growth itself is difficult to mispredict: in a mispredicted industry, the real labor productivity needs to increase by 363% in 11 years, which is incredible.

  Some people sometimes think that the introduction of free services can explain the decline in productivity growth. However, those seemingly free services are actually monetized through advertisements or data collection, and can eventually be included in GDP indirectly. The more general idea is that consumer surplus generated by goods and services is not included in the GDP data, because the value of the benefits that individuals receive from the products is greater than the prices charged by the company. It is not clear whether the untapped surplus brought by the Internet age is greater than that generated when television or telephone were invented.

   Therefore, although GDP and productivity must have been wrongly measured to some extent, the consensus of the research is that this miscalculation cannot fully explain the slowdown in productivity growth after 2004. Therefore, it is worth exploring what other factors have reduced productivity growth over time.

  2. Changes in industrial structure

   A related possibility is that the US labor market may have moved workers to industries with lower productivity levels or lower productivity growth. This situation may happen spontaneously and does not necessarily cause people to panic. If the output per unit hour of a department increases rapidly, but does not increase as a part of consumption, then as time goes by, there will be fewer and fewer people working in that department. In the United States, due to changes in trade and consumption patterns, the share of employment in manufacturing industries with high output per hour and high productivity growth has declined. As a result, labor flows into low-productivity industries, which may be one of the reasons for the slowdown in overall productivity growth.

  Triplett and Bosworth describe a widely accepted view that an increase in the share of the service industry in the economy will tend to reduce productivity growth. But they show that the service industry is the main consumer of information technology innovation, which promoted the recovery of productivity growth from 1995 to 2004, which makes a pure redistribution explanation seem unlikely.

   In addition, if redistribution is the whole reason for the slowdown, then productivity growth in each industry will remain stable, and redistribution to industries with lower productivity will lower the average level. However, preliminary observations of industry productivity growth indicate that productivity growth generally declined between 1995-2004 and after 2004. In other words, it’s not just that employment is shifted between industries in some way, which inhibits overall productivity growth. More precisely, labor productivity growth in most industries during 1995-2004 was higher than during 2004-2018.

   Figure 5 shows the annual growth rate of labor productivity in certain large industries during the period 1995-2004 and 2004-2018. During the period 1995-2004, the labor productivity of most industries showed strong growth trends. For example, the retail industry is growing by 4.5% annually, and the manufacturing industry is growing by 4.7% annually. In the subsequent 2004-2018, the growth of these two industries was much slower, 2.2% and 1.1% respectively. Among the industries shown in Figure 5, only mining and trucking grew faster in the latter period.

   Picture 51995-2018 Press Labor productivity growth in selected industries

   Source: U.S. Bureau of Labor Statistics 2020 b; author’s calculation. Note: Due to data availability, the accounting data is 1997-2018, and the hospital data is 1995-2016. The industries shown by this figure do not include the private, non-agricultural business sector; as of the first quarter of 2016, they represent 51.4% of total employment and 50.6% of non-agricultural business hours. The industries shown represent the largest specific industries of the 11 major industries. For example, accounting is the largest specific industry in the professional services sector.

   Researchers calculated the growth rate of labor productivity in these periods under assumptions, that is, assuming that the composition of the industry has not changed, and found that the counterfactual growth rate is very close to the actual observed growth rate. The cross-industry movement of workers does not seem to have contributed to an actual overall decline in productivity growth.

  3. Restrictions on innovation and productivity growth

   The growth of total factor productivity is not entirely determined by technological changes. For example, even without the emergence of new technologies, better management practices and systems can promote the growth of total factor productivity. But total factor productivity is still deeply affected by technological progress. For example, from the 1920s to the 1940s, total factor productivity increased by about 2% per year, which was driven by the application of technologies such as electricity, chemistry, and telecommunications. The rapid growth of productivity from 1995 to 2004 was mainly driven by the widespread use of new information technology and the Internet.

  The importance of these technological developments has led some people to believe that they can explain the decline in productivity growth after 2004. In fact, they can also explain the decline in productivity growth from 1974 to 1995. Most notably, economist Robert Gordon believes that the slowdown in productivity growth is because recent technological advances are far less impressive than earlier technological advances. At the end of the 19th century and the beginning of the 20th century, innovations from sanitary equipment to internal combustion engines revolutionized American lives. As these innovations were fully utilized in the mid-20th century, they brought about tremendous productivity growth. The argument is that, on the whole, technological progress since then has been relatively insignificant.

   However, this assessment does not mean that technological progress will remain weak in the next few years. Some researchers have seen the promise of technologies such as artificial intelligence and machine learning. These technologies are currently being developed and applied, but their benefits have not been widely disseminated. The economist Robert Solo, who won the Nobel Prize for his contribution to understanding economic growth, said in 1987 that the computer age is ubiquitous, except in productivity statistics. In the following 1990s, productivity began to surge, partly due to innovation in computer technology. Innovation and productivity growth brought about by innovation are not always synchronized.

   One possibility is that advanced economies like the United States are in a period of temporary technological stagnation. During 1995-2004, the benefits of investment in information processing technology were widely used, and productivity growth also increased rapidly. Figure 6 shows the rapid growth of investment in information processing equipment and software, which accounted for approximately 3% from the beginning in the early 1990s and reached a peak of 4.4% in 2000. However, after 2004, when productivity growth fell to a lower level, the increase in productivity growth brought about by this investment was short-lived.

   Figure 61974-2019 information Private fixed investment in processing equipment and software

   Source: BEA 2020; author’s calculation. Note: Shaded bars indicate periods of economic recession.

   Given the unpredictable growth and decline of labor productivity and total factor productivity in the past, it may be too early to conclude that the productivity of the United States or other advanced economies has reached the upper limit. If we know the innovative technologies that can revive the economy in the future, they should already be in the process of being realized now. At many times in history, innovation seems to be at a dead end, but then a new wave of innovation has begun. However, from a historical point of view, technological progress is indeed necessary to increase productivity to the level before 1974.

  4. The aftermath of the economic recession

   The reasons for the decline in productivity growth discussed above do not necessarily apply to any specific policy remedies. For example, if the measured productivity growth declines only because of miscalculations, then the implicit policy response should be to improve the measurement method. In the rest of this section, we will discuss the reasons for the economic recession, and these reasons do imply policy remedies. Let’s start with the impact of cyclical economic recessions on productivity growth.

   Economic recession tends to slow productivity growth, but this dynamic is not always widely recognized. Macroeconomic theory often draws a line between the exploration of long-term growth and the boom and bust of the business cycle. This distinction is based on the assumption that the ups and downs of economic activity revolve around trends driven by the fundamentals of productivity growth. However, recent studies have shown that economic downturns can have more long-term effects on output and productivity growth in many ways. Although these studies certainly cannot explain the slowdown in productivity growth that began in 2004-2005, they may help explain the long-term slowness of total factor productivity growth, especially after the Great Recession.

  The view that demand shocks have long-term effects can be traced back to Campbell and Mankiw, who noticed the lasting effects of shocks on GDP. Blanchard, Cerutti and Summers show that in many countries, the decline in economic output caused by demand shocks tends to last a long time. Fatas and Summers found that the initial shock to output in 2009 could explain the deviation from forecasted output in subsequent years, indicating that the shock of the financial crisis was permanent. Not only are these countries deeply mired in economic recessions, but these recessions seem to have reduced potential output.

  The reasons why economic recession will continue to depress output levels and output growth are as follows. First, when companies see the potential of more customers, they tend to increase investment, and the current increase in output growth in one year often indicates that investment growth in the next year will be faster-this dynamic is in line with the accelerator theory . As many companies sell around the world, the global economic recession has inhibited companies’ expectations of demand, which will put greater pressure on investment growth.

  Bivens pointed out that a high-pressure economy characterized by rapid growth has the potential to increase potential output, and focused on the relationship between output growth in one year and investment in the next year. We show this relationship in Figure 7. When the economy grows faster, investment in the next year will also be faster. This correlation suggests that the economic downturn may lead to reduced investment. Lower investment reduces the capital of each worker and also reduces the speed at which companies produce or use new and innovative technologies.

   picture 71948-2016 non Growth in residential fixed investment and all other components of GDP

   Source: Bivens 2017. Note: NRFI refers to non-residential fixed investment. The data comes from BEA’s national income and product accounts.

   After an economic recession, the unemployment rate is usually very high. If companies want to expand production, there will be sufficient labor available for employment. In the first few years after the Great Recession, the availability of labor and the slow growth of wages may help explain why companies do not need to invest in productivity-enhancing technology or capital. Reifschneider, Wascher, and Wilcox found that both total factor productivity and capital deepening dropped significantly after the 2008 financial crisis, and about half of the decline in productivity growth was caused by capital deepening. Companies fail to invest. As capital deepening slows down, this directly reduces productivity growth, but at the same time it also reduces total factor productivity growth, because new innovative technologies have not been developed or put into use.

   Other studies have found that the impact on demand after the Great Recession largely explains the decline in total factor productivity growth, because the decline in demand has reduced the use of new technologies. If this effect only caused a temporary delay in the realization of technology, then an explosion of productivity that achieved all accumulated technological improvements would follow. However, if this effect causes a reduction in innovation itself, then it represents a permanent decline in the level of output. If a certain part of the innovation is never realized, then we may even lose productivity growth over time.

  The policy implications of these ideas are relatively simple.

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