No. 42 Spring 2022 with Symposium on Well-being and Productivity (Part 1)
The International Productivity Monitor (IPM) is the joint flagship publication of the Centre for the Study of Living Standards (CSLS) in Canada and The Productivity Institute.
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Number 42, Spring 2022
Editors’ Overview Andrew Sharpe (Centre for the Studies of Living Standards) and Bart van Ark (The Productivity Institute, The University of Manchester)
- This edition of the International Productivity Monitor, No. 42, is a particularly large one (211 pages) as it not only includes four substantive articles as part of our regular line up, but also four articles which represent the first part of our Symposium on Productivity and Well-Being.
Productivity Growth in Construction Value Chains Tero Kuusi and Martti Kulvik (The Research Institute of the Finnish Economy), and Juha-Matti Junnonen (Tampere University)
- The construction industry has suffered from low productivity growth in recent decades. Motivated by the economic importance of the industry, we revisit the construction productivity puzzle by analyzing the construction value chains of 12 European countries using data from the World Input–Output, the EU KLEMS databases and complementary datasets. We decompose construction-related value added and productivity contributions to both the construction industry and the rest of the value chain and show that the traditional focus on the construction industry is adversely restrictive for understanding productivity growth in construction activities. There is a substantial contribution of construction-related value added generated in other industries, and the productivity growth in the value chains has, for the most part, been seen outside the construction industry. Furthermore, we show that there is a strong, long-term relationship between construction-related patents and the improvement of total factor productivity in the value chains, but the chains typically do suffer from low efficiency in the use of information technology.
The China Effect on Manufacturing Productivity in the United States and Other High-income Countries Daniel Lind (Arenagruppen)
- From a macroeconomic perspective and using input-output techniques, this article investigates to what extent, and how, the growing use of Chinese intermediates has contributed to the labour productivity growth within the manufacturing production processes of 22 high-income countries. The main result — based on almost 400 global value chains during the period 2000-2014 — is that this productivity effect is significant and economically relevant. This is also the case for the United States. The effect holds before and after the financial crisis, is robust to different specifications, and is identified in almost all production processes. Three mechanisms behind the identified pattern are — tentatively — identified: reduced employment, reduced prices, and productivity enhancing functional specialization. However, China is not special: the absolute productivity effect of the growing use of Eastern European intermediates seems to be even larger. Finally, China and Eastern Europe are special in relation to the high-income countries: growing intra-trade of intermediates among the high-income countries is associated with weaker productivity growth.
Trading Gains and Productivity: A Törnqvist Approach Ulrich Kohli (University of Geneva)
- This article looks at alternative Törnqvist measures of a country’s trading-gain and terms-of-trade effects, as they have been proposed in the literature starting with the seminal work of Diewert and Morrison (1986), and their link to standard measures of productivity. It strongly argues in favour of using the price of domestic final demand as a deflator when computing real Gross Domestic Income (GDI), and, by the same token, the trading gains and labour productivity measures. It shows that the trading gains then generally consist of two parts, a pure terms-of-trade component and an additional relative-price component, the latter of which can be interpreted as a real-exchange-rate effect. National and international statistical agencies, with the notable exceptions of Statistics Canada and the U.S. Bureau of Economic Analysis, tend to report incomplete trading-gain statistics in that they omit the second component. Consequently the real GDI estimates they publish must be viewed as flawed. Taking trading-gains into account has no direct effect on the measurement of total factor productivity, but it does affect the measures of average and marginal labour productivity when related to real GDI and its deflator. Numerical estimates for Switzerland are reported as an illustration. Appendix.
Why was US Labour Productivity Growth So High During the COVID-19 Pandemic? The Role of Labour Composition Jay Stewart (U.S. Bureau of Labor Statistics)
- In the first few weeks of the COVID-19 recession, around 20 million US workers lost their jobs, with half of those losses occurring in the last two weeks of March 2020. On the tail of these unprecedented job losses, labour productivity grew at an annualized rate of 10.3 per cent in 2020Q2 and the average hourly wage increased sharply. This study examines how these phenomena are related. Because most of the job losses were in lowwage industries or among low-wage workers in high wage industries, the average skill level of the labour force increased substantially. This study finds that this increase in average skill level accounted for 71 per cent (7.3 percentage points) of labour productivity growth in 2020Q2, and that about one-third of the increase in average skill level was due to the change in the distribution of workers across major industries, mainly because of the massive job losses in leisure and hospitality and other low-wage industries. Altogether, changes in the distribution of workers across major industries accounted for 24 per cent (2.5 percentage points) of the 10.3 per cent increase in labour productivity.
The Symposium on Well-being and Productivity (Part 1)
Introduction to the Symposium Andrew Sharpe (Centre for the Studies of Living Standards), Bart van Ark (The Productivity Institute, The University of Manchester), and Dan Sichel (Wellesley College and NBER)
- Articles published in the International Productivity Monitor have traditionally focused on the production sphere of economic activity and have seldom addressed the relationship between productivity and well-being. Recognizing the increasing attention to well-being issues by economists, government and the general public, this issue of the IPM goes some way to remedy
this past lack of attention to well-being by publishing a first symposium of four articles on productivity-well-being linkages. A second symposium of three articles on the same topic will appear in the next issue of the International Productivity Monitor.
Well-being and Productivity: A Capital Stocks Approach Jaimie Legge and Conal Smith (Victoria University of Wellington)
- In the widely used capital stocks approach to conceptualizing intergenerational wellbeing, the well-being of the current generation is considered a function of produced capital, human capital (labour), social capital, and natural capital. Most discussion of the sustainability of levels of well-being into the future is focused on considering whether the quantity of these capital stocks left for future generations will be the same, larger, or smaller than the quantity available to the current generation. However, the efficiency with which the capital stocks are used to produce well-being also matters. Because the capital stocks approach is grounded in a framework with strong parallels to that underpinning growth accounting, total factor productivity (TFP) provides a potentially useful way of examining this issue. This article explores the relationship between well-being and TFP.
Trust, Deep Trust, Productivity and Well-being in 136 countries Tim Hazledine (University of Auckland)
- The article explores the role of generalized or social trust (trust between strangers) in explaining cross-country differences in the level of productivity (output per worker) and in self-reported well-being for 136 countries. Trust is measured directly from survey data. In addition, a second trust variable called deep trust is estimated as a function of ancient cultural, historical, geographic, and linguistic factors. Both trust variables have significant bivariate relationships with each of productivity and well-being, each of which can also be modelled with fairly standard specifications: an augmented production function for productivity, and the multi-variate model of well-being developed in the annual World Happiness Reports. Yet when either trust variable is added to each of the standard models, neither contributes any additional explanatory power. So where is the bivariate significance of trust coming from? We find that, in every case, one or both of trust and deep trust is significant for the standard determinants of productivity, with deep trust doing better at predicting human capital, physical capital and institution quality, and actual trust being stronger for the well-being determinants. That is, trust in the 21st century appears to not directly contribute to productivity or well-being, but has a substantial effect working through the proximate determinants.
Time Use, Productivity, and Household-centric Measurement of Welfare in the Digital Economy Diane Coyle (University of Cambridge) and Leonard Nakamura (Federal Reserve Bank of Philadelphia)
- There is substantial interest in developing a broader understanding of economic progress than the standard indicator, real GDP, not least because digital technology is significantly changing both production within the GDP boundary and household activity outside the boundary. Market and household production and leisure now all involve substantial time online. This article describes a measurement framework that would encompass extended utility combining time allocation — over working for pay, producing at home, and leisure — with monetary measures of objective or subjective well-being during each activity and new ways of measuring productivity in digitalized activities. Implementation would require time use statistics in addition to well-being data and direct survey evidence on the shadow price of time. We advocate an experimental set of time and well-being accounts and discuss their data requirements.
The Link Between the Standard of Living and Productivity in the UK: A Decomposition Nicholas Oulton (Centre for Macroeconomics, London School of Economics, and National Institute of Social and Economic Research)
- According to Paul Krugman, “Productivity isn’t everything, but in the long run it is almost everything. A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker.” But productivity and the standard of living are different concepts and are measured in different ways, so the question is, what is the linkage between them? Productivity is typically measured by GDP per hour. The standard of living has potentially many aspects such as health, longevity, personal security, and relationships. But here I take a narrower view and stick to the national accounts. So the standard of living is measured by the household disposable income of the median individual. I use the median rather than the mean so that inequality is taken into account. I develop a decomposition of the growth of median household income which relates it to the growth of productivity via eight additional factors, one of which is inequality; four other factors are measures of labour market performance. I apply this decomposition to the UK over the period 1977 to 2019. I find that productivity growth was by far the most important factor in accounting for the growth of living standards which was substantial up to 2007; rising inequality prior to 2007 retarded the growth of living standards but not by much. Since 2007 productivity growth has collapsed as has also the growth of living standards. The fall in the latter has been mitigated somewhat by a fall in inequality.
