Comment on 'Computerizing Industries and Routinizing Jobs: Explaining Trends in Aggregate Productivity' by Sangmin Aum, Sang Yoon (Tim) Lee and Yongseok Shin

Comment on “Computerizing industries and routinizing jobs: Explaining trends in aggregate productivity” by Sangmin Aum, Sang Yoon (Tim) Lee and Yongseok Shin

Editors’ Introduction

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Capital Labor Substitution, Structural Change, and the Labor Income Share

Capital-Labor Substitution, Structural Change and the Labor Income Share

Investigating the Indirect Consequences of Advancements in Information Technology on US Productivity

Competition, Technological Change and Productivity Gains: The Contribution of Information Technologies

A slowdown in the rate of agricultural productivity growth is thought by many observers to be contributing to the recent rise in agricultural prices. In this article I decompose sources of output growth in global agriculture into aggregate input and total factor productivity (TFP) components and examine whether productivity growth slowed substantially in the years leading up to the recent rise in commodity prices. Contrary to widely held perceptions, I find no evidence of a general slowdown in sector‐wide agricultural TFP, at least through 2006. If anything, the growth rate in agricultural TFP accelerated in recent decades. However, the results do show a slowdown in the growth of agricultural investment. Accelerating TFP growth largely offset decelerating input growth to keep the real output of global agriculture growing at about 2% per year since the 1960s. Regionally, however, agricultural productivity performance has been uneven. These findings have important implications for the appropriate supply‐side policy response to the current agricultural price crisis.

This paper addresses the empirical relationship between the level of competition and the rate of productivity growth across thirty sectors of the French production system during the period 1978-2015. It shows that there exists an optimal level of competition for each sector that is defined by the mark-up that maximizes the growth rate of labor productivity. The persistence of nonoptimal mark-ups in French sectors is associated with a 0.4% loss in aggregate average annual labor productivity growth during the period (1.86%). Hence, long-term productivity growth could have reached 2.25% if mark-ups had been at their optimal level. There is a strong significant positive correlation between the optimal mark-up and the rate of Hicks-neutral technical progress in each sector. This finding implies that sectors with high technical progress require higher mark-ups to maximize their rate of labor productivity growth. Overall, the aggregate economy would benefit from a decrease in the gap between nonoptimal and optimal mark-ups, as such an alignment would foster productivity growth.

Has the Portuguese economy benefited from tertiarization in terms of aggregate productivity performance? Did human capital availability play a role in this expansion of the services sector? To answer these two research questions, we investigate the existence of causality among services sector expansion, human capital, and aggregate productivity for the period 1970–2006 in the Portuguese economy based on the estimation of VAR models and impulse response analysis. We distinguish between the contributions of five different services sub-sectors that can be broadly classified as either traditional personal services or modern progressive services. The evidence suggests bi-directional causality between services sub-sectors employment shares and aggregate productivity. Across services sub-sectors, community social and personal services, that include health care and education activities, seem to be the most influential sector, followed by finance, insurance, real estate and business services, making both a positive and lasting contribution to aggregate productivity. Although only indicative, this evidence points to the relatively low weight of modern progressive services sectors in Portugal, together with a relatively less important role for some traditional personal services sub-sectors that can be sources of human capital, as candidate explanations for the slowdown in aggregate productivity growth over the period under analysis. The causality analysis did not allow us to confirm the role of human capital in driving the expansion of services subsectors, although the impulse response analysis points to a positive impact on aggregate productivity and the expansion of finance, insurance, real estate and business services and community social and personal services.

The aggregate labor productivity in Pakistan has deteriorated during the last three decades. The study examines the causes of the slowdown in aggregate labor productivity. By examining the role of structural change in productivity slowdown, the study develops a novel shift-share methodology and decomposes aggregate productivity into within-sector productivity and structured components. The results revealed that within-sector, along with structural labor productivity in the manufacturing and construction sectors has deteriorated over time. Furthermore, within sector productivity growth in the agriculture sector has also declined. Whereas structural productivity level and growth have positively contributed to aggregate agricultural productivity growth. The core findings of the study demonstrate that within-sector productivity of agriculture, manufacturing and construction, along with structural labor productivity of the manufacturing and construction sectors, has deteriorated over time and played a considerable role in the reduction of aggregate productivity. This study also offered evidence for the validity of the novel decomposition, and the results indicate that the novel structural decomposition is more reliable for the identification of the sources of aggregate productivity growth.

This paper investigates the effect of shifts in output composition on the slowdown of productivity growth in the United States between 1947-67 and 1967-76. I employ a Leontief input-output framework and a Divisia index of aggregate productivity growth to separate the effects of changes in sectoral rates of technical progress from the effects of changes in output composition and interindustry flows on the change in overall productivity growth. Of the approximately 2 percentage point decline in overall total factor productivity growth, 17% to 22% was due to compositional effects and the remainder to other factors. T HE importance of shifts in input or output composition in explaining the recent productivity slowdown in the United States has been a source of some controversy. Estimates of such effects vary considerably. For example, Gollop (1982) calculated that resource shifts were actually an offset to the slowdown in productivity growth; Kutscher, Mark, and Norsworthy (1977) estimated that employment shifts had no effect on productivity growth; Thurow (1979) ascribed half of the slowdown between 1965-72 and 1972-77 to employment shifts; and Nordhaus (1972) attributed 77% of the decline from 1948-55 to 1965-71 to employment shifts. In a related paper, the possible reasons for these disparate results were discussed at length (see Baumol and Wolff, forthcoming). Briefly, these differences stem primarily from the use of different concepts and measures. Actually, three different concepts are used in the literature. The first is a resource or equilibrating shift which measures the increase in productivity that can result from a more efficient allocation of resources (cf. Denison (1979a, 1979b, and 1984); Norsworthy, Harper, and Kunze (1979); and Gollop (1982)). While interesting in itself, this resource reallocation effect is a somewhat limited notion, measuring the movement toward the efficient frontier instead of the outward movement of the frontier over time. The second concept is the so-called level which assesses the effect of resource shifts on overall productivity growth by holding constant the productivity levels of the various sectors of the economy (cf. Nordhaus (1972); Kutscher, Mark, and Norsworthy (1977); and Thurow (1979)). This measure was found to be quite arbitrary, depending on the (arbitrary) choice of base year used in the computation. The third is the so-called effect, which assesses the effect of shifts in resources by holding constant sectoral rates of productivity growth (cf. Nordhaus (1972); Baily (1982), and Gollop (1982)). All three authors found that the rate effect had a negligible influence on the productivity slowdown. This measure is the most theoretically sound of the three, and my measure will fall in this category, though differ in significant ways from previous formulations, and show a greater effect on overall productivity growth from compositional changes. I shall first develop a general model to measure such shifts or composition effects from a Leontief input-output framework (sections I and II). Results for the U.S. economy over the 1947-76 period will then be reported, with particular emphasis on accounting for the productivity slowdown after 1967 (sections III, IV, and V). Conclusions and a comparison with other results will be discussed in section VI, VII and VIII. I. The Standard Model Following the work of Peterson (1979), let us define: X,= (column) vector of gross output by sector at time t Y, = (column) vector of final demand by sector at time t at= matrix of inter-industry technical coefficients at time t It = (row) vector of labor coefficients at time t, showing employment per unit of output kt = (row) vector of capital stock coefficients at time t, showing the capital stock required per unit of output p,= (row) vector of prices at time t, showing the price per unit of output of each industry. Received for publication June 27, 1983. Revision accepted for publication October 19, 1984. * New York University. I would like to express my appreciation to Wassily Leontief, William Baumol, M. I. Nadiri, Mark Schankerman, Martin Baily, and Andrew Sharpe for helpful comments and to the Division of Information Science and Technology of the National Science Foundation for financial support.

Aggregate productivity growth in the U.S. has slowed down since the 2000s. We quantify the importance of differential productivity growth across occupations and across industries, and the rise of computers since the 1980s, for the productivity slowdown. Complementarity across occupations and industries in production shrinks the relative size of those with high productivity growth, reducing their contributions toward aggregate productivity growth, resulting in its slowdown. We find that such a force, especially the shrinkage of occupations with above-average productivity growth through "routinization," was present since the 1980s. Through the end of the 1990s, this force was countervailed by the extraordinarily high productivity growth in the computer industry, of which output became an increasingly more important input in all industries ("computerization"). It was only when the computer industry's productivity growth slowed down in the 2000s that the negative effect of routinization on aggregate productivity became apparent. We also show that the decline in the labor income share can be attributed to computerization, which substitutes labor across all industries.

In the 1970s, the United States experienced a dramatic slowdown in its labor productivity growth rate. After growing at a rate of nearly three percent per year from World War II through 1973, nonfarm labor productivity growth stalled. From the fourth quarter of 1973 through the first quarter of 1980, labor productivity grew at a mere 0.6 percent per year. Part of the residue of this or any other economic disaster is the blossoming of research interest into that particular problem. Much effort has been put into explaining the causes of such a steep decline in the rate of productivity growth. This literature on the determinants of productivity growth has identified a number of potential causes of the 1970s productivity disaster. Among the factors which have been identified as affecting the trend rate of growth in labor productivity are: a decrease in the rate of labor quality improvement, a dramatic increase in energy costs, an insufficient growth in capital stock, the enactment of growth hindering social regulatory policies (e.g., the Clean Air Act and the Occupational Safety and Health Act), and a slowdown in the rate of technological advancement. Although the productivity decline has inadvertently proven beneficial to the economic literature on productivity change and our understanding of the process of productivity enhancements, there is still much that needs to be explained about the 1970s. Denison's [3] careful growth accounting for the 1970s, which takes into account all of the hypothetical causes for the growth slowdown mentioned above and more, still finds a disconcertingly large unexplained residual. The residual in such growth accounting studies is partly attributed to technological change. This is, in part, the case since the impact of pure technological change is difficult, if not impossible, to measure in an independent manner. This large residual in growth accounting studies of the 1970s has been taken to mean that sluggish technological change played an important role in that decade's productivity growth slowdown.

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