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U.S. farm productivity growth has direct consequences for sustainably feeding the world’s still rapidly growing population, as well as U.S. competitiveness in international markets. Using a newly expanded compilation of multifactor productivity (MFP) estimates and associated partial-factor productivity (PFP) measures, we examine changes in the pattern of U.S. agricultural productivity growth over the past century and more. Considering the evidence as a whole, we detect sizable and significant slowdowns in the rate of productivity growth in recent decades. U.S. multifactor productivity grew at an annual average rate of just 1.16% per year during 1990–2007 compared with 1.42% per year for the period 1910–2007. U.S. yields of major crops grew at an annual average rate of 1.17% per year for 1990–2009 compared with 1.81% per year for 1936–1990. More subtly, but with potentially profound implications, the relatively high rates of MFP growth during the third quarter of the century are an historical aberration relative to the long-run trend.

Multifactor productivity (MFP) growth is an imperative economic engine. MFP dynamism across five advanced and seven developing countries from 1996 to 2015 is analyzed, elucidating its association with financing and intangible assets. Debt is manifested by its inverted U-shaped nonlinear relationship with MFP advancement, while corporate cash holdings are negatively (positively) associated with MFP development in five (three) countries. The heterogeneous relationships between intangible assets and MFP growth are identified across industries, countries, and time; intangible assets are requisite MFP growth enhancers for manufacturing in developing countries, for service businesses in advanced countries, and for the period after the global financial crisis. The greater the productivity effect of intangible assets is, the higher a country’s per-capita income and/or governance quality becomes. Additionally, the results evince the catching-up of MFP to the technological frontier. Moreover, older firms exhibit slower MFP growth than their peers, whilst the positive effects of firm size on MFP growth are larger in high-tech and knowledge-intensive industries.

We analyze for the first time the economic contributions of modern industrial robots, which are flexible, versatile, and autonomous machines. We use novel panel data on robot adoption within industries in seventeen countries from 1993 to 2007 and new instrumental variables that rely on robots’ comparative advantage in specific tasks. Our findings suggest that increased robot use contributed approximately 0.36 percentage points to annual labor productivity growth, while at the same time raising total factor productivity and lowering output prices. Our estimates also suggest that robots did not significantly reduce total employment, although they did reduce low-skilled workers’ employment share.

Long-run growth in many models is the product of two terms: the effective number of researchers and their research productivity. We present evidence from various industries, products, and firms showing that research effort is rising substantially while research productivity is declining sharply. A good example is Moore’s Law. The number of researchers required today to achieve the famous doubling of computer chip density is more than 18 times larger than the number required in the early 1970s. More generally, everywhere we look we find that ideas, and the exponential growth they imply, are getting harder to find.

We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor—the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added and may reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect, and always raises the labor share and labor demand. We show how the role of changes in the task content of production—due to automation and new tasks—can be inferred from industry-level data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades.

One of the remaining challenges in explaining differences in total factor productivity is heterogeneity between sectors and within a specific sector in terms of labor and capital. This paper employs the generalized method of moments (GMM) to identify factors that affect total factor productivity across 21 manufacturing sectors and to clarify the heterogeneous determinants of total factor productivity within manufacturing sectors for the period 2010-2015. Our estimations show that large firms have significantly greater total factor productivity levels than small firms in some fragmentations of firms in terms of both labor and total capital and in some manufacturing sectors. It is suggested that firm characteristics should be considered by the government in establishing relevant policies for enhancing firm productivity.

We estimate a model of importers in Hungarian microdata and conduct counterfactual analysis to investigate the effect of imported inputs on productivity. We find that importing all input varieties would increase a firm's revenue productivity by 22 percent, about one-half of which is due to imperfect substitution between foreign and domestic inputs. Foreign firms use imports more effectively and pay lower fixed import costs. We attribute one-quarter of Hungarian productivity growth during the 1993-2002 period to imported inputs. Simulations show that the productivity gain from a tariff cut is larger when the economy has many importers and many foreign firms.

Starting in the early 1990s, countries in southern Europe experienced low productivity growth alongside declining real interest rates. We use data for manufacturing firms in Spain between 1999 and 2012 to document a significant increase in the dispersion of the return to capital across firms, a stable dispersion of the return to labor, and a significant increase in productivity losses from capital misallocation over time. We develop a model with size-dependent financial frictions that is consistent with important aspects of firms’ behavior in production and balance sheet data. We illustrate how the decline in the real interest rate, often attributed to the euro convergence process, leads to a significant decline in sectoral total factor productivity as capital inflows are misallocated toward firms that have higher net worth but are not necessarily more productive. We show that similar trends in dispersion and productivity losses are observed in Italy and Portugal but not in Germany, France, and Norway.

This article analyzes how patent-induced shocks to labor productivity propagate into worker compensation using a new linkage of U.S. patent applications to U.S. business and worker tax records. We infer the causal effects of patent allowances by comparing firms whose patent applications were initially allowed to those whose patent applications were initially rejected. To identify patents that are ex ante valuable, we extrapolate the excess stock return estimates of Kogan et al. (2017) to the full set of accepted and rejected patent applications based on predetermined firm and patent application characteristics. An initial allowance of an ex ante valuable patent generates substantial increases in firm productivity and worker compensation. By contrast, initial allowances of lower ex ante value patents yield no detectable effects on firm outcomes. Patent allowances lead firms to increase employment, but entry wages and workforce composition are insensitive to patent decisions. On average, workers capture roughly 30 cents of every dollar of patent-induced surplus in higher earnings. This share is roughly twice as high among workers present since the year of application. These earnings effects are concentrated among men and workers in the top half of the earnings distribution and are paired with corresponding improvements in worker retention among these groups. We interpret these earnings responses as reflecting the capture of economic rents by senior workers, who are most costly for innovative firms to replace.

We study a Chinese policy that awards substantial tax cuts to firms with R&D investment over a threshold or “notch.” Quasi-experimental variation and administrative tax data show a significant increase in reported R&D that is partly driven by firms relabeling expenses as R&D. Structural estimates show relabeling accounts for 24.2 percent of reported R&D and that doubling R&D would increase productivity by 9 percent. Policy simulations show that firm selection and relabeling determine the cost-effectiveness of stimulating R&D, that notch-based policies are more effective than tax credits when relabeling is prevalent, and that modest spillovers justify the program from a welfare perspective.