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The Role of R&D Factors in Economic Growth
November 2024
Working Paper Number:
CES-24-69
This paper studies factor usage in the R&D sector. I show that the usage of non-labor inputs in R&D is significant, and that their usage has grown much more rapidly than the R&D workforce. Using a standard growth decomposition applied to the aggregate idea production function, I estimate that at least 77% of idea growth since the early 1960s can be attributed to the growth of non-labor inputs in R&D. I demonstrate that a similar pattern would hold on the balanced growth path of a standard semi-endogenous growth model, and thus that the decomposition is not simply a by-product of rising research intensity. I then show that combining long-running differences in factor growth rates with non-unitary elasticities of substitution in idea production leads to a slowdown in idea growth whenever labor and capital are complementary. I conclude by estimating this elasticity of substitution and demonstrate that the results favor complimentarities.
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Foreign Direct Investment, Geography, and Welfare
September 2024
Working Paper Number:
CES-24-45
We study the impact of FDI on domestic welfare using a model of internal trade with variable markups that incorporates intranational transport costs. The model allows us to disentangle the various channels through which FDI affects welfare. We apply the model to the case of Ethiopian manufacturing, which received considerable amounts of FDI during our study period. We find substantial gains from the presence of foreign firms, both in the local market and in other connected markets in the country. FDI, however, resulted in a modest worsening of allocative efficiency because foreign firms tend to have significantly higher markups than domestic firms. We report consistent findings from our empirical analysis, which utilises microdata on manufacturing firms, information on FDI projects, and geospatial data on improvements in the road network.
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Urban-Biased Growth: A Macroeconomic Analysis
June 2024
Working Paper Number:
CES-24-33
After 1980, larger US cities experienced substantially faster wage growth than smaller ones. We show that this urban bias mainly reflected wage growth at large Business Services firms. These firms stand out through their high per-worker expenditure on information technology and disproportionate presence in big cities. We introduce a spatial model of investment-specific technical change that can rationalize these patterns. Using the model as an accounting framework, we find that the observed decline in the investment price of information technology capital explains most urban-biased growth by raising the profits of large Business Services firms in big cities.
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Tracking Firm Use of AI in Real Time: A Snapshot from the Business Trends and Outlook Survey
March 2024
Working Paper Number:
CES-24-16
Timely and accurate measurement of AI use by firms is both challenging and crucial for understanding the impacts of AI on the U.S. economy. We provide new, real-time estimates of current and expected future use of AI for business purposes based on the Business Trends and Outlook Survey for September 2023 to February 2024. During this period, bi-weekly estimates of AI use rate rose from 3.7% to 5.4%, with an expected rate of about 6.6% by early Fall 2024. The fraction of workers at businesses that use AI is higher, especially for large businesses and in the Information sector. AI use is higher in large firms but the relationship between AI use and firm size is non-monotonic. In contrast, AI use is higher in young firms although, on an employment-weighted basis, is U-shaped in firm age. Common uses of AI include marketing automation, virtual agents, and data/text analytics. AI users often utilize AI to substitute for worker tasks and equipment/software, but few report reductions in employment due to AI use. Many firms undergo organizational changes to accommodate AI, particularly by training staff, developing new workflows, and purchasing cloud services/storage. AI users also exhibit better overall performance and higher incidence of employment expansion compared to other businesses. The most common reason for non-adoption is the inapplicability of AI to the business.
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Good Dispersion, Bad Dispersion
March 2024
Working Paper Number:
CES-24-13
We document that most dispersion in marginal revenue products of inputs occurs across plants within firms rather than between firms. This is commonly thought to reflect misallocation: dispersion is 'bad.' However, we show that eliminating frictions hampering internal capital markets in a multi-plant firm model may in fact increase productivity dispersion and raise output: dispersion can be 'good.' This arises as firms optimally stagger investment activity across their plants over time to avoid raising costly external finance, instead relying on reallocating internal funds. The staggering in turn generates dispersion in marginal revenue products. We use U.S. Census data on multi-plant manufacturing firms to provide empirical evidence for the model mechanism and show a quantitatively important role for good dispersion. Since there is less scope for good dispersion in emerging economies, the difference in the degree of misallocation between emerging and developed economies looks more pronounced than previously thought.
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High-Growth Firms in the United States: Key Trends and New Data Opportunities
March 2024
Working Paper Number:
CES-24-11
Using administrative data from the U.S. Census Bureau, we introduce a new public-use database that tracks activities across firm growth distributions over time and by firm and establishment characteristics. With these new data, we uncover several key trends on high-growth firms'critical engines of innovation and economic growth. First, the share of firms that are high-growth has steadily decreased over the past four decades, driven not only by falling firm entry rates but also languishing growth among existing firms. Second, this decline is particularly pronounced among young and small firms, while the share of high-growth firms has been relatively stable among large and old firms. Third, the decline in high-growth firms is found in all sectors, but the information sector has shown a modest rebound beginning in 2010. Fourth, there is significant variation in high-growth firm activity across states, with California, Texas, and Florida having high shares of high-growth firms. We highlight several areas for future research enabled by these new data.
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Collaborative Micro-productivity Project: Establishment-Level Productivity Dataset, 1972-2020
December 2023
Working Paper Number:
CES-23-65
We describe the process for building the Collaborative Micro-productivity Project (CMP) microdata and calculating establishment-level productivity numbers. The documentation is for version 7 and the data cover the years 1972-2020. These data have been used in numerous research papers and are used to create the experimental public-use data product Dispersion Statistics on Productivity (DiSP).
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Is the Gender Pay Gap Largest at the Top?
December 2023
Working Paper Number:
CES-23-61
No: it is at least as large at bottom percentiles of the earnings distribution. Conditional quantile regressions reveal that while the gap at top percentiles is largest among the most-educated, the gap at bottom percentiles is largest among the least-educated. Gender differences in labor supply create more pay inequality among the least-educated than they do among the most-educated. The pay gap has declined throughout the distribution since 2006, but it declined more for the most-educated women. Current economics-of-gender research focuses heavily on the top end; equal emphasis should be placed on mechanisms driving gender inequality for noncollege-educated workers.
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Productivity Dispersion and Structural Change in Retail Trade
December 2023
Working Paper Number:
CES-23-60R
The retail sector has changed from a sector full of small firms to one dominated by large, national firms. We study how this transformation has impacted productivity levels, growth, and dispersion between 1987 and 2017. We describe this transformation using three overlapping phases: expansion (1980s and 1990s), consolidation (2000s), and stagnation (2010s). We document five findings that help us understand these phases. First, productivity growth was high during the consolidation phase but has fallen more recently. Second, entering establishments drove productivity growth during the expansion phase, but continuing establishments have increased in importance more recently. Third, national chains have more productive establishments than single-unit firms on average, but some single-unit establishments are highly productive. Fourth, productivity dispersion is significant and increasing over time. Finally, more productive firms pay higher wages and grow more quickly. Together, these results suggest that the increasing importance of large national retail firms has been an important driver of productivity and wage growth in the retail sector.
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Local and National Concentration Trends in Jobs and Sales: The Role of Structural Transformation
November 2023
Working Paper Number:
CES-23-59
National U.S. industrial concentration rose between 1992-2017. Simultaneously, the Herfindhahl Index of local (six-digit-NAICS by county) employment concentration fell. This divergence between national and local employment concentration is due to structural transformation. Both sales and employment concentration rose within industry-by-county cells. But activity shifted from concentrated Manufacturing towards relatively un-concentrated Services. A stronger between-sector shift in employment relative to sales explains the fall in local employment concentration. Had sectoral employment shares remained at their 1992 levels, average local employment concentration would have risen by 9% by 2017 rather than falling by 7%.
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