Twisting the Demand Curve: Digitalization and the Older Workforce
November 2020
Working Paper Number:
CES-20-37
Abstract
This paper uses U.S. Census Bureau panel data that link firm software investment to worker earnings. We regress the log of earnings of workers by age group on the software investment by their employing firm. To unpack the potential causal factors for differential software effects by age group we extend the AKM framework by including job-spell fixed effects that allow for a correlation between the worker-firm match and age and by including time-varying firm effects that allow for a correlation between wage-enhancing productivity shocks and software investments. Within job-spell, software capital raises earnings at a rate that declines post age 50 to about zero after age 65. By contrast, the effects of non-IT equipment investment on earnings increase for workers post age 50. The difference between the software and non-IT equipment effects suggests that our results are attributable to the technology rather than to age-related bargaining power. Our data further show that software capital increases the earnings of high-wage workers relative to low-wage workers and the earnings in high-wage firms relative to low-wage firms, and may thus widen earnings inequality within and across firms.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
econometric,
payroll,
earnings,
employee,
employ,
employed,
productivity impacts,
labor,
accounting,
productivity wage,
younger firms,
profit,
revenue,
incentive,
workforce,
employing,
wages employment,
effect wages,
productivity shocks,
computer,
wage earnings,
firms young,
earnings age
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
Social Security Administration,
National Science Foundation,
National Income and Product Accounts,
Federal Reserve Bank,
Current Population Survey,
Research Data Center,
Department of Labor,
Social Security Number,
National Institute on Aging,
Alfred P Sloan Foundation,
Longitudinal Employer Household Dynamics,
Information and Communication Technology Survey,
AKM,
Employment History File,
Individual Characteristics File,
Quarterly Workforce Indicators,
Census Bureau Disclosure Review Board,
Ewing Marion Kauffman Foundation,
Disclosure Review Board,
International Trade Research Report,
Federal Statistical Research Data Center
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'Twisting the Demand Curve: Digitalization and the Older Workforce' are listed below in order of similarity.
-
Working PaperLocked In? The Enforceability of Covenants Not to Compete and the Careers of High-Tech Workers
January 2017
Working Paper Number:
CES-17-09
We examine how the enforceability of covenants not to compete (CNCs) affects employee mobility and wages of high-tech workers. We expect CNC enforceability to lengthen job spells and constrain mobility, but its impact on wages is ambiguous. Using a matched employer-employee dataset covering the universe of jobs in thirty U.S states, we find that higher CNC enforceability is associated with longer job spells (fewer jobs over time), and a greater chance of leaving the state for technology workers. Consistent with a 'lock-in' effect of CNCs, we find persistent wage-suppressing effects that last throughout a worker's job and employment history.View Full Paper PDF
-
Working PaperTechnology Use and Worker Outcomes: Direct Evidence from Linked Employee-Employer Data
August 2000
Working Paper Number:
CES-00-13
We investigate the impact of technology adoption on workers' wages and mobility in U.S. manufacturing plants by constructing and exploiting a unique Linked Employee-Employer data set containing longitudinal worker and plant information. We first examine the effect of technology use on wage determination, and find that technology adoption does not have a significant effect on high-skill workers, but negatively affects the earnings of low-skill workers after controlling for worker-plant fixed effects. This result seems to support the skill-biased technological change hypothesis. We next explore the impact of technology use on worker mobility, and find that mobility rates are higher in high-technology plants, and that high-skill workers are more mobile than their low and medium-skill counterparts. However, our technology-skill interaction term indicates that as the number of adopted technologies increases, the probability of exit of skilled workers decreases while that of unskilled workers increases.View Full Paper PDF
-
Working PaperBetween Firm Changes in Earnings Inequality: The Dominant Role of Industry Effects
February 2020
Working Paper Number:
CES-20-08
We find that most of the rising between firm earnings inequality that dominates the overall increase in inequality in the U.S. is accounted for by industry effects. These industry effects stem from rising inter-industry earnings differentials and not from changing distribution of employment across industries. We also find the rising inter-industry earnings differentials are almost completely accounted for by occupation effects. These results link together the key findings from separate components of the recent literature: one focuses on firm effects and the other on occupation effects. The link via industry effects challenges conventional wisdom.View Full Paper PDF
-
Working PaperProductivity, Investment in ICT and Market Experimentation: Micro Evidence from Germany and the U.S.
February 2003
Working Paper Number:
CES-03-06
In this paper, we examine the relationship between the use of advanced technologies, such as information and communications technologies (ICT), and related business practices and outcomes such as productivity, employment, the skill mix of the workforce and wages using micro data for the U.S. and Germany. . We find support to the idea that U.S. businesses engage in experimentation in a variety of ways not matched by their German counterparts. In particular, there is greater experimentation amongst young US businesses and there is greater experimentation among those actively changing their technology. This experimentation is evidenced in a greater dispersion in productivity and in related key business choices, like the skill mix and Internet access for workers. We also find that the mean impact of adopting new technology is greater in U.S. than in Germany. Putting the pieces together suggests that U.S. businesses choose a higher mean, higher variance strategy in adopting new technology.View Full Paper PDF
-
Working PaperCollege Majors and Earnings Growth
February 2026
Working Paper Number:
CES-26-14
We estimate major-specific earnings profiles using matched American Community Survey (ACS) and Longitudinal Employer-Household Dynamics (LEHD) data. Building on Deming and Noray (2020), we exploit a long earnings panel to overcome key limitations of cross-sectional approaches to lifecycle estimation. We find that engineering and computer science majors experience earnings growth that is comparable to or faster than that of other majors, a category including humanities, education, psychology, and similar fields. In contrast, Deming and Noray (2020) use a crosscohort approach and find that earnings for engineering and computer science majors decline relative to other fields over the lifecycle.View Full Paper PDF
-
Working PaperThe Shifting Job Tenure Distribution
January 2016
Working Paper Number:
CES-16-12R
There has been a shift in the U.S. job tenure distribution toward longer-duration jobs since 2000. This change is apparent both in the tenure supplements to the Current Population Survey and in matched employer-employee data. A substantial portion of this shift can be accounted for by the ageing of the workforce and the decline in the entry rate of new employer businesses. This shift is accounted for more by declines in the hiring rate, which are concentrated in the labor market downturns associated with the 2001 and 2007-2009 recessions, rather than declines in separation rates. The increase in average real earnings since 2007 is less than what would be predicted by the shift toward longer-tenure jobs because of declines in tenure-held-constant real earnings. Regression estimates of the returns to job tenure provide no evidence that the shift in the job tenure distribution is being driven by better matches between workers and employers.View Full Paper PDF
-
Working PaperThe Rising Returns to R&D: Ideas Are Not Getting Harder to Find
May 2025
Working Paper Number:
CES-25-29
R&D investment has grown robustly, yet aggregate productivity growth has stagnated. Is this because 'ideas are getting harder to find'? This paper uses micro-data from the US Census Bureau to explore the relationship between R&D and productivity in the manufacturing sector from 1976 to 2018. We find that both the elasticity of output (TFP) with respect to R&D and the marginal returns to R&D have risen sharply. Exploring factors affecting returns, we conclude that R&D obsolescence rates must have risen. Using a novel estimation approach, we find consistent evidence of sharply rising technological rivalry. These findings suggest that R&D has become more effective at finding productivity-enhancing ideas but these ideas may also render rivals' technologies obsolete, making innovations more transient.View Full Paper PDF
-
Working PaperComputer Investment, Computer Networks and Productivity
January 2005
Working Paper Number:
CES-05-01
Researchers in a large empirical literature find significant relationships between computers and labor productivity, but the estimated size of that relationship varies considerably. In this paper, we estimate the relationships among computers, computer networks, and plant-level productivity in U.S. manufacturing. Using new data on computer investment, we develop a sample with the best proxies for computer and total capital that the data allow us to construct. We find that computer networks and computer inputs have separate, positive, and significant relationships with U.S. manufacturing plant-level productivity. Keywords: computer input; information technology; labor productivityView Full Paper PDF
-
Working PaperThe Relation among Human Capital, Productivity and Market Value: Building Up from Micro Evidence
December 2002
Working Paper Number:
tp-2002-14
This paper investigates and evaluates the direct and indirect contribution of human capital to business productivity and shareholder value. The impact of human capital may occur in two ways: the specific knowledge of workers at businesses may directly increase business performance, or a skilled workforce may also indirectly act as a complement to improved technologies, business models or organizational practices. We use newly created firm-level measures of workforce human capital and productivity to examine links between those measures and the market value of the employing firm. The new human capital measures come from an integrated employer-employee data base under development at the US Census Bureau. We link these data to financial information from Compustat at the firm level, which provides measures of market value and tangible assets. The combination of these two sources permits examination of the link between human capital, productivity, and market value. There is a substantial positive relation between human capital and market value that is primarily related to the unmeasured personal characteristics of the employees, which are captured by the new measures.View Full Paper PDF
-
Working PaperInterpreting Cohort Profiles of Lifecycle Earnings Volatility
April 2024
Working Paper Number:
CES-24-21
We present new estimates of earnings volatility over time and the lifecycle for men and women by race and human capital. Using a long panel of restricted-access administrative Social Security earnings linked to the Current Population Survey, we estimate volatility with both transparent summary measures, as well as decompositions into permanent and transitory components. From the late 1970s to the mid 1990s there is a strong negative trend in earnings volatility for both men and women. We show this is driven by a reduction in transitory variance. Starting in the mid 1990s there is relative stability in trends of male earnings volatility because of an increase in the variance of permanent shocks, especially among workers without a college education, and a more attenuated trend decline among women. Cohort analyses indicate a strong U-shape pattern of volatility over the working life, which comes from large permanent shocks early and later in the lifecycle. However, this U-shape shifted downward and leftward in more recent cohorts, the latter from the fanning out of lifecycle transitory volatility in younger cohorts. These patterns are more pronounced among White men and women compared to Black workers.View Full Paper PDF
