The Relation among Human Capital, Productivity and Market Value: Building Up from Micro Evidence
December 2002
Working Paper Number:
tp-2002-14
Abstract
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.
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,
endogeneity,
payroll,
quarterly,
census data,
productivity growth,
growth,
earnings,
labor productivity,
productivity increases,
average,
productivity measures,
measures productivity,
accounting,
expenditure,
estimates productivity,
capital,
capital productivity,
economic census,
workforce,
wages productivity,
econometrician,
population,
census years,
census business,
research census,
economic statistics
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.
:
Standard Statistical Establishment List,
Standard Industrial Classification,
Bureau of Labor Statistics,
National Science Foundation,
National Bureau of Economic Research,
Labor Productivity,
University of Maryland,
Federal Reserve Bank,
Financial, Insurance and Real Estate Industries,
Current Population Survey,
Longitudinal Business Database,
Employer Identification Numbers,
Cornell University,
Economic Census,
Department of Labor,
National Institute on Aging,
Alfred P Sloan Foundation,
Longitudinal Employer Household Dynamics,
AKM,
Cornell Institute for Social and Economic Research,
LEHD Program,
Census Bureau Business Register,
Business Register,
IZA,
Sloan Foundation,
Occupational Employment Statistics
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 đŸ”¥ are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'The Relation among Human Capital, Productivity and Market Value: Building Up from Micro Evidence' are listed below in order of similarity.
-
Working PaperThe Measurement of Human Capital in the U.S. Economy
April 2002
Working Paper Number:
tp-2002-09
We develop a new approach to measuring human capital that permits the distinction of both observable and unobservable dimensions of skill by associating human capital with the portable part of an individual's wage rate. Using new large-scale, integrated employer-employee data containing information on 68 million individuals and 3.6 million firms, we explain a very large proportion (84%) of the total variation in wages rates and attribute substantial variation to both individual and employer heterogeneity. While the wage distribution remained largely unchanged between 1992-1997, we document a pronounced right shift in the overall distribution of human capital. Most workers entering our sample, while less experienced, were otherwise more highly skilled, a difference which can be attributed almost exclusively to unobservables. Nevertheless, compared to exiters and continuers, entrants exhibited a greater tendency to match to firms paying below average internal wages. Firms reduced employment shares of low skilled workers and increased employment shares of high skilled workers in virtually every industry. Our results strongly suggest that the distribution of human capital will continue to shift to the right, implying a continuing up-skilling of the employed labor force.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 PaperWithin and Between Firm Changes in Human Capital, Technology, and Productivity Preliminary and incomplete
December 2001
Working Paper Number:
tp-2001-03
View Full Paper PDF
-
Working PaperHigh Growth Young Firms: Contribution to Job, Output and Productivity Growth
February 2017
Working Paper Number:
carra-2017-03
Recent research shows that the job creating prowess of small firms in the U.S. is better attributed to startups and young firms that are small. But most startups and young firms either fail or don't create jobs. A small proportion of young firms grow rapidly and they account for the long lasting contribution of startups to job growth. High growth firms are not well understood in terms of either theory or evidence. Although the evidence of their role in job creation is mounting, little is known about their life cycle dynamics, or their contribution to other key outcomes such as real output growth and productivity. In this paper, we enhance the Longitudinal Business Database with gross output (real revenue) measures. We find that the patterns for high output growth firms largely mimic those for high employment growth firms. High growth output firms are disproportionately young and make disproportionate contributions to output and productivity growth. The share of activity accounted for by high growth output and employment firms varies substantially across industries - in the post 2000 period the share of activity accounted for by high growth firms is significantly higher in the High Tech and Energy related industries. A firm in a small business intensive industry is less likely to be a high output growth firm but small business intensive industries don't have significantly smaller shares of either employment or output activity accounted for by high growth firms.View Full Paper PDF
-
Working PaperInnovation, Productivity Dispersion, and Productivity Growth
February 2018
Working Paper Number:
CES-18-08
We examine whether underlying industry innovation dynamics are an important driver of the large dispersion in productivity across firms within narrowly defined sectors. Our hypothesis is that periods of rapid innovation are accompanied by high rates of entry, significant experimentation and, in turn, a high degree of productivity dispersion. Following this experimentation phase, successful innovators and adopters grow while unsuccessful innovators contract and exit yielding productivity growth. We examine the dynamic relationship between entry, productivity dispersion, and productivity growth using a new comprehensive firm-level dataset for the U.S. We find a surge of entry within an industry yields an immediate increase in productivity dispersion and a lagged increase in productivity growth. These patterns are more pronounced for the High Tech sector where we expect there to be more innovative activities. These patterns change over time suggesting other forces are at work during the post-2000 slowdown in aggregate productivity.View Full Paper PDF
-
Working PaperHigh Growth Young Firms: Contribution to Job, Output and Productivity Growth
January 2016
Working Paper Number:
CES-16-49
Recent research shows that the job creating prowess of small firms in the U.S. is better attributed to startups and young firms that are small. But most startups and young firms either fail or don't create jobs. A small proportion of young firms grow rapidly and they account for the long lasting contribution of startups to job growth. High growth firms are not well understood in terms of either theory or evidence. Although the evidence of their role in job creation is mounting, little is known about their life cycle dynamics, or their contribution to other key outcomes such as real output growth and productivity. In this paper, we enhance the Longitudinal Business Database with gross output (real revenue) measures. We find that the patterns for high output growth firms largely mimic those for high employment growth firms. High growth output firms are disproportionately young and make disproportionate contributions to output and productivity growth. The share of activity accounted for by high growth output and employment firms varies substantially across industries ' in the post 2000 period the share of activity accounted for by high growth firms is significantly higher in the High Tech and Energy related industries. A firm in a small business intensive industry is less likely to be a high output growth firm but small business intensive industries don't have significantly smaller shares of either employment or output activity accounted for by high growth firms.View Full Paper PDF
-
Working PaperDecomposing the Sources of Earnings Inequality: Assessing the Role of Reallocation
September 2010
Working Paper Number:
CES-10-32
This paper uses matched employer-employee data from the U.S. Census Bureau to investigate the contribution of worker and firm reallocation to changes in wage inequality within and across industries between 1992 and 2003. We find that the entry and exit of firms and the sorting of workers and firms based on underlying worker skills are important sources of changes in earnings distributions over time. Our results suggest that the underlying dynamics driving changes in earnings inequality are complex and are due to factors that cannot be measured in standard cross-sectional data.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 PaperThe Human Factor in Acquisitions: Cross-Industry Labor Mobility and Corporate Diversification
September 2015
Working Paper Number:
CES-15-31
Internal labor markets facilitate cross-industry worker reallocation and collaboration, and the resulting benefits are largest when the markets include industries that utilize similar worker skills. We construct a matrix of industry pair-wise human capital transferability using information obtained from more than 11 million job changes. We show that diversifying acquisitions occur more frequently among industry pairs with higher human capital transferability. Such acquisitions result in larger labor productivity gains and are less often undone in subsequent divestitures. Moreover, acquirers retain more high skill workers and they exploit the real option to move workers from the target firm to jobs in other industries inside the merged firm. Overall, our results identify human capital as a source of value from corporate diversification and provide an explanation for seemingly unrelated acquisitions.View Full Paper PDF
-
Working PaperEntrepreneurial Teams: Diversity of Skills and Early-Stage Growth
December 2020
Working Paper Number:
CES-20-45
We use employer-employee linked data to track the employment histories of team members prior to startup formation for a full cohort of new firms in the U.S. Using pre-startup industry experience to measure skillsets, we find that startups that have founding teams with more diverse collective skillsets grow faster than peer firms in the same industries and local economies. A one standard deviation increase in teams' skill diversity is associated with an increase in five-year employment (sales) growth of 16% (10%) from the mean. The effects are stronger among startups in innovative industries and among startups facing greater ex-ante uncertainty. Moreover, the results are robust to a variety of approaches to address the endogeneity of team composition. Overall, our results suggest that teams with more diverse collective skillsets adapt their strategies more successfully in the uncertain environments faced by (innovative) startup firms.View Full Paper PDF
