Learning by Doing and Plant Characteristics
August 1996
Working Paper Number:
CES-96-05
Abstract
Learning by doing, especially spillover learning, has received much attention lately in models of industry evolution and economic growth. The predictions of these models depend on the distribution of learning abilities and knowledge flows across firms and countries. However, the empirical literature provides little guidance on these issues. In this paper, I use plant level data on a sample of entrants in SIC 38, Instruments, to examine the characteristics associated with both proprietary and spillover learning by doing. The plant level data permit tests for the relative importance of within and between firm spillovers. I include both formal knowledge, obtained through R&D expenditures, and informal knowledge, obtained through learning by doing, in a production function framework. I allow the speed of learning to vary across plants according to characteristics such as R&D intensity, wages, and the skill mix. The results suggest that (a) Ainformal@ knowledge, accumulated through production experience at the plant, is a much more important source of productivity growth for these plants than is Aformal@ knowledge gained via research and development expenditures, (b) interfirm spillovers are stronger than intrafirm spillovers, (c) the slope of the own learning curve is positively related to worker quality, (d) the slope of the spillover learning curve is positively related to the skill mix at plants, (e) neither own nor spillover learning curve slopes are related to R&D intensities. These results imply that learning by doing may be, to some extent, an endogenous phenomenon at these plants. Thus, models of industry evolution that incorporate learning by doing may need to be revised. The results are also broadly consistent with the recent growth models.
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.
:
production,
economist,
econometric,
estimating,
industrial,
productivity growth,
growth,
earnings,
technological,
employ,
produce,
firms grow,
expenditure,
inventory,
economically,
spillover,
industry concentration
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.
:
Census of Manufactures,
Standard Industrial Classification,
Longitudinal Research Database,
National Science Foundation,
Ordinary Least Squares,
Bureau of Economic Analysis,
Census Bureau Longitudinal Business Database,
Survey of Industrial Research and Development
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 'Learning by Doing and Plant Characteristics' are listed below in order of similarity.
-
Working PaperLearning By Doing And Competition In The Early Rayon Industry🔥
February 1993
Working Paper Number:
CES-93-04
In this paper, I derive a structural econometric model of learning by doing from a dynamic oligopoly game. Unlike previous empirical models, this model is capable of testing hypotheses concerning both the technological nature and behavioral implications of learning. I estimate the model with firm level data from the early U.S. rayon industry. The empirical results show that there were considerable differences across firms in both proprietary and spillover learning. The results also indicate that two of the three firms took their rival's reactions into account when choosing their strategies.View Full Paper PDF
-
Working PaperIndustry Learning Environments and the Heterogeneity of Firm Performance
December 2006
Working Paper Number:
CES-06-29
This paper characterizes inter-industry heterogeneity in rates of learning-by-doing and examines how industry learning rates are connected with firm performance. Using data from the Census Bureau and Compustat, we measure the industry learning rate as the coefficient on cumulative output in a production function. We find that learning rates vary considerably among industries and are higher in industries with greater R&D, advertising, and capital intensity. More importantly, we find that higher rates of learning are associated with wider dispersion of Tobin's q and profitability among firms in the industry. Together, these findings suggest that learning intensity represents an important characteristic of the industry environment.View Full Paper PDF
-
Working PaperAsymmetric Learning Spillovers
April 1993
Working Paper Number:
CES-93-07
In this paper, I employ a linear-quadratic model of an industry characterized by learning by doing to examine the implications of asymmetric learning spillovers. Importantly, I show that distribution of spillover benefits can influence market structure in ways that can not be seen in models where spillovers are symmetric. If spillovers are asymmetric, a tradeoff between improved industry performance and increased market concentration can arise which does not occur when they are symmetric. This tradeoff leads to a policy dilemma; whether to promote static or dynamic efficiency in markets where learning is important.View Full Paper PDF
-
Working PaperIndustrial Spillovers In Developing Countries: Plant-Level Evidence From Chile, Mexico And Morocco
January 1998
Working Paper Number:
CES-98-02
Recent trade and growth models have underscored the potential importance of external economies of scale. However, many of the most frequently modeled externalities have either not been measured or have been estimated with data too aggregate to be informative. In this paper, plant-level longitudinal data from Chile, Mexico and Morocco allow me to provide some of the first micro evidence on several types of external economies from plant-level production functions. The results indicate that in many industries own-industry output contributes positively to plant-level productivity. However, the effects of geographic concentration are mixed. Cross-country concentration, as measured by a geographic GINI index, often decreases productivity but within-province, same industry activity enhances it.View Full Paper PDF
-
Working PaperProductivity Adjustments and Learning-by-Doing as Human Capital
November 1997
Working Paper Number:
CES-97-17
This paper measures plant-level productivity gains associated with learning curves across the entire manufacturing sector. We measure these gains at plant startups and also after major employment changes. We find: 1.) The gains are strongly associated with a variety of human capital measures implying that learning-by-doing is largely a firm-specific human capital investment. 2.) This implicit investment is large; many plants invest as much in learning-by-doing as they invest in physical capital and much more than they invest in formal job training. 3.) This investment differs persistently over industries and is higher with greater R&D. 4.) Consistent with a learning-by-doing interpretation, the human capital investment is much larger following employment decreases than increases. We conclude that learning-by-doing is a major factor in wage determination, technical progress and asymmetric employment adjustment costs.View Full Paper PDF
-
Working PaperIndustrial Spillovers in Developing Countries: Plant-level Evidence From Chile, Mexico, and Morocco
January 1998
Working Paper Number:
CES-98-01
This paper documents the procedure used to match firm-level data from the Quarterly Financial Reports (QFR) to plant-level (establishment) data from the Longitudinal Research Database (LRD). The resulting matched firms and their plants provide a link between a firm's financial structure and its manufacturing plants. The linked database provides a resource that researchers can use to examine the interaction of financial structure with firm decisions - including decisions such as employment, investment, mergers, and asset redeployment. Financial structure characteristics in the QFR include the composition and amount of debt claims.View Full Paper PDF
-
Working PaperThe Demand for Human Capital: A Microeconomic Approach
December 2001
Working Paper Number:
CES-01-16
We propose a model for explaining the demand for human capital based on a CES production function with human capital as an explicit argument in the function. The resulting factor demand model is tested with data on roughly 6,000 plants from the Census Bureau's Longitudinal Research Database. The results show strong complementarity between physical and human capital. Moreover, the complementarity is greater in high than in low technology industries. The results also show that physical capital of more recent vintage is associated with a higher demand for human capital. While the age of a plant as a reflection of learning-by-doing is positively related to the accumulation of human capital, this relation is more pronounced in low technology industries.View Full Paper PDF
-
Working PaperGOVERNMENT TECHNICAL ASSISTANCE PROGRAMS* AND PLANT SURVIVAL: THE ROLE OF PLANT OWNERSHIP TYPE
February 1999
Working Paper Number:
CES-99-02
This paper compares the survival rates of plants participating in manufacturing extension programs to nonparticipating plants. Participating plants receive technical and business assistance from one of a nationwide network of extension centers intended to assist smaller manufacturers. Results suggest that plant survival is related to plant size, age, productivity, capital intensity and ownership type. Importantly, the impact of extension services differs across ownership types. Participating in extension increases the probability of survival for single unit plants, but not for multi units. This result is consistent with the notion that single unit plants have less access to information on new technologies and would, therefore, benefit more from technical assistance programs such as manufacturing extension.View Full Paper PDF
-
Working PaperThe Span of the Effect of R&D in the Firm and Industry
May 1994
Working Paper Number:
CES-94-07
Previous studies have found that the firm's own research and spillovers of research by related firms increase firm productivity. In contrast, in this paper we explore the impact of firm R&D on the productivity of its individual plants. We carry out this investigation of within firm R&D effects using a unique set of Census data. The data, which are from the chemicals industry, are a match of plant level productivity and other characteristics with firm level data on R&D of the parent company, cross-classified by location and applied product field. We explore three aspects of the span of effect of the firm's R&D: (i), the degree to which its R&D is "public" across plants; (ii), the extent of its localization in geographic space, and (iii), the breadth of its relevance outside the applied product area in which it is classified. We find that (i), firm R&D acts more like a private input which is strongly amortized by the number of plants in the firm; (ii), firm R&D is geographically localized, and exerts greater influence on productivity when it is conducted nearer to the plant; and (iii), firm R&D in a given applied product area is of limited relevance to plants producing outside that product area. Moreover, we find that while geographic localization remains significant, it diminishes over time. This trend is consistent with the effect of improved telecommunications on increased information flows within organizations. Finally, we consider spillovers of R&D from the rest of industry, finding that the marginal product of industry R&D on plant productivity, though positive and significant, is far smaller than the marginal product of parent firm's R&D.View Full Paper PDF
-
Working PaperThe Impact of Vintage and Survival on Productivity: Evidence from Cohorts of U.S. Manufacturing Plants
May 2000
Working Paper Number:
CES-00-06
This paper examines the evolution of productivity in U.S. manufacturing plants from 1963 to 1992. We define a 'vintage effect' as the change in productivity of recent cohorts of new plants relative to earlier cohorts of new plants, and a 'survival effect' as the change in productivity of a particular cohort of surviving plants as it ages. The data show that both factors contribute to industry productivity growth, but play offsetting roles in determining a cohort's relative position in the productivity distribution. Recent cohorts enter with significantly higher productivity than earlier entrants did, while surviving cohorts show significant increases in productivity as they age. These two effects roughly offset each other, however, so there is a rough convergence in productivity across cohorts in 1992 and 1987. (JEL Code: D24, L6)View Full Paper PDF
