ArticlePDF Available

Abstract

In this paper I calibrate unobserved labor-generated knowledge spillovers within and between six large macroeconomic sectors covering the U.S. civilian economy from 1948 to 1991. Using quality-adjusted data I show that manufacturing and trade & transportation are the main source of knowledge flows to the overall economy for the entire period. However, the productivity slowdown of the early seventies coincides with trade & transportation taking over manufacturing as the main source and destination of post-73 knowledge flows. Furthermore, I compute the gap between the market and the optimal allocation of labor across sectors, and the wedge between market and optimal wages by sector. I find that, for the whole period, optimal employment in manufacturing and trade & transportation is, respectively, 20% and 27% above market. As a result optimal output in these sectors is 12% and 16% higher than the market’s, and optimal wages in manufacturing are 54% above market wages.
Referee Report for ”Knowledge Spillovers and TFP Growth
Rates”
January 2, 2009
This paper studies the relationship between sectoral TFP growth and labor growth rate.
The author inteprets the correlation between TFP growth at each sector and within/cross sec-
tor labor growth rate as strength of knowledge spillovers. The empirical part uses sectoral
input-output database developed by Dale Jorgenson for the preiod between 19481991. Using
constrained OLS regression, this paper argues that manufacturing is the main source of knowl-
edge flows to the overall economy. Finally, using the empirical estimates, the author calculates
optimal employment in each sector by internalizing the benefit of externalities. Not surpris-
ingly, the optimal employment in manufacturing needs to be higher.
I have two general comments and more specific suggestions follow.
First, this paper draws close similarity to early works by Caballero and Lyons (1990,1992).
Although the scope of data is slightly different in the sense that CL focused on two-digit indus-
tries within U.S. manufacturing, while this papers looks at six larger macroeconomic sectors:
manufacturing, mining, construction, services, trade and transportation, and agriculture. CL’s
finding of productive externalities depends crucially on the strong positive correlation between
sectoral productivity and aggregate activity. In this paper, aggregate activity is replaced by
within and cross sector labor growth rate, since the author argues for ”labor-generated knowl-
edge spillover”. There are also several well-known empirical concerns that were indeed addressed
in the work of CL which are not properly answered in this paper: (1) if there exists inreasing
returns, the constructed TFP growth using only cost-weighted input shares can be misleading.
1
Specifically, it is contaminated by including the growth of production factors such as labor and
physical capital. I suggest the author to follow the suggestions of Hall (1990) to estimate a
separate parameter of returns to scale for each sector in the data. (2) I don’t believe the ”labor-
generated knowledge spillover” proxied by labor growth rate can fully explain sector-level TFP
growth. So it is important to characterize the residual term in the empirical regression. If
there are other factors that drive TFP growth and are correlated with labor growth, the OLS
estimates can be inconsistent. I suggest the author to follow CL and Hall (1990) to adopt an
IV estimation strategy.
Second, again similar to earlier works by Hall and CL, this paper uses data of value-added
rather than total output. (Although the author models material use in the theoretical model,
on p.9. he claims that value-added is used as sector output measure). Basu and Fernald (1995)
in a series of paper show that using value-added measure to construct TFP could generate
”apparent productive spillovers”. The idea is simple: if there is increasing returns to scale
and/or imperfect competition, marginal product of materials exceeds its factor payment. Thus
value-added does not properly account for the productive contribution of intermediate inputs,
which implies that again constructed ”TFP growth” can very well be contaminated by omitted
intermediate inputs. Since the growth of intermediate inputs by definition are correlated with
aggregate and sectoral level inputs and outputs, this could very well lead to spurious finding of
spillovers. I suggest the author to consult Basu and Fernald (1995) to adopt their methodology
of checking the robustness of the finding of externality.
Some more minor and detailed suggestions follow:
I. Motivation
(1). The author shouldn’t claim to be the ”first” in terms of this type of empirical analysis.
Proper reference to Cabellaro and Lyons (1990, 1992) in the introduction is suggested.
2
(2). It needs to be motivated more why focusing on ”labor-generated spillover”. Is it pos-
sible to separate the research workers from the production workers in the model framework?
(3). Try to make use of the industry input-output patterns to cross-validate and motivate
the findings of the direction of knowledge spillovers. (Although I am not sure if there is informa-
tion outside of manufacturing sector). Right now, these numbers don’t mean much to the reader.
II. Estimation
(1). Report the standard errors of the estimates of the strength of ”spillovers” γij s.
(2). The normalization of the qilooks very arbitrary to me. More robustness check is needed
to show that the estimates are not sensitive to small changes in qi(while keeping the order same).
3
... A similar finding is reported by Kaiser (2002) in his analysis of a large dataset of German manufacturing and services firms (wholesale and retail trade, transport, traffic, banking, insurance, software, technical consultancy, marketing, and 'other' business related services): he finds that the probability that a service firm uses customers from the manufacturing sector as a source for innovation is much higher than the probability that a manufacturing firm uses customers from the service sector as a source of innovation. Finally, Quella (2009) reported evidence according to which, among six large macroeconomic sectors (Manufacturing, Mining, Construction, Services, Trade & Transportation, Agriculture) covering the totality of that US civilian economy from 1948 to 1991: 1) most knowledge flows occur between industrial knowledge and the tertiary sector; 2) these knowledge flows are largely unidirectional because manufacturing is the main source of spillovers in the economy while services (and agriculture) do not contribute at all to the generation of knowledge, neither internally nor externally; 3) Agriculture is last in the ranking of the capacity of both creating knowledge internally and absorb knowledge from elsewhere in the economy. These findings are confirmed in a recent survey by Belderbos and Mohnen (2013) who report a technology flow matrix based on patent citations. ...
Article
According to NEG literature (Baldwin et al. (2004)), spatial concentration of industrial activities increases growth at the regional and aggregate level without generating regional growth differentials. This view is not supported by the data. We extend the canonical model with an additional sector pro- ducing non-tradable goods which benefits from localized knowledge spillovers coming from the R&D performing industrial sector. This view, motivated by the evidence, generates both an anti-growth and a pro-growth effect of agglomeration for both the deindustrializing and the industrializing regions and leads to two novel results: 1) when agglomeration takes place, growth is lower in the periphery; 2) agglomeration may have a negative effect on the growth rate of real income, both at the regional and at the aggregate level. Our conclusions have relevant policy implications: contrary to the standard view, current EU and US regional policies favouring industrial dispersion might be welfare-improving both at the regional and the aggregate level and may reduce regional income disparities
Article
Full-text available
Most of our productive knowledge was handed down to us by previous generations. The transfer of knowledge from the old to the young is therefore a cornerstone of productivity growth. We study this process in a model in which the old sell knowledge to the young — old agents train the young, and charge them for this service. We take an information-theoretic approach in which training occurs if a young agent watches an old agent perform a task.Equilibrium is not constrained Pareto optimal. The old have private information, and this gives rise to an adverse selection problem: some old agents manage to sell skills that the planner would prefer to extinguish so as to allow more young agents to start new technologies. In this sense, there is too much resistance to change.
Article
Full-text available
In this paper, we argue that the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovative capabilities. We label this capability a firm's absorptive capacity and suggest that it is largely a function of the firm's level of prior related knowledge. The discussion focuses first on the cognitive basis for an individual's absorptive capacity including, in particular, prior related knowledge and diversity of background. We then characterize the factors that influence absorptive capacity at the organizational level, how an organization's absorptive capacity differs from that of its individual members, and the role of diversity of expertise within an organization. We argue that the development of absorptive capacity, and, in turn, innovative performance are history- or path-dependent and argue how lack of investment in an area of expertise early on may foreclose the future development of a technical capability in that area. We formulate a model of firm investment in research and development (R&D), in which R&D contributes to a firm's absorptive capacity, and test predictions relating a firm's investment in R&D to the knowledge underlying technical change within an industry. Discussion focuses on the implications of absorptive capacity for the analysis of other related innovative activities, including basic research, the adoption and diffusion of innovations, and decisions to participate in cooperative R&D ventures.
Article
The problem of deciding whether an intercept model or a no-intercept model is more appropriate for a given set of data is a problem with no simple solution. Often, the underlying physical situation will suggest an appropriate model; however, there still may be interest in assessing which model best fits the data or is the better predictor. In this article a different interpretation of regression through the origin is derived, that of a full fit to the original data set augmented by one further point. Examination of the leverage and influence of the augmented data point can provide help in comparing the models.
Article
Demonstrates that technical change is attributable to experience. The cumulative production of capital goods is used as the index of experience. New capital goods are assumed to completely embody technical change. The assumption is made that the model will be operating in an environment of full employment although reference is made throughout to the case of capital shortage. The implications of this model on wage earners are discussed, and profits and investments are examined. The rate of return is determined by the expected rate of increase in wages, current labor costs per unit output, and the physical lifetime of the investment. Learning is an act of investment that benefits future investors. Further analysis shows that the socially optimal ratio of gross investment to output is higher than the competitive level. (SRD)
Article
This paper considers the prospects for constructing a neoclassical theory of growth and international trade that is consistent with some of the main features of economic development. Three models are considered and compared to evidence: a model emphasizing physical capital accumulation and technological change, a model emphasizing human capital accumulation through schooling, and a model emphasizing specialized human capital accumulation through learning-by-doing.