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scarica il file pdf - Dipartimento di Economia
Product variety, product quality, and evidence of
Schumpeterian endogenous growth: A note
Francesco Venturini∗
Abstract
Using US manufacturing industry data, this paper re-examines empirical evidence of first- and second-generation Schumpeterian models of endogenous growth
focusing on innovation (patent) quality. It shows that semi-endogenous growth
models behave better than the other strands of Schumpeterian theory especially in
the knowledge-intensive section of the economy.
Keywords: Fully endogenous growth theory, Semi-endogenous growth theory,
Innovation quality, US manufacturing, High-tech industries.
JEL classification: O3, O4.
∗ [email protected]. Department of Economics, Finance and Statistics, University of Perugia,
Via Pascoli 20, 06123 Perugia (Italy). Tel.: +39 075 585 5291. I wish to thank Antonio Minniti, Cristiano
Perugini and Paul Segerstrom and the seminar participants at the Middldesex Business School and Università
Politecnica delle Marche for helpful comments.
1
1
Background
In the R&D-based endogenous growth theory, growth in knowledge is expressed as an
ideas-based innovation function:
Ȧ
X σ φ−1
=λ
A
A
Q
(1)
where Ȧ(·) is the annual flow of new knowledge (ideas) and A the knowledge stock
available each year (Ha and Howitt, 2007). The rate of change in knowledge is positively affected by R&D input X, and negatively by the rise in product variety, Q.
The latter is the product proliferation effect associated with demographic change L
(Qt ∝ Lβt ), that dilutes R&D expenses over a larger number of projects. β is a duplication parameter which is 0 when innovations are replications of existing products, and
1 when there are no duplicating innovations.
Equation (1) incorporates the main innovation mechanisms designed by the growth
theory (Table 1). Under σ = 0 and φ = 1, Ȧ/A is consistent with the neoclassical
prediction that productivity grows exogenously. The R&D-based, fully endogenous
growth setup of the first-generation Schumpeterian models (hereafter denoted by FE I)
emerges when σ > 0, φ = 1 and β = 0 (Aghion and Howitt, 1992; Romer, 1990).
Ȧ/A approaches the semi-endogenous, scale-invariant growth framework (SE) in the
original version designed by Segerstrom (1998) when σ > 0, φ < 1 and β = 0, or in
the hybrid version including a (weak) product proliferation effect when, other things
equal, β < 1. Lastly, equation (1) is consistent with the second-generation, fully
endogenous, scale-invariant growth mechanism (FE II) of Aghion and Howitt (1998,
Ch. 12) when σ > 0, φ = 1 and β = 1. SE and FE II frameworks have been motivated
on the basis of the Jones (1995) critique against the prediction of FE I models that
economic growth is proportional to the level of R&D.
The innovation function (1) has been assessed by several empirical works, most of
which found that FE II theories are more consistent with data (Ha and Howitt, 2007;
Madsen, 2008). Evidence corroborating the SE framework has been partially reported
by Ang and Madsen (2010), Barcenilla-Visús et al. (2010), and more extensively by
2
Table 1: Classification of growth models
Neoclassical
Fully Endogenous I
Semi-Endogenous
Fully Endogenous II
NEO
FE I
SE
FE II
φ
=1
=1
<1
=1
β
=0
[0,1)
=1
σ
=0
>0
>0
>0
Source: Ha and Howitt (2007).
Venturini (2010) looking at R&D races underlying these models. Findings inconsistent
with either branch of the most recent Schumpeterian theories are provided by Madsen
(2007).
Since Aghion and Howitt (1992), endogenous growth literature has developed as
quality ladder theory. However, the role of innovation quality has almost completely
been superseded by extant studies, which tested the various setups by estimating equation (1) with patent counts as a measure of innovation output, not controlling for their
quality content. This means considering only the horizontal dimension of innovation
(product variety). Also, the majority of works rely on country-level data, whereas new
growth models are conceived to describe innovation mechanisms occurring at the industry level. Due to this (non-negligible) twofold inconsistency with growth theory,
the present work revisits evidence on Schumpeterian endogenous growth by applying
US manufacturing industry data on product variety (patent counts), product quality
(patent quality) and research engagement (R&D capital) to the innovation framework
described by equation (1). The outline of the work is as follows. Section 2 illustrates
the econometric specification and the employed data. Section 3 reports results. Section
4 concludes.
2
Econometric specification and data
We estimate the steady-state framework where Qt = Lβt and equation (1) (in logs) is
reworded as:
ln Ȧit = α0i + α1 ln Xit + α2 ln Lit + α3 Ait + T D + it
3
(2)
where α0i = ln λi , α1 = σ, α2 = −σβ, α3 = φ. Subscripts denote time and industry.
α0i are industry fixed-effects, T D common time dummies, and it stationary error
terms. In contrast to the majority of works, A is considered as innovation output,
not as TFP, in order to avoid imposing a stationarity condition on productivity growth
which is hard to hold on disaggregated industry series (see Venturini, 2007).
The cointegration relationship (2) is estimated with the panel dynamic OLS estimator (Mark and Sul, 2003) on twenty US manufacturing industries for the period
1975-2003.1 Data on patent counts (number of applications) and patent quality (forward citations, backward citations, claims) are taken from NBER Patent Data files,
industry accounts data from EU KLEMS, and total R&D expenses from the National
Science Foundation and OECD ANBERD. Data details and statistical properties of the
series are provided in the web appendix.
The flow of new ideas Ȧ is initially measured by total patent applications; the stock
of available knowledge, A, by the cumulative value of the flow of new ideas, obtained
with the perpetual inventory method and geometric depreciation. We then discriminate
patented innovations by their quality content weighting each patent with the number
of forward citations received (scaled on manufacturing mean to control for truncation).
Although this is the most commonly used patent quality indicator (Trajtenberg, 1990),
as an alternative we also adopt backward citations made to existing patents, and priorities claimed in patent applications. Product proliferation, L, is measured by real gross
output; research input, X, by the stock of real R&D expenditure.
1 Industry list (ISIC Rev. 3 categories and OECD technological classes in parentheses): 1) Food , beverage
& tobacco (15-16; Low-Tech, LT), 2) Textile, leather & footwear (17-19; LT), 3) Pulp, paper, printing &
publishing (21-22; LT), 4) Petroleum, refining & extraction (23; Medium-Low Tech, MLT), 5) Chemicals and
chemical products (24; Medium-High Tech, MHT), 6) Pharmaceuticals (2423; High-Tech, HT), 7) Rubber
& plastics (25; MLT), 8) Other non-metallic mineral (26; MLT), 9) Basic metals (27; MLT), 10) Fabricated
metal products (28; MLT), 11) Machinery (29; MLT), 12) Office, accounting and computing machinery (30;
HT), 13) Electrical machinery and apparatus, nec (31; MHT), 14) Electronic valves and tubes (321; HT),
15) Communication equipment (322t3; HT), 16) Scientific instruments (331t3; HT), 17) Other instruments
(334t5; HT), 18) Motor vehicles, trailers and semi-trailers (34; MHT), 19) Other transport equipment (incl.
aerospace, 35; HT), 20) Wood, furniture and manufacturing nec (20, 36-37; LT).
4
3
Results
Estimates of eq. (2) are shown on the top of Table 2, the implied coefficient of product
proliferation, β, in the middle, while the bottom section sums up the values assumed by
the theoretical variables and the growth theory identified by the various specifications.
A linear Wald test is used to check the hypothesis of constant returns in the innovation
function (φ = 1), a non-linear one based on the delta method to assess whether β
equals zero (as in FE I or original SE), or β equals one (as in FE II).
In column (1), estimates are obtained with patent counts as a proxy for new ideas
Ȧ, and their cumulative value for A. The elasticity of Ȧ with respect to R&D input, X,
is 0.042, that of the ideas stock one (Wald test p-value for φ = 1: 0.65). The coefficient
of L is insignificant and the Wald tests performed on the ratio −α2 /α1 indicate that
product proliferation does not sterilise the R&D effort. Unambiguously, this evidence
supports FE I (φ = 1, β = 0, σ > 0). The innovation function is then examined
across technology-based industry groups. In medium- and low-tech sectors (col. 2),
we find decreasing returns and a negative effect of product proliferation which, clearly,
is not grounded theoretically. Mixed evidence emerges for the high- and medium-tech
group (col. 3): the positive, smaller than unity impact of product proliferation fits
the predictions of the hybrid SE framework (β = 0.38), while constant returns are
consistent with FE II.2 When the focus is restricted to high-tech industries only (col.
4), innovation counts turn out to be unrelated to R&D input (β is not definite).
Next, columns (5) to (8) show results yielded using forward cites-weighted patents
as a proxy for ideas. For the overall sample, results differ from col. (1) because of
a smaller elasticity of R&D input (0.019), the presence of decreasing returns (0.937)
and a strong (unitary) impact of product proliferation. In the light of such results, it
is not possible to establish which new R&D-based growth model is better grounded
empirically (φ < 1, β = 1, σ > 0). Though, more valuable information is obtained
by separately assessing the two large technology-based groups of industries (cols. 6
and 7). On the one hand, a neoclassic-type framework of growth is found to hold for
medium- and low-tech sectors (φ = 1, σ = 0, β non definite). On the other hand,
2 FE
I is not compatible with product proliferation.
5
evidence consistent with the hybrid version of SE framework emerges for high- and
medium-tech industries (φ < 1, σ > 0, β ∈ (0, 1)). The latter findings are confirmed
when attention is paid to high-tech manufacturing only (col. 8), for which we find a
larger impact of R&D capital (0.058) and a stronger sterilisation of R&D by product
proliferation (β = 0.74).
As robustness checks, backward citations are adopted as an alternative measure of
innovation quality, providing scarcely conclusive findings (cols. 9-12). This may depend on the derivative nature of such a patent indicator (Hall et al., 2007), which is
a powerful conduit of information on innovation quality only for the most technologically advanced manufacturing industries (col. 12); for high-tech sectors, evidence is
partially corroborating both SE and FE II (φ < 1, β = 1, σ > 0).
Some key findings obtained with forward cites are reaffirmed weighting patents
with claims. First, in technologically backward industries, innovation is found to be
independent of R&D input (col. 14). Second, although there is no clear-cut evidence
for the wide group of high- and medium-tech sectors (col. 15), the empirical model
is fully consistent with the SE framework in its original version when only the most
knowledge-intensive sectors are considered (φ < 1, σ > 0, β = 0; col. 16).
6
7
0.042**
(0.006)
-0.010
(0.008)
1.004**
(0.008)
α1 ln X
0.00
9
261
0.14
0.00
20
580
Wald test β=0 p-value
Wald test β=1 p-value
Industries
Obs
None
SE/FE II
<1
=1
>0
20
580
0.18
0.02
0.63
0.00
0.019**
(0.008)
-0.012*
(0.007)
0.937**
(0.013)
(5)
All
NEO
=1
ND
=0
9
261
ND
0.65
-0.015
(0.010)
0.054**
(0.021)
0.991**
(0.020)
SE
<1
(0,1)
>0
11
319
0.00
0.00
0.54
0.00
0.041**
(0.009)
-0.022**
(0.008)
0.898**
(0.014)
Forward citations × Counts
MediumHighLow
Medium
Tech
Tech
LT+MLT
HT+MHT
(6)
(7)
SE
<1
(0,1)
>0
7
203
0.00
0.00
0.74
0.00
0.058**
(0.012)
-0.043**
(0.010)
0.914**
(0.015)
HT
(8)
HighTech
None
>1
=0
<0
20
580
0.04
0.55
-0.40
0.09
-0.005*
(0.003)
-0.002
(0.002)
1.002**
(0.001)
(9)
All
None
>1
<0
<0
9
261
0.00
0.00
-2.00
0.00
-0.031**
(0.010)
-0.062**
(0.025)
1.016**
(0.006)
NEO
=1
ND
=0
11
319
ND
0.51
0.003
(0.002)
-0.006**
(0.002)
0.999**
(0.001)
SE/FE II
<1
=1
>0
7
203
0.33
0.00
0.82
0.00
0.011**
(0.003)
-0.009**
(0.002)
0.995**
(0.002)
SE/FE II
=1
(0,1)
>0
20
580
0.09
0.00
0.68
0.20
0.031**
(0.006)
-0.021**
(0.007)
1.006**
(0.006)
None
>1
ND
=0
9
261
ND
0.02
0.018
(0.011)
-0.043*
(0.025)
1.027**
(0.012)
SE/FE II
=1
(0,1)
>0
11
319
0.00
0.00
0.54
0.12
0.046**
(0.008)
-0.025**
(0.007)
0.987**
(0.008)
Alternative quality indicators
Backward citations × Counts
Claims × Counts
MediumHighHighAll
MediumHigh-Low
Medium
-Tech
Low
Medium
Tech
Tech
Tech
Tech
LT+MLT
HT+MHT
HT
LT+MLT
HT+MHT
(10)
(11)
(12)
(13)
(14)
(15)
Notes: Industry fixed-effects and common time dummies included. Pre-whitened standard errors in parentheses. ND=not definite.
** and * significant at a 5 and 10% level.
SE/FE II
MODEL IDENTIFICATION
FE I
None
<1
ND
=0
IMPLIED VALUES FOR THEORETICAL PARAMETERS
φ
=1
<1
=1
β
=0
<0
(0,1)
σ
>0
>0
>0
ND
0.08
0.010
(0.008)
0.021**
(0.008)
0.979**
(0.012)
7
203
0.00
0.04
0.38
0.35
0.045**
(0.008)
-0.017*
(0.010)
1.011**
(0.012)
HT
(4)
HighTech
Key results
11
319
0.02
0.24
-0.55
0.01
0.042**
(0.007)
0.023**
(0.008)
0.978**
(0.009)
β = −α2 /α1
Wald test φ = 1 (α3 = 1)
p-value
0.65
α3 ln A
α2 ln L
(1)
Dep: ln Ȧ
All
Row counts
MediumHighLow
Medium
Tech
Tech
LT+MLT
HT+MHT
(2)
(3)
Table 2: Cointegration estimates of innovation function
SE
<1
=0
>0
7
203
0.00
0.77
-0.08
0.00
0.026**
(0.008)
0.002
(0.006)
0.968**
(0.011)
HT
(16)
HighTech
4
Conclusions
This paper examined the innovation functions designed by the most recent Schumpeterian growth theories using US manufacturing industry data. In contrast to existing
evidence based on innovation counts, when innovation quality is adequately allowed
for (forward citations), semi-endogenous growth models are found to outperform other
theories especially for the most knowledge-intensive section of the economy.
8
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10
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Dicembre 2008
Pierluigi GRASSELLI
Cristina MONTESI
Roberto VIRDI
Antonio BOGGIA
Fabrizio LUCIANI
Gianluca MASSEI
Luisa PAOLOTTI
Elena STANGHELLINI
Francesco Claudio STINGO
Rosa CAPOBIANCO
Gianna FIGÀ-TALAMANCA
64
Maggio 2009
65
Giugno 2009
66
Settembre 2009
Fabrizio LUCIANI
67
Settembre 2009
Valentina TIECCO
Mirella DAMIANI
Andrea RICCI
Alessandra RIGHI
Dario SCIULLI
IV
Income inequality within European
regions: determinants and effects on
growth
Controversy over the interest rate
theory and policy. Classical approach
to interest rate and its continuations
Factor decomposition of crosscountry income inequality with
interaction effects
Employment Intensity of Growth in
Italy. A Note Using Regional Data
Technological
Change,
Labour
Demand and Income Distribution in
European Union Countries
L’analisi delle determinanti della
domanda di trasporto pubblico nella
città di Perugia
The willingness to pay for Renewable
Energy Sources (RES): the case of
Italy with different survey approaches
and under different EU “climate
vision”. First results
Ambiente operativo ed efficienza nel
settore del Trasporto Pubblico Locale
in Italia
L’interpretazione dello spirito del
dono
L’impatto ambientale ed economico
del
cambiamento
climatico
sull’agricoltura
On the estimation of a binary response
model in a selected population
Limit results for discretely observed
stochastic volatility models with
leverage effect
Factors behind performance-related
pay: evidence from Italy
The Timing of the School-toPermanent Work Transition: a
Comparison across Ten European
Countries
Economia agraria e pianificazione
economica territoriale nel Parco
nazionale del Sagarmatha (Everest,
Nepal)
I regimi di protezione dell’impiego
68
Ottobre 2009
69
Ottobre 2009
70
Ottobre 2009
71
Novembre 2009
72
Novembre 2009
73
Gennaio 2010
74
Febbraio 2010
75
Luglio 2010
76
Settembre 2010
77
Settembre 2010
78
Ottobre 2010
79
Ottobre 2010
80
Novembre 2010
81
Dicembre 2010
82
Dicembre 2010
83
Gennaio 2011
84
Febbraio 2011
85
Marzo 2011
86
Marzo 2011
87
Marzo 2011
Gianna FIGÀ-TALAMANCA Path properties of simulation schemes
for the Heston stochastic volatility
model
Cristina MONTESI
A comparative analysis of different
business ethics in the perspective of
the Common Good
Luisa FRANZINI
Determinants of Health Disparities in
Margherita GIANNONI
Italian Regions
Flavio ANGELINI
Evaluating
Discrete
Dynamic
Stefano HERZEL
Strategies in Affine Models
Giuseppe ARBIA
Institutions and geography: Empirical
Michele BATTISTI
test of spatial growth models for
Gianfranco DI VAIO
European regions
Mirella DAMIANI
Performance-Related Pay, Unions and
Andrea RICCI
Productivity in Italy: evidence from
quantile regressions
Davide CASTELLANI
The Effect of Foireign Investments on
Fabio PIERI
European Regional Productivity
Guglielmo M. CAPORALE
Time-varying spot and futures oil price
Davide CIFERRI
dynamics
Alessandro GIRARDI
Mirella DAMIANI
Labour
regulation,
corporate
governance and varieties of capitalism
Dario SCIULLI
University-to-work transitions: the
Marcello SIGNORELLI
case of Perugia
Olga DEMIDOVA
The Impact of Crises on Youth
Marcello SIGNORELLI
Unemployment of Russian Regions:
An Empirical Analysis
Misbah T. CHOUDHRY
The Impact of Financial Crises on
Enrico MARELLI
Youth Unemployment Rate
Marcello SIGNORELLI
Marco BELLUCCI
Fusioni ed acquisizioni: determinanti
ed effetti in un confronto europeo
Silvia MICHELI
Learning Curve and Wind Power
Leonardo BECCHETTI
Stefano CASTRIOTA
Elena GIACHIN RICCA
Davide CASTELLANI
Fabio PIERI
Stefano HERZEL
Marco NICOLOSI
Cătălin STĂRICĂ
Pierluigi GRASSELLI
Cristina MONTESI
Massimo DE FELICE
Franco MORICONI
Mirella DAMIANI
Fabrizio POMPEI
Andrea RICCI
V
Beyond the Joneses: inter-country
income comparisons and happiness
Foreign Investments and Productivity
Evidence from European Regions
The cost of sustainability on optimal
portfolio choices
Politiche orientate al bene comune e
politiche attive del lavoro
Un’estensione stocastica del modello
“Fisher-Lange”
Temporary job protection and
productivity growth in EU economies
88
Aprile 2011
Gaetano MARTINO
Paolo POLINORI
89
Aprile 2011
90
Maggio 2011
91
Giugno 2011
92
Giugno 2011
93
Luglio 2011
Stefano CASTRIOTA
Marco DELMASTRO
Roberto BASILE
Luigi BENFRATELLO
Davide CASTELLANI
Andrea RICCI
Robert WALDMANN
Francesca PIERRI
Alberto BURCHI
Elena STANGHELLINI
Francesco VENTURINI
VI
Productive process innovation as
sequential adjustment of the hybrid
governance structure: the case of the
poultry sector
Inside the black box of collective
reputation
Spatial clustering and nonlinearities in
the location of multinational firms
Job Security and Training: the Case of
Pareto Improving Firing Taxes
La capacità predittiva degli indicatori
di bilancio: una verifica sulle aziende
umbre
Product variety, product quality, and
evidence
of
Schumpeterian
endogenous growth: a note
ISSN 1722-618X
I QUADERNI DEL DIPARTIMENTO DI ECONOMIA
Università degli Studi di Perugia
1
Dicembre 2002
Luca PIERONI:
Further evidence of dynamic
demand systems in three european
countries
Il valore economico del paesaggio:
un'indagine microeconomica
A note on internal rate of return
2
Dicembre 2002
3
Dicembre 2002
4
Marzo 2004
Luca PIERONI
Paolo POLINORI:
Luca PIERONI
Paolo POLINORI:
Sara BIAGINI:
5
Aprile 2004
Cristiano PERUGINI:
6
Maggio 2004
Mirella DAMIANI:
7
Maggio 2004
Mauro VISAGGIO:
8
Maggio 2004
Mauro VISAGGIO:
9
Giugno 2004
10
Giugno 2004
Elisabetta CROCI ANGELINI
Francesco FARINA:
Marco BOCCACCIO:
11
Giugno 2004
12
Luglio 2004
13
Luglio 2004
14
Ottobre 2004
15
Novembre 2004
Gaetano MARTINO
Cristiano PERUGINI
16
Dicembre 2004
Federico PERALI
Paolo POLINORI
Cristina SALVIONI
Nicola TOMMASI
Marcella VERONESI
Cristiano PERUGINI
Marcello SIGNORELLI:
Cristiano PERUGINI
Marcello SIGNORELLI:
Cristiano PERUGINI
Marcello SIGNORELLI:
Cristiano PERUGINI:
VII
A new class of strategies and
application to utility maximization
for unbounded processes
La
dipendenza
dell'agricoltura
italiana dal sostegno pubblico:
un'analisi a livello regionale
Nuova macroeconomia keynesiana
e quasi razionalità
Dimensione e persistenza degli
aggiustamenti fiscali in presenza di
debito pubblico elevato
Does the growth stability pact
provide an adequate and consistent
fiscal rule?
Redistribution and labour market
institutions in OECD countries
Tra regolamentazione settoriale e
antitrust:
il
caso
delle
telecomunicazioni
Labour market performance in
central european countries
Labour market structure in the
italian provinces: a cluster analysis
I flussi in entrata nei mercati del
lavoro umbri: un’analisi di cluster
Una
valutazione
a
livello
microeconomico
del
sostegno
pubblico
di
breve
periodo
all’agricoltura. Il caso dell’Umbria
attraverso i dati RICA-INEA
Economic inequality and rural
systems: empirical evidence and
interpretative attempts
Bilancio ambientale delle imprese
agricole
italiane:
stima
dell’inquinamento effettivo