Transcript innovation - Kevin James Bowman, Ph.D.

Invention, Innovation, and Wage Inequality for
Developed Countries
(on Wage Inequality and Growth)
Kevin James Bowman, Ph.D.
Assistant Professor
Bloomsburg University
and
Sarinda Taengnoi, Ph.D.
University of Wisconsin - Oshkosh
A Puzzle Regarding
Inequality and Recent Tech. Change
•
U.S. wage and earnings inequality ↑ sharply, 1980-1995
•
Skill-biased Technological Change (SBTC)
the main culprit
•
SBTC & information and communication techs.
•
Yet France and Germany: no ↑ in inequality during this time
Aghion et al. (1999) surveys the lit.
- Even as they had exposure to these techs.
Evidence from (Dinardo & Pischke, 1997)…
The standard textbook explanation:
Continental Western Europe:
SBTC
=> ↓ LD with labor market rigidities (fixed wL)
=> ↑ UL
e.g., Mankiw (2000, p. 150) or
Frank and Bernanke (2001, pgs. 236-37)
Yet, U.S. has an unexplained higher return to
skills after controlling for
i) experience,
ii) wage setting institutions, and
iii) absolute levels of skills.
Blau and Kahn (2005)
Continental Europe as Innovation Secialists &
the U.S. as Invention Specialists
The Three Forces of Technological Change:



INVENTION: new ideas/techs. with potential to ↑output
with given labor.
most skill-intensive.
INNOVATION: early apps of inventions that ↑ output with
given labor.
moderately skill-intensive.
DIFFUSION: later apps of innovation across more
industries.
least skill-intensive
but still requires…
Examples
Late 1800s/
Early 1900s
Late 1900s/
Early 2000s
Invention
electricity
computer technologies
(DOS)
Innovation
early plant
redesigns &
electrified
equipment
MS Office software
& early business apps.
Diffusion
the spread of
More user-friendly &
electric tools & sector-specific Office
plant designs
applications
Novel, theory:
Specialization in innovation causes:
• A greater share of skilled workers
innovating rather than inventing
(as it licenses invention from abroad).
• Innovative output modeled as helping to diffuse
skill-biased, inventive (frontier) knowledge into
more general (adoptive) knowlege.
Supported by David (1990), Rogers (1995)
• Important Facts:
- Important info-age techs originated in the U.S.
- America’s numerous research universities…
For constant accumulation rates rates at the steady-state:
the Direct Effect from Specializing in Innovation:
A greater share of high-skilled in innovation =>
i) smaller ratio of inventive to innovative output =>
ii) smaller ratio of total to adoptive knowledge (V/A) =>
iii) smaller relative wage (wH/wL).
iv) a larger percentage of the population that is skilled due
to lower inequality (low skilled families can
afford higher ed., the cost of which is
dependent
on the high skilled wage.
From specializing in innovation (in simulations) there are:
Two Indirect Effects:
1) The Relative Accumulation Rate Effect:
Endogenously
The direct effect: ↓ (wH/wL)
=> ↑ (P/P*) => ↑ innovative output for given
licensed foreign invention
=> ↑ diffusion of skill-biased, frontier knowledge
into skill-saving adoptive knoweldge
=> ↓ (wH/wL) and ↑ (P/P*) further.
2) The Partial Licensing Effect:
The innovative specialist may choose to license a
smaller share of foreign, frontier knoweldge
=> education is more affordable => ↑ (P/P*)
=> more skilled workers in innovation:
↑ innovative output relative
to licensed foreign invention
=> ↑ diffusion into adoptive knoweldge
=> ↓ (wH/wL) and ↑ (P/P*) further.
The Direct Specialization in Innovation effect
And its Two Indirect Effects,
1. the relative accumulation rate effect and
2. the partial licensing effect)
all act in the same direction allowing
the innovative specialist to have:
A lower relative wage (and wage inequality)
A larger share of its population to have a relatively high
education
Where the higher skilled do not access as high
frontier knowledge
This helps explain for the U.S. (arguably an inventive leader):
higher returns to skill, and
greater variance in skills
for given economic growth rates.
Conclusion:
Importing inventions and specializing in innovation can help
explain Continental Europe’s:
- lower wage inequality
- smaller increases in wage inequality during SBTC
- lower returns to skill controlling for
labor market rigidities, &
variance of skills
- less variance of skill
(accessing stocks of knowledge that are
closer in size)
- Policy Implication:
Allowing foreign Ph.D. grads to stay in the
U.S. could decrease
(V/A) and wH/wL.
General Abbreviations List
LD = low skilled labor demand
UL = unemployment rate of the low skilled
L = low-skilled labor
H = high-skilled labor
w = wage rate
V= the stock of total knowledge
A=the stock of adaptive knowledge
(accessible by L and H)
(V-A)= frontier knowledge
(accessible by H)
(V/A) = ratio of total to adaptive knowledge
P = human capital investment (think Pupils)
g = economic growth rate
* = to denote the large economy
(which must invent – representing U.S.)
no star indicates the innovative specialist
(which represents Continental Europe)
In paper:
W for the Large Economy (instead of *)
X for the Innovative Specialist
More Technical Abbreviations
(for the formal model)
λ = student-teacher ratio
f = education fee per pupil
x = savings per saver
b = borrowing per pupil
r = the real interest rate
c = consumption per agent
θ = marginal propensity to save (MPS)
μ = productivity parameter
I for the inventive sector
N for the innovative sector
D for the adaptive sector
λ = adaptive knowledge spillover parameter
α = the relative importance of skills in
innovation.
sss = simultaneous steady state