Industrial research and development and real exchange rate depreciation in a small open economy

Published date01 September 2020
AuthorSaleh S. Tabrizy
DOIhttp://doi.org/10.1111/twec.12924
Date01 September 2020
2490
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wileyonlinelibrary.com/journal/twec World Econ. 2020;43:2490–2523.
© 2020 John Wiley & Sons Ltd
Received: 20 April 2019
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Revised: 20 December 2019
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Accepted: 6 January 2020
DOI: 10.1111/twec.12924
ORIGINAL ARTICLE
Industrial research and development and real
exchange rate depreciation in a small open economy
Saleh S.Tabrizy
College of Arts and Sciences, Department of Economics, The University of Oklahoma, Norman, Oklahoma
KEYWORDS
exchange rate, export intensity, R&D
1
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INTRODUCTION
A growing body of international economics literature is concerned with questions that are primarily
raised in the economics of innovation. Identifying the open economy determinants of investments in
research and developments (henceforth, R&D) is among those questions. In this research, I focus on
how industrial R&D expenditures in a small open economy respond to changes in relative national
prices, as measured by industry-specific effective real exchange rates (henceforth, IERER).
Firms’ current and future profits provide the channels for the interaction between R&D and ex-
change rates. For a given industry, R&D expenditures depend on the investments in R&D equipment
and the utilisation cost of that equipment (e.g., the wage bill for scientists, engineers or designers).
Over time, these expenditures are expected to affect the innovative capabilities and, hence, the future
profitability of the industry. In return, improvements in profit provide more resources that may be al-
located to R&D activities. Considering this interdependence, changes in relative national prices may
affect R&D expenditures through, at least, three channels. First, part of the inputs that are used for in-
novative activities may be imported. There may also exist a complementarity between other imported
inputs and R&D activities (Bøler, Moxnes, & Ulltveit-Moe, 2015). Lastly, current and future profits
that provide resources for innovative activities depend partially on export revenue. For a given indus-
try, the ultimate effect of these offsetting forces may depend on the importance of exporting activities,
the reliance on imported inputs and the relative magnitude of pass-through elasticities.
In this study, I employ industry-level observations from a panel of manufacturing industries in
the Republic of Korea. The data set in use includes information about the IERERs and industry-level
I am grateful to Rebecca Neumann for her supervision. I am also grateful to an anonymous referee, Kundan Kishor, Suyong
Song, Mohsen Bahmani-Oskooee, Avik Chakrabarti, Niloy Bose and Ariel Weinberger for their advice. Further, I would like
to thank seminar participants at University of Wisconsin–Milwaukee, the University of Oklahoma, Midwest Economics
Association Conference (2014), Southern Economic Association Conference (2014) and Eastern Economic Association
Conference (2016) for helpful comments. Also, the regression analyses of this paper are done using two estimation
procedures, one of which is written by David Roodman, and the other one is written by Giovanni S.F. Bruno. I have had free
access to these estimation procedures. For this, I am grateful to the authors. I remain responsible for any shortcomings and
errors.
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TABRIZY
R&D expenditures, as well as industry-level value added, exports and imports. It offers variations
across 22 manufacturing industries over a 15-year window: from 2001 to 2015. During this period,
R&D expenditures increased significantly in Korea. In 2001, the gross domestic R&D expenditures in
Korea was 2.34% of its GDP, just slightly above the figure for all OECD countries (2.16%). By 2015,
the gross domestic R&D expenditures in Korea reached 4.22% of its GDP, while the same figure for
all OECD countries remained almost steady (2.34%). In fact, no other OECD country experienced
such consistent growth in R&D activities during this time window (OECD, 2019).
I employ a dynamic model to examine the effects of lagged changes in IERER on contemporane-
ous changes in industry-level R&D. I control for lagged changes in industry-level R&D expenditures,
contemporaneous and lagged changes in other important covariates and time-invariant unobserved in-
dustry-specific characteristics. Considering the cross-section and time series dimensions of the above
panel, I make use of the corrected least square with dummy variables estimation procedure (Bruno,
2005a; Bun & Kiviet, 2003; Kiviet, 1995) to estimate the parameters of interest. Compared with con-
ventional estimation procedures, Judson and Owen (1999), Bruno (2005b) and Buddelmeyer, Jensen,
Oguzoglu, and Webster (2008) suggest that the above procedure provides better estimation for key
parameters in dynamic panel models with relatively small cross-section and time series dimensions.
The results reveal that among industries with medium levels of export intensity a lagged deprecia-
tion in IERER (i.e. increase in price competitiveness) leads to a decline in contemporaneous indus-
try-level R&D expenditures. Among industries with very low or very high export intensities, however,
I find no significant effects from lagged depreciation. This pattern may be the result of two factors.
First, compared with industries on the tails, industries that are at the middle of export intensity distri-
bution are likely to have relatively low pass-through elasticities (Garetto, 2016). Second, despite their
differences in exports intensity, evidence from input–output tables suggest that the reliance of Korean
industries with medium levels of export intensity on imported intermediate inputs is similar to the
reliance of other industries on those inputs. Given the complementarity between international sourc-
ing and R&D activities (Bøler et al., 2015), an increase in the relative price of imported inputs as a
result of real depreciation may adversely affect R&D investments.1 The reliance on imported inputs
being similar among all industries, this adverse effect may in particular be significant among indus-
tries that have relatively low pass-through elasticities, which include industries that are at the middle
of the export intensity distribution. This finding improves our understanding of how industrial R&D
expenditures may react to changes in relative national prices in a small open economy.
Previous empirical findings are summarised in Section 2. The data in use are fully described in
Section 3. The empirical analyses are discussed in Section 4. Section 5 concludes.
2
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BACKGROUND
This study contributes to a growing body of empirical research on the linkages between innovation
and selected open economy variables. While others examine the effects of greater access to foreign
markets (Baldwin & Gu, 2004; Bustos, 2011; Damijan, Kostevc, & Polanec, 2010; Lileeva & Trefler,
2010) or import competition (Autor, Dorn, Hanson, Pisano, & Shu, 2017; Bloom, Draca, & Van
Reenen, 2016; Scherer & Huh, 1992; Teshima, 2009), this paper explores the effect of changes in rela-
tive national prices. Within this line of literature, the existing empirical studies are of two types. Some
of them examine the effect of exchange rate uncertainty or volatility on R&D expenditures. Others
1 Chen (2017) offers a detailed description of how this complementarity may govern the relationship between exchange rate
and R&D expenditures.
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TABRIZY
examine the direction of changes in R&D expenditures following exchange rate swings. Empirical
evidence showing an adverse effect of exchange rate uncertainty or volatility on R&D expenditures
seem to be conclusive (Becker & Hall, 2009; Ito & Haneda, 2017; Mahagaonkar, Schweickert, &
Chavali, 2009). However, evidence on the direction of changes in R&D expenditures in response to
TABLE 1 Summary of previous empirical findings
Author(s) and
publication year Data
Main estimation
method(s) Main findings
Zietz and Fayissa
(1994)
Panel of 360
manufacturing firms
from 1975 to 1987 in
the US
Ordinary least square,
fixed effect, and random
effect
Increase in R&D expenditures
in response to exchange rate
appreciation among firms in R&D-
intensive industries
Funk (2003) Panel of 269
manufacturing firms
from 1979 to 1994 in
the US
Pooled mean group Increase in R&D expenditures
in response to exchange rate
depreciation among exporting firms
Also, decline in R&D expenditures
in response to exchange rate
appreciation among purely domestic
firms
Becker and Pain
(2008)
Panel of 11
manufacturing
industries from 1993 to
2000 in the UK
Ordinary least square and
dynamic panel data
Decline in R&D expenditures
in response to exchange rate
depreciation among manufacturing
industries
Chen (2017) Panel of 49 developed
and developing
countries from 1996 to
2011
Fixed effect and dynamic
panel data
Decline in aggregate R&D
expenditures per capita in response
to exchange rate depreciation among
developed countries
Kaiser et al.
(2017)
Panel of about 700
manufacturing firms
from 1996 to 2015 in
Switzerland
Fixed effect poisson
estimation
Increase in R&D expenditures
in response to exchange rate
appreciation for firms that have
access to considerable financial
means and small R&D-intensive
firms that that are not internationally
exposed
Also, decline in R&D expenditures
in response to exchange rate
appreciation for firms with average
net international exposures, firms
with low financial means, and
large R&D-intensive firms that are
internationally exposed
Alfaro et al.
(2018)
Panel of about 495,000
firms from 2001 to
2010 in 76 emerging
economies and 23
industrialised countries
Fixed effect Increase in R&D expenditures
in response to exchange rate
depreciation among firms in export-
oriented emerging economies in Asia
Also, decline in R&D expenditures
in response to exchange rate
depreciation among firms in
emerging economies in Latin
America and Eastern Europe

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