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Erschienen in: Empirical Economics 1/2019

14.12.2017

The cyclical behavior of R&D investment during the Great Recession

verfasst von: Zeynep Kabukcuoglu

Erschienen in: Empirical Economics | Ausgabe 1/2019

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Abstract

This paper investigates the cyclicality of research and development (R&D) activities during the Great Recession period by incorporating the role of credit constraints, using the Great Recession period as a natural case study. Recession period is a good setting in which to identify cyclicality and eliminate endogeneity issues that have been discussed in the literature. Using firm-level data on non-federally funded, high-technology firms in the USA, this paper shows that firms without bond ratings had more procyclical R&D investments than those firms with bond ratings. I also test whether capital or inventory investments of firms that also do R&D are procyclical. I find that firms without bond ratings adjust their inventories more rapidly compared to capital and R&D investments, when they are hit by a bad shock.

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Fußnoten
1
See Hall and Lerner (2010) for a detailed discussion of financing of R&D and a review of the literature related to financial constraints on R&D investment.
 
2
Using investment-cash flow sensitivity to test for the presence of financial constraints started with Fazzari et al. (1988). See Kaplan and Zingales (1997) for possible endogeneity issues in this approach.
 
3
See Erickson and Whited (2000) on measurement error problems in Tobin’s Q.
 
4
Highly cited papers are Brown et al. (2009) and Brown and Petersen (2009, 2011) for R&D investment in the USA and Brown et al. (2012) in Europe.
 
5
For this analysis, I construct capital stock series for each firm, using the perpetual inventory method and capital expenditures data. Inventory stock data are available on the Compustat database.
 
6
See Arvanitis and Woerter (2013) for a good summary of theories in this literature.
 
7
Erickson and Whited (2000), Almeida and Campello (2007), and Hennessy and Whited (2007) emphasize the importance of finding exogenous proxies in these estimations.
 
8
The steps that I followed to construct the datasets for Figs. 1, 2 and 3 are explained in detail in “Appendix”. The gray bars indicate recession periods.
 
9
These results are in line with Brown et al. (2009).
 
10
Using the data from National Science Foundation, Anzoategui et al. (2016) show that R&D expenditure per capita of the US corporations experienced a sharper contraction before and during the 2001–2002 crisis than the Great Recession period. Bianchi et al. (2014) find during the Great Recession, there was a significant drop in technology adoption and utilization rates, but small change in accumulation of knowledge. In contrast, during 2001 there was a modest change in the adoption rate of technology. They conclude that the aforementioned characteristics of the Great Recession resulted in severe contractions in the short-term, but had less effect on the trend growth.
 
11
The list of non-federally funded, high-tech industries was obtained from Brown et al. (2009).
 
12
Early papers that use the existence of bond ratings to identify potentially constrained firms are Fazzari et al. (1988) and Whited (1992) for capital investments and Kashyap et al. (1994) for inventory investments.
 
13
This fact is well documented by Brown et al. (2009).
 
14
The steps that I take in constructing the regression sample are explained in detail in “Appendix”.
 
15
This specification is similar to the one used by Aghion et al. (2012) in which they test the cyclicality of R&D investments for constrained firms in France, and the one by Kashyap et al. (1994), in which they test for bank dependence in inventory investments of the firms.
 
16
See Gilchrist and Himmelberg (1995) and Erickson and Whited (2000) for detailed discussions of the control variables and of Tobin’s Q. Alti (2003) shows that Tobin’s Q can be a noisy measure for investment opportunities for young firms.
 
17
See Hall and Lerner (2010) for a discussion of why there is often a large wedge between internal and external sources of finance for R&D investments compared to other types of investments.
 
18
Kashyap et al. (1994) apply this step before they test for the liquidity constraints on the inventory investment of the firms.
 
19
I apply this rule because due to small sample size there are very few firms without access to bond markets, and the estimation does not have enough statistical power with the previous definitions of \(B=1\) and \(B=0\).
 
20
Eberly et al. (2008) is an example of research that uses double-declining balance.
 
21
I used the FRED (Federal Reserve Economic Data) database from the Federal Reserve Bank of St. Louis to assemble the data used herein; see the references for information on the specific series.
 
22
I used the FRED (Federal Reserve Economic Data) database from the Federal Reserve Bank of St. Louis to assemble the data used herein; see the references for information on the specific series.
 
23
Some studies in the literature suggest taking a constant growth rate that applies to all firms, which is around 5 or 8% (Hall 1990, 1993; Hall and Mairesse 1995). Hall and Mairesse (1995) point out that the choice of growth rate has an effect on the initial stock, but it declines in importance as time passes. More recent studies choose growth rates that differ at the firm or industry level (Parisi et al. 2002; Lyandres and Palazzo 2012). In this paper, the main results are obtained by using different growth rates at the industry level. The results, obtained by using a fixed growth rate, are also reported as a robustness check.
 
24
I used the FRED (Federal Reserve Economic Data) database from the Federal Reserve Bank of St. Louis to assemble the data used herein; see the references for information on the specific series.
 
25
I used the Organization for Economic Co-operation and Development (OECD) database to assemble the data used herein; see the references for information on the specific series.
 
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Metadaten
Titel
The cyclical behavior of R&D investment during the Great Recession
verfasst von
Zeynep Kabukcuoglu
Publikationsdatum
14.12.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Empirical Economics / Ausgabe 1/2019
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-017-1358-7

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