A Schumpeterian view of business cycles and growth, is that recessions provide a cleansing mechanism for correcting organizational inefficiencies and for encouraging firms to reorganize, innovate or reallocate to new markets. The cleansing effect of recessions is also to eliminate those firms that are unable to reorganize or innovate. Schumpeter himself would summarize that view as follows; “[Recessions] are but temporary.
They are means to reconstruct each time the economic system on a more efficient plan”. This of course assumes that firms can always borrow enough funds to either reorganize their activities or move to new activities and markets. Without credit constraints, investment choices are indeed dictated by an opportunity-cost effect: namely, the opportunity cost of long-term innovative investments instead of short-term capital investments, is lower in recessions than in booms. Hence, the share of long-term investment in total investment should be countercyclical, whereas the share of short-term investment is procyclical (see Hall (1993), Gali and Hammour (1992), Aghion and Saint-Paul (1998), Bean (1990), Bloom (2007)).
However, as emphasized by Aghion et al. (2005), henceforth AABM, things become quite different when credit market imperfections prevent firms from innovating and reorganizing in recessions. In particular, suppose that firms can choose between short-run capital investment and long-term R&D investment, that innovating requires that firms survive short-run liquidity shocks, and that to cover liquidity costs firms can rely only on their short-run earnings plus borrowing.
Whenever the firm is hit by a bad (idiosyncratic or aggregate) shock, its current earnings are reduced, and therefore so is the firms’ ability to borrow in order to innovate. This in turn implies that a negative shock should hit R&D investments and innovation more in firms that are more credit constrained. In other words, R&D investments should be expected to be more procyclical in firms facing tighter credit constraints.
In this paper, we test this prediction using a French firm-level panel data set that contains information both, on the extent of credit constraints at the firm level each year, and on R&D investments by the firm, relative to total investment. The firm-level database we use has been collected by the Banque de France. The sample includes about 13,000 firms (all of them having at least one time a positive R&D investment) and covers the period 1993-2004.
The database contains an important number of small and medium firms that are particularly prone to be hit by credit constraints, and are thus especially relevant for the study of the above-mentioned mechanisms. The most interesting feature of this dataset is that it contains information on credit constraints at the firm level. More specifically, firms that fail to repay their trade creditors are identified on a list to which banks have access. Our first stage regression shows that being notified on that list under the heading ”incident de paiement”, is negatively and significantly correlated with a firm’s access to future loans.
Once equipped with this firm-level information on credit access, we regress firm R&D over total investment on firm sales and its interaction with credit constraints. Our main results from second stage regressions can be summarized as follows: the share of R&D investment over total investment is counter cyclical without credit constraints, and it becomes more procyclical as firms face tighter credit constrained; this effect is only observed during downturns: namely, in presence of credit constraints, R&D investment share plummets during recessions but it does not increase proportionally during upturns; the level of R&D investment is lower in more credit constrained firms whatever the firm’s position within the business cycle but it decreases more during recessions. Therefore, credit constraints, by preventing the R&D share from being countercyclical, may amplify the business cycle, increase productivity growth volatility and decrease average productivity growth.
This paper relates to a broader literature on cycles, innovation and growth. The theoretical papers that are most closely related to our approach in this paper, are Hall (1991), Gali and Hammour (1992), Caballero and Hammour (1994), Aghion and Saint-Paul (1998), Francois and Lloyd-Ellis (2003), Comin and Gertler (2006), Barlevy (2004), and Barlevy (2007). All these papers take a Schumpeterian approach to the relationship between growth and cycles, however they do not emphasize credit constraints. The empirical literature on the subject starts with Ramey and Ramey (1995) who provide cross-country evidence of a negative relationship between volatility and growth. More closely related to the analysis in this paper is AABM.
Based on cross-country panel data over the period 1960-2000, AABM show that structural investment (another proxy for growth-enhancing investment) is more procyclical in countries with lower ratios of credit to GDP, and that the correlation between macroeconomic volatility (measured as in Ramey and Ramey (1995) by the variance of growth rate) and average growth, is more negative the lower financial development. However, unlike in this paper, the data in AABM do not include R&D investments, and moreover credit constraints are not measured at the firm level. Prior evidence on R&D investments over the cycle, is provided by Griliches (1990), Comin and Gertler (2006), and Barlevy (2007), although not in relation to firms’ credit constraints.
The paper is organized as follows. Section 2 presents a simple model to derive our main predictions. Section 3 presents the data and the measurement variables. Section 4 presents the first stage analysis, where we regress credit access on firms’ past credit records. Section 5 presents the second stage results. Section 6 discusses the robustness of our results and their implications for productivity growth and volatility, and it concludes.
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