...have focused borrowers' credit-market conditions and their ability to propagate an initial real or monetary shock to the rest of the economy (Bernanke, Gertler, and Gilchrist, 1996 and 1998; and Hubbard, 1998).

This paper considers an alternative mechanism that may explain the observed large cyclical movements of investment with respect to the business cycle, based on firms' behavior under uncertainty. Important early contributions on the relationship between investment and uncertainty include those of Lucas and Prescott (1971), Hartman (1972), Nickell (1977a and 1977b), and Abel (1983). In the last decade, research has focused on a class of models in which real options influence investment behavior, because firms may have an incentive to wait for the arrival of new information, thus postponing the implementation of their investment plans (Bertola, 1988; Pindyck, 1988; Caballero, 1991; and Dixit and Pindyck, 1994; see also the survey by Carruth, Dickerson, and Henley, 2000).

Theoretical analyses have shown that the impact of uncertainty on the level of the capital stock in the long run is ambiguous in this class of models (Abel and Eberly, 1999; and Caballero, 1999). Perhaps for this reason, empirical studies have not reached any consensus on the sign or significance of this long-run relationship. However, more recent theoretical contributions have emphasized the effects of uncertainty on short-run investment dynamics (Abel and Eberly, 1999; and Bloom, 2000), and empirical studies have found evidence consistent with the predicted weaker response of investment to demand shocks at higher levels of uncertainty (Guiso and Parigi, 1999; and Bloom, Bond, and Van Reenen, 2003).

This paper extends this empirical research using data on Italian firms. Following Bloom, Bond, and Van Reenen (2003), we test for the nonlinear and heterogeneous investment dynamics predicted by models with partial irreversibility and uncertainty. An important difference is that we do not rely on a stock-returns measure of uncertainty. Like Guiso and Parigi (1999), we use a sample of firms that is representative of the Italian manufacturing sector, for which we can derive a measure of uncertainty from survey responses of the managers who are responsible for the firms' investment decisions. Exploiting the panel nature of our data set, we investigate the short-run effects of uncertainty on investment dynamics, thus extending the cross-sectional analysis of Guiso and Parigi (1999).

We find evidence of heterogeneity across firms in investment dynamics and, in particular, of a weaker effect of demand shocks on investment for firms facing higher uncertainty. Interestingly, our findings also point to an additional source of nonlinearity originating from a convex response of investment to positive demand shocks.

I. A Review of the Literature

Early contributions have shown that uncertainty may increase the value of the marginal unit of capital, thus leading to more capital accumulation. Hartman (1972) and Abel (1983) investigate the impact of uncertainty on capital accumulation by focusing on the investment behavior of a competitive firm with constant returns to scale and (symmetric) convex adjustment costs. Under these assumptions, the resulting profit function is convex in price and, therefore, a mean-preserving increase in price uncertainty raises the expected return on a marginal unit of capital. This Jensen's inequality effect suggests a positive relationship between uncertainty and investment.

Importantly, the (symmetric) convexity of adjustment costs rules out the possibility that investment expenditures may be subject to some degree of irreversibility, a feature first emphasized by Arrow (1968). When investment is completely irreversible, and future demand, cost conditions, and other relevant factors are uncertain, firms have an incentive to wait until more information becomes available. On the contrary, when a firm does invest "[i]t gives up the possibility of waiting for new information to arrive that might affect the desirability or timing of the expenditure; it cannot disinvest should market conditions change adversely" (Dixit and Pyndick, 1994, p. 6). In other words, the implementation of a given investment plan carries an opportunity cost equivalent to the exercise of a financial call option. The decision to exercise such an option is irreversible. In fact, although the holder may sell the asset at a later stage, he or she will not be able to recover the value of the option.

Caballero (1991) investigates the impact of uncertainty and irreversibility on investment, highlighting the role that different assumptions on the functional form of adjustment costs and on the degree of competition and returns to scale play in shaping the response of investment to uncertainty. Interestingly, Caballero shows that as we move away from the hypothesis of perfect competition and constant returns to scale toward an environment of imperfect competition or decreasing returns to scale, the response of investment to uncertainty tends to become negative. In this setting, Caballero also shows that the more asymmetric the functional form of adjustment costs is, the more negative the relationship between investment and uncertainty becomes.

However, Pindyck (1993) notes that Caballero's (1991) analysis treats the firm in isolation, describing the effect of a mean-preserving increase in the variance of price, which is exogenous to the firm. While individual firms' investment and production decisions depend on the price process, they also collectively generate that process. Hence, Pindyck analyzes the interactions between irreversibility and uncertainty at the industry level by making price and industry output endogenous, and shows that this further strengthens the negative relationship between uncertainty and investment. In fact, assuming an industrywide setting, the possibility of entry of new firms or the expansion of existing ones limits the amount by which price can increase following industrywide positive shocks. With (partial) irreversibility, however, there is no similar mechanism that prevents price from falling after negative shocks. This asymmetry acts as a disincentive to invest.

A number of the earlier theoretical models focused on onetime investment decisions, in which there is no distinction between the effect of uncertainty on the level of investment and on the level of the capital stock. An important recent contribution by Abel and Eberly (1999) considers repeated investment decisions and highlights the ambiguity of the long-run relationship between uncertainty and the average level of the capital stock. They analyze the interaction between the user-cost effect and the hangover effect on the long-run level of the capital stock. The former implies that firms may end up having less capital in the long run than in the absence of irreversibility and uncertainty, because the user cost relevant for investment under irreversibility would be higher than that in the standard case of costless reversibility. The latter effect accounts for the difficulties faced by firms in divesting capital during economic downturns caused by the irreversibility constraint. Accordingly, if the latter effect were to dominate, firms would end up having more capital on average in the long run compared with the frictionless case. Interestingly, Abel and Eberly characterize these opposing effects and show that in the long run either effect may dominate, depending on the values assigned to the parameters in the model.

Abel and Eberly (1999) and Bloom (2000) emphasize that, with partial irreversibility, a higher level of uncertainty implies both a higher-threshold required rate of return to justify positive investment and a lower-threshold required rate of return to justify disinvestment. Because the optimal investment policy is characterized by a wider distance between the two thresholds, this unambiguously reduces the probability of an investment action in response to a given exogenous demand shock. Bloom (2000) also shows that irreversibility and uncertainty induce richer short-term investment dynamics, with lagged responses to past demand shocks occurring when thresholds are eventually reached.

Cooper and Haltiwanger (2006) analyze the effects of various forms of adjustment costs on investment dynamics. Observing that, in their panel of U.S. manufacturing plants, inaction in investment activity is often followed by periods of intensive adjustment of the capital stock, they argue that nonconvex costs and irreversibilities may play a central role in investment decisions. They estimate a model of capital stock adjustment that incorporates a rich specification of adjustment costs. Their empirical results suggest that both convex and nonconvex adjustment cost components are required to explain the observed adjustment process.

Bloom, Bond, and Van Reenen (2003) elaborate on the implications of these previous studies for investment dynamics. They simulate firm-level data from a calibrated model in which firm investment is aggregated over a number of independent plants, which are subject to idiosyncratic plant-level productivity shocks as well as to a common firm-level demand shock. One implication of such aggregation is that zero-investment observations become rare at the firm level, although the presence of plants within the region of inaction continues to influence the firm-level investment series. Interestingly, their approach identifies robust empirical predictions on firm-level investment dynamics, which can be recovered after aggregation across multiple capital inputs as well as production plants within a firm.

Bloom, Bond, and Van Reenen (2003) emphasize the following predictions about firm-level investment, which are tested in our study. First, in the short run, firms facing a higher level of uncertainty should respond less following a given demand shock, because, according to this theoretical framework, higher uncertainty widens the region of inaction relevant for each investment decision. This captures the intuition that firms may have a greater incentive to adopt a more cautious policy and wait for the arrival of new information before implementing their investment projects and exercising real options. In addition, they note that there should also be a nonlinear effect of demand shocks on investment spending in a setting in which firms invest at multiple plants or in multiple lines of capital. Typically, following a positive demand shock, the line of capital closest to the investment threshold starts adjusting, thus increasing the marginal productivity of the other lines of capital if one assumes supermodularity in...

NOTE: All illustrations and photos have been removed from this article.



Looking for additional articles?
Search our database of over 3 million articles.

Looking for more in-depth information on this industry?
Search our complete database of Industry & Market reports by text, subject, publication name or publication date.

About Goliath
Whether you're looking for sales prospects, competitive information, company analysis or best practices in managing your organization, Goliath can help you meet your business needs.

Our extensive business information databases empower business professionals with both the breadth and depth of credible, authoritative information they need to support their business goals. Whether it be strategic planning, sales prospecting, company research or defining management best practices - Goliath is your leading source for accurate information.