The 50 reference contexts in paper Christopher F. Baum, Mustafa Caglayan, Oleksandr Talavera (2006) “On the Sensitivity of Firms' Investment to Cash Flow and Uncertainty” / RePEc:boc:bocoec:638

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    We specifically consider the effects of three different forms of uncertainty on firms’ cost of external funds, and thus on their investment behavior:Own (intrinsic) uncertainty, derived from firms’ stock returns;M arket(extrinsic) 1See
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    Hartman (1972), Abel (1983), Bernanke (1983), Craine (1989), Dixit and Pindyck (1994), Caballero (1999).
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    2 uncertainty, driven by S&P 500 index returns,2and the relations between intrinsic and extrinsic uncertainty. To capture the latter effect, we introduce acovarianceterm (ourCAPM-based risk measure) and allow the data to determine the differential impact of each of these components on the firm’s capital investment behavior.
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    We employ annual firm-level U.S. manufacturing sector data obtained fromCOMPUSTATand match it to firm-level daily financial data fromCRSP over the 1984–2003 period. Daily stock returns and market index returns are utilized to compute intrinsic and extrinsic uncertainty via a method based on
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    Merton (1980)
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    from the intra-annual variations in stock returns and aggregate financial market series. This approach provides a more representative measure of the perceived volatility while avoiding potential problems: for instance, the high persistence of shocks or low correlation in volatility.
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    In that respect, our study improves upon much of the literature in its method of using high-frequency data to quantify volatility evaluated at a lower frequency.3 The results of the paper can be summarized as follows. In contrast to earlier research such as
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    Leahy and Whited (1996),
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    we find a significant role for each uncertainty measure while factors such as cash flow and the debt ratio maintain their significance in explaining firm investment behavior.4 Our empirical model evaluates how the effects of uncertainty on investment may be strengthened or weakened by the firm’s current financial condition.
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    Furthermore, its effects through cash flow, along with those of intrinsic uncertainty, are significant but vary in sign over the range of cash flow values. Interestingly, we find that while 2In this paper we use the termsOwn, idiosyncratic and intrinsic uncertainty interchangeably. Likewise,Marketis taken as synonymous with extrinsic uncertainty. 3
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    Leahy and Whited (1996),
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    Bloom, Bond and Van Reenen (2007), Bond and Cummins (2004) have also utilized daily stock returns to compute firm-level uncertainty. However, the methodology they used to generate a proxy for uncertainty is different from ours. 4An exception are the findings of Baum, Caglayan and Talavera (2008), which also display a significant role for similar measures of uncertainty.
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    Interestingly, we find that while 2In this paper we use the termsOwn, idiosyncratic and intrinsic uncertainty interchangeably. Likewise,Marketis taken as synonymous with extrinsic uncertainty. 3Leahy and Whited (1996), Bloom, Bond and Van Reenen (2007),
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    Bond and Cummins (2004)
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    have also utilized daily stock returns to compute firm-level uncertainty. However, the methodology they used to generate a proxy for uncertainty is different from ours. 4An exception are the findings of Baum, Caglayan and Talavera (2008), which also display a significant role for similar measures of uncertainty.
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    Likewise,Marketis taken as synonymous with extrinsic uncertainty. 3Leahy and Whited (1996), Bloom, Bond and Van Reenen (2007), Bond and Cummins (2004) have also utilized daily stock returns to compute firm-level uncertainty. However, the methodology they used to generate a proxy for uncertainty is different from ours. 4An exception are the findings of
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    Baum, Caglayan and Talavera (2008),
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    which also display a significant role for similar measures of uncertainty. However, their analysis does not consider interactions of uncertainty with cash flow. 3 the effects ofOwnuncertainty through cash flows on firms’ fixed investment is positive, that ofMarketuncertainty is negative.
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    However, their analysis does not consider interactions of uncertainty with cash flow. 3 the effects ofOwnuncertainty through cash flows on firms’ fixed investment is positive, that ofMarketuncertainty is negative. In contrast to those of
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    Bloom et al. (2007),
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    our findings suggest that (although the two models differ) different types of uncertainty can enhance or impair fixed investment by themselves or through cash flow, potentially clouding the relationship between investment and uncertainty (Boyle and Guthrie (2003)).
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    In contrast to those of Bloom et al. (2007), our findings suggest that (although the two models differ) different types of uncertainty can enhance or impair fixed investment by themselves or through cash flow, potentially clouding the relationship between investment and uncertainty
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    (Boyle and Guthrie (2003)).
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    We also show that the impact of cash flow on capital investment changes as the underlying uncertainty varies. The rest of the paper is constructed as follows. Section 2, though not comprehensive given the vast literature on capital investment, provides a brief survey of the empirical literature discussing the effects of uncertainty on investment.
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    Fluctuations in aggregate investment can arise from various sources of uncertainty. For instance, many researchers have studied the impact of exchange rate uncertainty on aggregate or industry level investment behavior. To that end
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    Goldberg (1993)
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    shows that exchange rate uncertainty has a weak negative effect on investment spending. Campa and Goldberg (1995) find no significant impact of exchange rate volatility on investment. Darby, Hallett, Ireland and Piscatelli (1999) provide evidence that exchange rate uncertainty may or may not depress investment, while Serven (2003) unearths a highly significant negative impact of real exchange rate
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    For instance, many researchers have studied the impact of exchange rate uncertainty on aggregate or industry level investment behavior. To that end Goldberg (1993) shows that exchange rate uncertainty has a weak negative effect on investment spending.
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    Campa and Goldberg (1995)
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    find no significant impact of exchange rate volatility on investment. Darby, Hallett, Ireland and Piscatelli (1999) provide evidence that exchange rate uncertainty may or may not depress investment, while Serven (2003) unearths a highly significant negative impact of real exchange rate uncertainty on private investment in a sample of developing countries.
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    To that end Goldberg (1993) shows that exchange rate uncertainty has a weak negative effect on investment spending. Campa and Goldberg (1995) find no significant impact of exchange rate volatility on investment.
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    Darby, Hallett, Ireland and Piscatelli (1999)
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    provide evidence that exchange rate uncertainty may or may not depress investment, while Serven (2003) unearths a highly significant negative impact of real exchange rate uncertainty on private investment in a sample of developing countries.
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    Campa and Goldberg (1995) find no significant impact of exchange rate volatility on investment. Darby, Hallett, Ireland and Piscatelli (1999) provide evidence that exchange rate uncertainty may or may not depress investment, while
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    Serven (2003)
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    unearths a highly significant negative impact of real exchange rate uncertainty on private investment in a sample of developing countries. Many other researchers have investigated the importance of uncertainty arising from output, prices (inflation), taxes and interest rates.
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    Piscatelli (1999) provide evidence that exchange rate uncertainty may or may not depress investment, while Serven (2003) unearths a highly significant negative impact of real exchange rate uncertainty on private investment in a sample of developing countries. Many other researchers have investigated the importance of uncertainty arising from output, prices (inflation), taxes and interest rates.
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    Driver and Moreton (1991)
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    conclude that while a proxy for uncertainty driven from 4 output growth has a negative long–run effect on aggregate investment, the measure of uncertainty obtained from inflation has none. Calcagnini and Saltari (2000) suggest that while demand uncertainty has a significant negative effect on investment, interest rate uncertainty has none.
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    Driver and Moreton (1991) conclude that while a proxy for uncertainty driven from 4 output growth has a negative long–run effect on aggregate investment, the measure of uncertainty obtained from inflation has none.
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    Calcagnini and Saltari (2000)
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    suggest that while demand uncertainty has a significant negative effect on investment, interest rate uncertainty has none. Huizinga (1993) reports a negative effect on investment for uncertainty proxies obtained from wages and raw materials prices, but a positive effect for a proxy obtained from output prices.
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    Driver and Moreton (1991) conclude that while a proxy for uncertainty driven from 4 output growth has a negative long–run effect on aggregate investment, the measure of uncertainty obtained from inflation has none. Calcagnini and Saltari (2000) suggest that while demand uncertainty has a significant negative effect on investment, interest rate uncertainty has none.
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    Huizinga (1993)
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    reports a negative effect on investment for uncertainty proxies obtained from wages and raw materials prices, but a positive effect for a proxy obtained from output prices. Ferderer (1993) captures a measure of uncertainty on long term bonds using the term structure of interest rates and finds a negative impact on aggregate investment.
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    Calcagnini and Saltari (2000) suggest that while demand uncertainty has a significant negative effect on investment, interest rate uncertainty has none. Huizinga (1993) reports a negative effect on investment for uncertainty proxies obtained from wages and raw materials prices, but a positive effect for a proxy obtained from output prices.
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    Ferderer (1993)
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    captures a measure of uncertainty on long term bonds using the term structure of interest rates and finds a negative impact on aggregate investment. Hurn and Wright (1994) find that the linkage between oil price variability and the decision to develop an oil field (more specifically the North Sea oil field) is not significant.
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    Huizinga (1993) reports a negative effect on investment for uncertainty proxies obtained from wages and raw materials prices, but a positive effect for a proxy obtained from output prices. Ferderer (1993) captures a measure of uncertainty on long term bonds using the term structure of interest rates and finds a negative impact on aggregate investment.
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    Hurn and Wright (1994)
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    find that the linkage between oil price variability and the decision to develop an oil field (more specifically the North Sea oil field) is not significant. Pindyck and Solimano (1993) use the variance in the marginal revenue product of capital as a proxy for uncertainty to study an implication of irreversible investment models to find the effects of uncertainty on the investment trigger.
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    Ferderer (1993) captures a measure of uncertainty on long term bonds using the term structure of interest rates and finds a negative impact on aggregate investment. Hurn and Wright (1994) find that the linkage between oil price variability and the decision to develop an oil field (more specifically the North Sea oil field) is not significant.
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    Pindyck and Solimano (1993)
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    use the variance in the marginal revenue product of capital as a proxy for uncertainty to study an implication of irreversible investment models to find the effects of uncertainty on the investment trigger.
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    Edmiston (2004) investigates the role of tax uncertainty on investment and finds a significant negative effect between the two.5 Turning now to research which has used firm level data, we also see several studies employing measures of uncertainty that emerge from movements in exchange rates, output, demand, firm-specific liquidity, inflation or a CAPM framework.6
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    Brainard, Shoven and Weiss (1980)
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    find that aCAPMbased risk measure yields mixed results on the linkages between investment and their uncertainty measure. Ghosal and Loungani (1996) report a negative role of output uncertainty on investment.
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    two.5 Turning now to research which has used firm level data, we also see several studies employing measures of uncertainty that emerge from movements in exchange rates, output, demand, firm-specific liquidity, inflation or a CAPM framework.6Brainard, Shoven and Weiss (1980) find that aCAPMbased risk measure yields mixed results on the linkages between investment and their uncertainty measure.
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    Ghosal and Loungani (1996)
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    report a negative role of output uncertainty on investment. Leahy and Whited (1996), using risk measures constructed from stock return data, argue that uncertainty exerts a strong negative effect on investment and point out that uncertainty affects investment directly rather than through covariances.
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    employing measures of uncertainty that emerge from movements in exchange rates, output, demand, firm-specific liquidity, inflation or a CAPM framework.6Brainard, Shoven and Weiss (1980) find that aCAPMbased risk measure yields mixed results on the linkages between investment and their uncertainty measure. Ghosal and Loungani (1996) report a negative role of output uncertainty on investment.
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    Leahy and Whited (1996),
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    using risk measures constructed from stock return data, argue that uncertainty exerts a strong negative effect on investment and point out that uncertainty affects investment directly rather than through covariances.
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    Leahy and Whited (1996), using risk measures constructed from stock return data, argue that uncertainty exerts a strong negative effect on investment and point out that uncertainty affects investment directly rather than through covariances.
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    Guiso and Parigi (1999)
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    investigate the impact of demand uncertainty using firm level data to show that uncertainty weakens the response to demand and slows down capital accumulation. Minton and Schrand (1999) find evidence that cash flow volatility is costly and leads to lower levels of investment in 5See Edmiston (2004) for other studies that concentrate on the linkages between investment and volatility in taxes. 6Some
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    risk measures constructed from stock return data, argue that uncertainty exerts a strong negative effect on investment and point out that uncertainty affects investment directly rather than through covariances. Guiso and Parigi (1999) investigate the impact of demand uncertainty using firm level data to show that uncertainty weakens the response to demand and slows down capital accumulation.
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    Minton and Schrand (1999)
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    find evidence that cash flow volatility is costly and leads to lower levels of investment in 5See Edmiston (2004) for other studies that concentrate on the linkages between investment and volatility in taxes. 6Some researchers have studied the extent to which a proxy for analysts’ forecasts can explain firms’ investment behavior; see among others Abel and Eberly (2002). 5 capital expenditures, R&D
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    Guiso and Parigi (1999) investigate the impact of demand uncertainty using firm level data to show that uncertainty weakens the response to demand and slows down capital accumulation. Minton and Schrand (1999) find evidence that cash flow volatility is costly and leads to lower levels of investment in 5See
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    Edmiston (2004)
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    for other studies that concentrate on the linkages between investment and volatility in taxes. 6Some researchers have studied the extent to which a proxy for analysts’ forecasts can explain firms’ investment behavior; see among others Abel and Eberly (2002). 5 capital expenditures, R&D and advertising.
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    Minton and Schrand (1999) find evidence that cash flow volatility is costly and leads to lower levels of investment in 5See Edmiston (2004) for other studies that concentrate on the linkages between investment and volatility in taxes. 6Some researchers have studied the extent to which a proxy for analysts’ forecasts can explain firms’ investment behavior; see among others
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    Abel and Eberly (2002).
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    5 capital expenditures, R&D and advertising. Beaudry, Caglayan and Schiantarelli (2001) show that macroeconomic uncertainty captured through inflation variability has a significant effect on investment behavior of firms.
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    in taxes. 6Some researchers have studied the extent to which a proxy for analysts’ forecasts can explain firms’ investment behavior; see among others Abel and Eberly (2002). 5 capital expenditures, R&D and advertising. Beaudry, Caglayan and Schiantarelli (2001) show that macroeconomic uncertainty captured through inflation variability has a significant effect on investment behavior of firms.
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    Bloom et al. (2007)
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    suggest that higher uncertainty renders firms more cautious and reduces the effects of demand shocks on investment. Boyle and Guthrie (2003) argue that offsetting effects of payoff and financing uncertainty must be distinguished in order to accurately gauge their effects on investment.
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    Beaudry, Caglayan and Schiantarelli (2001) show that macroeconomic uncertainty captured through inflation variability has a significant effect on investment behavior of firms. Bloom et al. (2007) suggest that higher uncertainty renders firms more cautious and reduces the effects of demand shocks on investment.
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    Boyle and Guthrie (2003)
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    argue that offsetting effects of payoff and financing uncertainty must be distinguished in order to accurately gauge their effects on investment. Although these studies summarized above have examined various aspects of the linkages between uncertainty and investment, none of them have entertained the impact of intrinsic or extrinsic uncertainty and aCAPM-based risk measure in a regression model.
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    the analytical model used to link uncertainty faced by the firm to its choice of an optimal investment plan as well as the method that we use to obtain our proxies for uncertainty. 3 An extendedQmodel of firm value optimization The theoretical model proposed in this paper is based on the firm value optimization problem and represents a generalization of the standardQ models of investment by
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    Blundell, Bond, Devereux and Schiantarelli (1992).
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    The present value of the firm is equated to the expected discounted stream ofDt, dividends paid to shareholders, where 0< ρ <1 is the constant one-period discount factor: Vt= maxEt [∞ ∑ s=0 ρsDt+s ] .(1) At timet, all present values are known with certainty while all future variables are stochastic.
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    proxies of financial health.7Finally, the firm faces the transversality condition which prevents the firm from borrowing an infinite amount and paying it out as dividends: lim T→∞   T−1∏ j=t ρj  BT= 0,∀t.(5) The first order conditions of this maximization problem for investment, capital and debt are ∂Ct ∂It + 1 =λt,(6) ∂Πt − ∂Ct ∂Kt =λt−(1−δ)ρEtλt+1,(7) ∂Kt Et[ρRt+1] = 1 +μt,(8) 7See
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    Hubbard, Kashyap and Whited (1995)
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    for a similar modeling strategy. 7 where the Lagrange multipliersλtandμtrepresent the shadow prices associated with the capital accumulation and the borrowing constraint, respectively. Equation (6) sets the marginal cost associated with an additional unit of investment equal to its shadow price.
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    This term equals zero when the shadow price of external finance is equal to zero,μt=μt+i= 0∀i. We define averageQas Qt=Vt/Kt−1and the leverage ratio asBt/Kt−1. For the unlevered firm marginal q is equal to average Q in the case of no borrowing constraint.8 Similar to
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    Love (2003),
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    we assume that adjustment costs are quadratic and take the form C(It, Kt, ε) = b 2 [( It Kt ) −g ( It−1 Kt−1 ) −a+εt ]2 Kt.(11) To obtain an investment equation, we rewrite the first order condition (6) making use of the functional form of adjustment costs: It Kt =a− 1 b +g It−1 Kt−1 + 1 b(1−δ) Qt− Rt b(1−δ) Bt Kt−1 − 1 b Θt Kt−1 .(12) 8Hennessy (2004) obtains a similar result in which averageQove
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    case of no borrowing constraint.8 Similar to Love (2003), we assume that adjustment costs are quadratic and take the form C(It, Kt, ε) = b 2 [( It Kt ) −g ( It−1 Kt−1 ) −a+εt ]2 Kt.(11) To obtain an investment equation, we rewrite the first order condition (6) making use of the functional form of adjustment costs: It Kt =a− 1 b +g It−1 Kt−1 + 1 b(1−δ) Qt− Rt b(1−δ) Bt Kt−1 − 1 b Θt Kt−1 .(12) 8
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    Hennessy (2004)
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    obtains a similar result in which averageQoverstates marginalqby incorporating post-default returns to investment. 8 The last term in Equation (12) captures the role of financial frictions in the firm’s capital investment behavior.
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    of these sources would be operational when lenders evaluate the firm’s creditworthiness, we believe that use of firm-specific daily returns can provide us with a single proxy which embodies all potential sources of uncertainty relevant to the firm. Furthermore, using intrinsic and extrinsic uncertainty in our regressions we can determine whether investment behavior is more 9See, for example,
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    Almeida, Campello and Weisbach (2004).
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    10For instance, see Bloom et al. (2007) for a discussion of similar issues. 11Θt/Kt−1is a function of uncertainty and liquidity, evaluated as the ratio of cash flow to the lagged capital stock. We apply a first-order Taylor expansion to those factors to derive this expression. 12We explain how these measures are constructed using daily data in section 3.1. 9 sensitive to own- or market-specific un
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    Furthermore, using intrinsic and extrinsic uncertainty in our regressions we can determine whether investment behavior is more 9See, for example, Almeida, Campello and Weisbach (2004). 10For instance, see
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    Bloom et al. (2007)
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    for a discussion of similar issues. 11Θt/Kt−1is a function of uncertainty and liquidity, evaluated as the ratio of cash flow to the lagged capital stock. We apply a first-order Taylor expansion to those factors to derive this expression. 12We explain how these measures are constructed using daily data in section 3.1. 9 sensitive to own- or market-specific uncertainty.
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    The beginning of period averageQis defined as the market value of the firm (shares plus debt) net of the value of current assets (inventories and financial assets) divided by the replacement value of the firm’s capital stock, imputed by the method of
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    Salinger and Summers (1983).
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    13Finally, Iis investment,CFdenotes cash flow andBis the firm’s debt. All terms are deflated by the consumer price index taking into account the timing of the variables appearing in the numerator and denominator.
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    We also anticipate that the cash flow sensitivity of investment should increase in the presence of heightened uncertainty as captured through the interaction terms. 13This methodology was also employed by
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    Leahy and Whited (1996).
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    10 To summarize, our model contains three of the basic elements,Q, cash flow and leverage, which have been shown to explain the investment behavior of firms, along with three different measures of uncertainty.
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    , by themselves and interacted with a measure of the firm’s liquidity, we can determine whether investment behavior is more sensitive toOwn- orM arket-specific uncertainty while the covariance term helps us evaluate the predictions arising from theCAPM. The interaction terms in the model allow us to examine whether uncertainty makes managers more cautious in their investment decisions as
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    Bloom et al. (2007)
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    claim. 3.1 Generating volatility measures from daily data Any attempt to evaluate the effects of uncertainty on the firm investment behavior requires specification of a measure of risk. The empirical literature offers a number of competing approaches for the construction of volatility measures.
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    Furthermore, a proxy for uncertainty obtained from aGARCHspecification will be dependent on the choice of the model and exhibit significant variation over alternatives. In this study, we utilize daily stock returns and market index returns to compute intrinsic and extrinsic uncertainty via a method based on
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    Merton (1980)
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    from the intra-annual variations in stock returns and aggregate financial market series.14This approach provides a more representative measure 14See Baum, Caglayan and Ozkan (2004) for a more detailed discussion of the procedure 11 of the perceived volatility while avoiding potential problems raised above.
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    In this study, we utilize daily stock returns and market index returns to compute intrinsic and extrinsic uncertainty via a method based on Merton (1980) from the intra-annual variations in stock returns and aggregate financial market series.14This approach provides a more representative measure 14See
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    Baum, Caglayan and Ozkan (2004)
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    for a more detailed discussion of the procedure 11 of the perceived volatility while avoiding potential problems raised above. Also the use of daily returns on the stock provides one with a forward-looking proxy for the volatility of the firms’ environment.
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    If data were generated every calendar day, ∆φt= 1,∀t,but given that data are not available on weekends and holidays, ∆φt∈(1,5).The estimated annual volatility of the return series is defined as Φt[xt] = √∑ T t=1ς d twhere the time index for Φt[xt] is at the annual frequency. An alternative to Merton’s procedure (which makes use of squared highfrequency returns) is that proposed by
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    Ghysels, Santa-Clara and Valkanov (2006)
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    : the computation of realized absolute variation and bipower variation, which make use of absolute returns. We generate these measures from the firm-level daily data, and find that when aggregated to the annual frequency they were correlated above 0.93 with our Merton-based proxy.
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    on the S&P 500 index, inclusive of dividends. 4 Empirical findings 4.1 Data The estimation sample consists of an unbalanced panel of manufacturing firms for the 1984 to 2003 period drawn from Standard and Poor’s Industrial along with its merits. 12 AnnualCOMPUSTATdatabase.15There are 9,895 firm-years for which the replacement value of the real capital stock may be imputed by the method of
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    Salinger and Summers (1983).
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    A number of sample selection criteria are then applied. We only consider firms which have not undergone substantial changes in their composition during the sample period (e.g., participation in a merger, acquisition or substantial divestment).
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    The screened data are used to reduce the potential impact of outliers upon the parameter estimates. 13 4.2 The link between uncertainty and capital investment In what follows we present our results in Table 2 obtained using the dynamic panel data (DPD) approach developed by
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    Arellano and Bond (1991),
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    as implemented in Stata by Roodman (2007). All models are estimated in first difference terms to eliminate unobserved heterogeneity using the one-step GMMestimator on an unbalanced panel from a sample including 402 firms’ annual data.
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    The screened data are used to reduce the potential impact of outliers upon the parameter estimates. 13 4.2 The link between uncertainty and capital investment In what follows we present our results in Table 2 obtained using the dynamic panel data (DPD) approach developed by Arellano and Bond (1991), as implemented in Stata by
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    Roodman (2007).
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    All models are estimated in first difference terms to eliminate unobserved heterogeneity using the one-step GMMestimator on an unbalanced panel from a sample including 402 firms’ annual data. In column one, we start our investigation estimating a standard investment model which includes the basic explanatory variables for firm level investment (Q,CFt/Kt−1andBt−1/Kt−2) along with the lagged depende
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    use of suitably lagged endogenous variables as instruments.17In this model, neitherQnor the cash flow/assets ratio appear significant, but the lagged measure of intrinsic uncertainty has a negative and highly significant coefficient, while the interaction of the cash flow ratio with intrinsic uncertainty possesses a positive, significant coefficient estimate. This is an interesting finding as
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    Leahy and Whited (1996)
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    report that uncertainty affects investment behavior through Q(in their analysis the coefficient on their proxy for uncertainty becomes insignificant with the introduction ofQ). In our case, even in the presence ofQ(although insignificant), intrinsic uncertainty significantly affects the firm’s fixed investment behavior, not only on its own but through the interaction with cash flow.18 17The secon
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    ), intrinsic uncertainty significantly affects the firm’s fixed investment behavior, not only on its own but through the interaction with cash flow.18 17The second through fourth lags of (It−1/Kt−2),Qt, (CFt/Kt−1), (Bt/Kt−1) and lagged uncertainty measures are employed asGMMinstruments. 18The sceptical reader may be concerned about the possibility that Q may be measured with error (See
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    Erickson and Whited (2000)). To
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    dispel concerns that the use of lagged variables as instruments may not overcome an issue of Q mismeasurement, we tested the model by replacing Q with the ratio of (I/Kt+1+I/Kt+2)/(2I/Kt), following the approach taken in Almeida et al. (2004).
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    To dispel concerns that the use of lagged variables as instruments may not overcome an issue of Q mismeasurement, we tested the model by replacing Q with the ratio of (I/Kt+1+I/Kt+2)/(2I/Kt), following the approach taken in
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    Almeida et al. (2004).
    Suffix
    With that change made, the qualitative findings of Table 2 are virtually unchanged. The uncertainty proxies and interactions retain their significance, even though this “perfect foresight” approach yields highly significant coefficients on the alternative measure.
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  46. Start
    31694
    Prefix
    In contrast,extrinsic uncertainty has a significant negative coefficient on the interaction term: an increase in market-based uncertainty decreases the incentive to invest at any level of cash flow. Perhaps this finding suggests cautious behavior of managers as in
    Exact
    Bloom et al. (2007)
    Suffix
    when uncertainty increases. Finally, we observe that both the main effect and the indirect effect through theCAPMbased uncertainty term are significant. While the direct effect is negative, the indirect effect is positive.
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  47. Start
    32377
    Prefix
    Taking all effects into account, the firm’s rate of investment becomes more sensitive to available cash flow with an increase in uncertainty. Q is not seriously biasing our findings. 15 This result, supporting the implications ofCAPMtheory, is quite interesting and stands in clear contrast to the findings reported by
    Exact
    Leahy and Whited (1996)
    Suffix
    (although their model did not incorporate an interaction with cash flow). In the model of column five, the cash flow ratio and debt ratio play important roles in conjunction with uncertainty while Tobin’sQis generally insignificant.
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  48. Start
    33017
    Prefix
    The overall cash flow sensitivity of investment is an increasing function of uncertainty except forMarket(extrinsic) uncertainty. WhenMarketuncertainty increases, the impact of cash flow is reduced. This can be explained in the light of the findings of
    Exact
    Beaudry et al. (2001),
    Suffix
    who show that an increase in macroeconomic uncertainty would lead to a negative impact on firms’ investment behavior as firm managers will not be able to readily distinguish good from bad investment projects.
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  49. Start
    34099
    Prefix
    Even a casual inspection of these derivatives shows that the role of uncertainty on firm investment is not trivial, and varies considerably across types of uncertainty, in line with arguments put forth by
    Exact
    Boyle and Guthrie (2003).
    Suffix
    20In particular, one can see that an increase in the firm-level (η) uncertainty measure leads to an increase in 19Tables of numerical values underlying the graphs are available from the authors upon request. 20“. . . any attempt to empirically identify the relationship between uncertainty and investment will pick up offsetting uncertainty effects unless the exact nature of the uncertainty is caref
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  50. Start
    37251
    Prefix
    We specifically concentrate on the role of firm-specific (intrinsic), market-specific (extrinsic) andCAPM-based measures of uncertainty on firms’ investment spending in that relationship, allowing for interactions with cash flow. Both idiosyncratic and market uncertainty measures are constructed using a method based on
    Exact
    Merton (1980)
    Suffix
    from the intra-annual variations in stock returns using firm level stock prices and S&P 500 index returns. Employing annual data obtained fromCOMPUSTATfor manufacturing firms over the period between 1984–2003 we then investigate the linkages between investment, cash flow and uncertainty.
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