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    • The response to this problem has

    2018-10-30

    The response to this problem has been mixed in the literature, ranging from the development of alternative proxies that can better capture investment opportunities to a change in methodology that abandons the necessity of using Tobin’s Q. For the first approach, prospect of future expense in capital goods is used to complement information in Tobin’s Q in order to capture the internal view of opportunities (Carpenter and Guariglia, 2008), or more aggregate variables are used in this regard, as industry-level value-added growth when data glutamate transporter contains firms not traded publicly (Guariglia et al., 2011). For the second, it is better exemplified by the “Euler equation approach” to the problem, where one tests if the firms’ investment behavior is consistent with the first-order condition that may prevail when they solve a dynamic programming problem under perfect markets (Bond and Meghir, 1994). Although many of these proposed solutions may be ingenious, finding a proper control is a challenging task. Most studies are subject to the criticism that a statistically positive correlation between cash flow and investment may reflect mismeasured investment opportunities. Another challenge to this literature is given by how to classify firms with regards to to levels of information costs. In an influential paper, Kaplan and Zingales (1997) argued that theoretically the relation between the dependence of investments to internal funds and information costs was not necessarily monotonic. They reviewed the seminal article of FHP, and splitting their low dividend payment sample with respect to the probability of liquidity need, they showed that the relation between cash flow and investment was weaker in firms facing liquidity constraints, which was a contradiction to the hypothesis sustained by FHP. Moreover, KZ raised an interesting insight regarding whether this result is at odds in the literature, because the financial criteria used to classify firms according to their level of credit restriction in main papers may not correspond to the real information cost and hence effective credit constraints faced by these firms. For instance, firms linked to a bank (conglomerates) may be less credit constrained under an adverse selection story since “lemons risk” limits access to capital markets to those not linked to the conglomerates. KZ paper was the origin of a huge controversy in this literature, with some authors reaffirming KZ findings (Cleary, 1999) while others criticizing their approach (for instance, Hubbard (1998) or Allayannis and Mozumdar, 2004). One of the main arguments against KZ is that firms classified as most prone to suffer illiquidity are in general financially distressed, where creditors may seize their new generated funds as repayment for old debts, weakening in this way the relationship cash flow to investment. Beyond this controversy, a point that must warn researchers refers to the proper classification of firms by categories that really measure information costs. In fact, Cleary et al. (2007) argues that the sensitivity of cash flow to investment between firms with more or less financial restriction depends crucially on what variables are used to classify firms as credit constrained. Terra (2003) is one of the main references in the Brazilian literature. More recently, we can cite the work of Aldrighi and Bisinha (2010). The general conclusion of these authors is that Brazilian firms are indeed credit-constrained. However, at odds with the conventional literature, firms that should be more credit constrained when using some standard measure (size, for instance) do not appear to have a more significant coefficient in the investment — cash flow equation. In Terra (2003), the hypothesis that the cash flow coefficient is equal for large and small firms cannot be rejected, unless in a limited period of time (1994–1997) when credit constraints were softer among large firms. In Aldrighi and Bisinha (2010), the cash flow coefficient is always significant, and indeed increases with firm size. The authors suggest that financial difficulties between firms with smaller size may explain their findings, as the desire to maintain a “financial slack”, avoiding in this way future liquidity problems, may weaken the investment – cash flow relationship.