Financial Constraint, Liquidity Management and Investment

Financial Constraint, Liquidity Management and Investment * Timothy J Riddiough School of Business University of Wisconsin-Madison triddiough@bus.wisc.edu Zhonghua Wu School of Business Florida International University wuz@fiu.edu This Draft: November 2007 Abstract Investment and liquidity management are analyzed in a sector where firms are exogenously cash flow constrained Across the entire sector, we find high investment sensitivity to both q and measures of financial market frictions Liquidity is managed through cash retention (dividend) policy and access to short-term bank finance, in which bank line of credit smoothes variation in available cash flow and accelerates investment We show that cash flow constraint is not equivalent to financial constraint, where more (less) financially constrained firms in our sample exhibit high (low) investment and liquidity management sensitivity to variables that measure financial market frictions Empirical results provide support for debt overhang, free cash flow and asset tangibility as important financial market frictions that influence investment outcomes We thank David T Brown, Jim Clayton, Morris Davis, Piet Eiccholtz, Erasmo Giambona, Don Hausch, Franỗois Ortalo-Magnộ, Steve Malpezzi, Armin Schwienbacher, James Seward, David Shulman, Ko Wang, Toni Whited and seminar participants at Baruch College, University of Amsterdam, University of Wisconsin-Madison, and the 2006 ASSA meetings for helpful comments We gratefully acknowledge the Puelicher Center for Banking Education at University of Wisconsin-Madison for its financial support * Financial Constraint, Liquidity Management and Investment Introduction Fazzari, Hubbard, and Petersen (1988) convincingly argue that internal versus external sources of finance are imperfect substitutes in the context of funding investment, and hence that financial constraints impede the efficient allocation of resources Their study has had wide impact, and has come under intense scrutiny Critics, beginning with panelists that provided comments and discussion published alongside the original Brookings paper, have generally focused on three instrumental issues: i) endogeneity of financial constraint proxies; ii) measurement error in Tobin’s q; and iii) omitted variables and channels that provide more complete information about the link between financial market frictions and real investment outcomes Chirinko (1993) concisely summarizes these concerns by stating, “It is unclear whether significant liquidity and net worth variables are capturing a structural element heretofore missing in the investment equation or are merely reflecting a general misspecification.” Previous studies have addressed one or two of these instrumental issues at a time, but none have addressed all three in a systematic and comprehensive manner For example, Whited (1992) and Kaplan and Zingales (1997) primarily address the financial constraint issue, while Erickson and Whited (2000) focus on measurement error in q and Almeida, Campello and Weisbach (2004) emphasize the link between cash flow sensitivity of cash holdings and financial constraint The intent of this study is to address all three issues—endogeneity of financial constraint proxies, measurement error in q, and omitted variables/channels—simultaneously and comprehensively in order to provide additional perspective on the effects of financial constraint on investment decisions To address endogeneity in the financial constraint proxy and measurement error in q, we analyze a specific sector that provides an attractive natural economic laboratory: publicly traded firms that own commercial real estate assets in an investment vehicle called a Real Estate Investment Trust (REIT) These firms are regulated to pay out at least 90 percent of their GAAP net income as dividends, and most pay out at least 100 percent of GAAP net income to avoid negative tax effects This implies that the entire sector is constrained in its ability to retain cash, and therefore depends heavily on external finance to fund investment, which mitigates concerns over confounding effects in identifying constrained firms These firms also have well measured q values, due to the competitive nature of the industry and characteristics of the underlying commercial real estate assets The third instrumental issue revolves around omitted variables and resource channels We make two contributions in this regard First, we recognize that cash is not a sufficient statistic for available liquidity Firms will vary in their capacity and need to hold liquidity, and may decide to hold less internal liquidity when low-cost external sources such as bank lines of credit (L/C) exist Consequently, firms that might appear to be liquidity constrained may in fact have more than adequate stores of liquidity when external sources are recognized Second, we specify and estimate a structural model that accounts for endogeneity in cash flow retention, bank L/C usage, and investment decisions Cash flow retention and bank L/C usage together account for a firm’s liquidity management policy as related to investment, where simultaneous consideration allows us to better disentangle cause and effect as well as to better assess investment-cash flow and other sensitivities that have been a focus in the literature A unique panel data set covering the years 1990-2003 has been assembled to analyze these issues Preliminary analysis shows that REITs retain less cash flow, have a lower stock of cash, and use more bank L/C than a broad cross-section of other publicly traded firms In other words, based on these measures, REITs appear to be financially constrained We also find that REIT bank L/C usage increases monotonically with investment This suggests that, in the short run, and given their significant constraints on cash flow retention, bank L/C substitutes for internal cash in funding investment Full sample structural 3SLS estimation produces a number of noteworthy results First, in the investment equation, q and the liquidity flow measures of retained cash flow and bank L/C use all significantly affect investment, with coefficient estimates that imply high investment sensitivities Investment sensitivity to q is such that the elasticity of investment with respect to q is just shy of one, which places it near what standard q-theory would predict Given the cash flow constraints faced by REITs together with the fact that commercial real estate assets are tangible with significant debt capacity, high investment sensitivity to both retained cash flow and bank L/C use is consistent with effects of asset tangibility (Almeida and Campello (2007)) and incentives to accelerate current investment in order to create additional external financing capacity in the future (Hennesey, Levy, Whited (2007)) Across the full sample, firms are seen to invest at a rate of approximately 20 percent per year, which exceeds rates of investment by the broad cross-section of comparison industrial firms Moreover, most REITs pay well in excess of the minimum dividend payout requirement This raises the issue of whether these cash flow constrained and equity dependent firms are really financially constrained In other words, why is external finance available and affordable to these firms? We conjecture that limited discretion on cash retention mitigates adverse selection costs associated with raising outside finance This chain of reasoning implies that, contrary to conventional wisdom that emphasizes the primacy of information-based costly external finance as a premier financial market friction, cash flow constraints and equity dependence are not sufficient conditions for financial constraint To differentiate between the effects of cash flow constraint and financial constraint on investment and liquidity management, we split the sample based on Kaplan and Zingales’ (1997) methodology for indexing financial constraint Based on KZ index scores, we find the more constrained sub-sample invests less, generates lower cash flow and has a lower stock of cash, pays fewer dividends, employs more leverage, and is less likely to maintain relationships with bank lenders and security underwriters In other words, the KZ index method appears to accurately classify firms in our sample as more or less financially constrained Simultaneous equation estimation reveals substantial differences between firms that are more versus less financially constrained Consistent with arguments of Gomes (2001), the less financially constrained firms are responsive to investment signals contained in their stock prices, while the more constrained firms are not This outcome refines results of Baker, Stein and Wurgler (2003), who not differentiate equity dependent firms on the basis of financial constraint Sensitivity of investment and liquidity management to proxies for financial market frictions is generally much higher in the sub-sample of more financially constrained firms For example, cash retention policy responds to a number of variables in the financially constrained sub-sample of firms, including investment Establishing a statistically significant link between dividend policy and investment is a new result (see Fama and French (2002) for additional background), in which firms decrease their dividend payout when investment increases—presumably to redirect scarce cash flow away from shareholders towards capital acquisition Variables that cause dividend payout to increase in the more constrained sub-sample include equity issuance, a positive change in bank L/C capacity and a positive change in bank L/C use None of these variables have any effect on dividend payout in the less constrained sub-sample Stark differences between sub-samples also exist with respect to bank L/C usage An extra $1 of retained cash flow causes L/C usage to decrease by more than $1 in the more constrained subsample, whereas retained cash flow has no effect on L/C use in the sample of less constrained firms Thus, more financially constrained firms treat cash as negative short term debt by saving cash out of cash flow, whereas cash constrained but less financially constrained firms not Consistent with Sufi (2007), these results suggest that financially constrained firms closely monitor their bank L/C use due to concerns over covenant violations that would impose significant additional costs Bank L/C use is also highly responsive to investment, leverage and firm age in the more constrained sub-sample, while there is either less or no responsiveness to these effects in the less constrained sub-sample Thus, we show that cash flow constraint is not the same thing as financial constraint Subsample estimation reveals that cash flow constrained firms that are classified as financially constrained are highly responsive to shocks in variables that proxy for financial market frictions Higher cash flow results in a simultaneous paydown in bank L/C use and increase in investment, achieved in part through reduction in dividend payout Less financially constrained firms, in contrast, exhibit stability in their dividend policy with no sensitivity to investment or L/C use These findings point to the importance of agency costs over information-based costs of external finance in governing investment and liquidity management policies of financially constrained firms Our results are also generally consistent with cash flow focused liquidity management effects emphasized in Almeida et al (2004) and Almedia and Campello (2007) The paper is organized as follows Section provides further background on REITs and bank L/C usage Hypothesis development and empirical model specification are addressed in section Data are described and a preliminary analysis of the data are reported and analyzed in section Simultaneous system equation estimation for the full sample is undertaken in section 5, and sub-sample results are considered in section Section concludes the paper Further Background on REITs and Bank Lines of Credit The data employed in previous studies of corporate investment generally have limited and noisy variation One solution to the problem is to apply alternative specifications and more sophisticated econometric analysis (see, e.g., Hoshi, Kashyap and Scharfstein (1991), Erickson and Whited (2000)) A more direct solution is to try to obtain better data We emphasize the latter approach, and examine the Real Estate Investment Trust (REIT) sector The REIT sector, for several reasons, provide an attractive natural laboratory to study the effects of financial market frictions on firm investment First, all REITs are cash flow constrained by regulation, as they are required to pay at least 90 percent of taxable income to shareholders in the form of dividends.1 After accounting for the effects of depreciation and the fact that most REITs pay in excess of the minimum payout requirement, 65 to 90 percent of current cash flow is typically paid out as dividends.2 Cash flow constraints of this magnitude are typically thought to imply financially constraint due to the presumed high costs of accessing external finance Consequently, based on this logic, exogenously imposed cash flow constraints substantially reduce endogeneity problems associated with identifying financially constrained firms Combined adjustment and purchasing costs of investment should not exceed the shadow value of newly installed capital Shadow value follows from investor expectations of the marginal contributions of new capital gains to future profit In theory, marginal q provides a direct (isomorphic) measure of the shadow value of capital Marginal q is generally unobservable in the data, however, so analysts rely on average q If marginal q is badly measured by average q, an investment-cash flow relation may be a spurious, as current cash flow may contain information regarding investment opportunities Hayashi (1982) has shown that average q is a sufficient statistic for investment when the following necessary conditions are satisfied: i) there is perfect competition in factor and product markets, ii) fixed capital is homogeneous, and iii) product and adjustment costs are linearly homogeneous Commercial real estate asset markets and the firms (REITs) that own these assets satisfy these conditions to a remarkably close approximation The factor market is primarily land and physical capital, with relatively little reliance on human capital, and these markets are generally quite competitive Competitive market structure is important, since imperfectly competitive industries will generate quasi-rents that can cause a spurious correlation between cash flow and investment after controlling for average q (Abel and Eberly (2001), Cooper and Ejarque (2003)) Prior to 2000, the dividend payout requirement was 95 percent REITs that pay out less than 100 percent of net income incur an excise tax on the difference, which causes most to pay at least 100 percent of net income The average payout in our data and in other studies is approximately 120 percent of net income (see also Chan et al (2003)) The annual flow of depreciation expense (a non-cash item) is generally between two and three percent of the asset’s initial book value, which equates to between 25 and 40 percent of net operating income A large proportion of real estate asset operating expenses go to pay utilities, insurance and property taxes, which are effectively linear in scale Investment, which in this sector is primarily the acquisition of built (productive) assets, results in adjustment costs that are linearly homogeneous Furthermore, investment in built assets requires very little “time-to-build”, and also contain little option value that potentially distorts the marginal-average q relation In addition, regulation requires REITs to be monoline (non-integrated) companies This suggests that imperfect product substitution that confounds many multi-product firms is less problematic with REITs, which strengthens the link between average and marginal q.3 Finally, there are no taxes at the entity level to distort investment incentives Compounding the usual marginal q–average q measurement error problem is that average q is often badly measured in the data due the reliance on asset book values to proxy for the replacement cost of firm assets As Hartzell, Sun, and Titman (2006) and others have pointed out, however, book asset value is a relatively accurate measure of replacement cost with commercial real estate assets For example, they report a correlation of 92 between their book asset measure of q and a net asset value measure of q that is based on market sales data To begin to get a sense of the data, Figure shows how average q varies by year for REITs in our sample, where q is defined as market value of equity plus book value of debt divided by asset book value as of the beginning of the year Quartile cutoff values are displayed in addition to mean values Mean and median q values generally exceed 1.0 over the sample period, but not by a large amount It is also apparent that there is significant cross-sectional variation in q values in the early years of the sample period (particularly in 1992 and 1993), whereas this variation decreases after 1994 Figure Here See Hayashi and Inoue (1991) for more on the issue of imperfect asset substitution and investment In Figure the time-series of average q and rates of investment by year as a percentage of year-beginning asset value are displayed There is a clear direct contemporaneous relation between investment and average q, with cross-correlation measured at 78 Note that investment is in the 10 percent range for most years, but that the years 1995-98 resulted in higher rates of investment that generally exceeded 20 percent of year-beginning book assets Figure Here In their analysis of the REIT sector, Ott, et al (2005) document that only seven percent of firm-level investment was funded by retained cash earnings, as compared to 70 percent for other publicly traded firms Because of their inability to retain cash, REITs rely on outside financing sources to facilitate investment Seasoned equity, long-term unsecured debt, and secured mortgage debt are the claims typically issued to permanently finance acquisitions (see Brown and Riddiough (2003) for additional background) In the short term, REITs rely heavily on bank lines of credit (L/C) to fund investment 4,5 The typical funding cycle is as follows A firm identifies an investment opportunity, which often requires partial or full payment at closing Anticipating these investment opportunities, the firm arranges a bank L/C with sufficient capacity to meet its liquidity needs The bank L/C is drawn down to fund the investment, where the firm subsequently begins to work with an investment or commercial bank to secure permanent sources of finance Once there is sufficient scale, equity or We have explored whether REITs utilize the commercial paper market, and have found no evidence that they This is because REITs are generally younger firms without the AAA and AA credit ratings required to access this market The ratings outcomes are in significant part because REITs are unable to retain cash flow Thus, it appears that firms which have access to the commercial paper market are the larger, more mature firms that are able to retain cash— precisely the type of firms that are not likely to be financially constrained In contrast, REITs, which are by definition cash constrained, almost exclusivily rely on bank L/C for external-source liquidity needs Bank L/C account for a large proportion of total firm-level bank debt in the U.S A recent Federal Reserve Board survey reports that approximately 80 percent of commercial and industrial loans made by banks are arranged as shortterm bank loan commitments or lines of credit According to Martin and Santomero (1987) and Avery and Berger (1991), the primary stated reasons why firms use bank L/C are financial flexibility and speed of action In practice, firms that are short on cash often use bank L/C to meet their immediate liquidity needs See Sufi (2007) for further detail on the structure of bank lines of credit long-term debt is issued with proceeds used to pay down bank L/C and hence recreate capacity to fund the next round of acquisitions Table compares REITs to other publicly traded firms (C-Corporations) that are not subject to dividend payout requirements We show how five ratios vary and compare by year from 1990 to 2003 The five ratios, all as a percentage of beginning-year total book assets (K), are net investment (INV), dividends paid (DIV), net cash flow (NCF), the stock of cash and liquid securities (CS), and bank L/C capacity (L/C) We also report how investment correlates with the other reported variables over the sample period Table Here Observe the high rates of investment by REITs in the middle 1990s, and that average investment by REITs exceeded average investment by C-Corporations by almost 70 percent during the 1990-2003 sample period.6 As noted earlier, acquisitions were the largest component of net investment for REITs over the sample period, whereas capital expenditures and depreciation (a negative adjustment) were major components of net investment for C-Corporations.7 As a result of the dividend payout requirement, paid dividends are significantly higher and retained cash flow is significantly lower for REITs Interestingly, as noted earlier, a significant fraction of REITs pay dividends in excess of the minimum 90 percent of net income required by regulation Specifically, further analysis reveals that 70 percent of REITs pay at least 100 percent of the net income as dividends in any given year, with a median payout ratio of 120 percent This equates to most firms retaining between 10 and 35 percent of cash flow as deployable liquidity or an addition to cash stock Average rates of investment for REITs in this table not exactly match those reported in Figure because different data sources were used to generate the respective table and figure Real estate assets are highly durable with depreciation periods that generally exceed 30 years, whereas assets held by industrial firms typically depreciate at a much faster rate Consequently, capital expenditures are significantly higher for C-Corporations than for REITs Finally consider the L/C use equations in columns (3) and (6) Again, there are clear differences between the two sub-samples, in which more constrained firms display greater sensitivity to the system-wide effects For example, L/C use is much more sensitive to investment and net cash flow in the more constrained sub-sample This is consistent with the need of financially constrained firms to simultaneously fund investment with available liquidity as well as manage their available debt capacity to avoid costly covenant violations (Sufi (2007)) The more constrained firms are also sensitive to leverage and firm age The only variable that generates higher L/C use sensitivity among the less constrained firms is public debt issuance The interpretation of this latter result is that less constrained firms use the public debt issuance proceeds to reduce L/C use, whereas the more constrained firms are unable or unwilling to reduce their L/C use with issuance proceeds All together, our findings show that cash flow constraint is not the same thing as financial constraint All firms in our sample are cash flow constrained and equity dependent Cash flow constrained firms that experience fewer financial constraints as measured by KZ index score are highly responsive to investment signals contained in their stock prices, but are mostly unresponsive to other variables that proxy for financial market frictions—including cash flow There does appear to be interdependence between L/C usage and investment with the less constrained firms, but the effects are much less pronounced than with the more constrained firms In comparison, the more constrained firms are unresponsive to investment signals contained in their stock prices, but display extreme sensitivity in all three structural equations to a number of variables that proxy for financial market frictions Thus, firms that are equity dependent and financially unconstrained firms are sensitive to signals contained in stock prices, which refines earlier findings of Baker et al (2003) In contrast, financial market frictions overwhelm stock price signals to drive investment, cash retention and bank L/C use policies of severely constrained firms 29 Predictions contained in hypotheses through 4, which collectively state that investment, dividend policy, and L/C usage are endogenously determined and that there are significant interactions between variables, are supported by the sub-sample of more financially constrained REITs For example, more financially constrained firms pay out less cash as dividends and pay down bank L/C faster with available cash, which is consistent with precautionary saving motives identified by Almeida et al (2004) Consequently, our findings show that more financially constrained firms are more short-term focused than the less constrained firms and, in effect, take what they can get In contrast, the sub-sample of less constrained firms show a longer-term focus with less sensitivity to proxies of financial market frictions Conclusion We examine the role of liquidity management as it affects investment by cash constrained firms By employing a structural model to account for endogeneity, we find that investment and liquidity management interact in interesting and heretofore unexplored ways For example, bank lines of credit are found to smooth variation in cash flow and accelerate investment We also show that cash flow constraint is not equivalent to financial constraint, as firms that are both cash flow constrained and financially constrained behave very differently from firms that are cash flow constrained but are not financially constrained The sub-sample of more constrained firms shows high sensitivity to variables that proxy for financial market frictions, lending support for agencybased explanations of costly external finance over information-based explanations 30 References Abel and Eberly 2001 Q Theory Without Adjustment Costs and Cash Flow Effects Without Financing Constraints Unpublished Manuscript, University of Pennsylvania Almeida, Heitor and Murillo Campello 2007 Financial Constraints, Asset Tangibility, and Corporate Investment Review of Financial Studies 20, 1429-1460 Almeida, Heitor, Murillo Campello, and Michael S Weisbach 2004 The Cash Flow Sensitivity of Cash Journal of Finance 59, 1777-1804 Avery, B Robert, and Allen N Berger 1991 Loan Commitments and Bank Risk Exposure Journal of Banking and Finance 15, 173-192 Baker, Malcolm, Jeremy C Stein, and Jeffrey Wurgler 2003 When Does the Market Matter? Stock Prices and the Investment of Equity Dependent Firms Quarterly Journal of Economics 118, 9691006 Brown, David T and Timothy J Riddiough 2003 Financing Choice and Liability Structure of Real Estate Investment Trusts Real Estate Economics 31, 313-346 Chan, Su Han, John Ecrickson, Ko Wang 2003 Real Estate Investment Trusts: Structures, Performance, and Investment Opportunities Oxford University Press, New York, NY Chirinko 1993 Business Fixed Investment Spending: Modeling Strategies, Empirical Results, and Policy Implications Journal of Economic Literature 31, 1875-1911 Cooper, Russell and Joao Ejarque 2003 Financial Frictions and Investment: Requiem in q Review of Economic Dynamics 6, 710-728 Erickson, Timothy, and Toni Whited 2000 Measurement Error and the Relationship between Investment and Q Journal of Political Economy 108, 1027-1057 2005 Proxy Quality Thresholds: Theory and Applications Financial Research Letters 2, 131-151 Fama, Eugene F 1985 What’s Different about Banks? Journal of Monetary Economics 15, 29-39 Fama, Eugene F and Kenneth R French 2002 Testing Trade-off and Pecking Order Predictions about Dividends and Debt Review of Financial Studies 15, 1-33 Fazzari, M Steven, R Glenn Hubbard, and Bruce C Petersen 1988 Financing Constraints and Corporate Investment Brookings Paper on Economic Activity 141-206 Giambona, Erasmo and Armin Schwienbacher 2007 Debt Capacity of Tangible Assets: What is Collateralizable in the Debt Market? Unpublished Manuscript, University of Amsterdam Gomes, Joao F 2001 Financing Investment American Economic Review 91, 1263-1285 Ham, J.C and A Melnik 1987 Loan Demand: An Empirical Analysis Using Micro Data Review of Economics and Statistics 69, 704-709 31 Hartzell, Jay C., Libo Sun, Sheridan Titman 2006 The Effect of Corporate Governance on Investment: Evidence from Real Estate Investment Trusts Real Estate Economics 34, 343-376 Hausman 1975 An Instrumental Variable Approach to Full Information Estimators for Linear and Certain Nonlinear Econometric Models Econometrica 43, 727-738 Hayashi, Fumio 1982 Tobin’s Marginal and Average q: A Neoclassical Interpretation Econometrica 50, 213-224 Hayashi, Fumio and Tohru Inoue 1991 The Firm Growth–Q Relationship with Multiple Goods: Theory and Evidence From Panel Data on Japanese Firms Econometrica 59, 731-754 Hennessy, Christopher A., Amnon Levy, and Toni M Whited 2007 Testing Q Theory with Financing Frictions Journal of Financial Economics 83, 691-717 Hoshi, Takeo, Anil Kashyap, and David Scharfstein 1991 Corporate Structure, Liquidity, and Investment: Evidence From Japanese Industrial Groups Quarterly Journal of Economics 106, 3360 Houston, Joel, and Christopher James 2001 Do Relationship Have Limits: Banking Relationships, Financial Constraints, and Investment Journal of Business 74, 347-374 James, Christopher 1987 Some Evidence on the Uniqueness of Bank Loans Journal of Financial Economics 19, 217-235 Kaplan, Steven, and Luigi Zingales 1997 Do Financing Constraints Explain why Investment is Correlated with Cash Flow? Quarterly Journal of Economics 112, 169-215 Lamont, Owen, Christopher Polk, and Jesús Saá-Requejo 2001 Financial Constraints and Stock Returns Review of Financial Studies 14, 529-554 Lintner, John 1956 Distribution of Incomes of Corporations Among Dividends, Retained Earnings, and Taxes American Economic Review 46, 97-113 Martin, Spenser, and Anthony Santomero 1987 Investment Opportunities and Corporate Demand for Lines of Credit Journal of Banking and Finance 21, 1331-1350 Ott, Steven, Timothy J Riddiough, and Ha-Chin Yi 2005 Finance, Investment, and Investment Performance: Evidence from the REIT Sector Real Estate Economics 33, 203-235 Sufi, Amir 2007 Bank Lines of Credit in Corporate Finance: An Empirical Analysis Forthcoming, Review of Financial Studies Whited, Toni M 1992 Debt, Liquidity Constraints, and Corporate Investment: Evidence from Panel Data Journal of Finance 16, 469-478 Whited, Toni M and Guojun Wu 2006 Financial Constraints Risk Review of Financial Studies 19, 531-559 32 Figure Distribution of Tobin's Q from 1992 to 2003 This figure displays the distribution of Q values by year for firms in the sample Tobin’s Q is defined as the market-to-book ratio, i.e., (market equity + book debt) / total book assets All values are as of the beginning the year MinQ and MaxQ are the minimum and Maximum Q in a given year; P25Q and P75Q are Q at the 25 and 75 percentile; and MedianQ and MeanQ are the mean and median Q The data source is from the SNL's REIT Financial database 33 Figure Q and Investment from 1992 to 2003 This figure displays the average Q and average rate of investment by year for firms in the sample Q is defined as (market equity + book debt) / total book assets as of the beginning of the year Investment is calculated as net investment / total book assets Q is shown on the left axis and investment is shown on the right axis The data source is from the SNL's REIT Financial database 34 Table Financial Characteristics of REITs and C-Corporations REITs C-Corporations Year INV DIV NCF CS L/C INV DIV NCF CS L/C 1990 7.6 5.2 0.6 5.6 1.8 11.3 2.0 6.3 5.8 1.5 1991 4.1 4.2 0.8 3.6 4.4 13.2 1.9 5.0 5.5 1.9 1992 9.9 4.7 1.3 4.7 3.4 15.3 1.8 5.1 5.8 2.1 1993 28.5 7.3 1.2 3.9 2.8 17.4 1.8 5.1 6.2 3.1 1994 32.1 6.7 1.4 4.6 8.2 14.9 1.7 6.8 5.8 3.7 1995 24.6 6.8 1.6 2.7 14.7 9.4 1.9 7.5 6.6 5.3 1996 28.6 6.4 2.3 2.4 14.1 8.6 1.8 7.5 6.4 6.3 1997 39.1 5.8 2.2 2.5 15.7 8.9 1.8 7.4 6.3 6.7 1998 33.2 5.3 2.5 2.0 22.8 12.0 1.7 6.9 6.4 7.6 1999 11.8 4.3 2.0 1.3 15.2 11.3 1.7 7.0 5.4 4.9 2000 9.0 4.1 2.2 1.2 4.5 8.9 1.4 6.7 5.3 4.8 2001 7.8 4.0 1.6 1.7 8.7 10.8 1.4 5.1 5.2 4.8 2002 10.1 4.0 1.7 1.6 4.2 6.1 1.4 5.2 7.3 5.1 2003 10.6 4.1 1.4 1.4 4.8 4.7 1.3 5.5 8.4 3.9 Average 18.4 5.2 1.6 2.8 9.0 10.9 1.7 6.2 6.2 4.4 Correlation 0.78 0.49 -0.13 0.63 0.55 -0.22 -0.60 -0.43 This table compares financial characteristics of REITs and C-Corporations C-Corporations are selected from SIC codes 10003999 and 5000-6000 Total year-beginning assets of firms are used to scale the numbers, and are reported as percentages INV is the net investment; DIV is cash dividends paid; NCF is cash flow net of paid dividends; CS is the stock of cash and shortterm investments as of the beginning of the year; and L/C is the total credit line capacity as of the beginning of the year The bank L/C information is obtained from the Loan Pricing Corporation's DealScan database, and the firm financial information is from the Compustat Industrial Annual database Correlation indicates the cross-correlation between investment and each of the other variables over the sample period 37 Table Variables Common Across the System: Definitions and Economic Interpretation as Applied to Investment Variable RetainedCashFlowt CashStockt Leveraget LnAget EDumt DDumt L/CCapacityt-1 L/CUsaget Definition Cash flow in year t net of dividends paid, scaled by beginning-year book assets Year-beginning stock of cash and marketable securities, scaled by book assets Year-beginning total long-term debt, scaled by book assets Natural logarithm of beginning-year firm age Dummy variable that equals if an equity offering occurs during year t Dummy variable that equals if a long-term unsecured debt offering occurs during year t Change in L/C capacity during year t-1, scaled by beginning-year book assets Change in L/C use during year t, scaled by beginning-year book assets Economic Interpretation Proxy for costly external finance and debt overhang problems Proxy for costly external finance and debt overhang problems Control variable and proxy for debt overhang problems Control variable for unspecified financing frictions associated with firm age Control variable 38 Expected Coefficient Sign + +  ? ? Control variable ? Proxy for debt overhang problems Proxy for preemptive investment/ collateral capacity effects + + Table Descriptive Statistics Variable N Min Max Mean Median Std Investmentt 1257 -0.902 2.806 0.197 0.078 0.340 Qt 1257 0.442 3.714 1.217 1.164 0.326 RetainedCashFlow 1257 -0.590 0.125 0.0164 0.020 0.040 t CashStockt 1257 0.427 0.0189 0.0076 0.040 Leveraget 1257 1.0 0.395 0.399 0.203 Aget 1257 51 11.142 9.846 EDumt 1257 0.363 0.481 DDumt 1257 0.217 0.412 L/CCapacityt-1 1257 -1.227 4.677 0.072 0.321 L/CUsaget 1257 -0.563 0.911 0.0154 0.103 The table presents summary statistics for the full sample, with observations covering the years 1990 to 2003 Investmentt is net investment over total book assets in year t; Qt is the market value of equity plus book value of debt divided by the book value of assets in year t; RetainedCashFlowt is net cash flow (total cash flow minus dividend payout) over book assets in year t; CashStockt is cash and cash equivalents over book assets in year t; Leveraget is total long-term debt over book assets in year t; Aget is the age of the firm in years in year t; EDumt indicates whether a REIT issues equity during year t; DDumt indicates whether a REIT issues long-term public debt during year t L/CCapacityt-1 is the net increase in bank L/C capacity over book assets in year t-1; L/CUsaget is the net increase of bank L/C debt outstanding over book assets in year t; The data are from the SNL’s REIT financial database 39 Table OLS Investment Equation and Erickson-Whited Threshold Test Results Qt NetCashFlowt CashStock t Leveraget Lnaget EDumt DDumt L/CCapacityt-1 L/CUsaget N Adj R2 OLS Estimation Results (A) Partial Correlation Threshold (B) Partial Correlation Threshold (C) 0.139 (4.79)*** 0.608 (2.73)*** 0.634 (2.78)*** -0.044 (-0.91) -0.015 (-1.24) 0.150 (7.62)*** 0.030 (1.32) 0.139 (4.93)*** 1.355 (15.15)*** 0.000 (0.000) 0.119 (0.123) 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) 0.028 (0.020) 0.086 (0.086) 0.000 (0.000) 0.017 (0.018) 0.000 (0.000) 0.119 (0.123) 0.000 (0.000) 0.000 (0.000) 0.000 (0.000) 0.028 (0.020) 0.086 (0.086) 0.000 (0.000) 0.017 (0.018) 1257 0.410 This table presents OLS investment equation estimation and associated Erickson-Whited (2005) threshold test results Regressors are as defined in Table T-statistics are stated in parentheses for the OLS regression results ***, **, * indicate statistical significance at 1%, 5%, and 10% levels, respectively Standard errors are reported below the threshold estimates in columns (B) and (C) In column (B) it is assumed that the measurement error in q may be correlated with one or more regressors, but is uncorrelated with the disturbance term, whereas in column (C) it is assumed that the measurement error in q is uncorrelated with all other variables The data are an unbalanced panel from the SNL’s REIT financial database covering the years 1990-2003 All the models include an intercept term as well as year and firm property type fixed effects as part of the specification 40 Table 3SLS and IT3SLS Simultaneous Equation Estimation Results For Investment, Retained Cash Flow, and Bank L/C Use Qt RetainedCashFlowwt CashStock t Leveraget Lnaget EDumt DDumt L/CCapacityt-1 L/CUsaget Investmentt Panel A : Investment Equation (1) 3SLS (2) IT3SLS 0.118 0.107 (4.01)*** (4.33)*** 2.58 2.67 (3.05)*** (3.28)*** 1.22 1.22 (3.94)*** (4.09)*** -0.038 -0.035 (-0.74) (-0.71) -0.018 -0.018 (-1.32) (-1.37) 0.144 0.144 (6.67)*** (6.87)*** 0.010 0.012 (0.40) (0.51) 0.196 0.200 (6.56)*** (7.14)*** 0.625 0.673 (1.95)* (2.28)** GrossCashFlowt RetainedCashFlowt-1 GrossCashFlowt-1 TotalL/CCapt Panel B : Retained Cash Flow Equation (3) 3SLS (4) IT3SLS -0.203 (-5.40)*** 0.0078 (1.16) 0.0028 (1.75)* -0.0016 (-0.31) 0.0040 (1.34) -0.0030 (-1.34) 0.061 (1.41) 0.023 (0.78) 0.128 (2.70)*** 0.263 (7.65)*** -0.065 (-4.08)*** -0.206 (-5.53)*** 0.0081 (1.21) 0.0029 (1.79)* -0.0026 (-0.52) 0.0034 (1.16) -0.0051 (-0.97) 0.046 (1.09) 0.029 (1.06) 0.131 (2.89)*** 0.254 (7.48)*** -0.062 (-4.09)*** TotalL/COutt N Weighted R2 1257 0.263 1257 0.276 1257 0.263 41 1257 0.276 Panel C : L/C Use Equation (5) 3SLS (6) IT3SLS -0.938 (-2.87)*** -0.236 (-1.88)* -0.012 (-0.69) 0.0081 (1.73)* -0.041 (-4.32)*** -0.026 (-3.22)*** -0.975 (-2.88)*** -0.247 (-1.91)* -0.0098 (-0.53) 0.0084 (1.69)* -0.043 (-4.37)*** -0.026 (-3.04)*** 0.317 (7.60)*** 0.326 (7.95)*** 0.051 (2.97)*** -0.175 (-7.72)*** 0.060 (3.93)*** -0.175 (-7.43)*** 1257 0.263 1257 0.276 This table presents 3SLS and Iterated (IT)3SLS simultaneous equation estimation results for firm investment, retained cash flow and bank L/C use Regressors common to the investment and other equations are as defined in Table Other exogenous variables are: GrossCashFlowt-1,t, the ratio of cash flow prior to dividend payout over book assets in years t-1 and t, respectively; RetainedCashFlowt-1, the ratio of net cash flow to beginning period book assets in year t-1; TotalL/CCapt, total L/C capacity at year-beginning t over book assets; and TotalL/COutt, total L/C debt outstanding at year-beginning t over book assets T-statistics are listed in the parentheses ***, **, * indicate statistical significance at 1%, 5%, and 10% level, respectively The data are from the SNL’s REIT financial database All the models include an intercept term as well as year and firm property type fixed effects as part of the specification 42 Table Descriptive Statistics of the Sub-samples based on KZ Index Score Less Constrained Group (with lower KZ index) More Constrained Group (with higher KZ index) Variable Mean Median STD Mean Median STD It 0.249 0.127 0.423 0.145 0.052 0.338 Qt 1.250 1.210 0.367 1.185 1.144 0.275 CFt-1 0.092 0.085 0.049 0.055 0.057 0.031 CSt-1 0.023 0.007 0.052 0.015 0.008 0.022 DivRatiot-1 0.089 0.069 0.101 0.035 0.036 0.018 DivPayoutt-1 0.833 0.807 0.312 0.623 0.604 0.369 Levt-1 0.361 0.347 0.241 0.610 0.585 0.206 Aget 11.5 10.37 10.77 9.289 Bank Relationt 591 492 554 497 U/W Relationt 337 473 162 369 Total L/C Capt 215 183 199 135 128 108 TotalAssett 879 575 1,037 1,791 853 2,816 This table presents summary statistics for the sub-samples classified by KZ index score The less constrained group consists of 629 observations that are from lower-half of the full sample based on KZ index score, and the more constrained group consists of 628 observations that are from the upper-half of the full sample based on KZ index score It is net investment over year-beginning book assets in year t; Qt is the market value of equity plus book value of debt divided by the book value of total assets at the beginning of year t; CFt-1 is gross cash flow (prior to dividend payout) over year-beginning book assets in year t-1; CSt-1 is cash and cash equivalents over book assets at the beginning of year t-1; DivRatiot-1 is total cash dividend over year-beginning book assets in year t-1; DivPayoutt-1 is total cash dividend over Funds From Operations (FFO) in year t-1, where FFO is defined as net income plus depreciation and amortization; Levt-1 is the ratio of long-term debt over total assets in year t-1; Aget is the age of the REIT in year t; and TotalAssett is total book assets in millions of dollars at the beginning of year t The data are from the SNL’s REIT financial database 43 Table KZ Index Sub-sample Results: 3SLS Simultaneous Equation Estimations For Investment, Retained Cash Flow, and Bank L/C Use High KZ Index Score (More Constrained) Low KZ Index Score (Less Constrained) Qt RetainedCashFlowt CashStock t Leveraget Lnaget EDumt DDumt L/CCapacityt-1 L/CUsaget (1) Investment 0.128 (3.23)*** 1.23 (1.03) 1.01 (2.29)** -0.033 (-0.34) -0.011 (-0.59) 0.164 (5.17)*** 0.025 (0.65) 0.173 (4.49)*** 0.870 (1.78)* Investmentt GrossCashFlowt RetainedCashFlowt-1 GrossCashFlowt-1 (2) Ret’d Cash Flow -0.259 (-4.82)*** -0.0091 (-0.60) 0.0034 (1.16) 0.0010 (0.13) 0.007 (1.22) 0.0007 (0.09) 0.132 (1.56) 0.027 (0.77) -0.041 (-0.82) 0.216 (4.34)*** -0.061 (-2.58)*** TotalL/CCapt -0.232 (-0.57) -0.041 (-0.26) 0.0082 (0.27) 0.0048 (0.77) -0.043 (-3.42)*** -0.037 (-3.52)*** (4) Investment -0.026 (-0.92) 4.44 (6.69)*** 0.177 (0.29) 0.216 (2.33)** -0.035 (-1.78)* 0.128 (4.32)*** 0.019 (0.55) 0.280 (5.38)*** 1.516 (5.07)*** 0.279 (5.71)*** (5) Ret’d Cash Flow -0.031 (-1.09) -0.0069 (-1.61) 0.0034 (3.84)*** -0.0067 (-3.95)*** -0.0001 (-0.03) -0.0173 (-5.80)*** -0.062 (-3.89)*** 0.037 (3.90)*** 0.578 (13.11)*** 0.50 (15.18)*** -0.406 (-13.62)*** 0.032 (1.50) -0.126 (-4.68)*** TotalL/COutt N Weighted R2 (3) L/C Use 629 0.281 629 0.281 629 0.281 44 (6) L/C Use -1.74 (-5.55)*** -0.037 (-0.18) -0.092 (-2.92)*** 0.014 (2.00)** -0.052 (-4.57)*** -0.0158 (-1.38) 0.435 (9.34)*** 0.120 (3.62)*** -0.245 (-6.49)*** 628 0.605 628 0.605 628 0.605 This table presents 3SLS simultaneous equation estimation results for investment, retained cash flow and bank L/C use based on sub-samples Sub-samples are created by, first, calculating a Kaplan-Zingales (KZ) measure of the degree of financial constraint (see Lamont, Polk, and Saá-Requejo (2001, appendix) for a compact explanation of how the measure is calculated) and, second, splitting the full sample in half based on the ordered KZ index score A higher KZ index score indicates a more financially constrained firm Regressors common to the investment and other equations are as defined in Table Other exogenous variables are: GrossCashFlowt-1,t, the ratio of cash flow prior to dividend payout over book assets in years t-1 and t, respectively; RetainedCashFlowt-1, the ratio of net cash flow to beginning period book assets in year t-1; TotalL/CCapt, total L/C capacity at year-beginning t over book assets; and TotalL/COutt, total L/C debt outstanding at year-beginning t over book assets T-statistics are listed in the parentheses ***, **, * indicate statistical significance at 1%, 5%, and 10% level, respectively The data are from the SNL’s REIT financial database All the models include an intercept term as well as year and firm property type fixed effects as part of the specification 45 .. .Financial Constraint, Liquidity Management and Investment Introduction Fazzari, Hubbard, and Petersen (1988) convincingly argue that internal... cash flow constraint and financial constraint on investment and liquidity management, we split the sample based on Kaplan and Zingales’ (1997) methodology for indexing financial constraint Based... the basis of financial constraint Sensitivity of investment and liquidity management to proxies for financial market frictions is generally much higher in the sub-sample of more financially constrained