Financing Constraints and Corporate Investment

Most empirical models of investment rely on the assumption that firms are able to respond to prices set in centralized securities markets (through the "cost of capital" or "q"). An alternative approach emphasizes the importance of cash flow as a determinant of investment spending, because of a "financing hierarchy," in which internal finance has important cost advantages over external finance. We build on recent research concerning imperfections in markets for equity and debt. This work suggests that some firms do not have sufficient access to external capital markets to enable them to respond to changes in the cost of capital, asset prices, or tax-based investment incentives. To the extent that firms are constrained in their ability to raise funds externally, investment spending may be sensitive to the availability of internal finance. That is, investment may display "excess sensitivity" to movements in cash flow. In this paper, we work within the q theory of investment, and examine the importance of a financing hierarchy created by capital-market imperfections. Using panel data on individual manufacturing firms, we compare the investment behavior of rapidly growing firms that exhaust all of their internal finance with that of mature firms paying dividends. We find that q values remain very high for significant periods of time for firms paying no dividends, relative to those for mature firms. We also find that investment is more sensitive to cash flow for the group of firms that our model implies is most likely to face external finance constraints. These results are consistent with the augmented model we propose, which takes into account different financing regimes for different groups of firms. Some extensions and implications for public policy are discussed at the end.

Financing Constraints and Corporate Investment

macroeconomics, Financing Constraints, Corporate Investment

Financing Constraints and Corporate Investment: Response to Kaplan and Zingales

Kaplan and Zingales (1995, hereafter KZ) criticize Fazzari, Hubbard and Petersen (1988, hereafter FHP) and much ensuing research that uses cross-sectional differences in firm behavior to test for financing constraints on investment. This reply identifies flaws in the KZ analysis. The questions KZ raise have been considered extensively and rigorously in the literature (most of which is not addressed in KZ), with results broadly similar to those of FHP. We also challenge both of KZ's main results. First, their finding that most of the FHP firms are not financially constrained relies on an inappropriate operational definition of what it means to be constrained. Their definition ignores the incentives for firms that operate in imperfect capital markets to accumulate stocks of cash or maintain unused debt capacity to offset partially shocks to the flow of internal finance. Second, the KZ regression results (lower sensitivity of investment to cash flow for firms classified as constrained than for those classified as unconstrained) are uninformative. Their classification approach relies on possibly self- serving managerial statements that may present a distorted picture of firm's availability of finance. It also employs misleading criteria to make unrealistically fine distinctions in the degree of financing constraints, and emphasizes financial distress rather than financing constraints. Finally, econometric problems affect the interpretation of the KZ regressions. We conclude that the KZ findings do not contradict the interpretation of the empirical results in FHP and subsequent research.

Standard Meteorological Measurements

Instruments that measure weather variables have been invented and tested since the time of Leonardo de Vinci. The earliest instruments were crude by today’s standards and required manual observation and notation of the weather variable of interest. In recent years, the miniaturization of circuits–sensors and the use of electronic processors have made it possible to collect ever-increasing numbers of observations on scales not previously considered. In many agricultural applications, the primary portion of the atmosphere that is of interest is the lower planetary boundary layer, or that layer affected by the earth’s surface. Accurate measurement of weather variables in the lower planetary boundary layer requires an understanding of the interactions among the atmosphere, plant communities, and soils. Temperature and pressure are often measured because of their role in air movement and energy exchange between the earth’s surface and the atmosphere. Temperature is perhaps of greater interest in agricultural applications because it is a driving variable that determines the rate of growth and development of an organism, and thus determines what species can grow in a region. Wind speed and direction are measured because of their role in convective energy exchange and the movement of spores, pollen, odors, and chemicals as they drift in the atmosphere. Precipitation amount, intensity, frequency, and form are important in determining the availability of water for crops and play an important role in soil erosion by water and in water quality issues. Solar radiation and relative humidity are additional weather variables, important to agriculture, that are often measured by appropriate sensors at automated weather stations. These variables will be discussed by Klassen and Bugbee (2005, this volume) and Campbell and Diak (2005, this volume)

Standard Meteorological Measurements

Instruments that measure weather variables have been invented and tested since the time of Leonardo de Vinci. The earliest instruments were crude by today’s standards and required manual observation and notation of the weather variable of interest. In recent years, the miniaturization of circuits–sensors and the use of electronic processors have made it possible to collect ever-increasing numbers of observations on scales not previously considered. In many agricultural applications, the primary portion of the atmosphere that is of interest is the lower planetary boundary layer, or that layer affected by the earth’s surface. Accurate measurement of weather variables in the lower planetary boundary layer requires an understanding of the interactions among the atmosphere, plant communities, and soils. Temperature and pressure are often measured because of their role in air movement and energy exchange between the earth’s surface and the atmosphere. Temperature is perhaps of greater interest in agricultural applications because it is a driving variable that determines the rate of growth and development of an organism, and thus determines what species can grow in a region. Wind speed and direction are measured because of their role in convective energy exchange and the movement of spores, pollen, odors, and chemicals as they drift in the atmosphere. Precipitation amount, intensity, frequency, and form are important in determining the availability of water for crops and play an important role in soil erosion by water and in water quality issues. Solar radiation and relative humidity are additional weather variables, important to agriculture, that are often measured by appropriate sensors at automated weather stations. These variables will be discussed by Klassen and Bugbee (2005, this volume) and Campbell and Diak (2005, this volume)

A Gate-To-Gate Life-Cycle Inventory of Solid Hardwood Flooring in the Eastern US

Environmental impacts associated with building materials are under increasing scrutiny in the US. A gate-to-gate life-cycle inventory (LCI) of solid strip and solid plank hardwood flooring production was conducted in the eastern US for the reporting year 2006. Survey responses from hardwood flooring manufacturing facilities in this region accounted for nearly 28% of total US solid hardwood flooring production for that year. This study examined the materials, fuels, and energy required to produce solid hardwood flooring, coproducts, and the emissions to air, land, and water. SimaPro software was used to quantify the environmental impacts associated with the reported materials use and emissions. Impact data were allocated on their mass contribution to all product and coproduct production of 1.0 m3 (oven-dry mass basis) of solid hardwood flooring. Carbon flow and transportation data are provided in addition to the LCI data. Results of this study are useful for creating a cradle-to-gate inventory when linked to LCIs for the hardwood forest resource and the production of solid hardwood lumber in the same region

Health Care and Coming Out: Gay and Bisexual Mens Health Care

In this study a discriminant function analysis was conducted utilizing seven predictor variables to see if they could predict whether or not a gay or bisexual man had disclosed their sexual orientation to their health care providers. The discriminant function analysis confirmed that the predictor variables do serve as reliable predictors of disclosure status. Overall the seven predictor variables were able to correctly classify 90.1 percent of the participants. A one-way MANOVA was conducted to evaluate whether or not there were significant differences between participant's disclosure status to their health care providers and their importance ratings on a 24 item importance survey. The one-way MANOVA confirmed that there were significant differences between disclosers and non-disclosers. Post-hoc analyses utilizing Bonferroni corrected ANOVAs were ran on the 24 items which revealed that two items (desire to share and previous experience) were statistically significant between disclosers and non-disclosers. ThSchool of Teaching and Curriculum Leadershi