This project focuses on estimating optimal cash levels for firms by analyzing key predictors influencing cash reserves. Through extensive data preprocessing and statistical modeling, we estimate optimal cash levels for individual firms, shedding light on whether companies maintain surplus or inadequate cash reserves compared to their targets. By scrutinizing key variables and their correlations, our analysis offers actionable insights for firms to optimize cash flow, refine investment decisions, and capitalize on managerial expertise and sales growth for sustained financial health.
- Methodology focusing on data preprocessing, cleaning, and merging to ensure integrity and reliability.
- Comprehensive statistical modeling using SAS to estimate optimal cash levels and ascertain factors influencing cash reserves.
- Insights into correlations between various firm characteristics and cash levels, providing a holistic view of cash management dynamics.
- Recommendations tailored to bolster cash reserves, enhance operational efficiency, and drive sustainable revenue growth.
- Transparent discussion of limitations and considerations for context-specific applicability of findings.
Stakeholders in finance, strategy, and operations can utilize the findings of this analysis to inform decision-making processes related to cash management, investment strategies, and financial planning. By understanding the key drivers of cash reserves and implementing the recommended strategies, firms can navigate the complexities of cash management and optimize their financial performance in today's dynamic business environment.
DEREK K. OLER, MARC P. PICCONI, Implications of Insufficient and Excess Cash for Future Performance
Variable descriptions and calculation methodologies:
| Variable Name | Description & Calculation methodology |
|---|---|
| Firm Size | Natural logarithm of total assets, adjusted using the Consumer Price Index. |
| Net Working Capital | Net working capital excluding cash, scaled by total assets less cash. |
| Capital Expenditures | Capital expenditures scaled by total assets less cash. |
| Industry Sigma | Average standard deviation of "cash flow" within 2-digit SIC code industries over the prior 20 years. |
| Research and Development | Research and development expenses scaled by total assets. |
| Dividend Dummy | Binary variable indicating whether the firm paid dividends to common shareholders in the prior year. |
| Sales Growth | Growth rate of net sales, calculated as the difference between current and prior year net sales, scaled by prior year net sales. |
| Cash from Operations | Cash flow from operations scaled by total assets less cash. |
| Firm Age | Natural logarithm of the number of years the firm has been publicly traded. |
| Tax Burden on Foreign Income | Ratio of (Foreign pretax income - U.S. statutory tax rate) to foreign income taxes paid, scaled by total assets less cash. |
| Interest Rates | Interest rate is calculated as interest expense divided by long-term debt plus current debt scaled by total assets less cash. |
| Leverage | Total debt scaled by total assets less cash. |
| Market To Book | Market value of equity scaled by total assets. |
| Gvkey | Global Company Key (gvkey) is a unique number assigned to each company in the Compustat-Capital IQ database. |
| Nyear | The year extracted from ‘Datadate’ variable. |
| Year dummies | Dummy variables representing different years or periods. |
| Industry dummies | Dummy variables representing various industry categories or sectors. |