RDP 2016-03: Why Do Companies Hold Cash? 6. Results

6.1 The Determinants of Corporate Cash

The results of estimating Equation (2) are shown in Table 4. The pooled ordinary least squares (OLS) estimates indicate that public unlisted companies hold 1 percentage point more of their assets in cash than private companies, on average. The effect is estimated to be slightly stronger in the CRE model, with public companies having a cash-to-assets ratio that is 2 percentage points higher than that of their private counterparts, on average. The results are even stronger when we employ nearest neighbour matching techniques (Section 7.2) and when using a Hausman-Taylor (HT) model as a further robustness check (Appendix D). Each of the coefficient estimates are statistically significant. Taken together, the relatively high share of assets held in cash by public companies is evidence in favour of the agency costs hypothesis and is consistent with recent overseas research.

Turning to the control variables, we find, as expected, that size is inversely related to cash holdings; as a company grows larger, the cash-to-assets ratio typically declines, suggesting that there are costs in holding cash. However, the statistical significance of this result is sensitive to the specification of the model. The inclusion of company fixed effects in the CRE and HT models leads to the correlation becoming statistically insignificant. This suggests that size is correlated with the unobserved company fixed effect.

The negative coefficient estimates on age indicate that companies typically reduce their cash holdings as they become older, on average. This might point to the presence of financing frictions for younger companies. However, the economic effect of age is relatively small – an increase in age of 10 years is associated with cash holdings falling by around ½ to 1 percentage point relative to assets, on average.

Industry-level risk is positively associated with cash holdings, though the effect is only statistically and economically significant in the pooled OLS specification. This suggests that most of the company-level risk is idiosyncratic and absorbed by the company fixed effects. We also find evidence that working capital is a substitute for cash, with a one standard deviation increase in the share of assets devoted to working capital being associated with a 3 percentage point decline in average cash holdings.^[22] Also, higher levels of capital spending and leverage are associated with lower levels of corporate cash, on average.

Finally, the positive correlation between cash flow and cash holdings across all models is consistent with the ‘pecking order’ theory of financing sources, with companies saving at least some of the cash flow generated by their operations as a potential source of future internal funding. For every 1 percentage point increase in cash flows as a share of assets, companies save around 13 basis points in cash.

6.2 The Determinants of Listed Company Cash Holdings over Time

The regression output from estimating Equation (3) is provided in Table 5. In general, the coefficients on the key explanatory variables are of the expected sign and statistically significant. Moreover, the estimated correlations are generally consistent with that observed in the broader sample of public and private companies. This is true when we estimate the model using a pooled OLS regression and when we allow for company fixed effects (FE). (In unreported results, we also find very similar coefficients when estimating the model separately for resource and non-resource companies.)

For example, larger companies hold less cash, on average. In terms of economic significance, the coefficient on company size in the OLS estimates implies that a doubling in the level of real total assets (a 70 per cent increase in the log level) decreases cash holdings by around 2 percentage points. An increase in RISK from the 25th percentile to the 75th percentile (around 8 percentage points) is associated with the cash ratio being higher by around 2 percentage points. These results are consistent with the financing frictions hypothesis. Also consistent with the financing frictions hypothesis (and the speculative demand for cash), companies with better investment opportunities (proxied by TQ) hold relatively more cash as do companies with higher research and development expenditure, though the R&D effect is insignificant in the FE regression.

6.3 Are Australian Company Cash Holdings ‘Abnormal’?

To examine whether Australian corporate holdings of cash are ‘abnormal’ we compare the observed cash-to-assets ratio each period to ‘fundamental’ in-sample determinants of corporate cash. Any differences between actual and fundamental cash holdings provide a gauge of how much cash holdings are out of line with fundamentals, or abnormal. We do this by comparing the estimated year dummies () (the ‘conditional cash ratio’) to the observed mean of cash holdings each year (the ‘unconditional cash ratio’). Any differences in the trends for these estimates are due to variation over time in observed company-level characteristics.

Figure 6 plots the unconditional cash ratio against the conditional cash ratio (i.e. the time dummies from Equation (3) as estimated in column 2 of Table 5). The secular increase in the conditional cash ratio is far less pronounced than for the unconditional cash ratio, suggesting that much of the increase in the cash ratio can be explained by changes in company characteristics. Across all companies, the trough-to-peak increase in cash holdings over 1990 to 2008 is around 30 per cent based on the conditional estimates, which is much smaller than the 200 per cent increase based on the unconditional estimates. At its peak the unconditional cash ratio is over three standard deviations above the conditional estimates. This indicates that we can explain much of the ‘puzzle’ of the secular rise in corporate cash through changes in the observable factors that drive corporate decisions to hold cash.

The largest contributors to the secular rise in cash are better growth opportunities (as measured by Tobin's Q), which are positively associated with cash holdings, and, to a lesser extent, changes in leverage that occurred over the early 1990s and throughout the 2000s (Figure 7). Other factors, such as changes in the average company size and age, played less of a role.

It is not clear what has driven these underlying trends, but the dynamic of Tobin's Q seems to follow the evolution of corporate profitability (IMF 2014). The positive correlation between our estimates of Tobin's Q and corporate cash holdings suggests that some companies have a speculative motive for holding cash; these companies hold cash in expectation of investment opportunities arising in the future. In other words, high corporate cash might not be symptomatic of a weak corporate outlook but actually evidence of expected strength in the economy.

Likewise, aggregate trends in corporate leverage also tend to follow the investment cycle as well as shifts in the use of different forms of external funding, which in turn are affected by the differential between the (real) cost of debt and equity (Fang et al 2015). This notwithstanding, there are many factors that could affect company-level leverage (Shuetrim, Lowe and Morling 1993); a more detailed analysis of the determinants of long-run changes in Australian corporate leverage, and other characteristics, is left to future research.

There are some periods in which the model is less able to explain trends in cash holdings. For instance, the model under-predicts cash holdings in the mid 2000s and over-predicts cash in the period since 2011. This might reflect factors related to the terms of trade boom and bust that are difficult to capture in the observed data (e.g. changes in corporate uncertainty).^[23]

6.4 Cohort Effects on Cash Holdings of Listed Companies

In considering the long-run trend in corporate cash holdings, we can also examine whether companies that have listed more recently on the stock exchange hold more cash than companies that listed earlier. These ‘cohort effects’ can be estimated because we have information on each listed company's initial public offering (IPO).

Previous international research indicates that such cohort effects are important in explaining the rise in average cash holdings among public companies (Begenau and Palazzo 2015). The cohort effects are associated with an increased propensity for riskier companies to list and a trend toward industries with more risky business models (e.g. information technology, pharmaceuticals and biotechnology) (Brown and Kapadia 2007). For Australian companies, the increase in aggregate cash holdings over the mid to late 2000s may have been similarly affected by a trend in listing toward small mining exploration companies during the Australian mining boom.

To construct the cohort estimates we take an unweighted average of the company fixed effects estimated in Equation (3) for each cohort based on its IPO date. These fixed effects essentially capture any unobserved characteristics that the company posesses when it lists and that persist over time. We group companies into cohorts based on five-year windows, with the most recent cohort being based on companies that listed between 2010 and 2014.

The cohort estimates are displayed in Figure 8. The results indicate that recent cohorts hold much higher levels of cash than earlier cohorts. For example, the cash ratio of companies that have listed since 2010 is about 30 per cent higher than the corresponding cash ratio for companies that listed in the late 1980s. These estimates are obtained from the fixed effects in Equation (3) and so are conditional estimates that control for differences between cohorts in other observed characteristics (e.g. size, investment opportunities and leverage).

The trend in the aggregate cash ratio is, at least in part, due to differences in latent factors between companies that list today compared to companies that listed several decades ago. One explanation for this is that companies in recent cohorts are more reliant on intangible capital in their production technology, such as ‘knowledge workers’, relative to companies in older cohorts. Such capital may be harder to pledge as collateral to raise debt financing, thereby increasing companies' precautionary demand for cash (Falato, Kadyrzhanova and Sim 2013).^[24]

Footnotes

This finding is consistent with the theory outlined by Gao (2013) who suggests that improvements in inventory management, such as the adoption of just-in-time technology, have reduced inventory holdings and increased cash holdings over time. [22]

The conditional time trend is quite strongly associated with the ‘net opportunity cost of cash’ – measured as the return on business deposits less the cost of borrowing. This suggests that the ‘economy wide’ opportunity cost of allocating assets to cash might also play a role in explaining the secular trend in corporate cash holdings. [23]

The cohort estimates may also be affected by sample survivorship bias. In unreported results, we find that there is a positive correlation between cash holdings and the probability of failure. This suggests that surviving companies have lower cash holdings than the average company in their own cohort. This, in turn, implies that some of the observed increase in cash holdings across cohorts might be due to survivorship bias. [24]