RDP 2018-05: Do Interest Rates Affect Business Investment? Evidence from Australian Company-level Data Appendix B: Tobin's q Models

The use of company-level data helps to ameliorate endogeneity that arises from the mismeasurement of aggregate economic investment fundamentals, as we can use time effects to capture these fundamentals. However, we may be mismeasuring company-level investment fundamentals if company sales are a poor indicator of fundamentals. This could lead to other sources of endogeneity. For example, improvements in the outlook for future growth could lead to more investment. At the same time, the company's risk of default, and therefore its cost of debt and finance, is likely to fall. Current sales will be unaffected. This would cause our estimates of the effect of the cost of debt and finance on investment to be negatively biased, meaning our results would be overstated. Alternatively, if investment increases the company's risk of default and therefore funding costs, this would lead to a positive bias in our estimates and suggest our estimated relationships are understated.

To better capture these dynamics, we estimate a second model that incorporates company fundamentals in a different way. It includes two measures of company fundamentals. One is Tobin's average q, which measures the ratio of the average value of capital inside and outside the company. Under certain assumptions, the average q is equivalent to the marginal q – the ratio of the marginal value of an additional dollar of capital inside and outside of the company – which is the fundamental driver of investment according to the q theory of investment (Hayashi 1982).[25] If the value of capital is higher inside the company, the company should invest; if the value is higher outside, it should disinvest and return money to shareholders.

We construct our measure of the average q as:

where the market value of equity is calculated by multiplying the outstanding number of ordinary shares by the closing stock price at the end of the financial year.

Technically, the denominator of the average q should be the replacement value of the capital stock, rather than the book value of the assets. However, using the replacement value leads to a number of complications. In particular, companies' equity and debt fund a large number of non-capital assets, including financial instruments and other investments, and the ratio needs to be adjusted for these or else it will be systematically overstated. This adjustment is difficult and imprecise due to data limitations, and due to the accounting treatments of investments and intangibles. Instead, we use this simpler measure of q, which is very similar to the measure adopted in Gutiérrez and Philippon (2016). More broadly, even if the measure cannot be thought of strictly as a measure of q, it may still be useful as it provides a forward-looking indicator of the company's investment opportunities given it includes the market value of equity (Caballero 1999).[26]

Similar to Gilchrist and Zakrajšek (2007), we also attempt to account more directly for company default risk by including a measure of default risk (D2D). Again, D2D does not have a direct role in q-type models and should, in theory, be captured by the average q measure. However, given the already discussed difficulties in accurately measuring q, we incorporate D2D into the analysis.

We estimate the following simple model:

We use the change in the cost of debt or finance to be more consistent with the model outlined in Section 3. According to theory, the capital stock is a function of the level of the user cost of capital. Therefore, investment, which is the change in the capital stock, should be related to the change in the user cost of capital. In contrast to Section 3, we only include the contemporaneous change for simplicity, but the results are robust to including more lags.

Table B1 contains the results using the cost of debt in the Tobin's q model. For both the net and gross investment measures, the coefficients on the cost of debt are negative and significant. This provides additional support for our earlier findings regarding the relationship between investment and the cost of debt. The magnitudes are economically significant, though appear a bit smaller than those obtained in Section 3. A 1 per cent decrease in the cost of debt is associated with a ¼ percentage point rise in the investment rate.[27]

Table B1: Regression Estimates Using q Model
  Net investment Gross investment
Inline Equation −0.25***
qi,t−1 0.26***
D2Dt−1 −0.03***
Observations 375 385

Notes: *, **, *** indicate significance at the 10, 5 and 1 per cent levels, respectively; standard errors are reported in parentheses and are robust to autocorrelation and heteroskedasticity

Moreover, the coefficient on q is positive and significant. It is also somewhat larger than what is found in earlier Australian studies such as Mills et al (1994) and La Cava (2005), and in the literature more broadly. Nevertheless, it is broadly in line with the estimates from Gutiérrez and Philippon (2016) for the United States.

Somewhat surprisingly, there is evidence of a negative relationship between D2D and investment. That is, as companies become more risky they invest more. One explanation could be that there is a degree of reverse causality: the act of investing makes companies more risky. However, it is difficult to draw too strong a conclusion without a proper structural model, which is beyond the scope of this paper.


In Abel and Eberly (2004), it is actually the average q, not the marginal q that is relevant for investment. [25]

This type of interpretation is more in line with the model in Abel and Eberly (2004), where investment is related to average q because average q provides information on future profits. [26]

The results are robust to including cash flow in the equation. [27]