Bridge over ocean
2 January 2020 CFA Institute Journal Review

Government Debt and the Returns to Innovation (Summary)

  1. Michal Szudejko

This is a summary of "Government Debt and the Returns to Innovation," by M.M. Croce, Thien T. Nguyen, S. Raymond, and L. Schmid, published in the Journal of Financial Economics.

The authors argue that elevated levels of government debt adversely affect high-R&D firms. Increased government debt-to-GDP levels are associated with subsequent declines in productivity and economic growth, resulting from higher risk premiums demanded by investors that raise the cost of capital for R&D companies. The authors base their conclusion on a novel production-based asset model, with endogenous innovation and fiscal policy shocks.

What Is the Investment Issue?

The authors investigate whether government debt, as measured by the debt-to-GDP ratio (or DGDP), is a risk factor for stocks. Their first question is whether DGDP can be used for forecasting aggregate stock returns. Their second is whether increased government debt can have a negative impact on investment decisions by high-R&D firms.

The empirical results are interpreted in the context of an equilibrium production economy. In such an economy, endogenous innovation is the determinant of long-term growth. Corporate investments and innovations are related to a government’s fiscal policy. The government uses taxation to balance out budgetary fluctuations. Unexpected government actions regarding taxes can result in macroeconomic shocks that are priced in the cross section of stock returns.

The authors highlight that investors require a larger risk premium as the DGDP rises, leading to a higher cost of capital for R&D firms. Consequently, the authors attempt to determine whether the growth in government debt can cause a decline in the level of innovation and hamper future economic growth.

How Did the Authors Conduct This Research?

The authors use stock return data from CRSP and accounting data on companies’ fundamentals from Compustat. They construct a panel of quarterly data from Q1 1975 to Q4 2013, a period that begins when the Financial Accounting Standards Board implemented accounting standards on R&D expensing. The authors construct portfolios sorted on the intensity levels of their investment activity (as indicated by the ratio of R&D expenses to total assets). The portfolios have approximately the same market capitalization. In the time series analysis, the authors use aggregate market returns from Kenneth French’s website. To assure robustness, they use aggregate price/dividend ratios from Robert Shiller’s website.

The authors then develop a quantitative model of a stochastic production economy. In this economy, growth prospects are driven by endogenous innovation. The focus is on an economy with two types of capital stock: intangible innovations (e.g., patents) and physical capital. In the model, the government finances its expenditure via debt issues and taxes on corporate profits. Government debt movements drive changes in tax rates, which drive corporate investment and innovation, and finally, the equilibrium growth rate.

The authors allow for shocks to productivity, government expenditures, and financing. All three shocks are reflected in the stochastic discount factor and lead to the development of a three-factor asset pricing model. In this setting, rising DGDP elevates the exposure of returns to underlying risks and forces the firms to cope with a higher cost of capital.

What Are the Findings and Implications for Investors and Investment Professionals?

The authors examine a large cross section of US firms. They bring forward a model explaining the connection (risk channel) between public debt and future growth and identify innovations to government indebtedness as a risk factor that is priced in the market. Their results indicate that DGDP predicts higher future aggregate stock returns in the long term.

The model predicts that excess returns of high-R&D innovative firms can be explained through changes in DGDP because the cost of capital of such firms is highly dependent on the present value of volatile monopolistic rents, which is sensitive to tax rates. Hence, high-R&D firms are more exposed to uncertainty about future tax increases than low-R&D firms.

In conclusion, high-R&D firms have more exposure to government debt changes and pay higher expected returns than their low-R&D peers. Moreover, an increase in DGDP is positively correlated with an increase in the risk premiums paid by R&D firms. Consequently, a higher cost of capital for such innovative firms may lead to declines in productivity and economic growth. The government indirectly affects investment decisions of such firms through an adverse impact on the firms’ cost of capital. Therefore, the authors highlight how political and fiscal uncertainty help shape future aggregate growth.

The authors’ findings should be valuable to stakeholders, including investors, capital providers, and academics focusing on investment returns. Perhaps the most interested group should be government officials. The methodology presented highlights the role of political risk in risk premium determination. The authors provide clear guidance on how decisions regarding taxation or government indebtedness can affect future innovation and economic growth.

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