Innovation, Growth, and Asset Prices

• Author: HOWARD KUNG,LUKAS SCHMID
• DOI: http://doi.org/10.1111/jofi.12241
• Published date: 01 June 2015
• Date: 01 June 2015

THE JOURNAL OF FINANCE •VOL. LXX, NO. 3 •JUNE 2015

Innovation, Growth, and Asset Prices

HOWARD KUNG and LUKAS SCHMID∗

ABSTRACT

We examine the asset pricing implications of a production economy whose long-term

growth prospects are endogenously determined by innovation and R&D. In equilib-

rium, R&D endogenously drives a small, persistent component in productivity that

generates long-run uncertainty about economic growth. With recursive preferences,

households fear that persistent downturns in economic growth are accompanied by

low asset valuations and command high-risk premia in asset markets. Empirically,

we find substantial evidence for innovation-driven low-frequency movements in ag-

gregate growth rates and asset market valuations. In short, equilibrium growth is

risky.

AN ECONOMY’SLONG-TERM GROWTH prospects reflect its innovative potential.

At a fundamental level, innovation is a key source of sustained growth in

aggregate productivity. Empirical measures of innovation, such as research

and development (R&D) expenditures, tend to be volatile and quite persistent.

Such movements affect the dynamics of growth. Indeed, in U.S. post-war data,

productivity growth exhibits long and persistent swings.1Similarly,innovation-

driven growth waves associated with the arrival of new technologies, such

as telecommunication, computers, and the internet, to name a few, are well

documented.2Stock prices reflect such changes in growth prospects. Moreover,

if agents fear that a persistent slowdown in economic growth will lower asset

prices, these movements will give rise to high-risk premia in asset markets.

In this paper, we develop a general equilibrium model of innovation and

R&D to link asset prices and aggregate risk premia to endogenous movements

∗Howard Kung is at the London Business School. Lukas Schmid is at Duke University and the

University of California, Los Angeles. Wethank the Acting Editor Dave Backus and two anonymous

referees as well as Hengjie Ai, Ravi Bansal, Gian Luca Clementi, John Coleman, Diego Comin,

Max Croce, Ian Dew-Becker, Bernard Dumas, Lorenzo Garlappi, Jo˜

ao Gomes, Francois Gourio,

Leonid Kogan, Lars Lochstoer, Pascal Maenhout, Stavros Panageas, Dimitris Papanikolaou, Adri-

ano Rampini, Norman Schurhoff, TomTallarini, Amir Yaron, and Lu Zhang for helpful discussions.

We have also benefited from the comments of seminar participants at Bocconi, Boston University,

Carnegie Mellon University, Cornell University, Duke University, Federal Reserve Bank of San

Francisco, Imperial College, INSEAD, London Business School, London School of Economics, MIT,

Paris School of Economics, UCLA, and Universitat Pompeu Fabra, as well as from conference par-

ticipants at Western Finance Association, Society for Economic Dynamics, CEPR Macro Finance

Conference London, European Finance Association, Tel Aviv Finance Conference, Econometric

Society, American Finance Association, and NBER Spring Asset Pricing Meeting.

1See, for example, Gordon (2010) and Jermann and Quadrini (2004).

2For example, see Helpman (1998) and Jovanovic and Rousseau (2005).

DOI: 10.1111/jofi.12241

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in long-term growth prospects. Our setup has two distinguishing features.

First, we embed a stochastic model of endogenous growth based on industrial

innovation3into an otherwise standard production economy.In this model, pro-

ductivity growth is endogenous and sustained by the creation of new patented

technologies through R&D. Patents represent an endogenous stock of intangi-

ble capital. Second, we assume that households have recursive preferences, so

that they care about uncertainty regarding long-term growth prospects.

When calibrated to match empirical evidence on innovation and long-run

economic growth, our model can quantitatively replicate key features of asset

returns in the data. In particular, our model rationalizes a sizeable equity pre-

mium and a low and stable risk-free interest rate. Moreover, our model predicts

a sizeable spread between the returns on physical capital and intangible cap-

ital, which is related to the value premium in the data. In short, we find that

equilibrium growth is risky.

We first show that in the model innovation and R&D endogenously drive a

small but persistent component in the growth rate of productivity. In our gen-

eral equilibrium setting, these low-frequency movements in productivity trig-

ger long and persistent swings in aggregate growth rates, such as consumption

and output, which we label growth cycles. Intuitively, shocks affect the incen-

tives to innovate, which in turn impact long-term growth prospects. Notably,

transitory shocks in this setting have long-lasting permanent effects through

the innovation channel and generate endogenous persistence in growth rates.

Thus, a bad temporary shock not only lowers the level of consumption and

cash flows today, but also depresses long-term growth rates. When agents have

recursive preferences, they are sensitive to both short-run and long-run uncer-

tainty about consumption growth. Growth cycles help rationalize sizeable risk

premia in asset markets, as agents fear that such prolonged slumps in economic

growth coincide with low asset valuations. Similarly, agents save for extended

low growth episodes, driving down the real interest rate. Furthermore, in the

model, physical capital is endogenously more exposed to predictable variation

in growth than intangible capital, which generates a sizeable value spread.

An innovation-driven persistent component in productivity growth provides

an equilibrium foundation of long-run risks in the spirit of Bansal and Yaron

(2004). More precisely, in our model, long-run productivity risks, in the sense

of Croce (2014), arise naturally in equilibrium. Furthermore, persistent move-

ments in expected productivity affect all aggregate growth rates and therefore

give rise to equilibrium long-run consumption risks and cash flow risks.

The model helps to identify economic sources of long-run risks in the data. In

particular, the model predicts that R&D and innovation are equilibrium deter-

minants of productivity growth. In line with the predictions of the model, we

provide novel empirical evidence that measures of innovation have significant

predictive power for aggregate growth rates including productivity, consump-

tion, and output growth at horizons of one to five years.

3Here, we build on the seminal work of Romer (1990) and Grossman and Helpman (1991).

Innovation, Growth, and Asset Prices 1003

While predictability in growth rates is at the core of the long-run risk model,

empirical evidence regarding this channel is still limited. The model provides

novel theoretical and empirical support for the notion that movements in long-

term growth prospects are a significant source of priced risk in asset markets.

Moreover, our results suggest that extending macroeconomic models to account

for the endogeneity of innovation and long-term growth can make progress

toward an environment that jointly captures the dynamics of aggregate quan-

tities and asset markets. We therefore view stochastic models of endogenous

growth as a useful tool for macrofinance.4

Our paper is related to several strands of literature in asset pricing, economic

growth, and macroeconomics. The economic mechanisms driving the asset pric-

ing implications are similar to those in the consumption-based long-run risks

model of Bansal and Yaron (2004). We contribute to this literature by showing

that predictable movements in growth prospects are an equilibrium outcome

of stochastic models of endogenous growth and by providing novel empirical

evidence identifying economic sources of long-run risks.

A number of recent papers examine the link between technological growth

and asset prices. Garleanu, Panageas, and Yu (2012) model technological

progress as the arrival of large, infrequent technological innovations and

show that the endogenous adoption of these innovations leads to predictable

movements in consumption growth and expected excess returns. Garleanu,

Kogan, and Panageas (2012) examine the implications of the arrival of new

technologies for existing firms and their workers, and show that, in an

overlapping-generations model, innovation creates a systematic risk factor

labeled displacement risk. The asset pricing implications of displacement risk

are further examined in a model of heterogeneous workers and firms in Kogan,

Papanikolaou, and Stoffman (2012). P´

astor and Veronesi(2009) explain bubble-

like behavior of stock markets in the 1990s by the arrival of new technologies.

While our model has implications for consumption dynamics and asset re-

turns that are related to these models, our approach is different but complemen-

tary. In the above models of technology adoption, the arrival of new technolo-

gies is assumed to be exogenous. In contrast, we examine the asset pricing and

growth implications of the endogenous creation of new technologies through

R&D, which leads to a distinct set of empirical predictions. Moreover, by em-

bedding a model of endogenous technological progress into a real business cycle

model, our paper provides a straightforward extension of the workhorse model

of modern macroeconomics.

In this respect, the paper is closer to recent attempts to address asset pric-

ing puzzles within versions of the canonical real business cycle model. Start-

ing with the habit-based models of Jermann (1998) and Boldrin, Christiano,

and Fisher (2001), recent examples, such as Tallarini (2000), Campanale, Cas-

tro, and Clementi (2008), Kuehn (2008), Kaltenbrunner and Lochstoer (2010),

4In a companion paper, Kung (2015) shows that a similar mechanism coupled with imperfect

price adjustment quantitatively rationalizes many aspects of the term structure of interest rates

in a production economy.