Equilibrium Growth, Inflation, and Bond Yields - Duke University's ...

Thus, the endogenous growth paradigm provides a structural interpretation for this low-frequency component
by linking it to innovation rates. 16 Importantly, in the endogenous growth framework, the monetary authority
can affect this low-frequency component, or in other words, alter the distribution of long-run productivity
risk. As will be shown in the next section, monetary policy can significantly alter risk premia through this
channel.
Inflation Dynamics In the models above, the log-linearized inflation dynamics depend on real marginal
costs and expected inflation:
where γ1 = ν−1
φR > 0, γ2 = β∆Y
1 1− ψ
ss
�πt = γ1 �mct + γ2Et[�πt+1]
> 0, and lowercase tilde variables denote log deviations from the
steady-state. 17 Recursively substituting out future �π terms implies that current and expected future real
marginal costs drive inflation dynamics. Moreover, real marginal cost can be expressed as the ratio between
real wages and the marginal product of labor. Furthermore, real marginal costs, in log-linearized form, can
be expressed as:
�mct = �wt + α � lt − (1 − α)�at − (1 − α)�nt
where lowercase tilde variables denote log deviations from the steady-state. Thus, inflation is driven by the
relative dynamics of these aggregate variables. In the endogenous growth model, after a good productivity
shock, �wt, � lt, and �nt all increase after an increase in �at. Notably, in a calibrated version of the benchmark
model, the magnitude of the responses of last two terms in the equation are larger than that of the first
two terms. Consequently, marginal costs and inflation decrease persistently after a positive productivity
shock. On the other hand, as discussed above, expected growth rates increase persistently after a positive
productivity shock. Thus, expected inflation and expected growth rates have a strong negative relationship
in the benchmark model, as in the data. These dynamics will be examined further in the section below.
4 Quantitative Results
This section explores the quantitative implications of the model using simulations. Perturbation methods
are used to solve the model. To account for risk premia and potential time variation, a higher-order ap-
proximation around the stochastic steady state is used. Furthermore, ENDO 1 will refer to the benchmark
16 Kung and Schmid (2011) also highlight this mechanism in explaining the equity premium.
17 See appendix for details.
15