Communication frictions, sentiments, and nonlinear business cycles

• DOI: http://doi.org/10.1111/ijet.12163
• Published date: 01 June 2019
• Date: 01 June 2019
• Author: Apostolos Serletis,Libo Xu

doi: 10.1111/ijet.12163

Communication frictions, sentiments, and

nonlinear business cycles

Libo Xu∗†and Apostolos Serletis∗

In the context of a rational expectations macroeconomic model with communication frictions,

we show that the level of economic activity is a nonlinear and time-varying function of aggre-

gate economic fundamentals and sentiment shocks. In particular, because of communication

frictions, it is possible for small changes in sentiment shocks to cause large changes in aggregate

output, and, similarly, for large changes in sentiment shocks to cause small changesin agg regate

output. Wealso find that communication frictions have nonlinear effects on the variance of ag-

gregate output, meaning that improving the communicationdoes not always reduce the variance

of aggregate output.

Key wor ds economic fluctuation, friction, sentiment shock

JEL classification D83, D84, E32

Accepted 17 June2016

1 Introduction

Motivated by Angeletos and La’O (2013) and Benhabib etal . (2015), we consider a rational expec-

tations macroeconomic model with communication frictions, and show that the level of economic

activity is a nonlinear and time-varying function of aggregate economic fundamentals and a certain

type of extrinsic shocks that Angeletos and La’O (2013) refer to as “sentiments.” Weshow that com-

munication frictions amplify or shrink the effect of exogenous sentiment shocks on aggregate output,

meaning that it is possible for small changes in sentiment shocks to cause large changes in aggregate

output and for large changes in sentiment shocks to cause small changes in aggregate output. We

also show that improving communication does not always reduce the variance of aggregate output.

1.1 Theoretical background

One of the most celebrated business cycle models in the past 40 years is the information-based mone-

tary misperceptions model of Lucas (1972), originating from Friedman (1968) and Phelps (1970). In

this model, in a rational expectations setting, economic agents have incomplete information about

prices in the economy, and monetary shocks (created by the monetary authority) are a principal

cause of business cycles. In particular, economic fluctuations are induced because individual pro-

ducers, faced with a change in the price of their product, do not know whether it stems froma shift in

relative demands or a changed level of aggregate demand. If it was the former,the optimal response

∗Department of Economics, University of Calgary,Calgar y,Alberta, Canada. Email: serletis@ucalgar y.ca

†Present address: Department of Economics, Universityof San Francisco, San Francisco, California, USA.

Wewould like to thank an anonymous referee for comments that greatly improved the paper.

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Communication frictions Libo Xu and Apostolos Serletis

would require a change in output, whereas if it was the latter the optimal response would requireno

such change in the level of output. More recently, Barnett (2012) provides another possible expla-

nation of the non-neutrality of money and the sources of business fluctuations, consistent with the

price misperceptions model, stressing monetary misperceptions due to low-quality monetary data

provided by central banks.

In recent years, most economists believe that monetary shocks are not the principal cause of

business fluctuations. In fact, following the powerful Lucas (1976) critique, the modern core of

macroeconomics consists of the real business cycle approach and the New Keynesian approach.

The real business cycle approach (known as freshwater economics), developed by Kydland and

Prescott (1982), is a stochastic formalization of the neoclassical growth model and represents the

latest development of the classical approach to business cycles. It assumes rational expectations and

forward-looking economic agents, relies on market-clearing conditions for households and firms,

relies on shocks and mechanisms that amplify the shocks and propagate them through time, and is

designed to be a quantitative mathematical formalization of the aggregate economy. According to the

original real business cycle model, which has become a centerpiece of business cycle research, under

the classical assumption that wages and prices are fully flexible, most aggregate fluctuations are effi-

cient responses to random production function shocks (usually called real shocks) and government

stabilization policy is inefficient. More recent real business cycle models also assume some type of

nominal rigidity, so that both technology and demand shocks play a role in determining business

cycles, and recognize that some form of government stabilization policy is actually useful.

The opposing New Keynesian approach (known as saltwater economics) advocates models with

sticky prices (prices that do not adjust instantaneously to clear all the markets), consistent with the

assumption of sticky nominal wage rates in Keynes (1936). It points to economic downturns like

the Great Depression of the 1930s and the Great Recession that followed the recent global financial

crisis, and argues that it is implausible for the efficient level of aggregate output to fluctuate as much

as the observed level of output, thereby advocating government stabilization policy. In recent years,

however,the New Keynesian approach has made systematic use of the modeling methodology of the

real business cycle approach, and so the division between the two approaches has greatly decreased.

In fact, the current New Keynesian model is based on the “dynamicstochastic general equilibrium”

framework and combines it with Keynesian features, like imperfect competition and sticky prices,

to provide a theoretical framework for macroeconomic policy analysis. Both the real business cycle

model and the New Keynesian model are largely immune to the Lucas(1976) cr itique.

In the aftermath of the global financial crisis there has also been a revival of interest in endoge-

nous economic fluctuations, founded on (deterministic) chaos theory. The discovery that perfectly

deterministic systems of low dimensions and with simple nonlinearities can have stochastic behavior

has received a lot of attention in macroeconomicsand has brought about a profound reconsideration

of the issue of randomness. Besides its obvious intellectual appeal, chaos is interesting in macroe-

conomics, because of its ability to generate output that mimics the output of stochastic systems,

thereby offering an endogenous explanation of economic fluctuations. If, for example, chaos can

be shown to exist in macroeconomic variables, the implication would be that (nonlinearity-based)

prediction is possible, at least in the short run and provided that the actual generating mechanism

is known exactly. In the long run, however, chaos implies that prediction is all but impossible due to

its property of sensitive dependence on initial conditions. Chaos also implies the persistence of the

effects of temporary shocks and the impossibility of government stabilization policy in the absence

of changes in the values of the structural parameters that govern the behavior of the economic sys-

tem. For a review of this literature, see, for example, Benhabib and Nishimura (1985), Grandmont

(1985), Baumol and Benhabib (1989), Bullard and Butler (1993), and Barnett et al. (2015). For more

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