RDP 2015-04: The Sticky Information Phillips Curve: Evidence for Australia 1. Introduction

Modelling inflation is a core task for inflation-targeting central banks. Like other central banks, the Reserve Bank of Australia (RBA) evaluates and uses a variety of models for inflation. The set of models differ substantially in their style and purpose. At one end of the spectrum are reduced-form single or multi-equation models. These models typically impose few parameter restrictions and are used for forecasting. At the other end of the spectrum are microfounded dynamic stochastic general equilibrium (DSGE) models, which are mostly used for scenario analysis. In between these two extremes are more microfounded single-equation models. While reduced-form models typically provide the best forecasting performance, their lack of structure makes them less suited to policy analysis.

The New-Keynesian Phillips curve (NKPC) has become the canonical microfounded model of inflation in the academic community, being widely used in theoretical work. In its pure or hybrid variants, it is also a central element of DSGE models used by most central banks (e.g. Smets and Wouters 2007). Like all models, its usefulness for policy analysis depends on the assumptions underpinning the model. The key assumption of the New-Keynesian sticky-price model is a restriction on the frequency with which firms can change their prices. This assumption is consistent with the infrequency with which retail prices change for many goods and services. But a large literature highlights the inability of the basic sticky-price model to match the inertial behaviour of inflation, and the delayed and gradual response of inflation to monetary policy shocks.[1] Other counterfactual predictions of the sticky-price model are the possibilities of costless disinflations and disinflationary booms (Ball 1994).

The New-Keynesian model has trouble matching the inertial behaviour of inflation because it implies that, while the price level is sticky, the inflation rate can jump.

The model assumes that a randomly chosen subset of firms are able to change their price each period. Firms anticipate the likelihood of being stuck at their reset price for several periods, making inflation highly forward-looking and responsive to macroeconomic news. The peak response of inflation to a monetary policy shock in the canonical sticky-price NKPC is immediate, and thus the NKPC cannot match the persistence of inflation, or generate the output-inflation correlations evident in the data (Fuhrer and Moore 1995; Mankiw 2001).

As an alternative to the sticky-price model, Mankiw and Reis (2002) propose a Sticky Information Phillips Curve (SIPC). Building on Lucas (1973) and Carroll (2003), the SIPC assumes that macroeconomic news disseminates slowly throughout the population. Only some firms receive updated information about output and inflation each period, with the remainder continuing to set prices based on outdated information. Firms are always free to change prices, but only some firms change prices based on updated information. Slow dissemination of macroeconomic news generates inertial inflation dynamics when there is strategic complementarity in price setting. Firms acquiring new information take into account that other firms remain uninformed, and incorporate macroeconomic news into pricing decisions gradually, as the share of informed firms rises. In contrast, inflation in the NKPC model is entirely forward looking.

This paper provides the first estimates of the SIPC for Australian data. The model is tested using a range of inflation measures, forecast series and sample periods. Overall, the estimation results provide only weak support for the SIPC, particularly over the low-inflation period. The estimated degree of information rigidity differs substantially across sample periods and inflation measures. For consumer price index (CPI) inflation over the 1995–2013 period, the estimated degree of information rigidity using Consensus Economics and official RBA forecasts is theoretically inconsistent, indicating rejection of the model. But for underlying inflation, the estimated degree of information rigidity is theoretically consistent, with estimates implying that firms on average update their information sets each 6–8 quarters. Including data prior to the introduction of inflation targeting in the estimation sample improves the performance of the SIPC, but there is still substantial parameter instability across specifications.

Some of the estimated parameter instability can be explained by differences in inflation inertia across sample periods and inflation measures. A high degree of information rigidity puts substantial weight on old forecasts of current inflation, generating sluggish inflation dynamics. This is a key objective of the sticky-information model, but it is inconsistent with the behaviour of CPI inflation over the low-inflation period. Conversely, the variability of the inertial trend component of inflation was relatively high prior to the introduction of inflation targeting (IT), and the estimated degree of information rigidity is, in general, substantial. Reflecting this, the fit of the SIPC is generally better over sample periods including the pre-IT regime.

Reflecting the weak relationship between inflation and the output gap, particularly over the low-inflation period, the estimated degree of real rigidity is imprecisely estimated. The relationship between the nominal and real side of the model depends non-linearly on the degree of information rigidity, and the degree of real rigidity is most imprecisely estimated when the degree of information rigidity is high.

An important theoretical feature of the SIPC is its ability to generate costly disinflations. Despite this, the SIPC does not perform well during the early 1990s disinflation, except with very low levels of information rigidity. This is because the SIPC places weight on dated real-time long-horizon inflation forecasts, which substantially overpredicted inflation during the early 1990s disinflation. Coibion (2010) labels this the real-time forecast error effect. In contrast, the forward-looking NKPC model better predicts the disinflation because it places no weight on dated long-horizon inflation forecasts.

These findings are broadly similar to Coibion (2010) for US data, who finds that the SIPC generates excessively inertial inflation dynamics, and can be strongly rejected in favour of the NKPC. Kahn and Zhu (2006) present more favourable evidence for the SIPC using US data, estimating that firms update their information sets each 3–7 quarters. Döpke et al (2008) provide similarly favourable evidence for France, Germany and the United Kingdom, finding that firms update their information sets once a year. However, both Kahn and Zhu (2006) and Döpke et al (2008) impose the degree of real rigidity, rather than estimating the parameter. I find that imposing the degree of real rigidity can have a substantial effect on the estimated degree of information rigidity. Kiley (2007) and Koronek (2008) both reject the SIPC in favour of the NKPC using US data, although Kiley finds that a hybrid NKPC model fits the data best, and suggests that the importance of lagged inflation may capture information rigidity. However, both Kiley (2007) and Koronek (2008) use in-sample forecasts, which can be misleading, particularly when there are mean-shifts in inflation. I use only realtime or quasi real-time forecasts in assessing the empirical performance of the SIPC. More broadly, this paper's findings add to a body of work modelling Australian inflation. Norman and Richards (2010) provide a recent critical evaluation of structural and reduced-form single-equation inflation models for Australia. Their main finding is that an expectations-augmented standard Phillips curve and mark-up models outperform the NKPC in terms of in-sample fit and significance of the model coefficients. Given that I find the fit of the SIPC to be generally no better than the NKPC, the ranking of models in Norman and Richards is unchanged.

The remainder of the paper proceeds as follows: Section 2 describes the SIPC and NKPC models, and discusses estimation issues; Section 3 describes the forecasts used; and Section 4 presents the estimation results. Some concluding thoughts are offered in Section 5.


See Mankiw (2001), and the references therein, for a critique of the sticky-price model, and Christiano, Eichenbaum and Evans (1999) for evidence on the response of inflation to monetary policy shocks. [1]