Introduction

In recent years, central banks have increasingly focused on managing firm and house-hold expectations. This is mainly due to the constraints of the effective lower bound forcing central banks to rely on additional instruments (den Haan 2013). Given the central banks’ focus on price stability, inflation expectations are particularly relevant.

Inflation expectations are a key transmission channel from monetary policy to infla-tion, both directly and indirectly through the real interest rate. It is therefore important to understand how monetary policy affects inflation expectations of all actors in the economy. Given the scarce empirical evidence so far, this chapter focuses on the role of monetary policy for households’ inflation expectations.

I show that US households’ quantitative inflation expectations increase after a sur-prise tightening of monetary policy, i.e. a sursur-prise increase in interest rates after a federal open market committee (FOMC) announcement. For the inflation expectations I use data from the Michigan Survey of Consumers. Monetary policy surprises are measured using the high-frequency identified changes in interest rates in a small win-dow around FOMC announcements provided by Jaroci ´nski and Karadi (2020). The effect is robust to controlling for unobserved household heterogeneity and to using different measures of monetary policy. The results are not driven by outlier observa-tions or special episodes of US monetary policy. They are also robust across different demographic groups. In addition, results do not change when including other eco-nomic news released in the same month, in which the monetary policy announcement occurred.

The positive response to surprise increases is in line with a Delphic interpretation of monetary policy announcements (Campbell et al. 2012) or the information effect of monetary policy (Nakamura and Steinsson 2018). These theories propose that agents in the economy focus on the implication of the monetary policy announcement for the current inflation outlook, not on the effect of the changed monetary policy stance on the future development of inflation. This view of monetary policy goes back to the argument by Romer and Romer (2000) that the central banks may be (perceived to be) better informed about the future state of the economy than households and other economic agents. Because agents are aware of this informational advantage, they look to central bank announcements not only for information about the decision but also for information about the current economic outlook.

In order to verify that indeed this information effect is at play here, I analyze news-paper reporting after FOMC meetings. By now, it is commonly understood that most households do not directly follow monetary policy announcements (Binder 2017b).

However, in order to form expectations, households rely on various information sources

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including media reporting (D’Acunto et al. 2019b). I therefore use text analysis tools to classify articles published in US newspapers after monetary policy announcements into articles referring to high or increasing inflation and articles referring to low or de-creasing inflation. After tightening monetary policy surprises more articles referring to high or increasing inflation are published. Articles usually refer to high or increas-ing inflation as the explanation for the decision made. The newspaper reportincreas-ing in turn influences inflation expectations. I conclude that newspaper reporting provides a transmission channel of the information effect from the central bank to households.

This chapter relates to different strands of the literature studying expectations, namely studies of expectation formation generally, of the interaction between expec-tations and news reporting as well as monetary policy, and studies of the effect of expectations on outcomes. In the following, I discuss the most important papers from these strands.

The study of expectations has been quickly expanding in recent years with a focus on using micro level data. In part, this is due to the central banks’ increased focus on expectations management. Another reason for the increased interest are the missing disinflation puzzle after the financial crisis and the missing inflation puzzle during the recovery (Coibion and Gorodnichenko 2015b). While earlier work already emphasized that the full information, rational expectations hypothesis is not in line with the em-pirical evidence (see e.g., Carroll 2003), it focused on time series data. More recently, an emphasis is put on micro-level data and constructing moments from these data to inform models (Coibion and Gorodnichenko 2012, 2015a). Furthermore, the literature now goes beyond testing for rationality or specific models of deviation from rationality.

Among others, Binder (2017a) and Das, Kuhnen, and Nagel (2020) show that expec-tations depend on demographic factors and the socio-economic status of households.

Using a Finnish data set, D’Acunto, Hoang, Paloviita, and Weber (2019a) show that the IQ of a person has significant effects on their expectations, beyond education and income. In addition, individuals’ experiences matter. Malmendier and Nagel (2016) find that households extrapolate from their own experiences over their lifetime when forming expectations. Therefore younger people react more strongly to new informa-tion arriving (because their accumulated experiences are shorter), and older people who experienced the high inflation periods in the US, generally have higher inflation expectations. Recent research using a novel data set of scanner data by D’Acunto et al.

(2019b) highlights the importance of prices of frequently purchased goods. Their work indicates that observed price changes of groceries are one major source of information for inflation expectations. Previous literature already showed that inflation expecta-tions react strongly to aggregate changes in food and gas prices (see e.g., Coibion and Gorodnichenko 2015b). I will take the evidence on household heterogeneity into

ac-count by considering whether different households react differently to monetary pol-icy announcements. In addition, I control for current developments in food and gas price inflation given the relevance of these particular prices for households.

Another strand of literature analyzes whether news reporting affects the expecta-tion formaexpecta-tion process. Most work on this is related to tests of the epidemiological model of inflation expectations introduced by Carroll (2003). While earlier research focused on whether there are any effects of news, more recent contributions look at the determinants of these effects. Ehrmann, Pfajfar, and Santoro (2017) show that more pessimistic households have a larger initial bias in inflation expectations but also react more strongly to news. The content of news also matters. Lamla and Lein (2014) and Pfajfar and Santoro (2013) show that households react more strongly to news with a positive tone.¹ Lamla and Maag (2012) find that households respond more strongly to news when it is about higher prices or inflation. Generally, hearing news about inflation reduces the bias in inflation expectations.² This chapter provides additional evidence on the role of news by classifying articles based on their information about inflation. Furthermore, I add a new dimension to the analysis by also considering how monetary policy affects news reporting, and how monetary policy is transmitted to expectations via news.

The relevance of analyzing survey expectations of course depends on the assump-tion that expectaassump-tions reported in surveys are actually relevant for households’ deci-sions. Due to a lack of data on the individual level and general skepticism towards surveys, this has been difficult to do empirically for a long time. Early work by Bach-mann, Berg, and Sims (2015) found only a weak relationship between inflation ex-pectations and the willingness to spend on durable goods in the Michigan Survey of Consumers. Using the new and more detailed New York Fed Survey of Consumer Expectations, Crump, Eusepi, Tambalotti, and Topa (2015) find higher inflation ex-pectations lower expected consumption in the future, in line with the Euler equation.

Ichiue and Nishiguchi (2015) show that Japanese households increase current spend-ing and lower future spendspend-ing in response to higher inflation expectations. Dräger and Nghiem (2020) find a similar effect in Germany. Combining survey data with adminis-trative data in the Netherlands, Vellekoop and Wiederholt (2019) show that households with higher inflation expectations lower their net worth, i.e. save less, and are more likely to purchase a car, as a proxy for spending on durable goods.

However, these studies may still suffer from endogeneity issues due to omitted variables. Therefore, several authors have explored natural experiments. D’Acunto,

1The tone is determined by hand coding articles based on methodologies from media analysis.

2The bias is usually measured by computing the difference between households’ inflation expecta-tions and some benchmark expectaexpecta-tions series (such as professional forecasters) or realized inflation in the forecasting period.

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Hoang, and Weber (2018) show that the announcement of a VAT increase in Germany led to an increase in inflation expectations and an increase in spending before the VAT increase took place. Carrillo and Emran (2012) exploit an error in reporting of inflation in Ecuador. Officially reported inflation rates were higher than actual inflation, which led households to increase inflation expectations and lower savings at the same time.

Other authors have introduced exogenous variation into survey expectations. Coibion, Georgarakos, Gorodnichenko, and van Rooij (2019a) provide information treatments to households in a Dutch survey, which change the households’ inflation expectations. In reaction to higher inflation expectations induced by the information treatment, house-holds slightly increase their non-durable spending, but decrease their durable spend-ing, so that overall spending falls. This reaction is due to households expecting their real income to fall when inflation increases, i.e. they associate higher inflation with worse economic outcomes. In a related study, Kamdar (2019) argues consumers’ expec-tations can be explained by a single factor, which she labels sentiment. If households are generally optimistic about the future, they expect the economy to expand but infla-tion to decline. This result is in line with households expecting less real income when their inflation expectations increase. The recent evidence from survey experiments and natural experiments shows that expectations (also as reported in surveys) do matter for actions. Thus, the analysis of micro-level survey data can indeed provide insights into

‘actual’ behavior of agents in the economy.

Finally, regarding the empirical relationship between monetary policy and expec-tations, much of the literature so far has focused on the perception of central banks in general as well as the consistency of expectations with certain relationships deemed relevant for monetary policy. For a detailed discussion of the studies, see Binder (2017b). In addition, some authors have compared different communication channels and tools. Coibion, Gorodnichenko, and Weber (2019b) set up a randomized control trial within a survey of consumers where they provide different information treat-ments, ranging from information about actual inflation to newspaper articles about FOMC meetings and actual FOMC statements. The authors find households update inflation expectations most strongly in response to being provided with actual figures and with FOMC statements. Bholat, Broughton, Ter Meer, and Walczak (2019) show that simplifying text and relating information to people’s experiences in central bank communication improves comprehension of the information and increases trust in the central bank.

The direct effects of monetary policy on household expectations are now being con-sidered as well. Lamla and Vinogradov (2019) conduct an online survey within a few days around several FOMC meetings in 2016 and 2017 asking people about their infla-tion expectainfla-tions, among other things. They find only weak effects of monetary policy

announcements on inflation expectations, largely related to increased news coverage around FOMC meetings. However, the study lacks a panel dimension so the effect may be due to differences between the households interviewed before and after the announcements. In contrast to this result, Lewis, Makridis, and Mertens (2019) find a significant and negative effect of tightening monetary policy surprises on expectations about the general economic situation. The authors also have access to daily expecta-tions data but for a much longer time period than Lamla and Vinogradov (2019). In addition, they use high-frequency identified monetary policy surprises to quantify the announcement beyond the announced target rate change. Finally, Claus and Nguyen (2020) use aggregate Australian survey data and a latent factor model to identify the effects monetary policy. They find inflation expectations increase both after easing and tightening announcements.³ The initial response depends on the income level: richer households respond immediately while poorer households respond only a few months after the announcements.

This chapter directly relates to the set of papers discussed in the last paragraph.

Similar to Lewis et al. (2019), I study the effect of monetary policy using high-frequency changes in interest rates. However, I focus on inflation expectations instead of the eco-nomic outlook. While I lack the detailed information on the timing of the responses as available to Lamla and Vinogradov (2019) and Lewis et al. (2019), I cover a much larger sample of monetary policy announcements, namely all meetings since 1994. In addition, I can control for individual-specific effects using the panel dimension in my household data. I also explicitly control for the role of news by analyzing actual re-porting after monetary policy announcements. For the analysis of news or other text data in this context, the papers I am aware of, have so far relied on human coding or a general method of tone analysis to distinguish different types of reporting. In this chapter, I develop a new approach to classify newspaper articles about inflation based on a dictionary method.

To summarize, this chapter is the first to consider the direct effects of quantitative monetary policy surprises on households’ inflation expectations in a large micro-level sample with a long time dimension as well as a panel dimension. Additionally, it is the first to systematically link the effects of monetary policy and its transmission via news reporting for households.

The remainder of this chapter is structured as follows. The next section describes the data used. Section 2.3 describes the main results for the effect of monetary policy on expectations. Section 2.4 presents the text analysis approach and the results for the transmission of monetary policy to households via news reporting. Section 2.5 concludes.

3The authors distinguish announcements based on the announced target rate change.

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