Limitations and Further Research

The analysis conducted in this dissertation is facing a number of caveats. Above all, it is im-portant to keep in mind that both inflation expectations of households as well as the infor-mation content of news media coverage are unobservable variables. Professional forecasters construct econometric models and use expert judgment resulting in a precise quantitative estimate for future inflation. And in case of central banks, these estimates have a direct impact on policy decisions such as the setting of interest rates. As regards households, the picture is less clear-cut. We do not really know how economic agents arrive at the expected inflation rates which are provided in survey data or which kind of information they use in the process of expectation formation. Moreover, we cannot be sure whether survey re-sponses are indeed the best proxy for households’ beliefs on future inflation. As we have discussed in Chapter (4), surveys suffer from the “cheap talk”-problem and can be subject to wording and framing effects. In this respect, the use of Google search requests could serve as a promising complementary variable to measure agents’ beliefs, however, internet data also has its limitations. In particular, we do not know whether users actually type “infla-tion” if they seek for information on future price changes, or whether they use more specific keywords when thinking about investing money or buying a particular product.

The measurement of the news media agenda also comes with some problems. Counting how many times the term “inflation” has appeared in a given newspaper seems to be fine as a first approximation. However, this variable neglects the varying size of newspapers so that less can be said about the relative attention inflation receives. In addition, as we

have shown in Chapter (3), it is important not only to capture the amount of news coverage but also its content. Since available software has not yet proven to successfully detect the meaning of written articles, such data still has to be compiled by human resources making it expensive and less readily available. Finally, we would need more precise data on individual news consumption pattern. We have shown that news coverage of inflation by the German television channelRTLhas a much larger effect on younger households, which corresponds to the fact that the average viewer ofRTL is typically younger than viewers ofTagesschau.

However, we know much less about the news preferences of different income, education, or occupation groups.

Based on the results proposed in this dissertation, a number of further research questions seem to be worth investigating.

First, we think that it is important to test whether households actually “act on their beliefs”

(Armantier et al., 2012), i.e. whether the expected inflation rates stated in surveys affect consumption or saving decisions. Quantifying the link from beliefs to actions is important since macroeconomic models assign a prominent role to inflation expectations in explaining, for example, the zero lower bound (Eggertsson and Woodford (2003)) or the jobless recov-ery in the U.S. (Schmitt-Grohe and Uribe, 2013). Only a few studies have so far followed this research direction. Souleles (2004) has shown that consumer sentiment¹ can be useful in forecasting actual consumption spending. Combining a survey with an experiment, Ar-mantier et al.(2012) offer evidence that agents rely on their stated inflation forecasts when deciding on future investments in the experiment. Finally, Bachmann et al. (2012) use in-flation expectations from the Michigan survey and test whether these affect respondents’

“readiness to spend”, which is also captured by the survey.². According to their analysis, higher expected inflation indeed leads to a fall in respondents’ readiness to spend. How-ever, Bachmann et al. (2012) do not show whether households’ self-reported consumption plans are actually materialized.

Second, we think that more research could be done with respect to the policy implications of our results. For example, the analysis in Chapter (3) has shown that TV news have a much larger impact on households’ inflation expectations than newspaper articles, and that differ-ent households rely on differdiffer-ent news sources when forming expectations. It could be worth exploring whether announcements of central banks actually affect all kinds of households in a similar way, or whether some groups, by following different news media, are affected differently by policy statements than others. More broadly, the way expectations are formed can determine policy conclusions derived from macroeconomic models. In Fritsche et al.

1Consumer sentiment is typically measured by survey questions such as the one in the Michigan survey: “Now turning to business conditions in the country as a whole do you think that during the next 12 months we’ll have good times financially, or bad times, or what?”.

2Using the question “About the big things people buy for their homes - such as furniture, a refrigerator, stove, television, and things like that. Generally speaking, do you think now is a good or a bad time for people to buy major household items?”

(2014), we have shown that professional forecasters believe that central banks tolerate small deviations from the point inflation target by following a target zone. As a result, central banks do not have to change interest rates that much if inflation approaches the boundaries of the target zone, since professional forecasters already lower their inflation expectations in advance thereby dampening a possible acceleration of inflation. In this context, it could be worth exploring how an adjustment of the inflation target of central banks affects inflation expectations. In policy debates, it is now often argued that raising the official inflation tar-get to 4% would be beneficial for the economy as a whole (Blanchard et al.,2010,Ball,2013).

However, it is unknown how households would react to such a policy change.

Third, the role of Google search requests might be successfully explored further. Since a number of studies have documented its very good forecasting performance with respect to consumption, it could be worth testing whether this property also extends to inflation. In addition, internet search data can be used as a proxy for households’ inflation expectations, especially in countries that do not benefit from the existence of high quality survey data.

This applies to Germany, in particular, where the only available survey on inflation expec-tations does not ask respondents to provide a quantitative estimate of future price changes, and where the underlying micro data are not accessible. Finally, the role of social interac-tion in determining inflainterac-tion expectainterac-tions should be investigated in more detail, not least because this can give rise to “information cascades” (Akerlof and Shiller,2009). Since only a fraction of the population actively follows the news (Blinder and Krueger,2004), information could be processed by social interaction, i.e. by the transfer of the news media agenda from

“news-followers” to “un-followers”. This research direction would also build the bridge to agenda setting theory stressing the need to consider both cognitive information processing that operates on the individual level, and developments in a broader social context such as group identification or social interaction.