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Cognitive abilities and
inflation expectations
by Francesco D‘Acunto, Daniel Hoang,
Maritta Paloviita and Michael Weber
No. 126 | JANUARY 2019
WORKING PAPER SERIES IN ECONOMICS
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft econpapers.wiwi.kit.eduImpressum Karlsruher Institut für Technologie (KIT) Fakultät für Wirtschaftswissenschaften Institut für Volkswirtschaftslehre (ECON) Kaiserstraße 12 76131 Karlsruhe KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft Working Paper Series in Economics No. 126, January 2019 ISSN 2190-9806 econpapers.wiwi.kit.edu
Cognitive Abilities and Inflation Expectations
By Francesco D’Acunto, Daniel Hoang, Maritta Paloviita, and Michael Weber∗
Over the last few years, interest has re- the variation in their macroeconomic ex-
vived among economists in understanding pectations. Individuals with mid-to-low IQ
how households form and update their ex- levels have absolute forecast errors for 12-
pectations, as well as the determinants of month-ahead inflation rates 2.5 times as
the cross-sectional variation in economic large as individuals with high IQ levels, and
expectations across households (for a dis- about 4 times as large as the average re-
cussion, see Gennaioli and Shleifer (2018); alized inflation rate throughout the sam-
D’Acunto, Prokopczuk and Weber (2019); ple period. D’Acunto et al. (2018b) further
D’Acunto et al. (2018c)). Inflation expec- document mid-to-low IQ individuals are
tations have been at the center stage of this about 4 times more likely to provide round
strand of research, because of their rele- numbers when asked about their inflation
vance as a policy tool, especially when in- forecasts – which might reflect higher un-
terest rates are low (Coibion et al. (2018)). certainty in the forecasts – and are twice as
Forming and updating expectations likely to report implausible values for their
about future macroeconomic variables such average forecast.
as inflation requires the use of cognitive In a related paper, D’Acunto et al.
resources at several stages, ranging from (2018a) further show cognitive abilities are
collecting information about the prevailing an important friction to the effectiveness
inflation rates to forecasting future poten- of economic policies that aim to affect the
tial states of the world and their likelihood. overall economy through managing house-
Cognitive abilities thus appear as a natural holds’ expectations (D’Acunto, Hoang and
potential determinant of the cross-sectional Weber (2016) discuss unconventional fiscal
variation in inflation expectations. policy as one example). The facts that a
Indeed, D’Acunto et al. (2018b) docu- substantial part of a representative popu-
ment in a representative population that lation of economic agents (i) barely form
the variation in cognitive abilities across in- plausible inflation expectations and (ii) do
dividuals is an important determinant of not react to changes in their inflation expec-
tations when making plans about consump-
∗ Carroll School of Management, Boston College, tion and saving choices drive this result.
Chestnut Hill, MA, USA. e-Mail: dacuntof@bc.edu. A direct consequence of policies that aim
Hoang: Department for Finance and Banking, Karl-
sruhe Institute of Technology, Karlsruhe, B-W, Ger-
to stimulate consumption expenditure via
many. e-Mail: daniel.hoang@kit.edu. Palovi- managing inflation expectations is that the
ita: Bank of Finland, Helsinki, Finland. e-Mail: policy measure might be less effective than
Maritta.Paloviita@bof.fi. Weber: Booth School of Busi- a representative-agent model implies. An
ness, University of Chicago, Chicago, IL, USA and
NBER. This research was conducted with restricted ac-
indirect, unintended consequence of policies
cess to data from the Finnish Armed Forces and Statis- that aim to affect behavior via managing
tics Finland. The views expressed here are those of the expectations is, instead, that such policies
authors and do not necessarily reflect the views of the might imply a redistribution of resources
Bank of Finland, Finnish Armed Forces, or Statistics
Finland. We thank the project coordinator at Statis-
from the mid-to-low parts of the distribu-
tics Finland, Valtteri Valkonen, for his help with the tion by cognitive ability to the higher end
data and for very insightful comments. We gratefully of the distribution.
acknowledge financial support from the Deutsche Bun-
desbank. Weber also gratefully acknowledges financial I. IQ: Subcomponents
support from the University of Chicago Booth School of
Business, the Fama Research Fund at the University of
Chicago Booth School of Business, and the Fama-Miller The research described so far has treated
Center. cognitive abilities as a catch-all concept.
12 Cognition though is a complex human char- fective or required substantial investment acteristic and includes several facets that in financial education, cheap advice mech- are not necessarily highly correlated. For anisms such as robo-advising tools indi- instance, individuals who have strong quan- viduals could easily access through their titative cognitive skills need not have also phones might improve the quality of low- strong verbal or visuospatial skills. IQ households’ expectations and choice At the same time, one might expect that (D’Acunto, Prabhala and Rossi (forthcom- all these three facets of cognition are im- ing) and D’Acunto et al. (2019)). portant in the determination of expecta- tions regarding future economic variables. II. Data and Results Quantitative skills are crucial for individu- als to map changes in price levels into infla- In this paper, we propose a first step to tion rates. Visuospatial skills are important understand which types of cognitive abili- because they allow individuals to abstract ties might matter more or less to explain from their personal situation and form plau- the heterogeneity in inflation expectations sible scenarios about future general infla- across individuals. tion and other macroeconomic variables as We build on the empirical setting of well as attach plausible probabilities to D’Acunto et al. (2018b) and D’Acunto et al. these future states of the world. Ver- (2018a), who merge administrative data bal skills might matter because individuals on cognitive ability test scores from the need to obtain information about current, Finnish Armed Forces (FAF) for a repre- past, and potentially future states of the sentative sample of men with unique infor- world through sources such as newspaper mation on their inflation expectations from articles, television, or family and friends. Statistics Finland.1 Grinblatt, Keloharju Understanding which types of cognitive and Linnainmaa (2011) and Grinblatt et al. abilities might matter to explain the ob- (2015) use the data on cognitive abilities in served differences in expectations is still a finance research and discuss in detail the in- widely open question. Answering this ques- centives test takers have to put effect into tion is important to assess the viability of answering the questions. potential interventions that aim to increase For this paper, we exploit the fact that the effectiveness of economic policies. the 120 questions from the FAF test cog- Because short-term interventions are un- nitive abilities across three types, namely, likely to affect the cognitive abilities of eco- quantitative, verbal, and visuospatial abili- nomic agents, policymakers need to under- ties. FAF aggregate the scores within each stand the specific skills agents lack, in or- category and standardizes them within co- der to design policies that could effectively horts of test takers so that the IQ rank- substitute for such skills. For instance, ings follow a stanine distribution. Stanine if agents cannot process the information (STAndard NINE) is a method of scaling about economic variables from newspaper test scores on a nine-point standard scale articles or official central-bank statements, with a mean of five and a standard devi- policymakers might invest in communica- ation of two. The respondents with the tion strategies that aim to make such con- lowest 4% of test scores are at least 1.75 cepts easy to grasp for the broader popu- standard deviations from the mean and are lation (Coibion, Gorodnichenko and Weber assigned a standardized IQ score of 1, and (2019)). Alternatively, information might the 4% with the highest test scores are as- be provided to economic agents in a vivid signed a standardized score of 9. We thus fashion that does not require high cognition observe three scores per individual between or knowledge about basic economic con- 1 and 9 based on the relative performance cepts but relies on agents’ comparison of in each part of the test. their conditions with those of their peers (D’Acunto, Rossi and Weber (2019)). If, 1 D’Acunto et al. (2018b) and D’Acunto et al. (2018a) instead, information treatments were inef- contain detailed descriptions of these data.
3
The verbal part of the test asks individu- cast error across individuals in the same bin
als to compare words and pairs of words and by arithmetic, verbal, and visuospatial cog-
find synonyms and antonyms. In the arith- nitive abilities.2
metic part, individuals have to solve simple Figure 1 plots the average absolute fore-
arithmetic operations, solve verbal prob- cast error by bin of cognitive abilities or-
lems, or compare pairs of numbers. The dered from the lowest level of cognitive abil-
visuospatial part is similar to the Raven’s ities (IQ=1) to the highest level of cognitive
progressive matrices test and requires indi- abilities (IQ=9). Panel A refers to arith-
viduals to identify a missing item that com- metic abilities, panel B to verbal abilities,
pletes a pattern. and panel C to visuospatial abilities.
One might be concerned that the three Note we only have one absolute forecast
scores we obtain are highly correlated error per individual. Hence, to the extent
within individuals and that the different we observe different patterns in average ab-
portions of the test are ultimately unable solute forecast errors across different sub-
to capture different sources of variation in categories of IQ, we conclude that individu-
cognitive abilities across individuals. In als perform differently in different subparts
fact, we find the point estimates for the of the IQ test.
pairwise correlations of the three scores in The three panels of Figure 1 beget a
the individual-level data range from 0.56 to few comments. First of all, across all
0.66. These statistics suggest that even if, three types of cognitive abilities, we detect
indeed, a positive correlation exists between a monotonically decreasing association be-
each pair of scores, we still detect enough tween IQ levels and average absolute fore-
variation across the scores of each individ- cast errors. This fact suggests none of the
ual to make our test meaningful. types of cognitive abilities behaves differ-
We merge this individual-level cognitive- ently from the aggregate score for overall
ability information with the micro-data un- cognitive abilities D’Acunto et al. (2018b)
derlying the Consumer Survey of Statistics discuss in earlier research.
Finland, in which respondents report their The second notable feature of Figure 1 is
numerical 12-month-ahead forecast for in- the three scatter plots have different slopes,
flation on top of several other macro and in- especially for the levels of cognitive abili-
dividual economic expectations and a large ties up to the median bins (IQ=5). Specifi-
set of demographic characteristics. Every cally, the curve is steepest at lower values by
month, the survey asks a representative re- arithmetic IQ followed by verbal IQ and is
peated cross section of approximately 1,500 flattest at lower values by visuospatial IQ.
Finnish individuals questions about general One way to interpret this fact is that the
and personal economic conditions, infla- variation in visuospatial cognitive abilities
tion expectations, and willingness to spend across individuals is less relevant in explain-
on consumption goods. Statistics Finland ing the cross section of inflation forecasts
also collects additional information through relative to the variation in arithmetic and
supplementary questions about households’ verbal IQ.
plans to save and borrow. The sample pe- A third relevant result – not depicted in
riod is from January 2001 to March 2015. Figure 1 – relates to statistical inference.
We use the numerical inflation forecasts at We can reject the null hypothesis that any
the individual level to construct our main of the forecast errors in any bin are equal
outcome of interest – the absolute forecast to zero, as well as the null hypothesis that
error for 12-month-ahead inflation. We de-
fine this variable as the absolute value of 2 Because we compute the absolute value, we treat
the difference between the 12-month-ahead deviations from the realized inflation rate in either direc-
inflation forecast of individual i in a given tion identically. Our results are qualitatively unchanged
if we repeat the whole analysis computing the average
month and the ex-post realized inflation forecast error within each bin and hence allowing for
rate observed in Finland 12 months later. positive and negative forecast errors across individuals
We then compute the average absolute fore- within the same IQ bin to wash away.4
Figure 1. Mean Absolute Forecast Error for Inflation by Subcomponenents of IQ
Panel A. IQ Arithmetic Panel B. IQ Verbal
5
5
Mean Absolute Forecast Error
Mean Absolute Forecast Error
4
4
3
3
2
2
0 2 4 6 8 10 0 2 4 6 8 10
Normalized IQ Arithmetic Normalized IQ Verbal
Panel C. IQ Visuospatial
5
Mean Absolute Forecast Error
3 2 4
0 2 4 6 8 10
Normalized IQ Visuospatial
This figure plots the average absolute forecast error for inflation across IQ levels of Finnish men. Forecast error
is the difference between the numerical forecast for 12-month-ahead inflation and ex-post realized inflation. IQ
is the standardized test score from the Finnish Armed Forces that obtains integer values between 1 and 9.
Panel A reports results for arithmetic IQ, panel B reports results for verbal IQ, and panel C reports results for
visuospatial IQ. The sample period is from January 2001 to March 2015.
the averages across any adjacent bins across III. Concluding Remarks
each of the three sorting schemes are equal
for most bins. This result suggests that Large heterogeneity exists in how indi-
even though the relevance of different types viduals form, update, and act upon their
of cognitive abilities in explaining the cross expectations, which previous research re-
section of forecast errors for inflation might lates to individual-level cognitive abilities.
be higher or lower, higher scores in any We show that all three subcomponents of
of the three components of IQ are system- cognitive abilities we observe – arithmetic,
atically associated with lower forecast er- verbal, and visuospatial – matter for the
rors on average, and hence each component forecast accuracy for inflation, with the ef-
might matter. fect of arithmetic cognitive abilities being
Based on our data, we conclude that strongest.
arithmetic, verbal, and visuospatial cogni- The results could suggest policymak-
tive abilities are all likely to be relevant in ers should design targeted communication
explaining the cross section of inflation ex- strategies for different subpopulations. For
pectations in a representative population of instance, short and vivid messages such
men, even though arithmetic cognitive abil- tweets might be more successful in reaching
ities seem to be most relevant, especially for the lowest part of the population by cog-
those scoring lowest. nitive abilities, whereas more detailed andCOGNITIVE ABILITIES AND INFLATION EXPECTATIONS 5
technical reports could still be relevant to D’Acunto, Francesco, Marcel
shape the expectations and choices of high- Prokopczuk, and Michael We-
IQ individuals. ber. 2019. “Historical Antisemitism,
Moreover, policymakers might propose Ethnic Specialization, and Financial
simple and salient policy measures to en- Development.” Review of Economic
sure large parts of the targeted population Studies.
react to the policy and to alleviate con-
cerns about unintended consequences, such D’Acunto, F, Thomas Rauter,
as a redistribution from lower parts of the Christop Scheuch, and Michael
IQ distribution to higher parts (D’Acunto, Weber. 2019. “Mobile Overdraft Fa-
Hoang and Weber (2018)). cilities and Consumption Behavior:
Evidence from FinTech.” Working
REFERENCES Paper.
Coibion, Olivier, Yuriy Gorod- D’Acunto, F, U Malmendier, J Os-
nichenko, Saten Kumar, and pina, and M Weber. 2018c. “Salient
Mathieu Pedemonte. 2018. “Infla- Price Changes, Inflation Expectations,
tion Expectations as a Policy Tool?” and Household Behavior.” Working Pa-
National Bureau of Economic Research. per.
Coibion, Olivier, Yuryi Gorod- Gennaioli, N, and A Shleifer. 2018. “A
nichenko, and Michael Weber. 2019. Crisis of Beliefs – Investor Psychology
“Monetary Policy Communication and and Financial Fragility.” Princeton Uni-
Inflation Expectations.” Working Paper. versity Press.
D’Acunto, F, Alberto Rossi, and Grinblatt, Mark, Matti Keloharju,
Michael Weber. 2019. “Crowdsourcing and Juhani Linnainmaa. 2011. “IQ
Financial Information to Change Spend- and Stock Market Participation.” The
ing Behavior.” Working Paper. Journal of Finance, 66(6): 2121–2164.
D’Acunto, F, N Prabhala, and Grinblatt, Mark, Seppo Ikäheimo,
Alberto Rossi. forthcoming. “The Matti Keloharju, and Samuli
Promises and Pitfalls of Robo-Advising.” Knüpfer. 2015. “IQ and Mutual
Review of Financial Studies. Fund Choice.” Management Science,
D’Acunto, Francesco, Daniel Hoang, 62(4): 924–944.
and Michael Weber. 2016. “The effect
of unconventional fiscal policy on con-
sumption expenditure.” National Bureau
of Economic Research.
D’Acunto, Francesco, Daniel Hoang,
and Michael Weber. 2018. “Unconven-
tional Fiscal Policy.” AEA Papers and
Proceedings, 108: 519–23.
D’Acunto, Francesco, Daniel Hoang,
Maritta Paloviita, and Michael We-
ber. 2018a. “Human Frictions to the
Transmission of Economic Policy.” Work-
ing Paper.
D’Acunto, Francesco, Daniel Hoang,
Maritta Paloviita, and Michael We-
ber. 2018b. “IQ, Expectations, and
Choice.” Working Paper.Working Paper Series in Economics
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