AR T I C L E

Energy-related financial literacy and electricity
consumption: Survey-based evidence from
Finland

Panu Kalmi1 | Gianluca Trotta1,2 | Andrius Kažukauskas3

1School of Accounting and Finance,
University of Vaasa, Vaasa, Finland
2The Faculty of Engineering and Science,
University of Aalborg Copenhagen,
Kobenhavn, Denmark
3The Faculty of Economics and Business
Administration, Vilnius University,
Vilnius, Lithuania

Correspondence
Panu Kalmi, School of Accounting and
Finance, University of Vaasa, Vaasa,
Finland.
Email: panu.kalmi@uwasa.fi

Funding information
Academy of Finland, Grant/Award
Numbers: 269130, 327241; European
Regional Development Fund, Grant/
Award Number: 01.2.2-LMT-K-
718-02-0007; Liikesivistysrahasto; Yrjö
Jahnssonin Säätiö

Abstract

We provide new insights into (i) the level of energy-

related financial literacy in Finnish households, (ii) the

sociodemographic characteristics that affect energy-

related financial literacy, and (iii) whether energy-

related financial literacy influences household electric-

ity consumption. We use a data set consisting of

energy-related financial literacy questions combined

with monthly electricity consumption data. We draw

from the recent literature on energy-related financial

literacy and suggest two new variables based on subjec-

tive perceptions on energy-related financial literacy.

Gender has a strong association with energy-related

financial literacy. Our results also indicate that house-

holds of respondents with higher levels of energy-

related financial literacy tend to consume less electric-

ity when we control for other factors such as dwelling

and household characteristics. This implies that mea-

sures to promote energy-related financial literacy might

guide consumers' decisions toward energy efficiency

and conservation.

KEYWORD S

electricity use, energy-related financial literacy, households

Received: 17 June 2020 Revised: 16 March 2021 Accepted: 14 June 2021

DOI: 10.1111/joca.12395

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use,

distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

© 2021 The Authors. Journal of Consumer Affairs published by Wiley Periodicals LLC on behalf of American Council on Consumer

Interests.

1062 J Consum Aff. 2021;55:1062–1089.wileyonlinelibrary.com/journal/joca



1 | INTRODUCTION

The problems associated with global warming and the depletion of fossil fuels make the promo-
tion of energy conservation a timely issue. The key role of the residential sector in reducing
energy demand is not negligible: unlocking the potential of the residential sector to reduce
energy consumption can lead to significant abatements in environmental pressures.

Energy efficiency investments such as geothermal heat pumps, wall insulation, double or
triple glazed windows, and “A” class appliances offer considerable promise for reducing energy
consumption; however, consumers have not made such investments to the degree that would
be justified, thus creating the so-called “energy efficiency gap” between expected and actual
investments (Gerarden et al., 2017; Gillingham & Palmer, 2014). Low levels of investments in
energy efficiency have long been associated with market failures, such as credit constraints,
imperfect information, and the landlord-tenant problem (Allcott & Greenstone, 2012). More
recently, economists and psychologists have become interested in other potential reasons for
the persistent energy efficiency gap, such as bounded rationality in the consumer decision-
making process (Pollitt & Shaorshadze, 2013), systematic behavioral biases in consumer
decision-making such as incorrect “perceptions” of fuel cost savings, and a lack of attention to
and information about energy costs (Allcott et al., 2014; Tietenberg, 2009). According
to Brounen et al. (2013), the main reason for these behavioral failures is the lack of knowledge
about energy costs and consumption, although they represent a significant part of household
expenses. Recently, Blasch et al. (2021) developed a new concept of energy-related financial lit-
eracy that is based on the abovementioned assumptions of bounded rationality and other
behavioral biases to measure consumers' cognitive ability to calculate the lifetime costs of
energy efficiency investments. This concept is useful for integrating two key components that
can explain the lack of investment in energy efficiency measures, namely, computational skills
related to the application of financial concepts and awareness, such as of energy prices and
energy consumption.

In this article, we further develop the concept of energy-related financial literacy by intro-
ducing new indicators for it, and we present the first empirical study on the effects of energy-
related financial literacy in Finland. We use the definition of Blasch et al. (2021) and its three
dimensions (energy investment literacy, financial literacy, and cost awareness) as our starting
point for the construction of our concept of energy-related financial literacy. We augment it by
the considerations of Warmath and Zimmerman (2019) by including measures of self-efficacy.
Consistent with the work of Allgood and Walstad (2016), we include a measure describing sub-
jective perception of energy knowledge in our definition. Drawing from Brown and Graf (2013),
we also include a measure of interest in energy-related financial literacy. The inclusion of these
two new empirical measures of energy-related financial literacy is a key contribution we make
to the literature.

While financial literacy has been previously studied in Finland and has been found to be rel-
atively high (Kalmi & Ruuskanen, 2018; Klapper & Lusardi, 2020), the level of energy-related
financial literacy has not been studied in Finland to date. There are several reasons why there
is much to be learned from energy-related financial literacy in Finland. Mainly due to its cold
climate, the final residential energy consumption per capita in Finland is among the highest in
the EU, and residential electricity consumption increased by 54.2% over the period of 1990–
2016 (Eurostat, 2018a). Moreover, domestic consumers in Finland face among the lowest elec-
tricity prices in the EU (Eurostat, 2018b), thus undermining incentives to save energy. In Fin-
land, the retail side is a competitive market, whereas the distribution network is handled by

KALMI ET AL. 1063



Distribution System Operators (DSOs) with their regulated local monopoly (Ruokamo
et al., 2019). Many customers in Finland have separate contracts with a DSO and a supplier.
Customers have combined billing (supply and distribution) only when the supplier and DSO
are part of the same company group (NordReg, 2017). Additionally, the energy efficiency
improvements in the residential space-heating subsector registered in recent years in Finland
did not lead to actual reductions in energy consumption due to various issues, including an
increase in the average size of the stock of dwellings, aging population, rebound effects, and
improved thermal comfort expectations (Trotta, 2020a). Against this background, we collected
survey data on energy-related financial literacy and its components in Finnish households to
examine the level of energy-related financial literacy in Finnish households.

In the theoretical section of this article, we discuss the lessons from the literature of
bounded rationality in energy consumption and financial literacy and how this informs our
approach to energy-related financial literacy. We then review the existing literature on energy-
related financial literacy. Based on our literature review, we propose two new subjective mea-
sures of energy-related financial literacy.

In the empirical part of the analysis, we first discuss the alternative that we investigate
regarding the extent to which gender, age, education, and income are associated with different
aspects of energy-related financial literacy and the degree to which earlier findings by Blasch
et al. (2021), Filippini et al. (2020), and others can be observed in countries with very high elec-
tricity consumption levels, such as in Finland. We then follow the approach of Blasch
et al. (2017) in order to study the relationship of energy-related financial literacy to household-
level energy consumption.

The article proceeds as follows. Section 2 presents the relevant prior literature on bounded
rationality in the energy consumption and efficiency domains, financial literacy, and energy-
related financial literacy. Section 3 describes the data. Section 4 discusses the empirical strategy
employed and the main results in comparison with previous research. Section 5 provides con-
cluding remarks and policy implications.

2 | ENERGY-RELATED FINANCIAL LITERACY
REDEFINED

2.1 | Behavioral issues influencing household energy consumption

Multiple barriers prevent households from investing in energy efficiency solutions and/or
adopting conservation behaviors. Aside from market failures, there are behavioral failures asso-
ciated with limited attention and bounded cognitive abilities that influence consumers'
decision-making and energy use (Allcott & Mullainathan, 2010; Gillingham & Palmer, 2014).

Costa and Kahn (2013) trace several sources of difficulties in realizing energy-saving poten-
tial: first, consumers may lack the necessary information to act in their best interest; second,
even if consumers know in principle what is in their best interest, energy conservation may not
be high on their list of priorities; and third, consumers make suboptimal choices because of the
lack of salience of the energy-saving issue. Other studies provided evidence on households' lim-
ited knowledge about energy bills and the impact of own behaviors on energy consumption.
For example, Ameli and Brandt (2015), through an empirical analysis of the Organization for
Economic Co-operation and Development (OECD) Survey on Household Environmental
Behavior and Attitudes, found that although the respondents were asked to obtain their energy

1064 KALMI ET AL.



bills before answering the survey, only approximately 55% were able to provide information about
their energy spending. In the United States, the participants of a national survey considered energy
curtailment behaviors, such as turning off lights, more effective for saving energy than energy effi-
ciency investments, such as buying energy-efficient appliances (Attari et al., 2010). Although being
only one component of a successful intervention strategy, the authors emphasize the role of accu-
rate information in addressing misconceptions about energy consumption and savings to help peo-
ple make better decisions for their pocketbooks and the planet.

The literature on the impact of information provision on energy consumption has reached
somewhat mixed results. Using an experimental setting, Allcott and Knittel (2019) recently
found no significant effect of providing tailored fuel cost information on purchased vehicles'
average fuel economy. On the other hand, Cerruti et al. (2019) found that awareness regarding
the existence of fiscal incentives to promote the purchase of energy-efficient vehicles affected
consumers' decisions in Switzerland.

Newell and Siikamäki (2014) found that providing information on energy consumption of
water heaters in monetary terms rather than physical units increased the willingness to pay for
energy savings. Similarly, Blasch et al. (2019) found that displaying consumption information
in monetary rather than physical units increased the likelihood that consumers identify the
most energy-efficient household appliances and that more energy-literate consumers are more
likely to benefit from this information.

While there is broad literature on the lack of awareness of energy in terms of both prices
and quantities and on information provisions, few studies have investigated the impact of lim-
ited cognitive abilities on energy use. Such abilities are usefully investigated under the general
rubric of “literacy.” An important policy issue is how the provision of information about energy
consumption behaviors can be influenced through two different channels: improving cognitive
abilities and financial literacy skills and correcting price misperceptions (Allcott &
Kessler, 2019; Brent & Ward, 2018). We first review the literature on financial literacy and show
how this literature can be used to construct measures of energy-related financial literacy. We
then review the existing literature on energy-related financial literacy and how our contribu-
tions are positioned. Finally, we discuss the implications for our empirical work.

2.2 | Relevance of financial literacy to the concept of energy literacy

Probably the most influential contributors to the literature, Lusardi and Mitchell (2014) defined
financial literacy as people's ability to process economic information and to make informed
decisions about various financial issues. In various contributions, Lusardi and Mitchell (2008,
2011) studied this issue by including the so-called big three of financial literacy questions (dis-
cussed in more detail below). This approach defines financial literacy by the knowledge of con-
cepts and the ability to apply these concepts in solving financial problems occurring in
everyday life. There have also been other conceptualizations that have used a much broader set
of questions, for example, Huston (2010) and Houts and Knoll (2020). These articles still very
much focus on the knowledge dimension of the concept. Recently, Warmath and
Zimmerman (2019) used Bloom's domains of knowledge (Bloom et al., 1956) to broaden the
concept of financial literacy to include skills and self-efficacy (Bandura, 1982). Notably,
the mainstream approaches to financial literacy regard attitudinal factors such as cultural pref-
erences, behavioral biases and time preferences as external to the definition of financial literacy.
These factors are considered as external influences to financial behaviors (Huston, 2010).

KALMI ET AL. 1065



In terms of measurement, most empirical approaches to financial literacy heavily stress the
use of knowledge questions (Lusardi & Mitchell, 2014). However, there have been alternative
measures that have been related to financial literacy, perhaps most notably subjective self-
assessments of financial literacy. Allgood and Walstad (2016) provided evidence that subjective
measures can be as strongly linked to behaviors as objective measures. There has been relatively
little discussion on the role of attention in financial literacy. One notable exception here is
Carpena and Zia (2020), who found that financial awareness can be more easily influenced by
financial education than numeracy skills, but numeracy might have stronger influence on
behaviors than awareness. Clearly, this is a topic, that would benefit from further studies.

Financial literacy studies have also uncovered evidence on the determinants of financial lit-
eracy. Not surprisingly, financial literacy has been found to correlate heavily with education
(Lusardi & Mitchell, 2014). Perhaps a more interesting finding in this regard is that there are
systematic differences in financial literacy between men and women. Women score much lower
in objective measures of financial literacy than men, and they also give themselves lower sub-
jective financial literacy scores than men (Bucher-Koenen et al., 2017); there is also evidence
that women are less interested in financial issues than men (Brown & Graf, 2013).

2.3 | Energy-related financial literacy

The literature on energy-related financial literacy is still in its infancy compared with that of
financial literacy. An early contribution was that of DeWaters and Powers (2011), who proposed
a concept of energy literacy that emphasizes general knowledge of energy-related issues and
attitudes toward energy conservation. While in many ways it is a broad and holistic concept, it
is more related to engineering and natural sciences rather than to economics or personal
finance.

More recently, related concepts that focus more narrowly on the economic aspects of energy
consumption were proposed. For Brounen et al. (2013), energy literacy means consumers' abil-
ity to calculate the long-term impacts of energy efficiency investments. Therefore, their focus is
on energy efficiency investment decisions. They also employ the concept of energy awareness,
which they measure by the respondents' awareness of their energy consumption. Broberg &
Kažukauskas (2021) also included awareness of the costs related to the energy consumption of
various appliances in their measure of “attention.” Trotta (2021) constructed an indicator of
awareness of electricity use and consumption, which refers to consumers' attention and under-
standing of electricity bills, prices and costs and shows that consumers with higher levels of
“electricity awareness” tend to consume less electricity.

Blasch et al. (2021) proposed a new idea of energy-related financial literacy by combining
the three different concepts of (i) financial literacy, (ii) the ability to calculate the lifetime costs
of energy efficiency investments (energy literacy), and (iii) cost awareness measures. Their mea-
sures thus encompass both cognitive and computational skills related to the application of
financial concepts in the style of Lusardi and Mitchell (2014) but also broaden the domain by
including issues of awareness in the sense of alertness to relevant parameters, such as energy
prices and the energy consumption of, for example, household appliances. The inclusion of
awareness is likely to reflect its central role in the literature of household energy consumption
in general.

There is some prior empirical evidence on the determinants of energy-related financial liter-
acy. Similar to the literature on financial literacy in general, the previous literature on energy-

1066 KALMI ET AL.



related financial literacy has also highlighted the role of education and gender differences. Most
of the studies have found that women possess lower energy literacy levels than men
(e.g., Blasch et al., 2021; Brounen et al., 2013; Filippini et al., 2020; Martins et al., 2020a, 2020b).

Another interesting issue related to gender divisions in energy use is that in households with
spouses, women spend more time on energy-intensive household labor such as cooking and laun-
dry (IEA, 2018; Petrova & Simcock, 2021) and can often be more influential than men in the pur-
chase of household appliances (Blasch et al., 2021). This is one reason why energy-related financial
literacy, especially concerning energy efficiency investments, is crucial. It is worth mentioning, how-
ever, that energy efficiency is only one attribute in appliance replacement, building envelope insula-
tion, or heating and water systems changes. Comfort, convenience for organizing daily life, safety,
brand, aesthetics, and other nonenergy-related attributes play a significant role in purchasing and
renovation decisions, and their relative importance differs also with respect to the type of energy
efficiency investment (Aravena et al., 2016; de Ayala et al., 2021; Trotta, 2018; Wilson et al., 2015).
Also, energy efficiency investments might be perceived differently by men and women as a conse-
quence of different everyday practices that exist in a house, and these gender practices might reflect
different purchasing and renovation preferences (Tjørring, 2016).

2.4 | Energy literacy and energy consumption

Ultimately, the interest in energy-related financial literature is not to build this knowledge base
for its own sake but to promote the saving of energy. There are several channels through which
higher energy-related financial literacy could be transformed into energy-saving behaviors.
Among these are household investments in renewable energy sources, such as solar panels, geo-
thermal energy, or heat pumps; investments in energy-saving home appliances; and changes in
everyday behaviors, such as switching off the lights or using less hot water. Greater knowledge,
skills to apply the knowledge and greater awareness of the costs and savings would be expected
to correlate negatively with energy consumption, other things equal.

Another dimension in which we broaden the literature is that we consider how the direction
in which the respondents err in their cost awareness influences their energy consumption.
While improving the skills component will likely reduce consumption, the effect of changing
cost awareness might go both ways: consumers who underestimate electricity prices are likely
to reduce consumption, whereas consumers who overestimate prices may actually increase con-
sumption once misperceptions are corrected.

There are some prior works on this. Brounen et al. (2013) did not find any evidence on the
effect of energy literacy and energy awareness on Dutch households' self-reported energy con-
sumption. In contrast, Blasch et al. (2017), who used actual consumption data in lieu of self-
reported data, found lower levels of electricity consumption in Swiss households exhibiting
higher levels of energy and investment literacy. Brent and Ward (2018) found that respondents
who had higher financial literacy made core consistent choices in terms of willingness to pay
for energy efficiency investments.

One challenge in analyzing energy consumption at the household level is that in multi-
person households, energy consumption depends on the behaviors and decisions of other
household members rather than solely on the survey respondent. This is a general problem in
studies making inferences from a single survey respondent to household behavior and is rele-
vant to financial literacy research in general (Lusardi & Mitchell, 2014). We attempt to address
this issue by using household-level data where possible.

KALMI ET AL. 1067



2.5 | A visual model of comparing financial literacy and energy-
related financial literacy

In Figure 1, we present a visual model contrasting energy-related financial literacy with the
standard definition of financial literacy. At the intersection between financial literacy and
energy-related financial literacy, the figure presents the standard definition of financial literacy
drawing on figs. 1 and 2 of Huston (2010). Financial literacy according to that definition con-
sists of financial knowledge and the ability to apply that knowledge to make effective decisions
across a range of financial contexts. We augment Huston's (2010) definition by introducing the
subjective energy literacy measures, addressing self-efficacy issues discussed in Warmath and
Zimmerman (2019). These define financial literacy, which then in turn influences financial
behavior, together with cultural and economic conditions, time preferences, and behavioral
biases (including what is sometimes referred to as financial attitudes).

On the right-hand side, we then give a similar depiction of energy-related financial literacy,
drawing on the description in Blasch et al. (2021). Here, we also include financial knowledge,
where the key issues are very similar to standard financial literacy questions, thereby justifying
the use of standard financial literacy questions in assessing energy-related financial literacy.
These can be augmented by questions measuring the ability to apply financial literacy in
energy-related contexts, thereby suggesting energy investment literacy questions first developed
in Brounen et al. (2013). We also include herein cost awareness, consistent with the Blasch
et al. (2021) definition and due to its central role of awareness in the energy consumption litera-
ture. We augment the Blasch et al. (2021) definition in the spirit of Warmath and
Zimmerman (2019) and Brown and Graf (2013) by including the subjective energy literacy
and interest in energy-related financial literacy, respectively. These considerations together
form our measures of energy-related financial literacy. This in turn affects household energy
consumption, together with other influences, such as cultural and climate issues, economic
conditions, housing conditions, and environmental and energy-saving attitudes and behaviors,
and energy efficient renovations.

FIGURE 1 Visual model of financial literacy and energy-related financial literacy. Adapted from

Huston (2010), Blasch et al. (2021), and Warmath and Zimmerman (2019)

1068 KALMI ET AL.



3 | DATA

We study the connection between energy-related financial literacy and energy consumption by
drawing on a novel survey conducted in collaboration with an electric utility in Finland. The survey
questionnaire was designed in 2016–2017 and is based on an extensive literature review of survey
methodology (e.g., Beck et al., 2009; Bowling, 2005; Chang & Krosnick, 2009; Dillman et al., 2009)
and household surveys related to financial literacy and energy issues (Ameli & Brandt, 2015;
Broberg & Kažukauskas, 2021; Brounen et al., 2013; Lusardi & Mitchell, 2014). It was reviewed by
several national and international experts and pretested on a sample of colleagues in March 2017.1

Between April and May 2017, we collected data by using the online survey tool Webropol 2.0.2

Household customers of Vaasan Sähkö (a Finnish electricity provider) and Vaasan
Sähköverkko (a Finnish electricity distribution company) were asked to participate in a survey
consisting of 57 energy- and finance-related questions, including information regarding socio-
economic and demographic characteristics. In addition, the survey includes questions about
environmental attitudes, dwelling characteristics, and respondents' willingness to obtain more
information about energy consumption, how to save energy, and the operating costs of electric
appliances. An English version of the survey is available in the online Appendix.

Different methods and channels were used to recruit the survey respondents, such as
Vaasan Sähkö's customer magazine, local newspapers, e-mail, and a shopping mall.3 We
first collected the contact information of the individuals who were interested in responding
to the survey. Of the 244 adults who initially expressed interest in participating in the sur-
vey, 184 completed the questionnaire (75%). The questionnaire was provided in Finnish,
Swedish, and English, as most of the respondents lived in Vaasa, which is a bilingual city on
the west coast of Finland. The high penetration of the Internet across the Finnish popula-
tion likely reduced the coverage error; in 2017, 94% of people aged between 16 and 74 used
the Internet4 (88% including people aged between 75 and 895), which was significantly
above the EU average (82%).

Approximately 75% of the respondents were Finnish speakers, while 25% were Swedish
speakers. Only one person completed the questionnaire in English. Of those who submitted a
complete questionnaire, 20 respondents were randomly selected to be awarded a €100 gift card.

The survey data were then linked with the monthly electricity consumption data from
April 2015 to March 2017 provided by Vaasan Sähkö (the Finnish electricity provider) and
Vaasan Sähköverkko (the Finnish electricity distribution company).6 However, these data
were not available for all respondents. Ultimately, we had both complete survey data and
data on electricity consumption for 156 respondents. Because the survey data were collected
at one point only (April–May 2017) but electricity consumption data covered a two-year
period, we made all data cross-sectional by taking the averages of electricity consumption
for these 2 years.

Table 1 provides a summary of the primary data for these 156 observations used in the
empirical analysis, including all dependent and independent variables. To assess the representa-
tiveness of the data, we compared the data to the official survey data of Statistics Finland of
2016 (see Appendix 1). The main discrepancies appear in the education and income variables:
our survey respondents were more educated than the average Finnish adult and less likely to
have a low income (defined as a personal income below €20,000). Moreover, of our survey
respondents, 49.4% lived in single-family or detached housing, whereas the national average is
39.3% of households, and in the Vaasa region, the average is 44.4%. The overrepresentation of
single-family housing is likely an outcome of having wealthier respondents. These kinds of

KALMI ET AL. 1069



biases are common in online surveys (Hoogendoorn & Daalmans, 2009). Although the data
seems to be reasonably representative, the relatively small sample size may limit the possibili-
ties of data analysis, as there is a danger that models become overspecified (Table 1).

TABLE 1 Summary statistics (n = 156)

Variable Mean Standard deviation N

Female 0.47 0.50 73

Male 0.53 0.50 83

Age 18–28 years 0.15 0.36 23

Age 29–39 years 0.20 0.40 31

Age 40–50 years 0.19 0.40 30

Age 51–61 years 0.20 0.40 31

Old age (62+ years) 0.26 0.44 41

Education: BA or more 0.49 0.50 76

Low personal income (�€20,000 p.a.) 0.23 0.42 36

Middle personal income (€20,001–40,000 p.a.) 0.46 0.50 72

High personal income (€40,001 p.a.) 0.31 0.46 48

Low household income (�€40,000 p.a.) 0.38 0.49 59

Middle household income (€40,001–80,000 p.a.) 0.51 0.50 79

Household high income (€80,001 p.a.) 0.12 0.32 18

Rental 0.19 0.40 30

Single/detached housing 0.49 0.50 77

Electric heating 0.35 0.48 55

Floor size (m2) 110.12 51.28

Number of household members 2.28 1.10

Year of construction �1939 0.08 0.28 13

Year of construction 1940–1969 0.16 0.37 25

Year of construction 1960–1999 0.42 0.49 65

Year of construction 2000–present 0.33 0.47 51

Energy investment literacy 1.28 0.66

Financial literacy 2.38 0.83

Number of correct responses 1.40 1.44

No answer dominant 0.53 0.51 83

Overestimate dominant 0.08 0.27 12

Underestimate dominant 0.05 0.22 8

Energy interest 7.61 1.82

Subjective energy literacy 7.18 2.31

Energy consumption 582.60 510.07

Log of energy consumption 5.95 0.98

Note: Mean, standard deviation, and number of observations belonging to binary categories (N).

1070 KALMI ET AL.



4 | EMPIRICAL STRATEGY AND RESULTS

4.1 | Measuring energy-related financial literacy

4.1.1 | Dimensions of energy-related financial literacy

We use the definition of Blasch et al. (2021) and its three dimensions (energy investment liter-
acy, financial literacy, and cost awareness) as our starting point for the construction of our con-
cept of energy-related financial literacy. We augment it by the considerations of Warmath and
Zimmerman (2019) by including measures of self-efficacy (subjective energy literacy, interest in
energy issues). Consistent with the work of Allgood and Walstad (2016), we include a measure
describing subjective perception of energy knowledge in our definition. Drawing from Brown
and Graf (2013), we also include a measure of interest in energy-related financial literacy. Con-
sistent with mainstream definitions of financial literacy (Huston, 2010; Lusardi &
Mitchell, 2014; Warmath & Zimmerman, 2019) and the Blasch et al. (2021) definition of energy-
related financial literacy, we exclude attitudes toward energy consumption from our definition
of energy-related financial literacy.

4.1.2 | Energy investment literacy

Energy investment literacy is focused on making energy-efficient choices. We asked the respon-
dents two questions (presented in Table 2) that assess their ability to choose between two differ-
ent heating systems with the same lifespan but different retail prices and monthly heating bills.
The first question was adapted from Brounen et al. (2013). We also added another question to
reduce the impact of potential superficial and cognitive processing and therefore encourage the
respondents to perform an investment analysis. In the first question (economic lifespan of
15 years), the heating system A would cost €21.750 and model B would cost €19.400, while in
the second question (economic lifespan of 5 years), the heating system A would cost €9.750 and
model B would cost €9.800.

As shown in Table 2, regarding the first question, approximately 69% had a preference for
model B, 14% preferred A, 11% stated that the plans are equally good, and 6% could not say.
The percentage of respondents choosing the option that has the lowest cost over the lifespan
(B) was slightly higher than that found by Brounen et al. (2013). However, the preference for A
might also be due to time preferences.

The second question addresses this issue by shortening the relevant time span from 15 to 5 years.
This made model A slightly more attractive than B; in fact, unless we assume (perhaps unrealisti-
cally) time preferences where individuals actually place greater weight on future than current con-
sumption, no-one would choose model B in the second scenario. However, as the setup suggests that
model B is associated with lower energy use than model A, environmentally conscious consumers
may prefer model B over model A even in a situation where B is more expensive than A.

We capture these considerations in our variable Energy investment literacy, taking values 0–
2, which builds on the idea that a respondent rationally chooses B in the first scenario and A in
the second scenario.7 If the respondent makes both of these choices, we assign the respondent a
value of 2 on this variable. If the respondent makes one of the choices but not the other, we
assign a value of 1. If he/she makes neither of these choices, we assign a value of 0. The mean
of this variable is 1.28 (see Table 1).

KALMI ET AL. 1071



4.1.3 | Financial literacy

We next discuss the standard financial literacy questions popularized by Lusardi and Mitch-
ell (2011). These include questions related to understanding and applying the concepts of the
inflation rate, interest rate, and risk diversification. These questions are shown in Table 3.

The responses to the financial literacy questions, presented in Table 3, indicate a surpris-
ingly high level of financial literacy in this sample: for each question, more than three-quarters
of the respondents replied correctly. Previous research by Kalmi and Ruuskanen (2018) indi-
cated somewhat lower levels of financial literacy in Finland. The high level of financial literacy
in this sample might be a result of the above-average education level in the sample—financial
literacy correlates positively with the education level (Lusardi & Mitchell, 2014).

In the regression analysis, we will use the number of correct responses, taking values 0–3,
as the dependent variable. This variable, called Financial Literacy, takes the mean value of 2.38
(Table 1).

4.1.4 | Cost awareness

The third component of energy-related financial literacy in our study is cost awareness. Here,
we have five different components: the respondent's perception of electricity sales price per

TABLE 2 Energy investment literacy (correct responses in bold)

Energy investment literacy

Response
Trade-off between two models of
heating systems—lifespan of 15 years

Trade-off between two models of
heating systems—lifespan of 5 years

Q1. Think about a hypothetical situation
where you own your home, and your
heating system breaks down and is
beyond repair. As a replacement, you
can choose between two heating
systems. Model A sells for €3750, and the
heating is expected to cost €100 per
month. Model B is more expensive, with
a retail price of €5000, but the heating
will cost €80 per month. You can assume
that both models have an economic
lifespan of 15 years. Which heating
system would you choose?

• Heating system A
• Heating system B
• Both models are equally adequate
• Cannot say

Q2. What would happen if both models
had an economic lifespan of 5 years
(instead of 15 years as assumed
before)? Which heating system would
you prefer?

• Heating system A
• Heating system B
• Both models are equally adequate
• Cannot say

Heating system A 14.1 59.6

Heating system B 68.6 10.3

No preference 10.9 22.4

Cannot say 6.4 7.7

1072 KALMI ET AL.



kWh, the perception of electricity distribution price per kWh, the estimated cost of using an
ordinary dishwasher for 2 h, the cost of using an ordinary oven for 2 h, and the percentage
increase in the heating cost of increasing the desired temperature by two degrees. Table 4 pre-
sents these questions. The respondents either chose to provide an estimate or chose the option
“do not know.” When they provide an estimate, it may be roughly correct, an underestimate, or
an overestimate. In Appendix 2, we explain how we chose the critical values for these prices.

Table 4 also presents the distribution of the responses to each question. Note first that the
modal answer to each question is “do not know.” In 3 out of 5 questions, the majority of respon-
dents chose not to answer the question. Among those who responded, the modal response was
the correct one. This is, of course, dependent on the range of responses we accept as correct.
Our findings indicate that in most cases, the estimates were not too far off. Under- or overesti-
mates of costs were less common, but for the cost of using appliances and heating costs, there
was a larger proportion of overestimates than underestimates.

The upper part of Table 5 presents the distribution of the dominant mode of response, that
is, whether the respondent provided quantitatively more correct responses than over- or
underestimates or no responses, and so on. Approximately one-third of the respondents
tended to be well informed about the costs and gave more correct responses than any other
kind of response. More than one-half of the sample had very little idea of the costs, and the
dominant response was “do not know.” Few respondents tended to systematically over- or
underestimate the costs.

TABLE 3 Financial literacy (correct responses in bold)

Financial literacy

Response Inflation Compound interest rate Risk and diversification

Q1. Suppose you put €1000
into a savings account
with a guaranteed
interest rate of 1% per
year. The inflation rate is
2% annually. You do not
make any further
deposits into this account,
and you do not withdraw
any money. In 1 year's
time, will you be able to
buy:

• The same amount as
today

• Less than you could
buy today

• More than you could buy
today

• Cannot say

Q2. Suppose you put €100
into a savings account
with a guaranteed interest
rate of 2% per year. You
do not make any further
deposits into this account,
and you do not withdraw
any money. Assume that
there is no tax on interest
paid. How much would be
in the account at the end
of 5 years?

• More than €102
• Exactly €102
• Less than €102
• Cannot say

Q3. When you buy a wide
range of stocks, it usually
means a higher risk of
decrease in value than in
investing in one stock
only.

• True
• False
• Cannot say

Correct 85.2 75 77.6

Incorrect 7.7 18.6 13.6

Do not know 7.1 6.4 9

KALMI ET AL. 1073



The lower part of Table 5 presents the distribution of correct responses. This is used as a var-
iable ranging from 0 to 5 to measure cost awareness. Here, the modal response is zero—typi-
cally, the respondents failed to give any answer to the question. Even those respondents who
had at least one correct response seldom had more than a few—only 12% had 4 or 5 correct

TABLE 4 Energy cost awareness

Energy cost awareness

Response Awareness of electricity prices

Electrical energy cost Electrical distribution charge

How many cents per kilowatt hour do
you pay for electrical energy costs,
on average?

Please provide the exact amount or an
estimate.

• Cents per kilowatt hour [………….]
• Cannot say

How many cents per kilowatt hour do you pay
for the electrical distribution charge, on
average, including all taxes and levies?

Please provide the exact amount or an estimate.
• Cents per kilowatt hour [………….]
• Cannot say

Correct 43 28.9

Underestimate 4.5 7.7

Overestimate 4.5 6.4

Do not know 48.1 57.1

Awareness of different operating costs

Oven Heating bill

How much does it cost (in cents) to
use an ordinary oven for 2 h (at
200�C)?

Please provide an estimate.
• Cents [………….]
• Cannot say

What is the percentage (%) by which your
heating bill goes up, on average, if you
increase the temperature of your house by two
degrees in a month?

Please provide an estimate.
• My heating bill goes up by (percent) [………….]
• Cannot say

Correct 18.6 32.7

Underestimate 5.8 6.4

Overestimate 19.2 14.7

Do not know 56.4 46.2

Dishwasher

Q1. How much does it cost (in cents)
to run an ordinary dishwasher for
2 h?

Please provide an estimate.
• Cents [………….]
• Cannot say

Correct 17.3

Underestimate 5.1

Overestimate 20.5

Do not know 57.1

1074 KALMI ET AL.



responses. In this sense, the respondents display quite limited awareness of energy costs and
consumption.

4.1.5 | Interest in energy issues and subjective energy literacy

We broaden the concept of energy-related financial literacy to include more subjective assess-
ments. The first of these questions (Energy interest) was formulated: “How would you rate your
own interest in energy-related matters?” The second question (Subjective energy literacy) was:
“How would you evaluate your own capability to read and understand the electricity bills?”
Both of these questions take values from 1 to 10. The mean of Energy interest is 7.61, and the
mean of Subjective energy literacy is 7.18 (Table 1).

TABLE 5 Distribution of dominant responses and the number of correct answers to different questions (%)

Dominant responses

Correct responses dominant 34.0

Underestimates dominant 5.1

Overestimates dominant 7.7

No answer dominant 53.2

Number of correct answers

0 correct 38.5

1 correct 19.2

2 correct 19.9

3 correct 10.9

4 correct 9.0

5 correct 2.6

TABLE 6 Correlations between energy-related financial literacy variables

Energy
investment
literacy

Financial
literacy

Number of
correct answers

No answer
dominant

Energy
interest

Financial
literacy

0.20**

Number correct
responses

0.17** 0.32***

No answer
dominant

�0.26*** �0.24*** �0.68***

Energy interest 0.16* 0.21** 0.35*** �0.32***

Subjective
energy
literacy

0.23*** 0.35*** 0.40*** �0.41*** 0.50***

***p <0.01.
**p <0.05.
*p <0.1.

KALMI ET AL. 1075



In Table 6, we present the pairwise correlations of our measures of energy-related financial
literacy. All of them appear statistically significant and of expected sign. Generally, the lowest
correlations occurred with the Energy investment literacy—variable. The highest pairwise corre-
lations were between the awareness variables, but this largely occurred because they are code-
pendent by construction. The correlation between the two subjective variables was also
high, 0.50.

4.2 | Determinants of energy-related financial literacy

We next proceed to analyze the determinants of the five different components of energy-related
financial literacy. In this analysis, we control for gender by including the Female dummy, four
age dummies for various categories, one dummy variable for education (BA or higher), two
dummies for personal income, and a dummy for tenant housing. The summary statistics for
these variables can be found in Table 1.

In doing so, we report the average marginal effects from probit models for one binary
dependent variable (No answer dominant); for variables taking more than two values, we pre-
sent the ordered probit (OP) coefficients. These results are presented in Table 7.8

From specification 1, it is apparent that the variation in Energy investment literacy is difficult
to explain using any of the standard variables. The only explanatory variable that is (margin-
ally) significant is the age bracket 18–28 years. This is also the only specification in Table 7
where the likelihood ratio (LR) test indicates that the overall model is not statistically
significant.

The results concerning Financial literacy are more aligned with standard results. We find
that financial literacy is lower among women than men and is higher among more educated
respondents. Moreover, Financial literacy is lower among age category of 29–39 years.

Next, we examine the determinants of cost awareness. Specification 3 presents the results
for the variable Number correct responses, which takes values 0–5. There is a significant relation-
ship with gender (men being more cost-aware than women), age (younger persons being less
cost-aware), and education (the more educated being more cost-aware). In specification 4, we
use the binary variable No answer dominant. Here, only the relationship with gender is signifi-
cant; females are more likely to answer “do not know.”9

Above, we mentioned that the variation in Energy investment literacy is difficult to explain.
It is possible that the questions concerning Energy investment literacy are cognitively more tax-
ing. As noted, the results of Allgood and Walstad (2016) concerning the subjective measures of
financial literacy suggest that such measures can perform as well as objective measures. There-
fore, we report the results concerning these subjective measures concerning Energy interest and
Subjective energy literacy.

From these results, it is apparent that the main variable driving these subjective variables is
gender. Both Energy interest and Subjective energy literacy are much lower for women than men.
There are also some other significant results, notably the variable Tenant is negative and signifi-
cant in Subjective energy literacy (for the only time in these specifications). Education is margin-
ally significant and positive for Subjective energy literacy.

Assessing the entire set of results, we find many similarities when comparing our results
with those found in the literature. The fact that cost awareness measures are related mostly to
education and gender is consistent with prior results, for example, in Blasch et al. (2021) and
Filippini et al. (2020). The results that gender and education strongly affect financial literacy

1076 KALMI ET AL.



are also consistent with the literature reviewed by Lusardi and Mitchell (2014). However, the
inability to explain the variation concerning energy investment literacy differs from both
Brounen et al. (2013) and Blasch et al. (2021). The results indicate that, similar to earlier results
concerning financial literacy (Brown & Graf, 2013; Bucher-Koenen et al., 2017), women are less
interested in energy-related issues than men and give themselves lower subjective perceptions
of energy knowledge scores. Overall, the difference between men and women seems to be the
strongest result arising from this analysis.

TABLE 7 Determinants of energy-related financial literacy (n = 156)

Variable

Energy
investment
literacy

Financial
literacy

Number of
correct
answers

No
answer
dominant

Energy
interest

Subjective
energy
literacy

Female 0.014
(0.198)

�0.346*
(0.204)

�0.872***
(0.198)

0.259***
(0.074)

�0.358**
(0.151)

�0.760***
(0.184)

Age (Ref = ≥62)

18–28 0.604*
(0.345)

�0.248
(0.337)

�0.408
(0.330)

0.108
(0.141)

0.108
(0.308)

0.123
(0.308)

29–39 0.212
(0.284)

�0.592**
(0.289)

�1.119***
(0.291)

0.179
(0.115)

�0.517**
(0.259)

�0.261
(0.259)

40–50 0.089
(0.280)

0.053
(0.300)

�0.666**
(0.275)

0.034
(0.115)

0.276
(0.256)

0.034
(0.255)

51–61 0.155
(0.274)

0.134
(0.290)

0.044
(0.258)

�0.029
(0.113)

0.122
(0.252)

�0.115
(0.251)

Education: BA or
more

0.023
(0.201)

0.365*
(0.208)

0.687***
(0.202)

�0.089
(0.121)

0.208
(0.182)

0.317*
(0.182)

Personal income
(Ref = High
personal income)

Low personal
income

�0.143
(0.298)

�0.428
(0.305)

0.127
(0.290)

�0.088
(0.121)

0.173
(0.268)

�0.211
(0.268)

Middle personal
income

�0.069
(0.237)

0.143
(0.247)

�0.226
(0.224)

0.043
(0.095)

�0.036
(0.212)

�0.353*
(0.214)

Tenant �0.281
(0.277)

0.262
(0.284)

�0.185
(0.272)

�0.024
(0.114)

�0.298
(0.251)

�0.655***
(0.254)

Observations 156 156 156 156 156 156

Pseudo R2 0.013 0.061 0.107 0.085 0.030 0.059

Likelihood ratio 3.76 20.01*** 52.10*** 18.44** 17.60*** 37.93***

Method Ordered
probit

Ordered
probit

Ordered
probit

Probit Ordered
probit

Ordered
probit

Note: In the case of binary probit (No answer dominant), the coefficients are marginal effects. In other columns (ordered probit),

they are coefficients from the probit model. Cutoff values and constant have been omitted. Standard errors in parentheses.
***p <0.01.
**p <0.05.
*p <0.1.

KALMI ET AL. 1077



4.3 | Energy-related financial literacy and energy consumption

Ultimately, interest in energy-related financial literacy is motivated by the concern regarding
whether it is associated with lower electricity consumption. In the final empirical analysis of
this article, we examine the associations between electricity use and the components of energy-
related financial literacy. In this analysis, we control for various household and building-related
characteristics. The dependent variable in this model is the natural logarithm of the electricity
consumption in kilowatt hour per month.

We start Table 8 by providing a benchmark energy literacy regression model without includ-
ing any energy-related financial literacy variables (specification 1). We include largely the same
demographic variables as in the previous regressions (Table 7) with two exceptions: we use
household income instead of personal income. This seems more appropriate, as the behavior of
the entire household influences consumption. Similar to Blasch et al. (2017), we do not include
gender in the specifications. One reason for this is that because 75% of households in the survey
have more than one member (the energy consumption of the household is also determined by
more persons than just the respondent alone). Second, we have no theoretical reasons to expect
gender to influence energy consumption, and it is empirically not a significant determinant.
Third, gender exerts such a heavy influence on financial literacy, including the Female dummy
risks confounding the effects of both gender and financial literacy.

We also include household size and a host of building-related variables: whether it is a sin-
gle/detached house, the square meters of the apartment/house, whether electricity is used as
the main source of heating, and dummies for construction year. We do not include the electric-
ity price, however, because most households in the sample have the same provider and thus
face the same set of prices, leading to limited variation in price.10

In the first specification in Table 8, we see that few demographic variables are significant,
whereas most of the building-specific variables and household size are significant. Electricity
consumption is higher in single and detached houses than in other types of homes and in build-
ings with electric heating. Electricity consumption increases with both floor area and household
size. It is lower in buildings constructed between 1940 and 1969 than in buildings built in the
2000s. Regarding the demographic variables, younger respondents consume less electricity than
older respondents. The education of the respondent and household income are not significant
determinants of energy consumption.

We next add energy-related financial literacy variables one by one. In specification 2, we
add the Energy investment literacy variable. It is insignificant, with a very imprecise coefficient.
In specification 3, we include the variable Financial literacy. Higher levels of financial literacy
are associated with lower energy consumption. The coefficient is significant at the border of the
10% level. A one-point increase in financial literacy (on a scale of 0–3) leads to a reduction in
consumption of an estimated 10%.

In specifications 4–6, we investigate the different cost awareness variables. In specification
4, we insert the variable Number of correct answers, which is associated with significantly low
electricity consumption. The coefficient is significant at the 5% level and indicates that a one-
point increase in the number of correct answers reduces energy consumption by an
estimated 10%.

In specification 5, we insert the binary variable No answer dominant. This variable is signifi-
cant at the 1% level. When the respondent does not have an idea about energy costs, consump-
tion is over 31% higher than that of respondents who provide estimates of energy costs. In
specification 6, we also insert binary variables Underestimate dominant and Overestimate

1078 KALMI ET AL.



T
A
B
L
E

8
D
et
er
m
in
an

ts
of

en
er
gy

co
n
su
m
pt
io
n

(1
)

(2
)

(3
)

(4
)

(5
)

(6
)

(7
)

(8
)

(9
)

E
n
er
gy

in
ve
st
m
en

t
lit
er
ac
y

�0
.0
01
85

(0
.0
78
4)

0.
08
90

(0
.0
82
9)

F
in
an

ci
al

lit
er
ac
y

�0
.1
03
*

(0
.0
62
5)

�0
.0
67
0

(0
.0
66
1)

N
um

be
r
of

co
rr
ec
t
an

sw
er
s

�0
.0
95
4*
*

(0
.0
37
7)

�0
.0
77
2*

(0
.0
43
5)

N
o
an

sw
er

do
m
in
an

t
0.
31
4*
**

(0
.1
01
)

0.
26
5*
*

(0
.1
13
)

O
ve
re
st
im

at
e
do

m
in
an

t
�0

.1
53

(0
.2
13
)

U
n
de
re
st
im

at
e
do

m
in
an

t
�0

.2
02

(0
.2
39
)

E
n
er
gy

in
te
re
st

�0
.0
44
0*

(0
.0
23
9)

�0
.0
16
2

(0
.0
29
5)

Su
bj
ec
ti
ve

en
er
gy

lit
er
ac
y

�0
.0
49
2*

0.
02
86
)

�0
.0
20
7

(0
.0
33
1)

A
ge

(R
ef

=
≥
62
)

18
–2
8

�0
.3
91
**

(0
.1
86
)

�0
.3
91
**

(0
.1
89
)

�0
.4
14
**

(0
.1
86
)

�0
.4
47
**

(0
.1
84
)

�0
.4
51
**

(0
.1
82
)

�0
.4
67
**

(0
.1
84
)

�0
.4
07
**

(0
.1
85
)

�0
.3
97
**

(0
.1
85
)

�0
.4
92
**

(0
.1
89
)

29
–3
9

�0
.2
98
*

(0
.1
75
)

�0
.2
98
*

(0
.1
76
)

�0
.3
35
*

(0
.1
75
)

�0
.4
13
**

(0
.1
77
)

�0
.3
79
**

(0
.1
72
)

�0
.3
54
**

(0
.1
75
)

�0
.3
36
*

(0
.1
75
)

�0
.3
60
**

(0
.1
77
)

�0
.4
72
**

(0
.1
83
)

40
–5
0

�0
.0
64
5

(0
.1
71
)

�0
.0
64
3

(0
.1
71
)

�0
.0
52
7

(0
.1
70
)

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.1
41

(0
.1
70
)

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.1
06

(0
.1
66
)

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.0
65
2

(0
.1
74
)

�0
.0
47
7

(0
.1
69
)

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.0
50
7

(0
.1
70
)

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.1
14

(0
.1
73
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51
–6
1

0.
05
76

(0
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48
)

0.
05
77

(0
.1
49
)

0.
06
31

(0
.1
48
)

0.
06
23

(0
.1
46
)

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06
37

(0
.1
44
)

0.
07
01

(0
.1
46
)

0.
03
70

(0
.1
48
)

0.
07
07

(0
.1
48
)

0.
05
35

(0
.1
48
)

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du

ca
ti
on

:B
A
or

m
or
e

�0
.0
21
1

(0
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04
)

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.0
21
1

(0
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00
08
36

(0
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04
)

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03
84

(0
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09
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7

(0
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(0
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06
81

(0
.1
04
)

0.
05
39

(0
.1
06
)

(C
on

ti
n
ue

s)

KALMI ET AL. 1079



T
A
B
L
E

8
(C
on

ti
n
u
ed
)

(1
)

(2
)

(3
)

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)

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)

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)

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)

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)

H
ou

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h
ol
d
in
co
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(R
ef

=
H
ig
h

h
ou

se
h
ol
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in
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m
e)

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ow

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h
ol
d
in
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m
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16
6

(0
.1
99
)

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16
6

(0
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01
)

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12
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(0
.1
99
)

0.
14
2

(0
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95
)

0.
12
6

(0
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93
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0.
11
7

(0
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0.
12
1

(0
.1
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)

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1

(0
.1
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)

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1

(0
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)

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id
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h
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d
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e

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08
66

(0
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74
)

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08
61

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76
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07
54

(0
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73
)

0.
07
69

(0
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71
)

0.
06
84

(0
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07
19

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0.
10
8

(0
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10
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(0
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1

(0
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et
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om

e
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52
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**

(0
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72
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52
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71
)

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le
ct
ri
c
h
ea
ti
n
g

0.
60
8*
**

(0
.1
12
)

0.
60
8*
**

(0
.1
12
)

0.
61
3*
**

(0
.1
11
)

0.
59
7*
**

(0
.1
10
)

0.
60
6*
**

(0
.1
08
)

0.
59
1*
**

(0
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10
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58
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1080 KALMI ET AL.



T
A
B
L
E

8
(C
on

ti
n
u
ed
)

(1
)

(2
)

(3
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ra
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1.
23

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ot
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n
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m
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in

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w
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/m

on
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).
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an

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<
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01
.

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05
.

*p
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0.
1.

KALMI ET AL. 1081



dominant to determine whether the direction in which the respondents err in their estimates is
related to consumption. We do not find a statistically significant relationship with these issues.

In specifications 7 and 8, we evaluate the relationships between our subjective measures of
energy literacy and energy consumption. Both of these variables are negatively correlated with
consumption. A one-point increase in Interest in energy issues is associated with a 4% reduction
in energy consumption, whereas a one-point increase in Subjective energy literacy is associated
with an estimated 5% reduction in energy consumption.

In the final specification, specification 9, we insert all different aspects of energy-related
financial literacy into the same specification.11 Likely because of the multicollinearity of these
variables, only our measure of cost awareness, Number of correct answers, is significant and only
at the 10% level.

We include different F-tests in Table 8. The overall F-test indicates that the model is highly
statistically significant. However, for specification 1, we test the significance of respondent char-
acteristics and household income and find that these are not significant. The overall model is
thus driven by house characteristics and household size. For the remaining specifications, we
perform and report the F-test for the energy-related financial literacy variables. In most specifi-
cations with just one variable relating to energy-related financial literacy, this is equivalent to
the t-test, and the test produces no additional information. However, for the final specification
9, the F-test of joint significance of energy-related financial literacy variables is significant, but
only at the 10% level.

5 | CONCLUSIONS AND DISCUSSION

This study contributes to a small but growing literature on energy-related financial literacy as a
subset of financial literacy. Households' energy behaviors present significant externalities, espe-
cially in the form of CO2 emissions. An important question is whether households might volun-
tarily curb their electricity consumption if they were more aware of (at least) the private energy
costs and able to calculate the financial costs of different alternative actions.

In our conceptual section, we review the literature on household energy consumption and
especially its relation to skills and awareness. We suggest that the nascent literature on energy-
related financial literacy might be useful in addressing these issues. We first discuss the general
literature on financial literacy and then review the literature on energy-related financial liter-
acy. By contrasting these two strands of literature, we suggest that the previous literature on
energy-related financial literacy could be usefully complemented by considering subjective com-
ponents of energy-related financial literacy.

When we look at the determinants of various components of energy-related financial liter-
acy, we find that there are significant differences between males and females in most dimen-
sions of energy-related financial literacy. These results are closely aligned with what we know
about the determinants of financial literacy (Lusardi & Mitchell, 2014). The crucial role of
women in influencing energy consumption and decisions on purchases of household appliances
suggests that addressing the gender gap in energy-related financial literacy is an important pol-
icy issue. There are other results that are consistent with prior literature (especially the role of
education), but these do not appear to be as important as the role of gender.

We then proceed to investigate the role of energy-related financial literacy in energy-related
household consumption. We find that our energy-related financial literacy measures have a
negative and statistically significant (at least at 10%) relationship with energy consumption

1082 KALMI ET AL.



(with the exception of energy investment literacy). This relationship is especially strong con-
cerning cost awareness measures. The finding that energy-related financial literacy is associated
with lower household energy consumption is consistent with the results of Blasch et al. (2017),
though they are in stark contrast to the findings of Brounen et al. (2013), who used self-
reported data.

The results thus suggest that energy-related financial literacy may be useful in reducing
energy consumption. From a policy perspective, the important question is whether energy-
related financial literacy can be cultivated by educational or informational interventions. There
has been a substantial debate in the financial education literature on the possibility of influenc-
ing financial literacy through educational interventions (Fernandes et al., 2014). The more
recent literature takes the view that financial education can indeed be effective (Kaiser
et al., 2020; Kaiser & Menkhoff, 2017). The effects of education on energy-related financial liter-
acy remain largely untested.

Informational interventions can also improve energy savings at the household level. The
results are somewhat mixed, but most studies have found that information sharing is effective
in promoting energy-saving behaviors. Particularly important in this respect may be the find-
ings of Blasch et al. (2017), who reported that consumers who have higher levels of energy-
related financial literacy are more likely to identify energy savings, thus pointing out comple-
mentarity between information provision and energy-related financial literacy.

There are certain advantages in that awareness is a central variable in affecting consump-
tion. It is likely easier to influence awareness than cognitive skills. In supporting cognitive
skills, the use of various digital calculation tools might be useful.

In any case, even if both energy-related financial literacy skills and awareness could be
raised to a very high level, there might still be possible limitations. The consumption of energy
is constrained by the parameters imposed by technology; for instance, most dishwashers offer a
limited menu of various programs. Even with technically savvy consumers with the latest tech-
nology and high energy-related financial literacy, hard-wired habits developed by routines may
guide their decisions. Informed by theories of practice, a number of studies have highlighted
the crucial role of everyday practices, rhythms, sequences, material arrangements, and embod-
ied experience in practices in shaping domestic energy consumption (e.g., Shove &
Walker, 2014). A recent Danish study (Trotta et al., 2020) showed substantial heterogeneity of
electricity consumption patterns in households with very similar sociodemographic and dwell-
ing characteristics, which are mainly determined by different everyday practices and their order
in time.

Despite the well-documented role of consumer behavior in influencing energy consumption,
technology may also offer solutions, for instance in terms of home automation systems that
may lead to savings without continuous attention by household members. While home automa-
tion systems are often relatively expensive, there might also be low-hanging fruit, such as inex-
pensive devices that gather information about the electricity consumption of household
appliances. If the main objective of policymakers is to reduce the residential energy use even
for people with upward biased electricity cost perceptions or for people who are not responsive
to informational/educational measures, policymakers should continue with the policies that
affect the purchase decisions and the energy performance of new appliances.

Energy-related financial literacy might also become more important in the future due to
issues such as dynamic pricing (which makes the timing of electricity consumption substan-
tially important) or prosuming (where households can sell the surplus energy they produce
back to the distribution network). These enable households that are skillful in terms of energy-

KALMI ET AL. 1083



related financial literacy to benefit financially from their skills. Additionally, higher levels of
energy-related financial literacy could especially benefit vulnerable household members who
struggle with energy bills, are less likely to replace inefficient appliances with new ones or
invest in energy-efficient retrofits, and that, in the absence of any change in behavior, might be
proportionally more disadvantaged by dynamic pricing schemes.

Our approach, informed mostly by economics, particularly emphasizes the financial incen-
tives of energy savings: that consumers are aware of how they can save energy and that they
have skills to implement energy-saving actions. However, consumers may be motivated by
broader considerations than just their own purse. Many consumers are concerned about climate
change and may be interested in pursuing energy-saving actions even without financial incen-
tives to do so. The link between energy-saving attitudes and concern for the environment may
be usefully addressed in future studies.

Although there have been some recent contributions to energy-related financial literacy,
such studies remain limited in number. The methodology and measurement of the topic, as
well as investigations on the impact of education, will develop when more studies and knowl-
edge accumulate. This study helps to assess and consolidate the findings in the literature. One
clear shortcoming of our study is that it contains a relatively small sample. Future studies on
energy-related financial literacy should also address the small sample issue that limits our and
earlier works.

ACKNOWLEDGMENTS
The authors thank the Academy of Finland (projects 269130 and 327241), the European
Regional Development Fund (project no. 01.2.2-LMT-K-718-02-0007), Yrjö Jahnssonin Säätiö,
and the Finnish Foundation for Economic Education for financial support, the representatives
of Vaasan Sähkö, especially Hannu Linna, Olli Arola and Mikaela Jussila for help in data col-
lection, and the editor and three anonymous reviewers of the Journal of Consumer Affairs, the
participants of the IAEE Conference in Vienna, workshop on energy and electricity markets at
the University of Vaasa, energy economics seminar at the ETH Zürich, and Massimo Filippini
for constructive comments.

ORCID
Panu Kalmi https://orcid.org/0000-0002-1359-5109
Andrius Kažukauskas https://orcid.org/0000-0002-8458-2460

ENDNOTES
1 For the entire questionnaire text, see the online Appendix.
2 http://w3.webropol.com/start/.
3 Of the 244 respondents who initially signed up for the survey, 182 registered electronically and 62 did so in
the shopping mall. There was a stand in the shopping mall, and student assistants asked people to register.
The respondents who registered electronically had a higher response rate than those who did so in the mall.

4 https://ec.europa.eu/eurostat/databrowser/view/tin00028/default/table?lang=en.
5 https://www.stat.fi/til/sutivi/2017/13/sutivi_2017_13_2017-11-22_tie_001_en.html.
6 The survey respondents granted permission to access and use their monthly electricity consumption data.
7 This way of defining Energy investment literacy, while consistent with prior literature, can be criticized on the
grounds that in the first scenario, time preferences may lead a person to rationally choose A over B, whereas
in the second scenario, preferences toward environmental protection may lead a person to rationally choose B

1084 KALMI ET AL.



over A. We experimented with an alternative definition of Energy investment literacy that was based on the
idea that a person makes a time-consistent choice. However, this alternative variable did not produce addi-
tional insights in the regression analysis, so we omit the analysis from herein (the results are available from
the authors).

8 The results are virtually identical if we use ordinary least squares estimations instead of ordered probit. We
report here the OP results as they are technically more appropriate. The marginal effects interpretation is
messy in the case of OP, and therefore we report only the probit coefficients for the OP results.

9 The tendency of women being more likely to answer “do not know” is familiar also in the context of financial
literacy; see Bucher-Koenen et al. (2017).

10 Even within the same provider, there is some variation in average prices depending on the contract the
respondents have chosen and the relation between fixed and variable costs in consumption.

11 We use here Number of correct answers as the proxy for energy awareness; the results are similar (though
stronger for awareness) if we use the variable No answer dominant.

12 https://energiavirasto.fi/en/statistics-and-publications.
13 These are from https://www.vattenfall.fi/energianeuvonta/sahkonkulutus/.

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SUPPORTING INFORMATION
Additional supporting information may be found online in the Supporting Information section
at the end of this article.

How to cite this article: Kalmi, P., Trotta, G., & Kažukauskas, A. (2021). Energy-related
financial literacy and electricity consumption: Survey-based evidence from Finland.
Journal of Consumer Affairs, 55(3), 1062–1089. https://doi.org/10.1111/joca.12395

KALMI ET AL. 1087



APPENDIX 1

Table A1

APPENDIX 2: THE DETERMINANTS OF COST AWARENESS 2

The cost awareness variable has five components: awareness of the electricity sales price,
awareness of the electricity distribution price, the use of ovens and dishwashers for a
prespecified period, and the relative increase in heating costs relative to a change in tempera-
ture. Each of these variables is such that it is difficult to have one precise answer to these ques-
tions for reasons that we discuss below.

Concerning the electricity sales price and the electricity distribution price, one of the chal-
lenges is that although most respondents had both sales contracts and electricity distribution
contracts with Vaasan Sähkö and Vaasan Sähköverkko, our sample contained few observations
that had one of these contracts with another electricity provider. Furthermore, Vaasan Sähkö
offers different contracts with different combinations of fixed and variable pricing, and the price
may also depend on the type of housing. Finally, it is not entirely clear whether the respondents
interpreted the question to mean the average or the marginal price.

Data from the Finnish Energy Authority12 indicate that the lowest sales price offered in Fin-
land in March 2017 was 3.98 eurocents per kWh, and the average price was between 6 and

TABLE A1 Comparison of the sociodemographic and dwelling characteristics of the survey data with the

Official Statistics of Finland (%)

Survey data Official statistics

Gender

Male 53.2 48.8

Female 46.8 51.2

Respondent age

18–39 34.6 34.0

40–61 39.1 35.1

>62 26.2 31.0

Education

No BA 51.3 68.4

BA or higher 48.7 31.6

Respondent gross annual income

�€20,000 23.1 39.5

€20,001–€40,000 46.2 36.3

>€50,000 30.1 24.2

Housing

Single/detached housing 49.4 39.4

Rental housing 19.2 32.7

Note: Source: Survey data and Statistics Finland www.tilastokeskus.fi.

1088 KALMI ET AL.



7 eurocents per kWh. Here, we have interpreted responses of between 4 and 10 cents per kWh
as being correct. Concerning electricity distribution prices, the average price in March 2017 var-
ied between 3.6 cents per kWh for single houses with electrical heating and 8.3 cents per kWh
for multifamily properties. Here, we accept the range of correct responses to be between 3 and
10 cents.

The use of an oven for 2 h is estimated to consume 1.5–2 kWh of electricity, so with the
specified electricity prices, the correct cost can be estimated to be approximately 10–40 cents.
For dishwashers, the estimated consumption varies between 0.5 and 1.5 kWh, so we accepted
estimated costs in a range of 4–30 cents.13 Finally, for the heating cost, we used the rule of
thumb that an increase in the desired temperature by one degree raises heating costs by approx-
imately 3–5%. We accepted responses in the range of 5–10% because we asked about a two-
degree temperature increase; some variation in this estimate is expected related to the insula-
tion levels and heating systems of a home. However, any responses below the critical values
were regarded as underestimates, and any responses above them were regarded as
overestimates.

KALMI ET AL. 1089


	Energy-related financial literacy and electricity consumption: Survey-based evidence from Finland
	1  INTRODUCTION
	2  ENERGY-RELATED FINANCIAL LITERACY REDEFINED
	2.1  Behavioral issues influencing household energy consumption
	2.2  Relevance of financial literacy to the concept of energy literacy
	2.3  Energy-related financial literacy
	2.4  Energy literacy and energy consumption
	2.5  A visual model of comparing financial literacy and energy-related financial literacy

	3  DATA
	4  EMPIRICAL STRATEGY AND RESULTS
	4.1  Measuring energy-related financial literacy
	4.1.1  Dimensions of energy-related financial literacy
	4.1.2  Energy investment literacy
	4.1.3  Financial literacy
	4.1.4  Cost awareness
	4.1.5  Interest in energy issues and subjective energy literacy

	4.2  Determinants of energy-related financial literacy
	4.3  Energy-related financial literacy and energy consumption

	5  CONCLUSIONS AND DISCUSSION
	ACKNOWLEDGMENTS
	Endnotes
	REFERENCES