TCER Working Paper Series

Who changed food consumption behavior after the COVID-19 pandemic? Empiricalanalysis of Japanese household spending panel data
Shigeru Matsumoto
Thunehiro OTSUKI
September 2022
Working Paper E-173
https://www.tcer.or.jp/wp/pdf/e173.pdf

TOKYO CENTER FOR ECONOMIC RESEARCH
1-7-10-703 Iidabashi, Chiyoda-ku, Tokyo 102-0072, Japan©2022 by Shigeru Matsumoto and Thunehiro OTSUKI.
All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without
explicit permission provided that full credit, including ©notice, is given to the source.

Abstract
The COVID-19 pandemic has had far-reaching consequences in our daily lives. Afterthe pandemic, we were forced to stay at home, which significantly impacted foodconsumption behavior. People reduced their consumption of food-away-from-home (FAFH)
but increased their consumption of food-at-home (FAH) and food delivery services(FDS). This study aims to demonstrate how food consumption behavior has changed
after the COVID-19 outbreak. For this purpose, we analyze the household spending
panel data obtained from Macromill, Inc. The data set includes biweekly foodspending data from 1,448 households living in Tokyo, Tokai, and Kinki areas. Using
the data, we compare household food spending for FAFH, FAH, and FDS before and after
the COVID-19 outbreak. Although people shifted from FAFH to FAH and FDS on averagefollowing the COVID-19 outbreak, the intensity of the shift varies between sampling
periods. Empirical results show that during the state of emergency (the first wave),the average household decreased FAFH expenditure by about 2% year-on-year but
increased FDS expenditure by about 1.3%. We further investigate how the intensity ofthe transition from FAFH to FAH varies across households. Both single-person andsingle-parent households continued to rely on FAFH after the pandemic, whereas
households with parents and children shifted more aggressively from FAFH to FAH thanremaining households. These findings suggest that even during the COVID-19 pandemic,
households with severe time constraints (single-person households and single-parent
households) could not allocate time for meal preparation.

Shigeru Matsumoto
TCER
andAoyama Gakuin University
Economics
Room 828, Building 8, 4-4-25 Shibuya,
Shibuya, Tokyo, 150-8366 Japan
shmatsumoto@aoyamagakuin.jp

Thunehiro OTSUKI
Osaka University
Osaka School of International Public Policy
1-31 Machikaneyama, Toyonaka, Osaka,
560-0043 Japan
otsuki@osipp.osaka-u.ac.jp

Who changed food consumption behavior after the COVID-19 pandemic?
Empirical analysis of Japanese household spending panel data
after COVID-10 outbreak
Shigeru MATSUMOTO*,aProfessor, Aoyama Gakuin University
E-mail: shmatsumoto@aoyamagakuin.jp
Thunehiro OTSUKIb
Professor, Osaka University
E-mail: otsuki@osipp.osaka-u.ac.jp

Abstract
The COVID-19 pandemic has had far-reaching consequences in our daily lives. After the pandemic, we wereforced to stay at home, which significantly impacted food consumption behavior. People reduced theirconsumption of food-away-from-home (FAFH) but increased their consumption of food-at-home (FAH) andfood delivery services (FDS). This study aims to demonstrate how food consumption behavior has changed
after the COVID-19 outbreak. For this purpose, we analyze the household spending panel data obtained fromMacromill, Inc. The data set includes biweekly food spending data from 1,448 households living in Tokyo,
Tokai, and Kinki areas. Using the data, we compare household food spending for FAFH, FAH, and FDS before
and after the COVID-19 outbreak. Although people shifted from FAFH to FAH and FDS on average following
the COVID-19 outbreak, the intensity of the shift varies between sampling periods. Empirical results show thatduring the state of emergency (the first wave), the average household decreased FAFH expenditure by about
2% year-on-year but increased FDS expenditure by about 1.3%. We further investigate how the intensity of thetransition from FAFH to FAH varies across households. Both single-person and single-parent households
continued to rely on FAFH after the pandemic, whereas households with parents and children shifted moreaggressively from FAFH to FAH than remaining households. These findings suggest that even during the
COVID-19 pandemic, households with severe time constraints (single-person households and single-parent
households) could not allocate time for meal preparation.

Key words:

COVID-19, Dietary behavior, Food-at-home, Food-away-from-homeCategory Number: 10, 14
JEL Classification: Q13, I14, D12

Corresponding author: Room 828, Building 8, 4-4-25 Shibuya, Shibuya, Tokyo, 150-8366 Japan. Tel: +81-(0)33409-9640.
b
1-31 Machikaneyama, Toyonaka, Osaka, 560-0043 Japan. Tel: +81-(0)6-6850-6111*,a1

Food consumption after COVID

Who changed food consumption behavior after the COVID-19 pandemic?
Empirical analysis of Japanese household spending panel data

1. Introduction
Coronavirus infection (COVID-19) quickly spread throughout the world after the first infection case wasreported in Wuhan, China, in December 2019, and unprecedentedly impacted our social and economic life.
More than 500 million people were infected as of July 1, 2022, and more than 6 million people had died
(World Health Organization 2022). To curb the spread of the infectious diseases, governments have urged the
public to refrain from going out. They even issued stay-at-home orders during a period of a serious infection,prohibiting leaving the house for anything other than essential daily purchases and medical care. Such
COVID-19 countermeasures caused significant economic harm to the nation. In fact, several internationalorganizations predicted that the COVID-19 could cause the greatest economic harm to the world since theGreat Depression.1
The COVID-19 measures have had a significant impact on the country’s economy and our daily lives. Older
people started to take isolation measures on their own as medical facilities became overburdened with COVID19 patients and less accessible. They stayed at home much longer than they had previously, and they started to
avoid even seeing their children and grandchildren. Meanwhile, companies encouraged employees to work

1

2

International Monetary Fund (2020) projected that the global growth would be – 4.9% in 2020.

Food consumption after COVID

from home, and a far larger number of people began working at home.2 When schools were closed, parents
needed to stay at home to take care of their children. These changes in daily activities have significantly impacted
the way people consume food.
People were concerned about the risk of infection and avoided eating out voluntarily. Later, governments
stated that restaurants should shorten their business hours. Because they had more time at home, some families
increased their home cooking. As the cost of eating out rose and more home time became available due to the
COVID-19 pandemic, households reduced food-away-from-home (FAFH) and increased food-at-home (FAH).
Several studies have already been conducted to investigate the effects of COVID-19 on household foodconsumption behavior. In the early stages of the COVID-19 pandemic, Godard (2021) assessed the impact of
COVID-19 on food retail and food services in Canada, speculating that the roughly 30% of food dollars spenton FAFH would shift to FAH. Chenarides et al. (2021) conducted an online consumer survey in the UnitedStates in May 2020 to investigate food shopping behaviors and consumption during the lockdown. They
confirmed that people bought more groceries than usual due to food-service closures. They also discovered thatpeople increased their use of grocery delivery and pickup services. From mid-March to late April 2020, Ellison
et al. (2021) conducted a household survey in the United States to learn how the COVID-19 pandemic altered
food purchasing decisions. They noticed a decrease in FAFH expenditures and an increase in online grocery
shopping.

According to some surveys, the residential energy consumption increased after the COVID-19 pandemic period.
Sabau (2020) analyzed US energy consumption in the first three months following a lockdown and reported thatenergy consumption in the residential sector increased by 8%. The Jyukankyo Research Institute, Inc. (2020)
confirmed that energy consumption in Japan between April and June 2020 increased by 3.2% per household fromthe same period of the previous year.
2

3

Food consumption after COVID

These aforementioned studies were carried out to better understand the changes in household foodconsumption behavior during the initial period of COVID-19 outbreak. However, they assessed the impact of
COVID-19 based on a survey conducted in the outbreak year. Given the seasonality of eating habits, we believe
it would be difficult to accurately assess the impact of the COVID-19 pandemic based on a survey conductedin a relatively short period. A more accurate assessment of the impacts of COVID-19 necessitates a comparisonof pre- and post-occurrence household food consumption behavior.
This study aims to demonstrate how the COVID-19 outbreak has affected household food consumption
behavior. For this purpose, we analyze household spending panel data from 1,448 households in Japan’s mostdensely populated area. We divided food spending into three categories: (1) FAH spending, (2) FAFH spending,and (3) food delivery service (FDS) spending. We then examine how households’ spending changed before andafter COVID-19. We believe that our data analysis has two advantages. First, using household-level spending
data every two weeks enables us to assess the impact of the government’s COVID-19 countermeasures moreaccurately. Second, combining household characteristics and food spending data allows us to determine whochanged their food consumption behavior after the COVID-19 pandemic.
The results show that the shift from FAFH to FAH and FDS was maximized when the first state of
emergency was declared; the average household decreased FAFH expenditure by about 2% year-on-year but
increased FDS expenditure by about 1.3%. The results also shows that the intensity of the transition from FAFH
to FAH varies across households; both single-person and single-parent households exhibit a small shift, whereas
households with parent and children exhibit a large shift.

4Food consumption after COVID

The remainder of the paper is structured as follows. Section 2 discusses previous research on FAFH and
FAH and the new findings that the present study provides for future research in related fields. Section 3 provides
context for the COVID-19 pandemic in Japan and explains the data used in the subsequent empirical analyses.
Section 4 specifies the empirical model and reports on the empirical results. Finally, Section 5 concludes thepaper by summarizing the empirical findings and discussing the implications for the FAFH and FAH
discussions.

2. Food-at -home and food-away-from-home
The transition from FAH to FAFH is a phenomenon commonly observed in developed countries, andnumerous researchers have studied the factors that influence it. FAH requires more time for food preparation
than FAFH, even though FAFH costs more money. Previous research has demonstrated that the likelihood ofand expenditures for FAFH tend to increase as the value of home time increases, particularly as induced bygreater female labor force participation (Prochaskea and Schrimper 1973; Redman 1980; Kinsey 1983;
McCracken and Brandt 1987; Yen 1993; Jensen and Yen 1996; Nayga 1996; Lo and Tashiro 2011). Meanwhile,
several authors confirmed that the probability and amount of production time for FAH tend to decrease as thevalue of home time increases (Mancino and Newman 2007; Möser 2010).
Additionally, research has been conducted on the interchangeability of time and money in FAH. For
instance, Hamermesh (2007) analyzed time diaries and expenditure data for the United States between 1985
and 2003 to determine how households combine time and goods inputs into FAH. The results indicate that thesubstitution of goods for time becomes difficult as the price of time increases. Hamermesh (2008) analyzed the5

Food consumption after COVID

relative difficulty of goods–time substitution in home food production using time-diary and expenditure data fora sample of American households in 2003 and 2004. Results indicate that goods–time substitution in foodproduction is quite challenging. Meanwhile, Huffman (2011) developed a household production model toestimate the demand for FAH and FAFH, and applied it to the analysis of the U.S. household sector during thesecond half of the twentieth century. The results show that FAH and FAFH are substitutes, whereas the priceand income elasticities of demand for FAH are roughly twice as large as those for FAFH.
The illnesses caused by unhealthy habits impose monetary costs on society. In recent years, much attention
has been paid to policies designed to improve eating and exercise habits. Countries have implemented various
programs to assist people in maintaining a healthy diet and programs to return from FAFH to FAH. For example,
the Supplemental Nutrition Assistance Program in the U.S. was introduced to improve the health of low-income
individuals by assisting with food purchases. Davis and You (2011) argued that the time cost of food preparation
at home is overlooked and posed a question on the program’s effectiveness. An individual’s ability to allocate
time among various activities is limited. It is essential to identify the activities that are interchangeable with meal
preparation. Furthermore, Scharadin and Jeanicke (2020) reported that time spent on secondary childcare isnegatively correlated with the Healthy Eating Index of the household, whereas time spent on primary childcare
is positively correlated.
All of the aforementioned studies confirmed a degree of time substitution between activities. However, theyalso confirmed that the degree varies among households based on income, time cost, occupation, and thepresence of children.

6

Food consumption after COVID

We do not encounter a circumstance in which an exogenous shock uniformly alters time allocation because
time allocation is the ultimate choice for an individual. In addition, we do not encounter a situation in which thevalue of time decreases, as economic development tends to increase its value. Given these facts, we believe that
the COVID-19 pandemic presents a unique opportunity to examine how the relaxation of time constraints
influences household food consumption behavior. Did people return from FAFH to FAH when the COVID-19
outbreak eased time restrictions? If so, what type of person has returned? The following empirical analysis aims
to provide answers to these questions.

3. Background information and Data

3.1. Countermeasures for the COVID-19 outbreak

The time series changes in the number of newly infected individuals in Japan are depicted in Figure
1. The first infected person was confirmed on January 15, 2020. Since the number of infected people
began increasing rapidly by the end of March 2020, the government proclaimed the first state of
emergency for the Kinki and Tokyo metropolitan areas. On April 16, the government subsequently
expanded its coverage nationwide. Although strict prevention measures, including the closure ofelementary and junior high schools, were introduced under this first state of emergency, they werecompletely lifted on May 25. The government continued to urge the public to refrain from moving
between prefectures but eased such self-restraint of movement on June 19. Although the number of
infected people started to increase again soon after the movement restriction is relaxed, the government

7

Food consumption after COVID

started the “Go-to-travel campaign,” a subsidized travel promotion program, on July 22 in the regions
outside of Tokyo. This was done to help the damaged tourism industry. Tokyo residents were allowed touse this travel campaign program beginning on October 1 and running through December 14.
Meanwhile, since the second infection outbreak in the summer, the government has urged restaurants toimplement voluntary infection control measures. For instance, restaurants were asked to shorten theirservice hours from August 3 to 31. Despite beginning late September, the “Go to eat campaign,” which
distributed coupons redeemable at restaurants, ended on November 24.

[Figure 1 near here]

Although there was a temporary increase in eating out as the COVID-19 subsided, the food service
industry remained depressed throughout 2020. The Japanese government, like other countries, provided
a support fund for the food service industry. However, because the support fund was provided in a form
that did not accurately reflect the business scales, large-scale firms received less support than small firms.
For instance, there was little difference in funding between small and large restaurants.

8

Food consumption after COVID

3.2. Household spending panel data

We analyze the panel data on household spending obtained from Macromill, Inc.3 Macromill
Household Spending (MHS) data consists of spending information for survey monitors gathered via
online surveys. Macromill requests that the survey monitors download a household account bookapplication to scan the receipt data. The survey monitors must enter the pertinent information manually if
the receipt information cannot be scanned with the application. Macromill compensates the panel survey
monitors more than usual for online surveys to obtain reliable information. For the present study, we
utilize the biweekly food expenditure data.
The study areas are Tokyo area (Saitama, Chiba, Tokyo, and Kanagawa), Tokai area (Gifu,
Shizuoka, Aichi, and Mie), and Kinki area (Shiga, Kyoto, Osaka, Hyogo, Nara, and Wakayama). To
focus on the households that accurately report spending information with the application, we only
include households that routinely spent 10,000 yen or more on food in the previous two weeks. The
survey period is from January 1, 2019, to December 31, 2020, and the number of the households is
1,448.
The MSH database contains information on socioeconomic characteristics. Table 1 summarizes theinformation regarding the survey monitors and their households for this study. The average age of survey

monitors is 49.3 years old, and their average family size is 2.9 members. The table reveals that 70% ofmonitors are female, 80% are married, and 80% have children younger than 19 years old. As the primary

Macromill, Inc., is a Japan-based company engaged in the provision of marketing research and digital marketing
solutions mainly online.

3

9

Food consumption after COVID

food shopper in many households, the proportion of women would naturally increase relative to that ofmen. There are differences in the food consumption behavior between men and women, with men being
more likely to dine out.

[Table 1 near here]

Table 2 shows the family and job types of the survey monitors. About half of the monitored households
consist of couples and children. About 13.5% of households are single-person households, whereas about
22.3% of households are couple-only. Due to the urban setting of the survey area, the household size of thesurvey monitor is relatively small. In terms of occupation, 34.2% of the survey monitors are homemakers, and25.4% hold part-time jobs. Meanwhile, about one-third of the survey monitors have full-time jobs.

[Table 2 near here]

This study aims to examine the aforementioned food spending panel data to determine whether dietary
habits have changed due to COVID-19. Table 3 shows that the average household’s annual total foodspending was 747,825.4 and 772,267.6 JPY in 2019 and 2020, respectively. Therefore, the annual spending
for all food increased by 3.2%.. In 2019 and 2020, the average household FAH spending was 637,382.0 and
686,684.6 JPY, respectively. Therefore, the annual spending for FAH increased by 7.5%. Meanwhile, from2019 to 2020, FAFH spending fell dramatically. On average, it fell by 36.9%. Finally, there was a 29.3%

10

Food consumption after COVID

increase in FDS spending. The data clearly show that people stop eating at restaurants and began having foodat home.4[Table 3 near here]

4. Empirical model and results

4.1. Time series change in food spending expenditure
We compare FAH, FAFH, and FDS expenditure shares over two weeks between 2019 and 2020. During
the two weeks of the survey, a household may not purchase storable foods such as seasonings and crop.
Therefore, the analysis below is based on the four weeks’ average spending.
Let 𝑦 , , and 𝑦 , , be household h’s expenditures for the kth type of food consumption in period p in2019 and 2020, respectively. We approximate the expenditure share of the kth type of food consumption in2020 by the following logarithmic rate formula.
𝑠 , ,

ln ∑

, ,

(1)

, ,

Because a household may not eat out or use delivery food services during the corresponding period, we
add 1 to both the numerator and denominator.
To demonstrate how food consumption behavior changed following the COVID-19 outbreak, we firstconsider the following seemingly unrelated regression equations model.

4

The rates of change in the consumer price index from 2019 to 2020 were 0% for all items, 1.3% for food, and 2.1%
for eat out (Statistics Bureau of Japan, 2021).

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Food consumption after COVID

𝑠 , ,

𝑠 , ,

𝛼

𝑠 , ,

𝛼

𝛼

𝑠 , ,

𝑠 , ,

𝑠 , ,

𝛽

𝛽

𝛽

𝑟, ,
𝑟, ,

𝑟, ,

𝜞 ,

𝜞 ,

𝜞 ,

𝑫

𝑫

𝑫

𝜫

𝜫

𝜫

𝑹

𝑹

𝑹

𝜀, ,

(2)

𝜀, ,

𝜀, ,

We included the expenditure share in 2019 𝑠 , ,∙ to take account of the difference in food consumption

behavior among households before the COVID-19 outbreak. The variable 𝑟 , , is the logarithmic rate ofchange for total food spending. The associated parameter 𝛽 quantifies the change in the expenditure share of

the kth type of food consumption caused by an increase in total food spending. This variable is also included toaccount for the effect of price fluctuations and changes in household income over the study period.
We include period-specific dummies 𝑫 to account for the difference between sampling periods in 2020.

Parameter 𝜞 quantifies the period-specific effects. We impose the following estimation constraints toaccurately investigate how the choices among three meal types (FAH, FAFH, and FDS) were changed.
𝛾 ,

𝛾 ,

𝛾 ,

(3)

0

This constraint necessitates the reallocation of funds intended to purchase a particular type of meal during eachperiod to purchase a different type of meal. For example, if households reduced their FAFH expenditures, theywould increase their FAH or FDS expenditures.
The infection status and regulatory situation differ by region; hence, we decided to include prefecturedummies 𝑹 in the estimation model. Finally, the error terms of 𝜀 , ,to be corrected.

[Figure 2 near here]12,𝜀 , ,, and 𝜀 , ,are allowedFood consumption after COVID

Unsurprisingly, all three expenditures variables in Equation 3 reached statistical significance at the 1%
level; therefore, the expenditure share in the previous year has explanatory power in the present year.
Although the logarithmic rates of change for total food expenditures reached statistical significance in the
FAH and FAFH models at the 1% level, they reached significance in the FDS model at the 5% level. The
estimated parameters are 𝛽

0.048, 𝛽0.209, and 𝛽

0.087. The results suggest that

FAFH is a luxury good, whereas FAH and FDS are not.

The variation in the expenditure shares of FAH, FAFH, and FDS over the sampling periods is shown in
Figure 1. Each period’s vertical height of the curve is related to the value of the parameter 𝛾 . The figure

shows that the share of FAFH was high at the beginning of the year, compared to the previous year, but began
declining as the infection spread. With a decrease of about 1.8% from the prior year, FAFH’s shareexperienced the greatest decline during the time of the state of emergency declaration. Although a portion of
the decline increased FAH’s share, the majority increased FDS’s share because a large portion of the money
spent on eating out went to FDS.
However, such an increase in FDS was only temporary. People stopped using FDS after the state of

emergency was lifted. Figure 2 shows that households reduced their use of FAFH and FDS while increasing
their use of FAH only. Because FDS includes restaurant take-out meals, restaurants will likely be unable tocompensate for the decline in in-store sales by increasing take-out meal sales.
Figure 2 also shows that FAH’s share remained consistently high throughout the year. However, during
the “Go to Eat Campaign,” FAH’s share decreased. In fact, at the beginning of October, the proportions ofexpenditures for three meal types were roughly the same as the previous year.

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Food consumption after COVID

These findings show that while the state of emergency reduced FAFH, the “Go to Eat Campaign”
increased it. Therefore, the policies were effective at persuading people to change their food consumption
habits, although it is less clear whether they were effective at infection control.

4.2. Who changed food consumption behavior?
In the previous section, we confirmed that, during the state of emergency, the average household reduced
FAFH spending and increased FAH and FDS spending. After the lift of the state of emergency, households
ceased using FDS and compensated for a significant portion of the FAFH reduction with the FAH increase.
We expect that the pattern and intensity of such a shift in food consumption can vary by household. Thissection classifies households into various groups and compare the pattern and magnitude of food consumption
shifts across these groups. Using a subsample of each group, we estimate the empirical model specified in
Equation 3.

[Table 4 near here]

We initially compare the differences in food consumption patterns between married and unmarriedhouseholds. Table 4 shows the change in the expenditure share brought on by the rise in overall foodspending. The table demonstrates that as total food expenditure rises, married and unmarried households
decrease FAH share but increase FAFH’s and FDS’s shares. the able also shows that the share of FAFH
increases much faster in unmarried households than in married ones.

14

Food consumption after COVID[Figure 3 near here]

Figure 3 compares the changes in FAH, FAFH, and FDS spending shares over time. During the state of
emergency, both married and unmarried households reduced FAFH spending while increasing FDS spending.
After the state of emergency was lifted, married households began spending less on FDS than the previous
year, whereas unmarried households continued to spend the same amount. It has been confirmed that marriedhouseholds adjusted their food consumption behavior more smoothly than unmarried households throughout
the year in response to the COVID-19 pandemic.
We next examine how changes in food consumption behavior differed by family type. We specificallycompared the change in expenditure shares among single-person, couple-only, parent–child, senior, andsingle-parent households.
Table 4 compares the changes in expenditure share caused by the increase in total food spending. All three
expenditure share variables became statistically significant in households with a parent and children, but not
all of them did in the remaining households. According to the estimated parameters shown in the table, as total
food expenditure increases, single-person households increase FAFH the fastest, followed by couple-onlyhouseholds. Meanwhile, households with seniors tend to increase FDS faster than other households as total
food expenditure rises.
Subsequently, we look at how food consumption habits changed by household type during the survey
period. Figure 4 only shows changes in FAH spending for the sake of brevity. It shows that although all

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Food consumption after COVID

households increased or decreased their FAH share in a similar pattern, the magnitudes of the changes varied
by household type. The figure specifically shows that households with couples and children adjusted theirfood consumption behavior most smoothly in response to the COVID-19 infection and its countermeasures.
This is because the size of the household comprised of couples and children is often larger than the size of theremaining households, and children who usually ate outside the home began eating at home after COVID-19.
Figure 4 shows that single-person and single-parent households did not significantly increase FAH. Thisfinding suggests that those households struggle to find more time for meal preparation at home.

[Figure 4 near here]

Finally, we examine whether employment status influences food consumption behavior. Respondents’occupations are recorded in the Macromill survey, but their spouses’ occupations are not. Given that mostmale respondents work full-time (Table 2) and that women prepare meals more frequently than men in
Japanese households, we focus on the records of female respondents. The types of employment status arefurther divided into three categories: homemaker (no job and homemaker), part-time job, and full-time job (allremaining). Then, we investigate whether differences in employment status have contributed to the shift infood consumption behavior.

[Figure 5 near here]

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Food consumption after COVID

Table 4 compares the shift in the expenditure share caused by the rise in total food spending by
employment status. Regardless of employment status, we obtained the same sign for all three meal types; thesigns of FAH, FAFH, and FDS are negative, positive, and negative, respectively. The findings imply that as
the household’s total food expenditure increases, they increase FAFH share but decrease FAH and FDS
shares. The obtained parameters show that households with a wife who works part-time experience thegreatest changes in their food consumption patterns in response to an increase in overall food expenditures;
they experience the greatest transition from FAH to FAFH with an increase in income.
We examine how changes in food consumption behavior by employment status occurred during thesurvey period. Again, for brevity, Figure 5 only shows changes in FAH spending. It demonstrates that while
all households experienced an upward or downward trend in their FAH share, the magnitudes of the changes
varied depending on employment status. The figure shows that FAH spending increased significantly inhouseholds where women were homemakers but only slightly in those where women worked full-time.

5. Conclusion
We began spending more time at home during and even after the COVID-19 pandemic, which significantly
impacted food consumption behavior. Using household spending panel data, this study examined how
households changed their food consumption behavior after the COVID-19 outbreak. We observed the shifts
from FAFH to FDS at the start of the COVID-19 outbreak, but such a shift stopped after the state of emergency
was declared. As households became accustomed to the COVID-19 lifestyle, they began compensating for thedecrease in FAFH spending by increasing FAH spending.

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Food consumption after COVID

The results show that the degree of the shift from FAFH to FAH or FDS varied over the sampling period.
Specifically, the shift was maximized when the first state of emergency was declared. According to theestimation results, although FAFH expenditure decreased by approximately 2%, FAH and FDS expenditure
increased by approximately 0.7% and 1.3%, respectively. The magnitude of the shifts among FAH, FAFH, and
FDS was greatly reduced after the state of emergency was lifted.
We also found that the degree of the shift from FAFH to FAH or FDS varies by household; both singleperson and single-parent households exhibit a small shift, whereas households with parent and children exhibit
a large shift.
People must devote time to food shopping and cooking to prepare home meals. Previous studies havereported that households engaged in activities other than food preparation were less likely to increase FAH, evenwhen policies were implemented to make healthy foods more affordable. Although people spent more time athome following the COVID-19 pandemic, single and single-parent households still struggle to find time formeal preparation. Policies that target households with limited time and unable to share household chores withother family members are required to promote healthy eating habits. Unless such support is available, single
person and single-parent households are unlikely to eat healthily.
This research can be extended in several directions. Although this study compares food consumption
behavior between sampling periods, changes in time allocation for each household were not considered in detail.
The analysis using more detailed data on household time allocation is necessary for more accurate empiricalanalysis. This study did not consider the accessibility to FAFH and FDS. Persons who use FAFH or FDS more18

Food consumption after COVID

intensively are more likely to live in the areas where such services are readily available. It is necessary to conduct
a study how the accessibility to FAFH and FDS affects food consumption behavior.

Acknowledgments:
This work was supported by JSPS KAKENHI Grant Numbers 20H01496 and Institute of Economic Researchat Aoyama Gakuin.

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Food consumption after COVID

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Food consumption after COVID

Figure 2. Change in expenditure share
FAH

FAFH

FDS

1.5
1.0
0.5

%

0.0
1-Jan 1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul 1-Aug 1-Sep 1-Oct 1-Nov 1-Dec

-0.5
-1.0
-1.5
-2.0
State of emergency (4/7 – 5/25)

24

Go to eat campaign (9 late – 11/24)

Food consumption after COVID

Figure 3. Married vs. unmarried households

2.0

FAH (Married)

FAFH (Married)

Delivery (Married)

FAH (Unmarried)

FAFH (Unmarried)

Delivery (Unmarried)

1.5
1.0

%

0.5
0.0
1-Jan
-0.5

1-Feb 1-Mar 1-Apr 1-May 1-Jun

1-Jul

1-Aug 1-Sep 1-Oct

1-Nov 1-Dec

-1.0
-1.5
-2.0
-2.5

State of emergency (4/7 – 5/25)

Go to eat campaign (9 late – 11/24)

25

Food consumption after COVID

Figure 4. Change in FAH expenditure by household types
Single person

Couple only

With seniors

Single parent

Couple and children

0.800
0.700

Go to eat campaign (9 late – 11/24)

0.600

%

0.500
0.400
0.300
0.200
0.100
0.000
1-Jan

26

State of emergency (4/7 – 5/25)
1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul

1-Aug 1-Sep 1-Oct

1-Nov 1-Dec

Food consumption after COVID

Figure 5. Change in FAH expenditure by job type(Female respondents only)
Homemaker

Partime job

Fulltime job

0.8
0.7

Go to eat campaign (9 late – 11/24)

0.6

%

0.5
0.4
0.3
0.2
0.1
0
1-Jan

1-Feb 1-Mar

State of emergency (4/7 – 5/25)
1-Apr 1-May 1-Jun 1-Jul

1-Aug

1-Sep

1-Oct

1-Nov 1-Dec

27

Food consumption after COVID

Table 1. Descriptive statistics of the survey monitors
Average or shareStandard error

Minimum

Maximum

Age

49.3

9.7

27

65

Number of persons in a family

2.9

1.2

1

5

Female dummy

0.7

0

1

Marriage dummy

0.8

0

1

Children under 18 dummy

0.7

0

1

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Food consumption after COVID

Table 2. Family type, job type, and prefecture (%)
family typeJob type

PrefecturemalefemaleSingle-person

13.5

No job

0.4

46.2

Saitama

10.6

Couple-only

22.3

Homemaker

12.7

1.7

Chiba

6.5

Parents-and-children

49.3

Student

0.2

0.0

Tokyo

20.0

With seniors

4.6

Part-time job

7.7

31.7

Kanagawa

14.2

Single-parent

6.7

Freelance

2.7

1.1

Gifu

2.0

With non-relatives

1.2

Self-employed

6.7

1.7

Shizuoka

3.3

Others

2.6

President or executive

3.9

0.2

Aichi

11.0

Office worker (clerk)

15.2

9.9

Mie

2.0

Office worker (technical)

25.8

2.0

Shiga

1.7

Office worker (other)

19.6

3.7

Kyoto

3.7

Public servant

3.4

0.4

Osaka

14.6

Other

1.8

1.5

Hyogo

7.8

Nara

1.3

Total

100.0

Total

100.0

100

Wakayama

1.2

Total

100.0

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Food consumption after COVID

Table 3. Annual food spending before and after COVID-19
Before (2019)

After (2020)

Change

JPY

JPY

%

Total

747,825.4

772,267.6

3.2%

Food-at-home (FAH)637,382.0

686,684.6

7.5%

Food-away-from-home (FAFH)

95,150.3

65,804.2-36.9%

Take-out and delivery (FDS)

15,293.1

19,778.8

29.3%

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Food consumption after COVID

Table 4. Change in the expenditure share caused by the total food spending increase (𝜷)Comparison

Marital status

Family type

job type

Groups

FAH

FAFH

FDS

Married-0.048***0.135***-0.106 ***Unmarried-0.063***0.636***-0.026

Single-person-0.096***0.644***-0.083

Couple-only-0.054***0.349***

0.029

Parents-and-children-0.046***

0.097**-0.151***

With senior-0.052-0.0580.521***

Single-parent-0.005-0.068-0.304**

Homemaker-0.038**0.065-0.132**Part-time job-0.061***0.273***-0.087Full-time job-0.032*0.082-0.272***Note. ***, **, and * indicate statistically significant at the 1%, 5%, and 10%, respectively.

31