Discussion Paper No. 389
COVID-19 on Total Fertility Rates:
A Comparative Study of High-Income Countries

Mikito Masuda
Komazawa University
Tsukasa Matsuura
Chuo University
August 2023

INSTITUTE OF ECONOMIC RESEARCH
Chuo University
Tokyo, JapanCOVID-19 on Total Fertility Rates:
A Comparative Study of High-Income Countries

Abstract

BACKGROUND: The COVID-19 pandemic has caused rapid changes in fertility rates in highincome countries. Interestingly, it significantly increased fertility in some countries, while
significantly decreased fertility in others.
OBJECTIVE: We explored the countries’ differences in the impact of COVID-19 on TFR.
METHODS: First, we analyzed the trends in fertility rates across high-income countries, dividingthem into five groups: Japan and South Korea, Southern Europe, Western Europe and the UnitedStates, Northern Europe, and Central Europe. Second, we conducted an event study and differencein-differences (DID) analyses, controlling for economic factors such as inflation and unemployment
rates, to explain the observed differences.
RESULTS: The first analysis revealed substantial regional variations, with some regions
experiencing a sharp increase in fertility rates after the COVID-19, whereas others experienced asharp decline. The second set of analyses indicate that rising unemployment rates universally led toa decline in fertility rates across all. Additionally, the influence of inflation on fertility rates varies
across regions, with no significant changes observed before or after the COVID-19 pandemic.
Furthermore, significant regional disparities in the impact of the COVID-19 shock on fertility rates
1were found, even when controlling for unemployment and inflation rates, suggesting that economic
factors alone cannot fully explain these variations.
CONCLUSIONS: While COVID-19 substantially affected fertility rates, the nature of this impact
differed significantly across regions, implying the presence of non-economic factors.

Word: Total fertility rate; COVID-19, event study, DID

2

1. Introduction:
The rapid spread of the COVID-19 pandemic since February 2020 has had a profound impact onvarious aspects of society and the economy globally (Aassave et al. 2021). Numerous studies haveexamined the effects of COVID-19 on various socio-economic domains, including demographic
changes such as fertility rates. Aassve et al. (2020)
divided the regions into three categories: high-income countries, urban areas in low-to middle-income
countries, and rural areas in low-to middle-income countries, and predicted the trends in fertility rates
resulting from the pandemic. These studies suggest that fertility rates would decline in high-income
countries and increase in rural areas of low- to middle-income countries. However, to the best of ourknowledge, only a few studies have specifically investigated how the impact of COVID-19 on fertility
rates and subsequent trends vary across countries. Furthermore, these analyses did not examine causal
relationships.
Figure 1 illustrates that even among high-income countries, the impact of COVID-19 on fertility
rates varies significantly. The effects of the shock on fertility rates tend to manifest approximately 910 months after the initial outbreak. Notable fluctuations in fertility rates have been observed in many
countries from November 2020 to January 2021. Interestingly, despite belonging to the same highincome category, some countries have experienced a substantial increase in fertility rates, whereas
others have experienced a significant decline. Furthermore, when observing subsequent trends, many3

countries appear to converge toward pre-pandemic levels over a certain period; however, countries
such as Japan and South Korea exhibited a continued decline in fertility rates after the COVID-19
period.
Therefore, the aim of this paper is as follows: We categorize countries based on the extent anddirection of the shocks and subsequent changes in fertility rates caused by COVID-19. Subsequently,
we demonstrate that the impact of COVID-19 on fertility rates varies across regional groups. We
investigate the factors underlying these differences by focusing on socioeconomic variables. Throughthese examinations, this study aims to reveal that the changes in fertility rates resulting from COVID19, including the direction of change and subsequent trends, differ significantly among regionalgroups and that these differences can be attributed to variations in socioeconomic factors.
Specifically, this analysis involves the following. First, 14 high-income countries are categorized
into regional groups, considering their geographical and cultural proximity, to confirm the variationsin the impact of COVID-19 on fertility rates across regional groups. Second, using event study
analysis, we examined whether the immediate effects of COVID-19 on fertility rates and subsequent
trends differ among regional groups. Third, using monthly data on unemployment and inflation rates,
which are available for each regional group, we explore whether there are significant regional
disparities in the impact of the COVID-19 shock on fertility rates, even when controlling for
unemployment and inflation rates, and whether the influences of unemployment and inflation rates

4

on fertility rates differ among regional groups before and after the COVID-19 shock by Difference in
Difference (DID).
The implications of this analysis are twofold. By controlling for economic conditions andexamining the variations in immediate effects and subsequent trends resulting from the COVID-19
shock, this study elucidates how variations in family systems and policies among countries contributeto diverse impacts on fertility rates. Furthermore, this study provides insights into whether the effects
of COVID-19 on fertility rates represent temporary shocks or structural changes in each country.

2. Previous Studies
Few studies have focused on cross-country comparisons of the impact of COVID-19 on fertility rates,
and no studies have delved into causal relationships in this field.
One study that has focused on cross-country comparisons is that of Nitsche et al. (2022), which
examines the changes in variance in fertility rates between countries and within regions in countries
before and after the COVID-19 shock. This study utilized monthly data from 241 NUTS2 regions in
28 European countries. The variance decomposition results revealed that the variance in fertility rates
within countries decreased, while the variance between countries increased, indicating an intensified
impact at the national level.
From a cross-country comparison perspective, several studies have explained the impact of5

COVID-19 shock on births through socioeconomic factors. Based on monthly data from 24 European
countries, Pomar et al. (2022) reveal that higher per capita income has a mitigating effect on thedecrease in birth rates caused by the COVID-19 shock. Masuda (2022, 2023) suggests that countries
with strong gender role divisions may experience a more pronounced decrease in fertility rates due tothe pandemic, using monthly data from 14 advanced countries, same as in this study. Kitaki (2022),
using monthly data from various countries, demonstrates that the expansion of the COVID crisis
negatively affected fertility rates through a decrease in trust in others and an increase in poverty rates.
Although not specifically focused on cross-country comparisons, existing studies have analyzed
the relationship between COVID-19 and births. Iwasawa et al. (2021) examine the impact of the
COVID-19 shock on demographic trends in Japan by comparing the actual birth and marriage rates
with their projections. Lappegard et al. (2022) investigate the positive effect of the COVID-19 shockon births in Norway and explore the factors affecting the fertility rate using individual-level data.
Their results indicate that this positive effect primarily operates among women aged 28–35 years andwomen who already have children, who generally have higher birth rates, and are in economicallyand socially stable situations.
Furthermore, some studies have examined the influence of COVID-19 shock on birth intentions
rather than on actual births.
Micro data from Poland (Sienicka et al. 2022), China (Chen et al. 2022), Italy (Micelli et al. 2020,6

Arpino et al. 2021), and Australia (Lazzari et al. 2023, Mooi-Reci et al. 2023), revealed that the
COVID-19 shock had an impact on decision-making regarding childbirth, leading to the decisionmaking process to postpone or abandon childbearing.
In the field of analyzing the effect of COVID-19 on demographic changes other than the fertility
rate, there are studies that focus on the impact of the COVID crisis on marriage and divorce. Komura
and Ogawa (2022) utilize monthly data by prefecture in Japan, and Ghaznavi et al. (2022) analyze
monthly data by region in Japan, demonstrating that the COVID-19 shock reduced the number ofmarriages and divorces. Jung and Lee (2023) utilize region-level monthly data from South Korea andreveal that the COVID-19 shock decreased marriage rates in various regions.
While the aforementioned studies provide valuable information, there is currently no researchanalyzing the causal relationship in terms of international comparisons of the impact of COVID-19
on birth rates. In this study, we first identified the causal relationship between the impact of COVID19 and fertility rate using cross-country data based on event study and DID analyses.

3. Model and Data
3.1 Trends in Fertility rates by Country and Region:
This section explains the model and data used for the estimation. Figure 1 shows the trends in the
total fertility rates in high-income countries before and after the onset of the COVID-19 pandemic.

7

As previously mentioned, significant fluctuations in fertility rates were observed in many countries
from November 2020 to January 2021. Considering the gestation period of approximately 10 months,
it can be inferred that the shocks that affected fertility rates occurred between February and April
2020, when COVID-19 was prevalent worldwide, suggesting a substantial impact of the COVID-19
shock on fertility rates globally.
Interestingly, despite being high-income countries, there are significant variations in how COVID19 has affected fertility rates. For example, France experienced a rapid decline, followed by a sharp
increase, indicating a temporary dip before a subsequent rise, whereas South Korea showed aconsistent decline with minimal fluctuations. By contrast, Portugal witnessed a significant decline,
followed by a sharp increase, a period of stability, and subsequent upward trends.
This demonstrates that countries exhibit diverse responses to shocks caused by COVID-19 in termsof fertility rates. However, some common trends were observed to a certain extent across the regions.
Therefore, we conducted an analysis by categorizing the 14 countries into five regional groups: Japanand South Korea, Southern Europe, Western Europe and the United States, Northern Europe, andCentral Europe1, considering their geographical and cultural proximity. The results are shown in
Figure 2. Among these regional groups, Western Europe and the United States, Southern Europe, andJapan and South Korea experienced a sharp decline in fertility rates immediately after COVID-19,

1 Southern Europe: Italy, Spain, and Portugal; Western Europe and the United States: France, the US, Netherlands, and Belgium;

Central Europe: Germany and Austria; North Europe: Finland, Sweden, and Denmark.

8

while Northern Europe and Central Europe experienced a rapid increase in fertility rates after theshock. Hence, similarities were observed among the regional groups.
However, the regional differences in the impact of COVID-19 on fertility rates may be attributed
to economic factors. For example, regional variations in the economic impact of COVID-19 may
have influenced fertility rates. Nevertheless, the above analysis merely demonstrates the regional
trends in fertility rates before and after COVID-19, and does not consider factors related to changes
in the economic environment caused by the COVID-19 shock.

3.2 Estimation Model
Therefore, to account for economic factors, we utilize monthly data on inflation and unemployment
rates available for each region. We control for unemployment and inflation rates and conducted an
event study analysis to examine the effects of the COVID-19 shock on fertility rates ten months later
using the following model:

𝑌,

=

𝛾 𝐷,
∈{

+ 𝛽𝑋 , + 𝛼 + 𝛿 + 𝑢 ,,.. ,… }In this study, we utilize a model to examine the effects of COVID-19 on the total fertility rate
(TFR) across different regional groups. Variable i represents the regional groups, and t represents a9month. The dependent variable 𝑌 ,, represents the TFR 10 months after the reference point, which

was set as February 2020. We introduce the dummy variable 𝐷 ,to capture the impact of COVID-

19 on the TFR in each regional group at various time points (t-j months from the shock point).
Additionally, we include economic variables 𝑋 , namely the unemployment and inflation rates, tocontrol for their potential influence on fertility rates. The individual effects of the regional groups aredenoted as 𝛼 , while 𝛿 represents the time effects. Terms 𝑢 , represent the residual error componentsof the model.
By employing this framework, we can analyze how the TFR after 10-months changes before andafter the COVID-19 shock, considering both regional and temporal variations. To explore thepotential heterogeneity in the effects of COVID-19 on fertility rates across regions, we conducted an
event study analysis followed by a DID analysis.
Furthermore, we examine whether the impact of economic variables such as unemployment andinflation rates on fertility rates varies across regional groups. Additionally, we investigate whether
these economic variables have different effects on fertility rates before and after the COVID-19 shock.
Estimating these relationships will provide valuable insights into the complex interplay among the
COVID-19 pandemic, regional factors, and economic variables that shape fertility patterns.

𝑌,= 𝛾𝑅𝑒𝑔𝑖𝑜𝑛 × 𝐴𝑓𝑡𝑒𝑟 , + 𝑋 , 𝛽 + 𝛼 + 𝛿 + 𝑢 ,

10

𝑌,

= 𝛾𝑅𝑒𝑔𝑖𝑜𝑛 × 𝐴𝑓𝑡𝑒𝑟 , + 𝑋 , 𝛽 + 𝜃𝐶𝑜𝑢𝑛𝑡𝑟𝑦 × X , + 𝛼 + 𝛿 + 𝑢 ,𝑌,= 𝛾𝑅𝑒𝑔𝑖𝑜𝑛 × 𝐴𝑓𝑡𝑒𝑟 , + 𝑋 , 𝛽 + 𝜏𝐴𝑓𝑡𝑒𝑟 , × X , + 𝛼 + 𝛿 + 𝑢 ,In our estimation, we introduce the variable “Region” as a dummy variable representing four
different regions, with Japan and South Korea as the reference category. The variable "After" is also
included as an indicator variable after February 2020 as one to capture the pre- and post-shock periods.
It is important to note that our analysis is based on a fixed effects model, allowing us to account forunobserved heterogeneity at the country level. To address potential correlations within countries, weemploy clustered robust standard errors in our estimation.

3.3. Data
The data used in our analysis were based on monthly observations. For the TFR in Japan, we obtained
the number of births 2 from the "Vital Statistics Survey" by the Ministry of Health, Labour andWelfare. We divided this by the female population data from the "Population Estimates" by theStatistics Bureau of the Ministry of Internal Affairs and Communications, multiplied it by 5 toaccount for the 5-year age groups (15-49), and further multiplied it by 12 to obtain an annual indicator.
We then applied X-12-ARIMA for seasonal adjustment (without adjustment for weekdays or

2 We use preliminary figures.

11

holidays).
For the TFR in countries other than Japan, we utilized a seasonally adjusted series from the Human
Fertility Database, jointly provided by the Max Planck Institute for Demographic Research inGermany and the Vienna Institute of Demography in Austria3. We use data from January 2018 toJanuary 2023.
Unemployment rate data were obtained from a database from the Organisation for Economic Cooperation and Development (OECD) and were seasonally adjusted. However, consumer price index(inflation rates)4 data were sourced from the United Nations' Monthly Bulletin of Statistics Online
database and were not seasonally adjusted. Nevertheless, as no clear seasonality was observed, weused the original series in our estimation.
Regarding the selection criteria for advanced countries other than Japan, we followed the criteria
used by Masuda (2022, 2023), which include thirteen countries that are relatively similar to Japan interms of economic development among advanced Western countries, as well as culturally similarcountries like South Korea. We did not include countries for which data were not available until thesecond half of 2022.

4. Result

3 It was updated in March 2023.
4 It is an index where the year 2010 is set as 100.

12

4.1 Event StudyFirst, we estimated the models using an event study analysis. Figure 3 shows the results for Japan andSouth Korea. It can be observed that after the occurrence of the COVID-19 shock in February 2020,
the TFR in both countries experienced a rapid decline starting from April and this significant decrease
continued until February 2021. There was a slight tendency for recovery thereafter, but despite there
being months in which the decline was not statistically significant, no month surpassed the level ofFebruary 2020. In other words, in Japan and South Korea, the TFR has consistently remained low
since the COVID-19 shock.
Figure 4 illustrates the results for Southern Europe. A significant decrease in the TFR was observedin February 2020. Before February 2020, the TFR was significantly higher than in this month formost periods. Subsequently, there was a gradual recovery in the fertility rate, but until January 2021,
there was no significant difference compared with February 2020. However, from that point onwards,
the fertility rate showed an upward trend, indicating a recovery surpassing the pre-COVID-19 level.
Figure 5 presents the results for Western Europe and the United States. While there was a temporary
decline following the COVID-19 shock, the fertility rate remained higher than pre-COVID-19 levels
for over a year. However, a downward trend was observed after May 2021.
Figure 6 shows the results for Northern Europe. Before February 2020, the TFR was significantly
lower for several months. However, there was a sharp increase in the fertility rate from February to

13March 2020. Subsequently, there was a declining trend, and approximately one year after the COVID19 shock, the fertility rate became even lower than the pre-COVID-19 level. Figure 7 shows theresults for Central Europe. There was a temporary increase immediately after the COVID-19 shock;however, approximately four months later, the fertility rate returned to a level similar to that before
the shock, and no significant differences were observed thereafter.
By comparing the time series changes in the TFR shown in Figure 2 with the results of the event
study analysis, focusing on the differences between regions before and after the COVID-19 shock bycontrolling for unemployment and inflation rates, several common points were identified. However,the following differences can be observed. First, by examining the regional trends of the TFRs in
Figure 2, Northern Europe and Central Europe exhibit similar patterns, showing a trend of an increasein fertility rates for a few months following the COVID-19 shock, followed by a gradual decline.
However, according to the event study analysis in Figure 6, Northern Europe experienced a sharp
increase immediately after the shock, followed by a sustained decline, resulting in a level lower thanthat in the pre-COVID-19 period after approximately one year. In contrast, Central Europe did notexhibit a declining trend after an initial increase in Northern Europe.
Second, concerning Southern Europe, Figure 2 shows a sharp decline in fertility rates after the
COVID-19 shock, followed by a recovery to a level similar to that before. However, the event study
analysis in Figure 4 indicates that one year after the COVID-19 shock, there was a tendency for14

further increases in fertility rates, surpassing the pre-COVID-19 level. For Japan, South Korea,
Western Europe, and the United States, there were no significant differences between the results in
Figure 2 and the event study analysis. Japan and South Korea experienced a temporary decline infertility rates due to the COVID-19 shock, followed by a slight recovery; however, a structural decline
in fertility rates persisted before and after the shock. Western Europe and the United States witnesseda decline in fertility rates following the COVID-19 shock, followed by an increase, maintaining levels
higher than before. However, after more than a year, a downward trend was observed, returning toprevious levels.
From the event study analysis described above, it is evident that the COVID-19 shock had asignificant impact on fertility rates. However, this impact varied greatly across regions. Furthermore,
there are differences between fertility rate trends in each region and the results of the event study
analysis. One of the causes for this difference could be the control for unemployment and inflation
rates.

4.2 DID
Next, we use a difference-in-differences (DID) analysis that controls for unemployment and inflation
rates to examine not only regional differences in the impact of the COVID-19 shock on fertility rates
but also the effects of unemployment and inflation rates on fertility rates. In addition, we investigate

15whether the effects of unemployment and inflation on fertility rates differ across regions and whether
these effects vary before and after the COVID-19 shock.
Table 1 presents the results of the study. Column (1) shows the results without controlling for theunemployment and inflation rates. Southern Europe, Western Europe, the United States, and Central
Europe showed a significant increase in fertility rates after the COVID-19 shock compared to Japanand South Korea, while no significant difference was observed in Northern Europe. Column (2)presents the results for the controlled unemployment and inflation rates. The unemployment rate hasa significantly negative effect, whereas the inflation rate is not significant. An increase in
unemployment rate leads to a decrease in fertility rates. Columns (3) and (4) include the interaction
terms between region and unemployment or inflation rates. The interaction term between region andunemployment is not significant, indicating that the effect of the unemployment rate on fertility rates
does not vary across regions, as shown in Column (3). However, as Column (4) shows, the CPI has asignificant negative effect, and the interaction term between the CPI and region is positively
significant for Southern Europe, Western Europe, the United States, and Central Europe, while it isnegatively significant for Northern Europe. Examining the marginal effects, an increase of 1% in the
inflation rate leads to an increase of 0.011 in the TFR for Southern Europe, and a decrease of 0.003
0.002 0.024 0.01 for the United States and Western, Central Europe, Northern Europe, and Japan andSouth Korea, respectively. This indicates that the effects of inflation rate on fertility rates also vary16

across regions. Columns (5) and (6) show the interaction terms between the COVID-19 shock andunemployment or inflation rates. These terms were not significant, suggesting that the effects of
unemployment and inflation on fertility rates did not change after the COVID-19 shock.

5. Conclusion
We observed significant changes in fertility rates in 14 advanced countries from November 2020 toJanuary 2021. Considering a pregnancy period of approximately 10 months, it is inferred that
COVID-19 has had a substantial impact on birth behavior, leading to significant regional variations
in fertility rates immediately after the COVID-19 shock. Therefore, we divided the 14 countries into
five regions–Japan, South Korea, Southern Europe, Western Europe, the United States, Northern
Europe, and Central Europe–and examined the trends in fertility rates.
The results revealed that Central and Northern Europe experienced a sharp increase in fertility rates
immediately after the COVID-19 shock, followed by a steep decline. By contrast, Southern Europe,
Western Europe, the United States, Japan, and South Korea showed sharp declines in fertility rates
immediately after the shock, followed by a rapid increase. Notably, Japan and South Korea
experienced a subsequent decline, indicating the continuation of the pre-COVID-19 decreasing trend.
To further investigate these trends, we conducted an event study analysis by controlling for
unemployment and inflation rates, and using fertility rates after a 10-month period as the dependent

17

variable. Japan and South Korea experienced a rapid decline in fertility rates after the COVID-19
shock, with a slight recovery; however, overall, fertility rates remained lower than pre-COVID-19
levels. Conversely, Southern Europe showed a sharp decline after the shock, followed by a recovery
trend, and fertility rates were even higher than the pre-COVID-19 levels. Western Europe and theUnited States experienced a temporary decline, followed by a slight increase, maintaining higher
levels than before the shock. However, more than a year after the shock, fertility rates began to decline
and return to their previous levels. Northern Europe experienced a sharp increase immediately after
the COVID-19 shock, followed by a decline, and recent fertility rates fell below the pre-COVID-19
levels. Central Europe showed a sharp increase after the COVID-19 shock, followed by an immediate
decline, reaching a level similar to pre-COVID-19.
To assess regional differences in fertility rate changes before and after the COVID-19 shock andthe impact of inflation and unemployment rates on fertility rates, we conducted a DID analysis. The
results indicate that unemployment rates had a consistently negative effect on fertility rates,
irrespective of the region or pre/post COVID-19 periods. Inflation rates had a higher impact on
fertility rates in Southern Europe, Western Europe, the United States, and Central Europe than inJapan and South Korea, whereas Northern Europe showed a lower impact. Moreover, even after
controlling for unemployment and inflation rates, the COVID-19 shock's negative effect on fertility
rates remains weaker in Western Europe and the United States, Southern Europe, and Central Europe

18

than in Japan or South Korea. From a causal perspective, it can be interpreted that the COVID-19
shock had a more significant impact on fertility rates in Japan and South Korea.
In summary, this study demonstrates that the COVID-19 pandemic has had a profound shock to
fertility rates worldwide, resulting in varying effects depending on the region. Furthermore, ithighlights the significant influence of unemployment and inflation rates on fertility rates, withvariations in the effects of inflation rates on fertility rates across different regions. However, thisstudy has several limitations, as the regional differences in fertility rates caused by the COVID-19
shock were not entirely explained by controlling for unemployment and inflation rates alone.
Understanding the mechanisms underlying the impact of the COVID-19 shock on fertility rates,
including its directionality and whether the effects are temporary or permanent, remains a subject for
further investigation.

Reference
Aassve, Arnstein, Nicolo` Cavalli, Letizia Mencarini, Samuel Plach and Livi M. Bacci (2020) “TheCOVID-19 pandemic and human fertility,” Science, Vol.369, ISSUE 6502, pp.370-371.
Aassve, Arnstein, Nicolo` Cavalli, Letizia Mencarini, Samuel Plach and Seth Sanders (2021) “Early
assessment of the relationship between the COVID-19 pandemic and births in high income
countries,” PNAS, Vol.118, No.36, pp.1-3.
Arpino, Bruno, Francesca Luppi and Alessandro Rosina (2021) “Changes in fertility plans during the
COVID-19 pandemic in Italy: the role of occupation and income vulnerability,” SocArXiv, pp.119

53.
Chen, Tinggui, Peixin Hou, TiantianWu and Jianjun Yang, (2022) ”The Impacts of the COVID-19
Pandemic on Fertility Intentions of Women with Childbearing Age in China,” Behavioral Sciences,
Vol.12, No.335.
Ghaznavi, Cyrus, Takayuki Kawashima, Yuta Tanoue, Daisuke Yoneoka, Koji Makiyama, Haruka
Sakamoto, Peter Ueda, Akifumi Eguchi and Shuhei Nomura (2022) “Changes in Marriage,
Divorce and Births during the COVID-19 Pandemic in Japan,” BMJ Global Health, Vol.7, Issue
5, pp.1-11.
Iwasawa, Miho, Shiro Koike, Reiko Hayashi, Motomi Beppu and Yu Korekawa (2021) “The COVID19 pandemic and demographic process: What we know and what will happen to future
population,” IPSS Working Paper Series, No.51, pp.1-42. (In Japanese)Jung, Myunggu and D.Susie Lee (2023) “Subnational variations in births and marriages during the
COVID-19 pandemic in South Korea,” Demographic Research, Vol.48, Article 30, pp.867-882.
Kitaki, Hideaki (2022) “The Impact of COVID-19 on Birth Rates and its Socioeconomic Factors,”
NPI Economy and Society Study Group, Research Note, pp.1-13. (In Japanese)
Komura, Mizuki and Hikaru Ogawa, (2022) “COVID-19, marriage, and divorce in Japan,” Review of
Economics of the Household, Vol.20, No.3, pp.831–853.
Lappegård, Trude, Tom Kornstad, Lars Dommermuth and Axel Peter Kristensen, (2023)”
Understanding the positive effects of the COVID-19 pandemic on women’s fertility in Norway,”
Population and Development Review, In press, pp.1–25.
Lazzari, Ester, Anna Reimondos and Edith Gray, (2023) “Did the COVID-19 Pandemic Affect Fertility
Desires in Australia? Understanding Why People Changed Their Attitudes towards Having a First
or Additional Child,” Population and Development Review, In press, pp.1–34.
Masuda, Mikito (2022) “Demographic Changes in Japan and Their Responses during the COVID-19
Pandemic,” NPI Economy and Society Study Group, Commentary 11, pp.1-11. (In Japanese)20Masuda, Mikito (2023) “The Changes in Japan's Fertility Rates after the Coronavirus Pandemic: A
Comparison with South Korea and Western Developed Countries,” IERCU Discussion Paper
384, pp.1-21. (In Japanese)
Micelli, Elisabetta, Gianmartin Cito, Andrea Cocci, Gaia Polloni, Giorgio Ivan Russo, Andrea
Minervini, Marco Carini, Alessandro Natali and Maria Elisabetta Coccia (2020) “Desire forparenthood at the time of COVID-19 pandemic: an insight into the Italian situation”, Journal of
Psychosomatic Obstetrics & Gynecology, Vol.41, No.3, pp.183–190.
Miller, Douglas L. (2023) “An Introductory Guide to Event Study Models,” Journal of Economic
Perspectives, Vol.37, No.2, pp.203-230.
Mooi-Reci, Irma, Trong-Anh Trinh, Esperanza Vera-Toscano and Mark Wooden, (2023) “The
impact of lockdowns during the COVID-19 pandemic on fertility intentions,” Economics andHuman Biology, Vol.48, pp.1-9.
Nitsche, Natalie, Aiva Jasilioniene, Jessica Nisén, Peng Li, Maxi S. Kniffka, Jonas Schöley, Gunnar
Andersson, Christos Bagavos, Ann Berrington, Ivan Čipin, Susana Clemente, Lars
Dommermuth, Peter Fallesen, Dovile Galdauskaite, Dănuţ-Vasile Jemna, Mathias Lerch, Cadhla
McDonnell,
Arno Muller, Karel Neels, Olga Pötzsch, Diego Ramiro, Bernhard Riederer, Saskia te Riele,
Laura Szabó, Laurent Toulemon, Daniele Vignoli, Kryštof Zeman and Tina Žnidaršič (2022)“Pandemic babies? Fertility in the aftermath of the first COVID-19 wave across European
regions,” MPIDR Working Paper WP 2022-027, pp.1-57.
Pomar, Le´o, Guillaume Favre1, Claire de Labrusse, Agathe Contier, Michel Boulvain and David
Baud (2022) “Impact of the First Wave of the COVID-19 Pandemic on Birth Rates in Europe: aTime Series Analysis in 24 Countries,” Human Reproduction, Vol.37, No.12, pp.2921-2931.
Sienicka, Agnieszka, Agata Pisula, Katarzyna K. Pawlik, Joanna Kacperczyk-Bartnik, Pawel Bartnik,
Agnieszka Dobrowolska-Redo and Ewa Romejko-Wolniewicz (2022) “The impact of COVID21

19 pandemic on reproductive intentions among the Polish population,” Ginekologia Polska,
Vol.93, No.5, pp.345-350.

22

Fig 1.

The Trend of TFR by Countries

23Fig 2.

The Trend of TFR by Regime

24

Fig 3.

Event Study Analysis: Japan and Korea

25

Fig 4.

Event Study Analysis: Southern Europe

26Fig 5.

Event Study Analysis: Western Europe and USA

27

Fig 6.

Event Study Analysis: Northern Europe28Fig 7.

Event Study Analysis: Central Europe

29

Table 1 The Impact of Covid-19 on TFR(1)(2)
After:Southern_Euro
0.069 ***
0.059 ***
(0.013)(0.013)After:Western Euro_US
0.071 ***
0.080 ***
(0.015)(0.018)After:Northern_Euro
0.036
0.046
(0.039)(0.034)After:Central_Euro
0.073 ***
0.080 ***
(0.010)(0.013)CPI-0.002(0.002)
Unemployment-0.012 *(0.004)Southern_Euro:Unemp
Western Euro_US:Unemp
Northern_Euro:Unemp
Central:Unemp(3)
0.049 **
(0.014)0.076 ***
(0.017)0.046(0.033)0.086 ***
(0.014)-0.002(0.002)-0.024(0.017)0.000(0.020)0.016(0.015)0.009(0.018)-0.002(0.012)(4)
0.021 *
(0.007)0.069 **
(0.020)0.098 **
(0.030)0.064 ***
(0.007)-0.010 *(0.004)-0.007 *(0.003)(5)0.070 **
(0.023)0.084 ***
(0.016)0.051(0.031)0.081 ***
(0.013)-0.002(0.002)-0.011 *(0.005)0.021 **
(0.005)0.007 **
(0.002)-0.014 ***(0.002)0.008 *
(0.003)

Southern_Euro:CPI
Western Euro_US:CPI
Northern_Euro:CPI
Central_Euro:CPI-0.001(0.002)After:Unemp

0.002(0.002)After:CPI
Monthly DummyN
R2
logLikAIC(6)0.058 *
(0.020)0.072 **
(0.023)0.046(0.036)
0.073 **
(0.019)-0.005(0.003)-0.013 *(0.004)

yes
837
0.971
1486.590-2817.180

yes
837
0.973
1509.685-2859.370

yes
837
0.973
1519.809-2871.618*** p < 0.001; ** p < 0.01; * p < 0.05.
Reference: Japan and Korea
Clustered standard error within parentheses

30

yes
837
0.978
1602.217-3036.435

yes
837
0.973
1510.163-2858.326

yes
837
0.973
1513.459-2864.917

中央大学経済研究所( INSTITUTE OF ECONOMIC RESEARCH, CHUO UNIVERSITY)
代表者 林 光洋 (Director: Mitsuhiro Hayashi)〒192-0393 東京都八王子市東中野 742-1(742-1 Higashi-nakano, Hachioji, Tokyo 192-0393 JAPAN)
TEL: 042-674-3271+81 42 674 3271
FAX: 042-674-3278+81 42 674 3278
E-mail: keizaiken-grp@g.chuo-u.ac.jp
URL: https://www.chuo-u.ac.jp/research/institutes/economic/