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Corporate & Business Strategy Review / Volume 3, Issue 2, Special Issue, 2022
296
THE IMPACT OF THE COVID-19
PANDEMIC ON HOUSEHOLD INCOME,
CONSUMPTION, AND SAVING
Saranda Tafa *, Roberta Bajrami **, Gezim Shabani *, Adelina Gashi *
* AAB College, Prishtina, the Republic of Kosovo
** Corresponding author, AAB College, Prishtina, the Republic of Kosovo
Contact details: AAB College, St. Elez Berisha, No. 56 Fushë Kosovë Industrial Zone 10000, Prishtina, the Republic of Kosovo
Abstract
How to cite th is paper: Tafa, S., Bajrami, R.,
Shabani, G., & Gashi, A. (2022). The impact
of the COVID-19 p andemic on household
income, consumption, and s aving [Special
issue]. Corporate & Business Strategy Review,
3(2), 296–305.
https://doi.org/10.22495/cbsrv3i2siart11
Copyright © 2022 The Authors
This work is licensed under a Creative
Commons Attribution 4.0 International
License (CC BY 4.0).
https:// creativecommon s.org/ license s/by/
4.0/
ISSN Online: 2708-4965
ISSN Print: 2708-9924
Received: 01.06.2022
Accepted: 16.12.2022
JEL Classification: E3, G5, D1
DOI: 10.22495/cbsrv3i2siart11
The primary factors that were initially assumed to contribute to
a decline in household income were job losses, which affect
the decrease in consumption (Organisation for Economic Co-
operation and Development [OECD], 2020; Doerr & Gambacorta,
2020). Kosovo’s government has taken measures of social
distancing, having a major impact on households such as
the impact of dismissal due to the closure of businesses
indefinitely. This regime is continuing from the different waves
of COVID-19 variants and the family income as it goes and
decreases. Therefore, the purpose of this study is to measure
the impact of the COVID-19 pandemic on household income
including household consumption and savings for the years
2020–2021. The study uses a quantitative research method,
thus, for primary data collection, the online questionnaire is
used. The latent variable in this paper is the COVID-19
pandemic, while the factors that determine the latent variable
are: savings, job loss, family income before the pandemic, and
consumption expenditures. The study concludes that COVID-19
has a negative and significant impact on family income, saving,
job loss, and consumption expenditures. The results from
the structural equation modeling (SEM) are significant and
the likelihood ratio (LR) test is 47.46. These findings and those
of Martin, Hallegatte, and Walsh (2020), Dossche, Kolndrekaj,
and Slacalek (2021), and Bundervoet, Davalos, and Garcia (2021)
are consistent.
Keywords: COVID-19, Family Income, Savings, Consumption, SEM
Model
Authors’ individual contribution: Conceptualization — S.T., R.B., G.S.,
and A.G.; Methodology — R.B.; Software — S.T. and R.B.;
Validation — S.T.; Formal Analysis — R.B.; Investigation — S.T.
and R.B.; Resources — S.T., G.S., and A.G.; Data Curation — S.T.
and A.G.; Writing — Original Draft — S.T., R.B., G.S., and A.G.;
Writing — Review & Editing — S.T., R.B., G.S., and A.G.;
Visualization — S.T. and A.G.; Supervision — S.T. and R.B.;
Project Administration — S.T. and R.B.
Declaration of conflicting interests: The Authors declare that there is
no conflict of interest.
1. INTRODUCTION
Due to the COVID-19 pandemic, advanced economies
have collected a large stock of household savings,
far above what has previously been observed.
Because of their size, the savings collected since
early 2020 have the potential to shape the post-
pandemic recovery, but the main concern is whether
households will spend heavily once pandemic-
related limitations are lifted and customer
Corporate & Business Strategy Review / Volume 3, Issue 2, Special Issue, 2022
297
confidence returns, or whether other factors will
take their place (Attinasi, Bobasu, & Manu, 2021).
There are many reasons why the COVID-19
pandemic has affected consumer expenditure,
including the following (Corcoran & Waddell, 2020):
first, consumers’ inability to travel, dine out, or
stay in hotels due to stay-at-home orders limited
economic activity across a number of industries;
second, even in the absence of official restrictions,
some people have avoided going out in public for
fear of contracting the virus or unintentionally
spreading it; and third, uncertainty naturally restrains
spending, and the recent rise in unemployment and
the unpredictability in the stock market have added
to this feeling.
Developments in household disposable income
(HDI) offer a convenient window into the effect of
COVID-19 on households. The HDI is the amount of
money accessible for saving and final consumption.
On the other hand, in co mparison to the time prior
to the pandemic, the HDI shows whether households
have been ab le to retain their levels of material
well-being, or at least their capacity to maintain
present levels of consumption and wealth
(Organisation for Economic Co-operation and
Development [OECD], 2020).
In the fourth quarter of 2020, the EU household
saving rate continued to rise significantly year over
year, increasing by +6.6 percentage points (p.p.) over
the previous quarter. The EU’s household final
consumption spending was 7.0% lower than it was
a year earlier, while the household gross disposable
income was 0.6% higher in the fourth quarter of
2020 (compared to the fourth quarter of 2019).
These factors together account for the majority of
this increase (Eurostat, 2021).
At the first appearance of the COVID-19
pandemic, the International Monetary Fund (IMF)
considered that the crisis caused by this disease
would be an economic collapse for the global
economy. Forecasts found that the global economy
will shrink by 6.3% which is the biggest crisis since
the Great Depression. According to data from
the IMF, Kosovo in 2020 suffered economic losses of
5.34%, Albania had an economic decline of 3.5%, and
North Macedonia by 4.53%. In 2021, the economic
recovery of these countries begins with 5% growth in
Albania, 4.5% in Kosovo, and 3.8% in North
Macedonia. This eco nomic growth has not yet
returned these countries to the economic level of
2019. Part of the factual situation of the root is
the households from which it affects consumption
and savings. The virus caused unprecedented losses
in jobs and labour income and, also reduced
household spending, however, extraordinary fiscal
support more than offset these income losses,
so on balance, household income increased
(Schembri, 2021).
The pandemic prevention measures at
the international and national levels, such as social
isolation and business closures, have disrupted
the supply chain and decreased household income
and consumption. As a result, developing nations,
which are dependent on exporting services and have
external and fiscal weaknesses, have suffered.
Bosnia and Herzegovina, Serbia, and North
Macedonia are likely to face milder recessions with
reductions of 3.2%, 3% , and 4.1%, respectively,
compared to pre-COVID-19 estimates, whereas
Montenegro, Albania, and Kosovo are expected to
experience harsher shocks with a drop in gross
domestic product (GDP) of over 8 p.p. (Gjermeni &
Lika, 2020).
Regarding this, governments implemented
measures to safeguard their vulnerable healthcare
systems in response to the rapid spread of
the coronavirus in the Western Balkans. These
included buying medical supplies and equipment,
converting hospitals into COVID-19 centers, turning
concert and sporting venues into temporary field
hospitals, raising salaries for medical staff, and
altering work schedules to protect the staff.
Governments also responded in the second half of
March with lockdowns and partial shutdowns, which
led to the closure of borders, schools, restaurants,
and businesses as well as bans on mass
gatherings, limitations on internal movement, and
the implementation of curfews (OECD, 2020).
The Ministry of Finance, Labor, and Transfers
believes that it is necessary to begin the second
phase of addressing the challenges brought on by
the COVID-19 pandemic after bringing the situation
with COVID-19 under control and supplying
the required numbers of vaccines. As a result, the
ministry suggested various actions to accomplish
the following goals: employment and economic
formalization, with a particular emphasis o n
enhancing the participation of women and young
people in the eco nomy; enhancing the composition
of GDP by favoring specific economic sectors,
particularly those involved in the production, and
enhancing the trade balance of the nation; balanced
and all-encompassing economic growth that is
ensured to be accompanied by an increase in
important welfare metrics; preserving long-term
viability and reducing the country’s budgetary
vulnerabilities through greater cooperation with
the donor community, restraint of domestic debt
growth, and maximization of benefits to households
and the economy.
The Economic Recovery Package was
420 million euros, where 190 million euros were
from the state budget, whereas 230 million euros
were financing from borrowing (Government of
the Republic of Kosovo, 2020).
Taking into account the serious consequences
of the COVID-19 pandemic, as presented above,
the state of Kosovo has taken the necessary
measures to support economic agents in all its
dimensions. Behind these developments, special
attention is paid to the income of citizens to ensure
their livelihood. In this regard, the main purpose of
this study is to analyze the impact of the COVID-19
pandemic on household income, household
consumption, and household savings.
The following research questions are
formulated for this study:
RQ1: Has the COVID-19 pandemic had a negative
impact on household income?
RQ2: Has the COVID-19 pandemic had a negative
impact on household consumption?
RQ3: Has the COVID-19 pandemic had a negative
impact on household savings?
The 4.4% economic growth experienced by
Kosovo in 2019 and co mparable growth in prior
years was largely driven by consumption and state
spending; as a result, while public spending has
been impacted by lower tax revenue due to company
Corporate & Business Strategy Review / Volume 3, Issue 2, Special Issue, 2022
298
inactivity, co nsumption has been less affected.
In Kosovo, about 30% of all occupations are in
the public sector, where the average pay is
significantly higher than in the private sector.
As a result, public sector wages are a significant
contributor to consumption (Lluka, 2020).
For the Kosovar context, Ziberi, Rexha, and
Gashi (2021) researched the effects of the COVID-19
pandemic on personal consumption expenditures
(PCE). A sample of 233 respondents to an o nline
survey that was distributed at random via social
media was used for the study’s primary data
collection. According to the study’s findings,
the COVID-19 pandemic affected personal
consumption spending in t he Re public of Kosovo by
changing consumer preferences from luxury to basic
goods. According to the study, citizens will become
aware of their previously planned spending as soon
as the anti-COVID-19 actions are made public.
Christelis, Georgarakos, Jappelli, and Kenny
(2020) used data from the Consumer Expectations
Survey, which interviews 10,000 households monthly
across the six largest economies in the euro area,
and discovered significant differences in pandemic-
induced financial concerns of households across
population subgroups and countries, with financial
concerns being substantially greater for younger,
female, and low-income people in places where
the first wave of the pandemic hit. The study also
emphasizes a significant portion of the decrease in
total household spending in 2020, de monstrating
that fiscal measures will be most successful in
stabilizing total consumption and pro moting
economic recovery if they focus on the most
vulnerable populations with the mo st pressing
financial issues.
The research is divided into the following
sections. Section 1 shows the scope of the study.
Section 2 shows the literature review. Section 3
shows the research methodology used to convey this
study, and Section 4 shows the empirical results that
this study has collected. Section 5 presents
the discussion. Lastly, Section 6 concludes this
paper and shows recommendations for future
research.
2. LITERATURE REVIEW
The primary sources of the initial assumptions for
a decline in household income were job losses,
which will have an impact on consumption (OECD,
2020; Doerr & Ga mbacorta, 2020). Clothing and
footwear, furniture and home appliances, vehicle
purchases, package vacations, and personal care
services are all expected to come to an end
completely. Recreation and culture, hotels, and
restaurants, as well as the cost of operating
individual automobiles, are expected to decrease
by 50%. The calculations anticipate a decrease in
spending across the economy rather than just
a small decrease in a few key areas (OECD, 2020).
Szustak, Grado, and Szewczyk (2021) research and
evaluate the pandemic’s effects on household
finances in Po land in comparison to other CEE
nations (such as the Czech Republic, Slovakia, and
Hungary), placing a focus on changes in households’
savings levels. Multiple linear regression is used in
the study to identify the variables that affect
the amount of household savings. The study comes
to the conclusion that these variables are distinct in
each of the nations under consideration and affect
the gross saving rate at a different level.
Martin, Hallegatte , and Walsh (2020) assess
the socioeconomic effects of COVID-19 o n people
by estimating the direct effects of distance on
household income, savings, co nsumption, and
poverty using a microeconomic model. The study
comes to the conclusion that there are two periods:
a crisis period, in which some people face a decline
in inco me and can utilize their savings to continue
consumption; and a recovery period, in which
households save to top off their drained savings to
pre-crisis levels.
Dossche, Kolndrekaj, and Slacalek (2021)
investigate the impacts of the COVID-19 pandemic
on labor income, consumption, and saving of
specific euro area families using multiple household-
level statistics. Because of the underlying disparities
in their economic systems, the study discovers that
the pandemic has affected the economies of
the euro area in distinct ways.
A study by Almeida et al. (2021) analyses
the impact of the COVID-19 crisis on EU household
income taking into analysis also the fiscal policy
measures taken by the EU member states. The study
draws the conclusion that the COVID-19 epidemic
is expected to have a considerable impact on
households’ disposable income in the EU, with
lower-income households being particularly hard hit.
Also, their study highlights the importance of policy
intervention, in the impact of the crisis and suggests
that the pandemic’s negative effects on poverty will
be significantly mitigated by the use of discretionary
fiscal policy measures, which will reduce the extent
of the income loss (from 9.3% to 4.3% for the average
equalized disposable income).
The COVID-19 pandemic had an unequal
impact on the employment and earnings of different
laborers, consequently affecting households’ per
capita income and income inequality, thus
the impact of the pandemic lies specifically on
the employment and earnings of different laborer
types (Zhang, Lu, Yin, & Zhao, 2021).
According to a study by Bundervoet, Davalos,
and Garcia (2021), COVID-19 affects households in
poor nations in terms of employment, income, food
security, and learning. According to the findings of
this study, which used data from 34 countries with
a combined population of almost 1.4 billion, 36% of
respondents stopped working in the immediate
wake of the pandemic, over 64% of households
reported income declines, and over 30% of kids were
unable to continue their education during school
closures. The study also highlights that during
the COVID-19 pandemic, the self-employed and
casual workers — the most vulnerable workers in
developing countries — bore the brunt of
the pandemic-induced income losses.
The tragic effects of the coronavirus pandemic
on the labor market are revealed in a study by
Bottan, Hoffmann, and Vera-Cossio (2020) using
a household survey of 230,540 respondents in
seventeen developing nations. The research also
comes to the conclusion that existing inequality is
being worsened by the monotonically diminishing
link between job loss and business closure within
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299
income prior to the epidemic. Beyo nd income
inequality, the effects of the labor market o n
inequality also include food security and nutrition.
Another study by Fajardo-Gonzalez, Molina,
Montoya-Aguirre, and Ortiz-Juarez (2021) highlights
three findings: first, a distributive-neutral forecast
places 117 million people in extreme poverty and
a distributive-regressive projection places 168 million
people in extreme poverty, which may better reflect
how the shock affected poor and vulnerable
households. Second, a simulation of the potential
effects of a temporary basic income with
an investment of 0.5% of developing nations’ GDP
over a period of six months reveals that this sum
would significantly reduce, at least temporarily,
the rise in global poverty in both the $1.90- and
$3.20-a-day thresholds; however, poverty would still
rise significantly in the world’s poorest regions.
Third, t he study of income-support initiatives in
41 nations reveals that they might have, at least
temporarily, reduced the overall rise in poverty in
upper-middle-income nations, but they might not
have been adequate to reduce the rise in poverty at
any poverty level in low-income nations.
Nationally, during the lockdown period
between March and May 2020, the simulation results
estimate declines in household income by 33% on
average, thus the urban population experienced
the largest decline, averaging 40% during this period
(Diao, Rosenbach, Spielman, & Aragie, 2021).
Gopal and Malliasamy (2022) analyse the
transformation of savings and spending of rural
households during COVID-19 in the case of Malaysia.
A Likert scale was utilized in the questionnaire to
elicit the study variables, and structural equation
modeling was utilized to ana lyze the data after it
was gathered. According to the study, all types of
savings during COVID-19 had a favorable and
significant link with rural residents’ savings
intentions.
Jin, Zhao, Song, and Zhao (2021) investigated if
and how consumer preferences for saving are
affected by public health situations (vs. spending).
To evaluate the hypotheses, the study used two
online surveys and techniques including stepwise
regression analysis and bootstrapping. The study
concluded that materialism plays a moderating role
between risk perception and an individual’s
willingness to save (vs. spend); people who are more
materialistic have a lower willingness to save
(vs. spend) when they perceive the risks of
the pandemic. The study found that the severity of
emergencies has a significant positive impact on
the population’s willingness to save (vs. spend).
The COVID-19 pandemic is creating a new reality
worldwide. Western Balkans economies could seize
the opportunities arising from this new reality.
The global economy and production networks will
tend to become more resilient to shocks after
the pandemic. Western Balkan economies can also
emerge stronger if they change as the world is
changing (Jovanović et al., 2021).
A study by Kim, Koh, and Zhang (2020)
examines the short-term impact of COVID-19 on
consumption spending and its underlying
mechanisms, using individual-level monthly panel
data fro m Singapore. The study concludes that
the COVID-19 pandemic reduced consumption
spending by almost a quarter during its peak, with
a larger response from households with above-
median wealth. The study also emphasizes the link
between consumption spending and risk-aversion,
the national lockdown, increased economic
uncertainty, and lower income. Given that the primary
cause of this is the inco me decline, which accounts
for about a third of the decline in consumption
spending among households that have suffered
income losses due to the pandemic, it is likely less
likely that the income channel is what is causing
the overall decline in consumption.
Using a survival analysis of COVID-19 incidence
in Kosovo, Bajrami, Gashi, and Hashani (2021) found
that while some covariates, such as diabetes
prevalence and hospital beds per thousand, have
highly statistically significant coefficients, others,
such as the stringent index, total cases, GDP per
capita (an economic variable), respondent’s age , and
handwashing facilities, do not. This sugge sts that
these covariates are not significantly influencing
the hazard ratio.
A study by Hashani, Ziberi, and Bajrami (2022)
targeted individual use in the Western Balkan
nations. Results were drawn using ordinary least
squares (OLS), fixed-effect, random-effect, and
Hausman–Taylor estimator. The findings show
that a key factor in economic growth is private
consumption. By increasing their household
consumption, individuals and households have
a direct impact on the country’s GDP growth.
Hoti and Kurhasku (2022) investigate how
remittances from the diaspora affect social and
economic outcomes and how they can support
the emerging economy in battling the COVID-19
pandemic. According to the findings, remittances
were higher than ever throughout t he pandemic and
were vital in helping families in Kosovo pay for
necessities during the country’s economic difficulties.
In their study, Cantó et al. (2022) evaluated
the COVID-19 effects on household income and
the government’s policy responses in April 2020 in
four significant and severely affected EU countries
(Belgium, Italy, Spain, and the United Kingdom).
The results indicate that economic poverty grew
across the countries as a result of the pandemic,
according to household surveys associated with
COVID-19.
A total of 493 participants/families, including
364 males and 129 females, were participants in
the research carried out by Celik, Ozden, and
Dane (2020). In order to gather information about
household characteristics during the COVID-19
pandemic such as income, total expenses, and other
expenses, an online survey was employed as
the research instrument. According to the study’s
findings, the COVID-19 pandemic has significantly
affected the income and expenses of families from
various countries.
Using a Monthly Basic Current Population
Survey (CPS), Feinberg et al. (2022) gathered income
data from a sizable representative sample of
American families. The findings indicate that early
in the pandemic, government policy successfully
counteracted its effects on incomes, resulting in
a decrease in poverty and an increase in low incomes
across a variety of demographic and geographic
groupings.
Hanspal, Weber, and Wohlfart (2020) e xamined
the impact of the COVID-19 outbreak on household
Corporate & Business Strategy Review / Volume 3, Issue 2, Special Issue, 2022
300
income using surveys of a representative sample of
more than 8,000 US homes, particularly for young
people and those with lower incomes.
By analyzing online survey data from
442 respondents, Kansiime et al. (2021) evaluated
the effects of the pandemic on household income in
Kenya and Uganda, two countries in East Africa.
According to the findings, the COVID-19 issue
caused income shocks for over two-thirds of
the respondents.
Baker, Farrokhnia, Meyer, Pagel, and Yannelis
(2020) use Gallup Daily Tracker Data to evaluate
how household consumption responds to epidemics
by analyzing household transaction-level financial
data. Their research revealed that households
started drastically altering their usual spending
patterns in several important categories as
the number of instances rose. Firstly, spending rose
radically, particularly in the retail sector, on food
and credit cards.
Georgarakos and Kenny (2022) measure
the effect of COVID-19 on family consumption by
using the Consumer Expectations Survey (CES),
a new high-frequency online panel survey of
consumer expectations and behavior in the euro
area. The results demonstrated that consumer
spending is causally affected by simple and true
information treatments on government support
policies, particularly by increasing expenditure on
large items.
Zhang et al.’s (2021) empirical observations of
how the COVID-19 epidemic has impacted families’
saving choices offer insight into this discussion.
The COVID-19 pandemic’s effects on Chinese
household saving practices were assessed in
the paper. According to this study, households in
the worst-hit cities would save more during the
disaster, but tended to save less once it subsided.
Li, So ng, Pe ng, and Wu (2020) used data from
the China Household Finance Survey (CHFS). Their
findings show households’ liquidity constraints
become serious after the outbreak of COVID-19.
Meanwhile, the deterioration of individuals’ liquidity
significantly increases their willingness to save and
reduces their consumption.
The following research hypotheses were drawn
for this study:
H1: The COVID-19 pandemic has had a significant
negative impact on household income.
H2: The COVID-19 pandemic has had a negative
impact on household consumption.
H3: The COVID-19 pandemic has had a negative
impact on household savings.
3. RESEARCH METHODOLOGY
For the analysis of this paper, narrative methods
were used, through which a brief description was
made about the effects of the pandemic in different
categories in Kosovo and econometric methods for
the analysis of empirical results.
To determine the effects of the pandemic on
household income, a survey was initially co nducted
which is structured in two parts. The first part deals
with the demographic questions of the survey (age,
gender, location, family members) and the second
part of the survey deals with the substantive
questions of the topic:
– q9 (“Your family’s monthly income has
changed as a result of the COVID-19 pandemic”);
– q10 (“Your family’s monthly income was
higher before the COVID-19 pandemic period”);
– q11 (“At least one of your family members
lost their job as a result of the COVID-19 pandemic”);
– q12 (“Your family savings were higher before
the COVID-19 pandemic”);
– q14 (“Average monthly consumption
expenditures were higher before the pandemic”);
– q15 (“The COVID-19 pandemic negatively
affected the standard of your family living”).
The variables q9, q10, q11, q12, q14, and q15
are variables that define the latent variable.
The model from which the latent variable is
measured is the structural equation model (SEM).
The data was gathered between September and
December of 2021 through an online survey. Only
families with members employed by privately held
institutions and businesses were authorized to
participate in the study, which limited the makeup
of the complaints. The researchers utilized Slovin’s
formula — n = N/(1 + Ne2) — to increase the sample’s
representativeness. The sample included 507 families.
The statistics on all Kosovo families were provided
by the Kosovo Statistics Agency. Both the SEM model
analysis and the descriptive data analysis were
performed using Stata software (Table 2 and
Appendix).
In the table below, the descriptive statistical
data, from which we see that there are a total of
507 respondents surveyed, are presented. The survey
consists of answers from the Likert scale, where 1 is
“I completely agree”, while 4 means “I do not agree
at all”. Question q11 is the only one that needs
a “yes” or “no” response.
The selection sample is spread in all cities of
the Republic of Kosovo and the households that are
employed in private institutions are surveyed.
Table 1. Descriptive statistics
Variable
Observations
Mean
Std. dev.
Min
Max
q9
507
2.043393
0.9165209
1
4
q10
507
2.025641
0.926836
1
4
q11
507
0.7376726
0.4403342
0
1
q12
507
1.91716
0.8106513
1
4
q14
507
2.43787
0.8674994
1
4
q15
507
1.946746
0.8191895
1
4
Source: Authors’ calculations.
4. RESULTS
According to the IMF, economic growth in Kosovo
decreased by 6% in 2020 and increased by 4.5%
in 2021, which does not return to the economic
situation in 2019. The difference of -1.5% in
economic growth still reflects co mpared to 2019.
This root also reflects in the reduction of family
savings. From 2019 to 2020, savings have decreased
by 2.98% and the decrease continues in 2021
compared to 2019 by about 1%.
Corporate & Business Strategy Review / Volume 3, Issue 2, Special Issue, 2022
301
Table 2 displays the descriptive data from
the respondents’ responses using percentages. When
asked if the COVID-19 pandemic had an impact o n
family income, 72.4% agreed, while 27.6% disagreed.
When asked about their family’s monthly income
prior to the COVID-19 pandemic, 67.7% of
respondents replied that it was higher, while 32.3%
claimed it was not. When asked if they had more
savings before the pande mic, 76.9% of respondents
claimed they did, while 23.1% said they did not have
more savings before the pandemic. When asked
about job losses within the family, 73.8% of
respondents said that at least one family member
lost their job because of the pandemic, while 26.2%
said that no one lost their job. According to 45.5% of
respondents, their consumption was higher before
the pandemic, whereas 55.5% disagreed and strongly
disagreed with the claim that there was more
consumption prior to the pandemic. When it comes
to the standard of living, 78.5% of respondents
believed the pande mic had a negative impact
whereas the rest of the respondents do not believe
that the pandemic negatively affected their standard
of living.
Table 2. Descriptive statistics (in %)
Questions
Strongly agree
(1)
Agree
(2)
Disagree
(3)
Strongly disagree
(4)
q9
31.6%
40.8%
19.9%
8.3%
q10
35.7%
32.0%
26.4%
5.9%
q12
34.3%
42.6%
20.1%
3.0%
q14
17.9%
27.6%
47.1%
7.3%
q15
31.6%
46.9%
16.8%
4.7%
q11
Yes
(0)
No
(1)
73.8%
26.2%
Referring to the first figure of the SEM, we see
the correlation of the variables q9, q10, q11, q12,
q14, and q15 with the latent variable which
determines the effects of the COVID-19 pandemic on
family income.
COVID-19 is the latent variable used in this
research. In this case, the latent variable is
determined by factors shown through questions
q9–q15. Moreover, a latent variable is this study’s
dependent variable.
Figure 1. Structural equation model — Path and estimations of SEM
According to Table 2, we see that the results
from t he SEM model show the impact of
the COVID-19 pandemic on household income in
the Republic of Kosovo.
Empirical results fro m the SEM model show
that the COVID-19 pandemic has had a negative
impact on household income. The question on
whether incomes have changed as a result of
the COVID-19 pandemic (q9), according to the results,
is a constant question and its results are significant.
Since revenues have changed from the effects of
the pandemic, q10 confirms that revenues were
higher before the COVID-19 pandemic than after it,
according to the SEM model, results are significant.
Most of the surveyed households stated that at least
one of their family members lost their job, then
show a significant impact in terms of savings,
according to the results of the SEM model,
household savings decreased as a result of increased
spending on consumption and job loss.
The analysis of these results confirms
the hypotheses of this paper that the COVID-19
pandemic had negative effects on household income
(H1), negative effects on consumption (H2), and
negative effects on savings (H3).
Corporate & Business Strategy Review / Volume 3, Issue 2, Special Issue, 2022
302
Table 3. SEM model
Variables
SEM
Dependent variable (latent)
COV_19
Independent variables
q9
1 (constrained)
(0.000)***
q10
1.273787
(0.000)***
q11
0.3835906
(0.000)***
q12
0.9487917
(0.000)***
q14
0.494223
(0.000)***
q15
0.9530569
(0.000)***
No. of obsevations
507
Log. likelihood
-3190.515
LR test
47.46
(0.000)
Note: p-values are shown in parenthesis; *, **, and *** show significance at 10%, 5%, and 1% levels.
Source: Authors’ calculations.
5. DISCUSSION
According to OECD (2020), the COVID-19 pandemic
caused numerous employees around the world to
lose their jobs. As a result, many families were
forced to spend all of their income on groceries and
forgo travel, vacations, and dining out. People’s
reluctance to spend money on other items increased
the negative impact of the decrease in household
income, lengthening the economic decline in
the OECD countries. The results of this study are
similar to ours as they demonstrate how the COVID-19
pandemic has impacted family inco me, led to at
least one job loss in the fa mily, decreased spending,
and forced these families to use their savings to pay
for expenses as a result of the crisis. Our study’s
findings support those of Almeida et al. (2021), who
looked at how the COVID-19 pande mic affected
household income and savings in EU countries.
The results show that the COVID-19 pandemic
significantly affects income and savings. The research
carried out by Zhang et al. (2021) on family income
inequality and employment inequality is pertinent to
our find ings. Moreover, the findings of Bundervoet
et al. (2021) and Bottan et al. (2021) are also
pertinent as they determined that there are
disparities in employment losses in some industries
and income. Reduced household income is a result
of businesses being closed and job losses.
The findings in this paper are pertinent to Kim et al.
(2020) in regard to consumption as their study
found that the pandemic has an impact on reducing
family e xpenses. Kosovo recently overcome a severe
crisis due to remittances, which skyrocketed during
the pandemic despite the country’s weak economy
(Hoti & Kurhasku, 2022).
6. CONCLUSION
This paper analyses the impact of COVID-19 on
household income in Kosovo. The methods used for
the analysis of this paper are mainly empirical
methods using the SEM model, as the latent variable
in this paper is COVID-19.
This paper has two main limitations: first,
selective samples in this paper are only families who
are employed in the private sector (various economic
activities), this research are not included families
who have income from their private businesses,
families which have a family member e mployed in
public institutions. Second, in this paper, families
are not differentiated according to income levels
(low, medium, and high).
Referring to the limitations of this paper,
the results of the analysis from the SEM model show
that COVID-19 pandemic has a significant negative
impact on household income and a consistent
variance from the measurement model. Negative
income impacts are reflected in declining household
savings as a result of declining incomes following
the COVID-19 pandemic, rising costs, and job losses.
On average in every family, one of the family
members has lost his job
The SEM model is stable, as the variables are
correlated with each other and the results from
the SEM model are significant. The LR test of model
stability is 47.46 and is significant.
The paper is very important for future research
because it serves as an initial reference basis for
fostering further research on the i mpact of
the COVID-19 pandemic on household income.
Future work of this nature could be extended to
other household income variables, the analysis of
the differentiation of household income strata,
and the measurement of poverty levels as a result of
the COVID-19 pandemic. Future research on this
phenomenon can use additional econometric
methods. OLS, fixed-effect, random-effect, and GMM
are the methods that are most typically e mployed to
perform this research using seco ndary data from
the World Bank, the IMF, and other relevant sources.
The latent nature of the dependent variable in this
investigation makes SEM the most suitable model to
employ. In the event that the dependent variable in
subsequent research can be measured, Logit or
Probit are the most suitable models to use. This
establishes a strong foundation for that research.
Corporate & Business Strategy Review / Volume 3, Issue 2, Special Issue, 2022
303
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APPENDIX
Table A.1. Descriptive statistics
Age
Gender
Location
Family members
N
Valid
507
507
507
507
Missing
0
0
0
0
Mean
2.30
1.30
1.32
3.36
Median
2.00
1.00
1.00
4.00
Mode
2
1
1
4
Std. deviation
0.620
0.459
0.468
0.869
Variance
0.384
0.210
0.219
0.755
Variable coding: Age — 1 > 18; 2–18 until 35; 3–36 until 50; 4–51 until 64; 5 ≥ 64.
Gender: 1 — Female; 2 — Male.
Location: 1 — Urbane; 2 — Rural.
Family members: 1–2 members; 2–3 members; 3–4 members; 5 > 4 members.
Source: Authors’ calculations.
Corporate & Business Strategy Review / Volume 3, Issue 2, Special Issue, 2022
305
Table A.2. Analytic statistics
q9
q10
q11
q12
q14
q15
q9
Pearson correlation
1
0.522**
0.288**
0.391**
0.294**
0.372**
Sig. (2-tailed)
0.000
0.000
0.000
0.000
0.000
N
507
507
507
507
507
507
q10
Pearson correlation
0.522**
1
0.380**
0.534**
0.261**
0.491**
Sig. (2-tailed)
0.000
0.000
0.000
0.000
0.000
N
507
507
507
507
507
507
q11
Pearson correlation
0.288**
0.380**
1
0.321**
0.198**
0.372**
Sig. (2-tailed)
0.000
0.000
0.000
0.000
0.000
N
507
507
507
507
507
507
q12
Pearson correlation
0.391**
0.534**
0.321**
1
0.080
0.502**
Sig. (2-tailed)
0.000
0.000
0.000
0.073
0.000
N
507
507
507
507
507
507
q14
Pearson correlation
0.294**
0.261**
0.198**
0.080
1
0.250**
Sig. (2-tailed)
0.000
0.000
0.000
0.073
0.000
N
507
507
507
507
507
507
q15
Pearson correlation
0.372**
0.491**
0.372**
0.502**
0.250**
1
Sig. (2-tailed)
0.000
0.000
0.000
0.000
0.000
N
507
507
507
507
507
507
Note: ** Correlation is significant at the 0.01 level (2-tailed).
Source: Authors’ calculations.
Table A.3. SEM model for the measurement of the variables
Iteration 0: Log likelihood = -3191.8949
Iteration 1: Log likelihood = -3190.5336
Iteration 2: Log likelihood = -3190.515
Iteration 3: Log likelihood = -3190.515
Structural equation model: Number of obs. = 507
Estimation method = ml
Log likelihood = -3190.515
(1) [q9]COV_19 = 1
OIM
Coef.
Std. Err.
z
P > |z|
[95% Conf. interval]
Measurement
q9 ≤
COV_19
1 (constrained)
_cons
2.043393
0.040664
50.25
0.000
1.963693
2.123092
q10 ≤
COV_19
1.273787
0.0984249
12.94
0.000
1.080878
1.466697
_cons
2.025641
0.0411216
49.26
0.000
1.945044
2.106238
q11 <-
COV_19 |
0.3835906
0.0419898
9.14
0.000
0.3012922
0.4658891
_cons
0.7376726
0.0195366
37.76
0.000
0.6993815
0.7759637
q12 <-
COV_19
0.9487917
0.0837033
11.34
0.000
0.7847363
1.112847
_cons
1.91716
0.0359668
53.30
0.000
1.846666
1.987653
q14 <-
COV_19
0.494223
0.0770787
6.41
0.000
0.3431515
0.6452944
_cons
2.43787
0.038489
63.34
0.000
2.362433
2.513307
q15 <-
COV_19
0.9530569
0.085224
11.18
0.000
0.7860209
1.120093
_cons
1.946746
0.0363456
53.56
0.000
1.87551
2.017982
Variance
e.q9
0.5122032
0.0380842
0.4427435
0.59256
e.q10
0.3281401
0.0342827
0.2673803
0.4027071
e.q11
0.1455214
0.0099299
0.1273045
0.166345
e.q12
0.3622566
0.0285091
0.310476
0.4226731
e.q14
0.6714064
0.0434568
0.5914138
0.7622186
e.q15
0.3734994
0.0297191
0.3195659
0.4365354
COV_19
0.3261507
0.0464015
0.2467844
0.4310413
Note: LR test of model vs. saturated: Chi2(9) = 47.46, Prob. > Chi2 = 0.0000.
Source: Authors’ calculations.
