JEFMS Journal

ABSTRACT:

Pandemics are not a new phenomenon since they have happened numerous times throughout human history. Due to the globalization and interconnectedness of the business world today, the steps taken by governments around the world to stop the Corona Virus Disease 2019 (COVID-19) from spreading resulted to minimal movement of people and products, impacting business activities in Kenya. Although COVID-19 containment measures including stay at home requirement contributed to the reduction of coronavirus infection globally, household incomes were at risk due to the pandemic’s effects on business operations and economic activities. The study sought to analyze effect of COVID-19 stay at home requirement on household incomes in Uasin Gishu County, Kenya. The study was anchored on the relative income theory which guided the specification framework. An explanatory research design was adopted based on 304, 943 households with a sample of 399. The data was collected using structured questionnaires issued to household heads using simple random sampling. Correlation results indicated a strong negative significant correlation between stay-at-home requirement and household income . OLS results indicated that stay-at-home requirement coefficient had a negative significant effect (β=-0.343,p=0.00<0.05)on household income. The study concluded that COVID-19 stay at home requirement affected household incomes for Uasin Gishu County, Kenya households suggesting that the restrictions imposed to curb the menace extensively led to job loss and reduction in income.

KEYWORDS:

COVID-19, Household Incomes, Stay at Home Requirement, Economy

REFERENCES:

1) Anderson, R. M., Fraser, C., Ghani, A. C., Donnelly, C. A., Riley, S., Ferguson, N. M., ... & Hedley, A. J. (2004). Epidemiology, transmission dynamics and control of SARS: the 2002–2003 epidemic. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 359(1447), 1091-1105. Kenya Department of Foreign Affairs. (2022).

2) Badoux, M., Iazzolino, G., Mwangi, K., & Abuga, E. (2018). Eldoret, a city on the move: Drivers, dynamics and challenges of rural to urban mobility. Rift Valley Institute Report.

3) Bedson, J., Hebert-Dufresne, L., Scarpino, S. V., & Althouse, B. M. (2021). Seeding COVID-19 across Sub-Saharan Africa: An Analysis of Reported Importation Events across 49 Countries. Am. J. Trop. Med. Hyg, 104(5), 1694-1702.

4) Bonacini, L., Gallo, G., & Scicchitano, S. (2021). Working from home and income inequality: risks of a ‘new normal’with COVID-19. Journal of population economics, 34(1), 303-360.

5) Chandran, E. (2004). Research methods: A quantitative approach with illustrations from Christian ministries. Daystar University.

6) Deaton, A. (2005). Franco Modigliani and the life cycle theory of consumption. Available at SSRN 686475.

7) Deb, P., Furceri, D., Ostry, J. D., & Tawk, N. (2020). The effect of containment measures on the COVID-19 pandemic.

8) Diao, X. & Mahrt, K., (2020). Assessing The Impacts Of COVID-19 on Household Incomes and Poverty in Myanmar: A Microsimulation Approach (Vol. 2). International Food Policy Research Institute.

9) Drakopoulos, S. A. (2020). The Marginalization of Absolute and Relative Income Hypotheses of Consumption and the Role of Fiscal Policy.

10) Gondwe, G. (2020, July). Assessing the impact of COVID-19 on Africa’s economic development. In United Nations Conference on Trade and Development.

11) Issaias, A., Indokhomi, D., Shah, P., & Field, R., (2020). COVID-19: Impact on Businesses and Investments in Kenya

12) Kansiime, M. K., Tambo, J. A., Mugambi, I., Bundi, M., Kara, A., & Owuor, C. (2021). COVID-19 implications on household income and food security in Kenya and Uganda: Findings from a rapid assessment. World development, 137, 105199.

13) Kenya Population and Housing Census. (2019). 2019 Kenya Population and Housing Census Results. Retrieved 19 April 2021, from https://www.knbs.or.ke/?p=5621/

14) Kithiia, J., Wanyonyi, I., Maina, J., Jefwa, T., & Gamoyo, M. (2020). The socio-economic impacts of Covid-19 restrictions: Data from the coastal city of Mombasa, Kenya. Data in brief, 33, 106317.

15) Meghir, C. (2004). A retrospective on Friedman’s theory of permanent income. The Economic Journal, 114(496), F293-F306

16) Mervosh, S., Lu, D., & Swales, V. (2020). See which states and cities have told residents to stay at home. The New York Times, 3.

17) Mueller, V., Sheriff, G., Keeler, C., & Jehn, M. (2021). COVID‐19 Policy Modeling in Sub‐Saharan Africa. Applied Economic Perspectives and Policy, 43(1), 24-38.S

18) Mugenda, A., & Mugenda, O. (2003). Research Methods: Quantitative and Qualitative approaches NAIROBI: African Center for Technology Studies (ACTS).

19) Muragu, M. M., Nyadera, I. N., & Mbugua, C. W. (2021). Gearing up for the new normal: Kenya’s tourism sector before and after the COVID-19 pandemic. Journal of Policy Research in Tourism, Leisure and Events, 1-18.

20) Nafees, M., & Khan, F. (2020). Pakistan’s Response to COVID-19 Pandemic and Efficacy of Quarantine and Partial Lockdown: A Review. Electron J Gen Med. 2020; 17 (2): emXXX.

21) Nanyingi, M. (2020). The evolution of the COVID-19 pandemic in Kenya. TRSoTMa Hygiene, Editor.

22) Nechifor, V., Ramos, M. P., Ferrari, E., Laichena, J., Kihiu, E., Omanyo, D., ... & Kiriga, B. (2021). Food security and welfare changes under COVID-19 in Sub-Saharan Africa: Impacts and responses in Kenya. Global food security, 28, 100514.

23) Odhiambo, J., Weke, P., & Ngare, P. (2020). Modeling Kenyan economic impact of corona virus in Kenya using discrete-time Markov chains. Journal of Finance and Economics, 8(2), 80-85

24) Oloruntoba, S. O. (2021). Unity Is Strength: Covid-19 and Regionalism in Africa. The International Spectator, 56(2), 56-71.

25) Ozili, P. (2020). COVID-19 in Africa: socio-economic impact, policy response and opportunities. International Journal of Sociology and Social Policy.

26) Parker, J. (2010). Theories of consumption and saving. Economics, 314, 1-25.

27) Pavelescu, F. M. (2004). Features of the ordinary least square (OLS) method. Implications for the estimation methodology. Journal for Economic Forecasting, 1(2), 85-101.

28) Pinchoff, J., Kraus-Perrotta, C., Austrian, K., Tidwell, J. B., Abuya, T., Mwanga, D., ... & Ngo, T. D. (2021). Mobility patterns during COVID-19 travel restrictions in Nairobi urban informal settlements: who is leaving home and why. Journal of Urban Health, 98(2), 211-221.

29) Setia, M. S. (2016). Methodology series module 3: Cross-sectional studies. Indian journal of dermatology, 61(3), 261.

30) Siringi, E. M. (2021). Analysis of Economic Effect of COVID-19 Pandemic on the Kenyan Odhiambo, J., Weke, P., & Ngare, P. (2020). Modeling Kenyan economic impact of corona virus in Kenya using discrete-time Markov chains. Journal of Finance and Economics, 8(2), 80-85.

31) Statista. (2022). Cumulative number of confirmed coronavirus (COVID-19) cases in Kenya as of December 6, 2021, by county. Retrieved 2 March 2022, from https://www.statista.com/statistics/1136519/cumulative-coronavirus-cases-in-kenya-by-county/

32) Turner, B. (2010). International Air Transport Association (IATA). In The Statesman’s Yearbook (pp. 45-46). Palgrave Macmillan, London.