Systematic Literature Review: Unemployment Rate as factors affecting the Gross Domestic Product, Inflation Rate, and Population

Unemployment is one idea that explains how economies' production structures, sectoral developments, and regional and national developments. Covid-19 affects the unemployment rate, GDP, Inflation Rate, and Population. This is a systematic literature review, and the researcher used PRISMA in determining the literature used in this study. Out of 101 related topics in google scholar, only 6 were selected in this study. The COVID-19 health crisis is a great shock that is making a change in the lives and livelihoods of individuals around the globe. Apparently, and unfortunately, the pandemic reversed some of these gains. It wiped out 1.7 million wages and salary jobs in just 12 months until January 2021. The pandemic caused and created long-lasting effects on employment. Thus, it created a big impact on the economy. A phenomenon is known as hysteresis employment. Moreover, three transmission channels of the pandemic on modern employment have been listed: A higher number of job seekers-like those who lost jobs, dropouts from school, and new labor markets entrants that remain unemployed; next is the large re-allocation of job sectors; and companies that are modifying their businesses that rely on the uses of technology. These will exacerbate further the skill mismatch in the labor market. The methodology used a systematic literature review, wherein inclusion and exclusion criteria are set to narrow the research to studies for comprehensive analysis. The inclusion criteria were: 1) They were published between 2017 and 2022) they were published as an academic journal, 3) they were written in the English language, 4) they were original or empirical studies, and 5) the studies are focused on the analysis on how the Gross Domestic Product, Inflation rate, and population affects the Unemployment rate. The exclusion criteria were as follows: 1) Excluding the duplicated studies. 2) Excluding non-English studies. 3) Excluding studies that did not focus on the unemployment rate. The literature search was limited to 2017-2022. Hence, J D Urrutia et al. (2017) demonstrate that only the inflation rate, out of the five independent variables, has no significant link with the dependent variable, with a p-value of 0.178, which is more than the level of significance of 0.01 if the null hypothesis is accepted there is no significant relationship between the dependent and independent variable. Meanwhile, GDP shows a negative connection with the Unemployment Rate but a significant linear association with the unemployment rate based on their Pearson coefficient of determination (J D Urrutia et al., 2017). Moreover, the population shows a negative connection with the Unemployment Rate but a significant linear association with the unemployment rate based on their Pearson coefficient of determination (J D Urrutia et al., 2017). SARIMA (6, 1, 5) x (0, 1, 1) 4 is the formulated model for estimating and forecasting the unemployment rate in the Philippines. Forecasted values are within six to eight percent of actual values, and they are shown to be 72 percent accurate. Important determinants of the unemployment rate, Labor Force Rate, and Population are discovered. In addition, the dependent variable is Granger-caused by population, GDP, and GNI. These factors can influence the unemployment rate. Any change in those factors can cause the unemployment rate to rise or fall (J D Urrutia et al., 2017). When unemployment falls, disposable income grows, demand rises, and prices rise.