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FACTORS INFLUENCING UNEMPLOYMENT RATE IN MALDIVES Student Name: Institution: Date:

Abstract It is the desire for every world government to provide sufficiently and sustainably the lives of its citizens socially, mentally, and economically. A major way towards achieving this is to ensure the highest percentage of citizens are employed. While many studies have been conducted regarding the factors influencing the rates of employment, no valid conclusion has been derived regarding the exact factors affecting unemployment rates thus opening room for more studies. Therefore, this study was set to establish the predictive influence of inflation rates, GDP, currency value with respect to the US dollar, consumer price index, and government revenue on the level of unemployment, a case study of Maldives nation. This involved the use of multiple linear regression at a 5% level of significance. From the analysis, it was established a joint significant influence of inflation rates, GDP, currency value with respect to the US dollar, consumer price index, and government revenue on the level of unemployment in the country. Nevertheless, the study established that the variables did not individually predict the model, a factor that can be attributed to the presence of other factors affecting unemployment and that were excluded from the study and the smaller sample size. It is therefore concluded from the study that while establishing the influential factors towards the unemployment in the Maldives, the joint effect of inflation rates, GDP, currency value with respect to the US dollar, consumer price index, and government revenue on the level of unemployment must be considered.

Introduction Unemployment is a major problem experienced worldwide. In the Maldives, the current state of unemployment is 6.40%, a value that has been maintained since 2020. This was a 0.30% increase compared to the 2019 rate which was a 6.10% and 2.96% rise from 1991[CITATION Tra20 \l 1033 ]. It is worth noting that the level of unemployment in a given country is affected by many factors, some similar and others nation-specific. For instance, in 2020 and 2021 specifically, countries experienced a risen value of unemployment considering the emergence and effect of the coronavirus pandemic which saw most people work from home and some retrenched[ CITATION Nag20 \l 1033 ]. Besides, the pandemic did not allow for businesses to operate based on movement restrictions and as such, several businesses were closed reducing the percentage employed[ CITATION YIL20 \l 1033 ]. Other than the pandemic, unemployment rates are affected by the level of gross domestic product for that particular nation which determines the level of capital available for investment, the level at which workers are utilized and their level of pay, a factor that controls whether a worker will continue with the work or not[ CITATION Haf21 \l 1033 ]. On the other hand, unemployment is controlled by how the government sets up businesses and parastatals to accommodate its people[ CITATION Sal18 \l 1033 ]. As well, the business environment put for investors by the government determines whether the country is attractive to investors or not and as such, controls the number of people getting employed[ CITATION Lau20 \l 1033 ]. In a different perspective, the level of education of citizens within a particular country determines labor availability, competitiveness, and marketability. In line with this, a country with lower rates of literacy is likely to import foreign workers, both in the public and private sectors, thus rendering local workers jobless[ CITATION Dor08 \l 1033 ]. In contrast, a country that has an almost 100% literacy rate have highly

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competitive workers that attract both local and global attention thus have many opportunities to avoid unemployment[ CITATION Noo15 \l 1033 ]. This is, nevertheless, dependent on the economic level of that particular nation and that of the preferred destinations for skilled workers[ CITATION Ros20 \l 1033 ]. Different types of unemployment result from different causes. To start with, Frictional unemployment is caused by the duration spent by professionals moving between jobs, for instance, people changing workplaces since there is no perfect information and much time is taken finding work[ CITATION Dam21 \l 1033 ]. Secondly, structural unemployment results from skill mismatch in the market of labor. This may be due to occupational immobility which includes difficulty in acquiring new skills in a new industry and technical change; geographical immobility which is the technicality in moving to job regions, a technological change that may lead to a fall in demand for some specific skills and structural economic change due to uncompetitiveness of some industries like coal mines[ CITATION Pau18 \l 1033 ]. The third of unemployment, classical, may result from the pushing of wages in a competitive labor market above the point of equilibrium thus leading to the fall of that particular labor[CITATION Ala15 \l 1033 ]. Fourthly, a voluntary type of unemployment may result from the decision of individuals refusing to take the available jobs in the hope of a better one[ CITATION HAS21 \l 1033 ]. Finally, cyclical unemployment results from the fall of the economy below the full capacity in which case, firms decide to employ few workers when the output fall. From the above statements, it is clear that there are many factors affecting unemployment that needs to be addressed and that are not yet exhausted from past works of literature[ CITATION Kon11 \l 1033 ]. This study was set to establish the predictive influence of GDP, currency value, inflation rate, consumer price index, and government revenue on the

unemployment rates in the Maldives. This will involve the use of multiple linear regression and descriptive statistics tests at a 5% level of significance. Literature Review Many studies have been conducted regarding unemployment in different parts of the world. These studies have tackled various sections of unemployment starting from the causes, effects, and possible remedies. Besides, it is through the studies that significantly influential factors have been established and used in coming up with yearly rates of unemployment for every nation and region. In this section, the various works of literature are discussed with respect to factors affecting unemployment then narrowed down to GDP, inflation, currency value, consumer price index, and government revenue. Unemployment causes The labor force is a major factor influencing unemployment. While establishing this in the context of Indonesia, Erna (2018) established that as the volume of labor increases in a particular country, based on the laws of demand and supply, the unemployment rates increases. In an explanation for this, Zhang and Wang (2020) stated that assuming works available are kept constant, then increasing the labor supply will outstretch the available demand thus rendering most people jobless. Nevertheless, increasing labor and jobs available at the same time results in a positive relationship between the two variables and a negative association between the labor force and unemployment. This, according to Aljileedi and colleagues (2020) shows that the labor force is a factor influencing unemployment in different dimensions depending on the available

labor market. In a different context, Ali and Maryam (2011), while establishing the influence of GDP on the unemployment rates in Iran, discovered it to be a significant predictor of unemployment. This, according to Ladislav et al. (2020) is because gross domestic product determines the level of revenue earned by the country. It also determines the possibility of expansion of the labor market to accommodate the unemployed and the new graduates from schools. Gross domestic product, as stated by Amyir and colleagues (2020) is, therefore, the greatest influencer of unemployment in any given country. While explaining this, they stated that the amount of gross domestic product also influences the volume of goods and services exported thus controlling the level of foreign exchange and the home currency value thus determining the country’s level of economic development based on the global index. A country that has a higher value of a currency compared to the dollar is key to reducing unemployment[ CITATION Zah16 \l 1033 ]. While explaining this, Emmanuel and colleagues (2019), stated that high currency value is attractive to both foreign and local investors and as such, increases the available jobs thus minimizing the rates of unemployment. As well, many people in well- established economies such as those with highly-valued currency have citizens with better living standards, a factor that’s positively associated with lower birth rates, and thus few people are exposed to unemployment upon successful college completion[ CITATION Tey19 \l 1033 ]. Though providing a better ground for reducing unemployment, when not well controlled by government regulations, a high level of currency, according to Atif et al. (2016) can also lead to high levels of unemployment. They explain this by stating that the higher value of the currency, being favorable to businesses and workers, likely attracts more competitive foreign workers that can replace local workers who are less competitive. Inflation and consumer price index rates are key influencers of the economic growth in every nation[ CITATION Gat19 \l 1033 ]. While

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explaining the same, Marc (2016) stated that countries with high-level of inflation shun away investors, both local and foreign, and as such, reduce the level of employment within the country. Equally, Muhammad (2021) found that at higher rates of consumer price index where the cost is high, there is a likelihood of reduced production which in the long run may reduce the level of employment[ CITATION Ram21 \l 1033 ]. Finally, governments with higher levels of revenue are proven to create more employment chances for their citizens compared to those with lower revenue levels[ CITATION Ala15 \l 1033 ]. This, according to Ali and Maryam (2011) is because, after making its normal expenditure, the government has enough money to create new companies and bail out the ailing local parastatals. Besides, high revenue leads to improved infrastructure which attracts investors who in turn create more employment[ CITATION Dam21 \l 1033 ]. From these studies, it is therefore evident that the stated variables of interest (GDP, currency value, inflation rate, consumer price index, and government revenue). Nevertheless, it is still clear that the exact influences of these factors have not been substantially exhausted thus justifying the choice of the study topic and variables. Statement of the problem Unemployment comes with several problems among them poverty and lower standards of living among the unemployed groups. It also results in increased crime types and thus much money spent by the government in rehabilitation[ CITATION Jen12 \l 1033 ]. Therefore, there is a need to come up with possible ways to minimize the unemployment rates in the Maldives. Being that this can be achieved mainly through establishing the possible causes of unemployment, this study is justified as the results will be used for further study and to provide an insight into significant predictors of unemployment within the country.

Research objectives The study has five objectives which are: 1. To establish the influence of GDP on the unemployment rates in the Maldives. 2. To establish the impact of monetary value on the unemployment rates in the Maldives. 3. To determine the influence of the inflation rate on the unemployment rates in the Maldives. 4. To establish the influence of the consumer price index on the unemployment rates in the Maldives. 5. To determine the influence of government revenue on the unemployment rates in the Maldives. Research Questions 1. Is there a significant influence of GDP on the unemployment rates in the Maldives? 2. Does money value significance influence the unemployment rates in the Maldives? 3. Is there a substantial impact of the inflation rate on the Maldives' level of unemployment? 4. Is there an evident impact of the consumer price index on the unemployment rates in the Maldives? 5. Does government revenue influence the level of unemployment in the Maldives significantly? Research Hypothesis 1. Null Hypothesis (H 0 ): There is no evident influence of GDP on Maldives’s unemployment rate.

Alternative Hypothesis (H A ): GDP significantly influences the rate of unemployment in the Maldives. 2. Null Hypothesis (H 0 ): There is no evident influence of currency value on Maldives’s unemployment rate. Alternative Hypothesis (H A ): currency value significantly influences the rate of unemployment in the Maldives. 3. Null Hypothesis (H 0 ): There is no evident influence of inflation on Maldives’s unemployment rate. Alternative Hypothesis (H A ): Inflation significantly influences the rate of unemployment in the Maldives. 4. Null Hypothesis (H 0 ): There is no evident influence of the consumer price index on Maldives’s unemployment rate. Alternative Hypothesis (H A ): The consumer price index significantly influences the rate of unemployment in the Maldives. 5. Null Hypothesis (H 0 ): There is no evident influence of government revenue on Maldives’s unemployment rate. Alternative Hypothesis (H A ): government revenue significantly influences the rate of unemployment in the Maldives. Research methodology Research Design and Data collection This research involved a case study design since it focused on the influence of inflation rates, GDP, currency value with respect to the US dollar, consumer price index, and government revenue on the level of unemployment in the Maldives. The data used for the study was

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secondarily acquired from the world bank database ( https://data.worldbank.org/ ). The data source being secondary, there were no methods of primary data collection and hence factors such as questionnaires were not involved. The exclusion criterion was the year in which data between 1991 and 2020 which resulted in a sample size of 30. Data analysis The data were analyzed using descriptive and inferential statistics. The descriptive statistics involved summary statistics (mean, standard deviation, skewness, minimum and maximum) for the six variables (inflation, revenue, GDP, CPI, unemployment rate, and currency value (USD)). A histogram was constructed to display the distribution of the dependent variable (unemployment rate). For inferential statistics, multiple linear regression analysis was performed on the influence of the independent variables (inflation, currency value with respect to USD, GDP, revenue, and CPI index) on the unemployment rate. The model has the general formula, y = β0+β1x1+…+βnxn in which case, the coefficient values are represented by β and the variable values are represented by x. Data were analyzed using Excel.

Data Analysis Results Descriptive statistics The summary statistics test results for the variables are presented in the table below. Table 1. summary statistics Mean Standard Deviation Skewness Range Minimu m Maximu m Coun t Currency value by USD 0.07723 3 0.009888 0.133981 0.033 0.065 0.098 30 GDP 2.02E+09 1.67E+09 0.720145 5.36E+09 2.44E+08 5.61E+09 30 inflation rate 0.04709 8 0.05714 1.148754 0.218128 -0.01685 0.201274 30 CPI 87.5623 1 24.2245 0.675017 75.9556 56.7504 132.706 30 government revenue 1.85E+09 1.51E+09 0.731643 4.84E+09 2.13E+08 5.05E+09 30

unemployment rate 0.04856 7 0.032542 0.228039 0.1094 0.0076 0.117 30 From the table, the average unemployment rate of Maldives for the period 1991-2020 was 4.86% (SD=3.25%) while the inflation average for the same period was 4.71%(SD=5.7%) showing a wider variation from the mean. In addition, the country realized an average GDP of 2024138818 (SD=1668589904) and an average government revenue of 1847003981(SD=1508471325) for the stated period. For the consumer price index, the average was 87.56(SD=24.22) while that for the currency exchange for the stated period is 0.07(SD=.01). For the stated period, the lowest ever realized rate of unemployment is 0.76% (1991) while the highest ever rate is 11.7% (2009). All the variables were skewed to the right showing that most scores were towards the lower side, a factor that was extreme in inflation (1.15). The rate of unemployment was then displayed using a histogram and this is shown below. Fig 1. Histogram for the unemployment rate The histogram shows a slight skewness to the right thus justifying the 0.23 value gotten from the summary statistics. Inferential statistics The multiple linear regression results are as shown below.

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Table 2. Regression results From the results, currency value by USD, GDP, inflation rate, Consumer price index, and government revenue had a joint significant influence on the unemployment rate in the Maldives (F (5, 24) = 4.78, p<.05). The variables explained 49.89% of the model variation which is an average percentage. Individually, no variable was a significant model predictor as they all had p- values greater than a 5% level of significance. The resulting model equation is, Unemployment = 0.26278183 – 2.62220097 (currency) + 0.000000000176062 (GDP) + 0.027347217 (Inflation) – 0.0000853436 (CPI) – 0.00000000019593 (revenue) This implies that assuming all factors are kept constant, then a unit rise in the currency value results in a 2.62220097 decline in the rate of unemployment. Similarly, increasing the consumer price index and government revenue by a unit each result in a 0.0000853436 and 0.00000000019593 decline in the rate of unemployment respectively. On the other hand, a

positive association was realized between unemployment and GDP and inflation in which case, a unit rise in the value of each results in a 0.000000000176062 and 0.027347217 correspondingly. Discussion and Conclusion The study sought to establish the influence of currency value compared to the USD, inflation, consumer price index, government revenue, and gross domestic product on the unemployment rate in the Maldives. It was established that jointly, these variables had a significant impact on the country’s rate of unemployment. Nevertheless, the opposite was true for the individual variable predictive influence on the dependent variable. Having been discovered to individually influence the unemployment rates by past studies, the insignificance of individual variables can be attributed to the smaller sample size and the presence of the ever-changing influencers of the unemployment rate omitted in the study. While making the comparison to past works of literature, the joint influence significance finding is similar to that of Hafez et al. (2021) who established that the unemployment rate is majorly affected by the interaction effect between GDP, inflation, CPI, currency value, and government revenue. Besides, the study result is similar to that of Gatot et al. (2019) who found out that while these variables, some or all, may display individual insignificance, there is a joint predictive effect that they pose on unemployment rates. While discussing the predictive influence of government earnings, gross domestic product, and inflation rates, Atif et al. (2016) stated that higher earnings by the government result in more investment thus absorbing more people. Besides, a high level of GDP indicates that a country earns more and has high bargaining power in international trade, a factor that attracts more investors and creates more jobs, a statement that’s different from the finding in this study. In a different study, Ladislav (2020) established that high levels of inflation are not healthy for employers and this may cause retrenchment of some workers, a finding different from the one in

the study. Nevertheless, the level of change determines the impact it causes on the employers, for instance, a decimal change in the consumer price index and inflation may result in a small economic impact that’s hardly felt by the employers and as such, these factors fail to influence the job market. The opposite is true for high levels of change in inflation and consumer price index which tremendously affect the job market. It is worth noting from the study and past studies that the above independent variables have a role to play in Maldives’s rate of unemployment. The study set a solid ground through which research is conducted and report made hence the advantage. However, the study has the following limitation. First, the study involved a smaller sample size which likely interfered with the effect size and study power. Secondly, the study did not include most factors affecting the unemployment rate and hence suffered from the confounding effects. For instance, the corresponding condition of time such as the coronavirus pandemic in 2020 and 2021. Moreover, the government conditions in regards to foreign and local employment can affect unemployment rates yet these were not included. Therefore, I suggest a further study that will consider a longer duration, say between 1950 and 2022 as this will give a larger sample. I also suggest the inclusion of more variables in the regression to exhaustively establish the influencers of the unemployment rate within the country. In conclusion, it is found that GDP, inflation, currency value, CPI, and government revenue are jointly significant model predictors and individually insignificant predictors of the model. Nevertheless, having proved from past works of literature that the individual variables also influence the unemployment rate, I make the following recommendations:

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1. The government and concerned parties must seriously consider jointly, inflation rate, CPI index, currency value, GDP, and government revenue while addressing unemployment problems. 2. The government and the concerned parties should also view at an individual level the above independent variable while addressing matters of unemployment. This study result can be used by the government and economic agencies to address the issue of unemployment within Maldives. It can also be used by students as a learning avenue on the rates of unemployment.

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Puspadjuita, E., 2018. Factors that Influence the Rate of Unemployment in Indonesia. International Journal of Economics and Finance, 10(1). Qiwang, Z. X. W., 2020. Factors Influencing Employment Rate and Mobility of Science and Engineering and Economics and Management Graduates in Northeast China: An Examination. SAGE Open. Ramzan, M., 2021. Impact of Inflation and Unemployment on Economic Growth of Pakistan. European Journal of Business and Management Research, 6(4), pp. 282-288. Roshni, B. P. K., 2020. Effect of Population, GDP and Levels of Literacy on Unemployment. International Journal of Innovative Science and Research Technology, 5(1). Salah, a. F. H. A. A., 2018. A Study on the Causes of Unemployment among University Graduates in Kenya: A Case of Garissa County, Kenya. Open Journal of Economics and Commerce, 1(1), pp. 55-60. Savulea, D., 2008. Particularities of the Correlation Between the Unemployment Rate and the GDP in the Dynamics of the Romanian Economy. European Studies, 11(4). Teye, P. L. Y. A. M., 2019. The Impact of Exchange Rate and Unemployment Rate on the Real Gross Domestic Product Growth Rate in Ghana. Journal of Economics and Sustainable Development, 10(18). Trading economics, 2021. Unemployment in Asia. YILMAZKUDAY, H., 2020. Unequal Unemployment Effects of COVID-19 and Monetary Policy across the U.S. States. Journal of Behavioral Economics for Policy.

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