determinants of youth unemployment
229018284
Determinants of Youth Unemployment: Evidence from Jordan
Fuad M Kreishan Mohammad Selim
212802330
Socioeconomic Determinants of Youth Unemployment in Ethiopia, the Case of Wolaita Sodo Town, Southern Ethiopia
According to UN Secretariat, UNESCO,UNICEF, WHO, UNFPA and ILO youth are defined these individuals whose age is in between 15 24years, while for UN Habitat (Youth Fund) and the African youth charter, the age range is from 15 32 and 15 35, respectively. For others like organization for Economic Co operation and Development (OECD) defines youth as those men and women in between 15 and 29 years of age. To achieve the objective of this paper is to examine the socio economic determinants of urban youth unemployment logistic model was used. A simple random sampling technique employed to select 395 youth were used. Both quantitative and qualitative data were collected from sampled youth unemployed persons through questionnaire and interview. Both descriptive and econometric data analyses techniques were applied. From the econometrics result revealed that confidence ,education status access to information human related factor, institutional factors ,socioeconomic and demographic factors were significantly affect the youth unemployment status in the study area The result also indicates that the higher months spent on searching, the higher the probability of getting job. This shows the cost of job search is positively related with employment status of the youth, as cost of search increases the higher the probability of being employed. The result also indicates that educational level of the youth's household head has a negative and statistically significant effect on employment status of the youth at 10 percent level of significance. This finding is inconsistent with the general fact and the hypotheses of this study. Since confidence level of the youth matters for employment status of the youth, the concerned bodies should develop the confidence level of the youth by providing different trainings for the youth. The concerned body, especially the government should provide facilities related with information access like mass media and magazines in the study area. Keywords employment, Youth unemployment, Binary logistic regression. DOI 10.7176/DCS/9 10 05 Publication date :October 31 st 2019
Developing Country Studies
T Tegegne
159304519
The Determinants of Youth Unemployment: A Panel Data Analysis of OECD Countries
The aim of this study was to determine some of the key factors affecting youth employment from 2000 2015. Youth unemployment rate (YU) was the dependent variable while consumer price index (INF) domestic gross savings (GS) labor productivity (LP) and economic growth rate (GR) were the independent variables. Data from 31 OECD countries were obtained from World Bank (WB) and OECD databases. Panel Data Analysis was used to analyze the data. The results show that growth, inflation, and savings affect youth unemployment negatively while labor productivity affects youth employment positively. It is therefore concluded that growth, inflation, savings and labor productivity are among the key determinants of youth unemployment.
Riza Bayrak Halim Tatli
158586463
DETERMINANTS OF YOUTH UNEMPLOYMENT IN SOUTH AFRICA
The study empirically investigates the determinants of youth unemployment in South Africa using quarterly time series data from the period of 2008 to 2015. The main objective of this study is to investigate the main determinants of youth unemployment in South Africa. The study used or employed Vector Error Correction Model (VECM) The variables used in this study are Youth unemployment, education, Gross Domestic Product (GDP) inflation and Foreign Direct Investment (FDI) all these variables affect youth unemployment directly and indirectly. The data for this study was obtained from International Monetary Fund (IMF) World Bank and South Africa reserve bank (SARB) The results showed that education has a negative relationship and statistically significant to youth unemployment. Diagnostic and stability tests revealed that the model is good and stable in determining the impact of the determinants of youth unemployment.
Dipali Pravin Chhaganlal Patel Ireen Choga
55805357
Multilevel Modelling of Determinants of Youth Unemployment in Urban Ethiopia: Bayesian Estimation Approach
The main objective of this study was to identify and explain the effects of the Demographic and Socio economic determinant factors of Youth unemployment in urban of Ethiopia. The data used for this study is the 2016 Ethiopian Urban Employment Unemployment Survey (UEUS) which was conducted by Central Statistical Agency (CSA) of Ethiopia. The statistical methods of data analysis are multilevel logistic regression models and Bayesian multilevel models and the parameters are estimated by using maximum likelihood estimation method and Bayesian estimation method by Stata and WinBUGS software. The analysis result revealed that Out of the 3870 youth considered in the analysis, 1,757 (45.4% youth were unemployed, while 2113 (54.6% youth were employed at the time of data collection. Region, Sex of youth, Age of youth, Literacy status, marital status, Type of Training, Steps taken to search work, Household size and Educational level are found to be the significant determinants of youth unemployment in urban Ethiopia. The multilevel logistic model revealed that the random intercept is better fit than null and random coefficient multilevel models. The intra correlation coefficient suggests that there is clear variation of youth unemployment status across the region of urban Ethiopia. The result of classical and Bayesian multilevel shows high prevalence of unemployment among youth and the probability of being unemployed for youth was found to decline with increasing age, literacy level, training, educational level and household size.
Teshita Uke Chikako
54072222
Determinants of Youth unemployment in Developing Countries: Evidences from Tanzania
The aim of the study was to examine the factors which determine youth unemployment in Tanzania and suggest way forward towards reduction of the problem. The study uses Multinomial logistic regression model (MLM) to analyze the determinants of unemployment in Tanzania. The findings of the study show that gender, geographical location, education, skills and marital status are all significant factors in explaining the difference in youth employment status in Tanzania. From the findings the study several recommendations are made, first, the government and policy makers should review job market laws and regulation in order to promote a smooth transition of youth from education to job market. The government should create specific interventions especially in the creation of more formal jobs and strengthening job market regulation relating to youth people to ensure that all youth with education or skills realize their investments in education and contribute to the country development. The study also recommends that the government and policy makers should strengthen the laws and regulation relating to gender balance in the job market in order to give equal chance to the youth with the same level of skills or education. Keywords: Youth unemployment, Developing countries, Tanzania
Robert Ebihart Msigwa Erasmus Fabian Kipesha
168764543
Determinants of Youth Unemployment; Evidence from Ethiopia
Background: Youth employment presents a particular challenge to Ethiopia; the country faces growing youth landlessness in rural areas and insignificant rural job creation, potentially leading to an increase in migration to urban areas. Objective: The main objective of this study is so to identify and describe the determinants of youth unemployment in Ethiopia. Design: The sampling technique employed was multistage stratified cluster sampling. Results: The study is made based on the 2011 Ethiopian Demographic and Health Survey (DHS) which was conducted by Central Statistical Agency (CSA) of Ethiopia. The analyses result revealed that about 10.4% of the youth are unemployed while 89.6% are employed. The regional variations, access to electric power, age, gender, access to market information, economic status of their families and youthaEUR(tm)s educational level are found to be the significant determinants of youth unemployment in Ethiopia. Conclusion: The government should facilitate formalization of informal employment sector in order to motivate more youth to engage in different activities which are currently considered to be informal. This will help to reduce the problem of youth unemployment especially on skilled and educated youth in both urban and rural areas.
Amanuel Disassa Abshoko
1198763
Determinants of Youth Unemployment in Urban Areas of Ethiopia
Youth Unemployment is one of the most critical issues at global level. It represents the underutilization of scarce and precious resources, that would be important for nations' socio economic development. This study deals with identifying the main factors responsible for youth unemployment and constraints they face in self employment in Ethiopia. It is based on the cross sectional data collected by Central Statistical Agency (CSA) in 2015. From all regions of the country, a total of 16,984 samples are considered for analysis. Using descriptive and cross tabulation analysis, the study shows that youth unemployment is highly related with regional location, sex, marital status and education. The analysis also shows youths' dream to create their own job is constrained highly by shortage of finance and lack of work place. The government and others stakeholders need to consider the above determinants and challenges for future intervention.
Muhdin Muhammedhussen Batu
157079663
Macroeconomic Determinants of Youth Unemployment and Inactivity Rates in Bangladesh
This paper identifies the macroeconomic determinants of youth unemployment and inactivity rates in Bangladesh by using Labour Force Survey Data (LFS) 2013. It finds that although aggregate labour market condition does have significance implication for the job market status, the demographic characteristics have a greater influence. It also found that tertiary education has positive significant impact on the rate of not employment, and visualize the existing mismatch between labour demand and the quality of labour supply.
Mst Morium Khatun
199596501
DETERMINANTS OF YOUTH UNEMPLOYMENT IN AGANANG MUNICIPALITY, LIMPOPO PROVINCE
Kwabena A Kyei