Determinants of unemployment in less developed countries

Unemployment is a major issue all over the world in both developed and under developed countries. This study analyzes those factors which determine unemployment in Pakistan. The data is taken from1990-2015 to see the empirical relationship between GDP, Population, Technical & Vocational education, degree colleges and universities enrollment. ARDL (Auto Regressive Distributed Lag) approach is used to check the determinants of unemployment in Pakistan. Long run results show that there is a negative relationship between GDP and unemployment. Population has positive and significant relation and technical & vocational education has positive and insignificant relation with unemployment in Pakistan. The results of Short run ECM-1(Error correction model) show that the negative and significant relationship with unemployment. The CUSUM and CUSUMQ (Graph) are represent that model is structurally stable within critical bound at 5% level of significance.


Introduction
Unemployment is the major problem of every country.Unemployment is an ever rising in Pakistan as determined by Ahmed at.al [1].The variables are used in this paper, Population growth rate, inflation rate, Foreign Direct Investment and Gross Domestic Product growth rate in framework of Pakistan economy.also.The time series data from 1973 to 2010 was taken to analyze using the ARDL test.The results show that unemployment has significant positive relationship with output gap, Productivity and Economic Uncertainty while it has statistically significant negative relationships with Gross Fixed Investment and Trade .The data was taken from 34 million people are unemployed in all around the world.According to the Labor Force Survey 2013-14, the total labor force is 60.09 million in the country.Out of this, 3.58 million people are unemployed and 56.52 million people are employed.[4,5]"According to IPR's factsheet, 2012-13 and 2014-15 the number of jobs created was 1.4 million.Accordingly, the decrease in the number of unemployed workers was 100,000.As such, by the end of 2014-15, the number of unemployed workers was 3.6 million.However, the total number of unemployed currently in Pakistan 5.3 million" The latest Labor Force Survey of 2014-15 released by the Pakistan Bureau of Statistics [10].

Data and methodology
In the determinants of unemployment we take the data from Economic Survey of Pakistan [2,4,5,6,7] and from "The World Bank" [12].Data is collected from 1990 to 2015.The dependent variable is unemployment and the Independent variable is GDP, Population, Technical & Vocational Education and Universities enrollment.
For this purpose we use Econometrics model Unemployment=f (GDP, POP, T & V, DEG COLL, UNI NUM).GDP= All finale goods and services produce in the market in a given year.There is inverse relationship between GDP and unemployment.
POP= the number of persons are in a country called population.And if the population are increased then unemployment also raise.Population data in million.
T&V=technical and vocational data in thousands.

DEG COLL=no of enrollment in degree colleges data 16 years of qualification (In numbers).
UNI=universities enrollment data in numbers (16 years of qualification

Model
In the model of the paper where unemployment is the dependent variable and GDP, Population, Technical and Vocational education, Degree college's enrollment and Universities enrollment are independent variables.In the Table 3 estimated long run coefficients GDP has negative and insignificant relation with unemployment while population has positive and significant relationship with unemployment, Technical and vocational education and degree colleges has positive and insignificant relation with unemployment.In the Table 4 According to the short run results coefficient of gdp, population, technical and vocational education and universities enrollment are .062933,.011976and 0013848.The short run coefficient is smaller than long run.ECM (-1) is one period lag value of error term that is come from long run relationship.ECM values represent that the disequilibrium of short run will be fixes long time period.In CUSUM chart the lines are not crossing each other means that there is no issue of recursive residuals in terms of mean.Similarly, there is no issue of recursive residuals in terms of variance.This study is helpful for the policy makers which are trying to control unemployment in Pakistan.Government should increase the numbers of tech n vocational institutes.These institutions can play a vital role to decrease the unemployment in Pakistan.

Figure 1
Figure 1 and 2 represent that cumulative sum of recursive residuals the cumulative sum of square of recursive residuals.Both CUSUM and CUSUMSQ are within critical bound of 5% so this shows that model is structurally stable.

3 Conclusion
The impact of GDP, Population, Technical & Vocational education, Degree college's enrollment and universities was examined on the unemployment rate of Pakistan and the period is 1990-2015.We have used ARDL (Auto Regressive Distributive Lag) test on it.The Long Run results have shown that there is negative relation between GDP and unemployment.Population has positive relation with unemployment while Technical & Vocational education has positive effects on unemployment.Short Run results explain that Population, Technical and Vocational Education have positive effects.ECM (-1) represents the lag value one period of error term that come from long run relation.ECM (-1) represent disequilibrium of short run.ECM (-1) has statistically significant and negative value.The main focus of our study shows that our SHS Web of Conferences 48, 01015 (2018) https://doi.org/10.1051/shsconf/20184801015ERPA 2018 education or technical and vocational education system may control the determinants of unemployment in Pakistan.
Hand Book of State Bank of Pakistan 2010, This study applies augmented dicky fuller and Philips perron Unit Root tests to confirm the stationary of the

Table 1 .
Augmented Dicky-Fuller (ADF) test of stationarity of time series data In the Table 1 Augmented Dicky Fuller test are apply to see the stationarity of all the variables