Showing 4 results for Unemployment
Hossein Amiri, Dr Ebrahim Gorji,
Volume 2, Issue 3 (3-2011)
Abstract
The Phillips curve usually has been estimated in a linear framework which implies a stable constant relationship between inflation and unemployment. Some of the studies claim that the slope of the Phillips curve is a function of macroeconomic conditions and also the relationship is asymmetric. This article deals with a smooth transition regression model for relationship between inflation and unemployment for Iran, during the period of 1971 -2007. Smooth transition regression model is a non linear time series regression model which could be considered as developed form of regime switching regression model. Results show that there is a negative and nonlinear relationship between inflation and unemployment in short-term. Regarding this result it's highly important for policy makers to be able to make a relationship between these two variables
Dr Hassan Taee, Dr Javid Bahrami, Sima Bagheri,
Volume 4, Issue 13 (10-2013)
Abstract
One of the empirical relationships that have been used to study the dynamics of labor market is the Beveridge curve -the scatter plot of unemployment rates versus vacancy rates- that is used to summarize the state of that market. The starting point for deriving the Beveridge curve is a matching function between unemployed workers and vacant jobs.
In this research, provincial data are combined to estimate the Beveridge curve and the matching function of Iran. The matching function is estimated using provincial data for the period 1993-2008 and for estimating the Beveridge curve, provincial data for period 2005-2008 are used. The outcomes imply that the number of unemployed workers and vacant jobs has a positive and significant relationship with successful job matches. The elasticity of matching function for the unemployed and job vacancies equals 0.24 and 0.79, respectively. The Beveridge curve depicts a convex and negative relationship between unemployment rate and vacancy rate, although the relationship is not strong.
Saeed Eisazadeh, Mohammad Kazem Naziri, Hadi Naeini,
Volume 8, Issue 30 (12-2017)
Abstract
One of the causes of unemployment is lack of fit between individual skill and needs for skills in the community. The situation of mismatch between the demand and supply of labour, particularly in terms of skills is defined as structural unemployment. Therefore, in this study quantitatively explores the impact of skill mismatches one of the main parameters of structural unemployment on unemployment rate. For this purpose of information available in the Labour Force Survey from 2006 to 2013 is used. Skill mismatch index is calculated from the root mean square error in supply and demand for skills. According to results of this study, skill mismatch have a significantly and positively effects on the unemployment rate. So thata1%increase in skill mismatch index led to an increase in the unemployment rate will be 0.13%. Therefore, creating exact information about job vacancies , reforming the contexts of courses and creating new fields in new areas according to necessities of entrepreneurs in order to updating of applicants knowledge should be mentioned.
Davood Manzoor,
Volume 12, Issue 46 (12-2021)
Abstract
Higher Education (HE) in Iran have been subject to a major expansion and massification in the recent years, in a way that number of students approximately tripled from 2006 to 2016. This would have possibly affected labor market or unemployment rate of the country. Considering both provincial and national level, this study investigates the relationship between HE expansion and unemployment rate in the recent era (2006-2018) empirically. In this regard, number of assignments, students, and the state budget allocated to HE institutions are taken as variables indicating HE expansion so that their relationship with unemployment rate can be explored. The empirical methodology of this study in national level is to consider trends and calculating correlations for different lags. In provincial level, Granger causality and dynamic panel data regression with systemic GMM estimators are utilized as methods of the analysis. The results show a positive significant correlation exists between the state budget of HE and unemployment rate. Moreover, in provincial level, number of students and assignments Granger cause unemployment in some lags. Dynamic panel data model with numerous specifications also approve a positive significant relationship between HE expansion in provinces and their unemployment rate, however, the effect is not the same considering different models, especially for number of students.
