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-, Sneha Vardhan (2024) Estimating a job vacancy duration model to include a range of labour market variables and labour slack in Netherlands Economy. Masters thesis, Dublin, National College of Ireland.
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Abstract
Introduction: The labor market of the Netherlands, which is distinguished by high rates of participation and strong social safety nets, is essential to the economic stability of the nation. Comprehending the length of job openings is essential for evaluating the productivity and efficiency of the labor market. In order to examine the effects of economic factors including GDP, inflation rate, unemployment rate, minimum wages, and vacancy rate, this study examines job vacancy lengths from 1997 to 2023. The study uses both the friction cost approach, which takes into account the economy's capacity to replace people, and the human capital approach, which calculates productivity losses based on prospective future wages. This two-pronged strategy seeks to both influence policy-making and offer insights into the economic consequences of job openings.
Objective: This study's main goal is to estimate the length of job vacancies in the Dutch labor market using a recently assembled dataset that extends until 2023. The study intends to expand the current vacancy duration equation to account for current circumstances and investigate the influence of economic variables on vacancy durations. The research aims to improve understanding of the factors influencing job vacancy durations and provide policy recommendations for enhancing labor market efficiency by comparing the friction cost and human capital methods.
Method: Using a large dataset spanning from 1997 to 2023, this study uses a quantitative methodology to examine GDP, inflation, unemployment, minimum salaries, and vacancy rates. In order to evaluate variable correlations, collinearity, and important assumptions, multiple linear regression is utilized to examine the links between these factors and job vacancy durations. A more comprehensive formula for the length of vacancies is created, and statistical analysis is conducted using SPSS software, offering a solid assessment of labor market dynamics.
Results: The results of the analysis showed that the vacancy rate is a strong predictor of the length of job openings, with a positive correlation showing that longer durations are associated with greater vacancy rates. With an R2 of 0.981, the model fits the data quite well, accounting for 98.1% of the variation in vacancy lengths. Although there were no significant direct effects observed for GDP, inflation, unemployment, or minimum wages, the model as a whole was statistically significant (F-statistic = 194.921, p < 0.001). The Durbin-Watson statistic showed no discernible autocorrelation, however the results of normality tests were inconsistent. Typical diagnostic values did not raise concerns about multicollinearity.
Conclusion: The results of the analysis showed that the vacancy rate is a strong predictor of the length of job vacancies, with a positive connection suggesting that the study shows that the vacancy rate has a major impact on the length of employment vacancies in the Netherlands, while the direct influence of other variables is shown to be modest. In order to alleviate labor market inefficiencies and increase productivity, focused policy actions are necessary, as evidenced by the strong model fit and significant predictors.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Hanly, Paul UNSPECIFIED |
| Uncontrolled Keywords: | Job Vacancy Duration; Labor Market Efficiency; Human Capital Approach; Friction Cost Approach; Netherlands; Linear Regression; Economic Variables; Policy Recommendations |
| Subjects: | H Social Sciences > Economics H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work > Labour Market H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work > Unemployment |
| Divisions: | School of Business > Master of Science in International Business |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 11 Aug 2025 08:45 |
| Last Modified: | 11 Aug 2025 08:45 |
| URI: | https://norma.ncirl.ie/id/eprint/8468 |
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