Evaluating the Effects of Fiscal and Monetary Policies on the Unemployment Duration in Industrial Countries

Document Type : Original Article


1 Ph.D. Candidate in Economics, Faculty of Economics and Administrative Sciences, University of Mazandaran, Babolsar, Iran

2 Associate Professor of Economics, Faculty of Economics and Administrative Sciences, University of Mazandaran, Babolsar, Iran

3 Professor of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran


We investigated the effects of fiscal and monetary policies on the conditional distribution of unemployment duration in industrial countries to understand how job search time reacts to macroeconomic policies. We use data from four advanced countries, including the United States, Canada, France, and Australia, over the last two decades and apply the Bayesian quantile method to do the empirical analysis. We also employed the Bayesian panel data model with heterogeneous slopes over cross-sections. The evidence shows that monetary and fiscal policies heterogeneously affect different parts of the distribution of unemployment duration. Also, estimates show that government budget surplus is positively correlated with all quantiles of unemployment duration. In addition, nominal interest rate is negatively associated with the lower parts of the unemployment duration distribution, while this correlation is positive for high quantiles. The estimates of the heterogeneous slopes model reveal that fiscal and monetary policies are more effective in the US compared to other countries.


- Blanchard, O. J., & Diamond, P. (1994). Ranking, Unemployment Duration, and Wages. Reviewof Economic Studies, 61(3), 417-434.
- Bover, O., Arellano, M., & Bentolila, S. (2002). Unemployment Duration, Benefit Duration and the Business Cycle. The Economic Journal, 112(479), 223-265.
- Galvao, A. F., Juhl, T., Montes-Rojas, G., & Olmo, J. (2018). Testing slope homogeneity in quantile regression panel data with an application to the cross-section of stock returns. Journal of Financial Econometrics16(2), 211-243.
- Campolieti, M. (2001). Bayesian semiparametric estimation of discrete duration models: An application of the Dirichlet process prior. Journal of Applied Econometrics, 16, 1-22.
- Dashtebozorgi, Z., Keshavarz, G., Piraee, K. & Zare, H. (2019). The Effects of Unemployment Duration, Unemployment Insurance, and Occupational ‎‎Training on Wage. Journal of Economic Research (Tahghighat-E-Eghtesadi), 54(4), 965-993 (In Persian).
- Feizpour M A. (2011). Unemployment Duration and Its Determinants: Evidences from Job Seekers in Yazd Province during the Third Development Plan. Social Welfare Quarterly, 10 (39), 327-356 (In Persian).
- Ganjali, M. (2010). Statistical analysis of factors affecting unemployment duration. The Iranian Statistics Research Institute (In Persian).
- Ghasemzadeh, S., Ganjali, M., & Baghfalaki, T. (2020). Bayesian quantile regression for joint modeling of longitudinal mixed ordinal and continuous data. Communications in Statistics-Simulation and Computation49(2), 375-395 (In Persian).
- Geraci, M., & Bottai, M. (2007). Quantile regression for longitudinal data using the asymmetric Laplace distribution. Biostatistics8(1), 140-154.
- Hadian, E. (2005). Study of the effect of education of job seekers on the duration of their unemployment (case study of Shiraz). Journal of Economic Research, 40(2), 217-238 (In Persian).
 - Kherfi, S. (2015). Determinants of unemployment duration. The Egyptian Labor Market in an Era of Revolution, 90.
- Kriaa, F., Bouhari, M., & Mathlouthi, Y. (2020). Determinants of unemployment duration for young men and women in Tunisia. Economics, Management and Sustainability, 5(2), 78-95.
- Kupets, O. (2006). Determinants of unemployment duration in Ukraine. Journal of Comparative Economics, 34(2), 228-247.
- Koenker, R., and Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
- Luo, Y., Lian, H., & Tian, M. (2012). Bayesian quantile regression for longitudinal data models. Journal of Statistical Computation and Simulation, 82(11), 1635-1649.
- Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica74(4), 967-1012.
- Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93.
- Rodgers, W. M. (2008). African American and White Differences in the Impacts of Monetary Policy on the Duration of Unemployment. American Economic Review, 98 (2), 382-86.
-Sadeghinezhad, M. & Hassani Darmian, G. (2020). Changes in Unemployment Life Expectancy in the Provinces of Iran during 2006-2016. Population Studies, 6(1), 231-260 (In Persian).
- Seo-Hyeong, L.E.E., & Sunghee, C. H.O.I. (2016). Estimating Determinants of Unemployment Duration in Korea: Evidence from the Korean Labor and Income Panel Study. Editorial Board, 11(4), 42.
- Swamy, P. A. (1970). Efficient inference in a random coefficient regression model. Econometrica: Journal of the Econometric Society, 311-323.
- Zamanzadeh, A & Banerjee, R. (2021). Heterogenous Environmental Kuznets Curve. Working Paper, Business School, University of South Australia.
- Zamanzadeh, A., Chan, M. K., Ehsani, M. A. & Ganjali, M. (2020). Unemployment duration, Fiscal and monetary policies, and the output gap: How do the quantile relationships look like? Economic Modelling, 91(C), 613-632.