Hassan Heidari; Arash Refah-Kahriz
Abstract
Attitude towards the role of government and reasons for the existence of government have experienced several changes and revisions during the last century. Attitude changes alter the duties and responsibilities assigned to the government and thus change the size and composition of public expenditure. ...
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Attitude towards the role of government and reasons for the existence of government have experienced several changes and revisions during the last century. Attitude changes alter the duties and responsibilities assigned to the government and thus change the size and composition of public expenditure. In the context of these attitudes, there are factors that could explain the changes in the size and the growth of government and consequently the government intervention in the economy over time and among different countries. This study investigates the relationship between government size and macroeconomic variables including economic growth, growth of oil revenues, growth of tax revenues, inflation in Iran using seasonal data during the period of 1990:1 – 2014:4 by applying Markov Regime Switching model. The results show that in the selected model consisting of two regimes with different government sizes, economic growth has a significant negative impact on government size in both regimes of zero and one. But inflation has different effects on government size: it has a negative effect in the regime zero (smaller government) and a positive effect in the regime one (bigger government). Moreover, the growth of oil revenues has a positive effect in both regimes, but the growth of tax revenues has a positive effect only in the regime one. Also, the results indicate that the government size in Iran has often been in the regime one with bigger government size and it is predicted that bigger government will be more sustainable than smaller government.
Hassan Heidari; Parisa Jouhari Salmasi
Abstract
Low and stable inflation with sustainable growth is the first objective of any monetary authority. To achieve this prime goal, reliable forecast of macroeconomic variables play an important role. This paper investigates the forecasting performance of BVAR models with different priors for Iranian economy. ...
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Low and stable inflation with sustainable growth is the first objective of any monetary authority. To achieve this prime goal, reliable forecast of macroeconomic variables play an important role. This paper investigates the forecasting performance of BVAR models with different priors for Iranian economy. For this purpose we use BVAR approach with Gibbs sampling for quarterly data of the Iranian economy from 1989:Q1 to 2007:Q4. The main advantage of this paper is using Gibbs Sampling to estimate BVAR models and use of Quasi BVAR models with Normal Wishart and Minnesota priors in order to compare forecast accuracy of the macroeconomic variables. Comparison of the BVAR with Gibbs Sampler and Quasi BVAR models in this experience shows that the value of MSFE in predicting macroeconomic variables for the four ahead period forecasts in BVAR model with Gibbs algorithms is less than Quasi BVAR models. Generally BVAR model with Gibbs sampling algorithms performs better than Quasi BVAR models in forecasting.
Hassan Heidari; Roghayyeh Alinezhad; Rana Asghari
Volume 19, Issue 60 , October 2014, , Pages 101-132
Abstract
This study investigates the effect of rule of law on inflation rate for the 16 selected MENA countries over the period of 1996-2012. The relationship between variables has been estimated by applying Panel Smooth Transition Regression (PSTR) model and using Non-linear Least Squares (NLS) method of estimation. ...
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This study investigates the effect of rule of law on inflation rate for the 16 selected MENA countries over the period of 1996-2012. The relationship between variables has been estimated by applying Panel Smooth Transition Regression (PSTR) model and using Non-linear Least Squares (NLS) method of estimation. Our results reject the linearity hypothesis, and indicate existence of one continuous transition function with two regimes that gives a threshold at rule of law index of -0.525. Moreover, the results show that the rule of law index, openness index and GDP per capita have negative impact on inflation rate in two regimes that the intensity of the negative impact of these variables increases in the second regime. On the other hand, government consumption expenditure and liquidity have a positive impact on inflation rate in two regimes; the intensity of their positive impact reduces in the second regime. Therefore, the actions such as creating innovative mechanisms for dispute resolution, stabilization in government's plans and objectives and no chain changes in policies enhance the rule of law levels and decrease the inflation rate in this group of countries.
Hassan Heydari
Volume 17, Issue 50 , April 2012, , Pages 65-81
Abstract
This paper investigates the use of different priors to improve the inflation forecasting performance of BVAR models with Litterman’s prior. A Quasi-Bayesian method, with several different priors, is applied to a VAR model of the Iranian economy from 1981:Q2 to 2007:Q1. A novel feature with this ...
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This paper investigates the use of different priors to improve the inflation forecasting performance of BVAR models with Litterman’s prior. A Quasi-Bayesian method, with several different priors, is applied to a VAR model of the Iranian economy from 1981:Q2 to 2007:Q1. A novel feature with this paper is the use of g-prior in the BVAR models to alleviate poor estimation of drift parameters of Traditional BVAR models. Some results are as follows: (1) our results show that in the Quasi-Bayesian framework, BVAR models with Normal-Wishart prior provides the most accurate forecasts of Iranian inflation; (2) The results also show that generally in the parsimonious models, the BVAR with g-prior performs better than BVAR with Litterman’s prior
Hassan Heydari
Volume 16, Issue 46 , April 2011, , Pages 77-96
Abstract
This paper focuses on the development of modern non-structural dynamic multivariate time series models and evaluating performance of various alternative specifications of these models for forecasting Iranian inflation. The Quasi-Bayesian method, with Literman prior, is applied to Vector autoregressive ...
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This paper focuses on the development of modern non-structural dynamic multivariate time series models and evaluating performance of various alternative specifications of these models for forecasting Iranian inflation. The Quasi-Bayesian method, with Literman prior, is applied to Vector autoregressive (VAR) model of the Iranian economy from 1981:Q2 to 2006:Q1 to assess the forecasting performance of different models over different forecasting horizons. The Bewley transformation is also employed for the re-parameterization of the VAR models to impose the mean of the change of inflation to zero. Applying the Bewley (1979) transformation to force the drift parameter of change of inflation to zero in the VAR model improves forecast accuracy in comparison to the traditional BVAR.[1]
[1]. Acknowledgement
I would like to thank Paolo Girodani for comments and providing some GAUSS procedures, Ronald Bewley, David Forrester, Jan Libich, and two anonymous referees for their helpful comments and suggestions on an earlier version of this paper. Financial support from the Urmia University is gratefully acknowledged. The usual disclaimer applies.
Hassan Heydari; Soheila Parvin
Volume 12, Issue 36 , October 2008, , Pages 59-84
Abstract
This paper investigates the forecasting performance of different time-varying BVAR models for Iranian inflation. Forecast accuracy of a BVAR model with Litterman’s prior compared with a time-varying BVAR model (a version introduced by Doan et al., 1984); and a modified time-varying BVAR model, ...
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This paper investigates the forecasting performance of different time-varying BVAR models for Iranian inflation. Forecast accuracy of a BVAR model with Litterman’s prior compared with a time-varying BVAR model (a version introduced by Doan et al., 1984); and a modified time-varying BVAR model, where the autoregressive coefficients are held constant and only the deterministic components are allowed to vary over time. Application using quarterly data of the Iranian economy from 1981:Q2 to 2006:Q1 shows that the performance of different specifications of time-varying BVAR models for forecasting inflation depends on the number of lags, hyper parameter that controls time variation, and forecast horizons. Our results, however, show that the modified time-varying BVAR model performs much better than other models regardless of the factors above.
