Inflation is one of the key macroeconomic variables that its precise forecasting is the goal of policy makers and in particular the central bank. VAR model has a long history as a tool for forecasting and policy analysis; but the problem with this method is that it uses a little theoretical information about the relationships between variables. In addition, in VAR models, many parameters need to be estimated, some of them may be meaningless. Following this, the idea of hybrid models was introduced. One of the hybrid models is the DSGE-VAR model. This model combines DSGE, which is a structural model and more reliant on theory, with a VAR that provides better fitting data. In this study at the beginning, the theoretical structure and results of the estimation of the DSGE-VAR model for Iran's Economic Data are presented. Further, the forecasting of this method are compared with other models such as unrestricted VAR and Minnesota VAR. All three models are estimated recursively from the period 1991: 1 to 2012: 4 and then used to forecast inflation for one to eight-quarters-ahead over an out-of sample from 2011: 1 to 2015: 4. Comparison of the accuracy of forecasting of the above methods using the RMSE index shows a better performance of the DSGE-VAR approach compared to other models.

According to endogeneous growth models, variables such as investment or R&Dexpenditures can permanently influence economic growth. However, depending on the economy under study ,this hypothess can be rejected. To this end, the effects of R&Dexpenditures and Investment on the growth rate is examined for the Iran economy. The proxy for R&Dexpenditure is government research budget. First, The stationary of the variables is evaluated. Then, by a single-equation dynamic model, the permanent effects of R&D expenditures and also, capital growth rate on econimic growth rate is examined and finally the magnitude,timing and persistence of the shocks are estimated by a VAR model.

Asset markets play a pivotal role in dynamic economies by facilitating resource allocation, preserving wealth value, and shaping expectations about the future. Their fluctuations can exert broad effects on investment behavior and economic growth. In the case of Iran—an economy characterized by chronic inflation and recurrent shocks—understanding the effects of inflation on asset markets such as stocks, coin, gold, and housing is of particular importance. The nature of Iran’s economy, marked by diverse shocks and structural changes, renders the relationships between inflation and asset markets both dynamic and nonlinear. The objective of this study is to conduct a dynamic and nonlinear analysis of the impact of inflation on Iran’s asset markets and to examine the cross-market spillovers among them. To achieve this, monthly data spanning the period March 2011-February 2025 were collected from reliable sources and analyzed using the Time-Varying Parameter Vector Autoregressive (TVP-VAR) model within the Diebold–Yilmaz connectedness framework. This methodological approach allows for assessing time-varying dynamics in market behavior and the intensity of inflationary effects. The empirical findings reveal that inflation exerts its strongest influence on the gold and coin markets, which act as safe havens against inflationary shocks. The housing market demonstrates a weaker yet statistically significant response, while the stock market exhibits the lowest sensitivity to inflation fluctuations. Moreover, substantial cross-market spillovers are observed during inflationary periods, intensifying under crisis conditions.

This paper contains results of the first part of a study in which a Vector Auto-Regression (VAR)/vector Error Correction (VEC) model is developed and estimated to investigate dynamics of petroleum markets in OECD. Time series of the model comprises monthly data for the variables: demand for oil in OECD, WTI in real term as a benchmark oil price, industrial production in OECD as a proxy for income and commercial stocks of crude oil and oil products in OECD for the time period of January 1995 to March 2007. The detailed results of this empirical research are presented in different sections of the paper, nevertheless, the general result that emerges from this study could be summarized as follows: (i) There is convincing evidence of the series being non-stationary and integrated of order one 1(1) with clear signs of co-integration relations between the series. (ii) The VAR system of the empirical study appears stable and restore its dynamics as usual following a shock to the rate of changes of different variables of the model taking between 5 to 8 periods (months in our case). (iii) It appears that the null hypothesis of 'the expected mean of the series being insignificant from zero', cannot be rejected in 5% level for each of four time-series indicating lack of statistical proof for presence of the deterministic trend in time-series of concern, (iv) Normality tests and histograms of the series reveals that while distribution of the samples in level differ from theoretical normal distribution however this is not the case for the differenced time series and for the residuals, on the other hand autocorrelation functions of the series are consistent with unit root process .(v) We find the lag length of 2 as being optimal for the estimated VAR model. (vi), Significant impact of changes in the commercial crude and products' inventory level on oil price and on demand for oil is highlighted in our empirical study and in different formulations of the VAR model indicating importance of changes in stocks' level on oil market dynamics. (vii) Income elasticity of demand for oil appear to be prominent and statistically significant in most estimated models of the VAR system, while price elasticity of demand for oil is found to be negligible and insignificant in the short-run.

this study employs a structural vector autoregression (SVAR) model to investigate the macroeconomic shocks on Malaysian tourism industry, especially how the economy dynamically responds to oil price shocks, exchange rates, changes in price level, exports, economic growth and tourism income during the study time period from January 2001 to December 2012. The results indicate that oil price shocks, economic growth, exchange rate, and exports have a contemporaneous inverse impact on tourism revenues except for consumer price index which has a positive impact. This study added instant information to manage tourism industry in Malaysia. The findings of the study are useful to implement a number of corrective measures for the promotion of tourism in a country.

In recent decades, volatility of oil prices has led to such consequences as macroeconomic turbulences. Most of the researches look at the matter from oil importer's point of view while oil producers are usually neglected. This paper explains the relationship between oil price shocks and economic growth and inflation by the econometric methods like VAR model and OLS regression. Based on quarterly data, an unrestricted autoregressive model is estimated in order to gauge short run effects of oil shocks on different variables such as exchange rate, money, government expenditure, inflation and GDP. Long run effects are also measured by the aid of a co-integration autoregressive model. Impulse-response technique is used to estimate reaction of aforementioned variables to different shocks. At the end, the paper proposes the economic policies based on statistical results.

According to Fisher's theory, an increase in expected inflation results in a unit increase in nominal interest rates, and the real interest rate, which plays a key role in shaping investment and savings behavior, remains constant, and this factor, although inflation Leads to the neutralization of monetary policy;On the other hand, based on the theory of quantity of money and the direct relationship between the velocity of money and the general level of prices, as well as the direct effect of the velocity of money on interest rates, raising interest rates is expected to increase inflation.This effect of interest rates on the inflation index (according to some economists) is not only related to inflation and affects other macroeconomic variables, but the important issue is the type, manner and amount of this effect in the short term and It is a long-term study in the present study using VAR and VECM methods and in the period of 1360 to 1399.The results of the study show the confirmation of Fisher's theory in the Iranian economy both in the short and long term, and suggest that there is a positive and significant relationship between the interest rate variable and the inflation index in the Iranian economy.In addition, variable interest rate fluctuations overshadow other macroeconomic indicators, as this relationship is inverse for the economic growth index and physical investment and direct for the inflation rate index.

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.