فهرست مطالب بهرام آدرنگی

According to the economic literature, the exchange rate is one of the important channels of money transfer, so that changes in the exchange rate play an important role in creating the competitiveness and uncertainty of the economy. This can put monetary policy changes on inflation and production growth under different conditions in different conditions. In this regard, this article has investigated the role of exchange rate in the effect of money on inflation and gross domestic product growth by using the seasonal time series data of 1370-1400 and using the time-varying auto-correlation parameter method (TVP-VAR). The results of this study show that the lower the variance of the exchange rate growth, the more effective the monetary policy is in curbing inflation. On the other hand, if the average growth of the exchange rate is close to the growth of the monetary base, then the monetary policy will increase production. Also, if the exchange rate grows more than the monetary base, inflation increases and GDP growth decreases. The results of this research confirm that the growth of the monetary base more than the economic capacity leads to an increase in inflation and a decrease in production growth, and this inflationary process leads to an increase in the exchange rate. In such a structure of the economy, where high money printing is a prominent feature, the suppression of the exchange rate provides the basis for increasing the currency jump, and the currency jump is an important factor in strengthening the recessionary inflation in the economy. Therefore, the policy recommendation of the present study is to reduce the growth of the monetary base and not to manipulate the exchange rate

Consumption as the most stable variable of GDP, plays an important role in the economy. According to consumption theories, the form of the consumption function in the short and long run changes the coefficients of macro-variables multiplier, This has an effect on how macro policies affect economic variables. In this regard, in the present study, an attempt has been made to empirically test the hypothesis of the ratch effect of Duesenberry consumption using annual time series data of the Iranian economy during the period 1976-2020. For this purpose, the Autoregressive Distributed Lag (ARDL), BMA_ADL and deep learning method LSTM (Long short term memory) has been used. results indicate that this hypothesis is not consistent for Iran. In other words, empirical evidence shows that, contrary to Dusenberry's theory, the slope of the consumption function in the short term is higher than the slope of the long-run function. As a result, the Multiplier coefficient of demand management policies in the short run is more than the long run. This pattern of consumption behavior can be called the precautionary behavior of households, which originates from Iran's economic conditions.

The main purpose of this research is to investigate the important economic factors affecting the exchange rate pass-through to the Consumer Price Index (CPI) of Iran during the period 1993 to 2020. In this regard, by using the two methods of Bayesian model averaging (BMA) and weighted average least squares (WALS), which have been widely considered in recent years, the important factors affecting the exchange rate transition and the order of importance of these variables in Iran are determined, as well as, Random Forest (RF) algorithm has been used to determine the importance and ranking of identified factors.The results of BMA and WALS methods indicate that the variables of government size, level of development, economic uncertainty, and economic conditions are among the most important macroeconomic factors affecting the exchange rate. According to the research findings, controlling the effects of the exchange rate increase on consumer prices (exchange rate pass-through), reducing the size of the government, controlling economic uncertainties, improving economic conditions, and improving the level of development is an inevitable necessity in Iran, Therefore, The most important policy recommendations of this research are to control the effects of the exchange rate increase on the consumer price index in Iran

The main purpose of this study is to investigate how production growth is affected by liquidity growth, exchange rate growth and inflation. Considering that many macro variables affecting economic growth have high frequencies compared to economic growth; Ignoring this problem causes the loss of information and the lack of recognition of the exact relationships between variables. In this study, an attempt has been made to evaluate the monthly effects of Exchange rate growth, Inflation and liquidity growth on Iran’s seasonal economic growth by using MIDAS and MF-VAR with Iran’s economic time series data during the period of 1390-1400. The empirical findings of the research indicate that the growth of all three variables of price, exchange rate and real liquidity initially have a positive effect on economic growth, but then lead to a decrease in economic growth. In this way, the results show that if the real liquidity growth, inflation and exchange rate growth are about 0.12%, 1.93% and 2.02% per month respectively, the economic growth will be strengthene, and if the monthly growth exceeds the mentioned values, it will have a negative effect on the growth of Iran’s GDP.

The present research aimed to investigate the relationship between Iran’s stock price index and nine macroeconomic variables during 1996–2019. Three methods were employed to reduce uncertainty, namely three Bayesian averaging methods (BMA, BMS, BAS), weighted average least squares (WALS), and Vselect. The experimental results of the Bayesian methods and WALS showed that the exchange rate and the consumer price index are the most important variables among the nine macroeconomic variables considered in the model. Moreover, the results revealed that the exchange rate has a minor impact on the stock price index, while the stock price index exerts a substantial effect on the exchange rate. The findings of Vselect validated the conclusion that these two variables are the primary drivers of stock price estimation and are present in nearly all predictive modelsIntroductionThe harmonization of financial markets with the macroeconomic sector is crucial for stabilizing the economy and achieving the adopted policies. In recent years, several significant studies have been conducted on financial markets, particularly the stock market, highlighting their pivotal role in allocating capital resources efficiently in advanced economies. Empirical evidence supports the view that financial markets have evolved in tandem with all sectors of the economy. Therefore, it can be argued that financial markets constitute one of the most vital components of any country’s economy. Throughout history, major economic crises have resulted from the collapse of financial markets, which underscores their critical significance. The financial market comprises several components, with the stock market being a crucial part. Economists view it as a barometer of a country’s economic health due to its ability to reflect macroeconomic asset prices more accurately than other markets. The uncertainty surrounding stock prices in stock markets is a significant aspect of the entire economy, capable of generating and disrupting unsustainable growth. For investors, the risk of participating in an investment is a crucial consideration. To comprehend total risk, it is beneficial to examine two aspects: systematic and non-systematic risk.The present study aimed to examine the impact of economic factors on stock market prices in Iran with the high degree of risk involved. There is a consensus among economists that asset prices are responsive to economic news, and that stock prices and economic factors are strongly interconnected. Thus, this research investigated the potential impact of macroeconomic factors on the Iranian stock price index from 1996 to 2019 using Bayesian averaging methods, followed by an analysis of the effect size of each variable through the weighted average least square method (WALS).Materials and MethodsResearchers often draw conclusions based on the assumptions of their selected model, assuming that it can accurately predict real-world situations. However, this approach may overlook true uncertainty, leading to non-conservative conclusions. Statistical models comprise two parts: variables and assumptions, and the model selected based on these assumptions to estimate the variables. Uncertainty exists at both levels. For instance, a researcher estimating the impact of influential factors on an independent variable may choose a model based on their assumptions and report their estimates. But is this the best answer? Another researcher with different assumptions may opt for a different model with lower variance and error. In other words, numerous models may fit the sample data equally well but with different coefficient estimates and standard errors. Bayesian model averaging (BMA) is a robust method that aims to remove uncertainty. It assesses the robustness of results to alternative specifications by computing posterior distributions for coefficients and models. This study employed three models of BMA, BMS, and BAS, using various averaging methods to verify the reliability of the results. Moreover, two non-Bayesian methods, namely WALS and Vselect, were used to select the best variables for predicting the optimal models.ConclusionThis study tried to investigate the relationship between Iran’s stock market index and nine macroeconomic variables during 1996–2019 by using the models that identify and limit uncertainty. The models selected include three Bayesian averaging models as well as WALS and Vselect which were used to verify the results obtained. The results indicated that only two variables, the exchange rate and consumer price index, are statistically significant when assuming a uniform distribution of the prior distribution function, which is the assumption of the BMS method. The remaining variables are not statistically significant. Furthermore, the estimates derived from the BMA and BAS models were quite similar, with the exception of less important variables. However, the similarity decreased in the BAS method. Moreover, WALS and Vselect confirmed the results obtained from all the three methods.

The present study represents an attempt to examine the main macro determinants of stock prices in OPEC oil exporting and importing countries in the study period 1996 to 2016 using Bayesian model averaging (BMA). The oil importers in this study are the United States, Britain and Japan, and three countries, Iran, Saudi Arabia and Kuwait, have been selected as oil exporters. The findings of this study are that to predict and evaluate the stock price index for oil-importing countries, the three variables of exchange rate index, consumer price index and economic growth should be given more importance than other variables, while for oil-exporting countries, The three variables of broad money growth, exchange rate and import are the most important variables that should be considered. For oil-importing countries, among the macro variables studied, OPEC oil prices have a completely negative relationship with the stock price index of those countries, but in oil-importing countries, the gold price has a completely inverse relationship with the stock price index.