جستجوی مقالات مرتبط با کلیدواژه "مدل tvp-favar" در نشریات گروه "اقتصاد"

The current study uses TVP-FAVAR models to investigate the effect of monetary and financial shocks on inflation, with a focus on the intermediary role of banks, from 1370-1 to 2018-4. Main variables influencing inflation are considered to be money volume, current expenditures, construction expenditures, taxes, and the bank intermediation index. The rate of return variable of the speculative sector is considered as an unobservable and hidden variable. The findings show that not only the bank intermediation index, but also the variables of liquidity, construction expenses, and current expenses, have a positive and significant effect on the inflation rate, and that each standard deviation of change in these variables between one and three years has an effect on the country's inflation stability and permanence. Based on the model's findings, policies such as floating the bank interest rate and credit indexing can be implemented, as can supply-side policies such as increasing the level of work culture, increasing human resource productivity, and changing the labor market's composition. The annual anchoring of government spending in four-year periods, as well as the adoption of policies that reduce the uncertainty of inflation, can be effective in adjusting the inflation rate for the ratio of budget deficit or government debt to GDP.

For the first time, this research investigat the relationship between speculative sector on herding behavior in the Tehran Stock Exchange market by using the (TVP-FAVAR) model and seasonal data from the years (1388- 1) to (1400-4). The results confirm the existence of herding behavior in the in the stock market and it shows the negative effects of the speculative sector impulse responses on the beta-herding behavior. n addition, the effects of impulse responses of other main variables of the model on the behavior of investors were as follows: the effect of beta herding behavior on itself was almost zero that means this variable was not affected by itself, the effects of GDP in the first three periods were neutral and Then in the year 1400, it became slightly positive, the inflation variable with a two-season delay had insignificant positive effects, and then in the following seasons, mainly in the seventh seasonhas been strongly negative, the total stock return variable was almost positive, and finally, the stock liquidity variable had negative effects on the beta herding behavior variable.

In recent research, the need for regulators and policymakers to evaluate the effects of government policies on markets can be felt according to the behavior of market participants and their deviation. Herding behavior is an important behavioral element and refers to a process in which market participants imitate one another's actions and adjust their financial decisions based on other people's actions. Based on the estimations of the herding model, investors put aside their opinions about the equilibrium point of the market, and the beta-herding of individuals leans towards the beta-herding of the market. According to this method, investors consider the general trend of market return and introduce the amount of cross-sectional dispersion as a herding pattern. In this article, the relationship between the monetary policies of the central bank and herding behavior in Tehran stock market is investigated for the first time. Central banks have serious motivations to pay attention to the possible herding behavior caused by their actions for two reasons. First, the herding behavior may neutralize the intended outcome of a monetary policy. Secondly, the monetary policy has the ability to eliminate price bubbles in the financial markets by itself. In this study, a wide range of data related to Iran's economy is experimentally examined by using the (TVP-FAVAR) model to see if the central bank's monetary policies have an effect on the beta behavior of investors. If so, is it possible to say in which years these effects were greater, which monetary policy tools were more effective, and how fast this policy impacted the beta-herding behavior?

In this research the herding behavior is measured based on the beta-herding behavior model of Huang and Salmon (2009) in which addresses the change of the cross-sectional level of systematic risks. In this model, the dynamic characteristics of herding behavior are referred to and the herding of investors are considered as a variable in time. Huang and Salmon argue that behavioral biases may affect investors' understanding of the asset price equilibrium; as a result, the estimated beta deviates from the traditional risk-return relationship that can serve as the beta deviation from beta equilibrium to measure the herding. Besides, the main channel of transmitting these effects is through expectations in that the central bank can have significant effects on the stock prices of this market by shaping the expectations of investors in the stock market. Therefore, first by calculating the beta-herding coefficient in Tehran Stock Exchange market and then by estimating the variable of beta-herding behavior, the (TVP-FAVAR) model (designed by Koop and Korobilis, 2013) was regressed by the MATLAB-207 software to investigate the hidden variable effects of monetary policies on the beta-herding behavior of investors in Tehran Stock Exchange market from the quarterly data of 30 main variables in the Iranian economy from Jan, 2019 to Jan. 2021.

In the calculations for the beta-herding behavior, the existence of this behavior has been confirmed in the whole period of 2009-2021. According to the results, the peak of this behavior occurred from 2020 to the end of 2021 and, at a lower level, from 2015 until the end of 2016. The output of the TVP-FAVAR model regression shows that the impulse response of the hidden variable of the expansionary monetary policies up to the first four seasons has a high impact on the beta-herding behavior. This means that the changes in the monetary policy can have important effects on the beta-herding behavior in initial seasons. According to it, the peak of these reactions happened in the years 2013-2019. The impulse response of the variable GDP growth rate had insignificant positive effects after three seasons, and the inflation rate variable after two seasons had no effect but became positive in the third and fourth seasons. After that, these effects became negative. Although the variable of the total return of the stock market had little effects, it continued for four seasons positively and suddenly turned negative in the fifth season. Finally, the liquidity of the stocks was of small effects but positive in the first two seasons. From the third season onwards, these effects became negative. One of the strong points of this research is extracting the probability of influence of each of the monetary policy instruments on the numerical value of the hidden variable of monetary policy, according to which the rate of change in the volume of money and visual deposits has the greatest influence, and the rate of change in the volume of pseudo money has the least influence on it. In addition, during 2013-2019, economic decision makers used most of the monetary policy tools to implement these policies.

Conclusion and Policy Implications:

 In summary, Iran's economy is a developing economy and has its own limitations, and the plans and actions of economic decision makers affect people's behavior in the capital market. The results of the research show that the government can make effective changes in the stock market with monetary policies and guide investors’ behavior. Therefore, the government and economic decision-makers can influence the behavior of investors at times when this market has a price bubble or the market goes out of its way. It is to be mentioned that the government should not lose its information credibility in this market, because behavioral discussions pay attention to the behavior of ordinary human rather than economic human. This can even get an opposite response from investors. From another point of view, it can be claimed that, if the government decides to exert less influence on this market, it can implement its monetary policies by diversifying monetary policy tools and make its effects on the stock market unpredictable. Otherwise, the alternative proposal for the implementation of policies will be monetary disciplines that can reduce these effects. Another suggestion of attraction for the future research to delineate the direction of government policies is the investigation of the influence of monetary policies on each of the industries or each corporation on the stock market.