جستجوی مقالات مرتبط با کلیدواژه « liquidity volume » در نشریات گروه « علوم انسانی »

Examining the effect of economic factors on government and household sports expenses, it is possible to obtain how these factors can cause changes and developments in sports expenses. This knowledge helps the government, organizations and households to make better and more efficient decisions in the field of sports expenses and use their resources more optimally. In this research, instead of focusing on traditional and common factors that may have been considered in previous studies, we have focused on economic factors and their impact on sports expenses. This innovative approach to sports and economic factors can contribute to a deeper understanding of sports costs and provide new solutions for optimal management of sports costs. Also, most researches in this field have focused on the effect of social and health factors of sports, but in this research, the effect of expenses on the government and the household is considered. This innovative approach can not only be effective in better understanding the effect of sports expenses on eliminating the deficiencies of the sports industry system, but also in providing more effective strategies to reduce sports-related expenses in order to reduce government expenses and increase access to sports for households. Finally, it can be said that sports, as an important activity in society, brings significant costs, which can have a significant impact on government and household costs. Economic factors are also among the factors affecting sports costs, and the analysis of their impact on these costs is examined in this article. By considering the effect of economic factors, it is possible to make better and more optimal decisions in the field of sports expenses and management of available resources for the government and households. Sports has become very important by playing a role in the economy of countries. Therefore, the macro-economic effects of the sports industry, such as the share of sports in the gross domestic product and gross national product or its contribution in creating employment and health of the general public, have led countries to accurately and regularly measure the effects of sports on their country's economy every year. evaluate Therefore, on the one hand, due to the low share of the sports economy in Iran's economy, and on the other hand, due to the lack of identification of factors affecting the development of the sports economy in Iran and the existence of a research gap in this field, conducting research on the sports economy and how to develop and expand its volume It is important and necessary. Therefore, this research has been done in response to the question, what effect do economic factors have on government and household sports expenses? This research was conducted with the econometric method and the short-term and long-term relationships between the variables were examined from the vector autoregression (var) pattern, instantaneous response functions (IRF), and variance analysis (VD) as well as the accumulation test. The test of existing theories in this field, the relationship between economic factors and government and household sports expenses were analyzed in the period from 1363 to 1400. The software used to validate the data was Eviuz version 12. Household sports expenses, within the scope of the Statistics Center questionnaire, are a part of the expenses of recreation, entertainment and cultural services, as well as a part of the expenses in the procurement and sale of durable household goods in the non-food sector, which include: clothes, shoes, learning various sports, providing tickets, entrance and membership fees, equipment rental, all kinds of balls, billiard and ping pong tables and other sports equipment. Also, in order to access the household sports cost information, the results of the cost and income statistics plan of urban and rural households from 1363 to 1400 were used, and in this way, the average sports cost for an urban and rural household was calculated. Then, by using the available information about the number of urban and rural households in the mentioned years, by multiplying the sports expenses of an urban and rural household by the number of existing households and adding them together, the total consumption of household sports was obtained. It is worth mentioning that the statistics of the number of urban and rural households in the country were not available in all the years in question, and the researcher roughly extracted these statistics using the statistics available in the previous and subsequent years. The country's budget is divided into four sections of public affairs, defense, social and economic affairs, which are divided into other chapters and programs, and physical education and youth affairs are placed in the fifth chapter of social affairs. In order to determine the government's expenses in this sector, first the information available in the budget law of the whole country was checked, but due to the fact that the approved budget and the government's performance in this sector are not the same, as well as the lack of figures related to the performance in some years in the budget law, from the information Available in the economic reports of the Management and Planning Organization were also used. Statistics related to GDP, tax rate, liquidity volume, exchange rate, inflation rate, interest rate, trade balance, unemployment-employment rate and total stock market index were extracted from the time series data of Central Bank of Iran. According to the findings, among the identified economic factors, the GDP factor affects the government's sports expenses, and the GDP factor and the inflation rate affect the household sports expenses. According to the findings, among the identified economic factors, the GDP factor has an impact on the government's sports expenses. . An increase in incomes and economic growth can lead to an increase in export earnings and, as a result, an increase in expenses related to sports and the development of athletes in the country. GDP is affected by investment and consumption within the country. The effect of this gross domestic product on sports expenses of the Iranian government is investigated with two possible solutions. A) Increase in GDP: Increase in GDP can lead to economic growth and increase in domestic incomes. This increase in income can lead to an increase in the government's sports budget, and as a result, the government's sports expenses will increase; b) Decrease in GDP: Decrease in GDP can lead to decrease in domestic incomes and economic recession. In this case, the government's sports budget will also decrease and the government's sports expenses will also decrease. In general, an increase in the inflation rate means an increase in prices, and as a result, it can increase household sports expenses. As a result, buying sports equipment or joining a sports club, holding sports activities or attending sports events may become more expensive. This increase in prices may reduce the purchasing power and motivation of households to spend on sports and recreational activities. For example, if the price of sports equipment such as sports shoes or sports clothes increases due to inflation, households may feel uncomfortable buying these products or may not be able to afford them due to the higher cost. It can be said that the effect of the inflation rate on household sports expenses is strongly dependent on the level and growth rate of inflation. Finally, based on the findings, it is suggested that the government increase financial support for athletes by increasing credits and cooperating with companies and sponsors. This includes setting appropriate salaries for professional athletes, paying for training and equipment, as well as support for travel and competition expenses. This action can reduce the expenses of families to support athletes and provide the possibility for athletes to continue professional sports activities.

In financial markets and behavioral finance studies, the herding behavior of shareholders is considered an important variable. This behavior refers to a process in which capital market participants make decisions without relying on their own information and analysis, instead imitating the actions of others. Analyzing herding behavior can enhance our understanding of how bubbles form in stock markets and contribute to increased capital market efficiency. Herding behavior can distort asset prices, leading to deviations from their fundamental values, which subsequently impacts overall market stability. By understanding the factors that drive herding behavior, policymakers and market regulators can implement strategies to mitigate its adverse effects.
Given the significance of collective behavior, this research examines the relationship between monetary policies, changes in exchange rates, and the herding behavior of shareholders. To measure herding behavior, we utilized the model proposed by Chang et al. (2000). According to this model, herding behavior is indicated when the deviation of stock returns from the market return decreases, suggesting that investors are following the market trend rather than making independent decisions. Furthermore, to measure monetary policy variables and exchange rate changes, we employed indicators of seasonal changes in liquidity volume and monthly changes in the exchange rate, respectively. Using time series data from 2011 to 2021, which includes information from 133 companies listed on the Tehran Stock Exchange, we applied multivariate regression analysis to test our hypotheses. This comprehensive dataset allowed us to capture various economic conditions and policy changes over a significant period.
The research results indicate that changes in the exchange rate lead to the formation of herding behavior in the Tehran Stock Exchange. This suggests that as the exchange rate fluctuates, investors tend to mimic the actions of others rather than rely on their own analysis. Additionally, while changes in liquidity volume also contribute to the emergence of herding behavior among shareholders, these results were not statistically significant. This implies that liquidity alone may not be a strong enough factor to drive herding behavior, or that other underlying factors may be influencing these outcomes. The findings highlight the importance of exchange rate stability in maintaining market discipline and preventing irrational collective behaviors.
The herding behavior of shareholders has increased the distance between the market price and the intrinsic value of the stock, leading to an increase in stock prices and impacting the efficiency of the capital market. This misalignment between market prices and intrinsic values can create conditions for market bubbles and subsequent crashes. Some studies show that herding behavior is more prevalent when markets are in a stable state (rising or falling) than during periods of chaos and uncertainty. This indicates that investors are more likely to follow the crowd during predictable market conditions, while in volatile times, individual decision-making becomes more pronounced. Policymakers aiming to influence mass behavior should make decisions and implement policies when markets are stable, before a financial crisis or bubble formation occurs. Proactive measures can include regulatory interventions to ensure market transparency and the dissemination of accurate information to all market participants. Considering the results of the research on the effect of exchange rate fluctuations on the formation of mass behavior, it is recommended that stock exchange organizations use this factor to improve investment behavior, guide the market towards intrinsic values, and prevent bubble formation and subsequent collapse. Market supervisors, lawmakers, and the central bank should consider the potential limitations of rational models when designing policies and making decisions related to monetary policies, including determining liquidity levels and controlling the exchange rate. Additionally, the behavioral elements of market attitudes and psychological and cognitive factors should be taken into account when making these decisions. By addressing these aspects, policymakers can better manage market dynamics and foster a more stable financial environment.

In the field of the impact of monetary policy on inflation, much research has been done, in most of which structural failure has not been studied and the regression method with a fixed parameter has been used and reached different results. Lucas (1976) argues that any change in policy regime can lead to structural failures in inflation dynamics, and that any policy analysis that does not take these failures into account will naturally have little validity. Therefore, it is important to examine whether the volume of liquidity has a different effect on inflation over time and using new regression model methods with variable time parameters can lead to more accurate policy analysis and thus more accurate economic decisions.

Given the importance of the relationship between liquidity and inflation in monetary policy, it is important to examine whether the volume of liquidity has a different effect on inflation over time and using new regression model methods with variable time parameters can lead to more accurate policy analysis and thus more accurate economic decisions.
Using a regression model with time varying parameter (TVP) and the Kalman filter approach the present study examines the reaction of the inflation rate over time to the influential variables such as the inflation rate of the previous period, the expected inflation rate, the imported inflation rate, the production gap and especially the volume of liquidity in the  period under study in which the application of time-varying parametric technique is considered as an innovation of this research and gives us more accurate results. 

Examining the changes in the growth rate of liquidity, inflation rate and GDP growth rate shows that in most years, the growth rate of liquidity has a positive effect on the inflation rate of the next period. But in some years, despite the increase in the growth rate of liquidity, the inflation rate of the next period has decreased. Also, in some other years, despite the decrease in the growth rate of liquidity, the inflation rate of the next period has increased. It can be said that in short term, inflation in Iran is not just a monetary phenomenon. Also, due to the fact that in some years the inflation rate was relatively high, but in the next period, the growth rate of liquidity increased or in some other years, the GDP growth rate was relatively low, but in the next period, the liquidity growth rate decreased. It can be said that the changes in the growth rate of liquidity in Iran were not commensurate with the changes in inflation rates and economic growth rates and this shows that monetary policy has been wrong. 

In present study, the results of estimating the regression model as a variable time parameter and examining the trend of coefficients of explanatory variables over time in this study show that these coefficients have not been constant during the period under study and have changed over time due to external shocks such as revolution, war, oil price shocks, applied economic policies, structural changes, international political stances and economic sanctions. That is, in addition to the volume of liquidity, other variables such as delayed inflation rate, expected inflation rate, imported inflation rate and GDP gap also have a variable effect on inflation rate over time.

According to financial and monetary theories, the main role of banks in the economy is to create liquidity through cash deposits and provide them in the form of loans. The main purpose of this study is to investigate the effect of shadow banking system on the volume of liquidity in Iran. For this purpose, Iranian quarterly data during the years 1397-1388 have been analyzed using structural vector autoregression and ordinary least squares. The results of  the SVAR model in the form of shadow banking shock and analysis of variance show that the shadow banking system affects the liquidity of the country in the period under review, so that the effect of shadow banking shock on supply Money and quasi-money reached their highest levels in the second year, about 29.70 and 28.40 percent, respectively, and then began to decline. Also, the results of the ordinary least squares method show that there is a positive relationship between shadow banking and money supply and quasi-money and the correlation coefficient of shadow banking with money supply and quasi-money is 0.502677 and 1.043699, respectively. Therefore, the activities of the shadow banking system increase the volume of liquidity by promoting the volume of money and quasi-money, which are the components of the volume of liquidity.

Considering the most important industry and the high volume of economic activities of the service sector and the role of monetary policy in these two sectors, as well as due to the activity of monetary Shocks in periods of recession and periods of prosperity.The main goal of this research is to examine and test the asymmetric effects of Monetary Policy on the added value created by services, industries, and mines in selected oil exporting countries. For this purpose, the generalized moments method (Panel GMM) has been applied for the time period from 2002 to 2020. The results obtained do not confirm the existence of an asymmetry in positive and negative impulses in the industries and mining sector, whilst the existence of positive and negative impulses was found to have an insignificant effect on the growth of the added value of this sector. On the other hand, the existence of asymmetry in positive and negative impulses in the service sector was confirmed, whilst, the effect of negative impulse on the reduction of the value-added growth of the service sector was found to be greater than the effect of positive impulse in increasing the value-added growth of the service sector. In effect, the industry sector of the countries understudy performs poorly in response to asymmetric policies, but the service sector shows a better response to positive and negative impulses due to its expansion in these countries.

In economic literature, increasing each of the components of the basic monetary resources with the same coefficient called the increasing coefficient causes an increase in liquidity; But the degree of influence of each of the components of basic monetary resources may not be the same. Therefore, the composition of the components of basic monetary resources can also affect liquidity. Therefore, the current article seeks to investigate the impact of each component of monetary base resources on liquidity. For this purpose, the research model has been designed based on theoretical foundations and the statistical data of the years 1357-1400 have been used, and the model used is the self-explanatory approach with distributed intervals (ARDL). From the model estimation findings, it can be concluded that there are short-term dynamics related to long-term relationships. The interpretation of the error correction coefficients, which is equal to -0.72, shows that the short-term and long-term coefficients converge directly to each other. Also, the results of this study show that a one percent increase in the net debt of banks to the central bank increases the volume of liquidity in the short term and long term by 0.36 and 0.64 percent, respectively. Other findings of the model show that all components of basic monetary resources have a positive and significant effect on liquidity volume.

Uncertainty can have profound consequences for both companies and individuals hoping to make optimal decisions for their benefit. Economic agents in financial markets are generally concerned about uncertainty in the political, economic and environmental spheres. When prior expectations are compromised by the increased likelihood of uncertain outcomes, agents must wait for the waves of uncertainty to dissipate before making sound financial decisions. In this research, the relationship between economic uncertainty shock and illiquidity of the stock market has been analyzed using the Time-Varying Structural Vector Auto-regressive model TVSVAR during the years 2008:4-2020:3. The obtained results indicate that the effect of the economic uncertainty shock on illiquidity was positive and increasing in most of the periods and years under investigation, and the effect of the shock of liquidity volume growth on illiquidity had a decreasing effect in most of the periods and years. The effect of inflation shock on illiquidity increased in all the studied periods and years, but in 2016 and 2020, it had a decreasing effect in the final period.

The main goal of this research is to examine and test the asymmetric effects of monetary policy on the production of industries and mines. For this purpose, hidden cointegration analysis and Autoregressive distributed lag (ARDL) approach in Iran's economy have been used in the period from 1353 to1399.Hodrick Prescott filter was used to extract the positive and negative impulses of the liquidity variable. Then, the effects of positive and negative impulses of the variables were investigated separately on the positive and negative impulses of the production of this sector with latent cointegration analysis. In the last step, the long-term relationship between the variables is checked and the long-term coefficients are calculated using the auto-regression model approach with non-linear distribution intervals and the bounds test. The results showed that there is a hidden co-accumulation between the time series of M_2 and production in the industrial sector.The results showed that there is a hidden cointegration between the time series of M_2 and production in the industrial sector. So that the positive components of the M_2 and production in this sector have a long-term relationship with each other, as well as their negative components. Also, the effect of the positive shocks of M2 is greater than the negative shocks of this variable. Therefore, the existence of asymmetry in monetary policy was confirmed.

The aim of this study is to investigate the effect of oil revenues and exchange rates on the amount of investment in the stock market in Iran using seasonal data in the period 2008-2016. To this end, the impact of oil revenues and exchange rates and the amount of liquidity on investment in the stock market in Iran has been estimated using the Markov-Switching two-mode model. The results of model estimation show that oil revenues, exchange rates and liquidity have different effects on investment in the stock market in Iran. Second regime are related to the variance and high average ( Prosperity) and diet (2) are associated with variance and low average (recession) regimes. It should be noted that in regime (1) only the volume of liquidity has a positive and significant effect on the amount of investment in the stock market, but in regime (2) the exchange rate has a negative and significant effect and oil revenues have a positive and significant effect on the amount of investment in the market Has had shares.

The purpose of this study is to apply the system dynamics approach to predict the price of gold in Iran, identify factors affecting the price of gold and simulate the impact of monetary policy on the price of gold in the period 1389-1405. The simulation was performed with Vensim software. The present study simulates the change in liquidity volume, consumer price index and bank interest rates on the gold market in different scenarios. The results show that the price of gold is not only affected by the gold world price and the value of the dollar, but also the control of liquidity and curbing inflation will play a significant role in stabilizing the gold market. The results confirm that the volume of liquidity and the consumer price index have a direct impact and a significant role in increasing the price of gold. The findings also show that changes in bank interest rates have no effect on changes in gold prices.

 The housing market has been one of the most volatile sectors of the economy in recent times, experiencing periods of stagnation and boom. It is important to note that the housing sector is most closely linked to other sectors of the economy. With the recession, the whole economy will be in crisis. Also, the housing sector, given these features, has a stronger impact on investment and housing prices than short-term economic fluctuations, as well as its widespread and past relevance to other sectors, has the potential to generate growth and development in other sectors of the economy and can serve as an endogenous growth incentive. To play a slower role, and to stimulate, to stimulate economic growth in the short term and to drive the recession out. Therefore, further reflection is necessary in this section. Therefore, in this study, using the vector auto regression Time Series (VAR) analysis model, we investigate the interaction between housing price markets of some macroeconomic variables such as liquidity volume, per capita income. The results showed that the volume of liquidity has a significant share in the volatility of the housing market. Therefore, policymakers in the economic field should pay more attention to this.

Regarding the importance of the relationship between volume of liquidity and GDP in manufacturing sector policy making, using a time-varying parameter (TVP) regression model and Kalman filter approach, the present research studies the GDP's response to effective variables such as capital, labor force, and in particular liquidity volume during the period of 1978-2015. The results of estimating the regression model with time varying parameter and the study of the trend of the coefficients of explanatory variables over time show that these coefficients have not been constant over the period under study and have changed due to exogenous shocks such as revolution, war, oil price shocks, applied economic policies, structural changes, international political stances, and economic sanctions. By comparing the trend of changes in the GDP growth rate with changes in the rate of growth of liquidity, it can be said that the trend of changes in these two variables are not proportionate, showing that policy making in the monetary sector has not been efficient. Therefore, it is suggested that the central bank should have an appropriate operational independence and that the rate of liquidity growth vary proportionately with the rate of GDP growth.

One of the important factors in achieving sustainable and sustainable economic growth and development is owning a robust and efficient banking system. banking system with attracting deposits and mobilization of financial resources to investing in productive affairs provides a framework for increasing of economic growth and development. Mobilization and allocating of financial resources to economic activities does through the financial market and notice of the financial market of Iran is bank-based. Therefore, the role of the Iran's banking system in investment, employment, growth and economic development because of and mobilization of resources and finance for the implementation of projects, financing of working capital of manufacturing units, providing mortgages and meeting the basic needs of the society and also avoids deepening the decline in economic activity is so important that requires expansion of the bank's performance.
Introducing variables and presenting the model The present study with using of econometric techniques, 3SLS system methods and simultaneous equations examines the effect of effective factors on the performance of the banking sector in Iran during the period of 1393-1363, which with following of the studies conducted by Sufian and Zulkhibri (2013), Tchaidze and Tvalodze (2011), Shahabadi and Sammy (2011), Low et al (2010) and Arestis et al (2002), Bank Performance (FD) is the function of Economic Freedom Index (EF), liquidity volume (MS), gross domestic product (GDP) and real interest rate (RIR), and equation (1) is estimated.
LFDt = β0β1*LEFtβ2*LGDPtβ3*LRIRtβ4*LMStεt (1)
Also expecting:σLFDt⁄σLEFt>0, σLFDt⁄σLGDPt>0, σLFDt⁄σLRIRt>0, σLFDt⁄σLMSt>0
The Determinants of the Factors Affecting Banking Performance:Equation of Economic Freedom (EF): With following of the studies conducted by Shafiq and Zaman (2014), King et al (2010), Lundstrfm (2005) and Banaian and Luksetich (2001), the economic freedom index is the function of ratio of oil and gas exports to gross domestic product (OE), human capital (HC), inflation (IR) and civil liberties (CI), and equation (2) is estimated: LEFt = β0β1*LOEtβ2*LCItβ3*LIRtβ4*LHCtεt (2)
Also expecting:σLEFt⁄σLOEt>0, σLEFt⁄σLCIt>0, σLEFt⁄σLIRt>0, σLEFt⁄σLHCt>0
Volume of Liquidity Equation (MS): With following of studies conducted by Bittencourt (2011) and Mashayekh et al (2013) the liquidity volume is the function of the ratio of currency in circulation to the sum of currency and non-currency deposits (C/D), the ratio of legal deposits of banks in the central bank to the sum of currency and non-currency deposits (LD/D), the bank's debts to the central bank (BD) public sector debt to the central bank (PSD) and the equation (3) is estimated.
LMSt = β0β1*L(C/D)tβ2*L(LD/D)tβ3*LBDtβ4*LPSDtεt (3)
Also expecting: σLMSt⁄σL(C/D)t>0, σLMSt⁄σL(LD/D)t>0, σLMSt⁄σLBDt>0, σLMSt⁄σLPSDt>0
Equation gross domestic product (GDP): With following of the studies conducted by Burggraeve et al (2015), Ahmad and French (2011), Takii and Tanaka (2009), Falk (2007), Shaw (1973), Goldsmith (1969) and Jung (1986), gross domestic product is the function of accumulation physical capital (PCA), accumulation research and development expenditures (R & DA), Human capital (HC) and employment (EM), and equation (4) is estimated.
LGDPt = β0β1*LPCAtβ2*LR & DAtβ3*LHCtβ4*LEMtεt (4)
Also expecting: σLGDPt⁄σLPCt>0, σLGDPt⁄σLLR & Dt>0, σLGDPt⁄σLHCt>0, σLGDPt⁄σLEMt>0
Conclusion and Policy Recommendations : According the econometric topics, for avoid the formation of false regression should stationary of variables are examined firstly. The results of stationary of variables with using of the fuller Dicky test show that all variables are stationary in first differences. When examining the explanatory power of the equations in the simulation model, R2CN has the same role of R2 in other estimation methods. Therefore, the higher the value of this statistic is closer to the number one, the explanatory power of the estimated equation is greater and the results are more attributable (this index is defined by the MSE (Mean-Square-Error) criterion). Also, the RMSE value, which is the square of the MSE, is closer to zero, results are more reliable. According to the results of estimated equation of bank performance can be find out, the explanatory power of the estimated equation is high, and results are attributable. Results of estimation of the banking sector performance model during the period 1963-2014 shows that, variables of economic freedom, GDP and liquidity volume have a positive and significant relationship with banking performance, and the effect of the variable of the real interest rate is also meaningless. Also the variables ratio of oil and gas exports to gross domestic product, inflation rate and civil liberties have a negative and significant impact and human capital does not have a significant effect on economic freedom. Variables of physical capital, accumulation research and development expenditures and employment have a positive and significant impact, and human capital does not have a significant effect on gross domestic product. Also the liquidity volume with increasing, assets and debt central bank is increasing and decreasing, respectively. Therefore, with considering of the positive and significant impact of the economic freedom index, the liquidity volume and GDP on banking performance can find out that these variables provide a framework for mobilization of financial resources, strengthening the sense of deposit in banks and directing small depositor's funds towards production activities, because by improving economic freedom and coordination of growth rate of liquidity with growth rate of gross domestic product provide a framework for advancing the functioning of the banking sector.

The purpose of this paper is to consider the relationship between housing indexes with some Iran's macroeconomic variables by wavelet coherency approach between1992-2015. The results of wavelet coherency have shown that the relationship between housing price index and economic growth has been inverted in one-year time-frequency during the period 2012-2014 but in this frequency between2006-2010, this relationship has been the identical phase, and the housing price index causes economic growth. Furthermore, the intensity of the relationship between economic growth and land price index in the short-term horizon during 1993-1996 has been in the opposite phase but during 2001-2004 are co-movement. On the other hand, inflation and housing price index are co-movement and in short and medium term; inflation rate was the leading variable. As well as liquidity and price indices of the housing sector are co-movement in long-term.

The purpose of this study is the monetary inflation test in Iran’s economy and the identification of influential factors in inflation by estimation of two different econometrics models and during the period of a century half, i.e. the years between 1960-2009. So the current study aims at not only focusing on the direct impacts of volume of money and liquidity on inflation in the frame of monetary theories, but also distinguishing the other effective factors on inflation like gross domestic products, the exchange rate in the market parallel, imported price index, domestic interest rate, foreign interest rate and oil incomes in order to estimate the importance of these factors in forming the inflationary pressures. indeed two models of different econometrics would be estimated in order to study the relations among the aforementioned variable and the level of general prices. The stationary tests on the variables show that some variables of I(0) and I(1) are to be confronted, Accordingly the method of auto-regressive distributed lag (ARDL) are applied to estimate these kinds of models. The outcomes of the study show that 1- there is a kind of positive and meaningful relations between the inflation and liquidity in Iran’s economy, but this relation is not one to one; 2- the inflation phenomenon is not just the monetary one in Iran’s economy; 3- increase of liquidity content is one of important factors in causing inflation in Iran’s economy, but it is not the most important factor;4- except for the content of liquidity there are some other influential factors in causing inflation like gross domestic product, the imported price index,domestic interest rate, foreign interest rate and oil incomes.