Monetary economy
Rana Abbasgholi Nezhad Asbaghi; Hosein Samsami
Abstract
Some monetary policymakers attribute the persistent high inflation in Iran’s economy solely to the lack of central bank independence, arguing that granting the central bank autonomy is necessary to reduce inflation. However, empirical studies reveal that central bank independence faces significant ...
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Some monetary policymakers attribute the persistent high inflation in Iran’s economy solely to the lack of central bank independence, arguing that granting the central bank autonomy is necessary to reduce inflation. However, empirical studies reveal that central bank independence faces significant structural challenges due to the endogeneity of money within Iran’s economic system. This article aimed to identify the key components of requirements of central bank independence, with a particular focus on the government structure in Iran’s economy. A comprehensive review of existing literature on central bank independence was conducted. Moreover, a grounded theory approach was used to achieve theoretical saturation concerning central bank independence in Iran. Then, the study relied on the Bayesian model averaging (BMA) and analyzed 21 variables to identify the key factors defining the requirements of central bank independence in Iran. The findings highlighted several key factors, including the deviation of the effective exchange rate from the appropriate exchange rate, the government budget deficit, oil revenues, and the government effectiveness index. Furthermore, the results suggested that increasing central bank independence alone, within the context of variables contributing to endogeneity of money under Iran’s current economic conditions, has a weak and fragile effect. Thus, it is essential to undertake structural reforms targeting these critical variables as a prerequisite to meaningful discussions and efforts toward central bank independence.IntroductionThe theory of time inconsistency proposed by Kydland and Prescott (1977) posits that central bank independence can reduce inflation rates without incurring economic costs while enhancing stability by lowering inflationary expectations. However, several empirical studies (e.g., Bauman et al., 2021) emphasize that the effectiveness of central bank independence depends on the unique structural and institutional characteristics of each country. As a result, central bank independence is not a universal solution and may vary depending on the specific structural conditions of each economy. The relationship between central bank independence and inflation rates can significantly differ when structural and institutional factors deviate from the ideal. Iran’s economy has recently undergone substantial fluctuations in inflation rates. Some monetary policymakers attribute these high inflation levels solely to the lack of central bank independence, asserting that greater independence is necessary to control inflation. However, structural factors unique to Iran’s economy complicate this view. Issues such as an inefficient tax system, reliance on oil revenues, underdeveloped financial markets, exchange rate markets, and the quality of governance indicate that money is largely determined endogenously. These structural challenges undermine the effective implementation of central bank independence as a tool to reduce inflation and promote economic growth. Given these complexities, the present study sought to identify the key components necessary for central bank independence within Iran’s economic system. Focusing on the government structure, the study employed a grounded theory approach and Bayesian model averaging (BMA) to identify the requirements for central bank independence in Iran.Materials and MethodsThis research identified categories related to central bank independence by reviewing the existing literature. It used a grounded theory approach to achieve theoretical saturation. As a result, four key categories were identified: the exchange rate market, the government budgeting system, the quality of governance, and the central bank independence. Specific variables were analyzed within each subcategory to uncover the robust components influencing central bank independence in Iran’s economy. To collect data for the analysis, the study used reliable sources, including databases from the Central Bank of Iran, the Statistical Center of Iran, and the World Bank. The concept of central bank independence was treated as a dependent variable, consistent with the methodology proposed by Giannone et al. (2011) and informed by studies such as Rogoff (2019) and Baumann et al. (2021). These studies define the concept in terms of liquidity under optimal conditions. The variables were tested for their significance and intensity of influence on the dependent variable, allowing for the identification of those that retained their effects even when other variables were included in the model.Results and DiscussionThe results presented in Table 1 are based on coefficient calculations and posterior probabilities from 340,000 regressions. They helped identify four variables as statistically robust and non-fragile even when accounting for the presence of all other variables. These variables included the deviation of the effective exchange rate from the appropriate exchange rate, the government budget deficit, oil revenues, and the government effectiveness index. The result is supported by their posterior probabilities, which exceed the prior probability threshold of 50%, as assumed under the uniform distribution in the Bayesian model selection (BMS) method.Table 1. The Results of the Sampling Process and BMS Estimation Calculations based on 340 Thousand RegressionsA proportion of regressions withCond. Pos. SignPost SDPost MeanPIPSymbol 0.9910.09870.54240.9999DEA10.9710.14890.50730.9880BDG20.9110.03950.11060.9417GOR30.8500.0554-0.10400.8832EFG40.610.99990.03890.02360.3293COC50.580.01981.0681-0.57120.2869RET60.560.88091.05530.56240.2839REO70.560.92340.25230.13440.2786REG80.280.89960.00480.00110.1355BAC90.250.09150.0733-0.01200.1247CUK100.210.14430.0777-0.00510.1219MAT110.200.28310.0411-0.00080.0970GRI120.180.35270.0634-0.00590.0899DUM130.190.86900.00650.00130.0890UR140.170.99800.00310.00070.0875EC150.150.21920.1140-0.00740.0805TINF160.140.49550.0148-0.00150.0787ECI170.150.15390.0088-0.00120.0676RLA180.130.12760.0179-0.00210.0610DECM190.120.83750.00550.00060.0594HI200.090.90910.00340.00030.0549UNC21* Source: Research resultsThe weighted average of posterior coefficients further revealed that the variable representing the deviation of the effective exchange rate from the appropriate exchange rate is the most influential in the model, exerting the strongest positive effect in terms of intensity. Following this, the government budget deficit, oil revenues, and the government effectiveness index ranked as the next most significant variables, respectively, based on their influence coefficients. Yet, the results indicated that in the presence of all variables, central bank independence indices (i.e., GRI, CUK, MAT, and DUM) are fragile and statistically insignificant. This is due to their lower posterior probabilities of inclusion compared to the prior probability, underscoring their limited relevance within the model.ConclusionSince central bank independence indices lose significance when the four key components are considered, simply enhancing central bank independence is not a viable long-term solution under the current conditions of Iran’s economy characterized by the endogeneity of money. Therefore, during the transition phase, policymakers must prioritize structural reforms in several key areas: reforming the government budgeting system, improving governance with a focus on efficiency and effectiveness, and developing a competitive foreign exchange market capable of establishing an optimal and efficient exchange rate. Only after addressing these foundational issues should efforts to enhance central bank independence proceed, supported by a robust legal framework and coordinated collaboration with the government.
Behavioral economics
Taha Shishegari; Farhad Ghaffari
Abstract
Conventional economics posits that the presence of arbitrage in financial markets forces market participants to act rationally in order to maximize profits. This assumption underpins the efficient market hypothesis (EMH). However, in recent years, behavioral economics has challenged the assumption of ...
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Conventional economics posits that the presence of arbitrage in financial markets forces market participants to act rationally in order to maximize profits. This assumption underpins the efficient market hypothesis (EMH). However, in recent years, behavioral economics has challenged the assumption of market efficiency and rational behavior by demonstrating the significant impact of seemingly irrelevant factors (e.g., weather conditions, air temperature, and pollution) on financial markets. The present research aimed to compare the explanatory power of these two perspectives by analyzing daily data from the Tehran Stock Exchange index over two periods: February 20th, 2022 to February 19th, 2023, and February 20th, 2023 to February 19th, 2024. The study relied on the daily data on the growth rate of the dollar as an explanatory variable for the total stock market index growth from a conventional economics perspective. From a behavioral economics viewpoint, the analysis incorporated variables such as air temperature, weather conditions, and the pollution index. Given the nature of financial markets, the study used the EGARCH method for analysis. The results indicated that during the period from February 20th, 2022 to February 19th, 2023, when the dollar rate exhibited a significant upward trend, the explanatory power of behavioral variables decreased, with some even losing their significance in explaining the total stock market index. However, during the period from February 20th, 2023 to February 19th, 2024-when the exchange rate remained relatively stable-behavioral variables had a significant impact on the total stock market index. Introduction In the conventional economics perspective, which has long dominated the analysis of financial markets, actors are assumed to behave rationally. This means that they adjust their beliefs accurately (according to Bayes’ rule), aligning their subjective probabilities with reality and making decisions based on expected utility. However, in recent decades, the deviation of conventional economics theories from empirical data—along with the emergence of large, persistent, and severe price bubbles in financial markets—has led a group of economists to question the explanatory power of conventional theories and the assumption of rational behavior in financial markets. The present study aimed to address the duality between conventional and behavioral economics within the context of Iran’s developing economy. Focusing the country’s unique economic conditions, the study sought to determine which perspective—conventional or behavioral economics—provides a better explanation for stock market behavior. Two distinct time periods were analyzed: 1) from February 20th, 2022 to February 19th, 2023, during which the exchange rate (U.S. dollar) nearly doubled as a representative variable of the macroeconomic situation; and 2) from February 20th, 2023 to February 19th, 2024, when the exchange rate remained relatively stable, increasing by about 40%. The impact of behavioral variables on stock market returns was examined in two scenarios: one characterized by significant changes in macroeconomic variables and the other by more moderate changes. Conventional economics suggests that humans act rationally when the data is clear and the analysis is straightforward. However, as complexity increases and data becomes less clear, individuals tend to deviate from rational behavior due to limited rationality (Thaler, 2009). This hypothesis was tested by focusing on the two time periods of the study. In the first period, when macroeconomic variables exhibited a clear and specific trend, conventional economic theories were expected to provide a more accurate explanation of stock market behavior, with the influence of behavioral variables likely to decrease. Conversely, in the second period, when macroeconomic variables lacked a clear direction, it was anticipated that behavioral economics—along with variables rooted in psychological influences and the internal states of actors—would offer a better explanation for stock market performance. In this study, environmental variables such as air temperature, atmospheric conditions, and air pollution were considered representative of behavioral variables. The analysis investigated the impact of behavioral variables on the Tehran Stock Exchange index. Materials and Methods Financial sector data often exhibit heteroskedasticity, which makes the use of linear structures for estimation and modeling problematic. Additionally, fluctuations in financial data tend to cluster, indicating that the variance is self-explanatory. These characteristics make ARCH and GARCH models particularly suitable for modeling in this context. When using ARCH and GARCH models, it is essential for the estimated coefficients to be non-negative, which can present challenges in the estimation process. To address this issue, EGARCH models, which is the logarithmic form of the GARCH model, can be employed. This approach eliminates the need to impose the non-negativity condition on the variance coefficients. The current study estimated the daily growth rate of the total index of Tehran Stock Exchange over two separate time periods: from February 20th, 2022 to February 19th, 2023, and from February 20th, 2023 to February 19th, 2024. The analysis applied the AR(1) model and incorporated both behavioral and conventional variables into the variance component of the model to explain fluctuations in the total index efficiency. Results and Discussion During the first period (February 20th, 2022 to February 19th, 2023), the exchange rate experienced a clear and significant increase of 100%. Market players, adhering closely to conventional economic theories, operated under the assumption of rational and optimizing behavior. As a result, the exchange rate variable became more effective in explaining market fluctuations, while some behavioral variables, such as climate and air pollution, lost their explanatory power in the variance equation. In the second period (February 20th, 2023 to February 19th, 2024), the conventional variable (currency growth rate) became less significant and transparent. Market players increasingly relied on behavioral variables, which offered a better explanation for fluctuations in the total stock market index. The estimated coefficient for the conventional variable (foreign exchange growth rate) lost its significance during this period. The results showed that air temperature had a negative and significant impact on fluctuations in the growth index during both periods, consistent with the findings of previous studies. Conclusion This study analyzed two distinct economic periods: one marked by significant growth in foreign exchange rates, and the other characterized by relative stability in the foreign exchange market. The objective was to examine the behavior of financial actors and compare the explanations provided by conventional and behavioral perspectives on financial markets using the available data. According to the results from the two estimated models, the exchange rate growth (as the representative variable of the conventional view) had a significant and positive impact on stock index fluctuations during the first period, when exchange rates exhibited a clearly upward movement. However, this variable lost its significance in the second period, when exchange rates remained relatively stable. During the second time, the explanatory power shifted to behavioral variables such as weather conditions, pollution, and air temperature.
Macroeconomics
Sohail Rudari; Seyyed Hadi Arabi; Sanaz Rahimi Kahkashi
Abstract
The present study aimed to examine the transfer, reception, and the spillover of volatility from March 1982 to September 2022, using the time-varying parameter vector autoregression model based on Barunik-Krehlik (TV-VAR-BK) with monthly frequency. The results indicated that the primary relationship ...
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The present study aimed to examine the transfer, reception, and the spillover of volatility from March 1982 to September 2022, using the time-varying parameter vector autoregression model based on Barunik-Krehlik (TV-VAR-BK) with monthly frequency. The results indicated that the primary relationship among the volatility of the analyzed variables is of long-term nature, with the exchange rate emerging as the dominant factor in explaining the volatility of the examined network. In the short term, liquidity serves as the primary transmitter of volatility to inflation and the exchange rate. However, in the medium and long term, the exchange rate becomes the primary transmitter of volatility to inflation, while liquidity acts as the net receiver of currency volatility. Additionally, the long-term impact of the exchange rate is more pronounced. Failure to control currency volatility can lead to inflation turbulence by transferring volatility to liquidity, underscoring the significance of exchange rate stability in managing liquidity and inflation.IntroductionThe exchange rate is one of the key factors influencing inflation. In addressing the impact of exchange rate volatility, the status of inflation plays a crucial role (Tahsili, 2022). Moreover, assessing the factors influencing the exchange rate stands as one of the most challenging empirical problems in macroeconomics (Williamson, 1994). Since the exchange rate is significant economic indicator in any country, alterations in monetary variables (e.g., liquidity and inflation rates) as well as non-monetary variables can lead to fluctuations and instability in the exchange rate (Amrollahi et al., 2021). The causality of volatility between money and inflation can vary depending on economic conditions (Al-Tajaee, 2019). A deeper understanding of liquidity growth dynamics, inflation, and exchange rates in Iran elucidates the reasons behind high inflation, rapid and continuous liquidity growth, and the impact of exchange rate volatility. Extreme changes in each variable overshadow the others, indicating a complex relationship among exchange rates, inflation, and liquidity. Examining the relationship between the volatility of different assets unveils the phenomenon of volatility spillover, where fluctuations in one component trigger volatility in others. An additional crucial aspect is understanding the modes of transmission, reception, and intensity of the causal relationship among exchange rates, inflation, and liquidity in Iran during different periods. In different years, the mutual influence of these components may have varied based on political, economic conditions, health, and pandemic issues, each of which impacting decision-making concerning exchange rates, inflation, and liquidity as three vital macro-economic components. In this respect, the present study used the time-varying parameter vector autoregression model based on Barunik-Krehlik (TV-VAR-BK) with monthly frequency in order to examine volatility spillover from March 1982 to September 2022 in Iran, providing a new perspective on investigating causality by analyzing the time-frequency volatility among exchange rates, inflation, and liquidity.Materials and MethodsThis study is applied and analytical in terms of its purpose and research method, respectively. The data was sourced from the Economic Accounts Department and the National Accounts of the Central Bank. The TVP-VAR-BK model was employed to analyze the time series among exchange rates, inflation, and liquidity. The TVP-VAR-BK model helped analyze the transmission and reception of volatility of variables across different periods (short-term, medium-term, and long-term). Furthermore, the analysis delved into whether the variables acted as net receivers or net transmitters of volatility.Results and DiscussionThe results showed that, in the short term, liquidity exerted the most significant influence and transmitted volatility to other variables. Notably, the most substantial impact and transmission of volatility by the liquidity occurred in 2013, following the tightening of sanctions on Iran. In the medium and long term, the exchange rate emerged as the most influential factor on other research variables.Examining the causal relationship in the short term, a strong causal connection was identified from liquidity volatility to inflation and the exchange rate. However, no causal relationship was observed between inflation and the exchange rate in the short term. Therefore, in the short term, liquidity could be the primary cause of volatility in inflation and the exchange rate. Failure to control short-term liquidity volatility could lead to severe volatility directly and indirectly within the studied network.Moving to the medium term, the transfer of volatility was predominantly from the exchange rate to liquidity and, to a lesser extent, from liquidity to inflation. In the medium term, the transfer of volatility from the exchange rate to inflation was less pronounced. This suggests that fluctuations in the exchange rate strongly transfer volatility to liquidity in the medium term, and liquidity significantly contributes to the emergence of inflation volatility. The exchange rate, albeit to a minor extent, can directly contribute to the transfer of volatility to inflation. This underscores the dominant role of the exchange rate in the network during the medium term.In the long term, no causal relationship between liquidity and inflation was observed, and there was no causality in the transfer of volatility between inflation and the exchange rate. This implies that factors other than the investigated network can explain inflation volatility in the long term. Although there is causality in the transfer of volatility from the exchange rate to liquidity in the short- and medium-term periods, this causality is stronger in the long term. Hence, while the classical view on liquidity and inflation holds until the medium term, the post-Keynesian view becomes evident in the long term. Overall, the exchange rate stands out as the dominant factor in the investigated network. Without stability in the exchange rate, Iran’s economy shall anticipate the fluctuating growth of liquidity and inflation in the short- and medium-term periods.ConclusionThe primary relationship among the volatility of the examined variables proved to be long-term, with the exchange rate emerging as the dominant factor explaining the volatility within the investigated network. In the short term, liquidity functioned as the net transmitter of volatility to inflation and the exchange rate. However, in the medium and long term, the exchange rate takes on the role of the primary transmitter of volatility, while inflation and liquidity assume the positions of net receivers of currency volatility. Moreover, the impact of the exchange rate was found to be notably stronger. Should exchange rate volatility remain uncontrolled, it has the potential to induce inflation volatility by transferring it to liquidity. This underscores the critical importance of maintaining exchange rate stability for the effective control of liquidity and inflation.
Financial Economics
Gholamhossein Golarzi; Mahnaz Khorasani
Abstract
The exchange rate, as a fundamental variable, alongside other economic variables, has a significant impact on stock returns. Therefore, this study has investigated the effects of the exchange rate and its fluctuations on the pharmaceutical industry's stock returns through linear and nonlinear models ...
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The exchange rate, as a fundamental variable, alongside other economic variables, has a significant impact on stock returns. Therefore, this study has investigated the effects of the exchange rate and its fluctuations on the pharmaceutical industry's stock returns through linear and nonlinear models during the years 2005 to 2021. In this research, first, the exchange rate fluctuations were modeled using the GARCH model. Then, the symmetrical and asymmetrical effects of the exchange rate and its fluctuations, along with the macroeconomic control variables including the healthcare consumer price index, oil price, and industry-specific control variables including asset return ratio, asset turnover ratio, and debt ratio as well as the COVID-19 dummy variable, were investigated on the return of the pharmaceutical industry stock using both linear ARDL and nonlinear NARDL models. The study shows that in both the short and long term, the impact of the exchange rate on pharmaceutical industry stock returns is greater than the impact of exchange rate fluctuations. Additionally, negative shocks of the exchange rate and its fluctuations have a negative relationship with the pharmaceutical industry's stock returns, while positive shocks of the exchange rate and its fluctuations have a positive effect on the pharmaceutical industry's stock return. The study's findings suggest that the impact of positive and negative shocks of the exchange rate and its fluctuations have asymmetric effects on the return of pharmaceutical industry stock. Results show that control variables and COVID-19 have significant effects on pharmaceutical industry stock returns in linear and nonlinear models.1.IntroductionPharmaceuticals, as a strategically vital industry, can significantly contribute to a country’s economic growth and the enhancement of public health. However, a major challenge faced by this industry in Iran is its heavy dependence on imported raw materials and essential machinery, with nearly 60% of the required raw materials being sourced through imports. The pharmaceutical sector in Iran is particularly vulnerable to exchange rate fluctuations, given its high dependency on foreign currency. Consequently, the exchange rate and its fluctuations emerge as determining factors influencing the profitability and stock returns of companies operating in this sector. Divergent perspectives exist regarding how exchange rate fluctuations impact stock returns, with some studies asserting a positive correlation, others a negative one, and some maintaining a neutral stance. Since there is no consensus on the precise nature of the relationship between exchange rate fluctuations and stock returns, especially within the pharmaceutical sector, the present research tried to investigate and compare the effects of exchange rate and its fluctuations on stock returns in the pharmaceutical industry.2.Materials and MethodsUsing linear and nonlinear autoregressive distributed lag models (i.e., ARDL and NARDL), the study examined both the symmetrical and asymmetrical effects of exchange rate fluctuations on the return of pharmaceutical industry stocks during 2005 to 2021. The research also considered macroeconomic control variables, including healthcare consumer price index, oil price, COVID–19 dummy variable, and the variables specific to the pharmaceutical industry (e.g., asset return ratios, turnover ratios, and debt ratios). First, the generalized autoregressive conditional heteroskedasticity (GARCH) model was employed to model exchange rate fluctuations. The long-term linear equation for the return of pharmaceutical industry stocks can be defined as follows:(1) Also, the long-term nonlinear equation is defined as follows:(2) 3.Results and DiscussionThe research findings reveal that, in the short-term period and based on the linear ARDL model, the exchange rate significantly affects the return of the pharmaceutical industry stocks, with exchange rate fluctuations also causing a significant negative impact on stock returns. Moreover, the analysis of the long-term coefficient estimates from the linear ARDL model suggests a positive correlation between the exchange rate and pharmaceutical industry stock returns. Consequently, the results imply that an increase in the exchange rate can boost the competitive power and stock returns of pharmaceutical companies. However, in the long run, exchange rate fluctuations can have a detrimental effect due to heightened uncertainty in the stock market, dissuading investors from engaging in this industry. Additionally, the study indicates that an increase in oil prices results in a decrease in pharmaceutical industry returns, as investors seek profits in alternative markets. Inflation, too, negatively affects pharmaceutical industry stock returns, as heightened inflation fosters uncertainty, reducing investor inclination toward pharmaceutical stocks. Furthermore, the research findings highlight that various factors such as pharmaceutical industry asset returns, asset turnover, debt levels, and the dummy variable of COVID–19 positively impact pharmaceutical industry returns.The results obtained from the nonlinear NARDL model showed that both short-term and long-term negative shocks in the exchange rate and its fluctuations significantly decrease the stock returns of the pharmaceutical industry. In contrast, positive shocks in the exchange rate and its fluctuations positively affect the stock returns of the pharmaceutical industry. Hence, it can be concluded that the exchange rate and its fluctuations have an asymmetrical effect on pharmaceutical industry stock returns in Iran. Unlike the linear ARDL model, the results of the nonlinear NARDL model indicated that inflation and debt levels do not exert significant impact on pharmaceutical industry stock returns in the long run. Additionally, impact of oil prices on pharmaceutical industry returns is significantly negative in the long run, while pharmaceutical asset returns, asset turnover, and the dummy variable of COVID–19 contribute to an increase in pharmaceutical industry returns in Iran.4.ConclusionConcerning the importance of the pharmaceutical industry and the influence of the exchange rate on the stock returns in the Iranian stock market, the present research used ARDL and NARDL models to examine both the linear and nonlinear effects of exchange rate and its fluctuations on pharmaceutical industry stock returns during 2005–2021 in Iran. The research results indicated that, in both the short and long term, the impact of exchange rate is more significant than the impact of exchange rate fluctuations on the returns of pharmaceutical industry stocks. According to the findings, negative shocks to the exchange rate and its fluctuations can lead to a decrease in the returns of pharmaceutical industry stocks, while positive shocks result in an increase. The results suggest an asymmetrical impact of positive and negative exchange rate shocks and its fluctuations on pharmaceutical industry stock returns. In both linear and nonlinear models, the control variables of the study, along with the COVID–19 as the dummy variable, have significant impact in on pharmaceutical industry stock returns. In sum, the findings indicated a significant relationship between the exchange rate and its fluctuations and pharmaceutical industry returns in Iran. However, the impact of exchange rate and its fluctuations on pharmaceutical industry proves to be heterogeneous. It is thus recommended that investors take note of the differing results of linear and nonlinear models and the asymmetric effects of variables, utilizing modern financial engineering instruments to implement appropriate risk-hedging strategies against exchange rate fluctuations.
currency
Hassan Tahsili
Abstract
The effect of exchange rate changes on the general level of prices is one of the major issues in macroeconomics and has important results for the monetary policy maker. With respect to these two variables in Iran's economy, modern econometric approaches can provide new insights. In this regard, using ...
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The effect of exchange rate changes on the general level of prices is one of the major issues in macroeconomics and has important results for the monetary policy maker. With respect to these two variables in Iran's economy, modern econometric approaches can provide new insights. In this regard, using the threshold vector autoregressive model, the present study attempts to investigate the nonlinear exchange rate pass-through in Iran during 1369:1 – 1397:4. The results show that pass trough of exchange rate to the general price levels depends on the amount of inflation (inflationary conditions and its threshold). If seasonal inflation exceeds from 5.48%, the exchange rate shocks has lower effect on inflation. The results show that, exchange rate shocks have a severe effect. Due to the lack of inflation targeting policy in the Iran’s economy, the impact of exchange rate shocks on inflation is lower in values below the level of 5.48%. Accordingly, in inflation rates below the threshold, monetary policy has less freedom of action and the goals of reducing inflation and exchange rate policies need to be taken into account simultaneously.
Health Economics
Soheil Roudari; Masoud Homayounifar
Abstract
The present study investigates the effect of coronavirus outbreak and exchange rate and oil price variables on the stock market index using Markov Switching model during the period 1398/11/30 – 1399/03/27. The results show that exchange rate growth has no significant effect in the high regime ...
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The present study investigates the effect of coronavirus outbreak and exchange rate and oil price variables on the stock market index using Markov Switching model during the period 1398/11/30 – 1399/03/27. The results show that exchange rate growth has no significant effect in the high regime of the stock market index and has a negative and significant impact in the low and medium regimes. The growth of oil prices has had a negative and significant effect on all stock market index regimes. Also, in the high regime of the stock market index, the prevalence and increase in the coronavirus cases will lead to a decrease in the stock market index, and on the contrary, in the low regime of the stock market index, the prevalence and increase in the coronavirus cases will increase the stock market index. In the high regime of the stock market index, the coronavirus outbreak can lead to a decrease in the stock market index and the outflow of capital from the stock market and transfer to other parallel markets such as currency and housing can occur, and speculation increases.
International economy
Samira Motaghi; Anahita Saifi; Salah Ebrahimi
Abstract
The aim of this paper was to investigate the relationship between trade openness and inflation in selected developing and developed countries from 1990 to 2017 using a Panel data approach for testing Romer's hypothesis of relationship between inflation index and Trade Openness. The results of the paper ...
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The aim of this paper was to investigate the relationship between trade openness and inflation in selected developing and developed countries from 1990 to 2017 using a Panel data approach for testing Romer's hypothesis of relationship between inflation index and Trade Openness. The results of the paper show that the Romer hypothesis is rejected in both the studied groups (developed and developing). The results showed that the effect of trade openness on inflation rate was positive and significant in both groups. But the impact of trade openness on inflation has been greater in developing countries. The effect of money supply on inflation was positive and significant in both groups. According to other results of this study, GDP had a significant and negative effect on inflation. Also, the exchange rate has not been a determinant of inflation in developed countries but in developing countries it has had a positive effect on inflation.
Abdorasoul Sadeghi; Seyed Komail Tayebi
Abstract
Due to the historical importance of inflation in the Iranian economy and its serious effects on the society, the present study has explored the impacts of international sanctions and other effective factors on the inflation rate in Iran during 1981-2014. To this end, this paper has specified an econometric ...
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Due to the historical importance of inflation in the Iranian economy and its serious effects on the society, the present study has explored the impacts of international sanctions and other effective factors on the inflation rate in Iran during 1981-2014. To this end, this paper has specified an econometric model of inflation rate, which has been estimated by the ARDL method using relevant time series data including the above period. The empirical results obtained indicate that the international sanctions have had direct and significant effects on the inflation rate through changes in exchange rate and budget deficit. Additionally, exchange rate, money liquidity and deposit interest rate have had positive and significant effects on the inflation rate, while oil revenues and tax earnings have influenced indirectly and significantly Iran’s inflation rate over the period.
Habib Morovat; Ali Faridzad
Abstract
Exchange rate is one of the most important factors in open economies. So determining the factors which affect exchange rate behaviors is necessary. In this research we try to analyze the role of extrapolative expectations and chartists in the instability of exchange rate market. We use unofficial nominal ...
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Exchange rate is one of the most important factors in open economies. So determining the factors which affect exchange rate behaviors is necessary. In this research we try to analyze the role of extrapolative expectations and chartists in the instability of exchange rate market. We use unofficial nominal exchange rate data (Rial/Dollar) in weekly, monthly and quarterly horizons (from 1991 to 2015). We use fundamentalists- chartists approach and agent-based model (ABM) for simulation. The results show that when there is instability in market, the weight of chartists is much more than fundamentalists and vice versa. Also we show that chartists gain from this market so they don’t like to leave the market.
Parviz Mohammadzadeh; Hossein Asgharpur; Mohammad Bagher Beheshti; Ali Rezazadeh
Volume 16, Issue 49 , February 2012, , Pages 151-175
Abstract
The main objective of this paper is to examine of monetary approach to exchange rate determination in 14 MENA countries during 1975-2006. For this purpose, panel cointegration technique has been used to test the basic monetary model and flexible price monetary model of exchange rate determination. The ...
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The main objective of this paper is to examine of monetary approach to exchange rate determination in 14 MENA countries during 1975-2006. For this purpose, panel cointegration technique has been used to test the basic monetary model and flexible price monetary model of exchange rate determination. The empirical results indicate that there is a cointegration relationship between variables of basic and flexible price monetary models and therefore the monetary model is able to convincingly explain the exchange rates in MENA Countries. Hence, it could be concluded in the region the parity domestic currency vs. foreign currencies has been affected by mostly the amount of domestic money and increase (decrease) of amount of domestic liquidity leads to devaluation (evaluation) of domestic money. Also, the results show that there is negative significant relationship between exchange rate and output and positive significant relationship with expected inflation rate in Middle East and North Africa countries. This empirical evidence implies that in addition to liquidity, variables such as expected inflation rate and GDP are important in determination of the equilibrium exchange rate in MENA Countries.
Zahra Nasrollahi; Mina Shahviri,
Volume 15, Issue 44 , October 2010, , Pages 199-230
Abstract
Management of Foreign exchange reserves is important for every country. This matter is also of particular interest for Iran as an Oil exporting developing country. This paper designs an optimal portfolio for that part of foreign exchange incomes which is used for investment. Using the data on foreign ...
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Management of Foreign exchange reserves is important for every country. This matter is also of particular interest for Iran as an Oil exporting developing country. This paper designs an optimal portfolio for that part of foreign exchange incomes which is used for investment. Using the data on foreign exchange daily returns, for the period 2000-2008, and applying univariate and multivariate Garch models, we estimate a model which maximizes expected returns subject to a Value-at-Risk constraint. The results are examined using Backtesting, and then the most acceptable model is suggested. The results that the multivariate GARCH model is the most efficient method for selecting the foreign exchange optimal portfolio in Iran.
Mohsen Mehrara; Alireza Abdi
Volume 9, Issue 31 , July 2007, , Pages 1-26
Abstract
This paper studies the impact of Rial's real devaluation and scale variables (domestic and foreign real income) on Iran's trade balance using the Johansen-Juselius and ARDL methods for the period 1338-1383 (1960-2004).
According to co-integration tests results, trade balance variables, ...
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This paper studies the impact of Rial's real devaluation and scale variables (domestic and foreign real income) on Iran's trade balance using the Johansen-Juselius and ARDL methods for the period 1338-1383 (1960-2004).
According to co-integration tests results, trade balance variables, domestic and foreign income, and black market exchange rates are co-integrated indicating a long run equilibrium relationship among them. Moreover, all the long and short run coefficients have expected signs and are stable during the sample period. However, the official exchange rate is not able to explain trade balance fluctuations satisfactorily in this period. The results of co-integration tests reject the null of long run equilibrium relationship among trade balance, scale variables and official exchange rate. The diagnostic tests in the error correction models with official rate imply serious mis specifications as well. The study suggests the need to monitoring the black market rather than official exchange rate.
Reza Nasr Esfahani; Nematollah Akbari; Rasool Bidram
Volume 7, Issue 22 , April 2005, , Pages 43-68
Abstract
In this paper we examine the effects of nominal variables on the GDP gap in Iran. The potential GDP is obtained by Prescott filtering method.
A VAR model is set up & estimated for GDP gap, inflation, market exchange rate growth, and liquidity growth.
The results show that nominal variable ...
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In this paper we examine the effects of nominal variables on the GDP gap in Iran. The potential GDP is obtained by Prescott filtering method.
A VAR model is set up & estimated for GDP gap, inflation, market exchange rate growth, and liquidity growth.
The results show that nominal variable shocks influence the GDP gap in Iran in the same direction. Stability of these shocks indicates their long-run effect on the system. Thus, for economic growth, the economic policy must concentrate on production increases, which would affect the long run production.
Abbas Shakeri
Volume 6, Issue 21 , February 2005, , Pages 23-50
Abstract
The purpose of this paper has been to estimate the impact of price and non-price variables on non-oil exports of Iran. The non-oil exports are considred to be a function of monetary variables, such as the exchange rate, inflation rate, and two non-price variables, as productivity and competitiveness. ...
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The purpose of this paper has been to estimate the impact of price and non-price variables on non-oil exports of Iran. The non-oil exports are considred to be a function of monetary variables, such as the exchange rate, inflation rate, and two non-price variables, as productivity and competitiveness. We use the ARDL technique to estimate the relation. The results indicate that the non-price variables play a significant role in promoting non-oil exports in Iran. Free exchange rate and inflation rate, though had positive sign, are not very important. These findings indicate that in order to increase the non-oil exports, Iran has to remove the constraints on the efficient functioning of price variables and emphasis more on "productivity" and "competitiveness".
