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.
Optimization
Hamed Azizi Ganzagh; Ahmad Jafari Samimi; Zahra Mila Elmi; Amir Mansour Tehranchian
Abstract
Inflation forecasting is one of the most important issues for the economies of countries, As the existing literature suggests, hybrid models will bring better prediction accuracy due to attention to both linear and non-linear dimensions. Furthermore, the use of ARDL model can include lags of other variables ...
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Inflation forecasting is one of the most important issues for the economies of countries, As the existing literature suggests, hybrid models will bring better prediction accuracy due to attention to both linear and non-linear dimensions. Furthermore, the use of ARDL model can include lags of other variables in tandem with having linear features. It should also be noted that LSTM models have a forgetting gate due to their non-linear estimation characteristics, and they can incorporate data with very distant lags in the model. Therefore, the combination of these two models can significantly improve the prediction accuracy. Accordingly, attempts have been made in the current study to compare ARDL, NARX, LSTM and ARDL-D-LSTM models with one another and to introduce a suitable model for predicting Iran's monthly inflation rate in the short-term and long-term time horizon. After estimating the monthly inflation rate of Iran in the period of 4/21/2005 to 8/22/2018 and testing the model on the data for the period of 9/22/2018 to 12/21/ 2020 it was found that the NARX model and the ARDL-D-LSTM hybrid model performed well respectively for short-term time horizon and the long-term horizon according to the RMSE criteria.
Hamid Sepehrdoust; Mahsa Barooti
Abstract
One of the main policies for solving the problem of economic growth obstacles and eliminating the sole dependence of the economy on oil revenues is to improve the country's tax system performance. The purpose of the present study was to investigate the factors affecting the tax system performance in ...
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One of the main policies for solving the problem of economic growth obstacles and eliminating the sole dependence of the economy on oil revenues is to improve the country's tax system performance. The purpose of the present study was to investigate the factors affecting the tax system performance in Iranian economy with special reference to Tanzi inflation effect. In order to achieve the research objectives, an Autoregressive Distributed Lag Model (ARDL) was used to estimate the short-term as well as long-term effects of macroeconomic variables on tax system performance for the period 1984-2014, emphasizing on the Tanzi inflation effect as substantial factor. The results showed that in the long term and short term, the inflation rate and agriculture sector's value added have negative significant effects, while human development indicator, industry and service sector's value added and government's expenditures have positive significant effects on tax system performance in Iran during the period of the study.Therefore,effective measures are required to be adopted for the extension of tax bases in the industry as well as service sectors on the one hand, and timely collection of tax revenues through shortening the courses of tax collection is also recommended on the other. These steps along with removal of unnecessary tax exemptions would certainly cause strengthening the efficiency level of tax system performance in the Iranian economy.
Seyed Kamal Sadeghi; Reza Ranjpor; Fateme Bagherzadeh Azar; Soha Mousavi
Volume 20, Issue 65 , February 2016, , Pages 37-61
Abstract
In developing countries like Iran, fiscal policy instruments- especially taxes- affect the competitive power of financial markets and the performance of banking and non- banking institutions in these markets. Thus, the quality of combination of financial markets and tax policies for economic growth ...
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In developing countries like Iran, fiscal policy instruments- especially taxes- affect the competitive power of financial markets and the performance of banking and non- banking institutions in these markets. Thus, the quality of combination of financial markets and tax policies for economic growth has raised many issues. On the one hand, theories state that any increase in taxes leads to a reduction in investment funds and has an opposite impact on financial markets. On the other hand, they state that taxes reduce market fluctuations and prevent financial crises. This paper studies the impact of taxes on financial market in Iran during 1970 – 2011 by using Bounds test and Auto-Regressive Distributed Lag (ARDL) model. Results show that taxation has a positive effect on financial markets. This indicates that the role of taxation, according to improvements in state’s tax system in recent years, has become more prominent in the further development of financial markets.
Hamid La'l Khezri; Ali Akbar Naji Meydani; Mostafa Karimzadeh
Volume 19, Issue 59 , July 2014, , Pages 211-236
Abstract
The real exchange rate is considered as a basic indicator in determining the level of international competition that explain the internal situation of the country. Instability in the performance of this Index implies imbalance in the economy. Instability of the real exchange rate will effect total demand ...
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The real exchange rate is considered as a basic indicator in determining the level of international competition that explain the internal situation of the country. Instability in the performance of this Index implies imbalance in the economy. Instability of the real exchange rate will effect total demand of the economy by import and export and will influence overall economy through costs of intermediate and final imported goods. It’s the cause of changes and fluctuations in consumer and wholesale price indices that are calculated as the basis of inflation. The present study investigates the instability of the exchange rate on the private sector's consumption using annual data for the period 1352-1390. In this regard, values of the real exchange rate volatility using the pattern of generalized autoregressive conditional heteroskedasticity (GARCH), and then the impact of the real exchange rate instability on private sector consumption is surveyed by using the method of Autoregressive-Distributed Lag (ARDL). The results of estimations show that in long term, Disposable income, liquidity, real exchange rate and the volatility of the real exchange rate have positive effect and Real interest rates have a negative impact on private sector consumption.
Behzad Alipour; Mehdi Pedram; Iman Charghanian
Volume 18, Issue 54 , April 2013, , Pages 27-53
Abstract
We analyse short-run and long-run effects of government size on the economic growth of Iran ,using 1353-90 time series .the results of estimation , by using of ARDL and boundaries testing approach, indicate convergence of the dynamic model to the long-run trend. The error correction model also ...
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We analyse short-run and long-run effects of government size on the economic growth of Iran ,using 1353-90 time series .the results of estimation , by using of ARDL and boundaries testing approach, indicate convergence of the dynamic model to the long-run trend. The error correction model also show that 59 present of departure from the long-run trend will be corrected in every period. The long-run estimation shows a positive relation between oil price, oil revenues and ratio of investment to the real GDP as independent variables and economic growth as dependent variable, and a negative relation between government size and a dummy variable for war and revolution as independent variables and economic growth.
Teimur Mohammadi
Volume 16, Issue 47 , July 2011, , Pages 163-183
Abstract
Studies in applied econometrics and related disciplines are widely using time series techniques. Sound application of these techniques requires the satisfaction of their underlying assumptions. One of these techniques is ARDL Model. There are a number of examples in the published works in ...
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Studies in applied econometrics and related disciplines are widely using time series techniques. Sound application of these techniques requires the satisfaction of their underlying assumptions. One of these techniques is ARDL Model. There are a number of examples in the published works in Iranian economic studies which suffers from misconceptions leading to biased and inconsistent estimates of parameters. For example, without assuring the exogeniety of the other RHS variables of the model, estimates are biased and inconsistent. Although fitting an ARDL model to exogenous and/or predetermined RHS I(0) and/or I(1) variables may seem appropriate ,however ,to continue the path leading to the extraction cointegration vectors, would be a misleading strategy. The aim of this paper is to highlight these misconceptions in the application of ARDL technique. To this end, after a theoretical survey of the concept, a dynamic simultaneous equation model (DSEM) of macroeconomic equations is introduced and simulated. The simulated series are used to estimate various versions of the model including VAR, ARDL, DSEM, VECM . Then the correct and incorrect application of ARDL model is specified by using two scenarios.
Alireza Kazerooni; Hadi Mojiri
Volume 15, Issue 45 , February 2011, , Pages 77-102
Abstract
This study empirically analyses bilateral J-curve dynamics of Iran with her six trading partners using time series data over the period 1979 - 2005. Short and long - run impacts of the depreciation of Iranian Rial on the trade balance between Iran and her six trading partners are estimated by using ...
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This study empirically analyses bilateral J-curve dynamics of Iran with her six trading partners using time series data over the period 1979 - 2005. Short and long - run impacts of the depreciation of Iranian Rial on the trade balance between Iran and her six trading partners are estimated by using Auto Regressive Distributed Lag (ARDL) Approach and Error Correction Model (ECM). The empirical results indicate that there is J-curve effect in the short-run between Iran with China and UAE, but in the long - run, the real depreciation of the Iranian Rial has positive impact on trade balance with UAE. The stability of the long-run trade balance equations are tested by using CUSUM and CUSUMSQ stability tests.
Ali Akbar Gholizadeh; Behnaz Kamyab
Volume 14, Issue 42 , April 2010, , Pages 123-147
Abstract
In this paper we analyze the three responses of monetary policy to bubble in housing prices. First rule corresponds to a monetary authority that does not respond to house price inflation. The second rule corresponds to a monetary authority that respond to overall house price inflation, and in third alternative ...
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In this paper we analyze the three responses of monetary policy to bubble in housing prices. First rule corresponds to a monetary authority that does not respond to house price inflation. The second rule corresponds to a monetary authority that respond to overall house price inflation, and in third alternative is a policy in which a monetary authority responds to house price bubble. We use an ARDL model with quarterly data for Iran. The results reveal several practical monetary policy lessons. First، a monetary authority should generally respond to house price bubble because minimizes the loss function. Second، this finding holds even if a monetary authority cannot distinguish between fundamental and bubble house price behavior. Third, monetary authority should tighten when house price bubbles are inflating and should ease when house price bubble collapse.
Ebrahim Hadian; Hojat Parsa
Volume 12, Issue 36 , October 2008, , Pages 1-16
Abstract
The distributed lag effect of a unit change in one of the explanatory variables on the dependent variable is one of the major shortcomings of the standard linear egression model. The long run or error correction equation, with specifies a casual relationship between the inflation and its determinants, ...
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The distributed lag effect of a unit change in one of the explanatory variables on the dependent variable is one of the major shortcomings of the standard linear egression model. The long run or error correction equation, with specifies a casual relationship between the inflation and its determinants, states that a unit change in one of the explanatory variables can result in a change in the rate of inflation only during the period specified by the model. But in practice, changes in, for example, the country's money supply may affect inflation rate over a long period
This paper aims to estimate the adjustment path of the rate of inflation following exogenous monetary shocks. To do so, we use an ARDL model and time series data for the period 1961-2005 in the Iranian economy. The results indicate that one percent, once-and-for-all, increase in money supply positively affects the rate of inflation during three years. One percent increase in money supply at time t results in 0.42 percent in current period, 0.19 percent at time t+1 and 0.27 percent at time t+2 increase in the rate of inflation.
Reihaneh Gaskari; Ali Reza Eghbali; Hamid Reza Hallafi
Volume 7, Issue 24 , October 2005, , Pages 77-94
Abstract
Revenues obtained through gas and oil sale compose a considerable and important part of the Iranian government revenue and the GDP. In this paper, after a brief review on oil sector and income resulting from its export, the authors study the literature pertaining to export instability and its impact ...
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Revenues obtained through gas and oil sale compose a considerable and important part of the Iranian government revenue and the GDP. In this paper, after a brief review on oil sector and income resulting from its export, the authors study the literature pertaining to export instability and its impact on economic growth. Using moving average method with a five-year lag, they found a process for export divergence from which considered as a base for instability. They suggest five definitions for instability as follows: Divergence absolute value, square root of divergence, squared divergence, divergence absolute value for one unit of the estimated amount, and negative divergence. Instability is then considered as a variable in the traditional production function of Feder, which is estimated by ARDL model using five definitions of instability. The findings indicate that there is a negative relation between the first three different definitions of instability and economic growth. Regarding the fourth definition, there is no significant relation and cointegration among the variables is also doubtful. However, regarding the fifth definition, there is a positive and considerable relation between export instability and economic growth and it seems that the fifth definition is not a suitable method to define oil export instability.
Bizhan Safavi
Volume 6, Issue 19 , July 2004, , Pages 143-167
Abstract
This paper investigates the potential of industrial sector in generating indirect employment in its sub sectors. To determine the ability of Job creation, the demand for labor function in each sub sector is estimated, augmented by the demand for Labor growth matrix using the ISIC code. Then, the ...
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This paper investigates the potential of industrial sector in generating indirect employment in its sub sectors. To determine the ability of Job creation, the demand for labor function in each sub sector is estimated, augmented by the demand for Labor growth matrix using the ISIC code. Then, the long term relation between employment and capital stock is tested Using ARDL and Johansen Method. Finally, for ranking indirect employment generating potential, Input-Output accounting and semi social accounting frame work are used. Results show that clothing and leather, and textile sub sectors, with 13 and 12 employee respectively, have the largest employment coefficient, and therefore, the greatest employment generating potential. The direct employment coefficients for these sub sectors are the largest, showing the larger potentials to create employment.
