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Showing 12 results for Pourmohammadi
Volume 2, Issue 1 (Issue 1 (Tome 2)- 2012)
Abstract
Nowadays the urban growth pattern of cities is growing dramatically; and current suburbs of cities will form the inseparable components of the main city in the near future. In all cities of world vertical and horizontal urban growth have been one of the most important factors noticed by urban managers and planners. Urban growth is a spatial - structural process that refers to the increased importance of towns and cities as a concentration of population within a particular economy and society. Increase in urban points as quantitative issue shows itself in the forms of increase in population of cities and development in built up area scale. The unorganized physical growth of cities is due to their physical discrete and separate development which is mostly in form of forming individual and separate parts. Hence, analysis of the current physical status, and prediction of the future development of cities due to its influence on the politics and management of city and human resources, is of great importance. Regarding the numerous factors affecting the inharmonic physical urban growth, the present article has investigated the rate of urban horizontal growth from two aspects of area and direction.The research method in this article is analytical- comparative and with respect to the evolution of the physical- spatial pattern of Tabriz metropolitan in the 1956-2006 period. Shannon’s Entropy model is utilized for evaluation of the rate of the urban horizontal growth diversity. In order to use this model first we draw the complete and detailed plan of Tabriz city in concentric buffers with width of one kilometer between years 1956-2006 using Auto Cad software and the physical gravity center of Tabriz city which is the same center of cultural- historical part has been considered as basis for buffering modulation, and Sectoral- Geographical model is used for specification of urban growth directions. . In the next phase center of city gravity has drawn in the form of circle with determined diameter and the center of this circle was considered as basis for modulation of geographical sectors and sectoral buffering in 12 geographic directions. The attained results of analyzing the research findings has shown that the sprawl growth and diversity of inharmonic development has occurred in Tabriz metropolitan. The maximum of this rate has happened on the year 1996 and directions of horizontal urban growth are completely coincided on the margins of main connection corridors of city.
Volume 7, Issue 0 (0-2007)
Abstract
In some mobile systems, intelligent antennas are used to increase efficiency in a wide frequency band and different environmental and electromagnetic conditions. Environmental factors, such as position of nearby objects, antenna mobility and even user type, can vary the antenna input impedance appreciably. Therefore, it is necessary to incorporate an adaptive impedance matching circuit between the antenna array elements and the transceiver to maximize the antenna radiation power. In this research note, the design of adaptive matching circuit for intelligent quadrifilar helical antenna in the UHF band (for GSM) is presented. The GA algorithm is used to optimize the results. The designed circuit can decrease the VSWR from 20 to less than 2 at any frequency within the GSM bandwidth.
Volume 13, Issue 1 (4-2013)
Abstract
This paper presents a novel approach for driving stress assessment by fuzzy clustering. In previous researches, stress during real-world driving tasks has been detected in discrete levels, but in this study, we demonstrated that considering fixed-levels for stress in long periods is not authentic. Without employing discrete levels of stress, data remains unlabeled. So a clustering method has been proposed to compensate for the lack of the feasibility of classification. Due to uncertainties, the clusters can be defined in terms of fuzzy sets. Furthermore, using fuzzy clustering methods, data overlap is considered. In the proposed algorithm, utilizing membership values generated by fuzzy c-means, and weights assigned by fuzzy inference system (FIS), we present automatic continuous criteria for stress in the short time intervals. The continuous scale is defined between 0and100, where higher values represent higher stress levels. Our findings not only confirm rough results of previous studies, but also indicate improvements in precision and accuracy of stress assessment.
Volume 15, Issue 4 (1-2016)
Abstract
This paper presents a novel approach for driving stress assessment by fuzzy clustering. In previous researches, stress during real- world driving tasks has been detected in discrete levels, but in this study, we demonstrated that considering fixed-levels for stress in long periods is not authentic. Without employing discrete levels of stress, data remains unlabeled, so a clustering method has been proposed to compensate for the lack of feasibility of classification. Due to uncertainties, the clusters can be defined in terms of fuzzy sets. Furthermore, using fuzzy clustering methods, data overlap is considered. In the proposed algorithm, using membership values generated by fuzzy c-means, and weights assigned by fuzzy inference system (FIS), we present an automatic continuous criteria for stress in short time intervals. The continuous scale is defined between 0 and 100, where higher values represent higher stress levels. Our findings not only confirm rough results of previous studies, but also indicate improvements in precision and accuracy of stress assessment.
Volume 17, Issue 106 (December 2020)
Abstract
Texture analyzer is one of the important tools for analyzing and evaluating texture properties including hardness, softness, extensibility, tightness, fragility, adhesiveness, adhesion, compressibility, flexibility, shearability, elasticity, gel strength and springiness In this research, a texture analyzer was designed which, based on software and data processing ideas, while increasing the accuracy of performance and measurements, it provided calibration capabilities to make the output data close to real data . The main features of the texture analyzer are the ability to carry out the test in controlled temperature and humidity to analyze the texture parameters in order to reduce error in regions with different temperature and humidity. The results of the tests show that by carefully calibrating the calibration process and designing the calibration filter, the accuracy of the analyzer's performance is improved to 0.05% of the read value. Also, using the micro-stapling algorithm and the use of the screw mechanism, the movement of the jaw is precisely less than 0.005 mm and the speed of 0.1 millimeter per second is controllable. All of these features, along with the USB connection with any personal computer, will be able to communicate directly with the EXCEL program, and save and simplify data analysis under the EXCEL program. The results of the tests show that there is no statistically significant difference between the relative humidity of the texture analyzer and the relative humidity for each sample (p <0.05). Texture hardness of different samples of biscuits containing resistant starch was evaluated by commercial (C) and designed (D) instrument and there was no significant difference between the hardness of the texture obtained from both devices.
Volume 18, Issue 111 (May 2021)
Abstract
This study aims at evaluating the impact of pumpkin powder (12%) and Balangu seed gum (BSG) (0.00, 0.50, 1.00 and 1.50 %) on the physicochemical, rheology, textural properties and sensorial parameters of the sangak bread. First, the fresh pumpkin slices (5mm thickness) were dried (65°C) and samples were powdered and used in the sangak bread formulation. Pumpkin bread dough formulated with BSG showed pseudoplastic and thixotropic behaviour. The bread dough viscosity increased from 13.31 to 23.65 Pa.s with increasing BSG percent from 0.00 to 1.50 % (P<0.05). With increasing BSG concentration, the density of baked breads was reduced from 880.10 to 704.29 kg/m3. The surface color of samples was affected by addition of BSG. The pumpkin bread with 1.00 % BSG demonstrated a colour, with L*, a* and b* indexes equal to 65.38, 6.86 and 44.43, respectively. The weight, moisture content (MC) and volume values of breads increased from 52.83 to 57.02 g, 30.04 to 35.56 % and 65.38 to 80.99 cm3, respectively. BSG improved porosity of the breads and resulted in reduced baking loss and softer bread product. The sangak bread with 1.5% BSG had the best score of color, porosity and appearance, and the bread with 1% BSG had the highest satisfactory in terms of flavour, textural properties and total acceptance (P<0.05).
Volume 19, Issue 122 (April 2022)
Abstract
Phytic acid is an anti-nutritional compound found in bran and whole wheat flour. In order to reduce the amount of dough medium, single and co- culture of two strains of Lactobacillus plantarum and Lactobacillus acidophilus with 4 sourdough formulations (Formula 1 containing S. cerevisiae yeast, Formula 2 containing L. acidophilus + S. cerevisiae, Formula 3 containing L. plantarum + S. cerevisiae and Formula 4 containing L. plantarum + L. acidophilus + S. cerevisiae) were used and fermentation was performed at 27, 32 and 37 ° C at 8, 16 and 24 h. The amount of phytase, phytic acid and minerals (calcium and zinc) were measured at different temperatures and time intervals. First order model reaction was used to investigate the degradation of acid phytic and the increase of calcium and zinc at different temperatures. The data were in good agreement with this model. Moreover, the corresponding activation energies were calculated. The results showed that co- culture of L. plantarum + L. acidophilus + S. cerevisiae represented the highest content of phytase 163 U/mL and the highest calcium 27.4 mg/100g and zinc 1.69 mg/100g (at 37 °C). Although the highest efficiency of phytase production was observed in the first 8 hours of fermentation, however an increasing trend was observed in the content of zinc and calcium up to 24 hours of fermentation. The trend of phytase production was observed as follows: L. plantarum + L. acidophilus + S. cerevisiae> L. plantarum + S. cerevisiae> L. acidophilus + S. cerevisiae> S. cerevisiae. Moreover, the lowest content of phytic acid was observed after 24 hours of fermentation at 37 °C in sourdough of L. plantarum + L. acidophilus + S. cerevisiae and its amount reduced from 563.8 ± 20.5 mg/100 g in wholemeal flour to 43.8-110.3 mg/100 g.
Volume 19, Issue 124 (June 2022)
Abstract
Because food contamination with mycotoxins is a serious problem, in this study, the ability of aflatoxin B1 to bind to the Saccharomyces cerevisiae cell wall was investigated to reduce Sangak bread dough toxicity. For this purpose, aflatoxin B1 at a concentration of 10 μg/kg inoculated to the dough containing 0.27 g of viable saccharomyces cerevisiae, acid treated saccharomyces cerevisiae, and ultrasonicated saccharomyces cerevisiae. Toxin adsorption kinetics were investigated at 24, 28 and 32 °C and 8, 16 and 24 h incubation. The trend for toxin adsorption was as follows: ultrasonicated yeast ˃ acidic yeast ˃ viable yeast. With increasing the incubation temperature and time, toxin adsorption increased in acid treated and ultrasonicated Saccharomyces cerevisiae, while active yeast samples showed the highest toxin removal at 28 °C. The results showed that the adsorption kinetics by active yeast and acid treated yeast could be explained by means of pseudo first order model, while for the ultrasonicated yeast, the data are more consistent with the pseudo second order model. Also, both surface adsorption and intra-particle diffusion contributed to the adsorption rate steps. Therefore, live or non-living yeast cells are suitable biological agents for aflatoxin removal in a contaminated culture medium, however, ultrasonic treatment is more effective.
Volume 19, Issue 128 (October 2022)
Abstract
In order to achieve high-efficiency hydrolysis by α-amylase, freezing pretreatment of potato starch was performed at -25°C for 4 days (PF4) and 8 days (PF8). For this purpose, potato starch (NPS) and freeze pretreatment were suspended in water by exposure to alpha-amylase (0.15% w/v) for 10 hours at 25°C. Morphological properties, percentage of hydrolysis, degree of crystallinity by X-ray diffraction (X-ray) and pasting properties by rapid visco analyzer (RVA) were studied in native, freezed and hydrolyzed starches. Freezing caused surface damage of starch granule and according to the morphology results, scratches, dents and cracks were observed on the surface of the granule, and these changes were much more obvious after 8 days of freezing than after 4 days of freezing, and they were easily hydrolyzed. It was placed by α-amylase and caused the disruption of starch granules. The results of the hydrolysis percentage showed that freezing produced a trace percentage in the production of hydrolyzed starch. Hydrolysis percentage (%) of natural starch increased to 16.8%, 24.1% and 40.8% after hydrolysis in P, PF4 and PF8, respectively. In addition, the relative crystallinity after freezing decreased from natural starch (37.7%) to 34.8% in PF4 and 33.2% in PF8, and this decrease was very substantial (p˂ 0.05) after treatment with α-amylase which decreased to 34.3%, 29.4% and 25.5% in P, 4 days and 8 days of freezing, respectively. Gelatinization temperature and pick viscosity after amylase treatment in all natural starches under freezing treatment decreased significantly (p˂ 0.05) and the decreasing trend was observed in the order of PF8 > PF4 > P, which granular and intramolecular structures disruption as well as low swelling power could be the reason behind these results.
Volume 19, Issue 128 (October 2022)
Abstract
The high-pressure process is a novel non-thermal technology by which food is subjected to a pressure of 100-600 MPa. In this research, the effect of bacterial alpha-amylase on the degree of hydrolysis, crystallinity, morphological and thermal characteristics of natural corn starch before and after high pressure processing (300 and 600 Mpa) was investigated. The results showed that with increasing pressure, the effects of processing on the physicochemical and thermal properties of starch were increased. Also, starches treated with high pressure process were more sensitive to enzymatic hydrolysis. The results of SEM analysis showed that the starches treated with a pressure equal to 600 MPa had the highest porosity, indentation and roughness on the surface of the starch granules and showed the highest sensitivity to enzymatic hydrolysis. The amount of crystallinity in the starches treated with high pressure and enzyme was lower than the natural starch sample due to the destruction of the starch crystal structure. The results of the thermal characteristics of starches showed that with the increase of the applied pressure, the parameters of TO, TP, TC and enthalpy decreased significantly. The high- pressure processing can create favorable physical modifications on the starch, and because of these modifications, a lower amount of alpha-amylase can be used for starch hydrolysis.
Mr. Ahmad Pourmohammadi, Dr Zohre Tabatabaienasab, Yhya Abtahi, Dr Mohammad Ali Dehqantafti,
Volume 22, Issue 3 (Autumn 2022 2022)
Volume 22, Issue 3 (Autumn 2022 2022)
Abstract
The 2008 global financial crisis and the new coronavirus disease (COVID-19) pandemic have attracted interest in the issue of fiscal policy. Since fiscal policy plays an important role in alleviating the costs of these crises, understanding the relationships between fiscal policy components is crucial and has important implications for choosing fiscal policies in the field of public economics. This study aims to examine the causal links between the fiscal policy components, i.e., government expenditures (current and development) and government revenues (tax and oil) in Iran, using quarterly data for the period of 1990:2-2019:1. For this purpose, first, we employ the time domain Toda-Yamamoto causality test to check the causal relationship among these variables. Then, due to the various characteristics of variables in the frequency bands, we implement a dynamic analysis through wavelet coherence approach and wavelet phase-difference in order to explore the joint time-frequency domain causal relationship between government revenues and expenditure categories. The results of the wavelet analysis show that the linkage between the government revenues and expenditures pairs is not the same across all time horizons and a strong heterogeneity in the revealed interrelationships is detected over time and across scales. Overall, the results reveal various causal effects and confirm the expenditure dominance hypothesis for oil revenue, and revenue dominance hypothesis for tax revenue at different frequencies.
Mr Ahmad Pourmohammadi, Dr Zohreh Tabatabaiie Nasab, Dr Yhya Abtahi, Dr Mohammad Ali Dehqantafti,
Volume 24, Issue 2 (summer 2024)
Volume 24, Issue 2 (summer 2024)
Abstract
Introduction
Despite the increasing debate around the role of alternative renewable sources of energy such as solar and nuclear power, oil still has a central role for a vast portion of the world’s countries. Therefore, oil price is one of the key prices in the international economy, and its effects and mechanisms on macroeconomic variables has been an important topic of economic research. In oil-exporting countries, oil price fluctuations have implications for all macroeconomic and prudential policies but due to the government ownership of natural resources, fiscal policy is especially important and can be a main mechanism for transferring these fluctuations to the economy. In this regard, this study aims to analyze the complex relationships and dynamic co-movements between international oil price movements and macroeconomic variables, emphasizing the role of fiscal policy in a time-frequency approach in the years 1978-2020. For this purpose, we implement two novel wavelet analysis techniques, namely, multiple wavelet coherence (MWC) and partial wavelet coherence (PWC), which are used to explore the real relationship between variables. The use of the wavelet tool is superior to traditional tools because it allows the analyst to determine how the series interact at different frequencies and how they evolve over time. To the best of our knowledge, the current is the first paper to implement the wavelet framework to analyze the effects of oil price dynamics on macroeconomic variables in Iran. Therefore, this study makes a modest contribution to the empirical literature by unveiling the main transmission mechanism of oil prices at different time horizons.
Methodology
The econometrics techniques that have been previously used are focused on time domain analysis. This analysis may return incomplete and ambiguous information on the relationship between economic variables. Therefore, this study is focused on time and frequency domain analysis using the wavelet transformation approach that has been left out for the relationship dynamics among these variables.
The origin of wavelets can be traced back to Fourier analysis, which is the foundation of modern time-frequency analysis. Fourier transform, examine the periodicity of phenomena by assuming that they are stationary in time. But most economic and financial time series exhibit quite complicated patterns over time. The wavelet transform approach was introduced to overcome the limitations of the Fourier transform. In fact, if the frequency components are not stationary traditional spectral tools may miss such frequency components. The wavelet analyses do not follow the initial checks to observe if the series have unit root or not. The superior feature of the wavelet analysis is related to its flexibility in monitoring several non-stationary signals.
Wavelet Analysis is a method that allows simultaneous decomposition of original time series according to both time and frequency domains. This is very important for economics and finance, as many of the variables in this field can operate and interact differently on dissimilar time scales. So, in this paper, we used two innovative wavelet approaches to study and compare the interdependence between oil prices, non-oil GDP, public expenditure, and trade balance. This approach implements the estimation of the spectral features of time series as a function of time, displaying how the various periodic components of time series vary through time. To check the relevance of the coherence of multiple independents on a dependent one, we use multiple wavelet coherence (MWC), a similar method to the multiple correlations. The partial correlation is one of the tools that can be used in a simple correlation concept. In the wavelet, the researchers can attain this using partial wavelet coherence (PWC). This approach is able to identify the partial wavelet coherence between the two-time series y and x1 after eliminating the influence of the third time series x2. Hence, we use partial wavelet coherence to identify the wavelet coherence between oil prices and government expenditure when canceling out the effect of non-oil GDP and trade balance.
Results and Discussion
The results of the wavelet analysis show that there is a strong coherence between oil prices and the macroeconomic variables at different frequencies. multiple wavelet coherence, shows a high coherency between the four variables in the short-run (1-4 years) and in the long-run horizons (8-16 years). In fact, multiple wavelet coherence between variables shows that there is always a relationship between variables over time and different scales with different coefficients.
Partial wavelet coherence between oil and non-oil GDP has been significant by removing the effects of government expenditure in the short term during the years 1988 to 1992 and also 2000 to 2012. In the scale of 6 to 8 years from 2010, the partial coherence shows an approximate value of 0.6, which is maintained at this frequency until the end of the period. This issue shows the greater correlation between oil price fluctuations and non-oil GDP by removing the effects of fiscal policy fluctuations in these years. Also, by removing the effects of the trade balance, there is a partial wavelet coherence between the pairs of oil price and non-oil GDP from 1996 to 2012 in the short-term time horizon.
The partial wavelet coherence between oil price and trade balance by removing the effect of fiscal policy and also by removing the effect of non-oil GDP indicates a limited relationship between the pair of oil price and trade balance by removing the effects of other two variables during the study period. In both cases, the relationship between the two variables is limited to the early years of the study period, and there is no independent relationship in other areas.
The results of the partial wavelet coherence between oil price and government expenditure showed that by removing the effect of non-oil GDP, the highest correlation of the variable occurred in the short-term and medium-term region. In the short-term time horizon, during the years 1979 to 1992, a strong wavelet coherence can be seen between the oil prices and government expenditure, which was repeated during the years 2010 to 2011. Also, by keeping the variable effects of the trade balance constant until the end of the 80s, there is a co-movement between oil price and government expenditure independent of the effects of the trade balance. This net correlation between the two variables well indicates the role of fiscal policy in the transmission of oil price fluctuations in multiple time scales.
Conclusion
The most important effective factor in increasing oil price fluctuations is the unforeseen and increasing risks related to oil and its related industries. Since the world has seen rapid and successive developments in recent years (including the spread of disease, war, etc.), severe fluctuations have been observed in the global oil markets during these years. Therefore, in a fluctuating environment, oil prices have forced governments and policymakers to formulate policies to deal with the uncertainty of oil prices. To implement such policies, it will be useful to examine the relationship between oil price dynamics and its transmission mechanisms in the economy. In this regard, the present article analyzes the relationship between oil price dynamics and macroeconomic variables, emphasizing the role of fiscal policy in Iran through time-frequency analysis and the new approach of multiple and partial wavelet coherence.
The results of multiple wavelet coherence show the co-movement between oil price and other variables of the model in different time scales. In such a way that this co-movement shows the greatest intensity in short and long-time horizons. Also, the partial wavelet correlation results between the variables of oil price and non-oil GDP as well as government expenditures showed that by removing the effects of other variables, the co-movement between the pair of variables can still be observed in all time horizons. While regarding the trade balance, this net relationship with oil price was not observed.
In general, based on the partial wavelet coherence results, it can be shown that fiscal policy and economic growth are the main channels of oil price fluctuations transmission in this period, which are in line with the studies of Hossein et al. (2008) and El Anshasi (2008) who showed that Fiscal policies are the main propagation mechanism that transmits the oil price shocks to the economy.
Therefore, the reduction of oil price correlation by removing the effects of fiscal policy and business cycles shows the importance of the channel of fiscal policy and GDP in the transmission of oil price fluctuations. Therefore, it is recommended that the policymakers who adjust various economic stabilization schemes for greater stability, while paying attention to the main channels of oil financial resources flowing into the economy, should consider different frequency bands as well.
Despite the increasing debate around the role of alternative renewable sources of energy such as solar and nuclear power, oil still has a central role for a vast portion of the world’s countries. Therefore, oil price is one of the key prices in the international economy, and its effects and mechanisms on macroeconomic variables has been an important topic of economic research. In oil-exporting countries, oil price fluctuations have implications for all macroeconomic and prudential policies but due to the government ownership of natural resources, fiscal policy is especially important and can be a main mechanism for transferring these fluctuations to the economy. In this regard, this study aims to analyze the complex relationships and dynamic co-movements between international oil price movements and macroeconomic variables, emphasizing the role of fiscal policy in a time-frequency approach in the years 1978-2020. For this purpose, we implement two novel wavelet analysis techniques, namely, multiple wavelet coherence (MWC) and partial wavelet coherence (PWC), which are used to explore the real relationship between variables. The use of the wavelet tool is superior to traditional tools because it allows the analyst to determine how the series interact at different frequencies and how they evolve over time. To the best of our knowledge, the current is the first paper to implement the wavelet framework to analyze the effects of oil price dynamics on macroeconomic variables in Iran. Therefore, this study makes a modest contribution to the empirical literature by unveiling the main transmission mechanism of oil prices at different time horizons.
Methodology
The econometrics techniques that have been previously used are focused on time domain analysis. This analysis may return incomplete and ambiguous information on the relationship between economic variables. Therefore, this study is focused on time and frequency domain analysis using the wavelet transformation approach that has been left out for the relationship dynamics among these variables.
The origin of wavelets can be traced back to Fourier analysis, which is the foundation of modern time-frequency analysis. Fourier transform, examine the periodicity of phenomena by assuming that they are stationary in time. But most economic and financial time series exhibit quite complicated patterns over time. The wavelet transform approach was introduced to overcome the limitations of the Fourier transform. In fact, if the frequency components are not stationary traditional spectral tools may miss such frequency components. The wavelet analyses do not follow the initial checks to observe if the series have unit root or not. The superior feature of the wavelet analysis is related to its flexibility in monitoring several non-stationary signals.
Wavelet Analysis is a method that allows simultaneous decomposition of original time series according to both time and frequency domains. This is very important for economics and finance, as many of the variables in this field can operate and interact differently on dissimilar time scales. So, in this paper, we used two innovative wavelet approaches to study and compare the interdependence between oil prices, non-oil GDP, public expenditure, and trade balance. This approach implements the estimation of the spectral features of time series as a function of time, displaying how the various periodic components of time series vary through time. To check the relevance of the coherence of multiple independents on a dependent one, we use multiple wavelet coherence (MWC), a similar method to the multiple correlations. The partial correlation is one of the tools that can be used in a simple correlation concept. In the wavelet, the researchers can attain this using partial wavelet coherence (PWC). This approach is able to identify the partial wavelet coherence between the two-time series y and x1 after eliminating the influence of the third time series x2. Hence, we use partial wavelet coherence to identify the wavelet coherence between oil prices and government expenditure when canceling out the effect of non-oil GDP and trade balance.
Results and Discussion
The results of the wavelet analysis show that there is a strong coherence between oil prices and the macroeconomic variables at different frequencies. multiple wavelet coherence, shows a high coherency between the four variables in the short-run (1-4 years) and in the long-run horizons (8-16 years). In fact, multiple wavelet coherence between variables shows that there is always a relationship between variables over time and different scales with different coefficients.
Partial wavelet coherence between oil and non-oil GDP has been significant by removing the effects of government expenditure in the short term during the years 1988 to 1992 and also 2000 to 2012. In the scale of 6 to 8 years from 2010, the partial coherence shows an approximate value of 0.6, which is maintained at this frequency until the end of the period. This issue shows the greater correlation between oil price fluctuations and non-oil GDP by removing the effects of fiscal policy fluctuations in these years. Also, by removing the effects of the trade balance, there is a partial wavelet coherence between the pairs of oil price and non-oil GDP from 1996 to 2012 in the short-term time horizon.
The partial wavelet coherence between oil price and trade balance by removing the effect of fiscal policy and also by removing the effect of non-oil GDP indicates a limited relationship between the pair of oil price and trade balance by removing the effects of other two variables during the study period. In both cases, the relationship between the two variables is limited to the early years of the study period, and there is no independent relationship in other areas.
The results of the partial wavelet coherence between oil price and government expenditure showed that by removing the effect of non-oil GDP, the highest correlation of the variable occurred in the short-term and medium-term region. In the short-term time horizon, during the years 1979 to 1992, a strong wavelet coherence can be seen between the oil prices and government expenditure, which was repeated during the years 2010 to 2011. Also, by keeping the variable effects of the trade balance constant until the end of the 80s, there is a co-movement between oil price and government expenditure independent of the effects of the trade balance. This net correlation between the two variables well indicates the role of fiscal policy in the transmission of oil price fluctuations in multiple time scales.
Conclusion
The most important effective factor in increasing oil price fluctuations is the unforeseen and increasing risks related to oil and its related industries. Since the world has seen rapid and successive developments in recent years (including the spread of disease, war, etc.), severe fluctuations have been observed in the global oil markets during these years. Therefore, in a fluctuating environment, oil prices have forced governments and policymakers to formulate policies to deal with the uncertainty of oil prices. To implement such policies, it will be useful to examine the relationship between oil price dynamics and its transmission mechanisms in the economy. In this regard, the present article analyzes the relationship between oil price dynamics and macroeconomic variables, emphasizing the role of fiscal policy in Iran through time-frequency analysis and the new approach of multiple and partial wavelet coherence.
The results of multiple wavelet coherence show the co-movement between oil price and other variables of the model in different time scales. In such a way that this co-movement shows the greatest intensity in short and long-time horizons. Also, the partial wavelet correlation results between the variables of oil price and non-oil GDP as well as government expenditures showed that by removing the effects of other variables, the co-movement between the pair of variables can still be observed in all time horizons. While regarding the trade balance, this net relationship with oil price was not observed.
In general, based on the partial wavelet coherence results, it can be shown that fiscal policy and economic growth are the main channels of oil price fluctuations transmission in this period, which are in line with the studies of Hossein et al. (2008) and El Anshasi (2008) who showed that Fiscal policies are the main propagation mechanism that transmits the oil price shocks to the economy.
Therefore, the reduction of oil price correlation by removing the effects of fiscal policy and business cycles shows the importance of the channel of fiscal policy and GDP in the transmission of oil price fluctuations. Therefore, it is recommended that the policymakers who adjust various economic stabilization schemes for greater stability, while paying attention to the main channels of oil financial resources flowing into the economy, should consider different frequency bands as well.
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