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1- Ph.D. Candidate of Economics, Yazd Branch, Islamic Azad University, Yazd, Iran
2- Assistant Professor of Economics, Yazd Branch, Islamic Azad University, Yazd, Iran , tabatabaienasab@iauyazd.ac.ir
3- Assistant Professor of Economics, Yazd Branch, Islamic Azad University, Yazd, Iran
Abstract:   (450 Views)
Introduction:
Despite the increasing debate around the role of alternate 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, that 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 the macroeconomic and prudential policies but due to the government's 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 analyses 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 1357-1399 (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 focused on time domain analysis. this analysis may return incomplete and ambiguous information on the relationship between economic variables. therefore, this study focused on time and frequency domain analysis using the wavelet transformation approach that has been left out for the dynamical relationship 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 1367 (1988) to 1371 (1992) and also 1379 (2000) to 1391 (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 1375 (1996) to 1391 (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 1358 (1979) to 1371 (1992), a strong wavelet coherence can be seen between the oil prices and government expenditure, which was repeated during the years 1389 (2010) to 1390 (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.
Article number: 12
Full-Text [PDF 1774 kb]   (220 Downloads)    
Article Type: Original Research | Subject: Public Economics
Received: 2023/04/29 | Accepted: 2023/06/19

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