شناسایی عوامل موثر بر سیکل های تجاری در اقتصاد ایران: رویکرد رگرسیون کوانتایل (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
یکی از مهم ترین شاخص های عملکرد کلان اقتصادی، تولید ناخالص داخلی است که عدم سیاست گذاری صحیح اقتصادی با هدف ثبات بخشی و رشد آن، منجر به وقوع دوره های رکودی در سیکل های تجاری با اثراتی گسترده تر بر عملکرد اقتصادی بویژه رشد اقتصادی، بیکاری و تورم می شود. چرخه های مداوم تجاری منجر به افزایش نااطمینانی در سطح فعالیت های اقتصادی خواهد شد که اثرات منفی بر سرمایه گذاری، مصرف، پس انداز و عملکرد اقتصادی خواهد داشت. آگاهی از اثرات عوامل مؤثر بر سیکل های تجاری از جنبه پیش بینی صحیح این سیکل ها و سیاست گذاری در این زمینه، بسیار مهم و ضروری است. در این مطالعه عوامل مؤثر بر سیکل های تجاری در ایران با رویکرد رگرسیون کوانتایل برای دوره زمانی 1400-1360 بررسی و نتایج نشان داد دوره های رکودی در اقتصاد ایران با تشدید و اعمال تحریم های جدید و خروج آمریکا از برجام (برنامه جامع اقدام مشترک) و ظهور پاندمی کرونا در ایران بویژه از سال 2018 تا 2020 عمیق تر و سریعتر شده اند و نتایج بکارگیری روش ARDL نشان دهنده تأثیر منفی متغیرهای بهره وری نیروی کار، نرخ اشتغال و تجارت خارجی بر سیکل های تجاری و اثر مثبت مخارج مصرفی نهایی ، درآمدهای نفتی و تحریم ها بر سیکل های تجاری (منجر به تشدید رکود اقتصادی شده اند) بوده است و در مجموع اثرات این متغیرها بر سیکل های تجاری متقارن بوده است.Identifying factors affecting business cycles in Iran's economy: quantile regression approach
One of the most important indicators of macroeconomic performance is the gross domestic product, the lack of proper economic policy aimed at its stabilization and growth, leads to periods of recession in business cycles with wider effects on economic performance, especially Economic growth, unemployment and inflation. Continuous business cycles will lead to an increase in uncertainty in the level of economic activities, which will have negative effects on investment, consumption, savings and economic performance. It is very important and necessary to know the effects of factors affecting business cycles from the aspect of correctly predicting these cycles and making policies in this field. In this study, the factors affecting the business cycles in Iran were investigated with the quantile regression approach for the period 1360-1400 and the results showed that periods of stagnation in the Iranian economy with the intensification and application of new sanctions and the withdrawal of the United States from the JCPOA (Comprehensive Program) joint action) and the emergence of the Corona pandemic in Iran, especially from 2018 to 2020, have become deeper and faster. And the results of applying the ARDL method show the negative effect of labor productivity variables, employment rate and foreign trade on business cycles and the positive effect of final consumption expenditures, oil revenues and sanctions on business cycles (leading to the aggravation of recession have become economic) has been And in general, the effects of these variables on business cycles have been symmetrical. Extended abstract Introduction Gross domestic product (GDP) is one of the most important indicators of macroeconomic performance because it shows the size of a country's economy and its production capacity. The growth and stability of the level of economic activities is one of the main goals of economic policy makers. Business cycles, especially recessionary periods, have wide-ranging effects on economic performance, especially economic growth, unemployment, and inflation (Brodor et al., 2020). Business cycles are a kind of irregular fluctuations in the macroeconomic activities of countries, which are mainly created and organized based on the market economy and the activities of companies (Kanjoy et al., 2021). In other words, business cycles, which are also known as business cycles, refer to the fluctuations of the economy between periods of growth (boom) and recession (Chemingui and Eris, 2017). based on this, the period of prosperity begins almost simultaneously in most economic activities, followed by stagnation and contraction, which slows down and reduces the level of economic activity. after each period of stagnation, recovery occurs and the period of stagnation begins again. These changes are repeated many times, but they do not necessarily have a regular periodic state (Charonopoulos et al., 2021). The conventional literature of business cycles with a general approach are classified into six groups as follows: The first group, which includes economists before Keynes, and some of them consider the direction of fluctuations on the demand side and the other part on the supply side as the cause of the formation of business cycles. The second group was the Keynesians who considered the business cycle as a psychological theory because they saw its basis in economic analysis and forecasts on the optimistic or pessimistic behavior of the majority of people in the society and believed that The fragility and vulnerability of investment leads to the formation of business cycles. The third group of economists were from the Chicago school, who showed with the results of experimental tests that the rate of change in the volume of money with a long interval can form business cycles. The fourth group of new classics of the monetary branch, led by Robert Lucas, who believed that the origin of business cycles should be sought in unexpected and unforeseeable monetary policies. The fifth group of new classics in favor of true business cycles, who believe that what causes fluctuations and business cycles are tensions on the supply side, not on the demand side, and the roots of these tensions are derived from technology shocks that lead to a reduction in costs and Productivity and efficiency increase. The sixth group is the new Keynesians, who are divided into two main groups in the rooting of business cycles. The first group considers the origin of fluctuations (periods of prosperity and recession) in the stickiness of prices and wages and the second group believes that even if wages and prices are not sticky, some problems in the economy, including asymmetric information (in financial markets), can explain the roots of recession. Specification of the model In studies where the data is non-normal or not distributed, the use of traditional statistical methods such as mean and standard deviation may provide incorrect results. therefore, despite outlier data, using the quantile method can lead to more accurate results. Also, the quantile method is less sensitive to outliers due to the use of a percentage of the distribution. in many cases, the investigated data are deviated and with a high coverage of values in different ranges. In such a situation, using the quantile method can lead to a more accurate and reliable analysis of the data. because this regression has the possibility to calculate several quantiles for the regression values and calculate the corresponding confidence intervals for the results of each quantile. This advantage allows users of this method to more accurately interpret the results. In general, using the quantile method in the analysis of non-normal and non-distributed data can lead to more accurate results and avoid the problems that exist in traditional statistical methods. The quantile regression form used in this study is the following equation: In the above relation, Conditional quantile is the variable of business cycles calculated by Hodrick-Prescott filter method and It contains the desired information at time t. The variables related to the above equation are defined below and extracted from the Central Bank of Iran website. CYCLE: Business cycles (calculated by Hodrick-Prescott filter method. FORM: Formation of gross fixed capital as a percentage of GDP (percentage). EMP: Employment rate (percentage) PRO: Labor productivity (production per unit of labor) GOV: Final consumption expenditure of the government as a percentage of GDP (percentage) TR: Total import and export divided by GDP (percentage) OIL: Oil revenues SUN: Sanction index In the context of the sanctions index, in this study, the data of the sanctions index used in the study of Iranmanesh et al. (2021) have been adapted. Fuzzy logic method has been used to analyze the data and construct the index of economic sanctions in Iran for the period from 1979 to 2020. In this study, Hodrick and Prescott (1997) filter approach was used to calculate business cycles based on the following equation: In this function and potential production and actual production and T is the observation value which was 42 years in this research. The parameter λ is the weighting factor that determines the smoothness of the process. λ=1600 is used for seasonal data and λ=100 is used for annual data. Findings According to the findings of this study, the hypothesis of non-existence of collinearity among the variables of the model has been rejected. To estimate the long-term relationship between the variables of the model, the modeling approach of Sons and Shin (1999) and the unbounded error correction model (UECM) were used. And the results of the long-term relationship show that the impact of labor productivity on business cycles was negative and significant at the level of 10% error in other words, labor productivity has reduced business cycles in Iran. Also, for the variables of foreign trade, capital formation and employment rate, negative and similar effects have been obtained, that is, these variables have also reduced business cycles in the studied period. On the other hand, government final consumption expenditures and oil revenues have also had a positive and significant impact on business cycles. In other words, with the increase in government final consumption expenditures and government oil revenues, business cycles have increased in Iran. Sanction index has also had a positive and significant impact on business cycles. Economic sanctions by creating restrictions in the fields of finance, trade, financial transfer, oil sales, foreign currency inflow from exports and many other negative effects, lead to increase in fluctuations and as a result of business cycles. The results of the quantile regression show that the sign of the estimated coefficients in the quantile regression is the same as the long-term relationship in the ARDL method. But the size of the coefficients has been different in different quantiles. Based on the estimated results in the upper quantiles of business cycles, the impact of labor productivity on business cycles has decreased in total. For the foreign trade variable, with different results, it shows that in the upper quantiles of business cycles, the impact of foreign trade on business cycles has increased as a whole and the effect of the formation of gross domestic fixed capital in the upper quantiles of business cycles compared to the lower quantiles of business cycles has decreased in total. Results Iran's economy has always been in the condition of inflation stagnation in different periods. In the past decades, Iran's economy has faced problems such as high inflation, economic stagnation, international sanctions, and a drop in oil prices due to internal and external reasons. During these years, various monetary and financial policies have been implemented to reduce inflation and economic prosperity, but each of these policies has not been successful to a large extent for some reasons. In sum, the improvement and control of business cycles in the conditions of inflationary stagnation requires the use of appropriate monetary policies, improvement of the financial system, support of the labor market, reduction of dependence on exports, and increase of investment in infrastructure. Also, creating the right conditions to promote entrepreneurship and encourage investment can also help control business cycles. Finally, achieving these goals requires cooperation between the government, private sector, society and the cen
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