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آیا قیمت‌های نفت خام حاوی ریشه واحد غیرخطی با ضرایب تصادفی است؟ | ||
| پژوهشنامه اقتصاد کلان Macroeconomics Research Letter | ||
| دوره 16، شماره 32، آذر 1400، صفحه 91-116 اصل مقاله (722 K) | ||
| نوع مقاله: علمی | ||
| شناسه دیجیتال (DOI): 10.22080/iejm.2022.24061.1928 | ||
| نویسندگان | ||
| علیرضا نجارپور* 1؛ محسن اسلامی2 | ||
| 1دانشجوی دکتری مالی، گروه مدیریت، دانشکده علوم اداری و اقتصاد، دانشگاه اصفهان، اصفهان، ایران | ||
| 2دانشجوی دکتری مالی،گروه مالی و بانکی، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبایی، تهران، ایران | ||
| تاریخ دریافت: 08 شهریور 1401، تاریخ بازنگری: 05 آذر 1401، تاریخ پذیرش: 07 آذر 1401 | ||
| چکیده | ||
| مدلسازی قیمت نفت به این موضوع بستگی دارد که داده‌های آن مصادیقی از فرآیندهای روند قطعی یا روند تصادفی باشند. تمیز میان این فرآیندها به دلیل نحوه واکنش بلندمدت قیمت‌های نفت خام به شوک‌ها بسیار مهم است. در پژوهش حاضر، برای بررسی ریشه‌های واحد غیرخطی پیچیده از مدل RCAR استفاده شده است. در این نوع از مدلسازی، تایید وجود ریشه واحد RCAR به معنای آن نیست که قیمت‌های نفت خام از یک فرآیند براونی تبعیت کنند. بنابراین، حتی با تایید ریشه واحد نیز نمی‌توان کارآیی ضعیف بازار نفت را نتیجه گرفت. نتایج پژوهش نشان می‌دهد که ریشه واحد در داده های نفت خام از نوع تصادفی است. در نتیجه، با تفاضل‌گیری داده های نفت خام مانا نمی‌شود. لذا، استفاده از متغیر تفاضل‌گیری شده در مدل‌های هم‌انباشتگی نیز نادرست خواهد بود و باید از الگوهای RCAR استفاده شود. این موضوع در پیش‌بینی جهت آتی قیمت‌های نفت خام بسیار مهم است. همچنین، به دلیل آنکه نفت خام ورودی بسیاری از صنایع است؛ نامانایی نفت خام میتواند به سایر متغیرهای کلان اقتصادی منتقل شود. لذا، نظریه‌های ادوار تجاری که شوک‌های اقتصادی را موقت می‌انگارند از پشتیبانی ضعیفی برخوردار خواهند بود. | ||
| کلیدواژه‌ها | ||
| آزمون‌های ریشه‌ی واحد؛ رویکرد بیزی؛ ریشه واحد تصادفی؛ الگوریتم نمونه‌برداری گیبس | ||
| عنوان مقاله [English] | ||
| Do Crude Oil Prices Contain Nonlinear Unit roots with Random Coefficients? | ||
| نویسندگان [English] | ||
| Alireza Najjarpour1؛ mohsen eslami2 | ||
| 1Ph.D. Candidate. in Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran | ||
| 2Ph.D. Candidate. in Management, Department of Finance and Banking, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran | ||
| چکیده [English] | ||
| Modeling of oil price behavior depends on whether we distinguish the observed data as examples of deterministic or random trend processes. The distinction between these processes is crucial because of the long-term response of data series to shocks. Generally, in standard significance tests, the null hypothesis is tested for the difference between the insignificant and significant hypotheses. In the present study, to investigate the root of the non-difference stationary unit from Bayesian methods, we estimate the RCAR model considered for oil prices. The results of this study show that despite confirming the unit root in oil price data, it is not clear that whether a random step process is suitable for predicting Brent crude oil prices or not because confirming the existence of a random unit root does not necessarily mean that the crude oil spot prices follow a Brownian process. Therefore, it is not possible to conclude from such results that the efficiency of the oil market is insignificant. However, because the unit root in the crude oil data is random, it does not persist with the differentiation of the crude oil data; therefore, the use of the differentiated variable in conventional co-integration models will be incorrect. Also, because the crude oil is the input of many industries, this anonymity could be transferred to other macroeconomic variables. Therefore, theories of business cycles that portray temporary economic shocks will have weak support. | ||
| کلیدواژه‌ها [English] | ||
| Unit root tests, Bayesian approach, Random unit root, Gibbs sampling algorithm | ||
| مراجع | ||
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