دانشگاه تربیت مدرس پژوهش ها و چشم اندازهای اقتصادی 3115-9168 24 4 2024 11 21 Early Warning Model and Currency Crisis in the Iranian Economy A Probit Approach طراحی یک الگوی هشدار بحران ارزی برای اقتصاد ایران؛ رویکرد پروبیت 161 189 13625 10.22034/24.4.161 FA محمدجواد خسروسرشکی دانش‌آموختۀ دکتری اقتصاد، دانشکدۀ مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران یاور دشتبانی عضو مدعو علمی گروه علوم اقتصادی دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران Journal Article Aim and Introduction In managed floating exchange rate systems, one of the important issues facing monetary policymakers is defining the exchange rate corridor and committing to it. In developing countries (with a low flow of foreign capital and limited access to international financial markets), it is difficult to follow committed policies. Iran is not only an oil-exporting country but also has limited access to export earnings due to sanctions. The central bank is heavily dependent on the government policies. Consequently, these causes have led to 5 currency crises since 1991. Therefore, having an early warning system for Iran’s exchange market is essential for monetary policymakers. One of the prominent aspects of this study is the definition of crisis index, which considers not only the direct intervention of the central bank in the exchange market but also both the exchange rate growth and the central bank’s foreign reserve growth rate. Finally, using the Probit approach, an early warning system with a low noise-to-signal ratio is proposed. Methodology Quarterly data from 1990 to 2023 for Iran and the United States were used in the model. Domestic data represent the real and monetary sectors of Iran’s economy, and U.S. data represent the world economy. First, using Bai-Perron (1997) and oil revenue as a state variable of the economy, the duration was divided into three periods: low oil revenue, high oil revenue, and sanctions. The random walk equation was estimated. logoil t =a+b logoil t-1 + ε t (1) Second, for each period, according to Weymark's (1995) model, the exchange market pressure (EMP) and direct intervention indices were calculated. Then the average and standard deviation of both the exchange rate growth and the central bank’s foreign reserve growth rate were calculated. Third, the situation in each quarter is determined as shown in Tables 1 and 2: Table 1: The situation in each quarter in leaning with the wall intervention type rt≥r-σr rt<r-σr Type of intervention: leaning with the wall Crisis type (1) Mega-Crisis type (1) et≥e+σe Favorable Ordinary et<e+σe Table 2. The situation in each quarter in leaning against the wall intervention type rt≥r-σr rt<r-σr Type of intervention: leaning against the wall Ordinary Mega-Crisis type (2) et≥e+σe Favorable Crisis type (2) et<e+σe et is the exchange rate growth, and rt is the central bank’s foreign reserve growth. e and σe are the average and standard deviation of the exchange rate growth, respectively. r and σr are the average and standard deviation of the central bank’s foreign reserve growth, respectively. Ordinary and favorable situations are considered the same. But, the other situations are different. Fifth, equation 2 was proposed as an early warning system. CRI t =α+ ß 1 CRI t-3 + ß 2 SCN t + ß 3 COV t + ß 4 FRG t-2 + ß 5 ERG t-2 + ß 6 ERGEN t-2 + ß 7 BFRLiq t-2 + ß 8 GBDLiqG t-2 + ß 9 GDBLiqG t-2 + ß 10 LiqG t-2 + ß 11 GDPG t-2 + ß 12 OilGDP t-2 + ß 13 OilG t-2 + ß 14 USAGDPG t-2 + ß 15 USAInf t-2 + ε t All variables are I(0). CRIt is the quarterly situation. SCNt and COVt are the dummy variables for sanctions and COVID-19 respectively. The 2 lag variables are: FRG is the central bank's foreign reserve growth. ERG is the exchange rate growth. ERGEN is the deviation of exchange rate growth from its long-term trend. BFRLiq is the ratio of the central bank's foreign reserve to liquidity. GBDliqG is the growth of the ratio of the government budget deficit to liquidity. GDBliqG is the growth of the ratio of the government debt to the central bank to liquidity. LiqG is the liquidity growth. GDPG is the growth of GDP. OilGDP is the ratio of oil revenue to GDP. OilG is the Brent crude oil growth. USAGDPG is the growth of the USA's GDP. USAInf is the USA's CPI. Sixth, the forecasted variable is compared with the actual. Then, the NSR was calculated. NSR is between [0,1]. The less NSR, the better fitted the forecasted variable. Findings There were no crisis type 1 and also mega-crises type 1 and 2. Therefore, the situation in each quarter is either crisis type 2 or ordinary. The crises are 1994q1, 1995q2, 2012q1, 2012q4, 2018q3 and q4, 2020q1 to q4, and 2023q1. The Probit model is: (2) CRI t = -48.154 - 4.717* CRI t-3 + 1.718* SCN t + 11.496* COV t + 2.859* FRG t-2 + 302.002* ERG t-2 - 308.849* ERGEN t-2 - 40.659* BFRLiq t-2 - 36.540* GBDLiqG t-2 + 40.174* GDBLiqG t-2 + 99.098* LiqG t-2 - 14.066* GDPG t-2 + 98.677* OilGDP t-2 - 0.482* OilG t-2 - 4.932* USAGDPG t-2 + 9.820* USAInf t-2 + ε t The above equation can predict all crises. The NSR is 0.143 which means that the model can good predict the crises. Discussion and Conclusion In this article, in addition to examining the exchange rate seasonal growth and the central bank's foreign reserves' seasonal growth, the central bank's performance in the face of currency crises has been determined. Then, a model to predict currency crises with the Probit approach is also provided. The results show that the central bank and other economic agents do not consider the same seasons as critical. The economic agents expected a crisis in any season in which the sanction is approved, regardless of the time of its implementation. In most of the currency crises, the central bank has aggravated the currency crisis by buying foreign currency to increase its foreign exchange reserves. The crisis period has not exceeded two seasons in all cases except the Corona period. Among the internal variables of the model, the variables of liquidity growth, exchange rate growth, foreign exchange reserve growth, oil income to GDP ratio, and sanctions are effective factors in predicting a currency crisis. GDP growth, the Brent crude oil growth, and the difference in exchange rate growth from the long-term trend are also more effective variables in reducing the possibility of currency crises. The proposed early warning currency crisis system could predict all currency crises. Finally, as a policy recommendation, it is suggested that instead of stabilizing the exchange rate level, the central bank should stabilize the exchange rate growth in the mid-term to increase its credibility among economic agents by reducing the inflationary environment and currency fluctuations در این مقاله علاوه بر بررسی فصلی وضعیت رشد نرخ ارز و ذخایر ارزی بانک مرکزی، نحوۀ عملکرد بانک مرکزی در مواجهه با بحران‌های ارزی مشخص شده است. سپس یک الگو برای پیش‌بینی بحران‌های ارزی با رویکرد پروبیت نیز ارائه شده است. نتایج تحقیق نشان می‌دهد که بانک مرکزی و سایر عاملان اقتصادی فصل‌های یکسانی را بحرانی تلقی نمی‌کنند و هر فصلی که تحریم در آن تصویب شود فارغ از زمان اجرایی شدن آن، احتمالاً از منظر عاملان اقتصادی به بحران ارزی منجر خواهد شد. در اکثر بحران‌های ارزی، بانک مرکزی با خرید ارز جهت افزایش ذخایر ارزی خود، وضعیت بحران ارزی را تشدید نموده است. طول دوره بحران‌ها در همۀ موارد به جز دوران کرونا از دو فصل بیشتر نشده است. در بین متغیرهای داخلی الگو، متغیرهای رشد نقدینگی، رشد نرخ ارز، رشد ذخایر ارزی، وابستگی به درآمد نفتی و تحریم از عوامل مؤثر بر پیش‌بینی بحران ارزی هستند. همچنین، متغیرهای رشد بخش حقیقی، رشد قیمت جهانی نفت و تفاضل رشد نرخ ارز از روند بلندمدت از عوامل مؤثر بر کاهش احتمال وقوع بحران‌های ارزی هستند. الگوی پیشنهادی برای هشدار بحران‌های ارزی نیز از قدرت تبیین بالایی برخوردار است. به‌عنوان توصیه سیاستی پیشنهاد می‌شود که بانک مرکزی به جای تثبیت نرخ ارز به تثبیت رشد نرخ ارز در میان‌مدت بپردازد تا با کاهش محیط تورمی و نوسانات ارزی، اعتبار خود را در بین عاملان اقتصادی بالا ببرد

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