early warning system

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.

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.

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.

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

There have been many financial crises in economies in recent decades, often with political, social, and economic consequences. One of these crises is bank bankruptcy, the destruction of which can be transferred to other markets. The Islamic banking system, which is relatively new and still growing in the banking industry, due to its religious characteristics such as non-interest-bearing activities, faces more risks and bottlenecks than other banks, which highlights the need to prevent them. In this article, with the aim of designing a an early warning model to predict the probability of bankruptcy in the banking system of 8 selected Islamic countries during the period 1998-2020, the Multinominal Logit Method was used. Bankruptcy was determined using the Z-Score and financial ratios were considered as variables affecting the probability of bank bankruptcy. In the Multinominal Logit method, it is possible to predict the occurrence of bankruptcy in two periods, before the occurrence and during / after the occurrence of  bankruptcy. The results showed that the ratio of working capital to bank assets and the ratio of  bank income before zakat and taxes to net assets in the period before and after bankruptcy had a negative effect on the probability of  bank bankruptcy. The ratio of  total bank debt to equity in both periods had a positive effect on the probability of  bankruptcy. On the other hand, the ratio of accumulated profit to total bank assets in both periods did not have a significant effect on the probability of  bank bankruptcy in selected Islamic countries.

In this paper, in order to deal with systematic banking crises that lead to turmoil in various economic sectors, using the multiple logit method, the factors affecting the probability of banking crises in 27 selected developed countries during the period 1994-2018 were predicted. The results indicate the positive effect of inflation rate variables in the pre- and post-crisis period and the positive effect of the percentage of real interest rate changes in the post-crisis period on the probability of banking crisis. Economic growth rate and per capita production had a positive effect on the likelihood of a banking crisis in the pre-crisis period, but given the negative effect of these two variables in the post-crisis period, Granting bank loans to the private sector in the pre-crisis period had a negative effect on the likelihood of a banking crisis and doing it in the post-crisis period had a positive effect on it.

Analysis of communications and information dissemination in drought crisis (View of Farmers of Kermanshah Township)AbstractToday, drought planning has focused on risk management which one of its elements is dissemination and communication of early warning to farmers. Based on the evidence, the relevant organizations do not publish the results of their specialized actions for the use; or information dissemination face to defects. The purpose of this research was analysis of dissemination and communications during drought in Kermanshah Township. A descriptive survey method used. The study population included wheat farmers in Kermanshah (N = 31000) that 370 samples were selected using multi-stage cluster sampling method. The data collected by researcher-made questionnaire. Data were analyzed using descriptive statistics. The results showed that farmers mostly use channels such as television, experts of Jihad Agricultural, Meteorological Organization, and friends and neighbors. Also, according to the findings, the Agricultural Jihad, Meteorology and Sound and Vision Organization played the most important role in warnings dissemination and communication. In addition, warnings have provided in the post-drought phase by organizations. In general, it is concluded that organizations usually act poorly in providing information and warnings; and do not have the necessary coordination. It is suggested that the organizations by exchanging information and warnings, as a coordinated unit, provide the required information to farmers through valid channels.Keywords: Communication, Drought, Risk, Early Warning System, Information dissemination.In general, it is concluded that organizations usually act poorly in providing information and warnings; and do not have the necessary coordination. It is suggested that the organizations by exchanging information and warnings, as a coordinated unit, provide the required information to farmers through valid channels.Keywords: Communication, Drought, Risk, Early Warning System, Information dissemination.

Although currency crises evidently Valy based on size and durability in Iran and developing economies, the crises are similarly influenced by the national and international variables through the channel of foreign exchange market misalignements and BOP unsustainability. In this context, we aim to predict currency crises in Iranian economy. Meanwhile, Lasso Regression Method is applied to evaluate the impact of real sector, monetary and external sectors variables on the currency crises respectively two, one, and the same season of the crises incidence. The results underscore the role of the similar indicators to explain currency crises in Iran. The key indicators, which are empirically recognized, are comprised of the net gross domestic saving, and deficit of banks cash flows in the context of a transmission process that sequentially affects the growth of money base, excess aggregate demand, prices growth, net financial-capital transactions as well as the reduction in the disposable international reserves. The transmission process causes the foreign exchange rate deviations from the PPP and UIP rates. The estimation results also underline the likelihood of the EWS to predict the four currency crises in Iran, which respectively encompass the third quarter of 1372, third quarter of 1377, fourth quarter of 1379, and the second quarter of 1390. Moreover, all four-currency crises are evidently influenced by the external indicators (sanctions, and international oil price shocks) and domestic macroeconomic imbalances that periodically accelerated the unsustainability of foreign exchange market and BOP over the past three decades.

Solvency is one of the essential components that illustrates financial status of an insurance company. Therefore, providing a model with considering internal and external factors which could predict decreasing solvency can improve the efficiency of this index. The main purpose of this paper is to present a model for an early warning system based on decreasing probability of solvency from its critical amount in point of supervisory authority view in Iranian insurers. To this end, based on previous studies, a number of indexes, as independent variables affecting solvency, are selected and classified as economic, financial, and corporate governance. In this respect, the empirical model of research was estimated by econometric method of logit panel data for 18 Iranian companies during 1387-1396. The results depict that interest rates and the change in board of directors have the most and the least impact on the probability of falling insurers’ solvency, respectively. Also, the impact of loss ratio differs in various quantities. Moreover, the impact of variables on probability of decreasing of solvency of insurers are verified; including macroeconomic; interest rate, economic growth and international economic sanctions, Financial variables; current ratio, loss ratio, the Herfindahl–Hirschman Index, and change in board of directors.

Financial solvency is one of the essential components that illustrates financial status of a financial enterprise, at large, or an insurance company to be specific. In addition to solvency ratio, other metrics and indices are also early warning indicators of an upcoming crisis in insurance industry. Therefore, the main purpose of the present paper is to provide a model for an early warning system of solvency for insurance companies and Iranian insurance companies in particular. To this end, a number of indexes and ratios, as independent variables affecting solvency, are selected and classified as economic, corporate, and corporate governance, that distinct this article from other studies. In this respect, the empirical model of research was estimated by econometric method of panel data for 18 Iranian companies during 1387-1396. The results of the research depict that interest rates with one-period delay and the change in board of directors have the most and the least impact on Iranian insurers’ solvency, respectively. Also, due to its cube strength, the impact of loss ratio differs in various quantities. Moreover, all hypotheses that are based on meaningful impact of variables on financial solvency of Iranian insurers are verified; including macroeconomic (inflation rate with one delay), interest rate (with one delay), economic growth (with one delay), corporate variables (ratio of investments in risky assets to all assets), loss ratio, the Herfindahl–Hirschman Index, and corporate governance (percentage of major shareholder’s ownership and change in board of directors) along with international economic sanctions.

The purpose of this study is to Prediction the possibility of a banking crisis in a dynamic early warning system framework. We using data compiled from 10 middle-income countries for the period 1996-2017 and estimate static and dynamic logit model. The estimation results show that the dynamic logit model is better than the static model. We find that broad liquidity ratio, domestic credit to GDP ratio and stock market index are early warning signs of banking crisis. Also, the dynamic variable (lagged banking crisis) shows that if a banking crisis occurs in a year ago, there is a possibility of crisis in this year. Our result shows the possibility of continuation and persistence of banking crises for consecutive years. Then, the evaluation results of warning system show dynamic early warning system turns out to exhibit significantly better predictive abilities than the existing static one, both in- and out-of-sample.

The main purpose of this study is to estimate the probability of banking crisis using the second generation of early warning systems (logit models), for 13 selected high-middle income countries over the period of 1980-2016. In this regard, two types of logit models; binomial and multinomial, are estimated. The results of estimated binomial logit model show that three leading indicators of the crisis are broad liquidity ratio, stock price index and inflation, which are the main causes of crisis in the studied countries. These variables account for about 17 percent of the probability of a banking crisis. Then, to avoid post-crisis bias, the multinomial logit model is estimated. The empirical results confirm that above three leading indicators are warning. Also, among the above three variables, only stock price index variable with a probability of 12.68%, causes the economy to exit the banking crisis and change its situation from the crisis/recovery period to the tranquil period. The multinomial logit model exhibit significantly better in-sample predictive abilities than the binomial logit model.

The main purpose of this paper is to predict financial crisis in stock exchange market along with designing warning syetem by data analysis and then to present to financial policy makers for preventing the outbreak or decreasing the effects of crisis. Due to this purpose, it’s used the weekly datas during the years from 10.03.1997 to 03.22.2019. The mean of crises in this present paper is the falling more than 15% of stock price rather to last three months. Hence, it’s been used the dummy variable for operating the dependent variable. It’s been used the residual of autoregressive integrated moving average (ARIMA) for measuring the shocks caused by the index of stock price, exchange rate, price of oil and gold. Based on the results by the different data showed the financial crisis outbreak is the most important variable for predicting the crisis of Tehran stock exchange in weekly data in the last periods. Hence it’s claimed that falling the stock index is affected the value of index in the last periods more than external shock including shock of exchange rate as well as gold and oil. As it’s determined the detection accuracy of crisis is 81.82%, the same for all trees. It means that 36 crisises have been predicted and recognized from the 44 ocurred crisises during the mentioned periods (1121 weeks).

The occurrence of currency crises in recent decades has been one of the problems of the international monetary system. These crises impose heavy costs on the country where they occur and even other countries. For this reason, in recent years, systems for early warning of these crises have been developed to prevent the occurrence of such crises by their early detection and providing sufficient time for policymakers. Meanwhile, Iran's economy has faced several currency crises in the post-revolutionary years and has incurred heavy costs. Under these circumstances, designing an early warning system for currency crises in the Iranian economy can bring many benefits. Therefore, the purpose of this study is to design an early warning system for currency crises in Iran. Based on it, the endogenous crises that occurred in the period under review were identified. Using this system, it is possible to predict future crises and identify the factors affecting the occurrence and intensification of these crises separately in periods of tranquil and crisis.

In order to achieve the above goals, this article used the Markov-switching approach and the quarterly data of the Iranian economy during a period from February 1988 to March 2016. For this purpose, first the components of the designed early warning system, i.e. the dependent variable and the leading indicators of the crisis, were introduced. Afterwards, to estimate the model, first the unit root tests of the variables were used, and then the early warning system was estimated based on the Markov-switching approach in periods of tranquil and crisis. Finally, after diagnostic tests, the in-sample and out-of-sample prediction performances of the system were investigated and the characteristics of periods of tranquil and crisis were studied.

The results indicate that the designed system has a high ability to identify the past crises and anticipate future crises in the Iranian economy. Also, according to the results, in tranquil states, the increase of inflation rate, international reserves to foreign debt ratio, M2 to international reserves ratio, growth of foreign exchange earnings from oil exports and growth of domestic credit have positive and significant effects on the index of foreign exchange market pressure and the greater probability of a currency crisis. But in these tranquil states, the increase in the ratio of foreign exchange earnings to international reserves as well as the growth of industrial production has had negative and significant effects on this index. In other words, they have helped to prevent the occurrence of the currency crisis. Moreover, based on these results, in the crisis states, an increase in the inflation rate, the ratio of international reserves to foreign debt, M2 to international reserves ratio and budget balance to real gross domestic product ratio, with positive and significant effects on the foreign exchange market pressure, will intensify such crises. Of course, if a currency crisis occurs, the increase in the ratio of foreign exchange earnings to international reserves, the growth of domestic credit, the growth of industrial production and growth of real gross domestic product will help improve the crisis state. Finally, based on these results, in the tranquil states, inflation is the most important warning indicator and also the most important factor in increasing the probability of a currency crisis. The growth of industrial production is also the main factor reducing the probability of the crisis. Also, in the crisis states, inflation is the most important factor to intensify the crisis, while the ratio of foreign exchange earnings to international reserves and growth of real gross domestic product are the most important factors in improving the crisis state respectively.

Based on the early warning system designed for the Iranian economy, the occurrence of currency crises and the intensification of crisis states in Iran are due to a set of macroeconomic imbalances. These imbalances and the problems in the monetary, financial and foreign sectors as well as dependence on oil revenues have provided the basis for currency crises in the Iranian economy. However, the results showed that it is possible to deal with the occurrence of a currency crisis in Iran with policies such as inflation control, strengthening and proper management of foreign exchange resources, controlling liquidity growth, managing domestic credit, supporting industrial production, strengthening gross domestic product and controlling the government budget deficit. Also, it is possible to control the critical situation in the event of a currency crisis with such policies.

Encountering with financial crises of supervision and predicting such these events which are necessary to decrease their negative effects on finanicial and economical markets. The current paper is aimed to review the designing the early warning system of financial crisis outbreak in Tehran stock Exchange. Due to this purpose, it’s used the weekly datas during the years from 1997 to 2019 (1121 weeks). The mean of crises in this present papper is the falling more than 15% of price index (TEPIX) toward last three months. Hence, it’s been used the dummy variable for operating the dependent variable. It’s been used the residual of auto regressive integrated moving average (ARIMA) for measuring the shocks caused by the price of stocks, exchange rate, price of oil and gold. The result is modeled by Logit & Probit model and showed that probability of the crisis outbreak is increased by decreasing the stock price in past period as well as the outbreaking of crisis in past period after reviewing and analyzing the data. While the decreasing of exchange rate, increasing of the gold price, and decreasing of oil price don’t affect on crisis outbreak in current periods as meaningfully. Based on weekly data, 44 crisis has occurred which both models have predicted 36 crisis. The power of crisis predicting is 82% and the power of predicting for total model is about 99%.

The purpose of this article is to predict the likelihood of systematic banking crises in selected developing countries, so that economic policymakers can study and deal with this crisis and reduce the likelihood of its occurrence. For this purpose, 37 developing countries were selected and the probability of a banking crisis for the selected countries during the years 1994-2018 was estimated using the binary and multinomial logit model. The results showed that in the multinomial logit model, the percentage of correctly predicted critical periods is higher than in the binary logit model, and the multinomial logit model is more appropriate. The results of the multinomial logit model indicate the ineffectiveness of exchange rate deviation and the positive effect of inflation, real interest rate and trade relations on the probability of a banking crisis in the countries under study. Economic growth rate, per capita production and capital flow, and the ratio of the ratio of bank redits to private sector to production have had a negative effect on the likelihood of a banking crisis in the countries under study. The results also showed that the ratio of private sector credit to production was not a good predictor of the possibility of a banking crisis in the countries under study

The frequent occurrence of foreign exchange crises in recent years has brought back early warning literature to the focus of researchers .The aim of this study is to introduce a warning pattern before the crisis of the foreign exchange crisis in Iran. The purpose of this study was to introduce a warning pattern before the onset of the currency crisis in Iran. In recent years, a concept has been developed for an Early Warning System (EWS), which should be able to identify costly events such as currency crises in order to create enough time to reduce the cost of the crisis for economic researchers. In this study, factors affecting the contingency of an Iranian currency crisis during the years 1981-2016 are examined using a discrete dependent variable model in the Logit model. This study uses a combination of exchange rate changes, foreign exchange reserves and bank interest rate to calculate the adjusted currency crisis index. The results of the estimate logit model shows that the increase in variable ratio of budget deficit to GDP ratio of current account deficit to GDP ratio of domestic credit to the private sector to the GDP and inflation, the probability of a currency crisis increase. In other words, the increase in these variables (as indicators of the advancement of the currency crisis) is causing an intensification in the occurrence of the currency crisis. Other research results suggest that an increase in the GDP growth rate will reduce the probability of a currency crisis. This study uses a combination of exchange rate changes, foreign exchange reserves and bank interest rate to calculate the adjusted currency crisis index. The elasticity of government deficit to GDP ratio indicates that a one percent increase in this variable, assuming other variables are constant. Increases the probability of a currency crisis by 0.48 percent. On the other hand, the marginal Effect on the ratio of state budget deficit to gross domestic product (gdp) shows that in return for a single increase in this variable, the probability of a foreign exchange crisis will increase by 32 per cent. Thus an increase in the budget deficit is one of the leading factors in the occurrence of the currency crisis. It can be said that if the government finances part of its deficit from the reserve location, this would lead to a decrease in foreign exchange reserves and it increases the probability of a currency crisis in the country. On the other hand, the variable elasticity of the current account deficit to GDP ratio indicates that the probability of occurrence of a currency crisis increases by 0.38 percent for one percent increase in this variable assuming the stability of other conditions. On the other hand, the marginal effect of this variable indicates that the probability of a currency crisis occurring during the period under review increases by about 14% per unit increase in the current account deficit. Another leading indicator of the currency crisis that has a negative impact on the currency crisis is the GDP growth rate. In fact, the elasticity of this variable indicates that the probability of a currency crisis is reduced by 0.03% for a one percent increase in GDP growth rate. On the other hand, its marginal effect also indicates that for a unit increase in GDP growth rate, assuming the stability of other conditions, the probability of a currency crisis decreases by 0.24%. The amount of the variable of financial development variable indicates that for one percent increase in this variable, assuming the stability of other conditions, the probability of currency crisis will increase 0.007 percent. On the other hand, the marginal effect of this variable indicates that the probability of occurrence of currency crisis increases by 0.004% per unit increase in financial development. It should be noted that this coefficient is not statistically significant. Marginal ly, inflation rate elasticity indicates that for one percent increase in inflation rate, assuming the stability of other variables, the probability of currency crisis increases by 1.54 percent. The marginal effect of this coefficient also indicates that by one unit increase in inflation rate the probability of a currency crisis increases by 1.33% Therefore, inflation is also one of the leading factors in the currency crisis.

Drought is among disasters that caused a large amount of financial burden to Iranian economy. However, drought management strategies have focused on crisis management instead of risk management. Drought risk management strategies take early warning system as a its focal point in order to disseminate information to drought-affected individuals which in turn reduces drought risk. The purpose of this qualitative study is to analyze mechanisms needed to deploy the production and diffusion of drought early warning system information in Kermanshah Township. Using case study as well as documentary approach, a critical case sample of 26 specialist from Meteorological, Agricultural Organization, Regional Water Company, Agricultural and Natural Resource Engineering System, Agricultural Bank, Regional Sound and Vision Broadcasting and Crisis Department and Municipalities participated in the study. The findings revealed that drought early warning system is not unified in a systematic manner and the stakeholders use their own method of disseminating information independently with limited knowledge of local context and poor knowledge of farmers’ needs and reactions. The findings of this study have implications to design drought early warning system in Kermanshah Province as well as farmers’ empowerment in terms of drought risk reduction.

The purpose of this study is to introduce a pre-crisis warning pattern in Iran during the years 1981-2016 using Logit and Markov switching approaches. This study use a combination of exchange rate changes, foreign reserves and bank profit to calculate the adjusted currency crisis index. In this regard, to investigate the factors affecting the probability of currency crisis was used to Logit approach and  to investigate the effect of early warning variables on the currency crisis the Markov switching approach was used. The results of the Logit approach indicate that the increase in the variables of the ratio of government deficit to GDP, current account deficit to GDP ratio and inflation rate had a positive effect on the probability of a currency crisis. On the other hand, an increase in GDP growth and oil prices has reduced the likelihood of a currency crisis. The results of the Markov Switching approach also show that variables of the ratio of government deficit to GDP, current account deficit to GDP ratio and inflation rate have increased the occurrence of currency crisis. Also, the increase in explanatory variables of oil price and GDP growth rate will reduce the occurrence of currency crisis.

One of the stylized facts of economics is the spread of the financial crisis to various sectors and the ensuing downturn. Thus, observing the financial sector and predicting its crises is an attractive topic among economists, policymakers and investors. For this purpose, financial condition indexes are used. In this regard, the present study develops a new index for the financial condition by using the principal component analysis (PCA) and combining eight financial variables. Then, using the constructed index and applying Markov Switching approach, the financial sector is divided into three situations of crisis, stability and boom over the period 1990:2 - 2017:1. Then, the probability of exposure to these situations in financial sector is calculated. The results show that the critical situation in the financial sector has a relatively low stability, so, with probability 0.93, the financial sector becomes stable in the next period. According to calculations, it is impossible to move from critical and volatile situation to boom. The boom in the financial sector has low stability as well. If the financial sector is in boom at period t, it will remain in the same position with probability 0.27 in the next period. With probability 0.59, the financial sector will experience stability, and with probability 0.14, it will be in crisis condition.

Protected areas (PAs) are the basis of biodiversity protection. Societies invest in utilizing, managing, and protecting the primary roles of the PAs. Thus, performing management plans need much time, cost, and workforce by the increase in number and area of the PAs in recent years. In this research, the early warning system (EWS) is proposed as a solution to decrease the management cost of PAs and other significant and inaccessible areas. EWS is a general idea that can be used as a useful and cheap tool to ease the access to primary global strategic goals of protection of stable development. In some studies, it is attempted to utilize the EWS to describe biological mobility, environmental elements related to ecological security, to prevent the loss of resources in environmental disasters, and to decrease the flood damage. This study is based on research RS_GIS research and the pressure-status-response (P-S-R) model on the ecological security status in Darmiyan PA, located in the eastern part of Iran. The primary goal of this paper is to present the EWS for in time and appropriate monitoring, maintaining the mobility in relations, and preserving the health of the ecosystem of PAs. In this study, it is attempted to determine the ecological security index (ESI) of Darmiyan PA according to the P-S-R model to propose the EWS with the aid of this index for the study area. In this approach, 12 environmental indicators in three categories of pressure (the average annual temperature, annual precipitation, fragmentation, the hunter presence risk), status (distance from human-made areas, distance from farms, cover vegetation status, soil brightness, finite rate of increase wildlife), and response (the increment rate of governmental financing in the region, the Incompatibility percentage of the region with protection use, utilization and development of technology in protection) were chosen. These indicators were measured by the images of TM and OLI sensors of the LANDSAT satellite, DEM Aster, thermal data of Modis from the earth surface, and statistics and information of the environmental and meteorology organizations of South Khorasan. The ESI for each of the 30-meter pixels of the study area was determined by the Multivariate Composite Estimator (MCE) method using Weighted Linear Combination (WLC). According to the defined features for the EWS indicators, the leading and final indicators to act on the EWS system were chosen using decomposition to main components and multivariate regression. Finally, with the calculation of the thirty-year average of the mentioned indicators in the study area, the confidence interval for each of these indicators with the confidence factor of %95 was achieved. The results declared that the average ESI changed from 0/315 in the year 2000 to 0/518 in the year 2014. Checking the variance plot of the standard value of the useful indicators in ESI declared that except three indicators of distance from human-made areas, distance from farms, and the incompatibility percentage of the region with protection use, the other indicators held a better status in 2014 in comparison to the year 2000. These results represent the practical impact of protection and management in the region. However, the decrease in the standardized value of the three mentioned indicators declares the lack of attention to the exceptions of the PA and the increasing trend of land tenure in the study area.
Location changes in the ESI of a particular year have a close relation to the land shape. In the under study area, as we move from the flat areas to the heights, the ESI increases. Studying the categorized map of the sensitivity of the study area in 2014 indicated that 95 percent of the study area is located in medium and high sensitivity categories. The living locations of urials wild sheep in this map indicated that this species had chosen areas with medium and low sensitivity where are hilly with high ecological security to live.
Three indicators, including annual precipitation, cover vegetation status, and soil brightness, were chosen as the appropriate indicators to be utilized in the EWS of Darmiyan PA. While monitoring, the warning areas in the study area were determined by studying the status of these three indicators. This EWS was utilized in the study area in 2014. Based on the results, some parts of south-west and east of the area have been subject to danger. After determining the vulnerable areas, the operation accuracy of the proposed EWS was assessed using the field visit. This system had good accuracy. With the presented approach, one can have regular monitoring of the critical and inaccessible areas. This approach is practical with its minimum cost in optimum and oriented managing of Pas even though the choice of general and useful indicators in ecological security remains the most crucial part of this approach. In this research, one can see a reduction in managing expenses through the use of technology. The effective indicators on the ecological security of an area with a semi-arid climate are proposed. This research helps the ecosystem existence of the areas where they are the habitat to international species. In this study, the minimum number of indicators was used for a warning system even though the necessity for research on a warning system with more indicators and comparison with the presented results remains considerable. We believe this research is an appropriate starting point for discussion on the use of the warning system for essential and inaccessible areas of all around the world.

Because of high reliance of Iranian economy to oil revenues, it is affected by the price volatility of the oil market. Therefore, the forecast of the oil price movement is very important at least in two aspects including determining the correct oil price in the government budget and also for controlling the high price volatility for macroeconomic policy makers. Based on the importance of forecasting oil price movement, the purpose of this paper is to present an Early Warning System (EWS) for high oil price volatility in the OPEC crude oil market. This system, by forecasting the probability of staying in high volatility oil price in future periods, give a proper view of the trend of oil prices to policy makers. For this purpose, in the first step, by a Markov Switching GARCH model, the oil price trend and its volatility have been modeled and estimated during the period of 2010-2016. Then, using this model, the transition probability matrix, which involves the probability of staying in the high-volatility and low-volatility regimes, and the probability of switching between the regimes, has been obtained. Based on this matrix, the probability of being in a low-volatility and high-volatility crude oil price have been forecasted. so the policymakers and activists in the oil market can make better decisions to avoid of damaging effects of high oil price volatility.