فصلنامه اقتصاد مقداری
سال نوزدهم شماره 1 (پیاپی 72، بهار 1401)

Investigating the link between monetary policy and stock returns has been very important for monetary policymakers and financial market investors to employ appropriate monetary policy and make the right investment decisions. Moreover, it has been of great interest to economists whether monetary policy has the same sort of effects in bull and bear stock market cycles. If a monetary policy has asymmetric impacts, policy makers should consider stock market cycles while implementing it. The objective of the present study is to investigate the reaction of stock returns to monetary policy and asymmetries over bull and bear cycles in Iran. Moreover, the impact of monetary policy on the switching probabilities between bull and bear regimes is also examined. The theoretical framework for explaining the asymmetries over stock market cycles can be described by the models with financial restrictions. According to these models, financial restrictions are more in bear cycles because of lower net worth in these periods. The lower the net worth, the greater the external finance premium should be. Higher external finance premium create a financial propagation mechanism which amplifies the interest rate effects of monetary policy (Garcia and Schaller, 2002; Chen, 2007).

To examine asymmetries we employ Markov-switching (MS) models developed by Hamilton (1989). Unlike linear models this approach is nonlinear and can handle asymmetries. Besides, Hamilton algorithm endogenously determines bull and bear stock market cycles based on the data. In this study Hamilton (1989) MS model is modified to allow monetary policy to affect stock returns. Moreover, basic MS model is extended to a time-varying transition probability MS model (TVTP-MS) to allow the probability of switching between regimes depending on monetary policy.

According to the findings MS models identify two regimes with different means and variances conventionally labelled as bull and bear. Average expected durations of bull and bear regimes show that both regimes are highly persistent. They persists on average around 10 to 12 quarters. The results of MS models show that monetary policy significantly affect stock returns only in bear cycles. When a monetary policy is measured by real M2, it has a positive impact on stock returns. However, when it is measured by real interest rate it negatively affects stock returns. In other words, an increase in real M2 raises stock returns while increasing real interest rate reduces returns.To measure the impact of monetary policy on the dynamics of switching between regimes we estimate a TVTP-MS model. The results indicate that an expansionary monetary policy raises the probability of remaining in a bull regime. Furthermore, an expansionary monetary policy reduces the probability of switching from a bull regime to a bear one. In addition, an expansionary monetary policy decreases the probability of being trapped in a bear market while it can increase the probability of switching from a bear market to a bull one.

The results of a modified MS model indicate that monetary policy significantly affect stock returns only in bear cycles. More specifically, increase in real M2 raises stock returns while increasing real interest rate reduce returns for both nominal and real returns in bear regimes. These findings are in line with the prediction of the models with financial restrictions. Finally, Empirical results from estimating TVTP-MS models suggest that an expansionary monetary policy raises the probability of remaining in a bull regime while reduces the probability of being trapped in a bear regime.As a policy implication, monetary policy makers should consider stock market cycles in implementing monetary policies. Especially in bear market periods implementing an expansionary monetary policy may lessen the probability of remaining in bear markets and will raise the probability of switching from a bear regime to a bull one. Moreover, stock market investors should consider that the impact of monetary policy on stock returns may depend on the phase of stock market.

The commodity terms of trade shocks are important to explain the macroeconomic fluctuations of oil-exporting countries. Oil price shocks are the main source of terms of trade variability in oil-exporting countries. Given the significant effects of terms of trade fluctuations on domestic macroeconomic variables, understanding the transmission and propagation of terms of trade fluctuations is crucial in the design and conduct of macroeconomic policies in oil-exporting countries. An appropriate monetary policy can help to stabilize these shocks.This study evaluates three alternative monetary policy regimes’ responses to commodity terms of trade shock and export sector productivity shock using a New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model. In this study, the model has been developed based on Hove et al. (2015), Monacelli (2005) and Cashin et al. (2004) for the economy of Iran. This theoretical framework characterizes a small open oil-exporting economy by two domestic sectors: traded sector and the non-traded sector. In the non-traded sector, prices are sticky according to Calvo`s (1983). There is one external sector which is the rest of the world. Also, incomplete exchange rate pass-through is introduced via nominal rigidities on import prices. This model has been developed to evaluate the response of different monetary policy regimes to commodity terms of trade shocks and export productivity shocks. Based on empirical evidence such as Shajari et al (2015), pass-through is assumed to be incomplete in the model.Since oil exports account for a high percentage of export earnings and finance a significant portion of government spending in Iran, the analysis of different monetary policy responses to commodity terms of trade shocks in an oil-exporting country, like Iran, must be important.  This study aims at investigating the dynamic effects of commodity terms of trade shocks and evaluating the performance and the stabilization properties of various simple monetary policy rules for oil-dependent economies. Three alternative monetary policy rules have been considered: CPI inflation targeting (CIT) rule, non-traded inflation targeting (NTIT) rule, and exchange rate targeting (ET) rule. Different monetary policy rules are assessed based on the degree to which they minimize the volatility of selected macroeconomic variables as reflected by their impulse response functions.

The model is calibrated to match the key features of the Iran economy using data for the period 1991: Q1 to 2017: Q1. The series of Oil production and Non-oil production is obtained from the “Statistical Centre of Iran” The series of Interest rate and oil prices are obtained from the “Central Bank of Iran”. The series of production in the oreign intermediate sector and foreign intermediate good price are obtained from the “Archival Federal Reserve Economic Data”[1]. Other parameters were obtained from previous studies on the Iran economy and business cycle literature in the world. The model is calibrated to the Iran economy. The model is solved numerically and the parameter choices for the model are summarized in Table1.

The comparison of responses under different monetary policy regimes shows that CPI inflation targeting is superior to the NTIT and ET targeting when commodity terms of trade shock happen. For export productivity shock, the performance of the CIT rule is better than other examining monetary policy rules. Also, the real exchange rate, which is defined as a function of commodity terms of trade and productivity differentials, makes it possible to examine the role of export productivity shock on macroeconomic variations and test the existence of Balassa- Samuelson effect. Impulse responses to commodity terms of trade shock show increasing in total output and CPI inflation and decreasing in consumption and nominal exchange rate under three policy rules. The analysis also displays that commodity terms of trade shock induce lower responses of macroeconomic variables under CPI inflation targeting than under non-traded inflation targeting and exchange rate targeting. Under the export sector productivity shock, exported output increases while non-traded output decreases, possibly reflecting the symptoms of the Dutch disease. On the other hand, the dynamic responses of selected macroeconomic variables suggest the presence of the Balassa-Samuelson effect where an increase in productivity in the traded sector appreciates the real exchange rate and increases the prices of non-tradable goods through wage equalizations.

overall, when the economy is experiencing commodity terms of trade shocks or exported productivity shocks, CPI inflation targeting is relatively better than exchange rate targeting and non-traded inflation targeting in macroeconomic stabilization.

Exchange rate is a variable transferring international economic shocks to domestic economy. In countries like Iran which are experiencing a high inflation and whose GDP as well as consumption expenditures are mostly dependent on imports and foreign capital flows, exchange rate changes and its effects need to be carefully monitored by policy makers and economic researchers. Considering the importance of inflation in the theoretical discussions and the high inflation rate in some developing countries, the effect of exchange rate on inflation has attracted economists interested in monetary issues and international economics.Nonlinear behavior in the exchange rate effect on inflation can provide false estimates of exchange rate coefficient when the econometric model is estimated linearly. In such a circumstance, we can accommodate cases when the inflation condition and its rate affect economic factors in response to an exchange rate shock. Indeed, domestic prices may not be sensitive to an exchange rate shock due to a low and stable inflation. However, they may respond wildly to a similar shock when inflation is above some significant thresholds.Although studies have mostly focused on measuring the extent of exchange rate effect on price levels, we believet that investigating the possible existence of one or more thresholds in exchange rate effect is important, because the reaction of monetary policymakers may somehow depend on the extent of exchange rate effect with respect to one (or more) threshold value(s). For instance, policymakers might not take care of the exchange rate fluctuations below a certain level, but as soon as it crosses such a level, they believe it damages the economy and the country welfare, thus triggering some intervention in the currency market.

A reason for the non-linear response of inflation is the non-linear nature of exchange rate trend. In fact, geometrically, among all the time paths of exchange rate, the probability of a linear path between the two time points is very weak. The effect consequence of all determinants of the exchange rate is displayed in its changes. Here are two important points to note. First, the cross-effects of exchange rate determinants can influence the impact of each determinant. Second, the importance of currency, especially in developing countries, and its key role between the foreign exchange and financial markets, has made the exchange rate an intelligent variable, which corrects mistakes at the next rate through the learning process. Hence, the course of exchange rate over time is expected to be nonlinear.The purpose of the present paper is to the test a nonlinear model estimating the response of inflation to real effective exchange rate in Iran. In order to examine threshold effects of exchange rate on inflation in Iran, following Posedel & Tica (2009), pattern was used:where inflation π is a function of the Real Effective Exchange Rate (REER). The variable  is a dummy variable:  if the REER () is equal or bigger than the threshold () and  if the REER () is smaller than threshold ().

Finding based on time series data for the period 1971-2017 and Threshold Regression (TR) model indicates that real effective exchange rate of 6160.27 Rials has been applied as a threshold value. In other words, based on the above threshold value, the estimated model shows the exchange rate coefficient has increased somewhat from the first to the second regime.

Considering the fact that preserving the value of the national currency is one of the most important tasks of central banks and to control inflation, it seems necessary to give the due attention to exchange rate and its threshold impacts when planning, designing and implementing monetary and exchange policies. The results of this study suggests a policy guideline, namely, that, in order to limit the damaging effects of inflation on the economy and household welfare, monetary policymakers in Iran must restrain the foreign exchange shocks.

In the present era, banking is one of the most important sectors of the economy, which has led to the expansion of markets and the growth and prosperity of economies in organizing and directing receipts and payments, facilitating trade and commerce. Banks can play a very constructive role in the economy by equipping savings and allocating them to various businesses. Export Development Bank of Iran, as the only Exim Bank of the country, can increase its efficiency by paying low-cost loans to export companies and providing the required working capital, as well as financing investment projects and development projects to increase export capacity. and their competitiveness in global markets will help a lot.Seven criteria for evaluating firm performance are: effectiveness, efficiency, productivity, quality, profitability and Profitability, quality of working life and creativity and innovation.The amount of output produced by the firm using a certain amount of inputs is called productivity. Thus, improving the level of productivity is the result of producing more output using a fixed amount of input or producing a fixed amount of output using less input.

The following steps have been taken in the research for fulfilling the research objectives In the first step, in order to evaluate bank’s performance, the efficiency of various branches was measured using Stochastic Frontier Production Function.  Accordingly, 27 branches with continuous activity during the past three years were selected as sample and their monthly efficiency was estimated. For measuring branches’ efficiency, bank’s expenses were considered as a function of input and output variables and then estimated using Frontier 4 software. finally non-operating and operating incomes, as outputs, and impairment loan, provision of default and branches’ capital, as bank’s inputs, were identified.

As mentioned above, econometric estimation of cost function requires selection of function form. the translog function has been used to experimentally estimate cost inefficiency .also, the model was estimated with different inputs and outputs.the model was also estimated with different inputs and outputs. the general form of the function is as follows.TCit is the total cost of ith bank, Qit is output, Pjit is input price, Uit is cost inefficiency and vit is Statistical error with zero mean and constant variance. ln (TC),α, β are unknown parameters that Should be estimated.

Whereas inputs aproved in the above model for estimating branches’ efficiency include branches’ capital, impairment loans and provision of default branches' facilities, six strategies are suggested for improving branches’ efficiency and developing non-oil exports.a)Increasing the bank's capital continuity over time: The capital of the Export Development Bank is an exogenous variable due to the Being governmental bank, and increasing the bank's capital requires direct government support. In order to provide practical support for the country's exports, the government needs to try to expand the financing capacity of the Export Development Bank over time with the bank's capital.b) Although a slight decrease in the exchange rate of the rial against other currencies leads to an increase in the competitiveness of export goods and services,however, this advantage, through the occurrence of high domestic inflation, leads to an increase in the price of export goods and services and reduces the competitiveness of export products globally and against imported products. Therefore, the central bank should strictly avoid applying monetary policies that result in inflation in the economy.. c)The Central Bank is trying to reduce the restrictions of the rules and regulations related to commercial banks in Exim Bank Iran.d)Reduction and merger of loss-making branches that are unable to cover their costs due to the location and conditions of the branch.e)Increasing the productivity of human and physical capital by holding effective training courses and revising the recruitment and employment of manpowerin a traditional way and using scientific methods to attract talented, specialized, motivated and interested manpower, etc.f) The government should avoid appointing non-bank managers, especially at the level of the bank's board of directors and CEO, who do not have the necessary banking expertise, knowledge and familiarity with the bank's mission, culture, values and vision.

Human Development Index is a composite one to measure three criteria of longevity, access to knowledge and appropriate level of welfare. Since 2011, education, the combination of mean study years for adults (25 years of age and elder) and expected years of studying, life expectancy and income per capita have been considered as components of Human Development Index. Human Development Index is in fact the geometrical mean of these three indexes. This index is annually calculated for countries by the United Nations but not for their states, provinces, cities and regions. Therefore, researchers themselves must calculate this index for provinces for certain purposes.

Lack of such statistics is also a statistic deficit in Iran that has made regional and provincial researches limited and inaccurate. To remove this deficit in this research Khouzestan Human Development Indexes in the years 1996, 2006, 2011 and 2016 have been calculated using the latest formula. It needs to be mentioned that the simulation of Human Development Index is difficult and time consuming. Not paying attention to details can deviate the index. So in order to ensure the precision of calculations, the Human Development of the country has also been calculated and compared with the same index calculated by the United Nations for Iran in order to ensure the authenticity of Human Development Index in Khouzestan. The applied method was a simultaneous behavioral pattern which considers the changes in Human Development Index through components of the United Nations Human Development Index and also simultaneously predicts and includes it in Human Development Index. The estimation method is based on Stock and Watson (1993) Dynamic least squared method that is helpful for predicting variables.

According to results, Khouzestan Human Development Index for the period 1990-2019 can be simulated. The related results are presented in table 1.Table 1. Simulation of Khuzestan Human Development Index results  As table 10 shows, Khouzestan Human Development Index had a slow rising trend up until 2005 but from 2006, there seems to be a jump or structural failure in Human Development Index. However, during 2016-2018 the trend reached a plateau and it seems to have reached its stabilized level. Also, based on this simulation Khouzestsan Human Development Index was in an average level up until 2008 but since 2009 it has reached its high.

To assess this hypothesis, in this research using the new formula Khouzestan Human Development Indexes for the years 1996, 2006, 2011 and 2016 were calculated. The results showed that the indexes of life expectancy and education in Khouzestan were in a worse situation than that of the country but the index of income (taking oil into account) was more than that of the country. The calculation of Khouzestan Human Development Index without oil showed a worse situation than that of the country.Based on results, Kouzestan Human Development Index reached from an average level in 1996 to a high level during 2006 to 2016. This is an acceptable growth. Also, Khouzestan Human Development Index without oil is lower than that of the national index and this represents the worse status of the province compared to the country.The results of simulating Human Development Index show that up until 1389, there was a slight rising trend but from this year on there has been a jump or failure. Moreover, Khouzestan Human Development Index was in an average level up to 1385 but it has reached a high one since 2010.

In 2019, Iran is ranked sixth among world countries and fifth among Asian countries (including Russia) in terms of CO2 emissions. Therefore, studying the CO2 emission elasticity of the production sectors of this country is significant and important for energy and environmental policymakers. What factors influence changes in CO2 emission elasticities? Which are the stimulants and which are the inhibators? The answers to these questions are useful in reducing and controlling CO2 emissions. In the present study, CO2 emission elasticities of production sectors are calculated, and then, with the aim of identifying CO2 emission elasticity stimuli, the changes in CO2 emission elasticities are broken down into different components. The methodology of this research is based on Input-Output analysis and decomposition analysis. The novelty of this paper is to determine and calculate the components of changes in CO2 emission elasticities using SAD. Guo et al. (2018) have presented a method for calculating CO2 emission elasticities based on the Input-Output analysis.

Aim of this paper is to investigate the factors affecting CO2 emission elasticities, CO2 emission demand elasticity and CO2 emission production elasticity. In the first step, the elasticities are calculated and in the second step, changes of elasticities are decomposed. In this study, we have used input-output tables published in 2001 and 2011 by the Statistics Center of Iran. Due to the differences in the sector classification of the input-output tables of 2001 and 2011, we match some production sectors and finally take into account the 65 unified sectors. In order to calculate the CO2 emission of each production sector, we first obtain the total consumption of each energy for each year from the Iranian energy balance sheet, and then we allocate each energy consumption to production sectors and single household sector, according to input-output tables and the share of production sectors and the share of the household sector.                                                                                                                                                                                                                                                             

Findings show that the "Electricity generation, transmission, and distribution" sector has the most elasticity. The "Ghosh inverse matrix" effect is a strong stimulus to the CO2 emission elasticity of the sectors. This result indicates that the change in the share of output i, which is sold to sector j as an intermediate input, is a strong stimulus to increase the elasticity of CO2 emissions. These changes can be due to increased economic activities and the inefficiency of production structure.

"Electricity generation, transmission and distribution" sector should be considered by energy and environmental policy makers due to having the highest amount and changes in CO2 emission elasticity than other sectors. Increasing the share of renewable energy in the energy consumption basket of production sectors, increasing energy efficiency (reducing energy intensity) by replacing new and advanced equipment with old and worn equipment and improving production structure can help reduce the CO2 elasticity and CO2 emission in Iran's production sectors. Finally, due to the high of CO2 emission elasticities in the "Electricity generation, transmission and distribution" sector, future research can focus on this area and suggest solutions to increase production efficiency and energy efficiency. Also, future research can focus on the production structure of production sectors and provide solutions to improve the production structure of Iran's production sectors.