فصلنامه اقتصاد مقداری
سال هفدهم شماره 1 (پیاپی 64، بهار 1399)

Given the importance of economic growth in every country’s development, the effective factors contributing to the economic growth are considered in different schools of economy. Institutionalist theory has emphasized on removing institutional obstacles so as to accelerate the economic growth. According to the literature, there are two levels of institutions affecting the economic performance. The first level includes macro institutions affecting governments and other key players in the economy, while the second level includes micro institutions which facilitate business environment by reducing the transaction cost. According to the institutionalist theory, micro institutions are influenced by the macro institutions. However, some studies have reported that the relation between micro and macro institutions can be different in developing and developed countries. Accordingly, the present study was intended to examine the impact of various institutional factors on the economic growth and institutional reform priority in the Southwest Asian countries based on the institutionalist theory, and to compare the results to those of OECD countries during the period 2007-2014. Considering the micro and macro institutional features, good governance indices were used to measure the macro-institutional level. Besides, the ease of doing business was used to measure the micro-institutional level. In turn, the growth calculation was based on GDP per capita of 2011 real price. To analyze the relationship between the growth and institutional indeces first a model in the form of institutional theory was defined and estimated via dynamic panel data using GMM approach. After the model estimation, to see the interactional effect of micro and macro institutional effects and to prioritize the institutional reforms in the Southwest Asian countries and OECD, long term relation analysis between micro and macro institutions was done according to Johansson's co-integration method. Trace test was, in turn, used to determine the number of co-integration vectors. After determining the number of long term relation between the factors, factor cuasility direction was specified by error correction models. The results showed that the micro and macro institutional improvement had positive effect on the economic growth of both groups of countries. However, the impact of macro level institutional reform on the OECD economic growth was more than that of the Southwest Asian countries. Moreover, the causality and long term relation analysis using Johansson's cointegration method and error correction models showed that in OECD countries, according to the institutionalist theory, long term and causality relations were from the macro institutions toward micro ones. However, in the Southwest Asian countries the interactional relation between micro and macro institutions was not significant. These findings implied that among OECD countries, the macro institutions provided the requirements for the government and key players to do reforms at micro institutional level, while in the Southwest Asian countries there was no rule or framework to oblige the government and key players to reduce corruption, establish economic stability, and protect people's property rights. This is actually why governments and other key players in the economy preferably change micro institutions without considering the framework and rules governing them. In addition, analyzing the institutional indices for the Southwest Asian countries showed that there was a tendency to have a long term relationship with some of the macroeconomic components, including the ‘Quality of Laws and Regulations’ and the ‘Business Index’ for the period under review. This suggests that institutionalist theory in Southwest Asian countries would also apply if macro-institutions were strengthened. According to the above results, the good economic performance of the Southwest Asian countries like Iran requires attention and emphasis on the principles binding the government and key economic players to their duties. In effect, such principles can be pronounced in the country's basic laws and policies of development programs so as to strengthen the partnership of public and private sectors as the major institutions in these countries.

Multivariate time series data are often modeled using vector autoregressive moving average (VARMA) model. However, the presence of outliers can violate the stationary assumption and may lead to wrong modeling, biased estimation of parameters and inaccurate prediction. Therefore, a new robust simulation-based estimation for parameters of the VARMA model was introduced in this research. The simulation-based estimation as a kind of indirect estimation uses the estimation of the simple vector autoregressive (VAR) model with large order rather than the estimation of the complex VARMA model. To do this, the VAR model was first fitted on observation. Then, the data from different VARMA models were simulated and on each simulated data, the VAR model was fitted. The simulation-based method is based on the distance between the estimation of the VAR model on the simulation and observation data. The values of the parameters that use the VARMA model in the simulation and provide the minimum distance are indeed the estimates of the VARMA model parameters. Thus, if the estimates of VAR model are solid, we expect the VARMA model to be stable as well. For this reason, the robust BMM method of Muler and Yohai (2013) was used to estimate the VAR model. The simulation-based estimator has asymptotic normality and consistency properties. In addition, the simulation study in the data without outliers showed that the ratio of the mean square error of this estimator to the conditional maximum likelihood estimator was between 0.6 and 0.7 which is allowable for a robust estimator. Besides, when the 0.05 data is contaminated by the outliers, the mean square error of the robust simulation-based estimator is lower than the conditional maximum likelihood estimator.As a real example, the gold and dollar price data in the Tehran free market were collected and investigated weekly in the period 2013-2018. It should be noted that gold and dollar prices are often affected by economic, political, and war crises which, in turn, create outliers. Thus, a robust method was used to reduce the bad effects of these outliers to estimate the model correctly. As gold and dollar prices are highly correlated, the VARMA model can be used to predict the gold and dollar interactions. Fitting the VARMA (1, 1) model to these data shows that the variance of the gold price error in the robust model to the conditional maximum likelihood reduced by 38%. However, the variance of dollar error in the robust model to the maximum conditional likelihood reduced by 30%. In other words, using robust method leads to better predictions with less variance. According to the fitted vector model, the gold price forecast for each week was obtained using the gold price of the previous week and the gold and dollar errors of the previous week. Besides, a forecast of the dollar for each week was obtained by the dollar and dollar error of the previous week.

Analyzing the effects of investor confidence on the mechanism of monetary policy transition and economic growth without Crude oil exports in Iran:  The MGARCH approach is an important factor of the capital market and the investors. The main goal of every investor is, thus, to launch their investment in order to get a maximum profit from the output of their investment. To encourage the investors to invest in the financial assets, these sort of assets must be greater than the other options (Mehrani & Bahramfar, 2004). The implementation of efficient market economy theory, which has received considerable attention by governors in the recent years, has been able to partially increase the capital market's share of money in financing firms. In effect, the qualitative and quantitative development of the capital market and the Islamic financial affairs as the main sources of financing in the last two decades, the formulation of the accounting and auditing standards required for the economic entities and other corrective actions have turned the exchange markets to one of the best options for the investment. According to the latest statistics, more than ten million Iranians are investing part of their resources in the exchange market. Therefore, this study was intended to investigate the effect of financial sustainability on monetary policy transfer mechanisms. In effect, the correlation between investor confidence in the markets, money growth and macroeconomic growth without oil was, indeed, analyzed along with their fluctuations.  The practical research in the developed markets has shown that the change in macroeconomic variables, stock prices will also change, therefore it is expected that there is a strong relationship between the stock prices and macroeconomic variables. The stock price index is, indeed, the most important factor influencing investor decision making in the stock market; therefore we need to be aware of the factors influencing stock prices. The process of monetary policy transfer begins from the asset market because the cost of information and transaction for the most assets are lower than the costs of changing the production or adjusting the consumption or investment of durable goods, especially when there is uncertainty about policies whether they are permanent or temporary. As the asset market responds very quickly, therefore assets prices play an important role in the money transfer mechanism. Using the MGARCH estimator, this study investigated the relationship between investors' confidence ratios, real money growth, and economic activity without crude oil exports and their fluctuations.   Using this estimator enables the estimation of uncertainties so as to achieve perfectly consistent criteria. In this study, the PEG index of price-earnings to earnings growth for a variable of investor confidence, which is a better indicator than PE, was calculated. It should be considered that the potential growth of the companies can reflect the life of the investors as it uses several revenue generating factors such as brand, human capital and expectations and barriers to entry.  Thus, this study investigated the effect of financial sustainability on the monetary policy transfer mechanisms in Iran. Indeed, the correlation between investor confidence in markets, money growth and economic growth, without Iranian crude exports, was analyzed alongside their volatilities. In particular, the heterogeneity of error variances in an MGARCH framework was used to obtain the estimated uncertainty criteria. In this paper, seasonal data and the variables from the beginning of 1991 to the end of 2016 were considered. The results showed that there was a positive correlation between macroeconomic volatility without oil and PEG investor confidence. The results showed that M2 cash flow fluctuation negatively affected PEG. The results also indicated a bilateral Grange impact between macroeconomic volatility without crude oil exports and liquidity volume. The other results of the study are as follows: Monetary policy can only directly affect investor confidence and its fluctuations in a long term. There is no significant Granger relationship between macroeconomic without oil and GDP growth.  - The results showed the negative impact of macroeconomic uncertainty on oil noilGDP growth and the cause of the negative effect between production growth and its medium- and long-term volatility.  - If monetary policy can directly control the capital market and its sustainability, given the correlation between the noilGDP and its fluctuations, the production consolidation and asset prices seem to be sufficient goals. Obviously, having a smooth economic cycle can relatively stabilize the market. However, the analysis showed the importance of monetary policy, which reflects the strong negative correlation between currency fluctuations and macroeconomic stability without oil and assets.

The usual methods of measuring regional inequalities can not reflect the internal changes of the country in terms of displacement in different development groups. Thus, the indicators of inequalities are not effective in demonstrating the dynamics of the distribution of inequalities. For this reason, this paper examines the dynamics of the regional inertial transport in the country during the period of 2006-2016 using the CIRD multidimensional index and stochastic kernel density method. To that end, 25 indicators were selected in five dimensions including macroeconomic conditions (MEI), science and innovation (SII), environmental sustainability (ESI), human capital (HCI) and public facilities (PFI). In turn, a two-stage Principal Component Analysis (PCA) methodology was developed to create a composite index of inequality. Then, in the second stage, using a nonparametric analytical approach to internal distribution dynamics and a stochastic kernel density method, the convergence hypothesis of the CIRD index of the Iranian provinces was tested. Afterwards, based on the ergodic density, the long-run equilibrium was shown. At this stage, to adopt the most accurate regional policies, the distribution dynamics and the process of convergence or divergence of the Iranian provinces for each of the five dimensions in three successive periods (2006 and 2016) were studied separately. According to the results of the first stage in 2006, the highest level of development was related to Tehran province, followed by Semnan, Yazd and Markazi provinces. In turn, Sistan and Baluchestan province had the lowest level of development. In 2016, the highest level of development and the highest positive inequality were in Tehran, Yazd, Semnan and Isfahan provinces and the lowest level of development was in Sistan and Baluchestan, Chaharmahal and Bakhtiari, North Khorasan and Kurdistan provinces. The results showed that the central provinces of the country were at the highest level of development due to the effects of Tehran's knowledge spillover, while the country's lower provinces were at the lowest level of development. The main reason for this may be due to the lack of access to the markets in the border provinces. Based on the results of the second stage, which examines the dynamics of regional inequality transmission in the country during 2006-2016, the first year (i.e., 2006) was not multifaceted and according to the kernel density graph, the CIRD index of about 70% of the provinces was between -1.1 and -0.1. The rest of the sequence on the right was distributed at a level higher than -0.1. In the kernel distribution, a convergence process was observed. One peak was about 1 and the other about 3, but the main peak remains at -0.6 with about 55 percent of the provinces. In the second year (i.e., 2011), according to the kernel density diagram, the curve clearly showed the pattern of the triplet nature and there was a small but a clear increasing trend in the distribution of this year relative to 2006. In this year, the previous uniform distribution is divided into two parts at the highest level, one peak at about 1 and the other at about 3. However, the main peak remains the same at -0.6 with approximately 55% of the remaining provinces. In 2016, the multidimensional pattern remained constant and there was no mobility in the lower level groups. On the contrary, at the higher level, the CIRD index accounted for about 45% of the provinces at about -0.4. This year clearly faces the twin density pattern, indicating that the provincial provinces tend to be closely related to each other in terms of development. This way, the provincial provinces are low in terms of development. The findings tend to be -0.6 and the value of the more developed CIRD index tends to be about 0.4. These three curves show that the provinces tend to converge toward several different CIRDs in terms of development. Moreover, according to the distribution dynamics results, the provinces of Iran followed the single-density pattern in 2006. However, in 2016 they followed the double-peak density pattern in low and moderate inequality index levels as well as in the development index. In conclusion, the country diverged during the years 2006 to 2016.

The country's monetary authorities are trying to adapt the money supply to the country's goals in order to achieve such macroeconomic goals as achieving higher economic growth, stabilizing prices, balancing payments and controlling the volume of money. Therefore, a careful evaluation of the monetary policy transfer mechanism seems necessary to help us better understand how monetary measures affect production and price levels.  In this regard, the exchange rate as one of the key variables of the economy can be very decisive in the transmission of monetary policy effects. In other words, the exchange rate is an important indicator of the economy that, due to its interaction with other domestic and foreign variables, affects both domestic and foreign economic developments as well as the domestic economic variables. For this reason, the role of the exchange rate channel in the monetary transmission mechanism in the Iranian economy as an important issue has been very pronounced in recent years. This paper was, thus, intended to study the role of the exchange rate channel in transferring monetary policy effects.  However, it should be noted that most economic series undergo changes in trends and behaviors for various reasons, including structural economic changes or changes in the behavior of economic agents over time. Accordingly, time series changes can change the relationships between variables over time and non-linear monetary policy transfer seems very likely. Nonlinear monetary policy transfer means changing how monetary changes affect production and price levels. The purpose of this study was, thus, to study the mechanism of nonlinear transfer of monetary policy from the exchange rate channel, so as to examine how the exchange rate is affected by monetary changes, and how the exchange rate affects the production and price levels over different periods. In this regard, MSVAR method was used in this study to investigate the role of exchange rate channel in the non-linear monetary policy transfer mechanism, which has great potentials for incorporating structural changes. To that end, consumer Price Index, Currency Base Currency Volume were, thus, used during the seasons 1990Q1 to 2016Q4.  The results confirmed the theory of polion in the Iranian economy. This way, money in two regimes of zero (years after 2006) and regime one (years before 2006) was effective on the production in the short run and had no effect on the production in the long run. The most important distinction between the seasons of the zero regime and the regime of a real monetary base growth remained constant. In effect, the growth of the real monetary base balance was about eight times higher than that of the one in the zero regime compared to the one in the previous year. However, comparing the effects of money on the production in these two regimes suggests that money has had similar effects on production. Therefore, more money growth in the zero regime could not have a greater impact on the production than regime one. On the other hand, examining the effects of money on the price level suggests that in the long run under the zero-growth regime, money has had larger and more lasting effects on prices. The estimated results regarding the role of the exchange rate channel in the money transfer mechanism suggest that increasing money from the exchange rate channel in the zero regime did not play a role in generating money, whereas in regime one, the exchange rate channel had a significant share in it. Indeed, there has been a transfer of money over production, and money changes through this channel have reduced production. On the other hand, the share of the exchange rate channel in transferring money to prices in regime zero (high money growth) is higher and more stable than regime one (low money growth). In other words, in the zero regime, the increase of the currency will increase the exchange rate further and the exchange rate will have more lasting effects on the price level. According to the findings, it is recommended that the central bank restrict the growth of money supply in order to control inflation. This is because with the increase in money growth, the impact of money on production has not changed and only in the long run will it lead to higher prices. On the other hand, because the exchange rate channel in both regimes has a negative role in transferring money over production, it is recommended that the central bank, in order to increase production by controlling other factors affecting the exchange rate, prevent further currency jumps and growth so as to limit its negative effects on production.

According to studies, a financial market based on the power law as According to the literature, a financial market based on the power law as a dynamic system can reach a critical point (i.e., a financial crisis) and even go up to the infinity. In this study, four stock exchanges in Tehran, Moscow, Abu Dhabi, and New York were selected based on the availability of credible statistics and the observation of important economic areas in the global geography. Two questions were then formulated as follows. Firstly, did the four markets face crisis and how much was the magnitude of each one? Secondly, if the crisis affected the markets in 2007- 2009, how much was the value-at-risk and the expected shortfall in the crisis? The results indicated that financial crises occurred in the four markets based on the power law and Wakeby distributions and the magnitude of each one was also determined. It was also found that the financial crisis in 2007- 2009 affected all four stock exchanges. The crises that occurred in the Tehran Stock Exchange, respectively included: the first privatization impact of the stock exchange in 2003, the United Nations Security Council's sanctions in 2010, the devaluation of the national currency in 2012, the global financial crisis in 2007, the implementation of the nuclear deal between Iran and the Group 5+1 in 2016, the decline in oil prices in 2014, the nuclear negotiations in 2015, the first nuclear negotiations in 2013, the beginning of the Second Gulf War in 2003, the Russia conflict in 2013 and the Lausanne nuclear deal in 2015. The four crashes in the Russia’s market, respectively were: the global financial crisis in 2007-2009, the economic crisis in Asia in 1997, the Russian financial crisis in 1998 and the Russian Ruble collapse in 2014-2016. Two financial earthquakes occurred in the United Arab Emirates’ market, respectively included: the global financial crisis in 2007-2009 and the effects of the decline in oil prices in 2014. In turn, the crises affected the United States’ stock market were the global financial crisis in 2007, the crash in 1987, the stock markets fall in 2011, the stock market downturn in 2002, the economic crisis in Asia in 1997, the Russian financial crisis in 1998, the September 11 attacks in 2001, the spring in 2001, the flash crash in 2010, the technology bubble collapse in 2000, the stock market selloff in 2015-2016, respectively. Moreover, the worst losses in each market were determined by the value-at-risk and the expected shortfall in the recent global crisis based on the duration. The value-at-risk and the expected shortfall represented the worst possible loss at the end of the next trading day at 95% and 99% confidence levels. The goodness-of-fit statistic (KS) showed that GPD fitted well with the returns up to the given thresholds. Besides, the results of the estimation of value at risk during the period of financial crisis in 2009-2009 showed that the worst daily loss will not exceed 1.1%, 16.1%, 4.2% and 9.1% in the next trading day in 95% of the time in the Iran’s, Russia’s, United Arab Emirates’ and United States’ markets, respectively. Further, it will not exceed 2.5%, 26.3%, 6.9% and 11% in the next trading day in 99% of the time in the markets. Based on the estimation of the expected shortfall, the worst daily expected loss will not exceed 2.3%, 22.8%, 5.9% and 10.2% in the next trading day in 95% of the time. In addition, the worst daily expected loss will not exceed 5.1%, 35.7%, 8.9% and 11% in the next trading day in 99% of the time in the four markets, respectively. It was also found that in the 2007-2009 Russia’s and United States’ stock markets experienced the greatest loss compared to the crash in 1998. Indeed, the financial shocks can lead to relatively great values of the worst expected loss; however their severity is different in each market studied. The results also revealed that the financial crisis with the highest magnitude in 2007- 2009 created a large potential loss and damage in all markets.