پژوهشنامه اقتصادی
پیاپی 71 (زمستان 1397)

Supportive policies that lead to significant relative price changes have widespread impact on income distribution that cannot be considered by adjusting expenditures with the consumer price index. While households have different consumption patterns in different income deciles, the Consumer Price Index (CPI) measures changes in prices based on the pattern of consumption in the average-income households. To overcome the issue, this paper examines the impact of relative price changes on distribution of real income (real expenditure) based on the HSPI Index, which is calculated using the weights of goods in each household’s basket. The period under study is 2007-2015. To measure inequality, the Gini coefficient is used based on Ogwang method. The results show that in periods that price of foods increase more than other categories, income inequality is the more when calculated, respectively, based on Household Specific Price Index (HSPI) and Consumer Price Index (CPI) than Gini coefficient based on nominal expenditures. Because of higher share of foods in consumption basket of low-income households, higher relative price of this category leads to worsening of income distribution and loss of welfare for low-income class.

Housing price swings have always been under the spotlight for policy-makers and academics. Financial accelerator mechanism (developed by Bernanke and Gertler, 1999) can provide some explanation to these fluctuations. With focusing on the concept of financial accelerator, this paper sheds light on the long- and short-run correlation of housing prices and credit in Iran. We applied a Structural Vector Error Correction Model (SVECM) to housing and credit market over period 1988q2-2015q1. Our findings confirm the existence of a cointegrated relationship between credit and housing prices. In a long-run perspective, the causation goes from credit to housing prices. However, in the short-run we find an existence of contemporaneous bi-directional dependence between housing prices and credit. In general, we find the evidence of housing collateral effect in housing and credit markets in Iran. However, this role is small and limited compared to the same role in countries with developed financial and mortgage markets.

Research and development expenditure is a key indicator of resources allocated to science and technological activities, so knowledge about its features and factors underlying firm decision about R&D expenditures have great importance. According to international comparisons, R&D intensity in Iranian manufacturing firms is low compared to developing countries and emerging-market economies. Therefore, the aim of the paper is to analyze factors determining R&D intensity in Iranian manufacturing firms. Using data covering 1995-2014 based on two-digit ISIC data of Iranian manufacturing firms, we have developed a panel-data model to analyze R&D intensity. Our results show that high-tech companies with higher ratio of human resources with tertiary education are more open to foreign trade, have greater size and also have higher ratio of investment to value-added. The results show that profitability of high-tech companies and their value-added growth have no significant effect on their decision to make R&D activities. In mid- and low-technology companies, none of explanatory variables has significant effect on R&D intensity. This shows that these industries in Iran are not developed enough to be sensitive about R&D in their strategies. Based on these results and considering very different variables that affect decisions of companies about R&D, it is necessary to implement different policies for industries with different level of technology.

In this paper, an optimal investment portfolio including securities of four sectors: financial, chemical, pharmaceutical and automotive is estimated. Various types of Copula models are used to study the structure of asset co-dependency. Different types of GARCH models are used to explain volatility of asset returns, and Extreme Value theory is used to model the tails of the distribution. Also, expected shortfall model is used to calculate asset portfolio risk. The results of this research show that securities of chemical sector have the highest weight in optimal investment model. Also, in order to achieve higher returns (and of course, with higher risk tolerance), we can increase the weight of the pharmaceutical sector in the asset portfolio. The automotive sector does not have a significant weight in any of investment portfolios due to high level of fluctuations. The results of the Sharpe test also showed that two types of Copula models, Frank and Gumbel, were more effective in diversifying investment portfolios.

In international economics literature, there is a great emphasis on importance of exports on economic development and growth. Because of growth in international trade, all countries try to activate this engine of economy by implementing proper policies. The experience of emerging economies has shown that countries with high intensity of industrial exports have experienced faster economic growth than others. Thus, focusing on industrial export and studying factors which affect export intensity are very important. So, in this study we investigate the impact of firm- and industry-level characteristics on export intensity. For this purpose, the data for Iranian manufacturing firms during 2007 to 2013 have been used. The results of empirical model estimated by using Dynamic Panel-Data approach and GMM Estimator show that export intensity of firms is positively affected by research and development intensity, capital intensity, labor productivity of firms and export intensity of industry while firm size, industry concentration and industry-level labor productivity has negative and significant effect on export intensity.

Justice is known as one of the most important principles of any economic system and pursuing other objectives such as efficiency and economic growth should go along with achieving justice. In Islamic economics, redistributive justice as a kind of justice can be achieved through obligatory and voluntary charities or through government subsidies. In this study, we generalize two-period overlapping generations model by entering the Islamic guidelines for redistribution in this model and examine the economic impact of redistributive behavior by analyzing the model in Islamic economics framework. The results show that an increase in redistributive behavior that emerges in the form of in Infaq (Transfer payment), has a positive impact on saving and capital accumulation and therefore is consistent with economic growth. So, one optimal approach for implementation of redistributive justice is to encourage people to Infaq and voluntary donations.

The aim of this paper is to present a hybrid model to evaluate performance of loan portfolio of banking system regarding loan repayment status and to forecast credit status of loan applicants. At first stage, we have taken credit granting management approach in order to cluster and rank 100,224 loans granted by Karafarini Omid Fund. All the data on the loans granted to clients was extracted from core banking software of the Fund. Because of having access to this valuable and valid dataset, qualitative data collection methods are not used. In the first section of paper, a type of robust principal component analysis (ROBPCA) was utilized to classify the clients. Then, the eigenvector derived from ROBPCA was used as input to a two-step K-means clustering algorithm. Then, to propose a model to forecast credit status of applicants prior to granting loans, support vector machine (SVM) and artificial genetic neural networks were used. The results obtained from the applicants’ credit status forecasting showed that the model based on the artificial genetic neural networks with the mean-square error of 0.23 and %78 coefficient of determination leads to more accurate forecasting than support vector machine. Therefore, the proposed model for forecasting the applicants’ credit status can predict their performance with relative accurately. A new method in the form of data mining software provides credit institutions with the possibility of predicting applicants’ credit regarding loan repayments.

The main goal of every development plan is to achieve economic growth and mass production with considerations for the needs of economy and optimal utilization of resources and capital in the society. Urbanization is one of the most important aspects of the modern society, which embodies significant factors that can lead to economic growth. Urbanization is the relationship between population, employment, migration, physical construction and human environment, and its development at any time and in any geographical area is influenced by national and international conditions. Today, the effect of foreign direct investment on economic growth has been confirmed by theories and empirical evidence. This study examines the contemporaneous effects of urbanization and foreign direct investment on economic growth in Iranian provinces over period 2006-2015 by using Generalized Moment Method (GMM). Our results show that foreign direct investment, government size, capital stock and human capital index have a positive impact on economic growth in Iranian provinces. However, the effect of urbanization intensity on economic growth has been found to be negative.

First studies in inflation forecasting were mostly based on traditional Philips curve in which the relation between inflation and unemployment is studied. However, after several decades and especially after the Lucas criticism, Philips curve faced great takeovers. The new Philips curve ties real and expected inflation, not to unemployment rate but to a scale of the marginal cost. Since in the original form of Philips curve, marginal cost stimulates inflation, it is difficult to formulate models that are effective in predicting inflation. Therefore, using TVP-DMA model, which has the ability to fix these deficiencies, we try to improve predictability of inflation in Iranian economy. An independent variable in conventional models can be either significant or insignificant while in TVP-DMA model, it may be significant during a period of time and insignificant in rest of the times. Therefore, this approach lets us to determine the periods in which an independent variable is significant and when it is not. In this study, we use seasonal data during the period 1991-2015. The results based on outputs of the TVP, DMS, and DMA models show that, out of 100 time periods under study, the liquidity growth rate in 19, economic growth rate in 7, unemployment in 8, exchange rate growth in 31, changes in the bank deposit rate in 14, oil revenues growth rate in 15, inflation uncertainty in 14 and the budget deficit growth rate in 4 periods have significant effect on inflation. Based on these results, it can be stated that exchange rate growth, liquidity growth and oil revenues growth rate are the most important indicators influencing inflation rate in Iran.

This paper aims to study the role of gold, stock and foreign currency as hedges against inflation in Iran based on monthly data over period 2000-2016 by using a novel approach with nonlinear autoregressive distributed lags (NARDL). To achieve this goal, the effect of positive and negative inflation shocks  on price of these assets is estimated separately. The results show that all assets (foreign currency, gold and stock) are hedges against inflation in Iranian economy. As inflation rate increases, the prices of these assets also increase, but the magnitude and type of their hedge against inflation vary in different time horizons. The results show that the effects of both positive and negative inflation shocks on gold price are symmetric in the short-run, but in the long run, the effect of positive inflation shocks on gold price are more than negative shocks. The results of the inflationary coverage of foreign currency show that the effects of the positive and negative inflation shocks on it are asymmetric in the short-run and long-run; while these effects are symmetric for stocks in both short- and long-term. Furthermore, stocks is a proper hedge against inflation in the long run and not only it maintains purchasing power, but also it increases value of investors’ assets. Moreover, the inflationary coverage of foreign currency and gold are the same and less than rising inflation, but exchange rate is a hedge in the short-run and gold plays the role of hedge against inflation in the long-run.