Journal of Money and Economy

Today, social networks are fast and dynamic communication intermediaries that are a vital business tool. This study aims at examining the views of those involved with Facebook stocks so that we can summarize their views to predict the general behavior of this stock and collectively consider possible Facebook stock price movements, and create a more accurate pattern compared to previous patterns. In this study, we have analyzed two statistical samples, the first being a large dataset containing a variety of tweets with an emotional tag. That is, it needed a set that had already been extracted from each individual tweet by a trusted human or machine. Consequently, we have collected posts on Facebook in an eighty-day period. In this study, we used a tagged dataset using Python's programming language and vector-to-word algorithm. The research results show that, we need stock change information, machine learning and sentiment analysis, and on paper we conclude that positive news about a company excites people to have positive opinions about it which in turn results in people encouraging each other to buy and hold stocks. Meanwhile, the opposite trend is also true, but everything will not always be easy and clear, and it is in areas of high complexity and mental uncertainty that the art of using the three elements mentioned above is evident.

IIn recent years, policymakers have generally relied on regulatory policies to address financial stability concerns. However, our understanding of these policies and their efficacy in curbing housing prices is limited. In this paper, we examine the impact of three regulatory tools i.e. LTV (loan to value) ratio, reserve requirement rate (RR), and capital adequacy ratio (CAR) on housing price inflation in Iran for the1993: Q2 to 2017:Q1 period. We investigate whether tightening the policy tools are effective in curbing the housing price inflation by using a vector autoregressive model. The results indicate that all three regulatory policy tools exhibit countercyclical impact on housing inflation, but with varying degrees of influence. While the impact of CAR tightening in curbing housing prices is quite trivial, the impact of RR and LTV tightening are roughly significant.

The merger of banks is one of the methods for reforming the structure of banks, which has attracted Iranian banking policymakers in recent years. In the process of merging, paying attention to its effects can help to integrate banks. In Iran's banking network, financing of production is one of the main concerns of banking policymakers. Therefore, it is important to study the effect of banks' integration on financing. In this paper, considering the importance of this issue, using the financial statements of banks in the period 2006-2018, and the Panel Data method, the effect of the merger of banks on financing has been investigated. The static method has been used to integrate banks. For this reason, banks have been considered in terms of size and health. The results of the survey indicate that the combination of small banks with large bank and combination of healthy banks, as compared to other options, have more positive effect on the supply of facilities.

Abstract Household equivalent scale is an index to measure the impact of household demographic characteristics, such as the householder’s age and gender, the number of household members, etc., and plays a significant role in measuring poverty and inequality. By taking into account demographic characteristics differences, this index facilitates the reasonable comparison of households’ welfare, and functions as a coefficient for the target household in relation to the reference household. Using income and expenditures data of Iranian urban household in the period of 2012-2018, this study measures the relative child cost of each urban household in Iran while estimating the Quadratic Almost Ideal Demand System (QAIDS) and price scaling by means of Nonlinear Seemingly Unrelated Regression. Also, it calculates the elasticity of income and price of electric power goods. The results illustrate that the relative child cost in Iranian urban households is 33% of an adult cost, and electric power goods in Iranian urban households is a necessary yet low elasticity commodity. Therefore, pricing policies may not significantly influence demand for this product.

This paper investigates causal relations between economic growth, income inequality, and transmission channels during the period 1972 to 2016. These channels include saving rate, investment rate, redistribution policies, human capital, and conspicuous consumption. There is no strong evidence that supports uni-directional or bi-directional causality. In addition, some of the transmission channels lead to improvement of economic growth and equality simultaneously. It concludes that the rapid economic growth and the income inequality alleviation are not necessary conflicting objectives. Hence, strategy of “Redistribution with growth” is a more effective and perhaps politically more acceptable approach than “growth before redistribution” or “redistribution before growth” strategies.

Financial markets are one of the most fundamental markets in any country. In the financial markets, the securities market and the foreign exchange market are sensitive sectors. These two markets are affected by fluctuations and economic cycles so reflect economic changes rapidly. Changes in the returns of one market due to arbitrage conditions during time lead to changes in the returns of other markets. This paper by dividing the spillover effect into two parts, mean effect and volatility effect, employing DCC-GARCH method, aimed to capture the spillover effects of dollar return, global market and Iran financial market in the period 1394-1398. Mean conditional results show that stock returns react negatively to dollar returns. In other words, there is a substitution between dollar returns and stock returns among economic agents. For the global economy, the stock market returns decreases with the fluctuations of the global economy index, but for the dollar, the relationship is reversed so that increase in the global economy index volatility increases the dollar return. For the volatility spillover, the results also supported strong spillover between each market pairs.