Journal of Economic Research
Year:2017 | Volume:52 | Issue:1 |Papers Count:12

Consumer behavior is the most important issues in microeconomics. In neoclassical economics it is assumed that in order to reach the goals, human behavior is based on absolute rationality. While, Simon criticizes the paradigm assumptions of neoclassic school and introduces the bounded rationality. Since, because of uncertainty and lack of access to enough information, human faces with limited cognitive. So that cannot decide rationally, according to neoclassical economics predictions. So, based on the studies in this field, we can say that human behavior is affected by the intuitional and reasoning factors. The purpose of this paper is to discuss consumer behavior with a different approach and to mention the critics that are posed to neoclassical economics. The purpose of this paper is to discuss the consumer behavior by using four approaches of economics, psychology, social science and cognitive science. The most important approach which, in recent years, absorb a lot of attention, is cognitive science that attempt to percept human brain and mind which receipts, keeps and process the information. This science focuses on reasoning, perception, retention, cognizance, emotions, attention, awareness, creativity and connection between them which are used to understand the ability of the human brain. The purpose of this paper is to illustrate the function of cognitive science in consumers' behavior as an important matter in economics.

Poverty is one of the most important problems in developed and developing countries such as Iran. For solving this problem, many studies have investigated the effective factors on poverty. In this paper, the impact of financial development on absolute poverty in Iran has been investigated during 1985-2013 by using the Structural Time Series method. In order to do it, two indicators of financial development including “financial deepening” and “the facilities granted by the banking system to the private sector divided by GDP” have been applied. Estimation results of the models indicate that the financial development has a non-linear and threshold impact on absolute poverty. In other word, when “the financial development indicators” are less than a threshold level, financial development causes deterioration of the poverty in society but after this threshold level financial development in the country, has positive and significant effect on reducing poverty. The threshold level of “financial deepening” and “the facilities granted by the banking system to the private sector divided by GDP” have been estimated about 0.62 and 0.27 respectively.

The dominant view, regarding the relationship between globalization and economic inequality which is known as Washington Consensus, believes that globalization reduces income inequality. Heckscher-Ohlin model asserts that countries engaged in trade will export a commodity which uses their abundant factor of production. Moreover, based on Stolper-Samuelson theorem removing tariff and trade barriers will reduce pay differential between factors of production within and between countries and the final result is the reduction in income-inequality within and among countries.Recent empirical results confirm that globalization alongside its positive effects leads to the increase in income inequality. This paper tries to study the nonlinear relationship between globalization and income inequality using data from 2002 till 2013 for 71 countries and applying Panel Smooth Transition regression model by choosing GDP per capita and globalization index as transition variables to test the inverted U Kuznets curve on the one hand and to study the U curve on the other. This paper shows that if we choose real per capita income as a transition variable then we cannot reject the inverted-U Kuznets curve but if we choose globalization index as a transition variable then freer world result in less inequality initially but higher inequality appears gradually.

Human capital has important role on economic growth. This factor can increase labor and capital productivity. It can increase capacity of new technology and reduce criminal participation and improve voters’ political behavior and migration of people with high human capital to another region has effects on region and spatial spillover on other regions.The present study aimed to analyze the direct and spatial spillover effects of human capital on economic growth in provinces of Iran. For this aim, we estimate a Spatial Durbin Model in panel data by using ML technique for 28 provinces over the period 2001-2011. The results indicated that human capital has a positive and significant direct effect on economic growth of each province. Also, human capital has a significant and positive spatial spillover on economic growth in other provinces. This means that with increase human capital of each province, increase average of economic growth of other provinces.

Societies have paid attention to safety. This study examines the relationship between socio-economic factors and crime, emphasizing on immigration. Due to the locational aspect of the data, spatial econometric techniques are used. The model has been specified in the form of Spatial Durbin Panel Data Model (SDPDM). The specified model has been estimated for 30 provinces of Iran in 2006-11 by considering two variables of theft and murder. In model I, unemployment, urbanization and income per capita have had significant positive impacts on theft, while industrialization and Gini coefficient have inversely influenced theft. In model II, economic growth and income per capita have had significant positive impact on murder rate. Result show spatial dependence.

This paper compares alternative monetary policy rules for Iranian economy in faces to both internal and external shocks. In other words, we focus on investigating of macroeconomic variables responses respected to money base and terms of trade shocks, under three types of monetary rules including fixed exchange rate, inflation targeting and floating of nominal exchange rate at the hard peg through an intermediate exchange rate regime.The results show that the intermediate exchange rate regime create higher volatilities in investment and production in both tradable and non tradable sectors, but the reactions of inflation and real exchange rate are convincing. By contrast, the inflation targeting rule induces to lower volatilities in investment, consumption and production, but it tends to higher volatilities of inflation and real exchange rate. Therefore, it seems appropriate for Iranian monetary authorities to conduct this rule in the context of an intermediate exchange rate regime, as a preliminary phase before the transition to a floating regime.

The study has been done to identify the contribution of effective no nfundamental factors on the fundamental value of house price and effective factor on housing price bubble in Tehran city on Short term and long term and to determine the contribution of any economic factors in the housing price bubble. To do these aims, were determined two economic models according to available theoretical literature, then Data were collected for each variable on the period 1371 to 1392. In the next steps, each of models estimated by using of econometrics methods such as VAR and ARDL, Using Eviews & Microfit. Estimating the dynamic model of the fundamental value and Model validation and unit root test on the residual component of model (bubble) indicated that explained changes by the explanatory variables is meaningful compared to not explained changes (errors) and the residual component is stationary and It can be accepted as housing price bubble of Tehran city. About explanatory variables of the real - fundamental values of house price in Tehran also can be said that in the long term Number of households with the coefficient -1.112 is the most elastic variable and Loan-To-Value with the coefficient 0.0674 is the least elastic variable in fundamental price. Among the explanatory variables of housing price bubble of Tehran, Country real liquidity with a lag with the coefficient of 0.26 was the most important variable and the lag of real interest rate with the coefficient of 0.0048 was the least important explanatory variables of housing price bubble of Tehran city.

The frequent occurrence of currency crises in recent years brought the early warning literature back in the researchers spotlight. In recent years, concept of an early warning system (EWS) developed that should be able to identify various costly events, such as currency crises, early enough for policy makers to reduce the costs. This study attempted by using Iran' s economy quarterly data during the period 1988-2014 and using a model with discrete dependent variable, design an early warning system with all the required components on the Iranian economy and explain it. The results of this study indicate that the designed system to greatly explain the determinants of a currency crisis in Iran and has high ability in predicting this crises in the time periods studied. According to the results, currency crises in Iran are due to a combination of different imbalances in the real and public sectors, external balance and the financial sector. Based on these results, variables of ratio of bank loans to bank deposits, ratio of bank debt to the central bank to monetary base, inflation and industrial production growth (due to the high dependence on imports) are the largest and strongest role in increasing the probability of currency crises in Iran. As well as, variables of ratio of bank deposits to liquidity, ratio of foreign exchange earnings to the central bank's foreign assets and real GDP growth are most important role in reducing the probability of a currency crisis in Iran.

Due to increasing number of international tourists and the enhancing role of tourism in economies of countries and competing environment, recognizing determinants in attracting international tourists seems very essential than ever before. Public and private sectors need to examine determinants and forecast tourism demand. The primary aim of this study is using econometric techniques to analyzing determinants of attracting international tourists to Iran and estimating tourism demand function by the gravity model and panel data techniques. Our dependent variable is the number of inbound tourists to Iran from countries of origin in 2009-2013.Explanatory variables are Per capita GDP, population of countries of origin, geographical distance, real exchange rate based on 2010 data, and numbers of hotels’ bed, UNESCO world heritage sites and the country brand index which their data acquired from national and international authorities and examined in Eviews 7 software. The results estimated by fixed effects shows that national brand index of Iran has the most positive effect on tourism demand (18.19) and hotels’ beds stand is the second important factor (1.89). But existing UNESCO heritage sites doesn’t have any impact on attracting tourists to Iran.

The role of distance as border effects between trade partners has been created challengeable discussions in gravity model literature for international economists and lead to different theoretical aspects for measuring and modeling of it in recent years. Moreover, the necessity of non-linear method for estimation of gravity model has been perfectly agreed. The importance of this study is the estimation of border effects by using Poisson – Pseudo Maximum Likelihood (PPML).Hence, this study tries to evaluate border effects on bilateral trade among Iran and major partners during 1988-2014 using non-linear method for gravity model.The results show that coefficient of distance variable as proxy for border effects on trade relations among Iran and major partners has 0.28 and 0.94 in generalized least square and PPML methods respectively which it is relatively higher than other coefficients. Not being land-locked country, also could effect on trade relation and lead to increase it. As a policy recommendation, the role of distance and using maritime transportations to reduce it, should be considered.