JOURNAL OF ECONOMIC MODELING
Year:2021 | Volume:5 | Issue:4 (19)|Papers Count:6

Achieving happiness has always been one of the goals of human societies, attracting the attention of many governors, scholars and researchers. In this regard, the link between oil revenues and happiness in oil-exporting countries is an important issue that has been little considered. In many internal and external studies, the relationship between the rents of oil revenues and many important economic variables, such as economic growth, has been investigated within the context of the resource curse hypothesis, but so far, the impact of oil rents on happiness has not been studied within the framework of the resource curse hypothesis. Therefore, the purpose of this paper is to examine that how oil revenue rents affect happiness and is to test the resource curse hypothesis and the threshold impact of the oil rents on happiness in selected OPEC countries over the period of 2005-2016. For this purpose, using theoretical literature and applying the Threshold Panel method, the factors influencing happiness have been modeled. The results of the estimation of the research models have shown that the effect of oil on happiness is non-linear and threshold effect which it means that before the threshold of 43% of the ratio of oil rents to GDP, this variable has a significant positive impact on happiness, but so bypassing this threshold, the ratio of oil rents to GDP has had a significant negative impact on happiness in the OPEC countries.

This article investigates the effects of oil price shocks on different quantiles of real exchange rates of selected OPEC member countries (Islamic republic of Iran, Nigeria, Algeria and Saudi Arabia) from January 1993 to December 2018 with quantile regression approach. The result indicates that positive and negative oil price shocks have asymmetric effects on different quantiles of real exchange rates affected by market conditions. Rising oil prices at lower quantiles of real exchange rates, because of central bank intervention effect, and at the medium quantiles because of increase in import of industrial and semi-industrial goods lead to USD appreciation against the currency of Iran, Nigeria and Algeria while at upper quantiles has no meaningful effect on real exchange rate of these four countries. Also, falling oil prices only lead to deprecation of SAR against USD at lower quantiles of exchange rate. Ultimately current result confirms the Balassa-Samuelson effect for all of these countries.

One of the key issues that economists face when analyzing the evolution of economic activity is the attempt to explain business cycles. The behavior of macro variables during the business cycles and the effect of monetary and fiscal policy on their dynamics is a key stage in understanding the role of financial markets in the real economy. Therefore, the purpose of this study is to identify business cycles by using the Markov Switching model and to examine monetary and fiscal policies that affect it. To this target, using seasonal data during the period of 1996-2016, it was found that GDP growth has three regimes with average of negative, mildly positive and high positive growth. The results of the research indicate that monetary policy and exchange rate uncertainty have a significant negative impact on economic growth in business cycles of mildly boom and depression. However, oil revenues in all three business cycle regimes have a positive and significant effect on economic growth. Also, fiscal policy (tax) as an auto stabilizer has a very small contribution to the adjustment of business cycles during the recession and economic prosperity of Iran. In general, the impact of significant variables has led to a shortening of the recession and boom in economic growth.

Wealth distribution is one of the most important and effective factors in the economic and social stability of each society. Thus, assessing the behavior of income distribution have great importance and to do this, several indices have been introduced that their performance has been investigated in terms of precision. The main goal of this paper is to introduce the Total Time on Test (TTT) transformation and its corresponding graph as a beneficial index for measuring income inequality. We further compare its performance with the Lorentz and Zanga indices. The micro-data of Iranian household income in the period 2012-2018 has been used to analyze the performance of the proposed index. The results show that while the new index performs better than the Lorenz one, it performs as same as the Zenga index. We also introduced a new distorted model using distortion functions in the final section, and by considering the basement income distribution, the generalized version of these distributions are presented and some of their features, particularly the maximum likelihood estimator are investigated. In addition, the goodness of fit of the new distributions to the income data of citizens in Texas (Arnold 1983) and the income data of Iranian households in 2017 are other results of this article.

Scientific theories are a way of knowing man. The main difference between this method and other methods is the testability of its claims. Testability helps to correct scientific knowledge of error. In economics, this knowledge is created by using econometric methods and models. Assumptions Econometric models are called auxiliary assumptions. Two fundamental problems in econometrics that challenge testability; ignoring auxiliary assumptions and statistically significant. The Duhem (1904) stated that if the auxiliary assumptions are inconsistent with the reality falsity method will be questioned. In the present study, the Duhem problem in the EMH and financial data structure has been investigated. In another section, the use and interpretation of statistical significance is studied, which is usually evaluated with an index called p < /em>-value. While the p < /em>-value can be a good statistical metric, it is often misused and misinterpreted. As a result, some reputable scientific journals have banned the use of p < /em>-values. To make good use of this criterion in the econometric methodology, the recommendations of the American Statistical Association in this field have been discussed. In order to deal with the role of auxiliary assumptions, it is necessary to specify tests and pay attention to the data structure.

The purpose of this paper is to investigate the effect of economic policy uncertainty on exchange rate fluctuations in Iran. For this purpose, the data of the period 1368-1398 based on the frequency of quarterly data and the nonlinear autoregressive distributed lags have been used. The use of nonlinear models will lead to more realistic results than the response of the exchange rate variable to policy shocks. In this study, first, the exchange rate fluctuations index was modeled using the GARCH method, and in the second step, the effects of economic policy uncertainty in the form of positive and negative shocks on exchange rate fluctuations were estimated using the NARDL method. The results of the estimated model show that uncertainty in economic policies in the form of monetary and fiscal policy shocks has led to increased instability in the exchange rate in the country. The analysis of shocks showed that the impact of negative shocks on the exchange rate was more severe than positive monetary and financial shocks.