THE JOURNAL OF PLANNING AND BUDGETING
Year:2023 | Volume:28 | Issue:1|Papers Count:6

An inefficient firm causes a waste of resources by using a non-optimal combination of capital and labor and especially energy. Measuring inefficiency and identifying the factors that cause it is vital in achieving the firm's potential production and, as a result, the sustainability of economic growth and increasing the economic well-being of the society. Meanwhile, choosing the right model to measure inefficiency is always one of the basic challenges among researchers in this field. This study attempts to provide an overview of the concept of efficiency and its types and different measurement models with an emphasis on the Frontier Analysis. Considering the large volume of theoretical and experimental studies in inefficiency, our review aims to provide a proper understanding of their strengths and weaknesses by investigating the evolution of the models demonstrated in the literature, and thus helps the researcher to create a clear framework for analysis and choosing the appropriate model. Furthermore, this study offers suggestions to measure inefficiency as accurately as possible from the theoretical and technical viewpoints, which have been understudied in the literature.

Curbing inflation is one of the requirements of a good economic policy. The steady rise of inflation can exacerbate poverty and income inequality, and even increase crime. Therefore, various studies have identified inflation as a determinant in reducing economic welfare. Considering that the Iranian economy has experienced high inflation in recent decades, it seems that the welfare of the Iranian population responds quickly to this variable, and reducing the frequency of data may reduce pattern explanation. This study attempts to measure the effect of monthly inflation on economic well-being for the period 1982-2020. Since the index of economic well-being cannot be determined at a frequency higher than annual, it is necessary to employ a mixed-data sampling (MIDAS) approach. Economic growth has been also included in the model as a control variable. The estimation results indicate that inflation has a negative (unfavorable) effect, and economic growth has a positive (favorable) effect on economic well-being. Moreover, the effect of inflation is significantly larger than economic growth. In other words, controlling inflation may have a greater effect on the economic well-being of society in the long term than economic growth.

Considering the upward trend of the inflation rate and the relative stabilization of the nominal interest rate in Iran, this question becomes important: how have the stock returns of different industries reacted to these two macroeconomic variables? In this article, the effect of inflation and interest rate on stock returns of different industries in Iran is investigated empirically according to monthly data of the period April 2010-March 2022 using Panel-ARDL model. First, to make the comparison between stock indices of different industries possible, these indices were homogenized based on a base month and then the model was estimated. Empirical results show that inflation in the short and long term has a positive and significant effect on the nominal returns of stocks of various industries for the period, but inflation has a negative and significant effect on the real returns in the long term. The nominal interest rate in the short and long term causes a decrease in the nominal and real returns of stocks of various industries. In addition, the variables of exchange rate, global oil price, and liquidity were also considered as control variables. These results show that stocks have not been able to protect against inflation in the long term, and monetary authorities should pay attention to its effects on the stock market when managing interest rates.

Although various studies have investigated the impact of income inequality on the quality of the environment, the impact of income distribution on the consumption of renewable energy, which plays an important role in reducing CO2 emissions and improving the quality of the environment, has been understudied. The main purpose of this article is to investigate the effect of income inequality (Gini coefficient) on renewable energy consumption in Iran. For this purpose, the autoregressive distributed lag (ARDL) approach has been used to analyze the time series data related to the period 1983-2019. The results of the cointegration test show that the fair distribution of income leads to an increase in the consumption of renewable energy. Also, according to the results, economic growth, rate of economic openness, and rate of urbanization increase the consumption of renewable energy in Iran, while CO2 emission reduces the consumption of renewable energy in Iran. These results provide useful policy implications for managing energy consumption to improve the quality of the environment and reduce environmental pollutants.

One of the main goals of economic policy-makers is to realize a fair and proper distribution of income in society. Regarding the importance of this issue in Iran and the unfavorable situation of income distribution indicators in its provinces, this study attempts to investigate the relationship between income inequality, urbanization, and economic growth in the provinces of Iran for the period of 2006-2019. Accordingly, to study such a relationship, two approaches have been conducted, First, the causal relationship between income inequality, urbanization, and economic growth was investigated using the method of Dumitrescu-Hurlin (2012). Then, to complete the discussion and determine the impact of urbanization variables and GDP on income inequality, the income inequality model was estimated by considering the spatial structure and accounting for two variables of urbanization and GDP per capita and several control variables using the spatial econometric approach. The results of the Dumitrescu-Hurlin causality test indicate the existence of a one-way causal relationship from urbanization to income inequality and the existence of a two-way causal relationship between GDP and income inequality in the Provinces of Iran. The results of estimating the model using the spatial panel approach show that the variables of urbanization rate, GDP per capita, and literacy are the most important variables affecting the income inequality of the provinces of Iran.

The destructive effects of corruption on the economic, social, and political development of countries have invigorated numerous studies to identify the determinants of corruption and to attempt to provide strategies to fight and control this issue. Accordingly, the present study attempts to estimate the impact of electoral cycles (including election year, government's ideology, coalition, and minority government) on corruption in two groups of selected democratic countries during the period 2003-2018 using panel data and the generalized moment models (GMM) method. The first group includes the countries with a positive average of the democracy index for the period under review, and the second group consists of countries with a negative average. The results showed that the effect of the election year on corruption in the second group countries was positive and significant, but in the first group, it was negative and significant. The effect of the government's ideology on corruption in the second group countries is positive and meaningful and in the first group countries, it has been meaningless. The influence of the coalition and the minority government on corruption in both groups is negative and meaningful. Also, the effect of control variables including per capita income, E-government, and democracy on corruption in both groups of selected countries has been positive and meaningful. However, the impact of natural resource rents on corruption in the second group countries has been positive and meaningful, whereas it was meaningless for the first group countries.