Showing 5 results for Unit Root Test
K. Yurekli,
Volume 6, Issue 2 (7-2018)
Abstract
Aims: In this study, variation in annual and seasonal rainfalls in Southeastern Anatolian Project (GAP) area was analyzed using the non-parametric and parametric approaches.
Materials and Methods: According to the aim of the study, the data sets of the seasonal and annual timescales, based on monthly rainfalls in the GAP area, including 9 rain gauges operated by Turkish State Meteorological Service, were considered in the study. Mann–Kendall (MK) and unit root test to detect the direction of an available monotonic trend in any given data were used while obtaining the magnitude of the variation with Theil–Sen slope estimator.
Findings: Based on the MK test, decreasing trend in four of the seven different time scales was observed, whereas there was an upward trend in the only two (P-III and P-IV) of the all time scales while none of the stations in the P-II period showed a monotonic trend. However, the parametric unit root test detected the existence of variation in the period III for Sanliurfa station and the period V for Sirnak station.
Conclusion: The percentage change calculated by considering the MK varied between 19 and 57%.
Volume 9, Issue 1 (1-2009)
Abstract
In this paper a macroeconomic approach is derived to develop a long run electricity demand model to analyze the main factors affecting electricity demand in the Islamic Republic of Iran. According to the definition of a demand function, electricity demand, in general, is determined by some main factors including gross domestic product (GDP), prices, etc. This paper, by analyzing the specific political and economical conditions in the Iran, introduces electricity intensity and a dummy variable WAR into the electricity demand forecasting model. A binary dummy variable, WAR is applied to correct the model (between the years 1980-1988 during the Iran and Iraq war). In this study, two popular econometric techniques namely unit root test and cointegration model is derived for modeling the electricity demand. Cointegration is established between kWh and, respectively, GDP, electricity price, electricity intensity, and WAR as a dummy variable. The results show that although GDP is still the most important factor for electricity demand, electricity demand is negatively related to efficiency improvement and tariffs in Iran.
Volume 9, Issue 3 (10-2009)
Abstract
Understanding the different aspects of the relationship between energy consumption and economic growth can outstandingly help to adopt appropriate policies in energy sector. Structural breaks and regime shifts may affect the above relationship. Therefore, it is important to consider structural breaks and regime shifts in empirical analysis.
In this paper, the relationship between energy consumption and economic growth is analyzed in the presence of structural breaks. The empirical models are specified and estimated using Iran's time series data during 1967- 2005 period. To this end, unit root tests proposed by Zivot and Andrews (1992) are first used to identify structural breaks found endogenously and then the Gregory-Hansen cointegration test, which allows strctural breaks in time series, is employed to estimate the long-run relationship between energy consumption and economic growth. The results show that in the long run, there is a positive and significant relationship between energy consumption and economic growth in Iran.
Volume 12, Issue 1 (5-2012)
Abstract
The purpose of this paper is estimating output gap as one of the variables that affect inflation in the Iranian economy. Therefore, using seasonal data from spring 1989 to winter 2006 and through Hodrick-Prescott filtering techniques the potential output and output gap are estimated and then ordinary least squares approach has been used to find out the relationship between inflation and output gap. Variables such as exchange rates, price index of imported goods, and the adjusted output gap as real variables and expected future inflation have been used for estimating the model considering the facts and theories in the Iranian economy. This test has been done through the rational expectation hypothesis of an enterprise and using a new Keynesian Phillips curve. The research findings verify the new Keynesian opinion. Thus, in Iran where the average rate of inflation in the period, is 19.6% and therefore considered among the countries with galloping rate of inflation, Phillips curve has been estimated with a relatively steep slope. In the long run, the steep Phillips curve according to Keynesians implies that in case of demand shock, the production will increase and compared with the new classic models it has less impact on inflation.
Volume 14, Issue 3 (9-2014)
Abstract
The convergence hypothesis is a result of the neoclassical growth model. By definition, the concept of convergence is the faster growth of regions (economies) with lower per capita income compared to the regions (economies) with higher per capita income. This paper deals with convergence clubs among provinces of Iran during 2000-2009. For this purpose, the Panel unit root tests have been used to examine the convergence hypothesis after classifying the provinces with cross-sectional methods. The research results show that Iran’s provinces can be classified into two groups of provinces: (1) ones with low per capita income (18 provinces) and (2) ones with high per capita income (12 provinces). According to the panel unit root tests, the existence of absolute convergence (tendency to a certain standard) between two mentioned groups is confirmed. So, the convergence clubs hypothesis is verified among the Iran’s provinces.
