On the Measurement of Cointegration Relations Between the Indicators of the Time Series of the Current Account of the Balance of Payments and GDP (On the Example of the Republic of Azerbaijan)

Abstract

The article solves the problem of constructing an econometric model (based on time series of macroeconomic indicators) that reflects the relationship between changes in the current account of the balance of payments and GDP dynamics (on the example of the Republic of Azerbaijan).In order to assess the correctness of the application of mathematical and statistical methods for analyzing the impact of foreign economic activity on the final results of the country's economic activity, the constructed model was tested. So, to test the hypotheses about the normal distribution of the series, the Jarque–Bera test, the augmented Dickey–Fuller test (ADF), the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test were used, and histograms and correlograms were constructed.In the process of studying the time series of the indicators under consideration, their non-stationarity was revealed both according to the results of descriptive statistics, the Jarque–Bera test, histograms, plots of the sample autocorrelation function (ACF) and partial autocorrelation function (PACF), and according to the Dickey–Fuller test. The transition to absolute increments, that is, to the first differences, was applied. In addition, the Johansen test was performed to identify cointegration relationships. Based on its results, when comparing linear and quadratic trends with similar characteristics, a linear one was chosen, indicating the presence of a cointegration relationship. After carrying out the Trace and Maximum Eigenvalue tests, an alternative hypothesis about the presence of one cointegration vector was accepted.The results obtained allow us to conclude that the relationship between the indicators of the current account of the balance of payments and Azerbaijan's GDP is of a long-term nature. They can also serve as a basis for building an error correction model.