Econometric analysis and modeling of the dynamics of the balance of payments’ development in Azerbaijan
Authors: Ayyubova N. S. 
Published: May 2022

Purpose of the study. The study is devoted to econometric analysis and modeling of the dynamics of the balance of payments’ development of Azerbaijan, the formation of a mathematical and statistical trend that can give a perspective assessment of the development of the balance of payments. In accordance with the goal, the tasks of choosing the best composition of explanatory factors for the model were set, using the characteristics and criteria of correlation and regression analysis, econometric tests, calculating estimates of the nature and closeness of the relationship between the explanatory factors, dependent and independent factors, testing the stationarity of the series.Materials and methods. The official statistical data of the State Statistics Committee and the Central Bank of Azerbaijan, scientific works and studies of scientists, specialists, both Azerbaijani and foreign, in the fields of economics, mathematical and economic modeling were used. For the empirical analysis of non-stationary time series, statistical methods of information processing are used inthe work; to check the adequacy and test the multivariate model, the appropriate criteria and modern econometric procedures are used, taking into account the impact of exogenous factors. For calculations, application packages such as Excel and Eviews 8 were used.Results. A multivariate regression model has been created that makes it possible to conduct an economic and statistical analysis of the dynamics of the current account of the balance of payments; the form and directions of the functional relationship between dependent and independent variables were determined, variability of variables was estimated, the results of multivariate regression analysis using econometric methods were analyzed; the quantitative characteristics of the mechanisms of influence of explanatory factors on the balance of payments were measured and interpreted; correlation dependencies for causal dependencies were investigated in the model, the Granger test was performed and factors were identified that reliably explain the outcome with high probabilities based on the Fisher criterion; the stationarity of the model was measured based on the Dickey-Fuller test. With differences of the first and second degree, the stationarity of the autoregressive model was determined based on the Student’s criterion by changing the lag value. In the process of modeling, the initially constructed model, covering the years 1995-2017 with five factors such as foreign investment, exports, imports, manat exchange rate, general investments, showed insufficient adequacy, that is, non-stationarity of the current account series of the balance of payments. The exchange rate of the national currency, which is involved in the model as an explanatory factor, subjected the values of the dependent series to large fluctuations, an increase in the variance in the residue, which created non-stationarity and which can be explained by the denomination of the national currency in 2006. In the next step, the period covering 2006-2017 was examined. In addition, in the process of research, independent factors were added to the model, such as state budget deficit and foreign exchange reserves. As a result, a multifactorial econometric model was created. Conclusion. The constructed autoregressive model is quite adequate, demonstrates stationarity for the time series of the dependent variable and can be considered suitable for predictive values of the current account of the balance of payments. To develop specific recommendations for the long-term development of the balance of payments, the results of the study, substantiated by the analysis of the dynamics of the development of the balance of payments, make it possible to identify real trends in the balance of payments of Azerbaijan on the current account and determine its interdependence with other macroeconomic variables.