GDP Modelling and Forecasting Using ARIMA. An Empirical Assessment for Innovative Economy Formation

VINTU, Denis (2021): GDP Modelling and Forecasting Using ARIMA. An Empirical Assessment for Innovative Economy Formation. Published in: European Journal of Economic Studies , Vol. 1, No. 2021. 10 (23 April 2021): pp. 29-44.

Abstract

This article reconsiders the developing of a new forecast model using the interrupted timeseries of the gross domestic product for the Republic of Moldova. The theme arises from a first need to redefine, economic growth in the context of increasing globalization but also the complexity of commercial transactions. The forecasting method used is based on ARIMA each model partly emphasizing the urgent need to redefine, the economic growth in the context of the Association Agreement (AA) with the EU, which includes a Comprehensive Free Trade Agreement (2014) but also future prospects of integration among the countries with an average degree of development. The technique used comes to bring novelty in the field of forecasting, as an alternative to the one which should be —, a simultaneous equations method and traditional VAR. The policy and practical implications of the results are the strengths. The limits are due to the high degree of risk and uncertainty, which is due to the low degree of real convergence of the economy, but also to other factors such as the regional context, the lack of openness of the economy, the diversification of exports and services. The degree of complexity arises from the adaptation and study of the chronological interrupted series 1967−2019 for the branch – information and communications, subgroup GDP, categories of resources, which themselves have specific asymmetries and nuances. The basic ARIMA equations are generally used in conjunction with three sets of assumptions regarding the formation of the gross domestic product, referring to the elasticity of aggregate demand or excess sensitivity supply in the goods and labour markets. Another hypothesis concerns the rigid wage and sticky prices, including deflation with an positive output gap only in the telecom market. Also, the salary is rigid, while the price level is adjusted based on the market of goods and commodities, so that the excess supply appears only in the labour market. Finally, in a third assumption, both markets are assumed to be mutually adjusted. The multipliers of fiscal and monetary policy, besides the conclusions that can be drawn about economic policy, are obviously different in these three assumptions. The article presents a synthetic model that supports the three particular sub-regimes of assumptions of a single adapted ARIMA model, namely the trajectory of New Keynesian Small and Closed Economy Model – a balance in the goods and services, the labour market and the national financial system. In conclusion, the model aims not only to redefine the area of macroeconomic forecasting but also to offer a future perspective of adopting combined techniques such as the Stochastic Dynamic General Equilibrium (K-SDGE) Model with sticky prices and wages – technique, but also the scenario method. This framework is appealing because it has straight forward model setup, transparent mechanisms, sharp empirical analysis, and multiple important applications such as rational expectations.

• Item Type: MPRA Paper
• Language: English
• Keywords: economic growth and aggregate productivity, the gross domestic product, innovation and communications, cross-country output convergence, prediction and forecasting methods,time series analysis and modelling, ARIMA modelling, Box-Jenkins method.
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; D - Microeconomics > D6 - Welfare Economics > D62 - Externalities; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D84 - Expectations ; Speculations; F - International Economics > F1 - Trade > F15 - Economic Integration; F - International Economics > F2 - International Factor Movements and International Business > F21 - International Investment ; Long-Term Capital Movements; F - International Economics > F6 - Economic Impacts of Globalization > F61 - Microeconomic Impacts; O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O10 - General; O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O30 - General

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