Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition

Abstract

The gross capital formation (GCF), which helps to gradually increase GDP itself, is financed by domestic savings (DS) in both developed and developing countries. Therefore, forecasting GCF is the key subject to the economists’ decisions making. In this study, I use simple forecasting methods, namely dynamic relation model called “Autoregressive Distributed Lag Model (ARDL)”, and complex methods such as Adaptive Neuro Fuzzy Inference System (ANFIS) method and ARIMA-ANFIS method to determine which method provides better out-of-sample forecasting performance. In addition, the contribution of this study is to show how important to use domestic savings in forecasting GCF. On the other hand, ANFIS and hybrid ARIMA-ANFIS methods are comparatively new, and no GCF modeling using ANFIS and ARIMA-ANFIS was attempted until recently to the best of my knowledge. In addition, Autoregressive Integrated Moving Average (ARIMA) method and Vector Autoregressive (VAR) model serve as benchmarks, allowing for fair competing for the study.

Conceptual basis of Development and Application of Artificial Intelligence Technologies in Forecasting Economic Processes

“…Correction of error the term labor F(1, pˆ) indicates the rate of adaptation to the equilibrium level after impact. In theory, the sign of the term error correction should be negative and significant [7].…”

“…There are two approaches to conducting a comparative analysis of simple and complex forecasting methods: methodology and data set presentation [7].…”

“…One advantage of the Autoregressive Distributed Lag Model Approach is that all variables in the model are either purely I(1) or purely I(0) or a mixture of both. A second advantage of the Autoregressive Distributed Lag Model is that the Autoregressive Distributed Lag Model Approach is the most efficient model for empirical work if the researcher is unsure about the single root properties of the data [7]. The Autoregressive Distributed Lag Model can be presented as follows:…”

“…There are many different scientific publications and reports on the formation of new economic sectors based on artificial intelligence technologies, as well as on the interaction effects of artificial intelligence technologies and economic development [4,7,9,10,[13][14][15]. Although most of them are of a general nature, some of them also address specific problems.…”

“…In [7], a comparison of simple and complex forecasting methods and the structure of the forecasting process were considered. As is well known, the formation of total capital, which contributes to the increase of GDP, is financed by domestic savings in both developed and developing countries.…”