Development of a new model of gross domestic product forecasting

Öz

Economic growth is usually calculated as the increase in real Gross Domestic Product (GDP). Estimation of economic growth is made by countries or international organizations in order to predict the future cycle of the economy of a country. Thus, decision makers will be able to develop early policies against future situations. In this study, factorial designs, one of the experimental design methods, is used to estimate economic growth. It is observed that time series analysis and econometric methods are frequently used in the determination of the factors affecting economic growth and growth estimation studies. For the analysis, using correlation analysis among the factors that are considered to be ineffective on growth are eliminated, and correlation of the inflation rate, unemployment rate, industrial production index, foreign trade volume to GDP ratio, and the ratio of gross external debt stock to GDP are considered as factors in the analysis. The rate of change in GDP is taken into account as output. As a result of the analysis, a regression model is determined. When the regression model is provided, the novel forecasting model can be easily obtained. It is different from the conventional forecasting models that require the complex statistical evaluations. In this study, we present a novel 2k factorial design methodology in order to solve the GDP forecasting problem. Furthermore, we propose a general framework of the presented model in the econometrics perspectives, a numerical solution to illustrate this demonstration as well.

Anahtar Kelimeler

• Economics
• forecasting
• design of experiments
• economic growth
• factorial design

Kaynakça

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