Significance of Econometric Model
Econometric models are statistical tools used across various fields. They determine relationships between economic development and circular economy concepts. They measure the marginal prices of factors influencing housing prices and assess climate change effects on potato production. These models analyze factors influencing carbon efficiency and the impact of household behaviors on soil pollution. To avoid biased results, econometric models should account for interdependence. They also require accounting for heterogeneity.
Synonyms: Statistical model, Mathematical model, Regression model, Forecasting model, Predictive model, Econometric framework
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The concept of Econometric Model in scientific sources
Econometric models are statistical tools used across various fields, from analyzing carbon efficiency and housing prices to assessing economic development, climate change impacts, and pollution effects. They require careful consideration of interdependence and heterogeneity.
From: Sustainability Journal (MDPI)
(1) Econometric models, such as ARIMA, GARCH, VAR, and VECM, are commonly used for oil price prediction, but they often face challenges in handling complexity and nonlinearity.[1] (2) Econometric model is used to find the net effect of PCNPE on ATFP, leveraging recent advances in econometric modeling to construct a DID regression model with two-way fixed effects.[2] (3) Econometric models are used for determining the causality structure and evaluate the influence of different variables on future tourism demand.[3] (4) To further explore the key factors influencing the agglomeration of the creative class, an econometric model will be built based on existing research and considering the Chinese cultural context.[4] (5) Econometric models are used for different subgroups to improve understanding of specific market segments and develop targeted marketing strategies.[5]
From: International Journal of Environmental Research and Public Health (MDPI)
(1) These are statistical tools used to analyze economic data, test hypotheses, and estimate relationships between variables for informed decision-making.[6] (2) It is estimated by the two-step systematic generalized moment estimation method, which requires passing two tests: serial correlation and the Sargan test for over-identification of instruments.[7] (3) The econometric model is presented in Equation (1) for a panel of i observations over t time periods and is obtained by adding a subscript i and t.[8] (4) Is a statistical tool used to estimate the relationship between variables.[9] (5) Variables that are non-significant in econometric models and highly important in machine learning (ML) models are linked to dependent variables in a non-linear way.[10]