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Gross Domestic Product Modeling Using “Panel-Data” Concept

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Computational Management

Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 18))

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Abstract

In this work, we want to predict gross domestic product (GDP) using ‘panel-data’ models. Gross domestic product for fifteen individual countries of Europe in different four years (1995, 2000, 2005 and 2010) under various components of GDP are used here. The panel-data models have been developed using the investment, labour force growth and budget surplus as inputs in order to predict the GDP of the countries which help us to perceive the economic condition of Europe from the statistical point of view. The results indicate that the random effects model is more appropriate than fixed effects model. In addition, this chapter also contains a panel data regression model with cross-sectional dependence, heteroscedasticity and also considers serially correlated disturbances for random effects.

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Authors and Affiliations

  1. Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, 711103, India

    Sarada Ghosh & G. P. Samanta

Authors
  1. Sarada Ghosh
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  2. G. P. Samanta
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Correspondence to G. P. Samanta .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Faculty of Engineering, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  2. Strategic Management and International Business, Tokyo Institute of Technology, Tokyo, Japan

    Kayhan Tajeddini

  3. School of Management, Victoria University of Wellington, Wellington, New Zealand

    Vipul Jain

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Ghosh, S., Samanta, G.P. (2021). Gross Domestic Product Modeling Using “Panel-Data” Concept. In: Patnaik, S., Tajeddini, K., Jain, V. (eds) Computational Management. Modeling and Optimization in Science and Technologies, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-030-72929-5_9

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