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Markov-switching vector autoregressive neural networks and sensitivity analysis of environment, economic growth and petrol prices

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Abstract

The paper aims at evaluating the nonlinear and complex relations between CO2 emissions, economic development, and petrol prices to obtain new insights regarding the shape of the environmental Kuznets curve (EKC) in the USA and in the UK in addition to introducing a newly proposed nonlinear approach. Within this respect, the paper has three purposes: the first one is to combine the multilayer perceptron neural networks (MLP) with Markov-switching vector autoregressive (MS-VAR) type nonlinear models to obtain the MS-VAR-MLP model. The second is to utilize one of the largest datasets in the literature covering the 1871–2016 period, a long span of data starting from the late eighteenth century. Since the emission, economic development, and petrol price relation is subject to nonlinearity and trajectory changes due to many historical events, the development of the MS-VAR-MLP model is a necessity to contribute to the ongoing debate regarding the shape of the EKC curve and the stability of the relation. The third purpose is to develop the MS-VAR-MLP-based regime-dependent sensitivity analysis, which eases the visual interpretation of the nonlinear causal relationships, which are allowed to have asymmetric interactions in different phases of the expansionary and recessionary periods of the business cycles. Our results provide clear deviations from the findings in the literature: (i) the shape of the EKC curve cannot be assumed to be stable and is subject to regime dependency, nonlinearity, and magnitude dependency; (ii) the forecast results suggest that incorporation of regime switching and neural networks provide significant improvement over the MS-VAR counterpart; and (iii) for both USA and UK and for the 1871–2016 period, the positive impacts of economic growth on emissions cannot be rejected for the majority of the phases of the business cycles; however, the magnitude of this effect is at various degrees. In addition, the incorporation of petrol price provides significant findings considering its effects on emission and economic growth rates. The analysis suggest clear deviations from the expected shape of the EKC curve and puts forth the necessity to utilize more complex empirical methodologies to evaluate the EKC since the emissions-economic development relation is more complex than it was assumed. Following these findings, several policy recommendations are provided. Lastly, the proposed MS-VAR-MLP methodology is compared with the MS-VAR model and various advantages and disadvantages are enumerated.

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Notes

  1. It should be noted that in the MS-VAR analysis, the MS-VAR model was accepted against the linear VAR model in terms of certain portmanteau tests. The results are available from the authors upon request and are not included in the paper to save space.

  2. Early stopping algorithm continuously checks the MSE in the test and validation samples during estimation. If not conducted, lower values for in-sample MSE and various error criteria are also possible. However, without early stopping, the models could suffer from over-fitting and their out-of-sample performances could deteriorate significantly (for details, see Bishop 1995).

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  1. Department of Economics, Yildiz Technical University, Davutpasa, Istanbul, Turkey

    Melike Bildirici

  2. Department of Economics, Beykent University, Ayazaga-Sariyer, Istanbul, Turkey

    Özgür Ersin

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Bildirici, M., Ersin, Ö. Markov-switching vector autoregressive neural networks and sensitivity analysis of environment, economic growth and petrol prices. Environ Sci Pollut Res 25, 31630–31655 (2018). https://doi.org/10.1007/s11356-018-3062-3

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