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Research Article Open access CC BY 4.0

Time Series Modelling of The Volume of Overland Timber Export in The Bolgatanga Municipality

Henry M. Kpamma, Silverius K. Bruku, John A. Awaab

Journal of Scientific Research and Reports · pp. 124–138 · Published 8 Jun 2020

10.9734/jsrr/2020/v26i430253

Abstract

Aims/ Objectives: This research was carried out with the intention of using time series to model the volume of overland timber exported within Bolgatanga municipality Place and Duration of Study: Study of the time series was based on a historical data of the volume of timber exported for twenty consecutive years, from 1999 to 2019 within Bolgatanga municipality. Methodology: The three-stage iterative modeling approach for Box Jenkins was used to match an ARIMA model and to forecast both the amount of timber export and the confiscated lumber. ARIMA method incorporates a cycle of autoregressive and a moving average. The three-stage iterative modeling technique of Box Jenkins which were used are model recognition, parameter estimation and/or diagnostic checks were also made. Results: From the preliminary investigation, the study showed that the amount of timber exported in municipality is skewed to the right, suggesting that much of the amount of timber exported is below the average. This, together with the high volatility in the volume of timber exported, indicates that the amount of timber exported within the municipalities during the twenty-year period was low. The plots from the trends also showed robust variations in the volume of timber exported indicating that timber exporters do not have better grips with the concepts and applications of export technology, hence the erratic nature of the volume of timber exported over the period. The quadratic pattern and the ARIMA (1,1,1) model best represented the amount of timber exported. The analysis further indicated that there will be a further decrease in the amount of timber export from the five years projection into the future. Over the last two decades the Bayesian approach to VAR has gained ground. For a future report, this estimation method will be followed to examine the ”long-run equilibrium relationships” between timber export volumes and climate change. Conclusion: The quadratic pattern and the ARIMA (1,1,1) model best represented the amount of timber exported. There will be a further decrease in the amount of timber export from the five years projection into the future.

Autocorrelation function partial autocorrelation function stationary parameter estimation parsimonious model differencing time Series analysis linear trend quadratic trend timber analysis of variance ARIMA.

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