Time Series Behavior of the Volume of Wood Products Export in Ghana

Acquah, Stella Britwum; Avuglah, Richard Kodzo; Harris, Emmanuel

doi:10.5539/ijsp.v3n4p12

Cited by 7 publications

(6 citation statements)

References 10 publications

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“…This result obtained is backed by pre-existing literature and studies bySingh (2017) andBrajesh and Shekhar (2015). similar pattern of results was seen in case of Ghana in an earlier study Avuglah, et al, (2014). applies the Autoregressive Integrated Moving Average (ARIMA) time series model to study the trends and patterns of road traffic accident cases in Ghana as well as makes a fiveyear forecast.…”

supporting

confidence: 78%

Forecasting Road Accidental Deaths in India: An Explicit Comparison between ARIMA and Exponential Smoothing Method

Swain

Tripathy

Agrawal

2023

Preprint

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The number of deaths due to road accident is increasing day by day and has become an alarming global problem over the decades. India, with her rising motorization is no stranger to this global catastrophe. With the use of statistical methods and models it is possible to predict the future scenario of deaths due to road accidents with the available data. In this paper two relatively simple yet powerful and versatile techniques for forecasting time series data, autoregressive integrated moving average method (ARIMA) and exponential smoothing method are used to forecast the number of deaths due to road accidents in India from the year 2022-31 based on the data available from 1990-2021. The results based on the two methods are compared and it is found that they are in sync with each other and pre-existing literature. Furthermore, this is a unique attempt to use two time series analysis techniques on the same data and carry out a comparative analysis. The data was collected from the 2020 annual report of Ministry of road Transport and Highways, India and ADSI-2021 report of National Crime Record Bureau, Ministry of Home Affairs, India. After examining all the probable models, it is observed that ARIMA (2,2,2) model and exponential smoothing state space model (M, A, N) are suitable for the given data set. Further, the study also shows that forecasted number of deaths for the upcoming 10 years from the proposed models also reveals an upward trend is described.

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supporting

confidence: 78%

Forecasting Road Accidental Deaths in India: An Explicit Comparison between ARIMA and Exponential Smoothing Method

Swain

Tripathy

Agrawal

2023

Preprint

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“…A research conducted by Avuglah et al (2014) applied the Autoregressive Integrated Moving Average (ARIMA) time series model to study the trends and patterns of road traffic accident cases in Ghana and makes a five-year forecast using annual accident data from 1991 to 2011. The results showed that road traffic accident cases are increasing in Ghana.…”

Section: Review Of Related Literaturementioning

confidence: 99%

Forecasting Road Traffic Accidents in Metro Manila Using ARIMA Modeling

Sabenorio¹,

Enriquez²,

Ramel³

2023

World J. Adv. Res. Rev.

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In this paper, we have determined and analyzed the behavior of road traffic accidents (RTAs) in Metro Manila, Philippines over the period of 2012-2021, and created a forecast for the next 5 years using ARIMA modeling. This study used 10-year historical monthly data collated through the Metro Manila Accident Recording and Analysis System program for the years 2012 through 2021. Our result suggests that the total RTAs in Metro Manila gradually increased until the first quarter of 2020, then it plummeted and reached its lowest point in April 2020 due to COVID-19 lockdown. As lockdown eases, it bounced back but only halfway. Similarly, RTAs resulting in damage to property also bounced back to only halfway as lockdown eases, while RTAs resulting in injuries (fatal and nonfatal) bounced back to their normal range as before the lockdown. Despite the decrease in total RTAs, the ratio of RTAs resulting in injuries drastically increased during the lockdown due to reckless driving behaviors. Using Box-Jenkins methodology of ARIMA modeling, this study identified ARIMA (1, 1, 12) as the best model. With this model, the forecast shows that the total RTAs will stay halfway in 2022 and gradually decrease for the next 4 years.

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“…This study also concludes that intervention ARIMA model is superior to conventional ARIMA models. Acquah et al [7] applied intervention ARIMA model to analyse the impact of two different interventions of which one is a step function and the other a pulse function. The objective of the study is to quantify the effects of the review of the timber export levy downwards and the regulation of trade of a wood on the trade policies of wood products in Ghana.…”

Section: Review Of Literaturementioning

confidence: 99%

Modelling the Impact of Government Policies on Import on Domestic Price of Indian Gold Using ARIMA Intervention Method

Unnikrishnan

Suresh

2016

International Journal of Mathematics and Mathematical Sciences

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The study attempts to determine the impact of government policies of import of gold in India on the domestic price of gold during 2013 using Autoregressive Integrated Moving Average (ARIMA) intervention model. 2013 was an amazing year for Indian gold market where the price had reached its zenith. In April 2013, to curb a record trade deficit, India imposed an import duty of 10 percent on gold and tied imports for domestic consumption to exports, creating scarce supply of the yellow metal and boosting premiums to curtail the Current Account Deficit (CAD). The objective of the paper is to model the impact of this intervention by the government on the domestic price of Indian gold. Suitable ARIMA model is fit on the preintervention period and thereafter the effects of the interventions are analysed. The results indicate that ARIMA(1,1,1)is the most suitable model during preintervention period. Intervention analysis reveals that there is significant decrease in domestic price of gold by 56% from 2013. The model may be used by policymakers to analyse the future of gold before framing regulations and policies.

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Time Series Behavior of the Volume of Wood Products Export in Ghana

Cited by 7 publications

References 10 publications

Forecasting Road Accidental Deaths in India: An Explicit Comparison between ARIMA and Exponential Smoothing Method

Forecasting Road Accidental Deaths in India: An Explicit Comparison between ARIMA and Exponential Smoothing Method

Forecasting Road Traffic Accidents in Metro Manila Using ARIMA Modeling

Modelling the Impact of Government Policies on Import on Domestic Price of Indian Gold Using ARIMA Intervention Method

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