| Issue |
E3S Web Conf.
Volume 450, 2023
International Conference on SDGs and Bibliometric Studies (ICoSBi 2023)
|
|
|---|---|---|
| Article Number | 03004 | |
| Number of page(s) | 10 | |
| Section | Social Sciences, Hummanities, and Economics | |
| DOI | https://doi.org/10.1051/e3sconf/202345003004 | |
| Published online | 29 November 2023 | |
Forecasting poverty in East Java using vector autoregressive method and vector error correction model
1 Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Negeri Surabaya, Surabaya, East Java, Indonesia 60231
2 Statistics Department, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, West Java, Indonesia 16680
* Corresponding author: ayuninsofro@unesa.ac.id
People experiencing poverty are people who are unable to fulfil their basic needs. A region with a dense population is prone to problems overcoming poverty. In this instance, the gross regional domestic product, the human development index, and the open unemployment rate are the variables impacting poverty. Therefore, more study is required to address this issue of poverty. The vector autoregressive and error correction models are two possible approaches. The East Java Central Bureau of Statistics provided the data, which included gross regional domestic product, human development index, open unemployment rate, and percentage of poverty. Forecasting the number of poverty people is obtained using estimates from data that can affect forecasting results. In this article, the best forecasting results are obtained with an RMSE value of 21.51062 using the vector error correction model, namely with a percentage of poverty value of 7.2619.
© The Authors, published by EDP Sciences, 2023
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