Affiliation:
1. Zhytomyr Polytechnic State University
Publisher
Black Sea Research Institute of Economics and Innovation
Reference10 articles.
1. Kithure, M.E., Waititu, A., & Wanjoya, A. (2019) Modelling and Forecasting Volatility of Value Added Tax Revenue in Kenya. Science Journal of Applied Mathematics and Statistics, vol. 7, no. 1, pp. 1–7. doi: 10.11648/j.sjams.20190701.11
2. Lee, T.-H., & Kwak, S. (2019) Revenue volatility and forecast errors: evidence from Korean local governments. Local Government Studies, pp. 1–16. doi:10.1080/03003930.2019.1708726
3. Liu, Q., & Wang, H. (2015) Research on the forecast and development of China’s public fiscal revenue based on ARIMA model. Theoretical Economics Letters, vol. 5, no. 04, pp. 482–493. doi: 10.4236/tel.2015.54057
4. Sabaj, E., & Kahveci, M. (2018) Forecasting tax revenues in an emerging economy: The case of Albania. Available at: https://mpra.ub.uni-muenchen.de/84404/1/MPRA_paper_84404.pdf
5. Streimikiene, D., Raheem Ahmed, R., Vveinhardt, J., Ghauri, S. P., & Zahid, S. (2018) Forecasting tax revenues using time series techniques – a case of Pakistan. Economic Research-Ekonomska Istraživanja, vol. 31, no. 01, pp. 722–754. doi: 10.1080/1331677x.2018.1442236