Modeling Bukhara Region’s Export Using The Arima Model
Keywords:
ARIMA model, Time series analysis, Export forecastingAbstract
The development of international trade is one of the key drivers of regional economic growth. In particular, the export potential of Bukhara region plays a significant role in the economy of Uzbekistan. This paper aims to analyze and forecast the dynamics of Bukhara’s exports by applying the Autoregressive Integrated Moving Average (ARIMA) model. Using time series data on exports, the study identifies the optimal ARIMA specification, evaluates its statistical significance, and provides short-term forecasts. The results can support policymakers and entrepreneurs in designing effective export strategies.
References
Box, G. E. P., & Jenkins, G. M. (1976). Time series analysis: Forecasting and control (Revised ed.). San Francisco: Holden-Day.
Gujarati, D. N., & Porter, D. C. (2009). Basic econometrics (5th ed.). New York: McGraw-Hill.
Hamilton, J. D. (1994). Time series analysis. Princeton, NJ: Princeton University Press.
Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and practice (2nd ed.). Melbourne: OTexts.
Makridakis, S., Wheelwright, S. C., & Hyndman, R. J. (1998). Forecasting: Methods and applications (3rd ed.). New York: John Wiley & Sons.
Pindyck, R. S., & Rubinfeld, D. L. (1998). Econometric models and economic forecasts (4th ed.). Boston: Irwin McGraw-Hill.
State Committee of the Republic of Uzbekistan on Statistics. (2024). Foreign trade statistics of Bukhara region. Tashkent: Stat.uz.
Uzbekistan Ministry of Investments and Foreign Trade. (2023). Annual report on foreign trade development. Tashkent: MIFT.
Mioji, Y. (2023). Measuring the impact of trade protection on industrial production. [Working paper].
OECD. (2024). Terms of trade (indicator). Retrieved April 3, 2024, from https://data.oecd.org
Oteng-Abayie, E. F., & Frimpong, J. M. (2006). Bounds testing approach to cointegration: An examination of foreign direct investment, trade and growth relationships. American Journal of Applied Sciences, 3(11), 2079–2085.
Pankratz, A. (1983). Forecasting with univariate Box–Jenkins models: Concepts and cases. Wiley Series in Probability and Mathematical Statistics. New York: John Wiley & Sons.
Reddy, K. K. (2020). Exports, imports and economic growth in India: An empirical analysis. Theoretical and Applied Economics, 27(4), 323–330.
Richardson, K. E. A., & Sulemana, M. B. (2023). Terms of trade, governance and household income in selected African countries. Journal of Economic Development Studies. Retrieved from https://www.sciencedirect.com
Si, Y. (2022). Using ARIMA model to analyse and predict Bitcoin price. BCP Business & Management, 34, 1210–1216. https://doi.org/10.54691/bcpbm.v34i.3161
Siraj-ud-Doulah, M. D., Hassan, M. D. Z., & Sukanta, M. D. R. I. (2020). Forecasting the production of jute based on time series models in Bangladesh. International Journal of Statistics and Applied Mathematics, 5(1), 32–38.
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