Forecasting of foreign direct investments in Ukraine on the base of ARIMA-models

Bohdan Kyshakevych
Doctor of Economics, Professor, Head of Economics and Management Department, Ivan Franko Drohobych State Pedagogical University, Ukraine, e-mail: b_kyshakevych@ukr.net, ORCID ID: https://orcid.org/0000-0001-5721-8543

Maryna Nakhayeva
Postgraduate Student, Economics and Management Department, Ivan Franko Drohobych State Pedagogical University, Ukraine, e-mail: nachajevamaryna@ukr.net, ORCID ID: https://orcid.org/0000-0002-0587-6410

Cite this article:

Kyshakevych, B., Nakhaeva, M. (2018). Forecasting of foreign direct investments in Ukraine on the base of ARIMA-models. Ed.: M. Zveryakov (ed.-in-ch.) and others [Prohnozuvannia priamykh inozemnykh investytsii v Ukrainu za dopomohoiu ARIMA-modelei; za red.: М. I. Zveriakova (gol. red.) ta in.], Socio-economic research bulletin; Vìsnik socìal’no-ekonomìčnih doslìdžen’ (ISSN 2313-4569), Odessa National Economic University, Odessa, No. 2 (66), pp. 233‒243.

Abstract

The article analyzes the problematic aspects of constructing the models of forecasting foreign direct investment in Ukraine. The expediency of using the autoregressive integrated moving average methodology for this purpose is justified. The transformation method of non-stationary time series of direct foreign investments into Ukraine to the stationary type is proposed. In order to be able to use the ARIMA-model, the output time series have been converted to static ones using the Statistica package by two-step transformation. Firstly, smoothing based on a simple moving average for the two points and then subtraction of the linear trend have been conducted. The ARIMA-model (2,0,0) has shown the lowest error values for MSE, AIC and BIC, indicating that it approximates the time series of FDI in Ukraine for the analyzed period in the best way and can be selected for short-term forecasting. The obtained ARIMA- model (2,0,0) statistical parameters of foreign direct investment prediction in Ukraine prove the adequacy of ARIMA-model and suitability for the formation of short-term forecasts. The forecast of foreign direct investment in Ukraine for 2018 based on the proposed ARIMA-model (2,0,0) in fact coincides with the forecasts of most investment companies and the National Bank of Ukraine. The article emphasizes that despite the series of measures aimed to deregulate the economy, which have been adopted by the government, investors are still afraid to invest in Ukraine due to the high level of corruption, slow implementation of reforms and unstable economy. It is stressed that without cardinal improvement of business climate and investment attractiveness, an increase in investment or rapid economic development in Ukraine should not been expected.

Keywords

direct foreign investments; ARIMA-model; time series; forecasting; rolling average; subtraction of trend; Statistica.

JEL classification: C220; F210; O160; DOI: https://doi.org/10.33987/vsed.2(66).2018.233-243

UD classification: 330.5:330.4

References

1. Al-Abdulrazag, B., Bataineh, T. M. (2007). Causal relationship between foreign direct investment and savings in Jordan: an error correction model, International Management Review, No. 3 (4), pp. 12‒18.
2. Prasanna, Perera (2015). Modeling and forecasting foreign direct investment (FDI) into SAARC for the period of 2013‒2037 with ARIMA, International Journal of Business and Social Science. Vol. 6, No. 2, February 2015, pp. 264‒272.
3. K. Nithya, Kala, Aruna P., Remesh (2018). Forecasting foreign direct investment inflows into India using ARIMA model, International Journal of Research, Vol. 05, Issue 04, February 2018, pp. 1564‒1570.
4. Kyshakevych, B. Y., Nakhaeva, M. M. (2017). Methods of estimation of regions’ investment attractiveness [Metody otsiniuvannia investytsiinoi pryvablyvosti rehioniv], Ekonomichnyi prostir, PDABA Ukrainy, Dnipropetrovsk, No. 128, s. 71‒80 [in Ukrainian]
5. Kyshakevych, B. Y. (2011). Stress testing of banks’ loan portfolio based on multi-factor models [Stres testuvannia kredytnoho portfelia banku na osnovi bahatofaktornykh modelei], Ekonomichnyi prostir, PDABA Ukrainy, Dnipropetrovsk, No. 45, s. 161‒171 [in Ukrainian]
6. Kyshakevych, B. Y., Prykarpatskyi, A. K., Tverdokhlib, I. P. (2009). The analysis of optimal strategies of the portfolio competitive model of the stock market [Analiz optymalnykh stratehii portfelnoi konkurentsiinoi modeli rynku aktsii], Dopovidi Natsionalnoi Akademii Nauk Ukrainy, No. 1, s. 40‒47 [in Ukrainian]
7. Demirhan, Erdal, Mahmut Masca (2009). Determinants of foreign direct investment flows to developing countries: a cross-sectional analysis, Prague Economic Papers, University of Economics, Prague, Vol. 4, pp. 356‒369.
8. Abhijit, Biswas (2015). Forecasting net foreign direct investment inflows in India: Box-Jenkins ARIMA model, IJMBS, Vol. 5, Issue 3, pp. 49‒58.
9. World Bank official website [Ofitsiinyi sait Svitovoho banku], available at: https://data.worldbank.org/indicator/BX.KLT.DINV.WD.GD.ZS?end=2017&start=1990&view=chart [in Ukrainian]
10. Official site of the State Statistics Service of Ukraine [Ofitsiinyi sait Derzhavnoi sluzhby statystyky Ukrainy], available at: http://www.ukrstat.gov.ua [in Ukrainian]
11. Foreign business in Ukraine: will the investments come in 2017? BBC Official Site. News from January 26, 2017 [Inozemnyi biznes v Ukraini: chy pryidut investytsii u 2017 rotsi? Ofitsiinyi sait BBC. Novyny vid 26 sichnia 2017], available at: https://www.bbc.com/ukrainian/news-38758419 [in Ukrainian]