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Inspecting debt servicing mechanism in Nigeria using ARMAX model of the Koyck-kind

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Języki publikacji
EN
Abstrakty
EN
The burden of external debt affects the wellbeing of an economy (or a country) by making the economy vulnerable to external shocks and crowding out investment. When dealing with debt management in indebted poor countries like Nigeria, the rational approach is to allocate a portion of export earnings for debt service payments. Along this line, there is a need to identify the link between debt servicing and export earnings. Hence, the current and long-run effects of export earnings on debt service payments are modelled as a single-input-single-output discrete-time dynamical system within the framework of the Autoregressive moving average explanatory input model of the Koyck kind (KARMAX). The KARMAX model is identified for Nigeria using data from the World Bank database from 1970 to 2018 based on the maximum likelihood (ML) method, and the obtained results are compared to the prediction error and the instrumental variable methods. From a theoretical perspective, the KARMAX specification identified by the ML method is more ideal and inspiring. By doing so, this article contributes to the literature on the econometrics of public debt management.
Rocznik
Strony
5--20
Opis fizyczny
Bibliogr. 30 poz., rys.
Twórcy
  • Department of Statistics, University of Benin, P.M.B. 1154, Benin City, Nigeria
  • Monetary Policy Department, Central Bank of Nigeria, Abuja
Bibliografia
  • [1] ABDULLAH F.A., Development of an advance warning indicator of external debt servicing vulnerability, J. Int. Bus. Stud., 1985, 16 (3), 135–141.
  • [2] ABDULLAHI M.M., ABU BAKAR BT. N.A., HASSAN S.B., Determining the macroeconomic factors of external debt accumulation in Nigeria. An ARDL bound test approach, Proc. Soc. Beh. Sci., 2015, 211, 745–752.
  • [3] AJAYI S.I., Macroeconomic approach to external debt. The case of Nigeria, AERC Research Paper 8, Initiatives Publishers, Nairobi 1991.
  • [4] AKPOKODJE G., The effect of export earnings fluctuations on capital formation in Nigeria, AERC Research Paper 103, Nairobi 2000.
  • [5] ANYANWU J.C., Nigerian Public Finance, Joanes Educational Publishers, Ltd., Onitsha 1997.
  • [6] ARSLANALP S., HENRY P.B., Is debt relief efficient?, J. Fin., 2005, 60 (2), 1017–1051.
  • [7] BASS F.M., CLARKE D.G., Testing distributed lag models of advertising effect, J. Market. Res., 1972, 9 (3), 298–308.
  • [8] BENJAMIN J.D., JUD G.D., OKORUWA A.A., Forecasting the stock of retail space using the Koyck distributed lag model, J. Prop. Res., 1993, 10 (3), 185–192, DOI: 10.1080/09599919308724092.
  • [9] EDO S., OSADOLOR N.E., DADING I.F., Growing external debt and declining export: The concurrent impediments in economic growth of sub-Saharan African countries, Int. Econ., 2019, DOI: 10.1016 j.inteco.2019.11.013
  • [10] EKHOSUEHI V.U., OSAGIEDE A.A., A debt model for LDCs and HIPCs, ABACUS: J. Math. Assoc. Nigeria, 2007, 34 (2B), 447–451.
  • [11] ESSIEN S.N., AGBOEGBULEM N.T.I., MBA M.K., ONUMONU O.G., An empirical analysis of the macroeconomic impact of public debt in Nigeria, CBN J. Appl. Stat., 2016, 7 (1), 125–145.
  • [12] FRANSES P.H., VAN OEST R., On the econometrics of the geometric lag model, Econ. Lett., 2007, 95, 291–296, DOI:10.1016/j.econlet.2006.10.023.
  • [13] GÜLER H., GÜLTAY B., KAÇIRANLAR S., Comparisons of the alternative biased estimators for the distributed lag models, Comm. Stat. Sim. Comp., 2015, DOI:10.1080/03610918.2015.1053919.
  • [14] HANNAN E.J., DUNSMUIR W.T.M., DEISTLER M., Estimation of vector ARMAX models, J. Multiv. Anal., 1980, 10, 275–295.
  • [15] JIA L.-J., KANAE S., YANG Z.-J., WADA K., On parameter estimation of ARMAX model via BCLS method, IFAC Syst. Ident., Rotterdam 2003, 1113–1118.
  • [16] KOUTSOYIANNIS A., Theory of Econometrics, 2nd Ed., Pakgrave, New York 1977.
  • [17] LAGARIAS J.C., Effects of misspecification of lag structure in certain two-variable distributed lag models, Computers Math. Appl., 1991, 22 (10), 3–23.
  • [18] LUND P.J., MINER D.A., The nature of the error term in distributed lag models, Appl. Econ., 1975, 7 (3), 185–194, DOI: 10.1080/00036847500000020.
  • [19] MEI L., LI H., ZHOU Y., WANG W., XING F., Substructural damage detection in shear structures via ARMAX model and optimal subpattern assignment distance, Eng. Struct., 2019, 191, 625–639, https://doi.org/10.1016/j.engstruct.2019.04.084
  • [20] MUHANJI S., OJAH K., Management and sustainability of external debt: A focus on the emerging economies of Africa, Rev. Dev. Fin., 2011, 1, 184–206.
  • [21] MUHANJI S., OJAH K., External shocks and persistence of external debt in open vulnerable economies: The case of Africa, Econ. Model., 2011, 28, 1615–1628.
  • [22] OBADAN M.I., External debt and management policy, [In:] M.A. Iyoha, C.O. Itsede (Eds.), Nigerian Economy: Structure, Growth and Development, Mindex Publishing, Benin City 2002, 327–350.
  • [23] OMOTOSHO B.S., BAWA S., DOGUWA S.I., Determining the optimal public debt threshold for Nigeria, CBN J. Appl. Stat., 2016, 7 (2), 1–25.
  • [24] OSAGIEDE A.A., EKHOSUEHI V.U., Extending entropy stability measure to external debt structure, J. Sci. Technol., 2007, 27 (3), 156–162.
  • [25] QURESHI I., LIAQAT Z., The long-term consequences of external debt: Revisiting the evidence and inspecting the mechanism using panel VARs, J. Macroecon., 2020, 63, 103–184, https://doi.org/10.1016 /j.jmacro.2019.103184
  • [26] RAHEEM M.I., Assessing and managing external debt problems in Nigeria, World Dev., 1994, 22 (8), 1223–1242.
  • [27] SIDDIQUE A., SELVANATHAN E.A., SELVANATHAN S., The impact of external debt on growth. Evidence from Highly Indebted Poor Countries, J. Pol. Model., 2016, http://dx.doi.org/10.1016/j.jpolmod.2016.03.011
  • [28] SANUSI G.P., The impact of oil export earnings on Nigeria’s external debt, Working Paper, International Association for Energy Economics, USA, 2010.
  • [29] THEIL H., FIEBIG D., A maximum entropy approach to the specification of distributed lags, Econ. Lett., 1981, 7, 339–342.
  • [30] ZHENG W.X., On least-squares identification of ARMAX models, 15th Triennial World Congress, Barcelona, Spain, 2002, 391–396.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0bc8e0d0-ef8d-4a4b-9289-7f6fc4c9ea66
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