Artikel

Agricultural finance and economic growth: Evidence from Nigeria

The study performed an in-depth examination of the impact of guaranteed agricultural finance to oil palm, cocoa, groundnuts, fishery, poultry, cattle, roots, and tubers on the real gross domestic product of the country. Time series data was sourced from the Central Bank of Nigeria statistical bulletin of various issues. The data sets covered thirty-seven (37) years spanning from 1981 to 2017. The study used Autoregressive Distributed Lag (ARDL) model for its analysis. However, prior estimation and due to several exogenous variables, Phillip Perron stationarity test was used to determine the order of integration because of its robustness to serial correlation and heteroskedasticity. The study also specified the lag criterion based on LR, FPE, AIC, SC, and HQ using Newey-West covariance matrix estimator. Findings from both short-run and long-run models as confirmed by the Wald test, which shows that none of the guaranteed agricultural finance is statistically significant to real gross domestic product. The study, therefore, recommends increased funding and deliberate efforts at determining which of the nominated agricultural spending has the most contributory impact on growth.

Sprache
Englisch

Erschienen in
Journal: Verslas: Teorija ir praktika / Business: Theory and Practice ; ISSN: 1822-4202 ; Volume: 20 ; Year: 2019 ; Pages: 467-475 ; Vilnius: Vilnius Gediminas Technical University

Klassifikation
Management
Agricultural Finance
Agricultural Policy; Food Policy
Collectives; Communes; Agriculture
Thema
agriculture
finance
real gross domestic product
Phillip Perron
Wald Test
autoregressive distributed lag

Ereignis
Geistige Schöpfung
(wer)
Okunlola, Funso Abiodun
Osuma, Godswill
Omankhanlen, Alex
Ereignis
Veröffentlichung
(wer)
Vilnius Gediminas Technical University
(wo)
Vilnius
(wann)
2019

DOI
doi:10.3846/btp.2019.43
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Okunlola, Funso Abiodun
  • Osuma, Godswill
  • Omankhanlen, Alex
  • Vilnius Gediminas Technical University

Entstanden

  • 2019

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