PL EN


Preferences help
enabled [disable] Abstract
Number of results
2019 | 134 | 2 | 326-334
Article title

Modeling the Impact of Agriculture, Export Earnings and Inflation on Gross Domestic Product Using the Generalized Least Square (GLS) Approach

Content
Title variants
Languages of publication
EN
Abstracts
EN
The paper explored the impact of Agriculture, export earnings and inflation on gross domestic product (GDP). Time series data were obtained from the central bank of Nigeria statistical bulletin from 1981 to 2018. Each series consist of 38 observations. Evidence from our study showed that the predictor variables (Agriculture, export earnings and inflation) were significantly joint predictors of Gross Domestic Product. The predictor variables jointly explained 68.958% of GDP. Result of the analysis also revealed that both agriculture and export earnings have a positive impact on gross domestic product reaffirming the importance of the sectors to economic growth while inflation has a negative impact on gross domestic product. With evidence that agriculture has the potential to cause economic growth, spur industrialization as well as to enhance the living condition of the nation’s majority, there should be increased investment in the development of the sector. This study also revealed that inflation is detrimental to sustainable economic growth in Nigeria. The result has important policy implications for both domestic policy makers and development partners. It also implies that controlling inflation is a necessary condition for promoting economic growth. Thus, policy makers should focus on maintaining inflation at a low rate probably single digit.
Year
Volume
134
Issue
2
Pages
326-334
Physical description
Contributors
  • Department of Mathematical Sciences, Abubakar Tafawa Balewa University, Bauchi, Nigeria
author
  • Department of Mathematical Sciences, Abubakar Tafawa Balewa University, Bauchi, Nigeria
  • Department of Mathematical Sciences, Bauchi State University Gadau, Nigeria
References
  • [1] Alphonsus and Moffat (2018). Modelling the Auto correlated Errors in Time Series Regression: A Generalized Least Squares Approach. Journal of Advances in Mathematics and Computer Science, 26(4): 1-15.
  • [2] Safi, Samir and White, Alexander (2006). The Efficiency of OLS In The Presence Of Auto-Correlated Disturbances in Regression Models. Journal of Modern Applied Statistical Methods 5(1). DOI: 10.22237/jmasm/1146456540
  • [3] Koreisha, S. G. and Fang, Y. (2002). Generalized least squares with misspecifiedSerial correlation structures. Journal of the Royal Statistical Society, 63, Series B, 515-531.
  • [4] Koreisha, S. G. and Fang, Y. (2004). Forecasting with serially correlated regression models. Journal of Statistical Computations and Simulation, 74, 625-649.
  • [5] Kramer, W. (1980). Finite sample efficiency of ordinary least squares in the linear regression model with autocorrelated errors. Journal of the American Statistical Association, 75, 1005-1009
  • [6] Ullah, A., Srivastava, V. K., Magee, L., & Srivastava, A. (1983). Estimation of linear regression model with autocorrelated disturbances. Journal of Time Series Analysis, 4, 127-135
  • [7] Choudhury, A., Hubata, R. & Louis, R. (1999). Understanding time-series regression estimators. The American Statistician, 53, 342-348.
  • [8] Adeleke K.M (2014). Impact of Foreign Direct Investment on Nigeria Economic Growth. International Journal of Academic Research in Business and Social Sciences 4(8), 234-242
  • [9] Pankratz A. Forecasting with dynamic regressions models. 3rded. New York, John Wiley and Sons; 1991.
  • [10] Dalgaard P. Introductory statistics with R. 2nd Ed. Springer. 2008; 228.
  • [11] Moffat IU, Akpan EA. Modeling and forecasting trend function of a discrete-time stochastic process. American Journal of Scientific and Industrial Research 2014; 56: 195-202.
  • [12] Breusch TS. Testing for autocorrelation in dynamic linear models. Australian Economic Papers 1978; 17: 334–355
  • [13] Akpan EA, Moffat IU, Ekpo NB. Modeling regression with time series errors of gross domestic product on government expenditure. International Journal of Innovation and Applied Studies 2016; 18(4): 990-996.
  • [14] Tolulope and Chinonso E. Contribution of Agriculture to Economic Growth in Nigeria1. The 18th Annual Conference of the African Econometric Society (AES) Accra, Ghana at the session organized by the Association for the Advancement of African Women Economists (AAAWE), 22nd and 23rd July, 2013.
  • [15] Faraji K and Kenani M (2013). Impact of Inflation on Economic Growth: A Case Study of Tanzania. Asian Journal of Empirical Research 3(8): 363-380
Document Type
short_communication
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.psjd-18960dea-2892-4c99-97d7-443a1ddce478
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.