American Journal of Theoretical and Applied Statistics 2019; 8(6): 276-286 http://www.sciencepublishinggroup.com/j/ajtas doi: 10.11648/j.ajtas.20190806.18 ISSN: 2326-8999 (Print); ISSN: 2326-9006 (Online) Volatility of Internally Generated Revenue and Effects of Its Major Components: A Case of Akwa Ibom State, Nigeria Usoro Anthony Effiong, John Eme Eseme Department of Statistics, Faculty of Physical Sciences, Akwa Ibom State University, Mkpat Enin, Nigera Email address: To cite this article: Usoro Anthony Effiong, John Eme Eseme. Volatility of Internally Generated Revenue and Effects of Its Major Components: A Case of Akwa Ibom State, Nigeria. American Journal of Theoretical and Applied Statistics. Vol. 8, No. 6, 2019, pp. 276-286. doi: 10.11648/j.ajtas.20190806.19 Received: October 13, 2019; Accepted: November 12, 2019; Published: December 4, 2019 Abstract: In this work, volatility of Internally Generated Revenue of Akwa Ibom State with the contributory effects of its components was the major interest. Autoregressive Conditional Heteroscedasticity ARCH (1) model adopted revealed volatility in the IGR. This motivated investigation of the components as contributory factors to the volatility. The OLS regression of IGR volatility on the K-components revealed the contribution of each component to the IGR volatility. The F test result showed overall fitness of the regression model. Individual T test placed tax revenue volatility higher than any other component. The volatility in the tax revenue is explained by the inconsistency in the growing trend of the tax revenue. This is attributed to laxities in the revenue generation mechanism, therefore posing challenges to the revenue system. The revenue generation system in the state requires sound leadership in the Board of Internal Revenue, good revenue driven policy, transparent tax revenue consulting and innovative approaches by the labour force for improved revenue system. Government willingness to address the prevailing issues would enhance stability in the revenue generation, therefore, helping to reduce volatility and cope with the challenges of financial planning in Akwa Ibom State. Keywords: Volatility, Autoregressive Conditional Heteroscedasticity, Internally Generated Revenue, Tax Revenue 1. Introduction There is no gainsaying the fact that internally generated revenue, be it at the federal, state or local government level is a major concern as government desires to increase its revenue capacity so as to effectively surmount some financial challenges in a bid to offer needed services for development of the society. Apart from external aid, every level of government principally depends on two sources of revenue; the federation account and internally generated revenue. The role of internally generated revenue to the government cannot be overemphasized. This explains the reason for government commitment to increase in revenue generation. Revenue generation is observed to exhibit some non- linearity characteristics due to certain factors. In Akwa Ibom State, in particular, the relevant government authority saddled with the responsibility of revenue generation is Board of Internal Revenue. To complement the effort of the Board in boosting the revenue generation, different revenue consultants have been engaged by the state Government since 1995 to generate revenue for the state. The introduction of revenue consultants to the state was a hope for improved revenue generation and significant reduction in variability or discrepancy between the yearly budgeted and the actual IGR of the state. So far, the desired goal is yet to be achieved. High variability accounts for non-linearity of the revenue series. This explains the reason why some revenue researchers face challenges of inadequacy classical linear time series models in fitting revenue series due to non- linearity of the series. Facts have been established that most of the revenue series possess some characteristics of volatility clustering in certain time periods. This volatility describes wide swings of revenue for an extended time period followed by periods of short swings. Volatility periods are periods of high level of uncertainty in the revenue generation, antonymous with periods of relative calm which describe low variability between the expected and actual revenue. Like in financial time series, such as stock prices, exchange rates, inflation rates, volatility is of crucial