Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya

Anthony Makau

doi:doi:10.11648/j.ajtas.20170601.16

| Peer-Reviewed

Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya

Anthony Makau

Published in American Journal of Theoretical and Applied Statistics (Volume 6, Issue 1)

Received: 6 January 2017 Accepted: 16 January 2017 Published: 20 February 2017

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Despite Oil being one of the key drivers of the world economy, the recent fluctuations in oil prices has brought concerns about possible slowdowns in economic growth globally. To cushion their economies from these oil price volatility shocks, a number of developing countries have made structural reforms in their macroeconomic policies as far as domestic petroleum pricing system is concerned. In line with this, Kenya has undertaken to reform the energy sector so as to make it competitive, efficient as well as attracting investment in the sector. The main objective of this study was to investigate if volatility of oil price had an effect on Kenya’s GDP growth rate with Exchange rate and Inflation rate as intervening variables. The study used quarterly data from KNBS, CBK and ERC for the periods 2004 to 2013 to achieve its objective and all analysis were done in R. Analysis showed that fluctuation of Crude oil price in the international market coupled with fluctuations in the exchange rate and inflation rate determined 86.9 per cent of the trend in GDP growth rate. The study found that when crude oil price increases by KSh 1,000 per barrel, the Kenya shilling weakens by a single Kenya shilling for every US dollar and the inflation rate goes up by 1 per cent, then the GDP growth rate decreases by 0.132 percentage points (p=0.000). The study also found that the model used had no serial autocorrelation meaning that the error terms of the regression model at any given two different quarters were linearly uncorrelated. Moreover, Goldfeld-Quandt test statistic was found to be significantly higher than 5% or 1% significance levels. This was despite a plot graph of residuals vs the fitted values of GDP growth rate showing unequal distribution of residuals as the values of fitted GDP growth rate increased. Therefore the model was free from heteroscedasticity. The government should therefore focus on stabilizing exchange rate, increase domestic energy production to reduce reliance on importation of petroleum products and control the level of inflation.

Published in	American Journal of Theoretical and Applied Statistics (Volume 6, Issue 1)
DOI	10.11648/j.ajtas.20170601.16
Page(s)	44-51
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Ordinary Least Square, Balance of Payments, Best Linear Unbiased Estimator, Foreign Direct Investment, Heteroscedasticity, Serial Autocorrelation

References

[1]	Jiménez-Rodríguez, R., & Sánchez, M. (2005). Oil price shocks and real GDP growth: empirical evidence for some OECD countries. Applied economics, 37 (2), 201-228.
[2]	Jin, G. (2008). The Impact of Oil Price Shock and Exchange Rate Volatility on Economic Growth: A comparative analysis for Russia, Japan, and China. Research Journal of International Studies, 8 (11), 98-111.
[3]	Mecheo, J., & Omiti, J. (2003). Petroleum market structure and pricing following deregulation. Institute of Policy Analysis and Research.
[4]	Li, Z., & Zhao, H. (2011). Not all demand oil shocks are alike: disentangling demand oil shocks in the crude oil market. Journal of Chinese Economic and Foreign Trade Studies, 4 (1), 28-44.
[5]	O'Neill, T. J., Penm, J., & Terrell, R. D. (2008). The role of higher oil prices: a case of major developed countries. Research in Finance, 24, 287-299.
[6]	Oriakhi, D. E., & Osaze, I. D. (2013). Oil Price Volatility and Its Consequences on the Growth of the Nigerian Economy: An Examination (1970-2010). Asian Economic and Financial Review, 3 (5), 683.
[7]	Chuku, C. A., Effiong, E. L., & Sam, N. R. (2010). Oil price distortions and their short-and-long-run impacts on the Nigerian economy. In Proceedings of the 51st Annual Conference of the Nigerian Economic Society.
[8]	Gonzalez, A., & Nabiyev, S. (2009). Oil price fluctuations and its effect on GDP growth: A case study of USA and Sweden. Jonkoping International Business School.
[9]	Pindyck, R. S. & Rubinfeld, D. L. (1998). Econometric Models and Economic Forecasts, 4thEdition, Irwin/McGraw-Hill.
[10]	Gujarati, D. N. (2004). Basic Econometrics, 4^thEdition, the McGraw−Hill Companies.
[11]	Goldfeld, S. M. & Quandt, R. E. (1965). Some Tests for Homoskedasticity. Journal of the American Statistical Association. 60, 539–547.

Cite This Article

Plain Text BibTeX RIS

APA Style

Anthony Makau. (2017). Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya. American Journal of Theoretical and Applied Statistics, 6(1), 44-51. https://doi.org/10.11648/j.ajtas.20170601.16

Copy | Download

ACS Style

Anthony Makau. Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya. Am. J. Theor. Appl. Stat. 2017, 6(1), 44-51. doi: 10.11648/j.ajtas.20170601.16

Copy | Download

AMA Style

Anthony Makau. Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya. Am J Theor Appl Stat. 2017;6(1):44-51. doi: 10.11648/j.ajtas.20170601.16

Copy | Download

@article{10.11648/j.ajtas.20170601.16,
  author = {Anthony Makau},
  title = {Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {6},
  number = {1},
  pages = {44-51},
  doi = {10.11648/j.ajtas.20170601.16},
  url = {https://doi.org/10.11648/j.ajtas.20170601.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20170601.16},
  abstract = {Despite Oil being one of the key drivers of the world economy, the recent fluctuations in oil prices has brought concerns about possible slowdowns in economic growth globally. To cushion their economies from these oil price volatility shocks, a number of developing countries have made structural reforms in their macroeconomic policies as far as domestic petroleum pricing system is concerned. In line with this, Kenya has undertaken to reform the energy sector so as to make it competitive, efficient as well as attracting investment in the sector. The main objective of this study was to investigate if volatility of oil price had an effect on Kenya’s GDP growth rate with Exchange rate and Inflation rate as intervening variables. The study used quarterly data from KNBS, CBK and ERC for the periods 2004 to 2013 to achieve its objective and all analysis were done in R. Analysis showed that fluctuation of Crude oil price in the international market coupled with fluctuations in the exchange rate and inflation rate determined 86.9 per cent of the trend in GDP growth rate. The study found that when crude oil price increases by KSh 1,000 per barrel, the Kenya shilling weakens by a single Kenya shilling for every US dollar and the inflation rate goes up by 1 per cent, then the GDP growth rate decreases by 0.132 percentage points (p=0.000). The study also found that the model used had no serial autocorrelation meaning that the error terms of the regression model at any given two different quarters were linearly uncorrelated. Moreover, Goldfeld-Quandt test statistic was found to be significantly higher than 5% or 1% significance levels. This was despite a plot graph of residuals vs the fitted values of GDP growth rate showing unequal distribution of residuals as the values of fitted GDP growth rate increased. Therefore the model was free from heteroscedasticity. The government should therefore focus on stabilizing exchange rate, increase domestic energy production to reduce reliance on importation of petroleum products and control the level of inflation.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya
AU  - Anthony Makau
Y1  - 2017/02/20
PY  - 2017
N1  - https://doi.org/10.11648/j.ajtas.20170601.16
DO  - 10.11648/j.ajtas.20170601.16
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 44
EP  - 51
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20170601.16
AB  - Despite Oil being one of the key drivers of the world economy, the recent fluctuations in oil prices has brought concerns about possible slowdowns in economic growth globally. To cushion their economies from these oil price volatility shocks, a number of developing countries have made structural reforms in their macroeconomic policies as far as domestic petroleum pricing system is concerned. In line with this, Kenya has undertaken to reform the energy sector so as to make it competitive, efficient as well as attracting investment in the sector. The main objective of this study was to investigate if volatility of oil price had an effect on Kenya’s GDP growth rate with Exchange rate and Inflation rate as intervening variables. The study used quarterly data from KNBS, CBK and ERC for the periods 2004 to 2013 to achieve its objective and all analysis were done in R. Analysis showed that fluctuation of Crude oil price in the international market coupled with fluctuations in the exchange rate and inflation rate determined 86.9 per cent of the trend in GDP growth rate. The study found that when crude oil price increases by KSh 1,000 per barrel, the Kenya shilling weakens by a single Kenya shilling for every US dollar and the inflation rate goes up by 1 per cent, then the GDP growth rate decreases by 0.132 percentage points (p=0.000). The study also found that the model used had no serial autocorrelation meaning that the error terms of the regression model at any given two different quarters were linearly uncorrelated. Moreover, Goldfeld-Quandt test statistic was found to be significantly higher than 5% or 1% significance levels. This was despite a plot graph of residuals vs the fitted values of GDP growth rate showing unequal distribution of residuals as the values of fitted GDP growth rate increased. Therefore the model was free from heteroscedasticity. The government should therefore focus on stabilizing exchange rate, increase domestic energy production to reduce reliance on importation of petroleum products and control the level of inflation.
VL  - 6
IS  - 1
ER  -

Copy | Download

Author Information

Anthony Makau

Macroeconomic Statistics, Kenya National Bureau of Statistics, Nairobi, Kenya

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Anthony Makau. (2017). Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya. American Journal of Theoretical and Applied Statistics, 6(1), 44-51. https://doi.org/10.11648/j.ajtas.20170601.16

Copy | Download

ACS Style

Anthony Makau. Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya. Am. J. Theor. Appl. Stat. 2017, 6(1), 44-51. doi: 10.11648/j.ajtas.20170601.16

Copy | Download

AMA Style

Anthony Makau. Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya. Am J Theor Appl Stat. 2017;6(1):44-51. doi: 10.11648/j.ajtas.20170601.16

Copy | Download

@article{10.11648/j.ajtas.20170601.16,
  author = {Anthony Makau},
  title = {Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {6},
  number = {1},
  pages = {44-51},
  doi = {10.11648/j.ajtas.20170601.16},
  url = {https://doi.org/10.11648/j.ajtas.20170601.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20170601.16},
  abstract = {Despite Oil being one of the key drivers of the world economy, the recent fluctuations in oil prices has brought concerns about possible slowdowns in economic growth globally. To cushion their economies from these oil price volatility shocks, a number of developing countries have made structural reforms in their macroeconomic policies as far as domestic petroleum pricing system is concerned. In line with this, Kenya has undertaken to reform the energy sector so as to make it competitive, efficient as well as attracting investment in the sector. The main objective of this study was to investigate if volatility of oil price had an effect on Kenya’s GDP growth rate with Exchange rate and Inflation rate as intervening variables. The study used quarterly data from KNBS, CBK and ERC for the periods 2004 to 2013 to achieve its objective and all analysis were done in R. Analysis showed that fluctuation of Crude oil price in the international market coupled with fluctuations in the exchange rate and inflation rate determined 86.9 per cent of the trend in GDP growth rate. The study found that when crude oil price increases by KSh 1,000 per barrel, the Kenya shilling weakens by a single Kenya shilling for every US dollar and the inflation rate goes up by 1 per cent, then the GDP growth rate decreases by 0.132 percentage points (p=0.000). The study also found that the model used had no serial autocorrelation meaning that the error terms of the regression model at any given two different quarters were linearly uncorrelated. Moreover, Goldfeld-Quandt test statistic was found to be significantly higher than 5% or 1% significance levels. This was despite a plot graph of residuals vs the fitted values of GDP growth rate showing unequal distribution of residuals as the values of fitted GDP growth rate increased. Therefore the model was free from heteroscedasticity. The government should therefore focus on stabilizing exchange rate, increase domestic energy production to reduce reliance on importation of petroleum products and control the level of inflation.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Multivariate Regression Analysis of Oil Price Volatility on GDP Growth in Kenya
AU  - Anthony Makau
Y1  - 2017/02/20
PY  - 2017
N1  - https://doi.org/10.11648/j.ajtas.20170601.16
DO  - 10.11648/j.ajtas.20170601.16
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 44
EP  - 51
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20170601.16
AB  - Despite Oil being one of the key drivers of the world economy, the recent fluctuations in oil prices has brought concerns about possible slowdowns in economic growth globally. To cushion their economies from these oil price volatility shocks, a number of developing countries have made structural reforms in their macroeconomic policies as far as domestic petroleum pricing system is concerned. In line with this, Kenya has undertaken to reform the energy sector so as to make it competitive, efficient as well as attracting investment in the sector. The main objective of this study was to investigate if volatility of oil price had an effect on Kenya’s GDP growth rate with Exchange rate and Inflation rate as intervening variables. The study used quarterly data from KNBS, CBK and ERC for the periods 2004 to 2013 to achieve its objective and all analysis were done in R. Analysis showed that fluctuation of Crude oil price in the international market coupled with fluctuations in the exchange rate and inflation rate determined 86.9 per cent of the trend in GDP growth rate. The study found that when crude oil price increases by KSh 1,000 per barrel, the Kenya shilling weakens by a single Kenya shilling for every US dollar and the inflation rate goes up by 1 per cent, then the GDP growth rate decreases by 0.132 percentage points (p=0.000). The study also found that the model used had no serial autocorrelation meaning that the error terms of the regression model at any given two different quarters were linearly uncorrelated. Moreover, Goldfeld-Quandt test statistic was found to be significantly higher than 5% or 1% significance levels. This was despite a plot graph of residuals vs the fitted values of GDP growth rate showing unequal distribution of residuals as the values of fitted GDP growth rate increased. Therefore the model was free from heteroscedasticity. The government should therefore focus on stabilizing exchange rate, increase domestic energy production to reduce reliance on importation of petroleum products and control the level of inflation.
VL  - 6
IS  - 1
ER  -

Copy | Download