Hooker’s study on interrelation between oil price and macroeconomy
This paper is focused on the literature review of five papers that focus attention on the relationship that exists between the oil prices and the macroeconomic variables that prevail in the economy. The last review specifically focuses on China.
The paper written by Hooker, (1996) investigates the interrelation that holds between the oil price fluctuations and the variables of the macro economy. This relationship involves three different statistical methods to explore the relationship which are namely – firstly, the Vector Auto Regression (VAR) method is applied. In this method, it is predominantly observed that in and around the year 1973, the macroeconomic variables in the US suffered from many structural breaks and were not able to account for the fluctuation of oil prices thereby there was a weakening of the oil prices that were measured. Secondly, before the benchmark year 1973, the prices of oil were exogenous in nature and as of now, the prices of oil have become endogenous. A multivariable VAR of Granger Causality allocates a more specific and smaller role to the prices of oil. Thirdly, the fluctuations in oil prices were very asymmetric in nature. The results obtained by the author were that the fall in the prices of oil failed to account for the mismeasurement. The dominant macroeconomic variable considered in this paper is the FDP growth rate. There was possibly a structural break in the GDP growth rate around the year 1973 but this structural break was not held responsible for the oscillations in the price of oil. This break also did not alter the results obtained by the Granger Causality method. At around the period 1973, the prices of oil were exogenous, unlike the current times where the prices of oil are endogenous. This result was especially with respect to the US macroeconomy. The asymmetrical fluctuations of the prices of oil were consistent with the transformation of the prices of oil, but this consistency proved a failure to the Granger cause macro indicators since 1973. There were OPEC shocks prevailing at that time and these shocks proved of much importance these prices of oil seemed to be in connection with the recession that took place in 1974-75. In 1980-82, there was a recession too and this was partially responsible. Since 1981, the prices of oil began to fall and this reduction in the prices of oil was responsible for the relationship between the macroeconomic indicators and the oil price. The dominant Vector Auto Regression variables used in this paper are the three-month Treasury bill rate, unemployment rate or the real GDP, and the import price deflator and GDP deflator.
According to the paper written by Farhani, (2012), the reduction in the GDP growth was due to the two oil shocks that occurred in the year 1970. Since that year, there has been a consistent slowdown in the economic activities in the world and this was predominantly due to the fact that the prices of oil have been on the constant rise since 1970. This paper fundamentally estimates the SLRM (Simple Linear Regression Model), the VAR (Vector Auto Regression) model, and the DLRM (Dynamic Linear Regression Model) to examine the effect that the prices of oil have made on the economic growth of the macroeconomic variables in the US. The predominant results of this paper designate that the connection between the prices of oil and the macroeconomic indicators is very weak. There was a history of the presence of breakpoints and this existence enhanced the low significant effect and the asymmetric fluctuations in the prices of oil were also to be held responsible for this weak relationship. According to the author, the OECD (Organization for Economic Cooperation and Development) and the IEA (International Energy Agency) 2012 reported the oil market prices. According to this report, it was observed that the market prices of oil were an extremely important energy source and this itself proved itself as an important factor that enhances the growth and development of the economic sectors such as transport, agriculture, electricity, industry, and the other sectors which were noneconomic in nature such as the military service. Moreover, the paper predicts that the prices of oil have skyrocketed in the last decade and this rise may have an effect on the economic conditions of the countries since these economic activities are largely based on the consumption of huge quantities of oil. As a result, the demand for oil production increased as well the supply of oil production decreased while there was an increase in the extraction and refining cost and also the level of import. As mentioned earlier, the oil prices had asymmetric fluctuations. This paper aims to study the increases in oil prices and the decreases in oil prices separately. The results of this paper pertain to the fact that the changes in the prices of oil which were remarkable were due to changes of more than one factor or cause. Since the change accrues to more than one factor, therefore the paper determines to search for the sources and the effect of the oil prices on the macroeconomic variables. The results of this paper were that the DLRM and the SLRM can present non-significant coefficients as well as a weakening effect in the direct interconnection between oil prices and the macroeconomic variables. Hence, the paper first used a breakpoints detection test, and secondly, the paper used VECM by establishing factors that do not have a weakening relationship thereby improving the results. Hence, the author concluded that as there is economic growth, the prices of oil tend to increase.
Farhani’s study on weak connection between oil prices and macroeconomic indicators
On the other hand, the previous paper by Hooker established the link between the prices of oil and the GDP growth rate and investigated the breakpoints in that relationship and the resultant report was that the economy of the US had been denoted by the 1973 change since there was a stark change of oil prices before 1973 and after 1973.
Since the commencement of World War II, there has been an increase in the trend for the prices of oil. The author holds the recessions of the US responsible for this spike in prices (Hamilton, 2008). The author of this paper wanted to investigate whether this merely accrued as a coincidence and hence the real GDP growth rates were regressed on lagged changes in GDP growth rates as well as the logarithmic changes in the prices of oil. The paper also investigated another possibility of the alliance between the oil prices and the output. The paper uses the statistical method of OLS estimation to find out the relation of the t-statistic. The null hypothesis for this method was that the lagged oil prices had definite coefficients which were all zero. This null hypothesis was rejected and the p-value for this method was found to be 0.005. This method was also followed by other authors in their respective papers where even those authors rejected the null hypothesis and concluded that the relationship that exists between the prices of oil and the amount of output as just a statistical coincidence. This third possibility accrued to a third factor(s) which can possibly be a cause for the spike in the prices of oil as well as the recession. The author says that this could really not be predicted at least in the early years of the post-war period since the economy was disrupted. The author says that the hike in the prices of oil during the early post-war years could also accrue to the military conflicts that prevailed at that time and this was supposed to be an exogenous factor. The paper says that the economic decisions which are taken by the economy should be based on the real changes in the prices of oil rather than the nominal alterations in the oil prices. Generally, the size of any given shock moves in the direction of nominal prices. However, when the sample gets selected, the early part involves a generic frozenness of the nominal prices for a number of years, and then suddenly the nominal prices adjust themselves. The real prices generally are a result of the convergence of two factors that are – the events like the Suez Crisis which was responsible for the entire movement of the nominal prices between the years 1955-1965, and the second one is the change in the inflation that are based on a quarter-to-quarter basis and is a fully endogenous process with regard to the economy. The output of this change in inflation is also probable to be different from the output achieved from an oil shock. The author concludes by saying that the shock in the prices of oil has another effect on the macroeconomic variable of the economy, that is, on the inflation rate.
The trend for the prices of oil since World War II
This is similar to the paper by Hooker which also reinforced the fact that the shocks in the prices of oil had an immense contribution in the inflation rate of the US before 1981 but since that year, these shocks in the prices of oil have had little or no contribution.
The paper written by Milani, (2009) investigates into the everlasting interconnection between the oil prices and the variables of the macroeconomy that are supposedly changing. The model in this paper uses the demand and supply forces and these invisible forces are affected by the prices of oil and the importance of oil in the process of consumption and production. The economy is also affected by the prices of oil through an additional channel mentioned in this paper, that is, the effect on the emergence of the belief of the agent. The paper focuses on the estimated learning dynamics that implies that the belief or the point of view of the economic agents regarding the oil prices and their relative effects on the macroeconomic variables and the changes that have occurred in these cause and effect relationships. It is noted here the effects of the prices of oil had large impacts on the macroeconomic variables like the output and the rate of inflation during the 1970s but since the mid-1980s this effect of the prices of oil on the economy became milder. This paper, unlike the other papers studied before, focuses primarily on the expectations of the economic agents and their immense role in the establishment of the macroeconomic variables like the output and the rate of inflation. This effect of the oil prices rises on presumptions can enlarge the reaction of the variables of the macroeconomy to the shocks in the prices of oil. The model that was studied in this paper, had formed responses of the macroeconomic variables studied in this article that is the output and the rate of inflation, to the shocks in the prices of oil were more noticeable in the 1970s rather than in 2008. Hence, coming through the time variation of the influence that the prices of oil have made on the economic agents’ belief, this article has remarkably explained how there was a weakening in the shocks in the prices of oil on real activity and the rate of inflation. The rational expectations of the economic agents involve a strong informational assumption that is predominantly relaxed in this article. This model uses the Bayesian method. The paper initially starts with a belief that the prices of oil have on the variables of the economy as a whole such as the output, the rate of inflation, and the monetary policy, and these macroeconomic variables are used to commence the process of learning and these factors are taken together and roughly calculated along with the rest of the model parameters. Later on, the economic agents do make an effort to acquire the knowledge of the coefficients through the process of constant-gain learning by constantly modernizing their estimates with the most updated version of the coefficients.
OLS regression analysis of relationship between oil prices and GDP growth rate
This paper resembles the results that have been achieved by Hooker and Hamilton, concluding that the changes in the prices of oil have had an impact on the US recessions and also on the stagflation that occurred during the 1970s. This effect in recent years has faded off.
The last article studied in this paper involves the link between the oil prices and their effect on the macroeconomic variables with respect to China specifically (Du, Yanan & Wei, 2010). It is a statistical-based paper that focuses predominantly on the time series which is on a basis that is calculated monthly generated from 1995:1 to 2008:12 which again utilizes the method of the multivariate Vector Auto Regression (VAR). This method was also used in the paper written by Mark Hooker. Much like the other paper, this paper also projects that the prices of oil have had an effect on the macroeconomic variables, this time specifically in China, and this impact or the relationship is non-linear in nature. The macroeconomic variables considered in this paper are economic growth and the rate of inflation. In contrast to this, as mentioned in the paper, the economic activities of China are not able to impact the prices of oil prevailing in the world market rate and this implies that the prices of oil in the world remain exogenous with regard to the macroeconomy of China when conducted on a time-series basis and also that China does not have enough market power in the world to influence the prices of oil. The tests conducted in this paper are the structural ability tests that exhibit the presence of a structural break in the VAR model due to the reforms that had taken place in the oil pricing mechanism of China therefore, it is vital to collapse the entire sample into various sub-samples so that the approximation of the model is correctly done. China is supposedly the second largest consumer country of the world oil standing in a position just after the US. In 2007, the entire amount of oil that was consumed by China alone had amounted to 366 million tons. Moreover, with the pace at which the world is moving into a phase of industrialization and urbanization along with China, which involves the ownership of private cars, it is inevitable that the demand for oil in China is likely to increase in the future. This paper concludes by saying that China is increasing its demand for oil and hence its share of the market power in the world is increasing. This paper does not only use the VAR method, but also employs the Granger Causality Test, the impulse-response function, the variance decomposition, and the structural ability test too. The paper involves three main results – firstly, the market power of China was not significant in influencing the world market price of oil till 2002:1. After this breakpoint, China slowly started to gain significance in the world market for oil and this also accrues to the fact that China was experiencing oil price mechanisms during that time. Secondly, according to the Granger Causality Test conducted in this article, it is evident that China’s macroeconomy is insignificant in influencing the world market price for oil. In the oil market prevailing in the world, the price of oil prevailing in China is exogenous based on the monthly time series. The third result is that according to the impulse-response function, it is perceived that the GDP of China and the CPI are directly proportional to the world market price for oil. It is observed that when the world market price for oil increased by about 100%, the GDP of China and the CPI increased by about 9% and 2.008% respectively.
Conclusion
To conclude this paper, it can be said that some papers have concluded that the prices of oil do influence the macroeconomic variables whereas other papers believe that it is just a statistical coincidence. However, majority of the papers have worked on output, inflation rate and the economic growth as the macroeconomic variables and have found a relation between the oil prices and these variables.
References
Du, L., Yanan, H., & Wei, C. (2010). The relationship between oil price shocks and China’s macro-economy: An empirical analysis. Energy policy, 38(8), 4142-4151. doi:10.1016/j.enpol.2010.03.042
Farhani, S. (2012). Impact of Oil Price Increases on US Economic Growth: Causality Analysis and Study of the Weakening Effects on the Relationship. International Journal of energy economics and Policy, 2(3), 108-122. https://dergipark.org.tr/en/download/article-file/361170
Hamilton, J. D. (2008). Oil and the Macroeconomy. The new Palgrave dictionary of economics, 2. https://econweb.ucsd.edu/~jhamilto/JDH_palgrave_oil.pdf
Hooker, M. A. (1996). What happened to the oil price-macroeconomy relationship?. Journal of monetary Economics, 38(2), 195-213. https://doi.org/10.1016/S0304-3932(96)01281-0
Milani, F. (2009). Expectations, learning, and the changing relationship between oil prices and the macroeconomy. Energy Economics, 31(6), 827-837. https://doi.org/10.1016/j.eneco.2009.05.012
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