ANALYSIS AND FINDINGS
3. Analysis and Findings
3.1. Introduction
3.2. Analytical Tool – Regression
Multiple regressions are performed to assess the relationship of single independent variable i.e. crude oil prices (on Brent benchmarking) with all four dependent variables including Indian GDP growth, Indian Balance of Payments, Exchange rate between INR and USD, and the inflation rate in India.
3.3. Measures for Independent Variable – Crude Oil Price
Crude oil is the most commonly traded commodity in the international market. Crude oil price stands independent variable in the underlying study, and same is considered for this purpose of analysis. The Periodic time frame for change in oil price is determined on an annual basis. The model covers a time horizon of 29 years, which implies that 29 periodic changes are taken to evaluate their impact on each of the dependent variables (i.e. selected indicators of Indian Economy). Brent is one of several pricing classifications of light sweet oil that is specifically considered for the research focused on Indian economy. The price is determined in USD that is used for purchasing it from international market by India as well as many other nations.
3.4. Impact of Change in Oil Price on Indian GDP
Gross Domestic Production or GDP, in short, is normally used to assess and evaluate overall output and outlook of the economy. The GDP of Indian economy is the total amount of goods and services produced in India within a year. Total production of goods and services in India on an annual basis is the measure that is used as the dependent variable i.e. Indian GDP. Generally, it is considered in direct relationship with the economy.
As an important phase of assessing the impact of the change in oil price on the Indian economy, a regression was performed between the changes in oil price and Indian GDP on a timeframe ranging between 1987 and 2015. The findings are displayed as follows:
Figure 1 - Oil Price vs. Indian GDP
Δ GDP = 5.905505035 + 0.013649299 Δ Oil prices
Looking at intercept, it shows that if the change in oil prices were zero, the GDP growth would be positive and about 6%. The coefficient of the explanatory variable is positive indicating that for a unit increase in oil prices there will be a rise in the GDP growth but only negligibly by 0.0136 percentages. This is a surprising impact as normally a rise in oil prices would be expected to have a negative impact on the GDP growth. The results are totally contradictory to the idea of Mehra (2008), according to whom GDP of oil importing nation and oil prices are, usually, in a negative relationship. He argues that an oil importer has to pay less for the purchase of oil from the international market. Hence, the government can increase its spending for a public cause. Since end-users are also benefited, and oil is used heavily in manufacturing, fall in oil prices is likely to provide an encouraging atmosphere for production. Therefore, the impact of oil price on GDP is mostly inverse, which is also supported by the short term trends of this relationship retrieved from Statistia (2016), and Trading Economics (2016a). However, the findings of this model are not parallel to the results of the literature review.
R Square is very low at 0.045, which shows less than half a percentage of variations in the GDP are explained by the change in oil prices. The reliability (the significance) of the results is indicated by the F test. Here the F test is much than 0.05 and therefore the results is not significant, and the independent variable is not a good predictor of the dependent variable.
These problems could be attributed to the following factors:
The relationship between GDP growth and oil prices changes is not linear
The impact on the GDP from a change in oil prices is felt with a lag of one year or more. Therefore, the model may be should have been presented as a first differencing model
The variables have not been measured correctly
Since the value of significance F is greater than 0.05, the regression model is not significant on the confidence interval of 95%. One reason behind this insignificance can be that trends are developed in longitudinal time horizons, while timeframe selected for the research in hand is ranging between past 28 years. Then, there may be some other predictors in a stronger relationship with Indian GDP than crude oil.
3.5. Impact of Changes in Oil Prices on Inflation Rate in India
Inflation refers to increase in consumer price within any given timeframe. The inflation rate in India as a dependent variable stands for the positive change in the cost of goods and living in India. There is a general price level, which is called consumer price and is measured in percentage. Here, it is also notable that deflation refers to the reverse mode of inflation that denotes an annual decrease in annual price. It is also measured on a timeframe of 29 years i.e. 1987-2015 with a periodic change on an annual basis.
Figure 2 - Oil Price vs. Inflation Rate in India
Equation provided below further illustrates key results:
Δ Inflation = 7.71562108 + -0.018688495 Δ Oil Price
Referring to intercept, it is found that inflation would stand slightly above 7% even if there is no change in oil price. Furthermore, it is shown in the figure provided above that there will be a negative change in inflation for each unit of increase in oil price (coefficient value of explanatory variable = -0.018688495) that denotes a negative relationship between inflation and its predictor (oil price).
These findings are in line with the short term trends in relation derived from Trading Economics (2016b). They are also supported by the theoretical ideas found on World Bank (2015), where the author argues that oil price usually negatively affects the inflation rate in an oil importing nation. He further argues that declining oil prices are usually at the bottom of a cyclic economic curse. Due to declining oil prices, products and goods are available at cheaper rates due to less expenditure on manufacturing and shipment. This scenario may lead to deflation causing the interest rates to come down and foreign investors to stay away. It may lead to further decline of inflation rate resulting in long term deflation in the affected region.
R square value is critically low at 0.051, which shows that explanatory variable oil price is explaining slightly above half a percentage variations of inflation rates in India (dependent variable). F-Test is provided to determine the reliability of the underlying research model. Here, again significance F is much larger than 0.05, which implies that the research model does not qualify to be reliable and oil price is not a good predictor of inflation rate in India. The factors mentioned below can be at the bottom of this insignificance of relationship:
Linear relationship does not exist between oil price and the inflation rate in India.
The research model is based on the impact of oil price change to be felt on inflation rate with a time interval of one year, so it does not cover the variations in between the given period of time.
There are errors in measuring the dependent variable correctly.
The assumption relating to auto-correction of errors is not met because the date is provided in time-series format.
3.6. Impact of Change in Oil Price on Balance of Payment in India
Balance of Payments (BOP) refers to the record of transactions made between the residents that include businesses, individuals, and government of a country with the individuals, businesses, and government i.e. residents of all other countries. A positive change in the balance of payment indicates that inflow of foreign exchange has been greater than its outflow, which is a positive sign for the economy. On the other hand, a negative change is indicative of outflow exceeding the inflow that is in a negative relationship with economic growth of a country. Balance of payment in India is measured in the percentage that refers to the percentage change in this variable responding to change in oil price within a time period of one year for a time horizon of 29 years.
The results that are obtained after regressing Indian BOP against oil price are provided as under:
Figure 3 - Oil Price vs. Indian BOP
Equation provided below explains the relationship between explanatory and dependent variable:
Δ Balance of Payments = 10.99763 + -0.56022 Δ Oil Price
As shown, the value of intercept shows that 11% change in the value of BOP would occur even if the price of oil remains unchanged. Furthermore, the negative coefficient value of oil price shows that there will be a negative change of -0.56022 in the value of Indian Balance of Payment for each unit change in oil price. This shows that oil price and balance of payment are in an inverse relationship with each other.
These findings are in strong agreement with the general perception advocated by PTI (2016), and Verma (2016), in literature review according to which declining oil prices serve as good news for an oil importing nation with reference to its current account balance. They simply argue that government saves revenue by spending comparatively less on the import of oil. Hence, positive change in the balance of trade has a positive impact on the balance of payment (as BOT is one of the key components of BOP).
However, World Bank (2015), does not agree with these results where it is discussed in a post that declines in oil prices should not always be considered a positive sign for the economy of an oil importing country. As the price comes down, it is likely to bring about deflation and low interest rates. Low interest rates are threatening to foreign investment, which implies that inflow of foreign exchange is negatively affected by declining oil prices. In other words, a direct relationship may exist between oil price and balance of payment contrary to these findings.
However, high R square value (0.6616861) shows that 66% variations of the underlying dependent variable are explained by explanatory variable. Furthermore, the value of F-test is less than 0.05 (significance F < 0.05), which suggests that the research model is reliable at a confidence interval of 95%, and oil price is a good predictor of the balance of payment.
There are difference and contradictions among findings collected from different sources. However, it is found that the end-results are more in favor of the idea that oil price is in a negative relationship with Indian BOP than it agrees to otherwise scenario (positive relationship between the underlying variables). On the basis of that coupled with confirmation through general perception, it is wiser to generalize the findings of given statistical analysis for oil importing nations. In other words, fluctuations in oil prices inversely affect current account balance of the oil importers. Hence, the rise in oil price in the international market will cause a negative change in the balance of payment of this category of countries and vice versa.
3.7. Impact of Change in Oil Price on Indian Currency
Change in currency exchange rate is also considered one of the key predictors of a country’s economy. The value of each unit of Indian currency is taken in comparison with USD to evaluate the appreciation or depreciation of Indian currency exchange rate. For example, if USD is strengthening against INR, it is indicative of depreciation of Indian Rupee. By the same token, decreasing value of USD against INR shows that Indian currency is being appreciated. Change in currency is felt at each periodic gap of one year from 1987 to 1915.
A linear regression was performed between the independent variable oil price and dependent variable Indian currency value to assess and evaluate the relationship both between using a statistical model. The findings of regression are shown below:
Figure 4 - Oil Price vs. Indian Currency Value
For statistical explanation, key findings are given below in equation format:
Δ INR/USD = 27.73054 + 0.258414 Δ Oil Price
Intercept value i.e. 27.73045 shows that the dependent variable currency value would change by about 28% even if the price of crude oil remains zero. This change would be predicted by some other independent variables. On the other hand, it is found that each unit of change in oil price causes change at 0.2584 in the value of Indian currency, and both the variables are in a positive relationship (as the coefficient of the explanatory variable is positive).
A short term trend derived from XE (2016), also conform to these findings, as Indian currency has undergone depreciation over past few years that are also characterized by sharply declining oil prices. Therefore, there is a strong agreement between short term and long term trends in this regard. The direct relationship between fluctuation in oil prices and the currency value of oil importing nation like India is also backed by the theoretical insight into the underlying relationship as found in existing literature. For example, it is found and discussed several times that oil prices are in an inverse relationship with the inflation rate. In other words, prolonged downtrend of oil prices is likely to cause deflation that is discouraging to foreign investment due to declining interest rates. Here, it is important to note that foreign investment directly affects currency exchange rate, as it determines the patterns of demand and supply between two currencies (World Bank, 2015). Current depreciation of Indian currency can also be attributed to this factor.
When talking about R Square value, its value (0.401873) shows that change in oil price as an independent variable explains 40% variations of Indian Currency. Furthermore, F-Test is performed in order to assess the reliability of the underlying research model. It is shown that the value of significance F is smaller than 0.05 that makes the research model reliable at the confidence interval of 95%. In addition to that, the P value is also less than 0.05 due to which the relationship between underlying dependent and the independent variable is also significant.
A strong agreement between theoretical take on the case of the study and statistical findings also makes results and findings reliable. On the basis of this triangular analysis, it is safe to conclusively state that direct relationship exists between the price of crude of oil in the international market and the currency of oil importing nations. Any increase in oil price will also push the value of their currency upward while declining oil prices will cause depreciation of currency value. The researcher is in a position to rationally generalize these findings due to a high level of reliability of research model and significance of the relationship between dependent and independent variable.
List of References
Mehra, Y. P. (2008). Oil Prices and Consumer Spending: A Reprint from the "Economic Quarterly". Diane Publishing Co.
PTI. (2016). Budget 2016: Subsidy bill cut by over 4% to Rs 2.31 lakh cr for 2016-17. The Economic Times. Available from http://economictimes.indiatimes.com/news/economy/policy/budget-2016-subsidy-bill-cut-by-over-4-to-rs-2-31-lakh-cr-for-2016-17/articleshow/51192299.cms [Accessed 26th July 2016]
Statistia. (2016). India: Real gross domestic product (GDP) growth rate from 2010 to 2020 (compared to the previous year). Available from http://www.statista.com/statistics/263617/gross-domestic-product-gdp-growth-rate-in-india/ [Accessed 26th July 2016]
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Trading Economics. (2016b). India Inflation Rate. Available from http://www.tradingeconomics.com/india/inflation-cpi [Accessed 28th May 2016]
Verma, S. (2016). Budget 2016: Fiscal Deficit — Range, instead of number. Indian Express. Available from http://indianexpress.com/article/india/india-news-india/budget-2016-fiscal-deficit-range-instead-of-number/ [Accessed 28th May 2016]
World Bank Group. (2015). Global economic prospects: June 2015.
XE. (2016). XE Currency Charts (USD/INR). Available from http://www.xe.com/currencycharts/?from=USD&to=INR&view=5Y [Accessed 28th May 2016]
