Macroeconomic effects of crude oil shocks: Evidence from South Asian countries (2024)

Data source and variables

The study aims to investigate the association between crude oil prices and macroeconomic indicators that is GDP, inflation rate, interest rate, and exchange rate. To analyze this relation, last 21 years (2000–2020) of the selected variables are extracted from the World Bank.

The econometrics framework

This study utilizes E-views 12 to incorporate vector autoregressive (VAR) model, to analyze the crude oil price shocks on the GDP, inflation rate, interest rate, and exchange rate in South Asian countries (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka). The study variables are given in Table 1. Vector autoregression (VAR), as an increasingly popular statistical model, was used to forecast the relationship between multiple quantities as they change over time as well as for economic analysis. Different tools have been proposed by experts such as impulse response analysis, forecast error decompositions, historical decomposition, and the analysis of forecast scenarios for separating the relationship between the variables in the VAR model.

The standard VAR is a reduced form of model which is linked to an economic model, where economic interpretation of the result is often impossible. If the economic theory is used to provide a relationship between forecast errors and fundamental shocks, the resulting model will be SVAR. We assume that the economy is described by a structural form equation:

Where Y_t = (Y_1t,Y_{2t, …………}Y_nt) is n × 2 vector of endogenous variables, while Y_t−1, is the corresponding lag terms of order i, ∅_i is the n × n matrix of autoregressive coefficients of vector Y_t−1, for i = 1, 2, …... p.c = (c₁,c_{2, …………}c_n) is the n × 1 intercept vector of the VAR model. ε_t = (ε_1t, ε_2t, ………ε_nt) is the n × 1 vector of White Noise Process.

The variables considered in this study are crude oil prices, GDP, inflation rate, interest rate, and exchange rate.

Unit root test

The present study applied the Augmented Dickey–Fuller (ADF) Test to deduct the unit root in the data. Table 2 shows the ADF results, specifying that all the variables are stationary at 1st difference.

H₀. The series of variables has a unit root.

Granger causality test

To examine the causal relationship of the variables, the present study performed the Pairwise Dumitrescu Hurlin Panel Causality Test. The focus was on the causal relationship between the crude oil price and GDP, inflation rate, interest rate, and exchange rate of the South Asian countries that have experienced a series of reforms in crude oil pricing mechanism resulting in the significant changes. Thus, the correlation between the world oil prices and South Asian countries' domestic prices may have also changed considerably before and after the reforms. The result of the Table 3 shows that as an oil-importing country's dependence on outside oil has increased dramatically during the last decades, such as a 50% increase in 2007, and at the same time, the reforms of the oil-pricing mechanism have made the domestic oil price be more and correlated with the world oil price. Therefore, the crude oil price has been significantly affecting the South Asian economies which is consistent with the previous findings (Sharma et al., 2018; Zakaria et al., 2021).

Impulse-response functions

The impulse response function test was used to investigate the dynamic impact of crude oil price shocks on the VAR system. Figure 1 plots the responses of GDP, inflation rate, interest rate, and exchange rate to one unit innovation of the world crude oil price with two standard error bands. The impulse response function shows that exchange-rate negatively responds to crude oil prices in the 1st year and it takes almost 5 years to observe the oil price shocks. Similarly, GDP per capita is also severely affected by crude oil price shock and it responds in a monotonic fashion and it took 8 years to completely stabilize after oil shocks. Moreover, the interest rate, exchange rate, and inflation of the selected economies are also largely influenced by oil price movement in the initial phase, however; comparatively, it takes less time to absorb the shocks. It can be concluded from the impulse response function that all four macroeconomic variables of the South Asian counties are closely linked with oil price movements and their economies hugely rely on crude oil consumption. Hence, our findings confirm the previous research findings that crude oil prices significantly influence the macro-economic factors such as interest rate, price level, and industrial production (Ratti and Vespignani, 2016).

Variance decomposition

Variance decomposition separates the variation in an endogenous variable into the component shocks to the model and provides information about the relative importance of each random innovation in affecting the variables in the VAR model.

The findings of variance decomposition for real GDP, inflation, interest rate, and real exchange rate over ten-year horizons are presented in Table 4. Following the purpose of this study to examine oil price shocks and their impact on GDP, inflation, interest rate, and exchange rate, the discussion is limited to the forecast error variance when crude oil price changes. In the case of South Asian economies, the estimated impacts demonstrate that oil price shocks explain unlike variations in the variables under consideration. The shock of crude oil price accounts for GDP, 3.98–2.52%, inflation rate 10.98–20.24%, interest rate 0.66–0.88%, and exchange rate 3.22–16.34% variation over the period of the ten-time horizon in the case of Afghanistan. Similarly, in Bangladesh, variations in GDP, inflation rate, interest rate, and exchange rate because of crude oil price shocks are 1.02–1.96, 4.22–10.82, 2.98–1.11, 0.31–40.71%, respectively, during the period of the ten-time horizon. These results are in line with previous research that oil prices have a significant impact on the interest and exchange rate of Bangladesh (Das and Dutta, 2020). Hence, it indicates that variation in crude oil price significantly influences the macroeconomic variables over the long period.

However, oil price shock during the whole period of 10 horizons in Bhutan explains about 0.95–3.12, 0.53–0.97, 2.56–16.59, and 8.54–25.74% of forecast error variation in GDP, inflation rate, interest rate, and exchange rate, respectively. Similarly, 20.97–18.08% variance in the GDP, 30.44–36.73% in the inflation rate, 0.23–36.73% in the interest rate and 2.11–8.49% in the exchange rate in India are due to crude oil price shock over a ten-year period. While, the crude oil price shock induces around 0.52–3.67% of the variation in the GDP of Maldives and it also explains about 1.56–4.48% of fluctuation in the inflation rate, 1.89–2.94% variation in the interest rate and 0.91–21.70% variation in the exchange rate during the entire ten-year horizon. Similarly, 2.45–1.96% variation in the GDP, 1.43–10.82% variation in the inflation rate, 0.65–1.11% variation in the interest rate and 5.24–40.71% variation in the exchange rate were explained throughout the 10 years horizon in Nepal.

The crude oil price shock during the ten-year horizon in Pakistan explains about 8.63–8.67% in the GDP, 6.56–19.10% in the inflation rate, 2.46–1.34% in the interest rate, 3.43–20.07% in the exchange rate, and are largely consistent with that of Jawad (2013). At last, crude oil price shocks induce around 12.37–27.16% of the variation in GDP in Sri Lanka and it explains about 11.25–15.01% of fluctuations in the inflation rate during the ten-year time horizon. The crude oil price shock also accounts for 5.18–4.80%, 1.31–29.46% variance in the interest rate and exchange rate, respectively, throughout the entire horizon. Overall, these findings confirm the previous findings that oil price shock significantly influence the macro-economic indicators of the SAARC countries specifically real GDP, interest rate, inflation, and exchange rate (Ahmed et al., 2019).

Moreover, the impulse response and especially variance decomposition effects ratify that crude oil shocks have a significant impact on GDP, inflation rate, interest rate, and exchange rate almost in the South Asian countries. The possible reason for that may be these countries are unable and incompetent in their exports. However, any negative impact of crude oil price on GDP, inflation rate, interest rate, and exchange rate may cause effect their export demand to decrease. Moreover, these countries may also be unable to attract foreign direct investment (FDI), which leads to minimized investment and ultimately a fall in aggregate output. Therefore, this research study suggests that oil price shocks have both short- and long-term impacts on macroeconomic variables of the South Asian countries.

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