Growth Rate Of Gross Domestic Product Research Articles

Assessing Exchange Rate Volatility and Economic Growth in Nigeria: A Garch Model Approach

This study has examined the impact of exchange rate volatility on economic growth in Nigeria from the year 1981 to the year 2020. The study adopted secondary data (i.e. time series) obtained from World Bank National Account data and Central Bank of Nigeria Annual Statistical Bulletins, subjecting them to statistical analysis for relevant inferences to be made. Five variables were used in the study which were Growth rate of Gross Domestic Product (GRGDP), Exchange Rate Volatility (EXRV), Balance of Trade (BOT), Oil Price (OILP) and Inflation (INF) Rate. The variables were subjected to unit root test and they were stationary at different order of I(0) and I(1). Since the Variables were not all stationary at level but a mixed series, the ARDL bound test of cointegration was used to test for cointegration among them. Using the bound test, the variables were found to be cointegrated at 1% level of significance. The ARDL result indicated that; Exchange rate volatility has a significant impact on economic growth, with the impact being negative. In addition, other economic variables such as inflation has a negative and significant impact on economic growth while oil price have a positive and significant impact on economic growth. On the other hand, BOT has a positive effect on growth but the impact was significant at the 10 percent level. From the findings the study recommended that foreign exchange market should be well monitored with a view to ensuring that only ventures that would engender value added production in the real sector and export-oriented businesses should have more access. This will help to increase the value of the naira against major world currencies.

An Assessment of the Impact of Monetary Policy on Economic Growth in Nigeria: Toda-Yamamoto Approach

This study interrogated the impact of monetary policy on economic growth in Nigeria using annual time series data from 1981 to 2020. The paper used the growth rate of gross domestic product (GRGDP) as the endogenous variable, while, broad money supply (MS2), monetary policy rate (MPR), Inflation (INFL), liquidity ratio (LDQR) and exchange rate (EXCH) were the exogenous variables and proxies for monetary policy. Data were obtained from the Central Bank of Nigeria’s Statistical Bulletin of various years and World Bank National Account Data. The study used descriptive statistics, performed a unit root test using Augmented Dickey-Fuller, Autoregressive Distributed Lag (ARDL) Bound test, and to test for causality, Toda Yamamoto was deployed. Finally, the Toda Yamamoto Causality test revealed that all the exogenous variables had bi-directional causality with economic growth except for the exchange rate that had uni-directional causality with economic growth. In the light of the findings, the study recommends that Broad Money Supply (MS2) should be adequately managed and manipulated to achieve the needy growth, in line with pursued monetary policy stance of the monetary authority. Also, the monetary authority and the government should vigorously pursue policies that would increase financial inclusion in Nigeria as it would enhance the effectiveness of the monetary policy.

Impact of Economic Recovery on Market Capitalization in Nigeria

Abstract: The study examined the impact of economic recovery on market capitalization in Nigeria. The specific objectives of the study include: to examine the effect of Gross Domestic Product (GDP) growth rate on market capitalization, to determine the influence of Inflation rate on market capitalization and to assess the impact of Exchange rate on market capitalization. To achieve the objective of the study, ex-post facto research design was adopted. The researcher used secondary data in collating the required data. The data were collected from CBN statistical bulletin. In testing the hypotheses, multiple regression analysis was used. The findings revealed that GDP growth rate has positive impact on market capitalization while inflation rate and exchange rate have negative impact on market capitalization. The study recommends that Nigeria government should devise a means of increasing gross domestic product growth rate through effective utilization of their revenue allocation and expending. The study also recommends that during economic recovery, Nigeria government should ensure that their inflation rate is reduced. Inflation being the major economic factor that can be hampered by economic recession can reduce market capitalization in Nigeria.

Cointegration and causality analysis between foreign direct investment, exports and economic growth in the republic of Croatia

The main objective of this paper is to analyze the causal relationship between foreign direct investment (FDI), exports, and economic growth in the Republic of Croatia for the period 2000-2020 and determine the implications of research results on corporate management. The management of the investment enterprise is usually interested in high returns, whereas the management of the recipient enterprise is interested in higher productivity, spillovers, and larger market share on domestic and international markets. Several methodological approaches, including unit root tests, cointegration tests, and Granger causality test, were used to assess the relationship between gross domestic product (GDP) growth rate, on the one side, and the share of FDI and total exports of goods and services in real GDP, on the other side. The results of cointegration tests indicated there is no long-term relationship between the real GDP growth rate, the share of FDI, and the share of exports of goods and services in real GDP. Based on the Granger causality test, it cannot be concluded that there is no causal relationship between the analysed variables. Finally, the paper discusses the implications of the conducted research for corporate management. The results indicate that managers are not discouraged by the fact that FDI is not correlated to economic growth, as investment decisions are determined by numerous factors and not primarily by the growth rate of a recipient country.

Infrastructures Development, Environmental Quality and Economic Growth in Nigeria

The Earth as a planet supports human life, living and activities, attracting extensive and intensive socioeconomic influences on the economy. Such activities like infrastructures development exerts increasing and divers environmental quality concerns and hence the economic growth. While these variables appear interrelated due to many factors including population growth, urbanisation, etc. However, the relationship between infrastructures, environment and economic growth is not largely known especially in Nigeria. This study therefore investigated their relationship using time series data between 1990 and 2019 by adopting Co-integration estimation technique through the Bound test approach of auto regressive distributive lag method using percentage share of building and construction sector of gross domestic product (GDP), carbon dioxide, population growth GDP growth rate, etc. as variables. The study revealed that the infrastructures development and environmental quality explain economic growth and have both short and long run relationships while specifically population growth and agriculture, forestry, fishing, value added variables are positively significant to economic growth. The findings evidences of both short and long run relationships among the variables are significant and it is consequently recommended that new roles for infrastructure sets and production processes should consider environmental quality mindsets to achieve positive green economy outcomes in Nigeria. JEL Classifications: O18, O44, Q5

Study of China's Optimal Concentrated Solar Power Development Path to 2050

As an important form of clean energy generation that provides continuous and stable power generation and is grid-friendly, concentrated solar power (CSP) has been developing rapidly in recent years. It is expected that CSP, together with wind and solar photovoltaic, will constitute a stable, high percentage of renewable energy generation system that will be price-competitive with conventional energy sources. In this study, a dynamic programming approach based on minimum cost was used to explore the optimal development path of CSP generation in China by 2050. A learning curve model and a technology diffusion model were used as constraints. The impact of factors such as Gross Domestic Product (GDP) growth, incentive policies, technological advances, grid absorptive capacity, and emission regulation schemes on the development of CSP generation was discussed in the context of sensitivity analysis and scenario comparison. This study has reached the following conclusions: 1) the government cannot achieve the target for cumulative installed capacity in 2050. Considering the interaction of relevant factors, the target would be hard to achieve even under favorable conditions; 2) as a key factor affecting the development of CSP, the incentive policy is closely related to construction cost. It is noteworthy that although the target can be achieved with a higher investment ratio, the CSP industry has failed to create a good ecological environment in the early stage of development; 3) GDP growth and learning rate are important factors influencing the development path in later stages; and 4) although they operate as potential factors affecting construction costs, grid absorptive capacity and carbon permit prices have limited impact on the development of CSP generation.

IS THE REPORTS-BASED MEASURE OF UNCERTAINTY STATIONARY? EVIDENCE FROM A NEW PANEL RESIDUAL AUGMENTED LEAST SQUARES UNIT ROOT TEST

To avoid spurious inferences, researchers analyzing the dimensions of uncertainty need to determine whether it is nonstationary. The degree of persistence of uncertainty also indicates the duration of the negative impact of an uncertainty shock on the economy. We use a new panel residual augmented least squares unit root test that allows for heterogeneous structural breaks in both intercepts and slopes of a series to determine the degree of persistence of the reports-based measure of uncertainty and whether it is nonstationary for 143 countries. This group of countries accounts for 99% of the world’s gross domestic product (GDP). To assess the robustness of our results, we also use recently developed univariate time-series unit root tests that allow for structural breaks and panel unit root tests that accommodate cross-sectional dependence and nonlinearity. Furthermore, an autoregressive wild bootstrap approach is utilized to examine the stationarity of the series. The results are virtually unambiguous in indicating that the reports-based measure of uncertainty is stationary in all countries considered. The results also suggest that uncertainty has a negative impact on the growth rate of GDP. The policy implications of the results are also discussed.

A cross-country analysis of the relationship between human capital and foreign direct investment

PurposeThe Zhang–Markusen (Z-M) inverse U-shape theory uses education as a human capital variable to investigate the impact of educational attainment on foreign direct investment (FDI) inflows to a country. The objective of this research is to empirically test this theory in a cross-country framework.Design/methodology/approachFixed effect panel regression has been used to test the Z-M hypothesis for 172 countries for the period 1990–2015. For the purpose of this study, countries were divided into four groups as per the World Bank classification: Low-income economies, lower middle-income countries, upper middle-income economies and high-income economies.FindingsThe findings of this study reinforce the proposition that macroeconomic factors are the major determinants of FDI inflows into various countries. The authors find that the size of the market measured by gross domestic product (GDP), the growth potential of the market measured by real GDP growth rate and the availability of infrastructure are the major factors that enhance the attractiveness of a country as an FDI destination.Originality/valueThough the Z-M theory has been empirically tested in cross-country frameworks, no consensus has been reached. Thus, it is interesting to look again at the validity of the Z-M hypothesis using data covering longer and more recent periods. The study includes both macroeconomic and human capital determinants of FDI, so as to arrive at a comprehensive model explaining the FDI flows into various countries.

Factors of Production Influencing Gross Domestic Product in Nepal

This study has analysed the factors of production, viz; agricultural land, working force and gross fixed capital formation (GFCF) of Nepal between 2000/01-2017/18 AD and has determined their effects on national income, viz; Gross Domestic Product (GDP) by using Cobb-Douglas regression function. The results showed an average growth rate of GDP, agricultural land, working force and GFCF to be 3.9%, 0.8%, 1.5% and 7.9%, respectively, with the values plummeting in 2015/16, due to occurrence of the devastating earthquake in 2015, but then again variable values skyrocketed following years. The regression analysis found that GDP was affected significantly by agricultural land and working force, but insignificant with GFCF. On an average, with the increase in agricultural land and working force by 1 %, GDP increased by 1.1% and 1.7%, respectively. Thus, policy regarding an increment of agricultural land use and employment of labour force must be framed to improve the Nepalese economy.

Modelling Macroeconomic and Bank-Specific Determinants of Credit Risk in the Nigerian Banking Sector: Evidence from Bounds Test Approach to Co-Integration

Credit risk, represented in this study by the ratio of non-performing loans to total loan (NPL), is considered as one of the critical factors that causes bank distress and failure. This study examines the macroeconomic and bankspecific determinants of credit risk in the Nigerian Banking sector from the period 1998Q1 to 2018Q4 using the bounds test approach to co-integration. Literature survey in this subject area using Google Scholar resources reveals that there seems to be a consensus of findings in terms of the negative relationship between credit risk and Gross Domestic Product (GDP) growth rate, while other macroeconomic and bank-specific factors tend to have a random pattern relationship with credit risk attributable to various countries’ economic peculiarities. This study shows that GDP growth rate, return on asset, return on equity, interest rate, unemployment rate, and real exchange rate have a negative relationship with NPL. On the other hand, inflation rate, loan deposit ratio, and ratio of bank capital to asset have positive relationship with NPL. The relationships between the three variables and NPL were found to be individually insignificant to explain credit risk trends in the long run. Moreover, the Wald short-run causality test reveals that the macroeconomic and bank specific indicators jointly influence credit risk in the Nigeria banking sector in the short run. This study, however, recommends that since the macroeconomic and bank specific factors were found to be individually insignificant to explain credit risk trend in the long run, consideration should be accorded to some psychological, political, and socioeconomic factors such as the borrower’s attitude, business climate, social dislocations and distortions, availability of good infrastructural facilities, and the direction of government policies. These factors can affect borrowers’ ability to honor their debt obligations and, thus, determine the level of credit risk in the Nigerian economy.

THE IMPACT OF OIL PRICE SHOCKS ON ECONOMIC GROWTH: THE CASE OF TAIWAN

Most studies continue to analyze oil shocks. Earlier authors recognize that oil price volatility plays a critical role in the economy. There is accordingly evidence that oil price shocks negatively impact real gross domestic product (GDP) growth rates and cause higher inflation. However, this paper uses different perspectives to investigate whether it is beneficial to Taiwan's overall economy based on a low oil price event. This study's results reveal that an increase in the oil price leads to an increase in the consumer price index (CPI), causing higher inflation. Moreover, a long-term rise in oil prices would negatively impact the GDP growth rate. Alternatively, in the event of falling oil prices, there may not be an immediate decline in the price of goods. However, firms' reductions in the cost of goods resulted in declining CPI, due to the decreasing oil price over the past few months. Furthermore, it was observed that GDP would decrease when there is a long-term decline in the oil price. All the previously mentioned results are almost consistent with those of previous studies of high oil price events. In addition, the economy would be negatively impacted by a long-term decline in oil prices.Keywords: Oil price shocks, Oil fluctuation, Economic activity, Impulse response functionJEL Classifications: F62, M21, O11, Q43DOI: https://doi.org/10.32479/ijefi.11822

Goodness-of-Fit of Logistic Regression of the Default Rate on GDP Growth Rate and on CDX Indices

Under the Basel II and Basel III agreements, the probability of default (PD) is a key parameter used in calculating expected credit loss (ECL), which is typically defined as: PD × Loss Given Default × Exposure at Default. In practice or in regulatory requirements, gross domestic product (GDP) has been adopted in the PD estimation model. Due to the problem of excessive fluctuation and highly volatile ECL estimation, models that produce satisfactory PD and thus ECL estimations in the context of existing risk management techniques are lacking. In this study, we explore the usage of the credit default swap index (CDX), a market’s expectation of future PD, as a predictor of the default rate (DR). By comparing the goodness-of-fit of logistic regression, several conclusions are drawn. Firstly, in general, GDP has considerable explanatory power for the default rate which is consistent with current models in practice. Secondly, although both GDP and CDX fit the DR well for rating B class, CDX has a significantly better fit of DR for ratings [A, Baa, Ba]. Thirdly, compared with low-rated companies, the relationship between the DR and GDP is relatively weak for rating A. This phenomenon implies that, in addition to using macroeconomic variables and firm-specific explanatory variables in the PD estimation model, high-rated companies exhibit a greater need to use market supplemental information, such as CDX, to capture the changes in the DR.

Preliminary Assessment of Chinese Strategy in Controlling Reemergent Local Outbreak of COVID-19.

Reemergent local outbreaks of coronavirus disease 2019 (COVID-19) have occurred in China, yet few Chinese response strategies and its evaluation have been reported. This study presents a preliminary assessment of Chinese strategy in controlling reemergent local outbreaks of COVID-19. Time course of accumulative and daily new cases and time-varying reproductive numbers (Rt) of outbreak areas were presented. The asymptomatic rate, days required to control the outbreaks, seeding time (ST), and doubling time (DT) of areas with over 96 reemergent cases were calculated. National and local year-on-year growth rates of gross domestic product (GDP) were presented. Accumulative numbers of 30, 8, 11, 430, 15, 139, 1,067, 382, 42, and 94 confirmed reemergent COVID-19 cases were diagnosed in Hulun Buir, Shanghai, Tianjin, Kashgar, Qingdao, Dalian, Urumchi, Beijing, Jilin, and Harbin, respectively. Among them, maximum rate of asymptomatic infections was 81.9%. Time required to control the local outbreaks in the areas given above varied from 29 to 51 days. After activation of outbreak responses, the late-stage DTs of Kashgar, Urumchi, Beijing, and Dalian were apparently lengthened compared to the early-stage DTs. Although the year-on-year GDP growth rate of Urumchi was slightly affected, the GDP growth rate of Dalian, Beijing, Jilin, and Harbin kept rising during the reemergence. Moreover, the year-on-year GDP growth rate of Mainland China turned positive regardless of the reemergent local outbreaks. In general, the Chinese strategy to maintain the status of no or minimal transmission was effective in balancing the control of COVID-19 reemergent local outbreak and the recovery of economy.

Is the demographic dividend diminishing in China? Evidence from population aging and economic growth during 1990–2015

AbstractThis paper presents new empirical evidence on the effect of population aging on economic growth in China. Aging is widely assumed to impact economic growth by shaping the labor market performance and human capital. Using an interactive fixed effects model and a provincial panel data set during 1990–2015, and also exploiting the predicted province‐by‐year variation in population aging fraction as an instrument, we examine the impact of population aging on the growth rate of gross domestic product (GDP) per capita, labor force ratio, and labor productivity. The results show that a 10% increase in the fraction of the population aged 65+ decreases the growth rate of GDP per capita by approximately 2%. Furthermore, channel decomposition shows that half of the decrease is due to slower growth of the labor force ratio, whereas the rest may be due to slower productivity growth. In addition, the negative effect of aging on GDP growth is more substantial after the year 2000, and the effect of aging on the labor force ratio and productivity shows different patterns during different periods.

Applying the Fama and French three-factor model to analyze risk/reward in the Spanish REITs: an ARDL approach

PurposeThis paper aims to analyse the risk and excess returns of the Spanish real estate investment trusts (S-REITs) using various methods, though focusing primarily on the Fama-French three-factor (FF3) model, over the period from 2007Q3 to 2017Q2.Design/methodology/approachThe autoregressive distributed lag model is used for the empirical analysis to test long-term stable relationships between variables.FindingsThe findings indicate that the FF3 model is suitable for the S-REITs market, better explaining the S-REITs’ returns variation than the traditional single-index capital asset pricing model (CAPM) and the Carhart four-factor model. The empirical evidence is reasonably consistent with the FF3 model; the values for the market, size and value are highly statistically significant over the analysis period, with 68.7% variation in S-REITs’ returns explained by the model. In the long run, the market factor has less explanatory power than the size and value factors; the positive long-term multiplier of the size factor indicates that small S-REIT companies have higher returns, along with higher risk, while the negative multiplier of the value indicator suggests that S-REITs portfolios prefer to allocate growth REITs with low book-to-market ratios. The empirical findings from a modified FF3 model, which additionally incorporates Spain’s gross domestic product (GDP) growth rate, two consumer price index (CPI) macro-factors and three dummy variables, indicates that GDP growth rate and CPI also affect S-REITs’ yields, while investment funds with capital calls have a small influence on S-REITs’ returns.Practical implicationsThe regression results of the standard and extended FF3 model can help researchers understand S-REITs’ risk and return through a general stock pattern. Potential investors are given more information to consider the new Spanish investment vehicle before making a decision.Originality/valueThe paper uses standard techniques but applies them for the first time to the S-REIT market.

Changes of base-year and Indian GDP growth: an agnostic look

Purpose World over, change of base year in the gross domestic product (GDP) is a standard practice of GDP estimation. However, unless a consistent series of GDP is released with respect to the new base for the earlier period, the existence of multiple growth rates creates problems for applied researchers, policymakers and the general public alike. Faced with such a menu of GDP series researchers often try to interpolate a consistent series of GDP. The main purpose of this paper is to analyses the nature of the data generating process of such multiple interpolated series of quarterly growth rates and tries to discern the consistency of such processes. Design/methodology/approach The present paper tries to look into the statistical implications and complications of such interpolated quarterly GDP/growth series in India in terms of three series of GDP, namely, with 1999–2000, 2004–2005 and 2011–2012 as its bases. Findings The analysis reveals that as a result of a change of base year, the nature of the data generating process of the old and new GDP series could undergo changes and experience different breakpoints. While all these conclusions seem to be valid for GDP growth at quarterly intervals, taking the data at annual frequency is less problematic. Practical implications The observation suggests that in most applied work, researchers may not have the luxury of only working with annual data and certain consistency checks will be necessary to check the veracity of the results based on quarterly data with those based on annual data. Second, moving forward it may be useful for the Authorities to make a transition to a chain-based linking method rather than fixed time-period-based bases as is currently done. Originality/value The analysis of Indian GDP in this paper is, perhaps, indicative of the fact that usage of quarterly GDP data is to be handled with caution and it is preferable that any serious empirical analysis uses annual GDP data whenever it is available/feasible. The comparison of GDP growth rates at different frequencies and examining the true nature of the process are quite unique in their contribution towards empirical macroeconomic research.

Introduction

With an impressive economic growth rate averaging around 7.0 percent during 2003–2004 to 2019–2020, India is currently the fifth largest economy in the World. The growth has enabled India to make remarkable progress in absolute poverty reduction and make significant strides in its progress towards achieving Sustainable Development Goals. However, several crucial sectors of importance from the Human Development perspective, namely, health and education, continue to receive lower than desired level of attention. Over the period 2014–2015 to 2019–2020, the expenditure on education sector marginally improved from 2.8 to 3.1 percent of the gross domestic product (GDP), but remained well below the desired level of about 6 percent of GDP. The health sector over the same period improved its share from 1.2 to 1.6 percent of GDP, but the allocation in this sector too stayed below the recommendations of the 15th Finance Commission. The manifestation such under-allocation is reflected through worrying trends across various human development dimensions including close to 35 percent of the children in India suffering from malnutrition. It is also reflected in continuing under performance of India in the global human development index rankings. Equally concerning is India’s below par achievement in terms of gender equality. As per the World Economic Forum’s latest Global Gender Gap Report 2021, India slipped as many as 28 positions and ranked 140 among 153 countries. Among South Asian countries, only Pakistan and Afghanistan had lower achievements than India in bridging the gender gap. The gender gap is contributed among other dimensions by low levels of female labor force participation rates and significant gap between men and women in terms of the income earned. Further, the growing population, growing urbanization and higher consumption needs pose serious concerns regarding the sustainability of the impressive economic growth. The Covid-19 pandemic aggravated the already decelerating economic growth and pushed the GDP growth rate to negative digits. This has also put constraints on fiscal space to shape-up fast and effective recovery. The economic recovery is expected to take time and the impact of pandemic will be felt more acutely on the informal sector. All this will further hamper India’s developmental aspirations.

Understanding the New Normal: The Role of Demographics

We calibrate an overlapping-generations model with a rich demographic structure to observed and projected changes in U.S. population, family composition, life expectancy, and labor market activity. The model indicates that demographic factors associated with the post-war baby boom pushed up real interest rates and real gross domestic product (GDP) growth from 1960 to the 1980s. Since the 1980s, the model accounts for a little more than a 1-percentage-point decline in both real GDP growth and real interest rates—much of the permanent declines in those variables according to some estimates. Our model predicts GDP growth and interest rates will remain low by historical standards, consistent with a “new normal” for the U.S. economy.

Covid-19 and Its Impact on E-Administration, Employment and Migration in the Indian Economy, (In the Present Context)

India is the second largest populated country in the world and largest market Economy for most of the developed countries in the world like MNC’s (Multi-National Companies) like automobiles, telephone and communication, educational services, start-up’s, call centres and global level entrepreneurs like to invest in India, due to huge demand for consumer goods and technological products India is one of the largest growing developing economy in the world after China in 2019, with an average GDP (Gross Domestic Product) of 7 percent from2015-2019, with huge FDI (Foreign Direct Investment), India is said to be the country with huge foreign returns in the world. But due to covid-19 has made most of the states in India are in standstill position due to lockdown situation, the income generating sources of the government is unable to generate income as most of the unorganised sectors like migrant workers, small wage labourers contribution to Indian economic growth and business is in standstill stage in the 40 days of Indian government lockdown, this is causing to increase in unemployment ratio in many sectors like educational services, real estate companies etc. only in some organised sectors there is processing of work through online (e-commerce) or in digital mode of transaction, but the unorganised sector workers and daily wage workers or migrants who travelled from far states are unable to earn for their lively wages. Indian government preference to health emergency and relief package of 20 Lakh crore Atmanirbhar Bharat Abhiyan is burden for Indian economic growth as the government is distributing from March 2020. This pandemic has made India`s GDP (Gross Domestic Product) growth rate prediction below 4%, according to the report of ADB (Asian Development Bank). IMF (International Monetary Fund) has predicted that Indian economy is expected to grow at -10.3 %, according to the source provided by “The Hindu”. There is a need for all the sectors in the economy for digital inclusion, India can try to improve by making all payments and receipts in unorganised sectors through Digital Mode. India can use this global pandemic situation by making India as one of the favourite investment destination for FDI, business and e-commerce in the globe. The purpose of this study is to analyse Covid-19 impact on Indian economy through migration, e-commerce, business and remedies to overcome the pandemic to the growth of National Income (GDP), by implementing various schemes like Make in India and self-reliant India by fiscal and monetary policies.

The macroeconomic effects of increase and decrease in oil prices: evidences of asymmetric effects from India

PurposeThe purpose of this paper is to assess whether oil price shocks emanating from oil price increase and decrease have a different impact on the macroeconomic activity.Design/methodology/approachThis study conducts the empirical analysis using structural vector auto-regressive model on Indian data for the period from 1996 to 2017. This paper uses four key macroeconomic variables, namely, real gross domestic product (GDP), the real rate of interest, real money supply, wholesale price index inflation and various linear and non-linear measures of oil price shock.FindingsEmpirical results confirm that oil price shock has a significant impact on various macroeconomic variables used in the study. Specifically, shocks emanating from a decline in oil price have a stronger positive impact on real GDP, whereas, a shock due to the rise in oil price has a weaker negative impact on real GDP. Impulse responses confirm that shocks due to a decline in oil prices are long-lasting compared to similar shocks due to a rise in oil prices. Therefore, this study concludes that the macroeconomic impact of oil price shock is asymmetric in India.Originality/valueThis paper adds the following new insights: First, this paper presents a distinct relationship between the growth rate of oil price and GDP during increasing and decreasing phases of oil price to drive home the case for this study. Second, India has adopted crucial administrative initiatives such as deregulation of the market for petroleum products and the promotion of renewable energy during the study period. Finally, previous studies have revealed specific behavioral and economic features of people in India with respect to the demand for petroleum products. In light of these factors, this paper based on Indian experience would be justified.